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Connectome: Graph theory application in functional brain network architecture.

Fabrizio Vecchio1, Francesca Miraglia1,2, Paolo Maria Rossini1,2

  • 1Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy.

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Summary
This summary is machine-generated.

Network science, using graph theory and electroencephalography (EEG), reveals how brain network structure impacts cognitive function. This approach models brain resilience and vulnerability in aging and neurological disorders like epilepsy and Alzheimer's disease.

Keywords:
EEGFunctional connectivityGraph theoryResting-state networkseLORETA

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Area of Science:

  • Neuroscience
  • Network Science
  • Graph Theory

Background:

  • Network science and graph theory offer frameworks to understand cognitive functions and neuronal network structure.
  • Understanding network topology aids in modeling brain vulnerability and resilience to dysfunction.
  • Electroencephalography (EEG) is a key tool for investigating functional dynamic connectivity.

Purpose of the Study:

  • To review recent studies applying graph theory to EEG functional connectivity data.
  • To explore network studies in physiological aging and neurological disorders.
  • To highlight the role of network topology in characterizing brain health and disease.

Main Methods:

  • Analysis of functional dynamic connectivity using electroencephalographic (EEG) data.
  • Application of graph theory principles to network analysis of brain connectivity.
  • Review of pivotal studies focusing on network characteristics in aging and disease.

Main Results:

  • Graph theory analysis of EEG data provides insights into functional brain networks.
  • Network topology can characterize physiological aging processes.
  • Distinct network alterations are observed in epilepsy and neurodegenerative dementias, including Alzheimer's disease.

Conclusions:

  • Graph theory applied to EEG functional connectivity is a powerful tool for understanding brain function and dysfunction.
  • Network analysis can differentiate between healthy aging and neurological disorders.
  • This approach holds potential for characterizing and modeling brain vulnerability and resilience.