Self-regulation of Broca’s Area using Real-time Functional MRI in Stroke Patients with Expressive Aphasia Study Hypothesis & Methodology Sujesh S1, Anuvitha C1, Arathy J.S1, Annamma George, Sylaja P.N1, Kesavadas C1, Ranganatha S2,3,1 1Sree
Chitra Tirunal Institute for Medical Sciences & Technology, Trivandrum, INDIA
[email protected] *
HYPOTHESIS
2Department
of Biomedical Engineering, University of Florida, Gainesville, USA 32611
[email protected]
3The
Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen, Germany.
RT fMRI BASED NEUROFEEDBACK SYSTEM
• Patients with expressive Aphasia can learn to self-regulate (up regulate) the BOLD signal in Broca’s Area with real-time fMRI neurofeedback of a correlated BOLD signal from the Broca’s as well as Wernicke’s areas.
PATIENT SELECTION • 6 study and 6 control patients, a period between six weeks and six months post stroke. • Patients diagnosed with expressive aphasia (Broca’s) only ,comprehension is relatively preserved. • Protocol approved by the ethics committee of the institute, requires an informed consent
• Acquired up-regulation will lead to an improvement in expression of language (OR amelioration of expressive Aphasia)
FUNCTIONAL LOCALIZER
INTRODUCTION Functional MRI (fMRI) images the blood oxygen level dependent signal from the brain (BOLD). fMRI could be used to obtain signals from both cortical and sub-cortical brain regions, thus being able to image whole brain. Prominent among them are brain mapping of visual, auditory, motor and cognitive functions such as language, memory and emotion; and clinical imaging for locating regions affected by neurological diseases such as schizophrenia, epilepsy, and stroke. Real-time fMRI (RT fMRI) allows generation of brain activity information from the MR scans in a time period of 1-3 seconds. Advances in computing and faster image processing algorithms enable completion of the processing of image data within shorter time periods to generate the maps of brain activity. This data can then be fed back to the person being scanned to form a neurofeedback loop which has shown promising results for selfregulation of BOLD activity in specific brain regions. Further the brain activity data can be used for brain state classification for developing brain computer interfaces (BCI) for communication and control.
• Word generation task with a starting alphabet • To identify the Broca’s and Wernicke’s areas
PATIENT SESSIONS Patient Sessions
RT fMRI Session (pre/post/training)
Pre-training test session
Anatomical Scan
Training Sessions x 4
Functional Localizer
Post-training test session
RT fMRI runs X4
SPM RESULTS FOR PILOT RUN (L) AND PATIENT RUN (R) – SPM MAP, DESIGN, FITTED RESPONSE
TABLE 1: RESPONSE DURING NAMING TASK – POST BASELINE AND POST UP-REGULATION EPOCHS
METHODOLOGY
Time to Response
• Real-time fMRI - 1.5 T Siemens Avanto MRI Scanner - EPI Sequence, TR of 1.5s, 16 slices, 64 x 64 voxels, Size: 3 x 3 x 6 mm3; 216 volumes - Structural image (high resolution FLAIR) - Each scan exported from MR workstation to BCI computer by LAN
RESULTS
TBV SCREEN SHOT INDICATING ROIS
N Mean (seconds) Std dev
• Neurofeedback - Visual feedback of mean BOLD activity (BI) in chosen RoIs by means of a thermometer display. BI ( RoI 1 RoI 2 ) *{1 corr ( RoI1 , RoI 2 )} *Dr. C. Kesavadas, Professor of Radiology, Department of Imaging Sciences and Interventional Radiology, SCTIMST, Trivandrum – 695011. Kerala. INDIA. Email:
[email protected] Acknowledgment: We thank the Department of Biotechnology, Government of India for funding this project. We also thank the Department of Science & technology, Government of India for funding the travel of Dr. Sitaram Ranganatha under the CP-STIO scheme.
Pilot 1
Post Rest
Post Upregulation
Post Rest
Post Upregulation
14
14
12
12
1.98
2.32
1.99
2.00
0.56
0.69
0.41
0.55
T stat T crit (p
