Evidence map›Paper›PMID 36994445›Full record

ArticleFrontiers in computational neuroscience2023

A survey of neurophysiological differentiation across mouse visual brain areas and timescales.

Saurabh R Gandhi, William G P Mayner, William Marshall, Yazan N Billeh, Corbett Bennett, Samuel D Gale, Chris Mochizuki, Joshua H Siegle, Shawn Olsen, Giulio Tononi and 2 more

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Article in Frontiers in computational neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

12 authors.

Saurabh R GandhiMindScope Program, Allen Institute, Seattle, WA, United States.
William G P MaynerDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States.
William MarshallDepartment of Mathematics and Statistics, Brock University, St. Catharines, ON, Canada.
Yazan N BillehMindScope Program, Allen Institute, Seattle, WA, United States.
Corbett BennettMindScope Program, Allen Institute, Seattle, WA, United States.
Samuel D GaleMindScope Program, Allen Institute, Seattle, WA, United States.
Chris MochizukiMindScope Program, Allen Institute, Seattle, WA, United States.
Joshua H SiegleMindScope Program, Allen Institute, Seattle, WA, United States.
Shawn OlsenMindScope Program, Allen Institute, Seattle, WA, United States.
Giulio TononiDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States.
Christof KochMindScope Program, Allen Institute, Seattle, WA, United States.
Anton ArkhipovMindScope Program, Allen Institute, Seattle, WA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurophysiological differentiation (ND), a measure of the number of distinct activity states that a neural population visits over a time interval, has been used as a correlate of meaningfulness or subjective perception of visual stimuli. ND has largely been studied in non-invasive human whole-brain recordings where spatial resolution is limited. However, it is likely that perception is supported by discrete neuronal populations rather than the whole brain. Therefore, here we use Neuropixels recordings from the mouse brain to characterize the ND metric across a wide range of temporal scales, within neural populations recorded at single-cell resolution in localized regions. Using the spiking activity of thousands of simultaneously recorded neurons spanning 6 visual cortical areas and the visual thalamus, we show that the ND of stimulus-evoked activity of the entire visual cortex is higher for naturalistic stimuli relative to artificial ones. This finding holds in most individual areas throughout the visual hierarchy. Moreover, for animals performing an image change detection task, ND of the entire visual cortex (though not individual areas) is higher for successful detection compared to failed trials, consistent with the assumed perception of the stimulus. Together, these results suggest that ND computed on cellular-level neural recordings is a useful tool highlighting cell populations that may be involved in subjective perception.

Indexed as

Allen Institute for Brain Scienceconscious perceptionmouseneurophysiological differentiationNeuropixelsvisual cortex

Identifiers

PMID36994445
PMCPMC10040573

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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.