Data-Driven Spectral Decomposition Of Ecog Signal From An Auditory Oddball Experiment In A Marmoset Monkey: Implications For Eeg Data In Humans

This paper presents a data-driven method to extract spatiotemporal dynamics of mismatch negativity in a marmoset monkey. In this, we treat electrocorticographic (ECoG) data as observables of a skew-product dynamical system and extract the patterns of the neural dynamics from the point of view of the operator-theoretic formulation of ergodic theory. We successfully extract time-separable frequencies without bandpass filtering. Second, we examine in more detail the frequency band most commonly associated with MMN - beta-band activity (13-20 Hz) and proceed to cross-validate our results with those obtained by Komatsu, Takaura, and Fuji (2015). Having ensured the compatibility and statistical significance of the results, we then examine the spatiotemporal dynamics, and we find that MMN is in part driven by a synchronization in brain response following a deviation in the auditory stimuli.