fNIRS 2018

fNIRS 2018

Abstract

The University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo, JAPAN

fNIRS2018, biennial meeting of the Society for fNIRS http://fnirs2018.org

Logo designed by Daisuke Tsuzuki (Tokyo Metropolitan University, Japan) Fumitaka Homae (Tokyo Metropolitan University, Japan)

Abstracts

Oral presentation

Friday

Oct. 5th, 2018

Oral

2018年10月5日（金）

Keynote

Measuring the brain by near-infrared light: Achievements, challenges and solutions

M. Wolfa

a

Biomedical Optics Research Laboratory, Department of Neonatology, University of Zurich, Switzerland Corresponding author e-mail address: [email protected]

Abstract: 40 years ago near-infrared spectroscopy (NIRS) to measure brain oxygenation was born. And 25 years ago two important advances were achieved: 1) the assessment of brain activity by functional NIRS (fNIRS) and 2) the measurement of absolute values of cerebral tissue O2 saturation (StO2) by NIRS oximetry. There has been a tremendous development in NIRS techniques and applications in these two areas and the aim of this presentation is to give an overview of the achievements, challenges and possible solutions. fNIRS measures localized changes in cerebral oxy- and deoxyhemoglobin concentration (O2Hb and HHb) in response to stimulation. Absolute quantification is not important as long as a difference between stimulation and rest is visible. Whereas for oximetry of the brain precise quantification of the StO2 is relevant for clinical application. StO2 by NIRS indicates the balance between O2 supply and consumption and thus provides important clinical information. Although NIRS/fNIRS have many unique advantages, e. g. they are non-invasive, simple, harmless and relatively low-cost methods, several challenges are yet to be mastered: 1) StO2 readings systematically vary between different brands of oximeters, 2) absolute values of O2Hb, HHb, tHb could be useful, but are so far rarely measured and 3) the superficial layers of the head influence the measured NIRS/fNIRS signals. In response to challenge 1, NIRS oximeters were quantitatively compared in phantoms showing that the StO2 values are linearly correlated between the different manufacturers and hence conversion tables were generated to facilitate comparison. Technological advances enable time-resolved measurements, i.e. besides the light intensity also the time of flight of the photons through the tissue is determined, which in frequency domain instruments corresponds to the phase. From this additional information, absolute values of O2Hb, HHb, tHb are calculated, thus solving challenge 2. Technological advances of detectors and emitters enable such measurements at relatively low cost and by compact instrumentation. Challenge 3 is the most difficult one. It is crucial to know, where the NIRS/fNIRS is originating from. Is it from superficial tissues, from systemic physiology or the brain. Approaches to reduce the influence of superficial layers have been developed and will be discussed. One solution here are 3D image reconstructions that produce depth information and thus enable to resolve the different components of tissue. NIRS/fNIRS developed tremendously over the last decades and its advancement is still progressing rapidly. Due to its numerous and unique advantages NIRS/fNIRS will continue to enter many clinical fields. Although these challenges have to be mastered, they can and will be solved within the near future. Thus, NIRS/fNIRS can be exploited to its full potential and future methods that are even more powerful are envisioned.

Saturday Oct. 6th, 2018

Oral

2018年10月6日（土）

Morning tutorial I Advanced topics in fNIRS data analysis: Motion Artifact Detection and Correction

Meryem A. Yücela,b a

b

Neurophotonics Center, Boston University, Boston, MA, USA MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA Corresponding author e-mail address: [email protected]

Functional near-infrared spectroscopy (fNIRS) is a relatively new brain imaging technology. fNIRS allows measurements in relatively unrestrained environments. While this allows its adaptation to populations/studies where other modalities are difficult or impossible to implement such as infants, children, speech studies, gait studies, movement disorders or neuro-intensive care, the resultant fNIRS signal often contain motion artifacts. In this lecture we will go over motion artifact detection and correction in detail. Particularly, we will go over several commonly-used motion artifact correction algorithms and will discuss advantages and disadvantages of each comparatively.

Hardware Development [invited talk]

Correlation Spectroscopies for Monitoring Cerebral Blood Flow A. G. Yodh Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, 19104-6396, USA [email protected] Abstract: The spatial and temporal intensity fluctuations of light scattered by tissue are sensitive to the motions tissue constituents such as red blood cells. This concept has proved valuable for probing blood flow tissues over a wide range of sizes using both single- and multiply-scattered light. I will start with basic ideas of fluctuation spectroscopy and show how they lead to the diffuse correlation spectroscopy monitoring technique [1], which employs the fluctuations of diffusing light to quantify cerebral blood flow non-invasively. This approach provides access to the blood flow biomarker and, when combined with various forms of fNIRS instrumentation, permits investigation of oxygen metabolism and autoregulation. In this discussion, I will delineate challenges that are intrinsic to the methodology, as well as some technical advances on the horizon that can help ameliorate these limitations. Finally, I will describe some recent cerebral monitoring applications which we have been exploring at Penn in both pre-clinical work and in measurements at the bedside in the neuro-intensive-care units at the Hospital of the University of Pennsylvania (HUP) and The Children’s Hospital of Philadephia (CHOP). Among these, for example, are flow-oxygenation-metabolismautoregulation measurements during surgeries [2], during management of stroke/TBI patients and in healthy subjects [3], and during treatment (broadly defined) [4]. This work and the research of others illustrate the potential of the correlation spectroscopies for clinical and neuroscience applications in the future. References [1] Buckley, E.M., Parthasarathy, A.B., Grant, P.E., Yodh, A.G., and Franceschini, M.A., Neurophotonics 1, 011009 (2014); Durduran, T., and Yodh, A.G., Neuroimage 85, 51-63 (2014); Mesquita, R.C., Durduran, T., Yu, G., Buckley, E.M., Kim, M.N., Zhou, C., Choe, R., Sunar, U., Yodh, A.G., Philosophical Transactions of the Royal Society A 369, 4358-4379, (2011); Durduran, T., Choe, R., Baker, W.B, and Yodh, A.G., Reports on Progress in Physics 73, 076701 (2010). [2] Busch, D.R., Rusin, C.G., Miller-Hance, W., Kibler, K., Baker, W.B., Heinle, J.S., Fraser, C.D., Yodh, A.G., Licht, D.J., and Brady, K.M., Biomedical Optics Express 7, 3461-3470 (2016); [3] Parthasarathy, A.B, Gannon, K.P., Baker, W.B., Favilla, C.G., Balu, R., Kasner, S.E., Yodh, A.G, Detre, J.A., and Mullen, M.T., Journal of Cerebral Blood Flow & Metabolism 38, 230-240 (2018); Baker, W.B., Parthasarathy, A.B., Gannon, K.P., Kavuri, V.C., Busch, D.R., Abramson, K., He, L., Mesquita, R.C., Mullen, M.T., Detre, J.A., Greenberg, J.H., Licht, D.L., Balu, R., Kofke, W.A., and Yodh, A.G., Journal of Cerebral Blood Flow & Metabolism 37, 26912705 (2017); Baker, W.B., Parthasarathy, A.B., Ko, T.S., Busch, D.R., Abramson, K., Tzeng, S., Mesquita, R.C., Durduran, T., Greenberg, J.H., Kung, D.K., and Yodh, A.G., Neurophotonics 2, 035004 (2015). Favilla, C.G., Mesquita, R.C., Mullen, M., Durduran, T., Lu, X.P., Kim, M.N., Minkoff, D.L., Kasner, S.E., Greenberg, J.H., Yodh, A.G. and Detre, J.A., Stroke 45, 1269-1274, (2014). [4] Mesquita, R.C., Faseyitan, O.K., Turkeltaub, P.E., Buckley, E.M., Thomas, A., Kim, M.N., Durduran, T., Greenberg, J.H., Detre, J.A., Yodh, A.G., and Hamilton, R.H., Journal of Biomedical Optics 18, 067006 (2013).

Hardware Development

Effects of head of bed posture changes on cerebral hemodynamics measured with fast diffuse correlation spectroscopy J. B. Fischera,d, G. Giacaloneb, D. Fernández Cuencaa, A. Ghousea, T. Durdurana,c and U. M. Weigeld a

ICFO - The Barcelona Institute of Science and Technology, Spain; bSan Raffaele Scientific Institute, Neurology Department, Italy; cInstitució Catalana de Reserca I Estudis Avançats (ICREA), Spain; dHemoPhotonics S.L., Spain. [email protected]

Introduction: The microvascular cerebral blood flow response to head of bed (HoB) position changes has been shown to be a biomarker related to cerebral vasoreactivity alterations due to various conditions such as chronic obstructive sleep apnea1, acute ischemic stroke2 and traumatic brain injury3. Recently, the pulsatility of the microvascular blood flow at the heart rate frequency was introduced as a new biomarker that can be obtained by fast Diffuse Correlation Spectroscopy (DCS) measurements4,5. In this work, we present the effect on HoB position changes on the pulsatility of the cerebral blood flow at both the heart rate (HR) and respiratory rate (RR). Methods: A custom, multi-channel, stackable and synchronized hardware correlator was developed for fast DCS measurements. The correlator is based on a field-programmable gate array and allows sampling rates up to 100 Hz, while the user can set the acquisition settings manually. One differentiator of this hardware correlator is that the full intensity autocorrelation function is calculated on the firmware as opposed to compressed autocorrelation functions calculated by software correlators in the literature4,5. The pulsatile cerebral blood flow was measured on the forehead of ten healthy volunteers during a HoB protocol (baseline at supine position, elevated HoB of 30º and recovery at supine position, each for 5 minutes). Additionally, the subjects were asked to control the breathing at a fixed RR of 12 bpm supported by a metronome. Physiological parameters such as blood pressure, HR and end-tidal CO2 were recorded continuously and the controlled breathing was confirmed alongside the fast DCS measurements. Results: All changes in ΔrCBF and the additional physiological parameters were in accordance with Edlow et al.6. Moreover, the * p < 0.05 pulsatility ratio (PR) at RR and HR with respect to its DC component were analysed for each phase. Figure 1 shows a typical example of the amplitude spectral density (ASD) of the cerebral blood flow of a representative subject for the baseline and HoB 30º. The peaks at HR and RR are evident in both phases. The averaged results are summarized in Figure 1. Conclusions: Our results demonstrate the Figure 1 Typical amplitude spectral density of a representative subject for baseline and HoB 30º feasibility to obtain information about the pulsatility at HR and RR of cerebral blood flow during HoB changes. Further analysis of the data from an increased sample size will be presented. References: 1 C. Gregori-Pla et al., PLoS ONE 13 (3), e0194204 (2018) 2 C. Favilla et al., Stroke 45 (5), 1269-1274 (2014) 3 M. Kim et al., Neurocritical Care 20 (3), 443-453 (2014) 4 D.Wang et al., Biomedical Optics Express 7 (3), 776-797 (2016). 5 W. Baker et al., Journal of Cerebral Blood Flow & Metabolism 37 (8), 2691-2705 (2017). 6 B. Edlow et al., Physiological Measurement 31 (4), 477-495 (2010)

Hardware Development Increasing diffuse correlation spectroscopy sensitivity to brain using light at longer wavelengths K.C. Wuab, D. Tamborinia, K.A. Stephensa, O. Shatrovoyc, A. Siegelc, M. Blackwellc, S.A. Carpa, and M. A. Franceschinia a

Optics at Martinos, Massachusetts General Hospital, Charlestown, MA b Boston University, Boston, Massachusetts, USA c MIT Lincoln Laboratory, Lexington, Massachusetts, USA [email protected]

Abstract: Diffuse Correlation Spectroscopy (DCS) is an established optical modality which enables non-invasive measurements of blood flow in deep tissue. Similar to NearInfrared Spectroscopy (NIRS), DCS uses red and near-infrared light to interrogate biological tissue, but, instead of quantifying hemoglobin concentration and oxygenation from the measure of light attenuation, DCS quantifies an index of blood flow (BFi) by measuring the light intensity temporal fluctuations generated by the dynamic scattering of moving red blood cells. We demonstrate here the advantages of moving DCS operation to longer wavelengths than those typically used by NIRS. In particular, we show that using light at 1064 nm allows us to increase penetration depth and spatial resolution. Finally, we report the first DCS measurements in human subjects at this wavelength. Methods: NIRS employs light in the red and near-infrared spectral region, between 600 and 900 nm, where hemoglobin absorption is orders of magnitude lower than at shorter wavelengths, but considerably higher than water absorption. Analogously to NIRS, current DCS devices operate at wavelengths between 750-850 nm, but because the contrast mechanism of DCS is dynamic scattering of red blood cells, not hemoglobin absorption, it may be advantageous to use other spectral windows for which the effective attenuation coefficient, µeff, is lower. To increase penetration depth optical imaging technologies like multi-photon microscopy1,2 and optical coherence tomography3 operate at longer wavelengths. Between 1000-1700 nm water absorption dominates, but offers some transmission windows, and at around 1064 nm the water absorption is below 0.15cm-1. Fat has a small peak at 1040 nm, and hemoglobin absorption is strongly reduced. Scattering, which decreases with wavelength, at 1064 nm is 40-50% lower than at 750-850 nm. As a result the effective attenuation coefficient of biological tissues with high concentration of hemoglobin and low fat, like brain or skeletal muscles is lower at 1064 than in the typical NIRS spectral window. In this study, we tested feasibility of DCS measurements at 1064 nm and compared its performances with DCS at 767 and 852 nm. Results and Discussion: We performed Monte-Carlo simulation, phantoms and in-vivo measurements in healthy subjects. In particular, for the cuff occlusion experiments we found comparable relative BFi during repeated occlusions in the same subject and consistent differences across subjects. A difference of ~2 cm-1 in scattering is needed to match BFi absolute values at the 2 wavelengths. The lower scattering at 1064 nm provide longer g2 decay times increasing SNR. Melanin and dark skin color don’t affect measurements at 1064 nm, and we can deliver four times as many photons than at 765 nm, because photons carry less energy at longer wavelengths. The only challenge resides in the limited availability of commercial photon counting detectors operating in this spectral range. In conclusion, operation at 1064 is advantageous for DCS because of the reduced scattering which allows for higher penetration depth and improved resolution, and may ultimately lead to higher brain sensitivity while maintaining sensitivity to blood flow. References: 1. 2. 3.

Kobat, D. et al. Opt Express 17, 13354–13364 (2009). Kobat, D., Horton, N. G. & Xu, C. J Biomed Opt 16, 106014 (2011). Povazay, B. et al. J Biomed Opt 12, 041211 (2007).

Hardware Development Comparison of haemodynamic and metabolic mappings of cortical activations to lateralized visual stimulation using broadband NIRS. A. D. Levya,b, M. F. Siddiquic, P. Pintid , P. Phand, M. S. Matharub and I. Tachtsidisd a Wellcome Centre for Human Neuroimaging, Institute of Neurology, UCL, UK b Headache and Facial Pain, Brain Repair and Rehabilitation, Institute of Neurology, UCL, UK c Centre for Brain and Cognitive Development, Birkbeck College, University of London, UK d Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, UCL, UK Corresponding author e-mail address: [email protected] Abstract Broadband near-infrared spectroscopy (bNIRS) provides simultaneous measures of haemoglobin (Δ[HbO2], Δ[HHb]) and cytochrome-c-oxidase (Δ[oxCCO]) concentration changes. We demonstrate the capabilities of a multichannel bNIRS system to map cortical activations resulting from a visual stimulus alternating between the right and left visual hemifields. Motivation: Previous work has shown Δ[oxCCO] to have increased brain-specificity compared to changes in Hb concentration as a measure of cerebral oxygen delivery. [1] The primary objective of this study was to extend on this finding by investigating differences between the chromophores in localizing functional activity across the visual cortex. Method: Eleven heathy volunteers (6 females and 5 males, ages 24-35 years) were recruited for this study. The visual stimuli were left and right hemifield checkerboards. Stimulation duration was 18s followed by a resting period of 18s. We used an in-house built bNIRS system with four sources and ten detectors arranged to obtain 16 channels centered on the Oz reference point commonly used in EEG [2]. One sample T-tests vs 0 on the peak amplitude for each individual chromophore were used to construct statistical maps of cortical activations. Results:

Fig. 1. Group-level statistical activation maps for the three chromophores computed comparing the peak amplitude of each individual chromophore vs 0 through one-sample t-tests.

Discussion: In response to hemifield visual stimulation, all three chromophores demonstrated widespread significant activations in the corresponding contralateral hemisphere. Additionally, activations were shown in the ipsilateral hemisphere, in accordance with findings of extrastriate visual regions which contain representations of the entire visual field. [3] Interestingly, differences between the mappings of the chromophores were most apparent with the ipsilateral activations. Ipsilateral Δ[oxCCO] responses were more ventral when compared to the Δ[HbO2] and Δ[HHb]. This finding may relate to the main input to the ventral steam arises from the parvocellular pathway, which has been shown to have a higher density of Δ[oxCCO]. [4] References [1] [2] [3] [4]

Kolyva et. al, Neuroimage 2014. Phan et al., Biomedical Optics , 2016. Tootell et al, PNAS, 1998. Wong-Riley et al., Visual neuroscience, 1993.

Hardware Development High-resolution TR NIROT for brain imaging with >3000 source/detector pairs A. Kalyanova, J. Jianga, S. Lindnerab, L. Ahnena, A. Di Costanzo Mataa, J. Mata Paviaa, S. Sanchez Majosa, C. Zhangc, E. Charbonb, M. Wolfa aBiomedical

Optics Research Laboratory (BORL), Dept. of Neonatology, University of Zurich Quantum Architecture (AQUA) laboratory, School of Engineering, EPFL Lausanne cApplied Quantum Architectures, Delft University of Technology, Delft, Netherlands. Corresponding author e-mail address: [email protected] bAdvanced

Approximately 25’000 preterm infants between 23 and 32 weeks of gestation are born each year in Europe. Despite improved survival rate (~80%), up to 25% develop cerebral palsy or a low IQ, and significant cognitive delay is present in ~12% by school age [1, 2]. Most long-term impairments are caused by periventricular diffuse white matter injury (WMI) that occurs early after birth. It is mainly initiated by cerebral ischemia (low tissue oxygenation, or hypoxia). MRI and US cannot image hypoxia in neonates at the bedside, thus a new method is needed. To address this problem, we have recently designed and built the new time-resolved nearinfrared optical tomography (TR NIROT) system – Pioneer [3]. It aims at brain imaging of preterm neonates with high spatial resolution and at detecting hypoxia and bleeding (Fig. 1a). Pioneer is based on a camera with a high number (1024) of pixels capable of detecting the time-of-flight of single photons. The pixels comprise a single-photon avalanche diode (SPAD) with 116ps time response and an unprecedented sensitivity, i.e. a photon detection probability, of 12% at 800nm. This camera chip was especially designed for NIROT applications by BORL and AQUA [4]. Pioneer employs a super continuum laser to generate a narrow-band light at multiple wavelengths. The light is guided to 11 source fibers, which are hosted in a rigid source ring (Fig.1b). It embedded in soft, biocompatible silicon to provide a gentle contact to neonatal head [5]. We implement the wavelength normalization to correct for coupling and surface artifacts. At the current stage, we use 6-10 wavelengths at all 11 sources and ~300 detectors. Thus, the total number of source-detector pairs is greater than 3’000. In this work, we present results of Pioneer tests in phantoms, including penetration depth estimation. A highly absorbing silicon brick was immersed into a solution of 40ml Intralipid 20% in 1l of water (Fig.1c). It was imaged from the top with the Pioneer sensor being in contact with the liquid surface. We analyzed the timing response of a central pixel. The ratio of homogeneous (no inclusion) and heterogeneous data revealed a decrease in a number of detected photons due to the inclusion. The effect decreased with the inclusion depth, but was significant even at 30mm (Fig.1d). Noticeably, the deep inhomogeneity affects the late photons only (arrival time >2ns), which emphasizes the benefits of time-resolved measurements. With Pioneer a new TR NIROT for preterm brain imaging was built, that enables an unprecedented number of light source/detector pairs. The system performs as expected, namely, the readout correlates well with simulated data. The tests confirmed that Pioneer is sensitive to 3cm depth in scattering media; therefore, the location of WMI is reachable.

a) b) c) d) Fig.1. Pioneer sensor in NICU incubator, attached to a dummy head (a), the source ring (b). Penetration depth test layout (c), ratio of timing response of ‘hetero’ vs ‘homo’ phantoms (d). 1. 2. 3. 4. 5.

Fischer, N., et al., Arch Dis Child Fetal Neonatal Ed, 2009. 94(6): p. F407-13. Hutchinson, E.A., et al., Pediatrics, 2013. 131(4): p. e1053-61. Kalyanov, A., et al. in Optical Tomography and Spectroscopy. 2018. OSA. Lindner, S., et al. in Int. Image Sensor Workshop. 2017. Ahnen, L., et al., Adv Exp Med Biol, 2017. 977: p. 163-168.

