Temporal dynamics of MEG phase information during speech perception: Segmentation and neural communication using mutual information and phase locking
Cogan, Gregory Brendan
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The incoming speech stream contains a rich amount of temporal information. In particular, information on slow time scales, the delta and theta band (125 - 1000 ms, 1 - 8 Hz), corresponds to prosodic and syllabic information while information on faster time scales (20-40 ms, 25 - 50 Hz) corresponds to feature/phonemic information. In order for speech perception to occur, this signal must be segregated into meaningful units of analysis and then processed in a distributed network of brain regions. Recent evidence suggests that low frequency phase information in the delta and theta bands of the Magnetoencephalography (MEG) signal plays an important role for tracking and segmenting the incoming signal into units of analysis. This thesis utilized a novel method of analysis, Mutual Information (MI) to characterize the relative information contributions of these low frequency phases. Reliable information pertaining to the stimulus was present in both delta and theta bands (3 - 5 Hz, 5 - 7 Hz) and information within each of these three sub-bands was independent of each other. A second experiment demonstrated that the information present in these bands differed significantly for speech and a non-speech control condition, suggesting that contrary to previous results, a purely acoustic hypothesis of this segmentation is not supported. A third experiment found that both low (delta and theta) and high (gamma) frequency information is utilized to facilitate communication between brain areas thought to underlie speech perception. Distinct auditory/speech networks that operated exclusively using these frequencies were revealed, suggesting a privileged role for these timescales for neural communication between brain regions. Taken together these results suggest that timescales that correspond linguistically to important aspects of the speech stream also facilitate segmentation of the incoming signal and communication between brain areas that perform neural computation.