How heterogeneity shapes dynamics and computation in the brain

Much effort has been spent clustering neurons into transcriptomic or functional cell types and characterizing the differences between them. Beyond subdividing neurons into categories, we must recognize that no two neurons are identical and that graded physiological or transcriptomic properties exist within cells of a given type. This often overlooked "within-type" heterogeneity is a specific neuronal implementation of what statistical physics refers to as "disorder" and exhibits rich computational properties, the identification of which may shed crucial insights into theories of brain function. In this perspective article, we address this gap by highlighting theoretical frameworks for the study of neural tissue heterogeneity and discussing the benefits and implications of within-type heterogeneity for neural network dynamics, computation, and self-organization.

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Publication Details

Journal
Neuron
Published
2025-12-30
DOI
https://doi.org/10.1016/j.neuron.2025.11.023
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.00
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article

How heterogeneity shapes dynamics and computation in the brain

Richard Gast, Melika Payvand, Adilson E. Motter, Luca Mazzucato et al.
Neuron
Neural dynamics and brain function
article

How heterogeneity shapes dynamics and computation in the brain

Richard Gast, Melika Payvand, Adilson E. Motter, Luca Mazzucato, Giacomo Indiveri, Henrike Planert, David Dahmen, Ann Kennedy, Jérémie Lefebvre, Rishikesh Narayanan, Axel Hutt
article en

Abstract

Much effort has been spent clustering neurons into transcriptomic or functional cell types and characterizing the differences between them. Beyond subdividing neurons into categories, we must recognize that no two neurons are identical and that graded physiological or transcriptomic properties exist within cells of a given type. This often overlooked "within-type" heterogeneity is a specific neuronal implementation of what statistical physics refers to as "disorder" and exhibits rich computational properties, the identification of which may shed crucial insights into theories of brain function. In this perspective article, we address this gap by highlighting theoretical frameworks for the study of neural tissue heterogeneity and discussing the benefits and implications of within-type heterogeneity for neural network dynamics, computation, and self-organization.

NeuronVol. 114(5)
Northwestern University (US), Scripps Research Institute (US), SIB Swiss Institute of Bioinformatics (CH), Centre National de la Recherche Scientifique (FR), University of Ottawa (CA), Forschungszentrum Jülich (DE), University of Oregon (US), University of Zurich (CH), ETH Zurich (CH), Humboldt-Universität zu Berlin (DE), Neuroscience Institute (IT), Jupiter Medical Center (US), École Polytechnique Fédérale de Lausanne (CH), Indian Institute of Science Bangalore (IN), Université de Strasbourg (FR), Wilfrid Laurier University (CA), Charité - Universitätsmedizin Berlin (DE)
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Neural dynamics and brain function
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