The emergence of abnormal hypersynchronization in the anatomical structural network of human brain Academic Article uri icon

Overview

MeSH Major

  • Brain
  • Cortical Synchronization
  • Models, Neurological
  • Neural Pathways

abstract

  • Brain activity depends on transient interactions between segregated neuronal populations. While synchronization between distributed neuronal clusters reflects the dynamics of cooperative patterns, the emergence of abnormal cortical hypersynchronization is typically associated with spike-wave discharges, which are characterized by a sudden appearance of synchronous around 3Hz large amplitude spike-wave discharges of the electroencephalogram. While most existing studies focus on the cellular and synaptic mechanisms, the aim of this article is to study the role of structural connectivity in the origin of the large-scale synchronization of the brain. Simulating oscillatory dynamics on a human brain network, we find the space-time structure of the coupling defined by the anatomical connectivity and the time delays can be the primary component contributing to the emergence of global synchronization. Our results suggest that abnormal white fiber connections may facilitate the generation of spike-wave discharges. Furthermore, while neural populations can exhibit oscillations in a wide range of frequency bands, we show that large-scale synchronization of the brain only occurs at low frequencies. This may provide a potential explanation for the low characteristic frequencies of spike-wave discharges. Finally, we find the global synchronization has a clear anterior origin involving discrete areas of the frontal lobe. These observations are in agreement with existing brain recordings and in favor of the hypothesis that initiation of spike-wave discharges originates from specific brain areas. Further graph theory analysis indicates that the original areas are highly ranked across measures of centrality. These results underline the crucial role of structural connectivity in the generation of spike-wave discharges.

publication date

  • January 15, 2013

Research

keywords

  • Academic Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2012.09.031

PubMed ID

  • 23000784

Additional Document Info

start page

  • 34

end page

  • 51

volume

  • 65