Evidence map›Paper›PMID 36627310›Full record

ArticleNature communications2023

Choice selective inhibition drives stability and competition in decision circuits.

James P Roach, Anne K Churchland, Tatiana A Engel

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

  1. Article
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  7. Neural Oscillation as a Selective Modulatory Mechanism on Decision Confidence, Speed, and Accuracy.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

James P RoachCold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.ORCID 0000-0002-1034-9615
Anne K ChurchlandDepartment of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.ORCID 0000-0002-3205-3794
Tatiana A EngelCold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. engel@cshl.edu.ORCID 0000-0001-5842-9406

Funding

The role of parietal cortex in multisensory decision-makingR01EY022979 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ANNE KATHRYN CHURCHLAND · 2013 to 2026
$5.7M
Multiscale computational frameworks for integrating large-scale cortical dynamics, connectivity, and behaviorRF1DA055666 · NIDA · PRINCETON UNIVERSITY · PI ENGEL, TATIANA · 2021 to 2021
$1.3M
Discovering dynamic computations from large-scale neural activity recordingsR01EB026949 · NIBIB · COLD SPRING HARBOR LABORATORY · PI ENGEL, TATIANA · 2018 to 2020
$1.3M
Graphical Processing Units and a Large-Memory Compute Node for Applications in Genomics, Neuroscience, and Structural BiologyS10OD028632 · OD · COLD SPRING HARBOR LABORATORY · PI SIEPEL, ADAM CHARLES · 2020 to 2020
$437k
Using perceptual decision-making to understand the role of selective inhibitory activity in cortical computationF32MH123011 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ROACH, JAMES PATRICK · 2020 to 2022
$218k
NEI NIH HHS R01 EY022979NIBIB NIH HHS R01 EB026949NIDA NIH HHS RF1 DA055666NIH HHS S10 OD028632NIMH NIH HHS F32 MH123011
6 · The paper itself

Abstract

During perceptual decision-making, the firing rates of cortical neurons reflect upcoming choices. Recent work showed that excitatory and inhibitory neurons are equally selective for choice. However, the functional consequences of inhibitory choice selectivity in decision-making circuits are unknown. We developed a circuit model of decision-making which accounts for the specificity of inputs to and outputs from inhibitory neurons. We found that selective inhibition expands the space of circuits supporting decision-making, allowing for weaker or stronger recurrent excitation when connected in a competitive or feedback motif. The specificity of inhibitory outputs sets the trade-off between speed and accuracy of decisions by either stabilizing or destabilizing the saddle-point dynamics underlying decisions in the circuit. Recurrent neural networks trained to make decisions display the same dependence on inhibitory specificity and the strength of recurrent excitation. Our results reveal two concurrent roles for selective inhibition in decision-making circuits: stabilizing strongly connected excitatory populations and maximizing competition between oppositely selective populations.

Indexed as

Neural Networks, ComputerNeuronsFeedbackModels, NeurologicalNeural Inhibition

Identifiers

PMID36627310
PMCPMC9832138

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.