Bayesian modeling of the dynamics of phase modulations and their application to auditory event related potentials at different loudness scales

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Abstract

We study the effect of long-term habituation signatures of auditory selective attention reflected in the instantaneous phase information of the auditory event-related potentials (ERPs) at four distinct stimuli levels of 60, 70, 80, and 90 dB SPL. The analysis is based on the single-trial level. The effect of habituation can be observed in terms of the changes (jitter) in the instantaneous phase information of ERPs. In particular, the absence of habituation is correlated with a consistently high phase synchronization over ERP trials. We estimate the changes in phase concentration over trials using a Bayesian approach, in which the phase is modeled as being drawn from a von Mises distribution with a concentration parameter which varies smoothly over trials. The smoothness assumption reflects the fact that habituation is a gradual process. We differentiate between different stimuli based on the relative changes and absolute values of the estimated concentration parameter using the proposed Bayesian model.

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Mortezapouraghdam, Z., Wilson, R. C., Schwabe, L., & Strauss, D. J. (2016). Bayesian modeling of the dynamics of phase modulations and their application to auditory event related potentials at different loudness scales. Frontiers in Computational Neuroscience, 10(JAN). https://doi.org/10.3389/fncom.2016.00002

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