Dynamic models of large-scale brain activity

Breakspear, Michael

doi:10.1038/nn.4497

Cited by 1,239Neural dynamics and brain functionFunctional Brain Connectivity StudiesNonlinear Dynamics and Pattern Formation

Dynamic models of large-scale brain activity

Breakspear, Michael·2017·Nature Neuroscience

DOI 10.1038/nn.4497

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Abstract

Movement, cognition and perception arise from the collective activity of neurons within cortical circuits and across large-scale systems of the brain. While the causes of single neuron spikes have been understood for decades, the processes that support collective neural behavior in large-scale cortical systems are less clear and have been at times the subject of contention. Modeling large-scale brain activity with nonlinear dynamical systems theory allows the integration of experimental data from multiple modalities into a common framework that facilitates prediction, testing and possible refutation. This work reviews the core assumptions that underlie this computational approach, the methodological framework that fosters the translation of theory into the laboratory, and the emerging body of supporting evidence. While substantial challenges remain, evidence supports the view that collective, nonlinear dynamics are central to adaptive cortical activity. Likewise, aberrant dynamic processes appear to underlie a number of brain disorders.

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Population models allow one to treat an entire cortical column or region as a unit that sends and receives prediction/error signals.
“they allow one to treat an entire cortical column or region as a unit that sends and receives prediction/error signals (19).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [19]

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Authors: Breakspear, M.
Affiliations: QIMR Berghofer Medical Research Institute (AU)
Corresponding author: Breakspear, Michael
ORCID: Breakspear, Michael
Venue: Nature Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2017-02-23
Volume: 20
Issue: 3
Pages: 340-352
ISSN: 1097-6256 (ISSN-L)
1546-1726
DOI: 10.1038/nn.4497
OpenAlex: W2590144118
Cited by: 1,239
References: 151
Citations by year: 2026: 206 · 2025: 194 · 2024: 163 · 2023: 144 · 2022: 150 · 2021: 87 · 2020: 111 · 2019: 87 · 2018: 73 · 2017: 24
FWCI: 9.03
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Nature Neuroscience (publishedVersion)
PubMed (publishedVersion)
Funders: Australian Research Council
National Health and Medical Research Council
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Physical Sciences › Computer Science › Computer Networks and Communications › Nonlinear Dynamics and Pattern Formation
Keywords: nonlinear dynamical systems, cortical circuits, thalamus, spinal cord, computational neuroscience, brain disorders, cognitive activity, perception, movement
MeSH terms: Animals, Brain, Cognition, Humans, Models, Neurological, Movement, Nerve Net, Neurons

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