The application of graph theoretical analysis to complex networks in the brain

Abstract Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights...

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Published inClinical neurophysiology Vol. 118; no. 11; pp. 2317 - 2331
Main Authors Reijneveld, Jaap C, Ponten, Sophie C, Berendse, Henk W, Stam, Cornelis J
Format Journal Article
LanguageEnglish
Published Shannon Elsevier Ireland Ltd 01.11.2007
Elsevier Science
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Abstract Abstract Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.
AbstractList Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.
Abstract Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.
Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.
Author Reijneveld, Jaap C
Stam, Cornelis J
Ponten, Sophie C
Berendse, Henk W
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  fullname: Ponten, Sophie C
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  fullname: Berendse, Henk W
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  fullname: Stam, Cornelis J
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https://www.ncbi.nlm.nih.gov/pubmed/17900977$$D View this record in MEDLINE/PubMed
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Tue Oct 15 22:57:36 EDT 2024
IsPeerReviewed true
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Issue 11
Keywords Functional connectivity
fMRI
Scale free networks
EEG
Epilepsy
Schizophrenia
Cognition
Synchronization
Modeling
Small world networks
MEG
Cognitive disorder
Configuration
Theory
Memory
Electrophysiology
Electroencephalography
Review
Epileptic seizure
Psychosis
Wiring
Human
Nervous system diseases
Pathophysiology
Magnetoencephalography
Neural network
Nuclear magnetic resonance imaging
Cerebral disorder
Central nervous system disease
Planning
Language English
License CC BY 4.0
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Snippet Abstract Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory,...
Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and...
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SubjectTerms Adult and adolescent clinical studies
Biological and medical sciences
Brain - anatomy & histology
Brain - physiology
Brain Diseases - pathology
Brain Diseases - physiopathology
Brain Mapping
Cognition
EEG
Epilepsy
fMRI
Functional connectivity
Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy
Humans
Medical sciences
MEG
Modeling
Nerve Net - anatomy & histology
Nerve Net - physiology
Nervous system (semeiology, syndromes)
Neural Networks (Computer)
Neural Pathways - anatomy & histology
Neural Pathways - physiopathology
Neurology
Psychology. Psychoanalysis. Psychiatry
Psychopathology. Psychiatry
Psychoses
Scale free networks
Schizophrenia
Small world networks
Synchronization
Title The application of graph theoretical analysis to complex networks in the brain
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https://dx.doi.org/10.1016/j.clinph.2007.08.010
https://www.ncbi.nlm.nih.gov/pubmed/17900977
https://search.proquest.com/docview/68393016
Volume 118
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