Evidence map›Paper›PMID 40832352›Full record

ArticlebioRxiv : the preprint server for biology2025

Global and local origins of trial-to-trial spike count variability in visual cortex.

Anna J Li, Ziyu Lu, Alexander E Ladd, Pascha Matveev, Eric Shea-Brown, Nicholas A Steinmetz

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Anna J LiDepartment of Neurobiology and Biophysics, University of Washington, Seattle, WA, USA.ORCID 0000-0001-6287-2910
Ziyu LuDepartment of Applied Math, University of Washington, Seattle, WA, USA.ORCID 0009-0004-1446-601X
Alexander E LaddDepartment of Neurobiology and Biophysics, University of Washington, Seattle, WA, USA.ORCID 0000-0003-0999-1608
Pascha MatveevDepartment of Neurobiology and Biophysics, University of Washington, Seattle, WA, USA.ORCID 0000-0001-6860-4407
Eric Shea-BrownDepartment of Applied Math, University of Washington, Seattle, WA, USA.
Nicholas A SteinmetzDepartment of Neurobiology and Biophysics, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7029-2908

Funding

VISUAL SCIENCES TRAINING PROGRAMT32EY007031 · NEI · UNIVERSITY OF WASHINGTON · PI Wyeth Daniel Bair, Anitha Pasupathy · 1985 to 2026
$6.1M
The distributed basis of visual cortical variabilityF31EY035880 · NEI · UNIVERSITY OF WASHINGTON · PI Anna Li · 2024 to 2026
$149k
NEI NIH HHS F31 EY035880NEI NIH HHS T32 EY007031
6 · The paper itself

Abstract

Sensory neuron spiking responses vary across repeated presentations of the same stimuli, but whether this trial-to-trial variability represents noise versus unidentified signals remains unresolved. Some of the variability can be attributed to correlations between neural activity and arousal, locomotion, and other overt movements. We hypothesized that correlations with global activity factors, i.e., patterns of neural activity observable in other brain regions, may explain additional variability in spike count responses of visual cortical neurons. To test this, we used Neuropixels 2.0 probes to record neural activity in mouse primary visual cortex (V1) while subjects passively viewed images. We recorded videos of behavior alongside neural activity from other brain regions, either spiking activity of neural populations in anterior cingulate area (ACA) or widefield calcium signals from across the dorsal cortex. We then used a model based on reduced rank regression to partition the explainable variability of visual cortical responses by source. Some of the trial-to-trial variability in V1 spike counts was attributable to locally shared patterns of activity uncorrelated with either behavior or global activity patterns. Locally shared activity patterns explained trial-to-trial variability that was in excess of Poisson spike generation. Of the parts of variability attributable to non-local sources, global cortical activity predicted significantly more V1 spike count variability than behavioral factors. Additionally, behavioral factors explained little variability uniquely and comprised a geometric subspace of the globally predictable V1 activity. Finally, optogenetically perturbing ACA directly impacted V1 activity, and ACA activity patterns predicted V1 spike count variability even on trials without overt behaviors. Our data indicate that globally shared factors from other cortical areas contribute substantially to shared spike count variability in V1, with only a minority of shared variability confined to local V1 circuits.

Identifiers

PMID40832352
PMCPMC12363831

What OpenQuestion holds

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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.