Neonatal, pediatric & developmental neuroscience I [invited talk]

Dynamics of Functional Networks in the Developing Brain

Fumitaka Homaea,b

a

b

Department of Language Sciences, Tokyo Metropolitan University, Japan Research Center for Language, Brain and Genetics, Tokyo Metropolitan University, Japan Corresponding author e-mail address: [email protected]

Introduction: Structural and functional organization of the brain occurs rapidly in early infancy. Previous studies report that in neonates and young infants, this neural organization is sensitive to speech sounds, and related functions in distinct brain regions have been partially elucidated (Homae et al., 2014). It is known that short speech sounds induce eventrelated activation in the temporal brain regions in young infants; increases in oxygenated hemoglobin (oxy-Hb) signals are followed by signal decreases to the onset level within a 10to 20-second time scale. We can also visualize the static aspects of functional relationships, such as correlations between spontaneous activations in homologous regions (Homae et al., 2010). However, we have limited information on the dynamics of cortico-cortical interactions during the presentation of speech sounds to infants. In the present study, we calculated the dynamic functional connectivity (dFC) of cortical activation in neonates and 3- and 6-monthold infants in response to short sentences in Japanese. We hypothesized that functional relationships will not be constant, but will instead be modulated, during typical cortical hemodynamic responses to speech sounds. We further predicted that functional connectivity between distant cortical regions would change from a local to a global state depending on the stage of development. Methods: We analyzed data obtained from quietly sleeping neonates (N = 28) and 3- and 6month-old infants (N = 26 and 27, respectively). We presented auditory sentences while measuring brain activation using 94-channel fNIRS (ETG-7000, Hitachi). The continuous oxy-Hb signals were band-pass filtered from 0.01 to 0.2 Hz. The signal changes in response to speech sounds were examined by averaging the signals over segmented data blocks. We applied the Hilbert transform to the continuous data to estimate the phase of the signals in all channels. We defined dFC using the following equation (Cabral et al., 2017): dFC(p, q, t) = cos(θ(p,t) – θ(q,t)), where p and q are channels and t is a time point. Results and Discussion: We found that the frontal and temporal regions in all participant groups demonstrated increases in oxy-Hb signals when the sentences were presented. In addition, 3- and 6-month-old infants exhibited similar changes in the occipital regions, as in our previous studies (Homae et al., 2011; Taga et al., 2018). The dFC between homologous regions increased with age, consistent with our previous findings (Homae et al., 2010). Although frontal regions exhibit dense clusters in all groups, clusters over the temporal, parietal, and occipital regions were observed only in 3- and 6-month-old infants. Overall, we found that the dFC between the frontal and temporal regions changed with the presentation of speech sounds, and the organization of functional networks depended on age. These results support our hypotheses and suggest that the dynamics of functional networks will help in revealing how infants hear speech sounds and acquire their native language. Acknowledgements: This study was partly supported by Japan Society for Promotion of Science KAKENHI Grant Nos. JP16H06524, JP16H06525 and 26220004.

Neonatal, pediatric & developmental neuroscience I The role of timing in the consolidation of newborn’s memories S. Benavides-Varelaa, R. Siugzdaiteb, and J. Mehlerc a

Department of Developmental Psychology and Socialization, University of Padua, Italy b Data Analysis Department-Faculty of Psychological and Educational Sciences, Ghent University, Belgium c Language Cognition and Development Laboratory, International School for Advanced Studies (SISSA), Italy Corresponding author e-mail address: [email protected]

Introduction: The capacity to memorize speech sounds is crucial for language acquisition. Only a few days after birth human infants can recognize the sound of one word even if interleaved with other word sounds during encoding [3]. However, newborns do not recognize a previously learned word when interfering information is presented immediately after encoding, i.e. in the retention interval between the encoding and the recognition test [1]. At least two proposals can explain this retroactive interference phenomenon in the first stages of development: A. a storage-based hypothesis, which presupposes a failure in recognition due to limitations in the number of items that newborns can memorize, or B. a consolidation-based hypothesis, which assumes a need for protracted consolidation periods, which are reflected in weaker memory traces short after learning. The aim of the present study was to evaluate the second hypothesis by prolonging inserting a silent pause between encoding and the presentation of interfering sounds, therefore favoring consolidation. Methods: Forty healthy full-term newborns (13 males; mean age: 2.8 days, range: 2-5 days) were tested on their ability to recognize the sound of a word after an interfering word. The structure of the experiment consisted of an encoding phase and a test phase separated by a retention interval of 4 minutes that comprised two minutes of silence followed by two minutes of auditory stimulation (interference). During the test phase, brain hemodynamic responses to the familiarized word (Same-word condition) and a completely novel word sound (Novelword condition) were assessed. Hemodynamic responses were measured with functional near-infrared spectroscopy (fNIRS; ETG-4000, Hitachi) over 24 channels grouped on 6 regions of interest (ROIs) on the frontal, temporal, and parietal areas of both hemispheres [see also 2,3 for a similar approach]. Results and Discussion: Permutation tests performed over each ROI showed significant differences between conditions (same word vs. novel word) in the right-frontal region in the first block of the test phase (p = 0.006, Bonferroni-corrected). In agreement with previous studies with similar fNIRS paradigms [2,3], neonates in the novel-word group displayed greater hemodynamic responses than neonates in the same-word group. The results indicate that newborns are able to recognize the familiar word after hearing interfering words but only when the interfering sounds are presented after a silent retention interval. This supports the hypothesis that short silent resting periods are effective to facilitate the consolidation of newborns’ word memories, and therefore to make them more withstanding to eventual interfering sounds. References 1. Benavides-Varela, S., Gómez, D. M., Macagno, F., Bion, R. A., Peretz, I., & Mehler, J. (2011). Memory in the neonate brain. PLoS One, 6(11), e27497. 2. Benavides-Varela, S., Hochmann, J. R., Macagno, F., Nespor, M., & Mehler, J. (2012). Newborn’s brain activity signals the origin of word memories. Proceedings of the National Academy of Sciences, 109(44), 17908-17913. 3. Benavides-Varela, S., Siugzdaite, R., Gómez, D. M., Macagno, F., Cattarossi, L., & Mehler, J. (2017). Brain regions and functional interactions supporting early word recognition in the face of input variability. Proceedings of the National Academy of Sciences, 201617589.

Neonatal, pediatric & developmental neuroscience I

Statistical Learning of Phonemic Contrast in Neonates: Cerebral Networks and Activities

Eiichi Hoshinoa, Takeshi Arimitsub, Naomi Shinoharab, Takao Takahashib and Yasuyo Minagawaa

a

Department of Psychology, Faculty of Letters, Keio University, Japan b Department of Pediatrics, Keio University School of Medicine Corresponding author e-mail address: [email protected]

Background: In the course of the first year of life, infants acquire phonemic categories employed in their first language. One of the mechanisms of this learning process is statistical learning of phonemes (Maye et al., 2002). According to this, infants’ sensitivity to discriminate phonemes are attuned based on the statistical distributions of sounds in their ambient language. In fact, Maye et al. (2008) reported that 8-month-old infants increased their discrimination ability of difficult phonemic contrast after exposure to a bimodal statistical distribution of acoustic characteristics of those phonemic contrast. However, it remains unknown whether young infants learn phonemic contrast by employing statistical learning. Accordingly, we examined cerebral networks and activities underlying the statistical learning of phonemes by using fNIRS. For this purpose, we investigated whether resting state networks change (e.g. Homae et al. 2011) and discriminative response change as a result of statistical learning in neonates. Methods:19 full-term infants participated in this study (mean age: 4.8 days; range: 3 to 7 days). The experiment consisted of five phases: pre-resting, pre-discrimination, learning, post-resting and post-discrimination in order. In the pre- and post-resting phase, we measured spontaneous fluctuation of activity in the brain. In the pre- and post-discrimination and learning phase, we measured hemodynamic responses to auditory stimuli. The stimuli were generated from /light//right/ continuum by manipulating F2. For the learning phase, stimuli were stochastically sampled to form a bimodal distribution with the typical /light/ and /right/ sounds at the two peaks. In the preand post-discrimination phase, we measured discriminative response to either of /light/ or /right/ prototypical sounds against repetition of either /right/ or /light/ sounds for 15s as a baseline period. For pre- and post-discrimination and learning phases, oxy-Hb signals were averaged over the target period for each participant for each channel. For pre- and post-resting and learning phases, correlation coefficients (r) between the time courses of all channel pairs were calculated and transformed to Fisher-Z as functional connectivity. Results and Discussion: Neonates showed increased resting state connectivities between bilateral superior temporal gyrus (STG) and the frontal brain regions after exposure to a bimodal distribution of phonetic tokens. Moreover, results of the pre- and post-discrimination tests showed significantly increased hemodynamic response to the phonemic contrast in the left STG and the right dorsolateral prefrontal cortex (dlPFC) after the exposure. Increased hemodynamic response in the left STG was correlated with decreased amplitude of long-range connectivity between frontal and temporal regions. This suggests that successful learning of phonemic contrast enhances desynchronization of some parts of long-range connectivity. Based on these results, we discuss how statistical learning of phonemic contrast can impact on neonates’ brain.

Neonatal, pediatric & developmental neuroscience I Functional Connectivity Patterns in Monolingual and Bilingual Infants B. Blancoa, M. Molnarb, E. Amicoc, M. Carreirasa and C. Caballero-Gaudesa a

b

Basque Center on Cognition, Brain and Language, Spain. Dept. of Speech-Language Pathology, Faculty of Medicine, University of Toronto, Canada. c School of Industrial Engineering, Purdue University, USA. Corresponding author e-mail address: [email protected]

Introduction. In this work we evaluated whether brain adaptations are induced by the effect of an early and continued exposure to a bilingual vs. a monolingual environment by testing between group differences in resting state functional connectivity (RSFC). We also assessed the reliability of our previous results by testing sleeping, as opposed to awake infants, in order to maximize signal quality. Methods. Spontaneous hemodynamic activity was recorded (9 min.) using nearinfrared spectroscopy (NIRS) in 4-month-old infants (n=27 bilinguals, n=25 Spanish and n=26 Basque monolinguals). Within each group we measured the antiphase relationship between deoxy- (HbR) and oxyhemoglobin (HbO2), and perform a hierarchical spatio-temporal clustering. Network based statistics (NBS) (Zalesky et al., 2010) and connICA (Amico et al., 2017) procedures were also employed to explore differences in functional connectivity patterns between groups. Results and Discussion. In our three experimental groups we observed an antiphase relationship between HbR and HbO2 (Fig. 1A) which resembles the results of Watanabe et al., (2017). The spatial configuration of clusters (Fig. 1B) across groups also demonstrates a high degree of consistency with previously reported results (Homae et al., 2010). These results were not replicated in our previous study in awake infants. We assume that our previously reported effects were probably caused by motion artifacts in the signal, and recognize the importance of correct data quality assessment in NIRS studies with infants to avoid this type of spurious results. Pairwise comparisons with NBS revealed a network (Fig. 1C) involving spatially homologous channels of both hemispheres showing stronger synchronization in Spanish monolingual infants than in Basque monolingual infants (p=0.04). The same difference between groups is also observed in HbO2 (p=0.04) in a network showing a similar spatial disposition. ConnICA revealed a FC pattern (Fig. 1C) showing a significantly larger presence in Spanish than in Basque monolingual infants, in HbR (p=0.04) and HbO2 (p=0.04), which resembles the results obtained with NBS. Despite their small effect, the observed between group differences are consistent across HbR and HbO2, and show a similar spatial pattern regardless of the procedure being employed. Watanabe H. et al. (2017). Hemoglobin phase of oxygenation and deoxygenation in early brain development measured using fNIRS. Proc. Natl. Acad. Sci. 114(9), E1737–E1744. Homae F. et al. (2010). Development of global cortical networks in early infancy. J. Neurosci. 30(14), 4877– 4882. Zalesky A. et al. (2010). Network-based statistic: identifying differences in brain networks. Neuroimage, 53(4), 1197-1207. Amico E. et al. (2017). Mapping the functional connectome traits of levels of consciousness. NeuroImage, 148, 201-211.

Neonatal, pediatric & developmental neuroscience I Neural basis of attention cues assisting grammar learning in preverbal infants A. Martinez-Alvareza,b, J. Gervainc,d, E. Koulaguinaa,b, F. Ponsa,e and R. de Diego-Balaguera,b,e,f aUniversity

of Barcelona and Brain Plasticity Unit cCNRS dUniversité Paris Descartes eInstitute for Brain, Cognition and Behaviour fICREA bCognition

Corresponding author: [email protected] Introduction. A core ability in language acquisition involves the learning of non-adjacent rules (e.g. are walking, unbelievable). In natural language, non-adjacent rule learning is observed when salient cues are present in the speech signal such as repetition-based cues. However, in the absence of cues, learning is only observed after the first year of life (Gómez & Maye, 2005; Santelmann & Jusczyk, 1998). Previous studies investigated the brain basis of repetition-based rule learning in neonates and found increased responses to the repetition sequences in temporal and left frontal regions (Gervain et al., 2008). Recent proposals account for this developmental trajectory postulating that infants’ attentional system supports language development (de Diego-Balaguer et al., 2016). Methods. In a series of behavioural and fNIRS experiments we tested whether and how exogenous attention cues promote the learning of specific linguistic rules in infancy. We presented 8-10-month-old infants (n = 83) with sequences containing an AXB-type structure, where A and B predict one another with certainty (“pedibu”, “pegabu”) or a random control structure (“dibupe”, “bugape”). The stimuli either contained or lacked pitch cues in the dependent (A and B) elements. Infants’ rule discrimination was measured behaviorally using a Central Fixation Procedure and infants’ brain activity was measured in the temporal, parietal, and frontal lobes using functional near-infrared spectroscopy (fNIRS). Results. In the absence of pitch cues, behavioural results show that infants are unable to discriminate rule-following from random control structures. At a neural level, a larger activation (oxyHb) is observed in temporal areas but no difference between conditions (rule vs. no rule) arises, suggesting that infants’ brain processes the auditory stimuli similarly in both conditions. However, in the presence of subtle attention cues highlighting the elements to be learned, infants show successful rule learning behaviourally and a significant larger activation (oxyHb) for the rule condition is observed in temporal and frontal areas bilaterally (Figure 1). Discussion. These results suggest that only when infants’ exogenous attention is captured by salient cues the learning of linguistic rules is observed. This study contributes to our understanding of the brain substrates of rule language acquisition showing that the powerful attention system infants are equipped with early in life may assist grammar learning even in preverbal infants.

Figure 1. Gran averages of the hemodynamic response evoked by each condition in each channel. X-axis=time(sec) yaxis=concentration (mmol x mm). Small rectangle=time of stimulation. Channels 8, 11, 22 and 24 were not available on the machine used for the study.

Clinical applications I

Compensatory brain activation is associated with the relationship between aerobic fitness and working memory in the elderly

Kazuki Hyodoa, Takashi Jindoa, Tatsuya Tokudab, Kiyomitsu Niiokac, Ippeita Danb, Hideaki Soyad, and Toshiya Nagamatsua

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Physical fitness institute, Meiji Yasuda Life Foundation of Health and Welfare, Tokyo, Japan b Applied Cognitive Neuroscience Laboratory, Chuo University, Tokyo, Japan c Graduate School of Humanities, Hosei University, Tokyo, Japan. d Laboratory of Exercise Biochemistry and Neuroendocrinology, University of Tsukuba, Ibaraki, Japan [email protected]

Introduction: Working memory (WM), which is mediated by prefrontal cortex (PFC), declines with aging. On the other hand, recent studies have reported that elderly with higher aerobic fitness have higher WM capacity. However, the underlying brain mechanisms of the relationship are not well known. Previous neuroimaging studies reported that elderly recruit more PFC region during WM task than young adults to compensate for the age-related decline in PFC function. Thus, the compensatory brain activation might mediate the relationship. To test the assumption, in this study, we compared the brain activation during WM task between older and younger adults to find older-age-specific brain activation. Then, we examined the relationship between aerobic fitness, WM performance, and brain activation in the elderly. Methods: Twenty-two healthy elderly female (68.8 ± 2.4 years) and Sixteen young female (21.6 ±1.2 years) participated in the study. Both age groups performed computer-based verbal N-back task with letter stimuli as the WM task. The task consisted of three conditions: 0-back (no memory load), 1-back (low memory load), and 2-back (high memory load). Correct reaction time (RT) and correction rate (CR) in each condition were measured. During the task, we monitored prefrontal activation with multichannel fNIRS. fNIRS probes were set to cover lateral PFC activation foci, and neighboring channels were combined for the dorsolateral PFC (DLPFC), ventrolateral PFC (VLPFC), and frontopolar area (FPA) in each hemisphere using virtual spatial registration (Tsuzuki et al., 2007). On another day, only older group conducted a graded exercise test using a recumbent ergometer. During the exercise test, respiratory gas was measured and ventilatory threshold (VT) was analyzed as an indicator of aerobic fitness. Results: In WM performance, compared to the younger participants, older participants showed higher RT for all conditions lower CR for 2-back. Moreover, in older participants, RT for 2-back was slower and CR for 2-back was lower than 0- and 1-back conditions. Comparing the brain activation during WM task between age groups, right VLPFC during 2-back condition was more activated in older participants than the younger participants. Correlation analysis showed moderate relationship among higher aerobic fitness, lower RT for 2-back condition, and higher right VLPFC activation for 2-back condition in the older participants. Conclusion: From the results, the right-VLPFC activation could be considered as the olderage-specific compensatory brain activation. Moreover, it is suggested that this compensatory brain activation could mediate the relationship between aerobic fitness and WM in older adults.

Clinical applications I Disinhibition in children with ADHD: Simultaneous study of fNIRS and ERPs in Go/NoGo task Yoshimi Kagaa, Riyo Uedaa, Miho Tanakaa, Yosuke Kitaa, Kota Suzukia, Yasuko Okumuraa, Shota Mitsuhashia, Yuzuki Kitamuraa, Eiji Nakagawab, Masumi Inagakia a

Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry (NCNP), Japan b

Department of Child Neurology, National Center Hospital, NCNP, Japan Corresponding author e-mail:[email protected]

Introduction: Children with attention deficit hyperactivity disorder (ADHD) often exhibit deficit in executive function. In general, ADHD is diagnosed behaviourally because objective biomarker for ADHD is undetermined. It is well known that event-related potentials (ERPs) in Go/NoGo task could reflect inhibitory function in children. So, we aimed to clarify their executive dysfunction by simultaneous measurement of oxygenated hemoglobin concentration [OxyHb] through functional near-infrared spectroscopy (fNIRS) and ERPs during Go/NoGo task in children with/without ADHD. In addition, we evaluate the utility of fNIRS and ERPs as biomarker of executive functions. Methods: Subjects were 15 ADHD patients and 6 typically developing children (TDC) (8 to 11 years old). ERPs were recorded at Fz, Cz, Pz (10-20 method) and [OxyHb] was recorded at forehead during visual CPT task, which appeared five colored patches on LCD monitor in succession. Those tasks were presented the block design with Go and Go/NoGo condition. We calculated each latency and amplitude of NoGo-N2 and NoGo/Go-P3 waves. Correlation between hemodynamic and ERPs data was analysed. Results: TDC showed [OxyHb] increase at right frontal region during Go/NoGo condition. In contrast, children with ADHD presented significant decrease of [OxyHb] at that region (p.05) and no OAs showed noticeable decline. For YAs, HbO2 concentration increased from baseline during incongruent, but not congruent, trials in the left (t(11)=7.291, p=.0002) and right (t(11)=3.948, p=.016) ROI. The YAs showed a larger HbO2 increase from baseline versus OAs during incongruent trials in the left (t(23) = 3.175, p =.017) (Fig. 1b) and right (t(23) = 2.709, p = .025) ROIs, and the YA activation in the left ROI only was larger for incongruent than congruent trials (t(11) = 2.643, p =.046). No statistically significant differences were found in the OA group for either condition / chromophore, or for HbR in either condition in YAs (all p>.05). Discussion: Older adults with DS show reduced activation in bilateral inferior frontal areas during incongruent trials versus baseline in a picture-based Stroop task compared to younger adults, despite behaviourally performing equally well in the task. These results suggest that fNIRS is sensitive to changes in frontal cortical functioning with increased age, in a population at ultra-high risk of AD. Future research should explore whether individual differences in fNIRS measurements are predictive of subsequent cognitive decline.

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Wiseman, F. K. et al. Nat. Rev. Neurosci. 16, 564–574 (2015). Kaufman, A. S. & Kaufman, N. L. K-BIT, Second Edition. (Pearson Inc, 2004). Holland, A. J. & Huppert, F. A. CAMDEX-DS (Cambridge University Press, 2006). Ehlis, A.-C., Herrmann, M. J., Wagener, A. & Fallgatter, A. J. Biol. Psychol. 69, 315–331 (2005).

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Clinical applications II

Near infrared spectroscopy (NIRS) indicates hypoxia and cerebrovascular dysfunction in patients with chronic liver inflammation Chris C. Duszynskia,c,d,e, V. Avatib,c,d,f, F. Scholkmanng, M. G. Swainb,c,d,f, J. F. Dunna,c,d,e a

b c Department of Radiology, Department of Medicine, Cumming School Medicine, dUniversity of e f Calgary, Canada, Hotchkiss Brain Institute, Snyder Institute for Chronic Diseases, gBiomedical Optics Research Laboratory, Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland

[email protected] Background: There is growing evidence that peripheral organ inflammation activates inflammatory processes in the brain, which can result in cerebrovascular dysfunction and altered neural activity1,2. In this study, we used functional (continuous-wave) NIRS and quantitative (frequency-domain) NIRS to determine whether patients with the cholestatic liver disease primary biliary cholangitis (PBC) exhibit (i) altered neurovascular coupling, and (ii) hypoxia in cortical brain regions, and (iii) whether observed changes are associated with PBC-related impact on qualtity of life (QoL). Methods: Thirteen female PBC patients (median age 61 yrs; range 39-77) and 11 age-matched female controls underwent resting NIRS measurements. A TechEn continuous-wave fNIRS system was used to record a 7-minute resting state scan, over bilateral dorsolateral prefrontal and motor cortices. Global coherence was calculated using a wavelet coherence method for lowfrequency (0.08-0.15Hz) and very low-frequency (0.01-0.08Hz) bands, and is referred to as global connectivity (GConn). Absolute oxygen saturation (% StO2) was quantified using an ISS Oxyplex frequency-domain system (qNIRS). Wilcoxon rank-sum test and Cohens’ d were used to statistically evaluate group differences. Results: GConn was significantly reduced in the PBC group (fig. a, b; p=0.015, d=1.37). The PBC group also demonstrated significant cortical hypoxia (fig. c; p=0.027, d=0.63). No significant correlations were found between GConn and StO2, nor between QoL scores and either NIRS outcome. Conclusion: Our findings indicate a significant reduction in frontal cortex oxygenation and significant changes in cortical functional connectivity in PBC patients, independent of QoL scores. We hypothesize that cerebrovascular dysfunction in PBC drives these connectivity changes, given that the greatest difference in GConn occured at a frequency related to vasomotor activity (Mayer Wave; 0.08-0.15 Hz) and changes are global in nature. These findings are supported by our previously published observations that leukocyte recruitment to cerebrovascular endothelial cells is linked to neural dysfunction in cholestatic mice1. References: 1. D'Mello, C., et al., J Neurosci, 2013. 33(37): p. 14878-88. 2. Akopov, S., R. Sercombe, and J. Seylaz, Cerebrovasc Brain Metab Rev, 1996. 8(1): p. 11-94.

