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Fig. 4 | Brain Informatics

Fig. 4

From: Review of computational neuroaesthetics: bridging the gap between neuroaesthetics and computer science

Fig. 4

A workflow from functional connectivity measurement to brain functional network attributes. a. Neuroimaging data recorded from device, these data can be EEG, fMRI, or MEG. b Functional connectivity between brain regions is estimated from signals and form a correlation matrix. c The correlation matrix produces a binary connectivity graph by thresholding. d The visualization of binary graph. e The binary connectivity graph is randomly reconnected to produce a random reconnected graph. f The cluster coefficient (C) and average shortest path length (L) are extracted by measuring binary connectivity graph and random reconnected graph to obtain normalized brain functional network attributes

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