Evidence map›Paper›PMID 37148876›Full record

ArticleCurrent biology : CB2023

Amplified cortical neural responses as animals learn to use novel activity patterns.

Bradley Akitake, Hannah M Douglas, Paul K LaFosse, Manuel Beiran, Ciana E Deveau, Jonathan O'Rawe, Anna J Li, Lauren N Ryan, Samuel P Duffy, Zhishang Zhou and 3 more

Open access · greenAbstract read
In one paragraph

Article in Current biology : CB, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Neuronal Features of Visual Attention in the Mouse Superior Colliculus Depend on Learned Behavioral Relevance.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  3. Article
  4. Local Differences in Network Organization in the Auditory and Parietal Cortex, Revealed with Single Neuron Activation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Bradley AkitakeUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Hannah M DouglasUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Paul K LaFosseUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Manuel BeiranNash Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
Ciana E DeveauUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Jonathan O'RaweUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Anna J LiUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Lauren N RyanUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Samuel P DuffyUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Zhishang ZhouUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Yanting DengUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
Kanaka RajanNash Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Mark H HistedUnit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: mark.histed@nih.gov.
National Institutes of Health · USAllen Institute for Brain Science · US

Funding

Readout and control of spatiotemporal neuronal codes for behaviorU19NS107464 · NINDS · UNIVERSITY OF CHICAGO · PI SHOHAM, SHY · 2018 to 2022
$17.3M
Patterns of neuronal activity underlying behavioral decisionsZIAMH002956 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI HISTED, MARK · 2016 to 2025
$11.1M
Computation by recurrent circuits of the cerebral cortexZIAMH002967 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI HISTED, MARK · 2017 to 2025
$7.0M
Circuitry underlying response summation in mouse and primate: Theory and experimentU01NS108683 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI BRUNEL, NICOLAS, MILLER, KENNETH D · 2018 to 2020
$2.8M
The role of patterned activity in neuronal codes for behaviorU01NS090576 · NINDS · UNIVERSITY OF CHICAGO · PI FELLIN, TOMMASO, HISTED, MARK H · 2014 to 2016
$1.6M
BRAIN project (Histed): Readout and Control of Spatiotemporal Neuronal Codes of BehaviorZIAMH002972 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI HISTED, MARK · 2019 to 2023
$1.5M
Multi-region 'Network of Networks' Recurrent Neural Network Models of Adaptive and Maladaptive LearningR01EB028166 · NIBIB · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI RAJAN, KANAKA · 2019 to 2019
$1.2M
Intramural NIH HHS ZIA MH002956NIBIB NIH HHS R01 EB028166NINDS NIH HHS U01 NS090576NINDS NIH HHS U01 NS108683NINDS NIH HHS U19 NS107464
6 · The paper itself

Abstract

Cerebral cortex supports representations of the world in patterns of neural activity, used by the brain to make decisions and guide behavior. Past work has found diverse, or limited, changes in the primary sensory cortex in response to learning, suggesting that the key computations might occur in downstream regions. Alternatively, sensory cortical changes may be central to learning. We studied cortical learning by using controlled inputs we insert: we trained mice to recognize entirely novel, non-sensory patterns of cortical activity in the primary visual cortex (V1) created by optogenetic stimulation. As animals learned to use these novel patterns, we found that their detection abilities improved by an order of magnitude or more. The behavioral change was accompanied by large increases in V1 neural responses to fixed optogenetic input. Neural response amplification to novel optogenetic inputs had little effect on existing visual sensory responses. A recurrent cortical model shows that this amplification can be achieved by a small mean shift in recurrent network synaptic strength. Amplification would seem to be desirable to improve decision-making in a detection task; therefore, these results suggest that adult recurrent cortical plasticity plays a significant role in improving behavioral performance during learning.

Indexed as

LearningNeuronsAnimalsCerebral CortexMiceVisual Perceptionbehaviorcalcium imagingneural computationoptogeneticsperceptual learningplasticityRNNvisual cortex

Identifiers

PMID37148876
PMCPMC12965175
OpenAlexW4372287580

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.