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Graph Analysis of the Visual Cortical Network during Naturalistic Movie Viewing Reveals Increased Integration and Decreased Segregation Following Mild TBI.
Ruiz, Tatiana; Brown, Shael; Farivar, Reza.
Afiliação
  • Ruiz T; Department of Ophthalmology & Visual Sciences, McGill University, Montreal, QC H4A 0A4, Canada.
  • Brown S; Research Institute of the McGill University Health Center, Montreal, QC H3G 1A4, Canada.
  • Farivar R; Department of Ophthalmology & Visual Sciences, McGill University, Montreal, QC H4A 0A4, Canada.
Vision (Basel) ; 8(2)2024 May 10.
Article em En | MEDLINE | ID: mdl-38804354
ABSTRACT
Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain's processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article