Evidence map›Paper›PMID 39763769›Full record

ArticlebioRxiv : the preprint server for biology2024

Temporal dynamics of energy-efficient coding in mouse primary visual cortex.

S Amin Moosavi, Antonia Pastor, Alfredo G Ornelas, Elaine Tring, Dario L Ringach

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

S Amin MoosaviDepartment of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095.ORCID 0000-0002-8862-789X
Antonia PastorDepartment of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095.
Alfredo G OrnelasInterdepartmental Neuroscience Program, Brain Research Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095.
Elaine TringDepartment of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095.
Dario L RingachDepartment of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095.ORCID 0000-0001-6439-334X

Funding

Thalamic constraints on cortical organizationR01EY034488 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RINGACH, DARIO L · 2023 to 2025
$1.8M
Population codes and sensory discriminationRF1NS116471 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RINGACH, DARIO L · 2020 to 2020
$1.2M
Population codes and sensory discriminationR01NS116471 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RINGACH, DARIO L · 2023 to 2024
$789k
Cortical adaptation in neural populationsR21EY035064 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RINGACH, DARIO L · 2024 to 2025
$424k
NEI NIH HHS R01 EY034488NEI NIH HHS R21 EY035064NINDS NIH HHS R01 NS116471NINDS NIH HHS RF1 NS116471
6 · The paper itself

Abstract

Sparse coding enables cortical populations to represent sensory inputs efficiently, yet its temporal dynamics remain poorly understood. Consistent with theoretical predictions, we show that stimulus onset triggers broad cortical activation, initially reducing sparseness and increasing mutual information. Subsequently, competitive interactions sustain mutual information as activity declines and sparseness increases. Notably, coding efficiency, defined as the ratio of mutual information to metabolic cost, progressively increases, demonstrating the dynamic optimization of sensory representations.

Identifiers

PMID39763769
PMCPMC11702630

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.