Impact Factor 2.073

The world's most-cited Neurosciences journals

Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Comput. Neurosci. | doi: 10.3389/fncom.2018.00083

Task-related synaptic changes localized to small neuronal population in recurrent neural network cortical models

  • 1Center for Brain Science, RIKEN, Japan
  • 2Center for Brain Science, RIKEN, Japan

Humans have flexible control over cognitive functions depending on the context. Several studies suggest that the prefrontal cortex (PFC) controls this cognitive flexibility, but the detailed underlying mechanisms remain unclear. Recent developments in machine learning techniques allow simple PFC models written as a recurrent neural network to perform various behavioral tasks like humans and animals. Computational modeling allows the estimation of neuronal parameters that are crucial for performing the tasks, which cannot be observed by biologic experiments. To identify salient neural-network features for flexible cognition tasks, we compared four PFC models using a context-dependent integration task. After training the neural networks with the task, we observed highly plastic synapses localized to a small neuronal population in all models. In three of the models, the neuronal units containing these highly plastic synapses contributed most to the performance. No common tendencies were observed in the distribution of synaptic strengths among the four models. These results suggest that task-dependent plastic synaptic changes are more important for accomplishing flexible cognitive tasks than the structures of the constructed synaptic networks.

Keywords: recurrent neural network, plasticity, Synaptic weight, sparseness, cognitive flexibility, Prefrontal Cortex

Received: 13 May 2018; Accepted: 12 Sep 2018.

Edited by:

Omri Barak, Technion – Israel Institute of Technology, Israel

Reviewed by:

Guangyu Robert Yang, Columbia University, United States
Vishwa Goudar, New York University, United States  

Copyright: © 2018 KUROKI and Takuya. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. SATOSHI KUROKI, RIKEN, Center for Brain Science, 2-1, Hirosawa, Wako, Saitama, 351-0198, Japan, s.kuroki@brain.riken.jp