Clinical applications II Time-Domain Near Infrared Spectroscopy in acute ischemic stroke patients with different sites of large vessel occlusion.

Giacomo Giacalonea, Marta Zanolettib, Rebecca Reb, Davide Continib, Lorenzo Spinellic, Alessandro Torricellib,c, Luisa Roveria a

San Raffaele Scientific Institute, Neurology Department, Italy b Politecnico di Milano, Dipartimento di Fisica, Italy c Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Italy [email protected] Motivation and aim: steno-occlusive disease of large vessels might cause different degrees of hemodynamic impairment in acute ischemic stroke patients. The study of cerebral microcirculation by means of cerebral time-domain near infrared spectroscopy (TD-NIRS) could inform about the hemodynamic and metabolic effect of large vessel occlusion. Methods: we enrolled acute ischemic stroke patients due to internal carotid artery (ICA) or proximal middle cerebral artery (MCA) steno-occlusive disease documented on CTA or MRA. As comparator we used a previously described cohort of 56 healthy subjects older than 55 years [1]. According to the site of arterial steno-occlusion, patients were classified as “ICA” group (homolateral focal ICA steno-occlusion), or “MCA” group (focal MCA steno-occlusion). Collaterals were assessed using CT- or MR-based grading systems [2]. TD-NIRS measurements were performed during the sub-acute phase of stroke, consistent with clinical stabilization, on multiple brain regions using 3 wavelengths (690, 785, 830 nm). Data were fitted with the diffusion model for semi-infinite homogenous media. Probed brain areas were classified as ischemic area (IA), non-stroke areas of homolateral (NSH) and contralateral hemisphere (NSC) in agreement to neuroimaging performed with fiducial markers. Results: the ICA group included 4 patients with mean (±SD) age 69.7±12.7. Stroke severity scored with NIHSS scale was 3.5 (2.5-6.2) [median (IQR)]. Patients with steno-occlusive ICA had downstream circle of Willis featuring absent homolateral posterior communicating artery, prominent contralateral posterior communicating artery and anterior communicating artery. Leptomeningeal collateral circulation was intermediate. The MCA group included 2 patients with mean age 69.5±2.1. Stroke severity scored with NIHSS was 5 (3-7) [median (IQR)]. MCA patients had upstream preserved circle of Wills and downstream good leptomeningeal collateral circulation. Patients with steno-occlusive ICA had lower StO2 compared to controls in all probed brain areas (IA 49.2%, NSH 45.6%, NSC 47% vs. 57.8%, p=1.6 10-4; p=1 10-6, p=5 10-6). In addition, NSH and NSC had lower HbO compared to controls (respectively, 19,8 µM, 22.3 µM vs. 31.2 µM; p=0.005, p=0.043). For patients with steno-occlusive MCA, values of hemoglobin species and StO2 in all probed brain areas were comparable to controls. Probed brain areas had comparable values of hemoglobin species and StO2 within each group of patients. However, patients with steno-occlusive ICA had lower StO2 compared to MCA patients (respectively, IA 49.2% vs. 59.9%, p=0.011; NSH 45.6% vs. 60.4%, p=0.001; NSC 47% vs. 58.6%, p=0.039). Discussion: despite similar clinical severity, only patients with steno-occlusive ICA had lower StO2 compared to controls. In addition, patients with steno-occlusive ICA had lower StO2 compared to MCA patients. These findings might suggest that StO2 might discern different degrees of hemodynamic impairment. [1] G. Giacalone, M. Zanoletti, D. Contini, R. Re, L. Spinelli, L. Roveri, and A. Torricelli, Biomed. Opt. Express 8(11) 4987-5000 (2017) [2] B.K. Menon, d'Esterre CD, Qazi EM, Almekhlafi M, Hahn L, Demchuk AM, Goyal M. Radiology 2015 275 (2): 510-52

Clinical applications II

Non-invasive Optical Monitoring of Cerebral Blood Flow and Oxygen Metabolism in Adult Critically Brain-injured Patients Wesley B. Bakera,b, R. Baluc, L. Hed, D.R. Buschd,e, V.C. Kavurid, O. Amendoliaf, F. Quattronef, E. Maloney-Wilenskyf, E. Mahanna Gabriellib, A.G. Yodhd, W.A. Kofkeb Division of Neurology, Children’s Hospital of Philadelphia, USA Departments of b Anesthesiology & Critical Care, c Neurology, d Physics & Astronomy, and f Neurosurgery, University of Pennsylvania, USA e Department of Anesthesiology & Pain Management, University of Texas Southwestern, USA Corresponding author e-mail address: [email protected] a

Introduction: Treatment of acute brain injury is aided by using bedside cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) monitors for rapid detection of ischemic conditions. We carried out an observational pilot study in critically brain-injured adults that demonstrates the utility of non-invasive CBF and CMRO2 monitoring with a hybrid optical approach. The approach interleaves time-resolved NIRS (TR-NIRS) measurement of cerebral oxygen saturation and oxygen extraction fraction (OEF) with diffuse correlation spectroscopy (DCS) measurement of CBF. In combination, these measurements enable computation of CMRO2. Optical CBF and CMRO2 measures were compared to concurrent invasive brain tissue oxygen tension (PbtO2) and microdialysis measures. We successfully used CBF and CMRO2 information to distinguish between ischemic, hypermetabolic, and hyperemic conditions that arose spontaneously during patient care. We further compared optical and invasive measures of hemodynamic changes induced by pressor drugs. Methods: Eleven neurointensive care unit adult patients with invasive PbtO2 and microdialysis monitors were enrolled for ~8 hours daily (Recs

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Neuroscience

Decoding visual information from high density diffuse optical tomography neuroimaging data Kalyan Tripathya, Andrew K. Fishella, Zachary E. Markowa, Tracy Burns-Yocuma, Adam T. Eggebrechta, Bradley L. Schlaggara, and Joseph P. Culvera a

Department of Radiology, Washington University in St. Louis, United States of America Corresponding author e-mail address: [email protected]

Abstract: Decoding involves inferring information about sensory stimuli and mental processes from recordings of brain activity. Detailed visual decoding studies using fMRI have provided insight into visual system organization in healthy adults, with a more explicit, robust, and prospective level of validation in comparison to more traditional encoding or mapping paradigms. Decoding also has potential clinical utility, for instance as a means of augmented communication for patients with speech impairments. However, it is challenging to perform fMRI in some populations such as young children, and it is not economically or technically feasible for patients to use MRI scanners for daily communication. Optical neuroimaging, in contrast, is more cost effective and portable, provides potentially dramatic improvements in wearability, and can be used to image brain activity without contraindications across the lifespan. High-density diffuse optical tomography (HD-DOT) is a high-performance optical neuroimaging method with spatial resolution that has begun to approach that of fMRI, and thus holds promise as a means of performing decoding with similar detail. Here we present visual decoding with HD-DOT, showing the feasibility of decoding the location of a checkerboard viewed by a human subject in pseudo-real-time (i.e. without needing to blockaverage our test data), using a template matching strategy that required less than 10 minutes of independently acquired training data (Figure 1).

Figure 1: Visual stimulus information can be decoded using HD-DOT data and a template matching strategy. (A) Binary decoding: A participant viewed checkerboard stimuli in either the left or right visual hemifield while being imaged by HD-DOT. During training, data was block-averaged to define cortical activation “templates” corresponding to stimuli in the left and right hemifields. Independent test data was collected, here during a separate imaging session on a different day. The “actual stimulus” block design for this test data is shown. Below it is a plot of the “decoded stimulus” over time, determined by: (1) calculating the Pearson correlation coefficient (bottom left plot) between each template and the HD-DOT brain activity map at each time point, and (2) comparing these Pearson values to both an absolute threshold and to each other (thresholded winner-take-all strategy). (B) More complex retinotopic decoding: Here, the checkerboard rotated through 36 phases around the visual field (each phase is assigned a color, per color wheel), and 36 cortical activation template maps were generated from the training data. Pearson correlation values were calculated with each of these 36 templates for every time point in the test data and plotted on the grayscale heat map (bottom right). The “decoded stimulus” was again determined by a thresholded winner-take-all strategy, and the “actual stimulus” time trace is plotted above. ROC analysis (AUC=0.99 for left vs right) and permutation tests (mean error =14° for rotating stimulus vs 122° for 100 null models) were used to quantify the accuracy and significance of our decoding. Future studies will include more complex decoding and decoding in special populations such as children with visual disorders and patients with speech impairments.

Neuroscience

Multi-Channel NIRS Brain Imaging of Freely Moving Animals during Cognitive Stimulation Using a Customized Kit Box JuHee Kim, Shin-Young Kang, Zephaniah Phillips, Seung-ho Paik, Youngwoon Choi, Beop-Min Kim Department of Bio-convergence Engineering, Korea University, Seoul, Republic of Korea [email protected] Near-infrared spectroscopy (NIRS) is a portable and non-invasive method for monitoring cerebral hemodynamic activities and it has been used extensively in small animal studies. NIRS systems for small animals often consist of only a few number of channels, therefore, spatial fluctuation of cerebral hemodynamics cannot be investigated. Also, the animal often needs to be anesthetized and fixed in a stereotaxic device in order to reduce motion artifacts, which limits advanced studies. To overcome these limitations, we propose a NIRS system for freely moving mice using light weight, long optical fibers for multichannel hemodynamic measurement on the brain. Our NIRS system is composed of six laser diodes and four avalanche photodiodes (APD) and fiber-optic delivery system for two wavelengths (785nm, and 850nm). Multi-mode fiber coupler modules deliver two different wavelengths of separate laser diode sources using a single optical fiber. Combination of sources and detectors form 24 channels across the animal brain. The sweeping rate over the entire brain is 5 Hz, and our Matlab-based software provides a real time, 2D topographic imaging with Gaussian interpolation. To ensure a stable contact between the optical fibers and the cranial window, we use a custom-built cap that fits tightly onto the mouse’s skull shape. For each mouse, a template mold of the skull is created then scanned, from which the custom-fitted cap is 3D printed. Each of the optical fibers are attached to the cap using ferrules and sleeves. As a result, the motion artifacts is significantly reduced even in freely moving situations. Also, we built a kit box, within which the entire behavior of the mouse can be monitored. The kit box is designed to deliver various stimuli to the mouse, such as visual and audio stimulation, and allows for real-time monitoring of the mouse activities using an infrared camera. Using our NIRS system, we show an increase of cerebral oxygenation in the visual cortex due to light stimulation and an increase of cerebral oxygenation in the auditory cortex due to ultrasound stimulation for awake and freely moving mice. We also build various obstacles for freely moving mice in our kit box to monitor cerebral hemodynamic changes according to various challenges.

Neuroscience Functional high-density speckle contrast optical tomography (fSCOT) of cerebral blood flow in small animal brain E. E. Vidal Rosasa, T. Dragojevica, J. L. Hollmana, J. P. Culverb,c , C. Justiciad,e and T. Durdurana,f a

ICFO-Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels, Barcelona, Spain b Department of Radiology, Washington University School of Medicine, MO 63110, USA c Department of Physics, Washington University, St. Louis, MO 63130, USA d Department of Brain Ischemia and Neurodegeneration, Insitut d'Investigacions Biomèdiques de Barcelona (IIBB), Consejo Superior de Investigaciones Científicas (CSIC), Spain e Àrea de Neurociències, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Spain f Institució Catalana de Recerca i Estudis Avançats (ICREA), 08015 Barcelona, Spain [email protected] Abstract: Noninvasive, high-density functional speckle contrast optical tomography (fSCOT) of cerebral blood flow (CBF) in rat brain is demonstrated. An increase of relative CBF due to electrical forepaw stimulation was resolved in depth. The reconstructed images were compared with corresponding magnetic resonance images (BOLD fMRI) demonstrating comparable location and spatial extent of the active area. Methods: The left and right forepaws were alternatingly electrically stimulated for 30 s followed by a 90 s recovery. Nine source positions were scanned by a two dimensional galvo-scanner, speckle contrast was calculated from images collected at 150 Hz with a camera in a non-contact fashion. 3D images of rCBF were obtained through a reconstruction algorithm [1,2]. Results: Fig. 1 shows example BOLD fMRI activation maps (a,d) and fSCOT rCBF (b,e) due to left (a,b) and right (c,d) forepaw stimulations, respectively. Results indicate that the location and spatial extent of the active area are comparable. Additionally, the depth profiles (c,f) demonstrates that the location of the maximum change occurs in the cortex layer and not in the overlying tissue. Fig. 1g shows rCBF averaged over all animals (n=5) including a sham group. Conclusion: The feasibility of High-density fSCOT has been demonstrated. Our results offer new possibilities to study CBF in small animals in a noninvasive and quantitative way. (b)

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Fig 1. Summary of findings, please see the text for details Acknowledgements Fundació CELLEX Barcelona, Ministerio de Economía y Competitividad/FEDER (PHOTODEMENTIA, DPI2015-64358-C2-1-R), Instituto de Salud Carlos III/FEDER (MEDPHOTAGE, DTS16/ 00087), “Severo

Ochoa” Programme for Centres of Excellence in R&D (SEV-2015-0522), Obra Social “la Caixa” Foundation (LlumMedBcn) References [1] Varma, H.M., et al. BOE. 5, 1275-89 (2014) [2] Dragojevic, T. et al. NeuroImage (2017)

Poster presentation

Saturday Oct. 6th, 2018

Poster I

2018年10月6日（土）

I-1 OntoNIRS: Can we automatize and optimize experiment design and analysis in NIRS neuroimaging for more rigorous interpretation?

F. Orihuela-Espinaa, A. A. Torres-Garcíaa, C. Cruz-Martíneza, L. Villaseñor-Pineda and F. Martínez-Santiagob Instituto Nacional de Astrofísica, Óptica y Electrónica, México b Universidad de Jaén, Spain Corresponding author e-mail address: [email protected] a

Abstract: Mathematically, valid interpretations are system inputs that support a given model (e.g. a research hypothesis) under experimental observations (system outputs). At times experimenters, using NIRS neuroimaging, approach experiment design and analysis (ED&A) empirically -decisions are guided by “experience” and not by strict statistical rigor- and perceive them as separate processes -decisions during design are later “forgotten” during analysis- with implications to interpretation. However, both experiment design and posterior data analysis have been formalized in statistics and demonstrated to be intertwined and optimizable. Further, it has been shown that at least in restricted domains the whole scientific process can be automatized capitalizing on ontologies of ED&A [1]. On these premises, can we automatize ED&A in NIRS neuroimaging to reach more rigorous interpretation? Methods: An ontology (OntoNIRS) (Figure 1a) has been developed to represent knowledge about NIRS neuroimaging ED&A [2] following ontology engineering approach Methontology. The new ontology builds on top of existing ontologies (STATO, EXPO and OBI) and resources (NCIT -thesaurus-, fNIRS.org -literature repository-) adding or refining concepts related to the monitoring of brain haemodynamics with diffuse optics. We present here an exercise, common in ontology engineering, whose aim is to evaluate the coverage of OntoNIRS. Two published experimental papers from different groups using NIRS neuroimaging were manually revised by an experienced researcher and relevant terms and design and analysis decisions were extracted and matched to formal statistics. Results. OntoNIRS successfully covered most terms (P1: TP =33, FP=1, FN=7; P2: TP=34 FP=1, y FN=6), and provided a framework for the expert to decide on the quality of the two examined papers (|TP(P1)TP(P2)|=17). As a result of this exercise, we were able to define a small set of formal operating (logical) rules that can be used for reasoning over the ontology (Figure 1b). Conclusions. Formalization of knowledge in ED&A for NIRS neuroimaging is feasible but content validity (FN>0) cannot yet be claimed demanding extension of the ontology. The exercise showed that OntoNIRS is useful to support human reasoning over ED&A quality, but automatic optimized reasoning over this formalization to reach formal interpretation remains to be shown. Acknowledgements. CONACYT CB-2014-01-237251 for funding. Prof. Karl Helmer for advice.

IF a balanced design is sought THEN hint: block randomization IF simple randomization was applied THEN a balanced design cannot be guaranteed. IF interoptode distance is fixed across channels THEN neuroimage corresponds to optical topography.

a) b) Figure 1. a) A view of OntoNIRS on Protegé. b) Exemplary rules derived. References: [1] King, Ross D., et al. (2009) Science 324(5923):85-89. [2] OntoNIRS. https://osf.io/gtqyc/.

I-2 The Effects of Binocular Disparity and Masking Type on unmasking: An fNIRS study Haibo Yanga, b, Hejun Liub, Peng Zhangb , Huan Zhangb, Liang Lic a

Academy of Psychology and Behavior, Tianjin Normal University, Tianjin 300074, China b College of Education Science, Tianjin Normal University, Tianjin 300387, China c School of Psychological and Cognitive Sciences, Peking University, Beijing 100080, China Corresponding author e-mail address: [email protected] Abstract: A visual search for targets is facilitated when the target objects are on a different depth plane than other masking objects cluttering the scene. This phenomenon is named binocular unmasking. The parietal-occipital cortices have been widely accepted in the processing of depth perception by many neuroimaging studies, while the neural mechanism of visual masking during binocular depth perception is still unclear. In the present, by using a block and within-subjects design, the oxy-hemoglobin (HbO) responses to binocular stimuli presented by a visual search task were recorded over the whole visual dorsal area. Twenty typically developing adults (mean age: 22.5±1.67) participated in this study with normal or corrected-to-normal visual acuity while their brain activities were examined using a 31channel, functional near infrared spectroscopy (fNIRS)-based scanning. Each adult completed 8 trials across six conditions (3masker types x 2disparity types) represented in a random order, and each block continued for 20 seconds, and repeated for five times. Spatial registration methods were applied to localize the cortical regions underneath each channel and to define two regions of interest (ROIs), Visual primary sensory area(V1), and Visual association cortex(V2) regions.The RTs results showed that: Performance improved with target duration when there exists binocular disparity between target letter plane and lettermasker plane, but not when the target letters were on the same plane as the masker. Besides, the amount of unmasking from the pixel masker to the letter fragment masker, the letter masker is increased in turn. The imaging results showed that: Results from pair-sample t test showed that among different masker condition, the strength and regions of activation between non-zero disparity and disparity session are different to some extent. The majority of the ROIs were more active during pixel and fragment compared to letter. Performance was no significantly difference between letter and fragment masker, suggesting that the informational masking was reduced at the pre-orthographic processing stage. Besides, the difference in cortical activation between zero disparity and non-zero disparity among different type of maskers suggest that brain region of V1 and V2 may be involved in the integration of visual masking and binocular depth perception. Keywords: binocular depth perception, visual research, masking, functional near infrared spectroscopy (fNIRS), parietal-occipital cortices References: Gao, Y. Y., Schneider, B., & Li, L. (2016). The effects of the binocular disparity differences between targets and maskers on visual search. Attention Perception & Psychophysics, 79(2), 1-14. Wardle, S. G., Cass, J., Brooks, K. R., & Alais, D. (2010). Breaking camouflage: binocular disparity reduces contrast masking in natural images. Journal of Vision, 10(14), 71-76. Wijeakumar, S., Shahani, U., Simpson, W. A., & Mcculloch, D. L. (2012). Localization of hemodynamic responses to simple visual stimulation: an fnirs study. Investigative Ophthalmology & Visual Science, 53(4), 2266-73.

I-3 Same processing costs for encoding sameness and difference in the developing brain: An fNIRS study with 6-7-month-olds Silvia Rădulescu (Utrecht University), Sergey Avrutin (Utrecht University), Frank Wijnen (Utrecht University), Judit Gervain (CNRS Paris) [email protected] Introduction. How does encoding of linguistic regularities such as identity (e.g. ABB “wo fe fe”) develop in infancy? Previous research suggested different cognitive mechanisms, such as perceptual identity detection (Endress et al. 2007) and abstract rule learning (Marcus et al. 1999) to account for the encoding of repetition-based regularities. The nature, the developmental trajectory and the neural correlates of these mechanisms remain heatedly debated. Here we tested whether and how 6-month-old infants, never tested before in such tasks, are able to discriminate repetition-based linguistic regularities (ABB, e.g. “bu ra ra”) from random controls (ABC, e.g. “bu fa zo”). Methods. In an fNIRS study, 6-7-month-old infants (n=21) were exposed to a low complexity grammar (9 ABBs & 9 ABCs, 2x) and a higher complexity grammar (18 ABBs & 18 ABCs, 1x). In a simple block design, infants were exposed sequentially to both grammars in a balanced order. We used a NIRx NIRScout 8-8 system with a source-detector separation of 3cm, using two continuous wavelengths of 695nm and 830nm. The channels were overlaid on the temporal, parietal and frontal areas. Results. The channel-wise t-tests revealed significant activation compared to baseline for both the ABC and ABB conditions in channels 2, 6, 14, and 17. However, overall there was no significant difference between ABB and ABC conditions, or between low and high complexity stimuli (Figure 1). Discussion. These results suggest that both repetition and non-repetition patterns were being processed, but there was no significant difference in processing costs between them. In contrast to findings that showed different activation for repetition vs non-repetition grammars in newborns (Gervain et al. 2008), our results show similar processing demands for encoding both repetition/sameness and difference. This might point to a cognitive developmental change in rule learning between birth and 6 months when the encoding of difference comes online.

