A gain-field encoding of limb position and velocity in the internal model of arm dynamics

Eun Jung Hwang, Opher Donchin, Maurice A. Smith, Reza Shadmehr

Research output: Contribution to journalArticlepeer-review

95 Scopus citations

Abstract

Adaptability of reaching movements depends on a computation in the brain that transforms sensory cues, such as those that indicate the position and velocity of the arm, into motor commands. Theoretical consideration shows that the encoding properties of neural elements implementing this transformation dictate how errors should generalize from one limb position and velocity to another. To estimate how sensory cues are encoded by these neural elements, we designed experiments that quantified spatial generalization in environments where forces depended on both position and velocity of the limb. The patterns of error generalization suggest that the neural elements that compute the transformation encode limb position and velocity in intrinsic coordinates via a gain-field; i.e., the elements have directionally dependent tuning that is modulated monotonically with limb position. The gain-field encoding makes the counterintuitive prediction of hypergeneralization: there should be growing extrapolation beyond the trained workspace. Furthermore, nonmonotonic force patterns should be more difficult to learn than monotonic ones. We confirmed these predictions experimentally.

Original languageEnglish
JournalPLoS Biology
Volume1
Issue number2
DOIs
StatePublished - 1 Dec 2003
Externally publishedYes

ASJC Scopus subject areas

  • General Neuroscience
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences

Fingerprint

Dive into the research topics of 'A gain-field encoding of limb position and velocity in the internal model of arm dynamics'. Together they form a unique fingerprint.

Cite this