Split-belt treadmill adaptation shows different functional networks for fast and slow human walking

Erin V.L. Vasudevan, Amy J. Bastian

Research output: Contribution to journalArticlepeer-review

63 Scopus citations


New walking patterns can be learned over short time scales (i.e., adapted in minutes) using a split-belt treadmill that controls the speed of each leg independently. This leads to storage of a modified motor pattern that is expressed as an aftereffect in regular walking conditions and must be de-adapted to return to normal. Here we asked whether the nervous system adapts a general walking pattern that is used across many speeds or a specific pattern affecting only the two speeds experienced during split-belt training. In experiment 1, we tested three groups of healthy adult subjects walking at different split-belt speed combinations and then assessed aftereffects at a range of speeds. We found that aftereffects were largest at the slower speed that was used in split-belt training in all three groups, and it decayed gradually for all other speeds. Thus adaptation appeared to be more strongly linked to the slow walking speed. This result suggests a separation in the functional networks used for fast and slow walking. We tested this in experiment 2 by adapting walking to split belts and then determining how much fast regular walking washed out the slow aftereffect and vice versa. We found that 23-38% of the aftereffect remained regardless of which speed was washed out first. This demonstrates that there is only partial overlap in the functional networks coordinating different walking speeds. Taken together, our results suggest that there are some neural networks for controlling locomotion that are recruited specifically for fast versus slow walking in humans, similar to recent findings in other vertebrates.

Original languageEnglish (US)
Pages (from-to)183-191
Number of pages9
JournalJournal of neurophysiology
Issue number1
StatePublished - Jan 2010

ASJC Scopus subject areas

  • General Neuroscience
  • Physiology


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