Towards the next generation of recurrent network models for cognitive neuroscience

Curr Opin Neurobiol. 2021 Oct;70:182-192. doi: 10.1016/j.conb.2021.10.015. Epub 2021 Nov 26.

Abstract

Recurrent neural networks (RNNs) trained with machine learning techniques on cognitive tasks have become a widely accepted tool for neuroscientists. In this short opinion piece, we discuss fundamental challenges faced by the early work of this approach and recent steps to overcome such challenges and build next-generation RNN models for cognition. We propose several essential questions that practitioners of this approach should address to continue to build future generations of RNN models.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Cognition
  • Cognitive Neuroscience*
  • Models, Neurological*
  • Neural Networks, Computer