Optimizing effort: Increased efficiency of motor memory with time away from practice

Sarah E. Pekny, Reza Shadmehr

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


In motor tasks, efficiency can be measured via the commands that are produced to accomplish a goal. To maximize efficiency, the nervous system should produce task-relevant motor commands while avoiding behaviors that are task-irrelevant. The current view is that this is achieved through training, i.e., the optimum motor commands are learned by trial and error. However, in contrast to this view, there are numerous examples in which during an experiment, task-irrelevant commands are continuously produced. To address this, we trained human volunteers to reach in a force field. With practice, they learned to produce forces that compensated for the field, generating taskrelevant commands that were necessary to achieve success. As expected, training also resulted in generalization, the transfer of learning to other movements. We designed the task so that any forces produced as a result of generalization were unnecessary and therefore taskirrelevant. Importantly, there were no explicit cues to indicate that production of these forces was task-irrelevant. Rather, the only indicator was effort itself. Could this inefficiency of the motor commands be reduced? We found that even with extensive practice, the production of task-irrelevant forces persisted. However, if subjects were given sufficient time away from practice (6 or 24 h but not 3 or 30 min), they spontaneously reduced production of the task-irrelevant forces. Therefore, practice alone was insufficient to allow for increased efficiency of motor output. Time away from practice was a required element for optimization of effort.

Original languageEnglish (US)
Pages (from-to)445-454
Number of pages10
JournalJournal of neurophysiology
Issue number2
StatePublished - Jan 15 2015


  • Generalization
  • Long-term training
  • Motor learning

ASJC Scopus subject areas

  • General Neuroscience
  • Physiology


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