Bayesian Modeling of the Dynamics of Phase Modulations and their Application to Auditory Event Related Potentials at Different Loudness Scales
| Autor: | Daniel J. Strauss, Zeinab Mortezapouraghdam, Lars Schwabe, Robert C. Wilson |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Auditory event
Speech recognition Neuroscience (miscellaneous) Concentration parameter Bayesian inference event-related potentials Instantaneous phase 050105 experimental psychology Loudness 03 medical and health sciences Cellular and Molecular Neuroscience 0302 clinical medicine von Mises distribution 0501 psychology and cognitive sciences Habituation Bayesian models Original Research instantaneous phase 05 social sciences circular statistics Phase synchronization long-term habituation Biological system Psychology 030217 neurology & neurosurgery Neuroscience |
| Zdroj: | Frontiers in Computational Neuroscience |
| ISSN: | 1662-5188 |
| Popis: | 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 60dB SPL, 70dB SPL, 80dB SPL and 90dB 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. |
| Databáze: | OpenAIRE |
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