Quantification of neural functional connectivity during an active avoidance task

Many behavioral and cognitive processes are associated with spatiotemporal dynamic communication between brain areas. Thus, the quantification of functional connectivity with high temporal resolution is highly desirable for capturing in vivo brain function. However, brain functional network quantification from EEG recordings has been commonly used in a qualitative manner. In this paper, we consider pairwise dependence measures as random variables and estimate the pdf for each electrode of the arrangement. A metric imposed by the quadratic Cauchy-Schwartz Mutual Information quantifies these pdfs. We present the results by brain regions simplifying the analysis and visualization drastically. The proposed metric of functional connectivity quantification is addressed for temporal dependencies of the brain network that can be related to the task.

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