Functional connectivity networks in the autistic and healthy brain assessed using Granger causality.

Luca Pollonini, Udit Patidar, Ning Situ, Roozbeh Rezaie, Andrew C. Papanicolaou, George Zouridakis

Research output: Contribution to journalArticle

Abstract

In this study, we analyze brain connectivity based on Granger causality computed from magnetoencephalographic (MEG) activity obtained at the resting state in eight autistic and eight normal subjects along with measures of network connectivity derived from graph theory in an attempt to understand how communication in a human brain network is affected by autism. A connectivity matrix was computed for each subject individually and then group templates were estimated by averaging all matrices in each group. Furthermore, we performed classification of the subjects using support vector machines and Fisher's criterion to rank the features and identify the best subset for maximum separation of the groups. Our results show that a combined model based on connectivity matrices and graph theory measures can provide 87.5% accuracy in separating the two groups. These findings suggest that analysis of functional connectivity patterns may provide a valuable method for the early detection of autism.

Original languageEnglish (US)
Pages (from-to)1730-1733
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
StatePublished - 2010
Externally publishedYes

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Autistic Disorder
Causality
Brain
Graph theory
Communication
Support vector machines
Support Vector Machine

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Functional connectivity networks in the autistic and healthy brain assessed using Granger causality. / Pollonini, Luca; Patidar, Udit; Situ, Ning; Rezaie, Roozbeh; Papanicolaou, Andrew C.; Zouridakis, George.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, 2010, p. 1730-1733.

Research output: Contribution to journalArticle

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