Evidence map›Paper›PMID 37899886›Full record

ArticleFrontiers in computational neuroscience2023

Computational assessment of visual coding across mouse brain areas and behavioural states.

Yizhou Xie, Sadra Sadeh

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
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, 3 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Yizhou XieDepartment of Brain Sciences, Imperial College London, London, United Kingdom.
Sadra SadehDepartment of Brain Sciences, Imperial College London, London, United Kingdom.
Imperial College London · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Introduction: Our brain is bombarded by a diverse range of visual stimuli, which are converted into corresponding neuronal responses and processed throughout the visual system. The neural activity patterns that result from these external stimuli vary depending on the object or scene being observed, but they also change as a result of internal or behavioural states. This raises the question of to what extent it is possible to predict the presented visual stimuli from neural activity across behavioural states, and how this varies in different brain regions. Methods: To address this question, we assessed the computational capacity of decoders to extract visual information in awake behaving mice, by analysing publicly available standardised datasets from the Allen Brain Institute. We evaluated how natural movie frames can be distinguished based on the activity of units recorded in distinct brain regions and under different behavioural states. This analysis revealed the spectrum of visual information present in different brain regions in response to binary and multiclass classification tasks. Results: Visual cortical areas showed highest classification accuracies, followed by thalamic and midbrain regions, with hippocampal regions showing close to chance accuracy. In addition, we found that behavioural variability led to a decrease in decoding accuracy, whereby large behavioural changes between train and test sessions reduced the classification performance of the decoders. A generalised linear model analysis suggested that this deterioration in classification might be due to an independent modulation of neural activity by stimulus and behaviour. Finally, we reconstructed the natural movie frames from optimal linear classifiers, and observed a strong similarity between reconstructed and actual movie frames. However, the similarity was significantly higher when the decoders were trained and tested on sessions with similar behavioural states. Conclusion: Our analysis provides a systematic assessment of visual coding in the mouse brain, and sheds light on the spectrum of visual information present across brain areas and behavioural states.

Indexed as

behaviourdecodingencodingmouse visual cortexneural activityvisual coding

Identifiers

PMID37899886
PMCPMC10613063
OpenAlexW4387601720

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.