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Constructing brain functional networks from EEG: Partial and unpartial correlations

Jalili, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1142/S0219635211002725
  3. Abstract:
  4. We consider electroencephalograms (EEGs) of healthy individuals and compare the properties of the brain functional networks found through two methods: unpartialized and partialized cross-correlations. The networks obtained by partial correlations are fundamentally different from those constructed through unpartial correlations in terms of graph metrics. In particular, they have completely different connection efficiency, clustering coefficient, assortativity, degree variability, and synchronization properties. Unpartial correlations are simple to compute and they can be easily applied to large-scale systems, yet they cannot prevent the prediction of non-direct edges. In contrast, partial correlations, which are often expensive to compute, reduce predicting such edges. We suggest combining these alternative methods in order to have complementary information on brain functional networks
  5. Keywords:
  6. Brain functional networks ; EEG ; Graph theory measures ; Partial cross-correlation ; Synchronization ; Article ; Brain function ; Controlled study ; Correlation analysis ; Cortical synchronization ; Electroencephalogram ; Human ; Human experiment ; Intermethod comparison ; Normal human ; Prediction ; Adult ; Brain ; Brain Mapping ; Electroencephalography ; Female ; Humans ; Male ; Middle Aged ; Models, Neurological ; Nerve Net ; Signal Processing, Computer-Assisted
  7. Source: Journal of Integrative Neuroscience ; Volume 10, Issue 2 , 2011 , Pages 213-232 ; 02196352 (ISSN)
  8. URL: http://www.worldscientific.com/doi/abs/10.1142/S0219635211002725?journalCode=jin