Evidence map›Paper›PMID 40511993›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2025

Brain sources composing irregular field potentials have unique temporal signatures.

Ricardo Muñoz-Arnaiz, Julia Makarova, Valeri A Makarov, Oscar Herreras

Abstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2025. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ricardo Muñoz-ArnaizCajal Institute-CSIC, Translational Neuroscience, Av. Doctor Arce 37, Madrid 28002, Spain.
Julia MakarovaCajal Institute-CSIC, Translational Neuroscience, Av. Doctor Arce 37, Madrid 28002, Spain.
Valeri A MakarovInstitute for Interdisciplinary Mathematics, School of Mathematics, Universidad Complutense de Madrid, Av. Complutense s/n, Madrid 28040, Spain.
Oscar HerrerasCajal Institute-CSIC, Translational Neuroscience, Av. Doctor Arce 37, Madrid 28002, Spain.ORCID 0000-0002-8210-3710

Funding

European Commission Next Generation EU EU 2020/2094-IASOMM24006European Commission Next Generation EU PDC2021-121103-I00Spanish Ministerio de Ciencia e Innovación (MICIN) PID2021-124047NB-I00Spanish Ministerio de Ciencia e Innovación (MICIN) PID2022-137801NB-I00
6 · The paper itself

Abstract

The prevailing irregular pattern of field potentials is little used due to the uncertain origin and identity of the source populations. After recovering clean source-specific dynamics (field potential-generators) in multiple brain areas of anesthetized rats we explored if they contain temporal identity features and to what extent they remain upon blending in the volume (raw field potentials). Relevant factors and mechanisms were further explored through a feed-forward model of field potentials. Signals were characterized with a multivariate set of statistical, spectral and nonlinear measures and explored with machine-learning classifiers. Despite the strong variability of electrographic patterns, field potential generators exhibit unique temporal signatures that allow their discrimination. Signatures are contained in 1 to 5 s segments in any given brain region and are robust across groups of animals. In contrast, the spatial overlap of sources and the contribution by remote potentials cause indeterminacy of raw field potentials, making them approach a noisy behavior. The so revealed source-specific signatures contain spectral and nonlinear features, thus overcoming the traditional notion of waves and frequency bands. We propose that besides upstream dynamics cytoarchitectural factors of the source population contribute to these unique signatures. These findings pave the way to utilize the vast reserve of information contained in irregular field potentials.

Indexed as

BrainAnimalsBrain MappingElectroencephalographyMachine LearningMaleModels, NeurologicalRatsaperiodic activitydeep source separationindependent component analysissupervised machine learningvolume-conduction

Identifiers

PMID40511993
PMCPMC12163988

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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.