Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

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H Francis Song; Guangyu R Yang; Xiao-Jing Wang;
(2016)
  • Publisher: Public Library of Science
  • Journal: PLoS Computational Biology, volume 12, issue 2 (issn: 1553-734X, eissn: 1553-7358)
  • Publisher copyright policies & self-archiving
  • Identifiers: doi: 10.1371/journal.pcbi.1004792, pmc: PMC4771709
  • Subject: Computational Biology | Single Neuron Function | Research Article | Cognitive Psychology | Memory | Anatomy | Neural Networks | Learning | Computational Neuroscience | Neurons | Artificial Intelligence | Neural Pathways | Psychology | Working Memory | Cellular Types | Biology and Life Sciences | Cognition | Computer and Information Sciences | Neuroscience | Animal Cells | Machine Learning | QH301-705.5 | Cell Biology | Nervous System | Learning and Memory | Social Sciences | Decision Making | Neuroanatomy | Medicine and Health Sciences | Cognitive Neuroscience | Biology (General) | Cognitive Science

The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles... View more
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