Reward gain model describes cortical use-dependent plasticity

Firas Mawase, Nicholas Wymbs, Shintaro Uehara, Pablo A Celnik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Consistent repetitions of an action lead to plastic change in the motor cortex and cause shift in the direction of future movements. This process is known as use-dependent plasticity (UDP), one of the basic forms of the motor memory. We have recently demonstrated in a physiological study that success-related reinforcement signals could modulate the strength of UDP. We tested this idea by developing a computational approach that modeled the shift in the direction of future action as a change in preferred direction of population activity of neurons in the primary motor cortex. The rate of the change follows a modified temporal difference reinforcement learning algorithm, in which the learning policy is based on comparison between what reward the population experiences on a particular trial, and what it had expected on the basis of its previous learning. By using this model, we were able to characterize the nature of learning and retention of UDP. Exploring the relationship between reinforcement and UDP constitutes a crucial step toward understanding the basic blocks involved in the formation of motor memories.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5-8
Number of pages4
Volume2016-October
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
CountryUnited States
CityOrlando
Period8/16/168/20/16

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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    Mawase, F., Wymbs, N., Uehara, S., & Celnik, P. A. (2016). Reward gain model describes cortical use-dependent plasticity. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 (Vol. 2016-October, pp. 5-8). [7590626] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2016.7590626