Evidence map›Paper›PMID 39080254›Full record

ArticleNature communications2024

Flexible neural population dynamics govern the speed and stability of sensory encoding in mouse visual cortex.

Edward A B Horrocks, Fabio R Rodrigues, Aman B Saleem

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Connectivity, Computation, and Plasticity of the Early Visual System.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Synaptic dynamics govern spatial integration in mouse visual cortex.bioRxiv : the preprint server for biology · 2025
    Article
  14. Article
  15. Article
  16. Identification of movie encoding neurons enables movie recognition AI.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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.

Edward A B HorrocksInstitute of Behavioural Neuroscience, University College London, London, WC1V 0AP, UK. edward.horrocks.17@ucl.ac.uk.ORCID 0000-0003-4019-5351
Fabio R RodriguesInstitute of Behavioural Neuroscience, University College London, London, WC1V 0AP, UK.ORCID 0000-0002-4848-7167
Aman B SaleemInstitute of Behavioural Neuroscience, University College London, London, WC1V 0AP, UK. aman.saleem@ucl.ac.uk.ORCID 0000-0002-7100-1954

Funding

Human Frontier Science Program (HFSP) RGY0076/2018RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/W01579X/1RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) R004765RCUK | Medical Research Council (MRC) MR/W019914/1Wellcome Trust 200501Wellcome Trust 200501/Z/16/Z
6 · The paper itself

Abstract

Time courses of neural responses underlie real-time sensory processing and perception. How these temporal dynamics change may be fundamental to how sensory systems adapt to different perceptual demands. By simultaneously recording from hundreds of neurons in mouse primary visual cortex, we examined neural population responses to visual stimuli at sub-second timescales, during different behavioural states. We discovered that during active behavioural states characterised by locomotion, single-neurons shift from transient to sustained response modes, facilitating rapid emergence of visual stimulus tuning. Differences in single-neuron response dynamics were associated with changes in temporal dynamics of neural correlations, including faster stabilisation of stimulus-evoked changes in the structure of correlations during locomotion. Using Factor Analysis, we examined temporal dynamics of latent population responses and discovered that trajectories of population activity make more direct transitions between baseline and stimulus-encoding neural states during locomotion. This could be partly explained by dampening of oscillatory dynamics present during stationary behavioural states. Functionally, changes in temporal response dynamics collectively enabled faster, more stable and more efficient encoding of new visual information during locomotion. These findings reveal a principle of how sensory systems adapt to perceptual demands, where flexible neural population dynamics govern the speed and stability of sensory encoding.

Indexed as

NeuronsPhotic StimulationVisual CortexAnimalsFemaleLocomotionMaleMiceMice, Inbred C57BLPopulation DynamicsPrimary Visual CortexVisual Perception

Identifiers

PMID39080254
PMCPMC11289260

What OpenQuestion holds

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Registered trials

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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.