Evidence map›Paper›PMID 38452763›Full record

ArticleNeuron2024

Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number.

Jason Manley, Sihao Lu, Kevin Barber, Jeffrey Demas, Hyewon Kim, David Meyer, Francisca Martínez Traub, Alipasha Vaziri

Abstract read
In one paragraph

Article in Neuron, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing 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

58 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Jason ManleyLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA.
Sihao LuLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA.
Kevin BarberLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA.
Jeffrey DemasLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA.
Hyewon KimLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA.
David MeyerLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA.
Francisca Martínez TraubLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA.
Alipasha VaziriLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA; The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA. Electronic address: vaziri@rockefeller.edu.

Funding

Optimization, Application, and Dissemination of Imaging Modules for High-speed Mesoscopic Volumetric Recording of Neuroactivity in Scattering BrainsU01NS126057 · NINDS · ROCKEFELLER UNIVERSITY · PI VAZIRI, ALIPASHA · 2022 to 2025
$5.0M
Optimization, application and dissemination of high-speed hybrid multiphoton volumetric imaging technologiesU01NS115530 · NINDS · ROCKEFELLER UNIVERSITY · PI LOSONCZY, ATTILA, VAZIRI, ALIPASHA · 2020 to 2023
$4.7M
Cortex-wide volumetric imaging of neuronal activity.U01NS103488 · NINDS · ROCKEFELLER UNIVERSITY · PI VAZIRI, ALIPASHA · 2017 to 2019
$2.7M
NINDS NIH HHS U01 NS103488NINDS NIH HHS U01 NS115530NINDS NIH HHS U01 NS126057
6 · The paper itself

Abstract

The brain's remarkable properties arise from the collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, can such low-dimensional representations truly explain the vast range of brain activity, and if not, what is the appropriate resolution and scale of recording to capture them? Imaging neural activity at cellular resolution and near-simultaneously across the mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number in populations up to 1 million neurons. Although half of the neural variance is contained within sixteen dimensions correlated with behavior, our discovered scaling of dimensionality corresponds to an ever-increasing number of neuronal ensembles without immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine grained and cortex wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.

Indexed as

NeuronsAction PotentialsAnimalsCell CountCerebral CortexMaleMiceMice, Inbred C57BLModels, Neurologicaldimensionality reductionlarge-scale imaginglight beads microscopyneural decodingneural manifoldsneural population dynamicsspontaneous behaviorspontaneous cortical dynamicstwo-photon microscopyvolumetric calcium imaging

Identifiers

PMID38452763
PMCPMC11098699

What OpenQuestion holds

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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.