The variable monitored by the CNS to continuously optimize walking: energy cost or perception of effort? Samuele Marcora, University of Kent, England (
[email protected]) In this paper, Selinger et al. (2015) present findings in support of the hypothesis that energetic cost minimization is a control objective of the central nervous system (CNS) during locomotion. In the press release, the authors argue that their study provides a physiological basis for “laziness” by demonstrating that even within a well--rehearsed movement like walking, the CNS subconsciously monitors energy use and continuously reoptimizes movement patterns in a constant quest to move as cheaply as possible. Here I would like to propose an alternative psychobiological hypothesis: a control objective of the CNS during locomotion is minimization of perceived exertion, defined as the conscious sensation of how hard, heavy and strenuous a physical task is. This proposal is in accordance with the “principle of least effort” which has been applied to a variety of natural and social phenomena. This psychobiological hypothesis is supported by several findings. For example, humans choose to start running at about 2.067 m/sec even if, at the same speed, walking requires significantly less energy and would be the obvious choice if energetic cost minimization was the main control objective of the CNS during locomotion. The most likely explanation is that, at 2.067 m/sec, running feels much easier than walking (Hreljac, 1993). Similarly, when cycling at about 200W, humans choose a cadence that is higher (about 80 revolutions per min, RPM) than the cadence (50 RPM) at which energy expenditure is minimized. Again the most likely explanation is that perceived exertion at 80 RPM is significantly lower than perceived exertion at 50 RPM (Whitty et al., 2009). It is therefore plausible that, in the study by Selinger and colleagues, the step frequency chosen in the normal, penalize-high, and penalize-low conditions was the one perceived as the least effortful in each condition. As I will discuss later, the fact that the chosen step frequency was also optimal from a bioenergetic point of view may have been a (very important) coincidence. Importantly, a control system based on perceived exertion can also explain why people can adapt their step frequency in real time. Contrary to widespread belief, perception of effort is not generated by central processing of sensory signals produced by interoceptors (Marcora, 2009). There is now solid neurophysiological evidence suggesting that perception of effort is generated by central processing of corollary discharges (de Morree et al., 2012; Zénon et al., 2015). These are sensory signals produced by premotor areas of the brain when a central motor command is sent to the active skeletal muscles. Unlike the relatively slow sensory signals produced by interoceptors that monitor blood gases and muscle metabolites, corollary discharges change as fast as central motor command. Therefore, when central motor command is quickly adjusted to compensate for changes in resistive torque, perception of effort changes accordingly and triggers an automatic or deliberate response to adjust step frequency so that walking requires the least possible effort. This effort-based decision-making is based on learning how perceived exertion changes according to step frequency in each of the three conditions. In my opinion, this learning could have occurred in a few minutes during the “exploration period”, and it was used by the CNS to adjust step frequency in a few seconds during the “second adaptation” and “cost mapping” periods.
An interesting question is why we seem to have a control system based on the conscious sensation of effort instead of one based on subconscious monitoring of energy use. One possible answer is that humans don’t have interoceptors that can provide valid information to the CNS about energy use. For example, during prolonged whole-body exercise at moderate intensity, lots of energy is used despite no significant changes in blood gases sensed by central chemoreceptors (e.g., arterial CO2) or muscle metabolites sensed by Group III and IV afferents (e.g., lactic acid). Furthermore, blood gases and muscle metabolites can change greatly even without any physical activity (e.g., altitude and muscle ischemia). On the contrary, it is impossible to naturally produce skeletal muscle contractions that consume significant amounts of energy (i.e., whole-body physical activity) without central motor command. Therefore, a conscious sensation associated with central motor command seems a “good enough solution” to limit energy use. This hypothesis is supported by the fact that perception of effort increases with both intensity and duration of whole-body exercise (Kearon et al., 1991) and that perception of effort limits exercise performance (Marcora and Staiano, 2010). Although perceived exertion is not a direct measure of energy expenditure, the aversive nature of effort can dissuade people from whole-body physical activity (and related energy expenditure) when there are no pressing reasons for being active (e.g., to procure food or defend one’s family from enemies). In the prehistoric environment where energy from food was not always readily available, wasting energy via unnecessary physical activity may have reduced survival. So it is not hard to see how perception of effort may have evolved. The role of perception of effort in limiting energy expenditure is also supported by the finding that modern humans report perceived exertion as one of the main barriers to regular exercise in an environment where physical activity is no longer required for immediate survival (Bauman et al., 2012). Therefore, further research on perception of effort and effort-based decision-making will help not only to understand how humans and other animals regulate their locomotion. It may also help solving the physical inactivity pandemic that is prematurely killing millions of people around the world. References Bauman, A. E., Reis, R. S., Sallis, J. F., Wells, J. C., Loos, R. J., Martin, B. W., & Lancet Physical Activity Series Working Group. (2012). Correlates of physical activity: why are some people physically active and others not?. The lancet, 380(9838), 258-271. de Morree, H. M., Klein, C., & Marcora, S. M. (2012). Perception of effort reflects central motor command during movement execution. Psychophysiology, 49(9), 1242-1253. Hreljac, A. L. A. N. (1993). Preferred and energetically optimal gait transition speeds in human locomotion. Medicine and Science in Sports and Exercise, 25(10), 1158-1162. Kearon, M. C., Summers, E., Jones, N. L., Campbell, E. J., & Killian, K. J. (1991). Effort and dyspnoea during work of varying intensity and duration. European Respiratory Journal, 4(8), 917-925. Marcora, S. (2009). Perception of effort during exercise is independent of afferent feedback from skeletal muscles, heart, and lungs. Journal of applied physiology, 106(6), 2060-2062. Marcora, S. M., & Staiano, W. (2010). The limit to exercise tolerance in humans: mind over muscle?. European journal of applied physiology, 109(4), 763-770.
Selinger, J. C., O’Connor, S. M., Wong, J. D., & Donelan, J. M. (2015). Humans Can Continuously Optimize Energetic Cost during Walking. Current Biology, in press. Whitty, A. G., Murphy, A. J., Coutts, A. J., & Watsford, M. L. (2009). Factors associated with the selection of the freely chosen cadence in non-cyclists. European journal of applied physiology, 106(5), 705-712. Zénon, A., Sidibé, M., & Olivier, E. (2015). Disrupting the Supplementary Motor Area Makes Physical Effort Appear Less Effortful. The Journal of Neuroscience, 35(23), 8737-8744.
