Geometric classification of brain network dynamics via conic derivative discriminants

Matthew F. Singh, Todd S. Braver, ShiNung Ching
2018 Journal of Neuroscience Methods  
Over the past decade, pattern decoding techniques have granted neuroscientists improved anatomical specificity in mapping neural representations associated with function and cognition. Dynamical patterns are of particular interest, as evidenced by the proliferation and success of frequency domain methods that reveal structured spatiotemporal rhythmic brain activity. One drawback of such approaches, however, is the need to estimate spectral power, which limits the temporal resolution of classification.
doi:10.1016/j.jneumeth.2018.06.019 pmid:29966600 pmcid:PMC6417100 fatcat:tvbw6xw6mjhtbkqktzc6owm4ja