Figure 1. The NIRS responses obtained in the 4 experimental conditions. The x axis represents time in seconds, the y axis concentration change in mmol x mm. Legends: N: no repetition (ABC), R: repetition (ABB), L: low complexity, H: high complexity, O: oxyHb, D: deoxyHb

I-4 Verifying Wavelet coherence analysis on fNIRS data using pseudorandom visual stimulation sequence X. Zhanga*, J. A. Noaha, S. Dravidab , Y. Onoa,d, and J. Hirscha,c,e,f Department of Psychiatry, Yale School of Medicine, USA Neuroscience Program, Yale School of Medicine, USA c Department of Neuroscience, Yale School of Medicine, USA d Department of Electronics and Bioinformatics, Meiji University, Japan e Department of Comparative Medicine, Yale School of Medicine, USA f Department of Medical Physics and Biomedical Engineering, University College London, UK *Corresponding author e-mail address: [email protected] a

b Interdepartmental

Neural mechanisms that underlie dynamic interpersonal interactions are thought to include temporally synchronous signals that reflect coupled processes between two brains [1]. Wavelet coherence analysis of hemodynamic signals acquired simultaneously during hyper-scanning experiments has been proposed for analysis of these neural processes [2,3]. However, this computational approach has not been validated against known markers. Here we generate a set of known neural coherences using pseudo random sequences of reversing checkerboard patterns. It is expected that input sequences that were more highly correlated generated higher cross-brain output correlations of wavelets in the visual cortex across pairs of subjects. Each visual stimulus event was a 2-second full-field reversing checkerboard pattern. Three random sequences, called sequence A, B and C (inset in figure), of such visual stimuli were presented for 2 minutes and repeated twice. The sequences were generated to have varying levels of correlation (e g: A-B more correlated than A-C). The expected coherence (left panel) was obtained by coherence analysis on the modeled fNIRS waveform, which was generated by convolving the stimulus sequence and the hemodynamic response function (HRF).The overall expected coherence is summarized as the average coherence within 0-30 second wavelength range (horizontal lines and numbers in left panel). Ten subjects participated. Subject’s data were randomly paired with every other subject’s data, resulting in ninety possible pairs. The combinations included A-A, B-B, or C-C, where both subjects viewed identical sequences of the stimuli (green). The other pairings were AB (red), A-C (blue) and B-C (cyan). The wavelet coherence results from measured fNIRS deOxyHB data (right panel) confirmed the expected coherence. Our results validate wavelet coherence as a technique for quanitfying the The wavelet coherence vs the wavelet wavelength for coherence of brain signals across participants the expected waveforms (left) and the measured during hyperscanning to study social interaction fNRIS deOxyHB signals (right) in ecologically valid paradigms. References 1. Hasson, Uri, and Chris D. Frith. "Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions." Phil. Trans. R. Soc. B 371, no. 1693 (2016): 20150366.

2. Cui, Xu, Daniel M. Bryant, and Allan L. Reiss. "NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation." Neuroimage 59, no. 3 (2012): 2430-2437. 3. Jiang, Jing, Chuansheng Chen, Bohan Dai, Guang Shi, Guosheng Ding, Li Liu, and Chunming Lu. "Leader emergence through interpersonal neural synchronization." Proceedings of the National Academy of Sciences 112, no. 14 (2015): 4274-4279.

I-5 Incorporating neural reliability measures to isolate functional connectivity differences across populations S. Jaffe-Daxa, M. Gayleb, and L. L. Embersona a

Psychology Department, Princeton University, USA b Spelman College, USA [email protected]

Cortical connectivity supports the development of broad cognitive aptitudes and skills, from perception to language to social behavior. Moreover, atypical development (e.g., of preterm infants) is often associated with impaired connectivity. It is thus important to be able to measure connectivity and compare across populations reliably. When measured by functional connectivity (FC), long-range connectivity is difficult to compare across populations where neural noise levels may vary. Specifically, greater neural noise in individual neural regions leads to lower reliability in the neural response which will appear as diminished connectivity. Thus, the comparison of functional connectivity across populations is difficult because of possible differences in the reliability of the univariate, localized neural responses. Here, we combine representational decoding (to quantify neural reliability) with functional connectivity to better isolate long-range connectivity from other population differences. This study is the first to apply this approach using fNIRS. This technique allows us to conduct recordings with actively perceiving infants and present the first comparison of representational similarity and functional connectivity between infants and adults. We use a broad coverage fNIRS recording in adults (139 channels, LABNIRS, Shimadzu) and in infants (74 channels). Neural reliability or noise is quantified through Representation Similarity Analysis (RSA;[1]). Participants watch a set of video clips of animate and inanimate scenes. Using a large multichannel fNIRS array, we decode neural responses between categories (animate vs. inanimate) and compare the pattern similarity within-category to the pattern dissimilarity between-category. The decoding accuracy for the perceived stimulus and correspondence between the stimulus space (animate vs. inanimate), and fNIRS patterns quantify the reliability of neural representation. Preliminary results from adults reveal stronger similarity within each category than between the categories of stimuli. Data collection is ongoing with infants but we hypothesize that while the RSA (i.e., the ability to decode responses across stimulus categories) across infants and adults will be comparable, FC values will differ. Overall, this approach gives us a tool to compare neural reliability and will allow us to determine specific functional connectivity differences when comparing across populations. Figure 1. Schematic illustration of the two methods that are used in this study. Whole-cortex fNIRS was recorded from infants and adults watching short audio-visual clips of animals and vehicles. Functional Connectivity (FC) and neural reliability was calculated based on the same data set. References 1.

Kriegeskorte, N., Mur, M., Ruff, D.A., Kiani, R., Bodurka, J., Esteky, H., Tanaka, K., and Bandettini, P.A. (2008). Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey. Neuron 60, 1126–1141.

I-6 Investigating Spatial Specificity Between Channels of Functional Near-infrared Spectroscopy

Ho-Ching Yanga, Zhenhu Lianga,b, Xiaopeng Zhouc, Yunjie Tonga

Weldon School of Biomedical Engineering, Purdue University, West Lafayette, US Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China c School of Health Sciences, Purdue University, West Lafayette, US a

b

[email protected] Motivation: Functional near infrared spectroscopy (fNIRS) is one of the popular imaging technique with high temporal resolution and high mobility.[1] However, one of problems for fNIRS comes from its low spatial resolution.[2] In this study, we addressed the question about the spatial specificity of different NIRS channels placed in the prefrontal region in resting state (RS) using concurrent fMRI (Siemens 3T Prisma at Purdue MRI Center).[3] Methods: We conducted concurrent fNIRS/ fMRI studies during RS and use fMRI data with high spatial resolution to assess the spatial specificity of each NIRS channel. Three subjects (males, age=31; SD=12.4) data were analyzed. Each subject underwent a 10 minutes concurrent RS fMRI and fNIRS scan. The NIRS probes were placed on subject’s forehead and right ear (Fig. 1a). RS fMRI and fNIRS data were preprocessed by FSL and NIRS Lab separately. After preprocessing, a band pass filter (0.01-0.1Hz) was applied on BOLD signal from fMRI and oxy-hemoglobin (HbO) signal from fNIRS. For each subject, fMRI signals from all the voxels in the brain were correlated with HbO from each NIRS channels (from prefrontal cortex and right ear). For each NIRS channel, a correlation map was generated with certain threshold (>0.3). Lastly, the spatial relations between these correlation maps were assessed using fslcc from FSL. Results: Our result revealed that: 1) the correlation patterns of some NIRS channels are similar which matches the high temporal correlations between these channels (Fig.1c-d); 2) the correlation patterns of some NIRS channels are “global”, while some are “regional”, indicating the different signal component in each NIRS channel. The results illustrated the importance of understanding the anatomy of the brain region being studied by NIRS. Carefully selected positions of NIRS channels will: 1) increase spatial specificity and 2) catch global noise to be used in denoising.

Figure1. a) Configuration of fNIRS sources (red), detector (blue) and channels (circled number). b) Correlation patterns of channel 9 (upper panel) and channel 16 (down panel). c) Spatial correlation between channels’ correlation patterns. d) Correlation coefficients between NIRS channels’ temporal series.

1. Strangman, G., et al., A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation. Neuroimage, 2002. 17(2): p. 719-731. 2. Wijeakumar, S., et al., Validating an image-based fNIRS approach with fMRI and a working memory task. NeuroImage, 2017. 147: p. 204-218. 3. Sasai, S., et al., A NIRS–fMRI study of resting state network. Neuroimage, 2012. 63(1): p. 179-193.

I-7 Predictability modulates response amplitude and boosts background connectivity in infants and in adults S. Jaffe-Daxa, I. N. Trevesb, V. R. Bejjankic and L. L. Embersona a

b

Psychology Department, Princeton University, USA Princeton Neuroscience Institute, Princeton University, USA c Department of Psychology, Hamilton College, USA [email protected]

While predictions allow infants to orient their attention towards surprising events and facilitates learning, little is known about how predictions manifest in the developing brain. In adults, it is believed that predictions involve top-down modulation to compare sensory input against the prediction. Similar to what is found in adults, recent work has suggested that prediction-related neural activity is evident in sensory cortices in infancy. However, these previous studies were limited in their cortical coverage and spatial separation and were not able to compare directly between infants and adults on the same task. Here, we investigate prediction-related processing in both infants and adults using a broad cortex coverage fNIRS system (infants: 74 channels, adults: 139 channels, Shimadzu LABNIRS). We recruited 30 typically-developing full-term infants at 6 months and 30 adults. We measured infants’ and adults’ cortical response in two conditions: Predictable and Unpredictable. In the Predictable condition, the temporal order of audiovisual stimuli was constant across trials, while in the Unpredictable condition, the temporal order of audiovisual stimuli varied from trial-to-trial. Thus, in the Predictable condition, once the temporal pattern is learned, the subject would be able to predict which stimulus should appear next. Such prediction will be impossible in the Unpredictable condition. We found that in the Unpredictable condition infants had a higher level of neural response amplitude in both frontal and posterior (occipital and temporal) regions than in the Predictable condition (Fig. 1A), and that this difference in adults was restricted to the frontal cortex (Fig. 1B). After removing the contribution of event-related activity from the measured oxy-Hb signal, we calculated the correlation between the residual of the signal from each lobe. This analysis revealed the background functional connectivity of each condition (Predictable vs. Unpredictable). While the amplitude or univariate effects indicate differences across these populations, investigations of background connectivity suggest similarities. We found greater background connectivity between the parietal and frontal regions in the Predictable versus Unpredictable condition for both populations. Taken together, our results suggest that prediction supports learning in early sensory cortices in infancy through top-down modulation from the frontal cortex. Comparisons with adults are inconsistent: Univariate findings suggest different neural responses to prediction and patterns we did not hypothesize. However, background connectivity analyses suggest similarity across the populations and are consistent with the hypotheses. One possibility for these univariate differences across populations is that the task is optimized for infants (e.g., long stimulus presentations of simple stimuli with obvious consistency) and could be too simple for adults, who might explicitly verbalize the predictability of events. A. B.

Figure 1. Oxy-Hb t-contrast Unpredictable > Predictable. A. Infants at 6 months old. B. Adults.

I-8 An fNIRS screening procedure to determine compatibility for neuroimaging studies J.A. Noaha*, M.S. Kelleyb, S. Dravidab, Y. Onoa,c, X. Zhanga and J. Hirscha,d,e,f a Department

of Psychiatry, Yale School of Medicine, USA Neuroscience Program, Yale School of Medicine, USA c Department of Electronics and Bioinformatics, Meiji University, Japan d Department of Neuroscience, Yale School of Medicine, USA e Department of Comparative Medicine, Yale School of Medicine, USA f Department of Medical Physics and Biomedical Engineering, University College London, UK *Corresponding author e-mail address: [email protected] b Interdepartmental

Background: It is well known that participants in fNIRS experiments vary with respect to strength of endogenous signals. The reasons for this are likely rooted in anatomical factors such as bone thickness, bone density, fat deposits or other structures that do not allow the path of emitted near infrared light to be detected. Numerous techniques have been developed to filter out systemic and superficial artifacts1,2. Currently there is no standard method to determine if a potential subject will generate fNIRS signals. While filtering systemic artifact is best practice to assure neural origin of signals, it is also necessary to determine if subjects are compatible with fNIRS, i.e. show a hemodynamic response to a fiducial task. A complementary solution to systemic artifact removal is a screening procedure to assure all subjects in a study are indeed compatible with fNIRS. Aim and Hypothesis: The goal in this study was to develop a screening procedure to determine if a subject is compatible with fNIRS prior to participation in tasks that are complex or without known responses. Methods: 128 participants performed a 3 minute finger-thumb tapping procedure using a Shimadzu LABNIRS with 40 pairs of optodes providing full head coverage. An optimization curve was generated in which subjects were ordered in rank from least significant to most significant activity in a channel showing the largest hemodynamic response in the motor area. Criteria selection for a positive response was based on the highest t-value for the group when at least one channel met the statistical criteria of p≤0.0165 for both Oxy- and DeOxyHb signals. Subjects were removed sequentially in rank to determine group effects in the pre-determined region of interest, left motor cortex. Results: Figure 1 shows the results of the screening procedure comparing all subjects (left column) vs the compatible (right) and incompatible subjects (center). While the 128 subject All group shows a fiducial response, it is reduced due to the addition of the signals from the 25 incompatible subjects.

Figure 1. Results of screening procedure comparing all, not eligible and eligible subjects

Conclusion: The results of this experiment show that it is not only important to filter systemic noise, but also to remove subjects on whom hemodynamic signals cannot be detected using fNIRS. We suggest this simple method can be used prior to other experiments to best optimize results and exclude subjects that may be fNIRS incompatible due to various anatomical and physiological characteristics.

References: 1. Tachtsidis, I. and Scholkmann, F., 2016. Neurophotonics, 3(3), p.031405. 2. Zhang, X., Noah, J.A. and Hirsch, J., 2016. Neurophotonics, 3(1), p.015004.

I-9 Impact of blood glucose variability on the very preterm neonatal brain: Preliminary results S. Brigadoia, A. Galderisib, R.J. Cooperc,d, S. Cutinia,e, E. Baraldib, C. Cobellif, R. Dell’Acquaa,e and D. Trevisanutob a

b

Department of Developmental Psychology, University of Padova, Padova, Italy Neonatal Intensive Care Unit, Department of Woman’s and Child’s Health, University of Padova, Padova, Italy c Department of Medical Physics and Biomedical Engineering, UCL, London, UK d neoLAB, The Evelyn Perinatal Imaging Centre, Rosie Hospital, Cambridge, UK e Padua Neuroscience Center, University of Padova, Padova, Italy f Department of Information Engineering, University of Padova, Padova, Italy Corresponding author e-mail address: [email protected]

Abstract: Preterm neonates are at high risk of hypo- and/or hyperglycemic episodes during the first week post-partum. Both hypo- and hyperglycemic episodes have been associated with increased mortality and exposure to cognitive and neurological deficits, mostly located in the occipital and parietal cortex, but with contradictory results. Previous studies demonstrated a relationship between glucose values and cerebral blood flow in preterm infants, and hypothesized the presence of a cerebral glucose sensor1. Continuous glucose monitoring (CGM) is a promising tool to reduce glycemic variability in the preterm population2, providing real-time data to continuously adjust glucose intakes and deliver prompt correction of hypoglycemia. The impact of tight glycemic control on brain development and long-term outcome is however still unknown. Diffuse Optical Tomography (DOT) is the most suitable neuroimaging technique to shed light on this question, providing regionally specific information on oxy-(HbO) and deoxyhemoglobin (HbR) changes in relation to glycemic variability. Methods: In a first of its kind pilot study, a neonate admitted to the NICU at the University Hospital of Padova, born at 28 weeks gestation (birthweight: 1145 g, head circumference: 26.5 cm) was enrolled for the study. The neonate was monitored from the 48th hour of life continuously for 7 days, with the combined use of a CGM device inserted in the thigh and a DOT cap. DOT data were acquired with a multichannel continuous-wave system over the whole head (105 channels)3. Results/Discussion: Nine hypo- (144 mg/dL) episodes were identified during the 7 days monitoring period. Glucose values Fig. 1. Relation between glycemic were positively related with both HbO and total values and HbO/HbR/CBV changes hemoglobin (HbT) and negatively with HbR only when during the hypo/hyperglycemic looking at channels in the centro-parietal areas (Fig. 1). episodes. CBV = Cerebral Blood Our preliminary results suggest that DOT and CGM has Volume ≈ HbT. Hemodynamic changes the potential to investigate the effect of glycemic changes were measured relative to the previous euglycemic period. on brain oxygenation. 1

Skov & Pryds, Pediatrics 90(2), 1992; 2Galderisi et al., Pediatrics 140, 2017; 3Galderisi, Brigadoi et al., Neurophotonics 3, 2016.

I-10 Removal of Extracerebral Activity Improves Signal Quality and Channel Specificity in a Motor Imagery Neurofeedback Paradigm

Franziska Klein a, Ling-Chia Chen a, Cornelia Kranczioch a,b

a

Neuropsychology Lab, Department of Psychology, University of Oldenburg, Oldenburg, Germany. b Research Center Neurosensory Science, University of Oldenburg, 26111 Oldenburg, Germany

Corresponding author e-mail address: [email protected] In motor imagery neurofeedback (MI NFB), brain activity associated with imagining a motor task is fed back on a single trial level to the person performing the MI. For online NFB it is therefore of particular interest to have clean data to prevent feeding back noise instead of brain-related data. However, conventional filtering methods are not able to completely eliminate the frequencies overlapping with the task frequency, e.g. respiration and slow frequency waves. Moreover, the data is typically contaminated with task-related extracerebral activity. To accurately remove such a global component (GC) from the data short-distance channels can be applied. Short-distance channels are not standard yet, therefore alternative methods should be considered. Here we aimed to quantify the effects of conventional online bandpass filtering (BP) and the more elaborated methods of wavelet MDL detrending filtering (WL, NIRS_SPM toolbox; [1]) and WL in combination with a GC removal, a method that combines Singular Value Decomposition with a Gaussian kernel smoother (WLGC; [2]) on signal quality, channel specificity and statistical results. In total, 50 data sets were analyzed, including motor execution before and after a period of MI training with and without NFB. For the offline analysis, for BP, the same bandbass filter was used as for online NFB. WL and WLGC were only applied offline. We expected an improvement of the signal quality from BP to WL to WLGC. Furthermore, statistical effects were expected to diminish from BP to WL to WLGC [3]. The results indicated a significant improvement of data quality from BP to WL to WLGC. As expected, statistical effects decreased strongly from BP to WL to WLGC. Furthermore, the channel selected for online NFB based on BP filtered data differed for a number of participants from the channel that would have been chosen based on WL or WLGC cleaned data. This suggests that for those subjects, online channel selection was suboptimal, and that the feedback was contaminated by noise. The overall results strongly underline the importance of appropriate means to deal with noise also in online setups either through the addition of shortdistance channels or an appropriate statistical correction method. References: [1] Jang, K.E., Tak, S., Jung, J., Jang, J., Jeong, Y., & Ye, J.C. (2009). Wavelet minimum description length detrending for near-infrared spectroscopy. Journal of biomedical optics, 14(3), 034004. doi: 10.1117/1.3127204 [2] Zhang, X., Noah, J. A., & Hirsch, J. (2016). Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering. Neurophotonics, 3(1), 015004. doi: 10.1117/1.NPh.3.1.015004 [3] Pfeifer, M.D., Scholkmann, F., & Labruére, R. (2018). Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results. Frontiers in human neuroscience, 11. doi: 10.3389/fnhum.2017.00641

I-11 Multi-distance, multi-exposure, functional speckle contrast optical spectroscopy (fSCOS) of the adult brain T. Dragojevića, E.E.Vidal-Rosasa, J.L.Hollmanna, J.P.Culverb,c, F. Zappad and T.Durdurana,e a

ICFO - Institut de Ciencies Fotoniques, Av. Carl Friedrich Gauss, 3, 08860, Castelldefels, Barcelona, Spain; bDepartment of Radiology, Washington University School of Medicine,St. Louis, USA; cDepartment of Physics, Washington University, St. Louis, USA; dPOLIMI Politecnico di Milano - Dip. Elettronica Informazione e Bioingegneria, Milano, Italy; eInstitucio Catalana de Recerca i Estudis Avancats (ICREA), Barcelona, Spain [email protected] Introduction: Speckle contrast optical spectroscopy (SCOS) exploits multi-exposure and/or multi-distance approach to measure deep tissue blood flow [1, 2]. In earlier implementations, we have shown single exposure time, multi-distance SCOS in vivo as a proof-of-principle [1] and later, we have developed a single source-detector separation, multi-exposure device and a method for the measurement of cerebral blood flow (CBF) in the adult brain [2]. Here we introduce multi-distance, multi-exposure functional SCOS (fSCOS) using single-shot acquisition multi-exposure speckle imaging (sMESI) with a two-dimensional single photon avalanche photodiode (SPAD). This allows for the implementation of methods for the removal of the extra-cerebral contributions and high-density tomography. Methods: A custom SPAD array (64 by 32 pixels) with a high-frame rate was developed for effective sMESI acquisition as a non-contact imager. We have used a two-dimensional scanning system to place source in the corner of the field-of-view on the forehead of the subjects. For the initial study, the subjects were asked to perform a math test for one minute after a three minute baseline. The protocol was repeated three times. Results: Fig. 1 shows averaged rCBF at two distances (5 and 25 mm) during the math test. The error bars are standard error of the mean over three repetitions from one subject.

