Evidence map›Paper›PMID 39229215›Full record

ArticlebioRxiv : the preprint server for biology2024

Network influence determines the impact of cortical ensembles on stimulus detection.

Hayley A Bounds, Hillel Adesnik

Abstract readPreprint
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. 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

5 · Who and what money

Authors and funding

2 authors.

Hayley A BoundsDepartment of Neuroscience, University of California, Berkeley.ORCID 0000-0002-2774-6596
Hillel AdesnikDepartment of Neuroscience, University of California, Berkeley.ORCID 0000-0002-3796-8643

Funding

Validating Theoretical Models with Neurophysiology and OptogeneticsU19NS107613 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ADESNIK, HILLEL · 2018 to 2022
$16.7M
Excitation and Inhibition in Neural Circuits of the Visual CortexR01EY023756 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI Hillel Adesnik · 2013 to 2026
$6.1M
Mesoscale bidirectional two-photon holographic optogeneticsRF1NS128772 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI ADESNIK, HILLEL · 2022 to 2022
$3.2M
NEI NIH HHS R01 EY023756NINDS NIH HHS RF1 NS128772NINDS NIH HHS U19 NS107613
6 · The paper itself

Abstract

Observation of neural firing patterns can constrain theories for the types of activity patterns that the brain uses to guide behavior. However, directly perturbing these patterns, ideally with great specificity, is required to causally test any particular theory. We combined two-photon imaging and cellular resolution optogenetic photo-stimulation to causally test how neural activity in the mouse visual cortex is read out to detect visual stimuli. Contrary to expectations, targeted activation of highly sensitive neural ensembles did not preferentially modify behavior compared to random ensembles, contradicting a longstanding hypothesis for how neural activity drives stimulus detection. Instead, the main predictor of a targeted neural ensemble's impact on perception was its effect on network activity. This argues that downstream regions summate visual cortex activity without preferentially weighting more informative neurons to make sensory detection decisions. Comparing mouse behavioral performance to decoding models of neural activity implies that mice employ this simple, albeit suboptimal strategy to solve the task. This work challenges conventional notions for how sensory representations mediate perception and demonstrates that specific neural perturbations are critical for determining which features of neural activity drive behavior.

Identifiers

PMID39229215
PMCPMC11370385

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.