Redistribution of neural phase coherence reflects establishment of feedforward map in speech motor adaptation

R Sengupta, SM Nasir - Journal of Neurophysiology, 2015 - journals.physiology.org
Journal of Neurophysiology, 2015journals.physiology.org
Despite recent progress in our understanding of sensorimotor integration in speech
learning, a comprehensive framework to investigate its neural basis is lacking at
behaviorally relevant timescales. Structural and functional imaging studies in humans have
helped us identify brain networks that support speech but fail to capture the precise
spatiotemporal coordination within the networks that takes place during speech learning.
Here we use neuronal oscillations to investigate interactions within speech motor networks …
Despite recent progress in our understanding of sensorimotor integration in speech learning, a comprehensive framework to investigate its neural basis is lacking at behaviorally relevant timescales. Structural and functional imaging studies in humans have helped us identify brain networks that support speech but fail to capture the precise spatiotemporal coordination within the networks that takes place during speech learning. Here we use neuronal oscillations to investigate interactions within speech motor networks in a paradigm of speech motor adaptation under altered feedback with continuous recording of EEG in which subjects adapted to the real-time auditory perturbation of a target vowel sound. As subjects adapted to the task, concurrent changes were observed in the theta-gamma phase coherence during speech planning at several distinct scalp regions that is consistent with the establishment of a feedforward map. In particular, there was an increase in coherence over the central region and a decrease over the fronto-temporal regions, revealing a redistribution of coherence over an interacting network of brain regions that could be a general feature of error-based motor learning in general. Our findings have implications for understanding the neural basis of speech motor learning and could elucidate how transient breakdown of neuronal communication within speech networks relates to speech disorders.
American Physiological Society
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