Fig. 1: Relative cerebral blood flow change during the math test averaged over all repetitions for two different distances. Conclusion: We will present the group averaged results from the subjects and initial results of high-density speckle contrast optical tomography. Acknowledgements: Fundació CELLEX Barcelona, Ministerio de Economía y Competitividad FEDER (PHOTODEMENTIA, DPI2015-64358-C2-1-R), Instituto de Salud Carlos III / FEDER (MEDPHOTAGE, DTS16/00087), the “Severo Ochoa” Programme for Centres of Excellence in R&D (SEV-2015-0522), the Obra social “la Caixa” Foundation (LlumMedBcn) References: 1. Valdes, et.al. BOE, 2014. 2. Dragojević, et.al. BOE, 2018.

I-12 Removing extra-cerebral signal contamination for Brain fNIRS studies using Frequency Domain multi-distance measurements Joshua Deepak Veesa, Hamid Dehghani School of Computer Science, University of Birmingham, Birmingham, B15 2TT, U.K. Corresponding author e-mail address: [email protected] Abstract: Functional Near-Infrared spectroscopy (fNIRS) allows the observation of the hemodynamic changes in the human brain by analyzing the transmission of NIR light through tissue. This fNIRS signal is known to be contaminated by the systemic interference occurring in the extra-cerebral tissue of the head, hindering the accurate recovery of brain related changes. Frequency Domain (FD) fNIRS measures both the attenuation of modulated light and its phase shift due to propagation through tissue and it has been shown that this phase varies significantly with the haemodynamics of the tissue, along with attenuation data [1]. Several methods have been proposed to use measurements at multiple source-detector separations to allow implementation of a short-separation signal regression assuming that these short distance data only sample the extra-cerebral tissue [2]. Here, the application of modelled based regional sensitivities/Jacobians [3] to separate the hemodynamics of cerebral and extra-cerebral tissue based on FD fNIRS data is presented. A study is shown in Fig.1 where the data is modelled [4] for a probe geometry similar to ISS OxiplexTSTM system (source-detector distances: 20, 25, 30, 35 mm and wavelengths: 690 and 830 nm) on a three-layered model (skin, skull and brain) with different superficial layer thicknesses (skin: 2 to 6 mm, and skull: 4 to 8 mm). The changes in hemoglobin levels of skin and brain are modelled differently (Fig.1) to clearly observe any possible cross-talk in recovery of the brain specific data. By using regional Jacobians (generated on a different model to avoid inverse crime) it is shown that the hemoglobin changes in all layers can be recovered qualitatively and quantitatively using this FD device. The results indicate that this system, without any further instrumentational changes, but with appropriate use of parameter recovery algorithm is superior to other more advanced fNIRS systems. This highlights the importance of model based parameter recovery in fNIRS.

(a)

(b)

(c)

(d)

Fig.1. Hemoglobin changes: (--) modelled change, (—) recovered change in (a) skin oxy-hemoglobin, (b) skin deoxy-hemoglobin, (c) brain oxy-hemoglobin, (d) brain deoxy-hemoglobin. Error-bars show the standarddeviation of recovery across various combinations of skin and skull thicknesses.

Acknowledgements: This project has received funding from the European Union's Horizon 2020 Marie Sklodowska-Curie Innovative Training Networks (ITN-ETN) programme, under grant agreement no 675332, BitMap. References: [1] V. Toronov, A. Webb, J. H. Choi, M. Wolf, L. Safonova, U. Wolf and E. Gratton, Optics Express, vol. 9, no. 8, pp. 417-427, 2001. [2] R. B. Saager, N. L. Telleri and A. J. Berger, NeuroImage, vol. 55, pp. 1679-1685, 2011. [3] H. Dehghani, B. W. Pogue, J. Shudong, B. Brooksby and K. D. Paulsen, Applied Optics, vol. 42, no. 16, pp. 3117-3128, 2003. [4] H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, M. C. Carpenter, B. W. Pogue and K. D. Paulsen, Communications in numerical methods in engineering, vol. 25, pp. 711-732, 2008.

I-13 The detection of repetition-based regularities from visual input at 6 months of age Judit Gervain1,2, Irene de la Cruz-Pavía1,2, Iris Berent3 [email protected] 1 Laboratoire Psychologie de la Perception, CNRS, Paris, France 2 Laboratoire Psychologie de la Perception, Université Paris Descartes, Paris, France 3 College of Science, Northeastern University, Boston, MA, USA

The experiment consisted of 8 block ditions (consistent, inconsistent, no c the presentation of 6 tone pairs, for a were spaced by silent time intervals 32 s) to avoid inducing phase-locked b 8–12 s. Within blocks, tone pairs were (480 ms), yielding blocks of about 8–12 sented in an interleaved fashion in such than two consecutive blocks of the sam the blocks was randomized and counter

2.1.3. Procedure Infants were tested with a NIRx NIRS detector separation: 3 cm; two wav 850 nm; sampling rate: approximately ward of the Robert Debré Hospital, Par sion lasted about 16–17 min. The opti

Introduction. Infants’ ability to learn regularities related to repetitions in linguistic sequences (e.g. ABB: “wo fe fe”) has received considerable attention since Marcus et al.’s (1999) first showed that 7-month-olds can generalize different linguistic rules based on these patterns (e.g. ABB vs. ABA). But whether this capacity is specific to speech or whether it also extends sign language is unclear (Rabagliati et al., 2012). Its neural correlates also remain only partly understood.

N. Abboub et al. / Brain & Language 162 (2016) 46–59

1

No Repetition

Repetition

Methods. Here, we used NIRS to investigate whether 6-month-old infants, never exposed to Sign sign language, were able to extract repetitionbased regularities from visual stimuli. In Experiment 1, infants were presented with 6 sequences of two novel disyllabic signs in each Non-
 block, for a total of seven blocks per condition, Sign in two conditions: in the repetition condition (AA), the signs were identical, in the control conditions (AB), they were No Repetition 3 Repetition different (Figure 1). In Experiment12, still underway, replaced No Repetition signs were Repetition 1 by visual analogues, matched for spatiotemporal properties (Figure 1). Sign We measured infants’ brain responses in the bilateral temporal, parietal Sign and frontal areas using a NIRx NIRScout system (Figure 2 – Exp 1: 12 channels/hemisphere, Exp 2: 10 channels/hemisphere). Blocks with artifacts in the signal or when infants were not attending to the stimuli NonNonSign were discarded. We averaged responses across the remaining blocks Sign * * of each condition. Results & Discussion. Preliminary results suggest that infants showed discrimination between the AA and AB patterns in both experiments. Remarkably, though, the effect of repetition differed in the two experiments. While signs elicited greater activation to AA relative to AB sequences (Figure 3), visual analogs elicited the opposite pattern (Figure 4). These results suggest that linguistic visual stimuli may be processed differently from other visual input.

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The experiment consisted of 8 blocks of each of the three conon newborns’ heads targeting the fronto ditions (consistent, inconsistent, no contrast), each comprising tory areas. The optical sensors were inse N. Abboub et al. / Brain & Language 162 (2016) 46–59 the presentation of 6 tone pairs, for a total of 24 blocks. Blocks cap and were placed bilaterally on the in were spaced by silent time intervals of varying duration (26– Fig. anatomical landmarks (inion, nasion, 2. (A) Picture of a neonate with the cap placv The experiment consisted of 8 blocks of each of the three conon newborns’ heads targeting the fronto-te in the probe setsee are projected 32 s) to avoid inducing phase-locked brain responses and lasted channels preauricular points; Fig. 2). down from ditions (consistent, inconsistent, no contrast), each comprising tory areas. The optical sensors were inserted 8–12 s. Within blocks, tone pairs were also separated by pauses We approximated the location of the co the presentation of 6 tone pairs, for a total of 24 blocks. Blocks cap and were placed bilaterally on the infant (480 ms), yielding of about 8–12 s. 24 blocks were(26– preour NIRS channels following procedur were spaced by blocks silent time intervals ofThe varying duration anatomical landmarks (inion, the nasion, vert sented interleaved in suchbrain a way as to disallow more et al. (2014), using age-appropriate, 32 s) in to an avoid inducingfashion phase-locked responses and lasted preauricular points; seeof Fig. 2). than two consecutive blocks of thewere same condition. The MRIs and stereotaxic et 8–12 s. Within blocks, tone pairs also separated by order pausesof We approximated the atlases locationfrom of theShi cortic the blocks randomized counterbalanced acrosswere subjects. localization analysis suggests that on a (480 ms),was yielding blocks ofand about 8–12 s. The 24 blocks preour NIRS channels following the procedure d in the LH andofchannels 13, 14, 15i.e. an sented in an interleaved fashion in such a way as to disallow more etand al. 5(2014), using age-appropriate, tioned over the inferior-middle thanProcedure two consecutive blocks of the same condition. The order of MRIs and stereotaxic atlases fromfrontal Shi etare al. 2.1.3. and 17, 19,analysis 22 and suggests 24 were that mostly the blocks wastested randomized counterbalanced across subjects. localization on posit aver Infants were with aand NIRx NIRScout 816 machine (sourcelobe including the superior middle and 5 in the LH and channels 13,and 14, 15 and 1 detector separation: 3 cm; two wavelengths of 760 nm and tioned over7, the area, channels 9, inferior-middle 10 and 12, and frontal channels 18,C 2.1.3. 850 nm;Procedure sampling rate: approximately 10 Hz) at the maternity and 17,located 19, 22 and were mostly position often over24 the central gyrus, supr tested with a NIRx NIRScout 816 machine (sourcewardInfants of the were Robert Debré Hospital, Paris, France. The testing seslobe including the superior and middle te detector separation: 3 cm; two wavelengths of 760 nm and angular gyrus (see Fig. 3). Given the high sion lasted about 16–17 min. The optical probe cap was placed channels 7, 9, 10 and 12, and channels 18, 20, 850 nm; sampling rate: approximately 10 Hz) at the maternity often located over the central gyrus, supram ward of the Robert Debré Hospital, Paris, France. The testing sesangular gyrus (see Fig. 3). Given the high va sion lasted about 16–17 min. The optical probe cap was placed

Fig. 2. (A) Picture of a neonate with the cap placed upon the head (right view), (B), A scalp surface from MRI neonate templates (Shi et al., channels in the probe set are projected down from the scalp surface to the cortical surface. Red circles indicate sources, while write circles

Fig. 2. (A) Picture of a neonate with the cap placed upon the head (right view), (B), A scalp surface from MRI neonate templates (Shi et al., 201 channels in the probe set are projected down from the scalp surface to the cortical surface. Red circles indicate sources, while write circles indi

Fig. 3. Configuration of probe sets overlaid on a (using the LPBA40 atlas) is illustrated according to parietal area and the purple over the temporal ar

2 2

* *

*

Fig. 3. Configuration of probe sets overlaid on a schematic newborn brain. For each fNIRS channel located within this probe set, the identi Fig. 3. Configuration of probe sets overlaid on a schematic newborn brain. For each fNIRS channel located within this probe set, the identity of (using the LPBA40 atlas) is illustrated according to their localization. The blue channels indicate the position of the probe over the frontal are (using the LPBA40 atlas) is illustrated according to their localization. The blue channels indicate the position of the probe over the frontal area, th parietal area and the purple over the temporal area on the infant head. Grey circles indicate sources, while black circles indicate detectors. parietal area and the purple over the temporal area on the infant head. Grey circles indicate sources, while black circles indicate detectors.

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I-14 Comparison of Kernels in Online SVM Classification of fNIRS Data Ruisen Huanga, Ho-Ryong Yoob and Keum-Shik Honga a

School of Mechanical Engineering, Pusan National University, Busan 46241, bNeurology Disorder Center, Dunsan Korean Medicine Hospital, Daejeon University, Daejeon 35235, Republic of Korea [email protected]

Abstract: Objective: Support vector machine (SVM) is widely used in brain signal classification[1], but the optimized kernel for SVM remains unknown yet. Method: We have investigated the brain signals collected from 8 healthy subjects. The signal was collected by functional near-infrared spectroscopy (fNIRS) from the prefrontal cortex. The subjects were asked to perform the mental arithmetic (AR) and mental counting (MC) tasks[2]. Slope (approximated by least square regression), mean, variance, maximum and minimum features were extracted from each channel and SVM was finally used for binary and multi-class classification tasks. Several different kernels including linear, Gaussian, polynomial, etc. were tested in this process. Results and discussion: The classification rates vary enormously from kernel to kernel. Parameters such as the standard deviation in a Gaussian kernel and the 0 order term in a polynomial kernel can greatly influence the classification accuracy. The results prove that the optimized value of those tunable parameters are subject-specific, because with the same value the classification rates can be over 85% or as low as 32% as well. The pros and cons for each kernel were concluded and discussed. Training Process Training Labels

Filtering

Training Data

Feature Extraction

AR-Classification rate with Gaussian kernel (σ=0.0035)

Support Vector Machine

What kernel to use? (Linear, Gaussian, polynomial, etc.)

Brain signal fNIRS

Feature Extraction

Support Vector Machine

Classified Labels

Classification rate

100.00% 80.00% 60.00% 40.00% 20.00% 0.00% 1 Filtering

Classification Process

Figure 1. Experimental flow chart.

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Figure 2. AR classification rate for all subjects when Gaussian kernel is adopted.

Acknowledgements: This work was supported by the National Research Foundation (NRF) of Korea under the auspices of the Ministry of Science and ICT, Republic of Korea (grant nos. NRF-2017R1A2A1A17069430 and NRF-2017R1A4A1015627). References

[1] N. Naseer, and K.-S. Hong, “fNIRS-based Brain-Computer Interfaces: A Review,” Front. Hum. Neurosci., vol. 9, no. 3, pp. 1-15, 2015. [2] A. Zafar and K. S. Hong, “Detection and Classification of Three-class Initial Dips from Prefrontal Cortex,” Biomed. Opt. Express, vol. 8, no. 1, pp. 367-383, 2017.

I-15 fNIRS-based Gender Classification upon Voice Hearing

So-Hyeon Yooa and Keum-Shik Honga,b

a

School of Mechanical Engineering, bDepartment of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea [email protected]

Abstract: Objective: In real life, a listener does not have to struggle to distinguish the speaker's gender. As we talk, we unconsciously distinguish the gender of the speaker, and this mechanism has not been clearly defined. Several fMRI studies have performed to find the relationship between human voice and brain activation [1]. In this study, we tried to compare brain activation during different gender voice stimuli using functional near-infrared spectroscopy (fNIRS). Methods: A continuous wave fNIRS instrument (DYNOT; NIRx Medical Technologies, USA) with two wavelengths 760 nm and 830 nm is used to obtain hemodynamics with a sampling rate 1.81 Hz. Total 18 channels were placed on the left temporal cortex. Ten healthy Korean volunteers (6 male, 4 female, mean age: 27.6 ± 5 years) participated in this experiment. Experiment consists of four categories: Korean female voice, Korean male voice, frequency-modulated Korean female voice (160 Hz), frequency-modulated Korean male voice (160 Hz). The experimental procedure is composed of 1 minute of resting time and twenty-four trials; each trial consists of 10 sec voice stimulation and 20 sec rest. The obtained signal was converted to the concentration changes of HbO and HbR using the Modified Beer-Lambert Law. The concentration changes of HbO was filtered by a low-pass filter with the cut-off frequency of 0.1 Hz to remove physiological noises. To investigate the region of interest (ROI) of four voice categories, t-value was calculated using the expected hemodynamic response. The ROI channels were selected by t-test (t-value > tcrit). Results and conclusion: Figure 1 shows t-map of the averaged data in four categories of Sub. 3. In Figure 1, female voices revealed high activation on the left temporal cortex than male voices. In frequency modulated cases, the original voices showed high activation than frequency modulated voices in both genders. Acknowledgement: This work was supported by the Busan Institute of S&T Evaluation and Planning, Korea (grant no. B0060417001006) Figure 1. t-map of the averaged hemodynamic and the National Research Foundation under the signals in the left temporal cortex (Sub. 3). Ministry of Science and ICT, Korea (grant no. NRF-2017R1A2A1A17069430). References [1] Philip S.J.Weston, Michael D. Hunter, Dilraj S.Sokhi, Iain D. Wilkinson, Peter W.R.Woodruff, “Discrimination of voice gender in the human auditory cortex”, NeuroImage, Volume 105, Pages 208214, 15 January 2015.

I-16 Do personal experiences affect how typically fluent speakers perceive stuttering? Data from neurological, psychophysical, and surveyed responses. D.C. Pricea, S. L. Novib, C. A. Imbalzanoa, B. C. Spilsburya, A.G. Yodhc, R.C. Mesquitab,d, E. M. Heinmillera, J. L. Seproskya, G. M. Tellisa and C. M. Tellis a a

Department of Speech-Language Pathology, Misericordia University, Dallas, PA, USA b Institute of Physics, University of Campinas, Campinas, SP, Brazil c University of Pennsylvania, Philadelphia, PA, USA d Brazilian Institute of Neuroscience and Neurotechnology, Campinas, SP, Brazil Corresponding author e-mail address: [email protected]

Introduction: Jones et al. (2011) indicate that there seems to be an association between emotions and stuttering regarding physiological aspects of emotion. To date, there are no known studies that have paired autonomic nervous system (ANS) and fNIRS as participants view negative and positive videos depicting stuttering. The purpose of this study was to determine the hemodynamic and psychophysical responses of participants as they viewed videos of people explaining positive and negative experiences of their stuttering. Methods: fNIRS was used to measure oxy- (HbO) and deoxy- (HbR) hemoglobin concentration changes in the brain. Probes were placed on the cap based on the 10-5 system for EEG, over regions of the brain associated with language and emotion. Mindware Technologies measured the ANS through obtaining heart rate variability (HRV), electrodermal activity, and respiration rate. A 60-second baseline was collected pre-stimuli exposure. Thirty participants watched a randomized E-Prime 3.0 presentation. Stimuli were 20-seconds in length, repeated 10 times, and each alternated with a 20-second baseline. Stimuli consisted of a male who stutters speaking of his positive experiences with stuttering and a male who stutters speaking negatively about experiences with stuttering. After data collection, participants completed a survey that evaluated how they felt about the videos and their familiarity with stuttering. Results and Discussion: Preliminary results indicate that when participants viewed the male videos, statistically significant (p < .05) increases in HbO in the Pars Opercularis in the left hemisphere and the Temporopolar Area and Pars Triangularis in both hemispheres were noted when participants did not know a person who stutters (PWS). We also found HbO changes from baseline over different scenarios i) when male participants who did not know a PWS watched positive videos; ii) when female participants who did not know a PWS watched positive videos; iiiwhen female participants who did not know a PWS watched negative videos, and; iv) when female participants who knew a PWS watched negative videos. When viewing the videos of the male who stuttered, there was a significant difference (p tcrit). For the comparison of respiration rate, the signals were filtered using a bandpass filter of a cutoff frequency of 0.2 to 0.4 Hz and fast Fourier transform (FFT) was taken. Results and conclusion: We have used only ΔHbO for analysis. Figure 1 shows the averaged ΔHbO over all active channels and trials for without and with stress condition tasks of Sub. 2. In comparison to the without stress condition, a significant decrease in ΔHbO was observed in the stress condition. Also the results of FFT for without and with stress condition task show that the respiration rate increased in the stress condition task (i.e., 0.29 Hz without stress condition and 0.33 Hz with stress condition). It was also observed that the ΔHbO and the respiratory rate varied between subjects. The results demonstrate that the stress can be detected using fNIRS as a standalone device. Acknowledgment: This work was supported by the Busan Institute of S&T Evaluation and Planning, Korea (grant no. B0060417001006) and the National Research Foundation under the Ministry of Science and ICT, Korea (grant no. NRF2017R1A2A1A17069430). References [1] A. Brugnera, C. Zarbo, R. Adorni, G. A. Tasca, M. Rabboni, E. Bondi, A. Compare, and K. Sakatani, “Cortical and cardiovascular responses to acute stressors and their relations with psychological distress”, International Journal of Psychophysiology, vol. 114, 38-46, 2017. [2] K. Dedovic, R. Renwick, N. K. Mahani, V. Engert, S. J. Lupien, and J. C. Pruessner, “The Montreal Imaging Stress Task: using functional imaging to investigate the effects of perceiving and processing psychosocial stress in the human Figure 1. Averaged ΔHbO over all brain,” Journal of Psychiatry and Neuroscience, vol. 30, no. active channels and trials of Sub. 2. 5, pp. 319-325, 2005.

I-35 A High Spatiotemporal Resolution and Modular System for 3D Neuroimaging

M. Atif Yaquba, Amad Zafara, Seong-Woo Wooa, and Keum-Shik Honga,b

a

School of Mechanical Engineering, b Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea [email protected]

Abstract: The development of a portable and cost effective neuroimaging system is the key for early detection of the cerebrovascular or degenerative brain diseases as its fatality rate is quite high. Functional near-infrared spectroscopy (fNIRS) provides reasonable spatiotemporal resolution that provides the benefit over other neuroimaging modalities, which is effective in extracting the real time hemodynamics that uses the near-infrared spectrum of light in range of 650 nm to 1000 nm to detect physiological parameters like blood volume and tissue oxygenation changes [1]. In this paper we present a modular fNIRS system based on bundled optode approach for 3D imaging [2]. The system consists of 128 dual wavelength LEDs of 735 nm and 850 nm and 1 photodiode (Figure 1). This way a total of 128 fNIRS channels will be formed at various locations and depths in the brain including the short separation channels. The center to center distance between two sources is 5 mm. Mostly researchers use many detectors compared to sources but if we swap the sources and detectors in a configuration, the locations and channel count are unaffected. Therefore, we have used more sources to increase the sampling rate because the analog to digital conversion (ADC) of a detector is much slower than switching of a source. The system comprises of mbed microcontroller (LPC1768), serial peripheral interface based switches for LEDs, an onboard ADC, and WiFi module for communication with the software program running on a computer. The LEDs and detectors were tested with a phantom. The simulated capacity of sampling rate for the current system is 45 Hz. This design allows a better spatial resolution and it is a step towards developing 3D fNIRS imaging devices.

