Abstract #1663

Estimating whole brain connectivity dynamics using spectral clustering

Ivor Cribben¹

¹Finance and Statistical Analysis, Alberta School of Business, Edmonton, AB, Canada

A great challenge in neuroscience is the understanding of the dynamic manner in which brain regions interact with one another in both task-based and resting-state brain imaging studies. In this work, we introduce a novel statistical method, called Network Change Point Detection (NCPD), which dynamically clusters brain regions by their functional connectivity. NCPD promises to offer deeper insight into the large-scale characterizations and mechanisms of the brain as it can be used for the dynamic modelling of a very large number of voxels or brain regions. We apply this new method to a resting-state fMRI study.

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