Recurrent Network Models of Sequence Generation and Memory.

TitleRecurrent Network Models of Sequence Generation and Memory.
Publication TypeJournal Article
Year of Publication2016
AuthorsRajan, K, Harvey, CD, Tank, DW
JournalNeuron
Volume90
Issue1
Pagination128-42
Date Published2016 06 03
ISSN1097-4199
KeywordsAlgorithms, Animals, Choice Behavior, Decision Making, Memory, Short-Term, Mice, Models, Neurological, Neural Pathways, Neurons, Parietal Lobe
Abstract

Sequential activation of neurons is a common feature of network activity during a variety of behaviors, including working memory and decision making. Previous network models for sequences and memory emphasized specialized architectures in which a principled mechanism is pre-wired into their connectivity. Here we demonstrate that, starting from random connectivity and modifying a small fraction of connections, a largely disordered recurrent network can produce sequences and implement working memory efficiently. We use this process, called Partial In-Network Training (PINning), to model and match cellular resolution imaging data from the posterior parietal cortex during a virtual memory-guided two-alternative forced-choice task. Analysis of the connectivity reveals that sequences propagate by the cooperation between recurrent synaptic interactions and external inputs, rather than through feedforward or asymmetric connections. Together our results suggest that neural sequences may emerge through learning from largely unstructured network architectures.

DOI10.1016/j.neuron.2016.02.009
Alternate JournalNeuron
PubMed ID26971945
PubMed Central IDPMC4824643
Grant List1U01NS090541-01 / NS / NINDS NIH HHS / United States
R01-MH083686 / MH / NIMH NIH HHS / United States
R01-NS089521 / NS / NINDS NIH HHS / United States
R01 MH083686 / MH / NIMH NIH HHS / United States
RC1-NS068148 / NS / NINDS NIH HHS / United States
RC1 NS068148 / NS / NINDS NIH HHS / United States
U01 NS090541 / NS / NINDS NIH HHS / United States
R01-MH107620 / MH / NIMH NIH HHS / United States
R01 MH107620 / MH / NIMH NIH HHS / United States
R01 NS089521 / NS / NINDS NIH HHS / United States