Figure 1. Dense optode configuration of single module (left) and multi-module arrangement to cover larger area (right) Acknowledgement: This work was supported by the National Research Foundation (NRF) of Korea under the auspices of the Ministry of Science and ICT, Republic of Korea (grant nos. NRF-2017R1A2A1A17069430 and NRF-2017R1A4A1015627). References: [1] A. Zafar and K.-S. Hong, “Detection and classification of three-class initial dips from prefrontal cortex,” Biomedical Optics Express, Vol. 8, No. 1, pp. 367-383, 2016. [2] H. D. Nguyen, K.-S. Hong, and Y. I. Shin, “Bundled-Optode Method in Functional NearInfrared Spectroscopy,” PLoS One, Vol. 11, No. 10, AN0165146, 2016.

I-36 Effect of Visual Training on Motor Imagery Ability: Application to fNIRS-BCI Usman Ghafoora, Amad Zafara, Ho-Ryong Yoob, and Keum-Shik Honga a

School of Mechanical Engineering, Pusan National University, Busan 46241, bNeurology Disorder Center, Dunsan Korean Medicine Hospital, Daejeon University, Daejeon 35235, Republic of Korea [email protected] Abstract: Objective: Motor imagery has been used for brain-computer interface (BCI) applications since long but have limitation of not giving better accuracy upon classification because of weak hemodynamic response (HR) [1]. This study aims to gain insights into the effects (improvement) in HR of the sensorimotor cortex while imagining movement of right hand (i.e., ball squeezing) with and without visual training. Method: We have used functional near-infrared spectroscopy (fNIRS) to obtain changes in oxyhemoglobin (oxy-Hb) and deoxyhemoglobin (deoxy-Hb) of motor imagery tasks. The DYNOT (NIRx, USA) system was used to acquire brain signals at sampling frequency of 1.81 Hz. Two sources and 10 detectors were placed on the left sensorimotor cortex using C3 as reference of the international 10-20 system for electrode placement, to form 13 emitter-detector channels. Six healthy male volunteers were participated in the experiment having mean age of 27±1.5 years. The experiment was conducted in accordance with the latest Declaration of Helsinki. During experiment, the participants were asked to relax on the chair and perform the motor imagery task. The experiment was divided into two sessions: In the first session the subjects’ task was to imagine ball squeezing with his right hand while, in the second session, the task remained the same but video was played on a screen that showed a person continuously squeezing the ball for visual training that can help to improve imagination of subject. Each experiment session contains five trials of 40 sec. The trial consists of 10 sec task and 30 sec rest with the baseline of 120 sec. Results and conclusion: The active channels (i.e., t-value greater than tcri) were taken and averaged across all trials. Figure 1 shows averaged oxy-Hb over all active channels and trials of Subject 4 for the motor imagery with and without visual training. A significant increase in oxy-Hb was observed while performing the task with visual training that is consistent with the previous findings [2]. The peak values obtained with/without training imagery task are 4.6770e-4 and 3.9697e-4, respectively. Significance: These results demonstrated the improvement in motor imagery ability for fNIRS-based BCI. Acknowledgment: This work was supported by the National Research Foundation (NRF) of Korea under the auspices of the Ministry of Science and ICT, Republic of Korea (grant nos. NRF-2017R1A2A1A17069430 and NRF2017R1A4A1015627). References: [1] K.-S. Hong, N. Naseer, and Y. H. Kim, “Classification of prefrontal and motor cortex signals for three-class fNIRS-BCI,” Neuroscience Letters, vol. 587, pp. 87-92, 2015. [2] V. Kaiser, G. Bauernfeind, A. Kreilinger, T. Kaufmann, A. Kübler, C. Neuper and G.R. Figure 1. Averaged oxy-Hb of motor imagery (MI) Müller-Putz “Cortical effects of user training in a motor imagery based brain–computer interface measured by fNIRS and EEG,” Neuroimage, 85, pp.432-444, 2014.

I-37 A preliminary report on the probabilistic-atlas-guided DOT

Daisuke Tsuzukia,b, Jay Dubbc, Robert J. Cooperd, Ippeita Danb ,David A. Boasc and Meryem A. Yücelc,e

a

Department of Language Sciences, Tokyo Metropolitan University, Japan Applied Cognitive Neuroscience Lab, Faculty of Science and Engineering, Chuo University, Japan c Neurophotonics Center, Boston University, USA d Department of Medical Physics and Biomedical Engineering, University College London, UK e Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, USA b

Corresponding author e-mail address: [email protected] Abstract: High-density functional near-infrared spectroscopy (fNIRS) allows the reconstruction of brain activation maps through Diffuse Optical Tomography (DOT) with superior spatial resolution and localization accuracy compared to the conventional channelwise fNIRS analysis. Utilizing single-atlas-guided DOT1 allows such reconstruction without obtaining subject’s MRI volume, however it worsens localization accuracy compared to using the subject's true head anatomy. Here, we propose a “probabilistic-atlas-guided DOT (pDOT)” approach (Fig. 1) that uses multiple individual MRI volumes as referential atlases2 and combines the resulting images to obtain a probabilistic representation. Our results show that using such a probabilistic atlas approach reduces the error inherent in atlas-guided imaging caused by the deviations of the subject’s true anatomy from that of a single atlas head model (Fig. 2). Probabilistic-atlas-guided DOT (a) DOT Reconstruction on Subject: Average Metric

Subject

(b) DOT Reconstruction on Colin Atlas: Average Metric

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(d) pDOT Reconstruction: Centroid Average Metric 40

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Fig.1. A Schematic illustration of pDOT framework.

Fig.2. Comparison of the local error metrics among reconstructed activations on the subject’s own anatomy (a), single-atlas-guided-DOT (b) and pDOT approaches (c, d).

Custo, A., Boas,D.A., Tsuzuki,D., Dan,I., Mesquita, R.,Fischl, B., Grimson,W.E.,WellsIII,W., 2010. Anatomical atlas-guided diffuse optical tomography of brain activation. Neuroimage 49, 561–567. Singh, A.K., Okamoto, M., Dan, H., Jurcak, V., Dan, I., 2005. Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI. Neuroimage 27, 842–851.

I-38 Neurovascular Coupling Assessment during Clinical Tests for Early Alzheimer Disease Diagnosis: a Multimodal EEG-fNIRS and Deep Learning Approach AM Chiarellia, P Crocea, F Zappasodia, C Filippinia, D Perpetuinia, D Cardonea, L Rotunnob, N Anzolettib , M Zitob, and A Merlaa Department of Neurosciences, Imaging and Clinical Sciences, University G. D’Annunzio of Chieti, Italy b Department of Medicine and Science of Ageing, University G. D’Annunzio of Chieti, Italy Corresponding author e-mail address: [email protected]

a

We report results from an ongoing study of multimodal EEG-fNIRS (Fig 1a), ecologically recorded on patients during the clinical test FCSRT [1], a test employed for early diagnosis of Alzheimer Disease (AD). FCSRT assesses subject’s memory with good specificity and sensitivity to AD. FCSRT is quite long (~1 hour), since it involves remembering figures few tens of minutes after their administration, and it is alternated with other tests exploring different domains of cognition. The last important phase assessing memory is called Delayed Recall (DR). The tests require interaction between patient and physician, not allowing defined paradigms and standard signal analysis. Synchronous EEG and fNIRS provide the opportunity of exploring the neurovascular coupling (NC, the link between electrical and hemodynamic brain activity) by estimating their spatiotemporal association during tasks. NC is a non-linear phenomenon [2]. Moreover, since EEG and fNIRS provide different spatial sensitivities and rely on many recording locations, the assessment of their link is a multiparametric problem. Deep Learning algorithms (i.e., Deep Neural Networks, DNNs) are increasing their popularity for studying non-linear multiparametric phenomena, outperforming other procedures [3]. We employed a DNN (Fig 1c) to assess the link between EEG band powers (α, β, θ), estimated through whole head 128 channels EEG (DNN inputs), and O2Hb and Hbb recorded in frontal area by means of 20 channels fNIRS (DNN outputs) (located based on the 10-20 System) (Fig 1b). The DNN was trained in Tensorflow [4] through a supervised learning approach based on backpropagation [5] that iteratively minimized the mean square error (MSE) between the predicted and the recorded fNIRS with EEG bands as input (signals were artifact corrected, resampled at 1 Hz, low-pass filtered at 0.4 Hz and normalized with unitary variance). The DNN was trained on the whole experiment (disregarding DR) on 20 controls and 5 early ADs (for a total of ~5·104 samples), through a 10-fold cross-validation. Fig 2a shows the cross-validated performance. Employing an early stop approach, the DNN provided a fNIRS hemoglobin forms’, channels’ and subjects’ average explained variance (EV, 1-MSE) of 0.6% (above chance, t=4.37, df=9, p=0.002). When testing the DNN on DR, we obtained an EV of fNIRS higher in ADs than controls(1.6% vs 0.4%, t=2.24, df=23, p=0.034) only in long fNIRS channels (sensitive to brain activity) and O2Hb (Fig. 2b). Although this is a preliminary result (higher ADs numerosity is required), the increased fNIRS EV, hence increased NC, in frontal area of ADs during DR may be caused by the higher task demand in early ADs when brain status is still not heavily compromised. This study shows the feasibility of assessing NC employing multi-modal EEG-fNIRS and DNNs in complex environments and populations.

Ref 1. Buschke H et al 1997 2. Stephan KE et al 2004 3. LeCun Y et al. 2015 4. Abadi M et al 2016 5. Kingma DP & Ba J 2014H2020, Acknowledgements: Study funded by grant: H2020, ECSEL-04-2015-Smart Health, ASTONISH

I-39 The frontal pole activity in imagination of a self-related future situation

Yumi Oboshia, Kohei Miyatab, Takahiko Koikeb and Norihiro Sadatob

a

Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, Japan b Department of System Neuroscience, National Institute for Physiological Sciences, Japan Corresponding author e-mail address: [email protected] Introduction: The medial prefrontal cortex (mPFC), including the frontal pole, has been reported to be involved in prospective memory, future thinking and self-prospection. In a previous study, mPFC, especially the rostral anterior cingulate cortex was reported to be activated in imagining self-related happy future events1. However, it is not clear whether this activation was specifically induced by the self-relevance or the mental representation of future events regardless of the agent. Furthermore, it remains unclear whether the emotional valence factor inevitably affects the frontal pole activity. To explore these points, we conducted functional near-infrared spectroscopy (NIRS) measurements during the task in which participants imagined the self- and other- related emotional future situation and evaluated their own feelings after the imagination. Methods: Subjects were 15 heathy young volunteers (mean age: 21.3 y). We measured cerebral blood flow (CBF) changes during the Situation Imagination Task extended from the Positive Emotion Induction Task1, using a NIRS device (OEG-SpO2, Spectratech, Inc.). Each trial had an Introduction (2.5 sec), Imagination (15 sec) and Rating phase (5 sec). In the Imagination, participants were required to imagine the situation vividly as their own situation (SELF-condition) or as a stranger’s (OTHER-condition). In the Rating, they were asked to evaluate their own present feelings using a Visual Analogue Scale (VAS), specified at the -50% point of the scale “very unhappy”, 0% point “neither happy nor unhappy”, and 50% point “very happy”. There were 12 situations to imagine under 8 conditions; 2 protagonists (SELF/OTHER) and 4 conditions (3 emotional conditions; Happy/ Unhappy/ Neutral and low level control). We analyzed the averaged oxy-hemoglobin concentration change value (Δ[oxy-Hb]) as an index of CBF change in each condition during the Imagination and Rating calculated with a baseline correction of 5 seconds prior to the each phase-start, for the channels corresponding to the frontal pole (ch7 and ch10) . Results and discussion: Regarding the VAS score, the main effects of Protagonist and Emotion, and their interaction [Protagonist * Emotion] were significant (P < .001). Significant differences between SELF and OTHER in Happy and Unhappy conditions were also found (p < .001), indicating that stronger feeling was evoked after the self-relevant imagination than other-relevant one. On Δ[oxy-Hb] in the frontal pole, we found a significant main effect of Protagonist (P = .0242), and no significant main effect of Emotion, and their significant interaction (P = .0141). A post-hoc test revealed that SELF-Δ[oxy-Hb] was significantly larger than OTHER- in unhappy condition (t = 5.433, p < .001). After the imagination, oxy-hemoglobin level decreased and main effects of Protagonist and Emotion, and their interaction were not significant in Δ[oxy-Hb] of the frontal pole during the Rating phase in any emotional valence. It suggests that self-relevance was not noted while evaluating the current one’s own feelings. In the present study, we found that imagination of a future situation per se activated the frontal pole, and its activity was specifically enhanced by the self-related imagination. Considering that a significant increase was only found in unhappy condition, the frontal pole may represent self-conscious emotion which is evoked by the imagination of unhappy future situation. Reference: 1 Matsunaga, M., Kawamichi, H., Koike, T., ・・・ Sadato, N. (2016), Structural and functional associations of the rostral anterior cingulate cortex with subjective happiness. NeuroImage.

I-40 Neural correlates of inner speech – fNIRS- and fMRI-measurements H. Storchaka, T. Dreslera,b, J. Hudaka,b, A. J. Fallgattera,b,c, A.-C., Ehlisa,b a

General Psychiatry and Psychotherapy, University Hospital Tuebingen LEAD Graduate School & Research Network, University of Tübingen, Gartenstr. 29, 72074 Tübingen, Germany c Werner Reichardt Centre for Integrative Neuroscience (CIN), University of Tübingen, Otfried-Mueller-Str. 25 72076,Tübingen, Germany

b

Corresponding author e-mail address: [email protected]

Abstract: One of the main clinical features of schizophrenia are positive symptoms, which constitute a distortion of normal psychological functions (e.g. hallucinations, delusions, and thought disorder. Auditory (verbal) hallucinations (AVHs) are a characteristic symptom of psychosis, affecting 60-80% of schizophrenia patients. AVHs tend to be resistant to antipsychotic medication in 25-30% of schizophrenia patients. An influential cognitive model accounting for the mechanisms of the generation of AVHs describes a defective monitoring of inner speech to be causal, leading to the misidentification of internally generated thoughts and images as externally generated events. Two studies will be presented: A combined fNIRS-fMRI study with healthy participants (n=20) additionally rated with schizotypy questionnaires (study 1) and an fNIRS study with schizophrenic patients with and without AVHs and healthy participants (n=50) (study 2). In both studies, an inner speech paradigm was utilized during the measurements to investigate the underlining mechanisms of AVHs. The examination of schizotypal characteristics provides the opportunity to investigate the vulnerability for schizophrenic disorders and schizophrenia- and psychosis-like symptoms without confounding factors, such as medication, hospitalization and diagnosis stigma. The results of the combined fNIRS-fMRI study show a specific activation pattern for the inner speech paradigm in accordance to other studies investigating the processing and monitoring of inner speech. High correlations between the BOLD signal and O2Hb were detected. Furthermore, negative correlations between schizotypy rating and activations were revealed, indicating a relationship of schizotypal characteristics and a deficient activation pattern. In the fNIRS study with schizophrenic patients and healthy controls (study 2) we observed different patterns for the processing and for the monitoring of inner speech in both groups. Furthermore, schizophrenic patients with and without AVHs showed a deficient activation pattern in comparison to healthy controls for the processing and monitoring of inner speech.

I-41 Simultaneous EEG and fNIRS co-localization of theta band activity and hemodynamic responses to fusiform gyrus during face perception S. Dravidaa, Y. Onob,c, J. A. Noahc, X. Zhangc and J. Hirschc,d,e,f* a

Interdepartmental Neuroscience Program, Yale School of Medicine, USA b Department of Electronics and Bioinformatics, Meiji University, Japan c Department of Psychiatry, Yale School of Medicine, USA d Department of Neuroscience, Yale School of Medicine, USA e Department of Comparative Medicine, Yale School of Medicine, USA f Department of Medical Physics and Biomedical Engineering, University College London, UK *Corresponding author e-mail address: [email protected]

Abstract:

The relationship between hemodynamic signals and the spatial sources of electrocortical frequency band oscillations is not well understood. Using simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), we measured brain activity when participants viewed pictures of faces and objects. A Shimadzu LABNIRS with 40 optode pairs arranged in a 134-channel layout and g.tec system with 32 EEG electrodes covering the full head (Figure 1) were used to acquire data simultaneously. As expected for face processing, hemodynamic activity in the right fusiform gyrus increased during face viewing compared to object viewing, and the N170 event-related electrocortical response to faces localized to the right fusiform gyrus. However, it is not known if specific frequency band oscillations are associated with face processing. Specifically, based on reported associations between the theta band (4-8 Hz) and visual processing1, we hypothesized that increased hemodynamic activity in the fusiform gyrus during a passive face perception task would be associated with greater theta band activity originating in the same area. Consistent with our hypothesis, theta band oscillations were also localized to the right fusiform gyrus more for faces than for objects, while alpha (8-13 Hz) and beta band (13-30 Hz) oscillations were not (Figure 2). Together, these findings suggest that theta band oscillations originating in the fusiform gyrus may be part of the facespecific processing mechanism. These findings further suggest that simultaneous EEG and fNIRS can be successfully used to explore the relationship between hemodynamic and electrocortical signals during face perception. Reference 1. Başar, E., Schürmann, M., & Sakowitz, O. (2001). The selectively distributed theta system: functions. International Journal of Psychophysiology, 39(2-3), 197-212.

I-42 Automated Spatial Co-Registration Method from Simple Video

S. Jaffe-Daxa, A. H. Bermanob, and L. L. Embersona

a

b

Psychology Department, Princeton University, USA Computer Sciences Department, Princeton University, USA [email protected]

Spatial co-registration of scalp channel positions is a wide spread problem in fNIRS acquisition, especially with developmental populations. Current methods either rely on approximate assumptions (e.g., spherical shape of the subject’s head), or require the subjects to remain still for a long duration. Other suggested solutions involve expensive high-end equipment (e.g., customized 3D scanners) and non-trivial expertise. We propose a fast and accurate method for scanning the subject’s head shape using commodity equipment and computer vision based algorithms. Through the automatic detection of fiducials, our method is resilient to small motions during the acquisition, and hence was found feasible for all ages, from neonates to adults. The method requires a single short (under half a minute) video of the subject’s head and mounted probes. From the video we extract usable frames (Fig. 1A), omitting unstable or blurry ones, and employ Structure from Motion [1] to build a 3D model of the scene (Fig. 1B). We then identify fiducial locations on the 3D model and use the SPM-fNIRS Spatial tool to project the probes and channel locations to MNI space (Fig. 1C). Through a user-friendly interface, our spatial co-registration method eliminates the need for expensive hardware or training, approximation assumptions, long spatial registration sessions or manual image annotations. This robust co-registration method enables the full exploitation of the spatial separation advantage of fNIRS and potentially allows precise cross-subject aggregation of data for averaging and comparisons.

Figure 1. Schematic illustration of the co-registration process. A. Low quality video is parsed to photos. B. Photos are matched and a model is reconstructed through Structure from Motion. C. Reference positions are used to interpolate all channel positions using the SPMfNIRS Spatial tool. References 1.

Wu, C. VisualSFM : A Visual Structure from Motion System. Available at: http://ccwu.me/vsfm/.

