The impact of sparsity in low-rank recurrent neural networks.

The impact of sparsity in low-rank recurrent neural networks.

Neural population dynamics are often highly coordinated, allowing task-related computations to be understood as neural trajectories through low-dimensional subspaces. How the network connectivity and input structure give rise to such activity can be investigated with the aid of low-rank recurrent ne...

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Bibliographic Details
Main Authors:	Elizabeth Herbert, Srdjan Ostojic
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2022-08-01
Series:	PLoS Computational Biology
Online Access:	https://doi.org/10.1371/journal.pcbi.1010426

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