Sign in
NeuroscienceJournal of Neurophysiology
Peer-reviewed journal article

Increasing the gradient of energetic cost does not initiate adaptation in human walking

Surabhi N. SimhaiD, Jeremy D. WongiD, Jessica C. SelingeriD, Sabrina J. AbramiD, J. Maxwell DonelaniD

Abstract

When in a new situation, the nervous system may benefit from adapting its control policy. In determining whether or not to initiate this adaptation, the nervous system may rely on some features of the new situation. Here we tested whether one such feature is salient cost savings. We changed cost saliency by manipulating the gradient of participants energetic cost landscape during walking. We hypothesized that steeper gradients would cause participants to spontaneously adapt their step frequency to lower costs. To manipulate the gradient, a mechatronic system applied controlled fore-aft forces to the waist of participants as a function of their step frequency as they walked on a treadmill. These forces increased the energetic cost of walking at high step frequencies and reduced it at low step frequencies. We successfully created three cost landscapes of increasing gradients, where the natural variability in participants step frequency provided cost changes of 3.6% (shallow), 7.2% (intermediate) and 10.2% (steep). Participants did not spontaneously initiate adaptation in response to any of the gradients. Using metronome-guided walking-- a previously established protocol for eliciting initiation of adaptation--participants next experienced a step frequency with a lower cost. Participants then adapted by -1.41{+/-}0.81 (p=0.007) normalized units away from their originally preferred step frequency obtaining cost savings of 4.80{+/-}3.12%. That participants would adapt under some conditions, but not in response to steeper cost gradients, suggests that the nervous system does not solely rely on the gradient of energetic cost to initiate adaptation in novel situations.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
10
FWCI
0.66
Field percentile
top 37%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSimha '19Jin '26Abram '19Sánchez '20Selinger '19Sánchez '19
74% semantic matchNeuroscience
Surabhi N. Simha, Jeremy D. Wong, Jessica C. Selinger+1 more·IEEE Transactions on Neural Systems and Rehabilitation Engineering·May 17, 2019· 18 citations