I-43 Towards an fNIRS-Based Objective Measure of Speech Understanding in Children with Cochlear Implants: Our Search for a Suitable Auditory Baseline for Speech Processing

F. Mushtaqa,b, I. M. Wigginsa,b, P. T. Kittericka,b, C. A. Andersonc and D. E. H. Hartleya,b,d

a

b

NIHR Nottingham Biomedical Research Centre Division of Clinical Neuroscience, University of Nottingham c Action on Hearing Loss d Nottingham University Hospitals NHS Trust

Corresponding author e-mail address: [email protected] Aim: Our long-term aim is to develop an fNIRS-based objective speech perception measure for clinical use with young cochlear implant users. In this study, we sought to identify an appropriate auditory baseline stimulus for measuring speech-specific activation using fNIRS. It remains challenging to functionally separate linguistic and lower-level auditory responses from one another as they are often expressed similarly. To attempt to overcome this issue, responses to speech can be contrasted against an auditory baseline to distinguish between speech and non-speech responses [1]. At present, it is unknown which of several popular baselines for speech used with other neuroimaging modalities are best at retaining speechspecific responses in an experimental set-up involving fNIRS. Methods: 25 normally hearing children aged 6-12 years underwent fNIRS neuroimaging. Three auditory conditions were presented in an event-related format: normal speech, timereversed (TR) speech and signal-correlated noise (SCN) with 25 sentences per condition. Participants passively listened to the experimental stimuli whilst monitoring for an occasionally presented warble tone that was easily distinguishable from the other stimuli. In order to measure brain activity, 30 probes were arranged in two 5 x 3 arrays, targeting both cerebral hemispheres. Results: Significant activation was observed bilaterally in channels targeting auditory regions when stimuli were contrasted against silence. No significant activation was observed when normal speech was contrasted against TR speech or SCN. Estimated response amplitudes were calculated for channels targeting auditory regions and subjected to RM-ANOVA analyses: no statistically significant effects were found under any contrast. Left minus right hemisphere activity was calculated to examine responses lateralized to the left hemisphere. Again, no significant activation was observed under any contrast. Interestingly, a left-sided channel targeting posterior temporal regions showed significant activity in response to normal speech only, so this was investigated further. Significantly greater activation was observed in this left posterior channel in response to the normal speech vs SCN contrast only. Conclusion: It appears that TR speech is not a suitable baseline for isolating speech-specific responses when imaging using fNIRS. It is possible that SCN may serve as a suitable alternative, but this requires further investigation. This work represents an important step towards developing an fNIRS-based measure that has the sensitivity and specificity required to identify children struggling to hear with their cochlear implants at an individual level. References: 1. Stoppelman, N., T. Harpaz, and M. Ben-Shachar, Do not throw out the baby with the bath water: choosing an effective baseline for a functional localizer of speech processing. Brain and Behavior, 2013. 3(3): p. 211-222

I-44 Impact of Acute Stress on Risky Decision Making: An fNIRS Study Vrinda Kalia1, Bryan Von Der Vellen,1 Jose Jacbobo and Karthik Vishwanath2   1 Department of Psychology; 2Department of Physics, Miami University Decision-making is a cognitive process that occurs when weighing the benefits and risks of two or more options (Figner & Weber, 2011). Research shows that when making a decision under stress, risk-taking increases (Lighthall et al., 2009). Hence, it is ironic that the most meaningful decisions in one’s life are often made under stress. The assumption is that acute stress makes the rewards that result from a risky decision appear more appealing to an individual (Mather & Lighthall, 2012). Using fMRI, Lighthall and colleagues (2012) demonstrated that risky decision-making following acute stress induction was implicated in the left anterior insular and left dorsal striatum regions of the brain. In the presented study we examined the effect of acute stress induction on risky decision-making. In addition to behavioral measures we used fNIRS to examine brain hemodynamic response during stress induction to explore relations with behavioral response on the risk taking measure.   Method   Thirty-one participants (20=Female; ages 18-21) were randomly assigned to one of two conditions: Stress or No Stress. Participants reported on their stress levels pre and post the experimental manipulation. Stress condition: Participants (n = 17) submerged their non-dominant hand in icecold water for 3 minutes (Cold Pressor Task; CPT; Lovallo, 1975). No Stress condition: Participants (n = 14) placed their non-dominant hand in room temperature water for 3 minutes. fNIRS data: A 64 channel NIRx Scout system configured using the 8x7 Prefrontal Cortex Layout was used to derive temporal concentration changes of HbO and HbR across 20 spatial channels. These concentration changes were then separated into HbO and HbR changes in the superficial tissues (scalp/skull) and in deeper tissues (brain) using a statistical approach based on minimizing the average mutual information of the hemodynamic signal. The separated functional (brain) signal was averaged in 10s blocks for HbO and HbR across each channel and grouped into 4 spatial regions from the midline (based on the location of channels sensing the brain) as the far-left, mid-left, mid-right and far-right.   Risk taking measure: Risk taking was assessed immediately following the stress induction using the Balloon Analogue Risk Task (BART; Lejuez et al., 2002). The BART is a computerized measure consisting of 30 trials. Participants pump a virtual balloon to earn money. As the balloon gets bigger they make more money but also face increased risk of losing it all if the balloon explodes. Thus, number of balloon explosions is a key indicator of risky behavior (Lejuez et al., 2002). Results Repeated measures ANOVA on reported stress levels, pre and post manipulation, revealed a significant interaction effect F(1, 29)=5.90, p =.02; indicating the experimental manipulation only increased stress levels in the Stress group. Independent samples t-test (one-tailed) showed participants in the Stress (M=8.94, SD=5.18) condition had marginally more balloon explosions than participants in the No Stress (M=6.57, SD=4.97) condition, t(29) -1.29, p = .10. For the fNIRS data, oneway ANOVA indicated that participants in the Stress condition had higher HbO levels in the Right mPFC in comparison to the No Stress condition F(1, 29) = 5.90, p = .02 ηp2 = .17. Pearson correlations revealed that HbO levels in the Left mPFC in the Stress group, was positively correlated with number of explosions (r = .53, p = .02). However, in the No Stress group HbO levels in the Left mPFC were negatively correlated with number of explosions (r = .54, p = .05). Our findings are consistent with previous work conducted by Lighthall and colleagues (2012) and suggest that fNIRS can be used to examine the impact of acute stress on decision-making.

I-45

I-46 Brief Mindfulness Intervention and Risky Decision Making: An fNIRS Examination of Intervention Efficacy Meryem Yucel1, Kira Osowski2, Karthik Vishwanath3 and Vrinda Kalia2 1

Neurophotonics Center, Boston University; 2Department of Psychology, Miami University; 3Department of Physics, Miami University

Mindfulness is being aware of the present moment (Ruedy & Schweitzer, 2010). Mindfulness is shown to lessen the severity of risk taking, which allows individuals to make more adaptive decisions (Lakey et al., 2007). Most studies examining the effect of mindfulness on behavior have used lengthy interventions. For instance, 8week interventions that require daily practice are fairly standard (Robbins et al., 2012). Lengthy interventions pose two problems. First, they may not be feasible for everyone. Second, individuals who are able to stick with long-term interventions may have other personality traits (e.g. persistence) that may impact the efficacy of the intervention in changing behavior (Tang et al., 2015). We present the results of a study examining the effect of a 15-minute mindfulness intervention on risky decisionmaking. In addition to behavioral measures we used fNIRS to examine brain hemodynamic response during the mindfulness intervention to explore relations with behavioral response on the risk taking measure. Method Participants were 21 (11=female; 18-23 years) college students who were naïve to mindfulness. Prior to the intervention, trait level mindfulness was assessed using the Mindful Attention Awareness Scale (MAAS; Brown & Ryan, 2003). For the intervention, participants were individually exposed to a 15-minute guided breathing, meditative exercise. A 64 channel NIRx Scout system configured using the 8x7 Prefrontal Cortex Layout was used to acquire the hemodynamic data during the mindfulness intervention. A dynamic functional connectivity analysis was performed on the Oxy-Hemoglobin time course at homologous NIRS channels, across the left and right hemispheres, using the sliding window method (300 sec window moved forward by 10 sec).   Post mindfulness intervention, risk taking was assessed using a computerized measure, Balloon Analogue Risk Task (BART; Lejuez et al., 2002). BART consists of 30 trials of pumping a virtual balloon to earn money. As the balloon gets bigger the participant makes more money but also faces increased risk of losing it all if the balloon explodes. Number of balloon explosions is a key indicator of risk-taking (Lejuez et al., 2002) Results and Discussion Since research has shown that males take more risks than females (Figner & Weber, 2011) we conducted one-way ANOVA, on the number of balloon explosions on the BART, as a function of sex. Male (M=4.66, SD=2.74) participants had significantly fewer explosions than female (M=8.54, SD=3.36) participants (F(1, 18) = 7.76, p = 0.01; ηp2 = .30). But, the two sexes did not differ on trait mindfulness (p > .05). Thus, males benefitted more from the mindfulness intervention than females. Pearson correlations, conducted for the two sexes separately, showed that trait mindfulness was unrelated to performance on the BART for either group. Increased crosshemispheric functional connectivity from baseline to midpoint in the intervention was positively correlated with number of balloon explosions for the female participants only (r = .68, p = .02). Our data indicate that fNIRS can provide useful information about important individual level brain processes that occur during a brief mindfulness intervention. This could help design more effective brief mindfulness interventions.

I-47 The Time-delay of Oxygenated-hemoglobin Changes in Early Infancy c Zhenhu Lianga,c, Hao Tiana, Yasuyo Minagawab, Takeshi Arimitsu , Takao Takahashic and Yunjie Tongd

a

Institute of Electrical Engineering, Yanshan University Department of Psychology, Faculty of Letters, Keio University c Department of Pediatrics, Keio University School of Medicine, Tokyo, Japan d Weldon School of Biomedical Engineering, Purdue University Corresponding author Zhenhu Liang e-mail address: [email protected] b

Abstract: The assessment of the brain development of neonates is a challenging issue for neuroscientists. Functional near-infrared spectroscopy (fNIRS) is an important tool for monitoring the hemodynamic changes in infants. In this study, we analyzed the time delay of oxyhemoglobin (HbO) signals in the early preterm and term babies with the postnatal age(PNA) up to 50 days. The time delays between different brain regions and their corresponding entropy were employed to investigate the brain development, especially in cerebrovasculature. Methods:Time delay map was constructed based on the 46- channels HbO recordings in 0.010.1 Hz. The time-delay distribution entropy (TDDE) algorithm described as follow: (1) The CPSD method was used to measure the cross spectrum phase of two time series (see in figure 1(A)). (2) The magnitude of the CPSD was shown in figure 1(B) and the phase of the cross spectrum can be achieved by the angle function. The frequency with the high-coherence corresponds to the lag of phase with two signals. (3) The time delay of two time series was 𝜃 calculated as: timedelay = 𝑚𝑎𝑥 , where the 𝜃𝑚𝑎𝑥 is the phase lag and the 𝑓𝑚𝑎𝑥 is the peak 2𝜋𝑓𝑚𝑎𝑥

coherence frequency. (4) The time delay between the pair-wise channels can be calculated and presented as the time delay map (see in figure 1 (D)). (5) The histogram of all the time delay values with one subject was shown in figure 1(E). Based on the histogram, we can calculate the proportion in each bin. The entropy of the time delay distribution can be calculated based on the Shannon entropy E = − ∑𝑗 𝑝𝑗 𝑙𝑜𝑔𝑝𝑗 , where the 𝑝𝑗 represents the proportion of the 1

bin. The normalized entropy defined as 𝐸𝑛𝑜𝑟 = 𝐸/𝑙𝑜𝑔 𝑁, where the N is the number of the bins. Results: The PNA of the early preterm and term infants are 3.71±1.07 (mean±standard deviation) and 0.59±0.18 weeks, respectively. The gestational age (GA) of early preterm and term babies are 32.09±1.46 and 38.44±1.29 weeks, respectively. The result shows that the TDDE with term are significant higher than early preterm (0.87  0.04 v.s. 0.92  0.03 with p] [ a j], where [< L i,j >] is the SSM, which is predicted by light propagation in the head model. The columns of the SSM represent the spatial sensitivity profiles. Light propagation in both the individual and atlasbased head models was calculated by Nirfast [4] to obtain the SSM. Cooper et al. summed along the spatial sensitivity profiles to obtain the aggregate sensitivity of their probe geometry to the absorption change at each voxel [3]. In this study, the optical signal detected by the probe pairs caused by the absorption change in the functional areas was calculate using the individual head models. Twenty-five source probes and twenty-four receiver probes were alternatively placed at 10-mm interval lattice points in a 60 mm × 60 mm area to construct the 22.4-mm, 30-mm and 41.2-mm probe pairs. The intensity change detected by the probe pairs were back-projected onto the individual and atlas-based head models to visualize the SSM weighed by the optical signal: [ S j ] = [ < L i,j > ] t [ OD i ]. The results were registered to the ICBM152 space to evaluate the difference in the SSM between the individual and atlas-based head models. Results: The back-projection of the SSM weighted by the optical signal detected by the probe pairs was broadly distributed on the brain and covered the functional area in both the individual and atlas-based head models. The distribution of the intense region on the atlas-based brain deviated from that on the individual model. When the difference in the geometry of brain surface between the individual and atlas-based head models was large, the gyrus in which the intense region is mainly distributed in the atlas-head model was different from that in the individual head model. References [1] A. T. Eggebrecht et al., NeuroImage, 61, p.1120 (2012). [2] A. Custo et al., NeuroImage, 49, p.561 (2010). [3] R. J. Cooper et al., NeuroImagge, 62, p.1999 (2012). [4] H. Dehani et al., Commun. Numer. Methods, 25, p.711 (2008).

II-7 Development of NIRS (Near Infrared Spectroscopy) System for Diabetic Foot Screening

J. H. Seo1 and Y. J. Jung

1,2*

Dept. of Multidisciplinary Radiological Science, Graduate School, Dongseo University

1

Dept. of Radiological Science, Dongseo University

2

[email protected] Abstract: The purpose of this study is to develop a NIRS (Near-Infrared Spectroscopy) system that can identify its possibility for screening of diabetic foot. Although PET-CT or MRI is used for diagnosis of diabetic foot, those imaging modalities are expensive and may have radiation exposure risk. In fact, diabetic foot patients should take a daily monitoring, disadvantages of conventional diagnosing devices are limiting daily care. In order to overcome those issue, Novel NIRS based Portable system for diabetic foot screening was suggested and developed.

Methods: In order to develop the portable NIR system which is cost-effective and easy to use, APD sensor and Multi-wavelength LED are employed for monitoring blood oxygenation level signal from foot. To Isolate between body and electrical device, an optical cable was utilized. The developed system can measure foot condition with contact to wound area.

Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning (No. NRF-2017R1C1B5017047).

II-8 A fNIRS-based hyperscanning study of inter-brain neural synchronization during a cooperative task M. Mizuno, S. Taniguchi, S. Hiwa, T. Hiroyasu Doshisha University, Kyoto, Japan Introduction: Social interaction is a dynamic behavior between individuals who modify their actions and reactions depending on the actions of their partner. In this study, we investigate the relationship between social interaction and brain functions. Cui et al. analyzed the neural synchronization between two participants who played a cooperation game involving synchronizing each other’s response timing and revealed that the interpersonal brain coherence of the participants increased during the cooperative task [1]. In this study, to easily facilitate the cooperative behavior of the participants, we improved the experimental design and examined the inter-brain neural synchronization during the cooperative task. Methods: A total of twenty-two healthy adult males (11 pairs, age: 22.7 ± 1.0 years old, righthanded) participated in this experiment. The experimental environment is shown in Fig 1. The brains of the two participants during their social interaction were simultaneously measured by hyperscanning using a single functional near-infrared spectroscopy (fNIRS) device (ETG-7100, Hitachi, Ltd.). A 3 × 10 probe consisting of 47 measurement channels was attached to the forehead of each participant. Participants were instructed: (1) to synchronize the response timing of their partner after the cue (synchronization task), (2) to respond faster than their partner (competition task), and (3) to respond quickly to the cue (single A/B task) [1]. In the synchronization task, the time difference between the responses of the two participants were fed back to each of them. Each participant predicted his partner's behavior based on the time difference, and was asked to synchronize monitor keyboard his responses at the next cue. Wavelet fNIRS participant A device transform coherence was calculated from two sets of time-series data of cerebral blood flow changes. Then we performed a distribution participant B one-sample t-test (p < 0.05) of the PC coherence increase of each task and investigated the brain regions where the Fig1. Experimental setup coherence increased. Results & Discussion: The difference in response time between the two participants in the synchronization task was significantly larger than that of the single A and B task (p < 0.05). This result indicates that the participants not responded quickly to the cue, but reacted by anticipating the behavior of their opponents. A t-score map of coherence increase is shown in Fig 2. The coherence within the left superior frontal gyrus (SFG) and left middle frontal gyrus (MFG) increased significantly in the synchronization task. The left SFG is involved in building a trust relationship [2]. Hence, it is assumed that this region affects cooperative behavior. Furthermore, the coherence in these two regions did not increase significantly in either the competitive or single task. Therefore, we suggest that the inter-brain synchronization in these brain regions can be utilized as a metric of cooperativeness. Fig 2. t-score map of inter-brain neural synchronization [1] Cui, X., Bryant, D. M., & Reiss, A. L. (2012). NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation. Neuroimage, 59(3), 2430-2437. [2] Reyes-Aguilar, A., Fernandez-Ruiz, J., Pasaye, E. H., & Barrios, F. A. (2017). Executive Mechanisms for Thinking about Negative Situations in Both Cooperative and Non-Cooperative Contexts. Frontiers in human neuroscience, 11, 275.

II-9 Cortical Brain Activation during Playing a Rhythm Game with and without Musical Stimuli

Gihyoun Leea, Seung Hyun Leea, Sang Hyeon Jina, Jinung Ana,*, a

Convergence Research Center for Wellness, DGIST, Daegu, Republic of Korea Corresponding author e-mail address: [email protected]

Abstract: In this paper, it is a study to observe cortical brain activation difference between with and without musical stimuli during playing a rhythm game. The rhythm game request complicated and sequential tasks such as responses for musical rhythm and actions about cognitive tasks. Basically, rhythms are played based on musical rhythm and beat. If there is no music at the playing, it has to perform according to visual timing and imagined beat. Therefore, this study could observe brain function to perform a game task depending on given information. Brodman area 41 and 42, which is the part of the temporal lobe, are well known the primary auditory cortex that processes auditory information in the human brain. Broca area is a region in the frontal lobe and it plays a significant role in language comprehension to use syntactic information. Recently, Broca area is also involved in various cognitive and perceptual tasks such as sequential execution of grasping and manipulation. Through the experimental result, although the achieved game scores are similar, the cortex brain activation maps show quite different results. The result of the experiment with music shows the auditory region was mostly activated and premotor cortex of hand region is also slightly activated. However, Broca area is significantly activated at the experiment without musical stimuli. It seems the result that uses a cognitive function of the brain instead of musical beats or rhythms to perform without music. The activation of auditory cortex seems a result of the imagined musical rhythm during playing game. Methods: So as to obtain experimental fNIRS data, the fNIRS brain imaging system (FOIRE300, Shidmazu, Japan) and the rhythms game (DJMAX, NEOWIZ, Korea) were used. The experiment was performed by a task-oriented method that has rest blocks of the 20s, task blocks of 20s, and 3 repetitions. The normal game playing experiment was firstly performed with music and the control experiment was performed about same game playing without musical stimuli. Figure 1 shows mapping results of the compare experiment.

Figure 1. Brain activation map, (a) with musical stimuli, and (b) without stimuli. Acknowledgements: This research is supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No.2016R1A6A3A11933819), and this work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (No. 2017-0-00451).

II-10 Influence of Skillfulness on Cortical Excitability: An fNIRS Study Seung Hyun Leea, Sang Hyeon Jina, GiHyoun Leea and Jinung Ana* a

Convergence Research Center for Wellness, DGIST, South Korea [email protected]

Introduction: Human brain could be reorganized by the processing of the motor learning. In the past several decades, may functional neuroimaging studies have been reported on the brain function in motor learning. Proficiency at manipulating a tool is a type of motor learning. However, no study has investigated the effect of motor learning in the brain during manipulate tools. fMRI might not be appropriate for this study because use of tools can cause sensitivity to large movements. In contrast, fNIRS is less sensitive to motion, therefor appears to be more appropriate for this study. The aim of the study is to investigate the cortical activation between skilled and unskilled person during manipulate tools. Methods: Six right-handed normal subjects were recruited. The experimental task included transfer of almonds using stainless steel chopsticks using dominance hand. FOIRE-3000 (Shimadzu Co., Japan) performed the fNIRS study with 45 channels measurements with 10 Hz sampling. Deoxy-hemoglobin (HbR) was measured for analysis and we selected four regions of interest: the primary somatosensory cortex (S1), primary motor cortex (M1), Premotor cortex, and supplementary motor area (SMA). After the experiment, we divided into two groups: three people who transferred a lot of almonds (skilled) and three people who transferred less of almonds (unskilled). NIRS-statistical parametric mapping (NIRS-SPM) built the map of cortical activities with the level of significance at a p-value of < 5%. Results and Discussion: Results demonstrated that there is evidence of differential brain activations in the two groups during executed motor task. Skilled subjects appear more focused brain activation patterns during task (contralateral M1&S1). Unskilled subjects on the other hand, showed a more widely distributed M1 and S1, and increased ipsilateral premotor cortex. These findings showed that a skilled person uses fewer brain regions and uses it more efficiently than an unskilled person.

Figure 1. Cortical activation results (a) skilled person, (b) unskilled person

Acknowledgements: This study was supported by DGIST R&D Program of the Ministry of Science, ICT and Future Planning [18-IT-02], and Institute for Information & Communications Technology Promotion (IITP) grant funded by Korea [2017-0-00451].

II-11 Age-specific transcranial brain atlas for children and adolescents from 6 to 18 years old Zong Zhanga, Xiang Xiaoa, Yang Zhaoa, Zheng Lia, b and Chao-Zhe Zhua, b* a

b

State Key Laboratory of Cognitive Neuroscience and Learning IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China

[email protected] Introduction: The non-invasive transcranial brain mapping techniques, such as fNIRS and TMS, relying on scalp-placed devices to record or stimulate regional cortical activities, have been widely applied. These techniques generally provide no brain anatomical information, making the transcranial targeting a fundamental challenge. Xiao et.al developed a new kind of brain atlas: transcranial brain atlas (TBA), based on a defined scalp space and an adult structural MRI data set (n=114). A TBA is a probabilistic mapping from scalp space to atlas label space, allowing guide the placement of transcranial devices directly on the scalp surface in a straightforward (xiao.et.al). However, the head and brain are both still developing in children and adolescents, which may influence the scalp-brain correspondence. Whether or not the adult TBA can be used directly to the developing brains should be validated. If the adult TBA is not suit for children and adolescents, the age-specific TBA is essential. Material & Methods: According to the developmental trajectory of scalp-brain correspondence, we split 281 participants (age:12.07±2.90; 120 males and 161 females) into four age group: 6-8, 8-12, 12-14 and 14-18 years and constructed four age-specific TBAs respectively. We evaluated the performance of adult TBA applied to children and adolescents and compared it with using age-matched TBA in coordinate-level and area-level. The Euclidean distance between the MNI coordinate predicted by TBA and the individual ground truth represented the prediction error in coordinate-level. The discrepancy of atlas label between the TBA prediction and the ground truth label was used as the performance evaluation index in area-level. Results and Discussion： Fig.1A shows the TBA built from LPBA for 6-8 years. The group-averaged prediction error maps of adult TBA and age-matched TBA were shown in Fig.1B.The adult TBA introduces larger prediction errors (~1cm) for younger children (6-12 years) in frontal and temporal lobe.Fig.1C shows the errors of applying adult TBA were larger with greater age discrepancy and the agematched TBA can significantly reduce the prediction error in coordinate-level. While both TBAs have similar performance with high prediction accuracy (>80%) in arealevel. In conclusion, the adult TBA is still working for transcranial locating in arealevel for 6-18 years. The age-specific TBA Figure1. (A) TBA built from LPBA (6-8 yeas.) (B) The is essential to the fine-scale transcranial prediction error map in coordinate-level (mm). (C) and (D) locating requirement, such as TMS. Comparison in coordinate-level and area-level.

