Residual dynamics resolves recurrent contributions to neural computation

Relating neural activity to behavior requires an understanding of how neural computations arise from the coordinated dynamics of distributed, recurrently connected neural populations. However, inferring the nature of recurrent dynamics from partial recordings of a neural circuit presents considerabl...

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Vydáno v:Nature neuroscience Ročník 26; číslo 2; s. 326 - 338
Hlavní autoři: Galgali, Aniruddh R., Sahani, Maneesh, Mante, Valerio
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Nature Publishing Group US 01.02.2023
Nature Publishing Group
Témata:
631/378/116/1925
631/378/116/2393
631/378/2649/1409
Animal Genetics and Genomics
Animals
Behavioral Sciences
Biological Techniques
Biomedical and Life Sciences
Biomedicine
Circuits
Decision making
Dynamics
Macaca
Mental task performance
Neurobiology
Neurosciences
Perturbation
Prefrontal Cortex
Saccades
Saccadic eye movements
ISSN:1097-6256, 1546-1726, 1546-1726
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Shrnutí:Relating neural activity to behavior requires an understanding of how neural computations arise from the coordinated dynamics of distributed, recurrently connected neural populations. However, inferring the nature of recurrent dynamics from partial recordings of a neural circuit presents considerable challenges. Here we show that some of these challenges can be overcome by a fine-grained analysis of the dynamics of neural residuals—that is, trial-by-trial variability around the mean neural population trajectory for a given task condition. Residual dynamics in macaque prefrontal cortex (PFC) in a saccade-based perceptual decision-making task reveals recurrent dynamics that is time dependent, but consistently stable, and suggests that pronounced rotational structure in PFC trajectories during saccades is driven by inputs from upstream areas. The properties of residual dynamics restrict the possible contributions of PFC to decision-making and saccade generation and suggest a path toward fully characterizing distributed neural computations with large-scale neural recordings and targeted causal perturbations. Activity in a neural population arises from both its inputs and its recurrent connections. Here the authors show that analyzing the dynamics of trial-to-trial variability in activity can offer insights into delineating these contributions.
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ISSN:1097-6256
1546-1726
1546-1726
DOI:10.1038/s41593-022-01230-2