Cited by 354Neural dynamics and brain functionFunctional Brain Connectivity StudiesNonlinear Dynamics and Pattern Formation

Dynamical consequences of lesions in cortical networks

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Honey, Christopher J., Sporns, Olaf·2008·Human Brain Mapping

Abstract

To understand the effects of a cortical lesion it is necessary to consider not only the loss of local neural function, but also the lesion‐induced changes in the larger network of endogenous oscillatory interactions in the brain. To investigate how network embedding influences a region's functional role, and the consequences of its being damaged, we implement two models of oscillatory cortical interactions, both of which inherit their coupling architecture from the available anatomical connection data for macaque cerebral cortex. In the first model, node dynamics are governed by Kuramoto phase oscillator equations, and we investigate the sequence in which areas entrain one another in the transition to global synchrony. In the second model, node dynamics are governed by a more realistic neural mass model, and we assess long‐run inter‐regional interactions using a measure of directed information flow. Highly connected parietal and frontal areas are found to synchronize most rapidly, more so than equally highly connected visual and somatosensory areas, and this difference can be explained in terms of the network's clustered architecture. For both models, lesion effects extend beyond the immediate neighbors of the lesioned site, and the amplitude and dispersal of nonlocal effects are again influenced by cluster patterns in the network. Although the consequences of in vivo lesions will always depend on circuitry local to the damaged site, we conclude that lesions of parietal regions (especially areas 5 and 7a) and frontal regions (especially areas 46 and FEF) have the greatest potential to disrupt the integrative aspects of neocortical function. Hum Brain Mapp, 2008. © 2008 Wiley‐Liss, Inc.

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  • Simulation experiments using structure-function models predict that purely focal and transient perturbations in activity result in diffuse network reorganization affecting distant brain systems.

    “simulation experiments using structure-function models have predicted that even purely focal and transient perturbations in activity should result in diffuse network reorganization that affects distant brain systems (Alstott et al., 2009; Honey and Sporns, 2008; Misic et al., 2015).”

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  1. Lachaux J‐P,Rodriguez E,Martinerie J,Varela FJ ( 1999): Measuring phase synchrony in brain signals. Hum Brain Mapping 8: 194–208. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Authors
Honey, C. J., & Sporns, O.
Affiliations
Indiana University Bloomington (US)
Venue
Human Brain Mapping
Publisher
Wiley
Published
2008-04-25
Volume
29
Issue
7
Pages
802-809
ISSN
  • 1065-9471 (ISSN-L)
  • 1097-0193
OpenAlex
W2105504969
Cited by
353
References
39
Citations by year
2026: 7 · 2025: 8 · 2024: 13 · 2023: 18 · 2022: 23 · 2021: 18 · 2020: 14 · 2019: 25 · 2018: 15 · 2017: 33 · 2016: 32 · 2015: 18 · 2014: 26 · 2013: 26 · 2012: 22
FWCI
9.47
Type
journal article
Language
en
Open access
Locations
  • Human Brain Mapping (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
James S. McDonnell Foundation
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
cortical lesions, cortical oscillations, neural mass model, directed information flow, network synchronization, structural connectivity, network clustering, parietal cortex, frontal cortex
MeSH terms
Animals, Cerebral Cortex, Macaca, Models, Neurological, Nerve Net, Neural Pathways

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