Detection of irregularities in auditory sequences: A neural-network approach to temporal processing

Joachim Hass, Stefan Blaschke, Thomas Rammsayer, J. Michael Herrmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Combining experiments and modeling, we study how the discrimination of time intervals depends both on the interval duration and on contextual stimuli. Participants had to judge the temporal regularity of a sequence of standard intervals that contained a deviant interval. We find that the performance to detect the deviant increases with the number of standards preceding the deviant and decreases with the duration of the standard. While the effect of the standard duration can be explained by an neural network model that realizes the concept of multiple synfire chains, the position effect is incorporated into the model by an in-situ averaging process. Furthermore, experiments are discussed that are critical for the predictions of the model.
Original languageEnglish
Title of host publicationProceedings of the 11th Neural Computation and Psychology Workshop: Connectionist Models of Behaviour and Cognition
EditorsJ Mayor , N Ruh, K Plunkett
PublisherWorld Scientific
Number of pages12
Publication statusPublished - 2009

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