Pre-attentive Spectro-temporal Feature Processing in the Human Auditory System
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In the present study, we investigated the pre-attentive processing of low-level acoustic properties and the impact of this mechanism on functional lateralization in the human auditory system. Mismatch negativity (MMN) of the event-related potentials (ERP) were recorded in 19 adult humans who passively listened to a standard stimulus and spectrally and temporally deviant sounds. We predicted modulations of the MMN amplitude in response to spectrally and temporally graded deviants. Based on recent models of functional hemispheric lateralisation, we further hypothesized a left-lateralized source of the MMN in response to temporal deviants and, in contrast, a right-lateralized source of the MMN in response to spectral deviants. In agreement with our hypothesis, we showed that spectrally and temporally deviant sounds lead to robust MMNs recorded from frontocentral scalp electrodes. The amplitudes of the MMNs were modulated by the grade of spectral and temporal deviation from the standard sound. Furthermore, by using an assumption-free source localization approach (LORETA) we demonstrated functionally lateralized activations with dominance of the right hemisphere for the processing of spectral characteristics and of the left hemisphere for the processing of temporal acoustic properties. Results of our study further contribute to the ongoing debate on the role of low-level acoustic feature perception in functional hemispheric lateralization in the context of auditory and speech processing. Our data indicate that the pre-attentive feature-specific deviant processing is mediated by partly distinct neural subsystems for temporal and spectral information.
KeywordsEEG MMN Auditory spectral processing Temporal processing Functional lateralization
The authors wish to thank Dr. Thomas Jacobsen and Marcus Cheetham, as well as three anonymous reviewers for their helpful comments on previous version of the manuscript. This work was supported by Swiss National Science Foundation Grant No.: 320000-120661/1.
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