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Moo K Chung

1 paper in the library · publishing 2017

Papers

Topological Network Analysis of Electroencephalographic Power Maps.

Connectomics in neuroimaging : First International Workshop, CNI 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, proceedings. CNI (Workshop) (1st : 2017 : Quebec, Quebec) January 1, 2017 Yuan Wang, Moo K Chung, Daniela Dentico et al.

Topological data analysis (TDA) of EEG power maps can reveal differences in brain activity between long-term meditators and meditation-naive practitioners that standard methods miss. The authors propose a new inference procedure based on persistent homology, a TDA technique that tracks topological features across sublevel-set filtrations of high-density EEG topographic maps. Applied to simulated and real EEG data, the method compares persistent homological features of spectral power in high-frequency bands between the two groups. The findings suggest that TDA offers additional insight into the neuroplastic effects of meditation on brain activity beyond conventional statistical approaches.