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Modulation of effective connectivity during vocalization with perturbed auditory feedback.

Amy L Parkinson¹, Oleg Korzyukov, Charles R Larson

¹Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX 78229, USA. Parkinson@uthscsa.edu

Neuropsychologia

|May 14, 2013

Summary

This study reveals how the brain processes voice pitch errors using auditory feedback. Dynamic causal modeling of event-related potentials shows distinct neural pathways for self-voice versus non-self-voice errors, crucial for vocal motor control.

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Area of Science:

Neuroscience
Auditory Perception
Speech Motor Control

Background:

Auditory feedback is critical for regulating voice fundamental frequency (F0).
Understanding the neural mechanisms of voice error detection is essential for speech motor control.

Purpose of the Study:

To investigate the neural network involved in processing auditory feedback errors during vocalization.
To differentiate the brain's response to self-voice errors versus external pitch shifts.

Main Methods:

Utilized a pitch-shift paradigm with varying feedback magnitudes (+100, +400 cents).
Measured event-related potentials (ERPs) during vocalization and passive listening.
Applied dynamic causal modeling (DCM) to analyze effective connectivity between brain regions (STG, inferior frontal gyrus, premotor areas).

Main Results:

Intrinsic superior temporal gyrus (STG) connectivity and interhemispheric STG connections are vital for identifying self-voice errors and sensory-motor integration.
Distinct left-to-right STG connectivity patterns were observed between 100 and 400 cent shift conditions.
Evidence suggests differential processing of self- and non-self-voice errors in the left and right hemispheres.

Conclusions:

The findings highlight the role of STG connectivity in voice error detection and sensory-motor integration.
Dynamic causal modeling of ERPs offers a method to characterize network properties in voice control models.
Neural processing of auditory voice feedback is lateralized and sensitive to error magnitude.