Doctoral Research Seminar on "Feedback Gains modulate with Internal Model Uncertainty" by Dr. Sae Franklin, ICS.
Title: Feedback Gains modulate with Internal Model Uncertainty
Abstract: When humans experience large initial errors during adaptation to novel dynamics, visuomotor feedback gains are upregulated. We proposed that this increase is due to the increased internal model uncertainty (1,2). That is, when we experience large errors, we have increased uncertainty in our ability to predict the environment, and therefore upregulate feedback gains and co-contraction as a coping mechanism. This initial increase in reactive feedback gains gradually decreases as both feedforward muscle activation and predictive feedback gains are gradually tuned to provide adaptation to these novel dynamics (2). While our theory suggests that internal model uncertainty drives these increases in visuomotor feedback gains, one possibility is that it is simply the presence of the visual error signal itself that drives these changes. Here, we test this directly by having participants adapt to both abrupt and gradual changes in dynamics, similar to our previous work (2), but in the absence of online visual error signals. The absence of visual error information suppressed the visuomotor feedback gains, but the pattern of adaptation throughout the experiments was identical. This suggests that the overall changes in reactive and predictive feedback gains are driven not just by visual error signals but underlying internal model uncertainty. The lack of visual error information inhibited the visuomotor feedback gains and increased co-contraction, demonstrating that visuomotor feedback responses are independent from the level of co-contraction. Our result suggests that the visual feedback benefits motor adaptation tasks, however if unavailable, we can learn the same dynamics, but often with higher levels of muscle activation and therefore energy expenditure. We have demonstrated a direct connection between learning and predictive visuomotor feedback gains, independent from the visual error signals. Overall, we provide further evidence of our hypothesis that internal model uncertainty drives initial increases in feedback gain modulation.
1. Franklin S, Wolpert DM, Franklin DW (2012) J Neurophysiol 108(2): 468-478
2. Franklin S, Franklin DW (2021) NBDT Vol.5 Issue 2 DOI: 10.51628/001c.22336
November 22, 2021 at 11:00-12:00 online. Please get in touch with the organiser, if you wish to attend.