References: (1) Xiang Xiao.et.al. Transcranial Brain Atlas. Under review

II-12 Group level power analysis using linear mixed-effects model Xiao-Su Hua,c, Neelima Wagleyb, Alexandre DaSilvaa,c and Ioulia Kovelmana,b a

Center for Human Growth and Development, University of Michigan b Department of Psychology, University of Michigan c Headache and Orofacial Pain Effort Lab, Biologic & Materials Sciences, School of Dentistry, University of Michigan Corresponding author e-mail address: [email protected] Abstract: Functional near-infrared spectroscopy (fNIRS) is becoming a new forefront for brain imaging due to its many advantages over other neuroimaging modalities; it is childfriendly, low-cost, virtually silent and portable across various testing environments. The statistical power represents the probability that a fNIRS study will detect an effect of interest. Thus, before planning a fNIRS study, one of the first steps is to carry out a power analysis to define a design with proper sample size that will result in a well-powered study. Especially, given measurement noises and physiological signals, corrupting fNIRS signals, will lead to relative small effect-sample size ratio. In the current study, we developed a power calculation method based on two-level fNIRS data analysis framework, that can be used for a variety of study designs. Our example compared the planned power with different study design parameters, including sample size, scanning time, and sampling frequency. Methods: Data was collected with 30 bilingual Spanish-English speaking children as part of a larger study on bilingual language and literacy development, using a TECHEN CW6 system. Children listened to short sentences in English (female native speaker) assessing a morphosyntax grammaticality judgment. Children listened to a total of 60 sentences with correct grammatical form, omission of the –ing verb ending, and omission of the –ed and –s verb endings (20 for each condition). During fNIRS imaging, children were instructed to listen carefully to each sentence (3 sec.) and indicate if the sentence was correct or incorrect (2 sec. response time) via a button press on a button box. The first- and group-level analysis were done using NIRS toolbox (Santosa et al., 2018). We used the approach described by Bernal-Rusiel and co-workers to calculate the power of group-level hypothesis (Bernal-Rusiel et al., 2013). We tested the following factors that may affect power of the data: 1) number of participants in the study, 2) number of stimulus in the study, and 3) sampling frequency of the data collection. Conclusion: Group level power increases with number of participants and number of stimulus. However, it decreases when sampling frequency is higher. References H. Santosa, X. Zhai, F. Fishburn, T. Huppert, 2018. The NIRS Brain AnalyzIR Toolbox. Algorithms 5-11, 73. J.L Bernal-Rusiel, D.N. Greve, M. Reuter, B. Fischl, M.R. Sabuncu, 2013. Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models. Neuroimage 66, 249-260.

II-13 Investigation of the pattern of the haemodynamic response as measured by fNIRS in newborns (less than a month old)

I. de Roevera, G. Balea, S. Mitrab, J. Meekb, N. J. Robertsonb and I. Tachtsidisa

a

Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom b Institute for Women’s Health, University College London, United Kingdom Corresponding author e-mail address: [email protected]

Abstract: The haemodynamic response to fNIRS is well-established in adults, with typically an observed increase in the concentration change of oxygenated haemoglobin (∆[HbO2]) and decrease in deoxygenated haemoglobin (∆[HHb]). However, functional studies in newborns have revealed a mixed haemodynamic response, particularly in regards with HHb, where both positive and negative responses are observed. The aim of this meta-analysis is to collate the findings from the literature to date that have employed fNIRS in term newborns less than 30 days old and identify potential reasons for this heterogeneity. Methods: Papers were identified using PubMed and Scopus, searching for a combination of keywords including (near-infrared spectroscopy | optical | tomography) and (neonate | newborn) and (functional activation | activation | evoked response). Term newborns less than 30 days old were deemed eligible for inclusion. Results: A total of 46 eligible studies were identified. The fNIRS parameters reported varied, with 45/46 studies reporting ∆[HbO2], 37/46 studies reporting ∆[HHb] and 14/46 studies reporting total haemoglobin concentration ∆[HbT] (=∆[HbO2] + ∆[HHb]). However, of the 37 studies reporting ∆[HHb] in graphs or tables, only 23 studies explicitly discuss the response (i.e. direction of change) of this variable. In total, 23 studies reported both ∆[HbO2] and ∆[HHb]. Figure 1 shows a summary of the reported haemodynamic changes from all eligible studies. Discussion: By reviewing this body of literature, we identified the most common response when both parameters are discussed is an increase in ∆[HbO2] and decrease or no change in ∆[HHb] (16/23 studies). The remaining studies reported either an increase (2/23) or varied (5/23) ∆[HHb]. No clear association between the response and stimulus type or instrumentation was identified here. The reason for this heterogeneity is unknown with potential explanations arising from differing physiology in the developing brain, or possibly differences in instrumentation or methodology.

Figure 1: Summary of haemodynamic responses in fNIRS studies in newborns. Changes in HbO2 shown in red, HHb in blue and HbT in black. The total number of studies (n) reporting each variable is stated. Direction of responses are indicated with an arrow or a line if no change; responses with a double arrow indicate a mixed response (both positive and negative changes observed). Size of arrows correspond to occurrence.

II-14 Hemodynamic Brain Activations during Rhythmic Finger Tapping: The effect of motor pacing on frontal HBO2 S. Guerina, M. Vincenta, C.I. Karageorghisb and Y. Delevoye-Turrella a

SCALab, UMR CNRS 9193, Department of psychology, University of Lille, Lille, France b Department of Life Sciences, Brunel University London, UK Corresponding author e-mail address: [email protected]

Abstract: This study aimed at highlighting the cerebral correlates involved in performing a finger tapping task under rhythmic constraints using functional near-infrared spectroscopy (fNIRS). We used a spatial-tapping motor task previously developed in our lab [1] and measured the changes in the hemoglobin responses (HbO2) in both frontal and motor areas. Methods: Three right-handed men (22.5 years) provided written informed consent. The HbO2 concentrations were collected using a continuous-wave fNIRS system (FOIRE-3000/16; Shimadzu) at three specific wavelengths: 780 nm, 805 nm and 830 nm. The source-detector was placed at a distance of 3 cm with a sampling frequency of 2.27 Hz. The participants were placed in front of a tactile screen on which was presented a visual figure, which consisted of 6 visual-targets placed around a virtual circle. The participants’ task was to tap each target at the tempo of a metronome that was set at 4 Hz (slow) or 8.3 Hz (fast). A total of 6 blocks of 60 s were performed at each speed, with random inter-blocks rests of 20 – 40 s [2]. Results: A systematic procedure of signal pre-processing was conducted (band-pass filter [0.01-0.2 Hz]. The quality of the signals collected in subjects with (haircuts < 0.5 cm) and without hair (Fig1) were contrasted to illustrate the need of further processing tools [3]. Once processed, the results indicated that a motor task performed at slow tempo increased the activities of the frontal areas of the brain (especially over the left hemisphere), confirming the role of cognitive control for the slowing of spontaneous motor pacing.

Figure 1. HbO2 concentration over the right frontal lobe in a participant with (left) and without (right) hair while performing the tapping task at a fast tempo.

References, acknowledgements: This study was supported by the French National Agency for Research (grant ANR-11-EQPX-0023) and the ERFD European grant “SCV-IrDive”. [1] Dione, M.& Delevoye-Turrell, Y. (2015). Arguments in favour of the coexistence of the two distinct timing modes of action control in a single taskperformedwith a unique effector: the spatial-tappingtask. HumanMovement Sciences (Volume 43, October 2015, Pages 45–60). [2] Obrig, H., Hirth, C., Junge-Hülsing ... & Villringer, A. (1997). In Oxygen Transport to Tissue XVIII (pp. 471-480). Springer, Boston, MA. [3] Tak, S., & Ye, J. C. (2014). Statistical analysis of fNIRS data: a comprehensive review. Neuroimage, 85, 72-91.

II-15 Seeing into the brain of an actor with fNIRS and mocap A. Hamilton1, P. Pinti1,2, D. Paoletti2, J.A. Ward2 1

Institute of Cognitive Neuroscience, Alexandra House, University College London

2

Department of Medical Physics and Biomedical Engineering, University College London Corresponding author e-mail address: [email protected]

Abstract: Wearable fNIRS gives us the potential to understand human social behavior outside the lab, but substantial challenges remain in the analysis and interpretation of real-world fNIRS data. In this project, we use actors in the theatre as a test-bed for examining repeatable, meaningful social interactions. We collect fNIRS data in conjunction with whole body motion capture (mocap) and aim to develop new recurrence-quantification methods that use the mocap data to reveal patterns of neural activation across a dynamic social interaction Methods: Two trained actors and one theatre director took part. Both actors wore full-body, inertial sensor-based mocap suits, from Perception Neuron, which capture the location of the head and limbs at 120Hz. One actor (B) wore an 16 channel fibreless fNIRS system (WOT, Hitachi) recording neural activity in prefrontal cortex at 5Hz. The recording took place in a 10x10 m ‘black box’ theatre space. The 20 minute recording session included control actions (reading lines / walking silently) and the performance of two short scenes from Shakespeare’s The Tempest: a) Miranda rejects Caliban’s advances, and b) where Caliban creeps behind Prospero and startles him. The actors perform each scene 3 times, then swap roles and play again for 3-6 repetitions. Data analysis: fNIRS data was filtered, corrected for motion artifacts, downsampled and converted to a neural activation signal with the CBSI transform. Mocap data was filtered and converted to motion energy signals for 6 features (head, hips, 2 hands, 2 feet) for each actor across the 1000 second experimental time course. Each possible 8 second sample of mocap data was correlated against each possible 8 second window in the remaining mocap data to create a recurrence plot (Fig 1A). Diagonal yellow patterns in this plot indicate when the actors repeatedly performed the same scene and match the video annotations (red lines). The centre of each repeated pattern (pink / black dots) was taken as the centre of each critical event, and fNIRS data were then averaged over the 8 seconds before and after this event. This gives a mocapdefined image of the fNIRS signal in each repeated scene performed by the actors (Fig 1B). Discussion: These data show that meaningful fNIRS data can be recorded in the context of theatre. Critically, wholebody motion capture of actors allowed us to implement a datadriven analysis of the fNIRS data and visualise the cognitive events taking place in the actor’s brain.

II-16 Diffuse optical parameterization of cerebral autoregulation in healthy adults L. Kobayashi Friska, C. Gregori Plaa, F. Marucciab, T. Durdurana,c and JM. Kainerstorferd a

ICFO -Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels (Barcelona), SPAIN; b Neurotraumatology and Neurosurgery Research Unit (UNINN), Vall d’Hebron University Research Institute (VHIR), Universidad Autònoma de Barcelona, SPAIN; c Institució Catalana de Recerca I Estudis Avançats (ICREA), 08015 Barcelona, SPAIN; d Department of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 Corresponding author e-mail address: [email protected] Background: Cerebral autoregulation (CAR) is the mechanism which regulates cerebral blood flow (CBF) despite changes in arterial blood pressure (ABP), or more accurately cerebral perfusion pressure, through vasomotor effects. CBF recovery in response to a dynamic change in ABP has been shown to be a measure of CAR, where the CBF recovery time is indicative of the autoregulation efficiency [1]. Transcranial Doppler (TCD) measurements during thigh cuff inflation and deflation have shown that hypocapnia can improve CAR [1]. However, TCD measures non-local macrovascular blood flow. Here we present an all optical method using diffuse correlation spectroscopy (DCS) to measure CAR in the local microvasculature. Methods and Discussion: Thigh cuff occlusion experiments were conducted on healthy adult volunteers (n = 8) according to the protocol by Aaslid [1]. During two-minute thigh cuff occlusions at 200 mmHg subjects were asked to breath normally, followed by another thigh cuff occlusion with hyperventilation at 20 breaths per minute. Beat to beat blood pressure (Finapres Medical Systems) and CBF were measured simultaneously, where CBF was measured with DCS probes placed bilaterally on the subjects’ foreheads. A representative case of CBF and ABP response to thigh cuff release is seen in Figure 1.

Figure 1: Example of CBF and ABP changes in response to thigh cuff occlusion during normal breathing and hyperventilation. Time traces of CBF and ABP changes were parameterized using a modified double exponential function. Optical measurements using DCS have previously been reported [2], however we will present the effect of hypocapnia on CAR as seen from the results of this parametrization. References: 1. Aaslid et.al. Stroke, 1989 2. Parthasarathy et.al. JCBFM, 2017

II-17 Global Low frequency oscillations in fNIRS - mapping systemic signals using a specifically designed multimodal probe L.M. Hockea,b, K. Cayetanoa,b, Y. Tonga,b, B.deB. Fredericka,b a b

McLean Imaging Center, McLean Hospital, Belmont, MA 02478, USA;

Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA Corresponding author e-mail address: [email protected]

Abstract: fNIRS has become increasingly popular for the study of brain function. However

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neuronal signals are contaminated by the blood signals from extra-cerebral layers1,2 and systemic physiological noise3. The purpose of this study is to elucidate the influence of systemic physiological noise on fNIRS using high resolution fMRI data. 10 subjects were measured with our multimodal fMRI/fNIRS probe4 (Figure 1a) during resting state, mental subtraction and rapid semantic tasks. fMRI (Siemens Trio 3T, 1.8cm isotropic voxels, TR=0.72) data was acquired with fNIRS (ISS Imagent, 6.25 Hz) probes (3-4cm source-detector distance) directly integrated into the design. Data analysis was conducted in MATLAB (for fNIRS) and FSL (for fMRI) as well as in house Python software (RapidTiDe)5,6. LFO signals extracted from voxels in the vasculature in fMRI were used to evaluate the global LFOs in the fNIRS signal. We found high correlation between the global LFOs and the fNIRS signal (Figure 1b). In addition the fNIRS signal was highest correlated to regions in the brain, which are highly vascularized (Figure 1c,d) with less influence of superficial layers than the global LFOs within the grey matter (Figure 1d).

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II-18 Young adults with high IQ shows a faster peak of brain hemodynamic activity during a cognitive control task: a fNIRS experiment. Costa DSa, de Paula JJa, Mesquita RCb, Miranda DMa, Romano-Silva MAa a - Universidade Federal de Minas Gerais, Faculdade de Medicina, Belo Horizonte, Brazil. b – Universidade Federal de Campinas, Instituto de Física, Campinas, Brazil Corresponding author e-mail address: [email protected] Introduction: the pattern of brain activity underlying cognitive control tasks is relatively known in terms of which brain regions contribute to the tasks. Prefrontal and premotor areas, as well as the superior parietal lobes, are highly associated with cognitive control tasks, including the n-back paradigm. However, less is known about how the hemodynamic activity of those brain regions correlates with cognitive performance. Researchers have proposed brain efficiency models where subjects with higher general cognitive skills (such as intelligence, measured by IQ tests) may demand less neurobiological resources for information processing, showing a faster and more concentrated pattern of brain activity. Objective: we tested if young adults with very high IQ and young adults with average/above average IQ may present differences in brain hemodynamic activity during an n-back test. Methods: 26 young adults with no psychiatric or neurological disorder were submitted to the n-back test during functional near-infrared spectroscopy (fNIRS). They were divided into two groups according to IQ, measured by the WMT-II test (a non-verbal fluid IQ test): those with above 120 (n=12) and those between 100 and 119 IQ (n=14). Cortical activity was assessed from the cortical hemodynamic response generated by the cognitive task using continuouswave fNIRS equipment (NIRScout Tandem 1616, NIRx Medical Technologies, Glen Head, USA). Probes were distributed on the dorsolateral prefrontal cortex and the superior parietal lobe, bilaterally. Four hemodynamic measures were developed using a region of interest approach: left/right frontal regions (LF, RF) cortex and left/right parietal regions (LP, RP). For each region, we analyzed hemodynamic data considering average time (across multiple blocks) for oxyhemoglobin reaches its highest peak during the cognitive task. We used ANOVA to compare both groups. Results: we found significant group differences in the RF (p=0.014, d=1.18) and RP (p=0.017, d=1.11) regions of interest during the 0-back condition. No other comparison was statistically significant, although statistical trends were observed in the LF during 0-back (p=0.084) and 2back (p=0.068) conditions. To further investigate the associations between hemodynamic activity and performance, we performed Spearman correlations with all hemodynamic data with the time and errors during the n-back test. The procedure was conducted independently in both groups. The median of shared variance between hemodynamic activity and cognitive performance was higher in the High IQ group than the Average IQ group in the 0-back condition (14% x 6%), 1-back condition (19% x 11%) and 2-back condition (16% x 9%) Conclusion: faster peaks of hemodynamic activity during cognitive control were observed in participants with higher IQ. In this group, we found a more strong and consistent association between hemodynamic activity and cognitive performance.

II-19 Investigation of use of Sample Entropy in fNIRS to infer brain functional activation Perpetuini D.a, Pinti P.b, Merla A.a, Tachtsidis I.b ITAB–Institute for Advanced Biomedical Technologies, University G. d’Annunzio, Chieti, Italy Department of Medical Physics and Biomedical Engineering, University College London, UK

a b

Corresponding author email address: [email protected] Abstract: Sample Entropy (SampEn) [1] is a widely used technique for neuroimaging signals analysis, especially to discriminate between the healthy and diseased brain [2]. SampEn is the negative natural logarithm of the conditional probability that two sequences similar for m points remain similar at the next [1]. However, questions regarding how to interpret SampEn results in certain clinical applications and its relationship to cortical activation are still an open issue. Motivation: the aim of this work is to characterize SampEn for fNIRS data analysis and its relationship to cortical activation. Methods: SampEn was computed on both (1) syntetic and (2) real experimental fNIRS data. (1) Synthetic fNIRS signals were generated by adding Hemodynamic Response Functions (HRFs) with different amplitudes and simulating both block and ecological event related protocols to resting state real fNIRS data recorded on 44 healthy participants over the prefrontal cortex [3]. (2) Real experimental fNIRS signals were collected over the visual cortex in 8 healthy participants during a block designed visual stimulation. The signals were analyzed using both the General Linear Model (GLM) and SampEn approaches. Results: (1) Using a paired t-test, it was assessed that the introduction of synthetic HRFs to resting state fNIRS signals collected over prefrontal cortex produced a significant decrease in the SampEn values for oxyhemoglobin (HbO) (pASD, p≈0.01; left superior temporal gyrus and left middle temporal gyrus, TD>ASD, p=0.04; Left superior frontal gyrus and left middle frontal gyrus, p=0.04; and also single channels located at left middle frontal gyrus p=0.03 and right inferior frontal gyrus - pars opercularis p=0.04. b) Rotation: only a single channel located at left superior frontal gyrus, TD>ASD, p = 0.049. Conclusion: Our preliminary results suggest that between-group differences are evident in brain areas associated with biological motion perception in typical individuals noted in previous research to be atypically activated in children with ASD. Observed differences seem more specific to biological motion than general motion response and point to extensive bilateral involvement in neural circuitry involved in the processing of biological movements.

Figure 1: Group mean Oxy-Hb hemodynamic responses in ASD and TD participants overlaid over brain surface for biological motion. The color bar indicates the scale of the concentration change in μM units.

References: [1] A. Krakowski, 2014, Biological motion processing in typical development and in the autism spectrum, PhD thesis, City University of New York, USA. [2] C. M. Freitag, et al., 2008, Perception of biological motion in autism spectrum disorders, Neuropsychologia, Vol 46, pp. 1480–1494.

II-72 Progression of cerebral perfusion and metabolism in neonatal hypoxic-ischaemic encephalopathy G.Bale1, N.Taylor1, S.Mitra2, I.de Roever1, A.Sudakou3, J.Meek2, N.Robertson2, I.Tachtsidis1 1

Medical Physics and Biomedical Engineering, University College London, UK 2 Institute of Women’s Health, University College London, UK 3 Nalecz Institute of Biocybernetics and Biomedical Engineering, Poland Corresponding author e-mail address: [email protected]

Introduction: During hypoxic-ischaemic encephalopathy, there are significant fluctuations in cerebral perfusion as the injury evolves; including hypoperfusion during the latent phase immediately after hypoxia-ischaemia and during therapeutic hypothermia, and hyperperfusion after rewarming1,2. Methods: We used broadband near-infrared spectroscopy (NIRS) to monitor cerebral blood flow (CBF) and metabolism (via oxidation state of cytochrome-c-oxidase, oxCCO) in 64 term neonates with hypoxic-ischaemic encephalopathy (HIE) in the first days of life3. During monitoring, spontaneous oxygen desaturation events were common. CBF was calculated from the NIRS cerebral oxygenation data (HbD = oxyhaemoglobin - deoxyhaemoglobin) combined with arterial saturation (SpO2) during desaturation events using a method based on Fick’s Law4. Results: CBF was calculated from 385 eligible events in 47 neonates (see Table 1). Figure 1 shows the weighted mean of CBF in babies with different levels of HIE over the first 5 days of life (therapeutic hypothermia on days 1-3, rewarming on day 4). The CBF was stable (p>0.05) across all days in moderate injury (thalamic Lac/NAA