Abstract #1701

Multi-node directed cortical network for speech processing revealed by multivariate Granger causality analysis

Yayan Yin¹, Jiahong Gao¹, Bing Wu², Yang Fan², Bingjiang lyu¹, and Jianqiao Ge¹

¹Peking University, Beijing, China, People's Republic of, ²GE Healthcare, Beijing, China, People's Republic of

For decades, how the information flows among multiple brain regions remains unclear for speech processing, due to the challenge of mapping multi-node directed cortical pathways from brain images. In this work, multivariate Granger causality analysis is employed on functional MR images to reveal the effective connectivity of Chinese language-speech network for the first time. The results showed that left insula and posterior middle temporal gyrus were the strong driver nodes, the left middle frontal gyrus and superior temporal gyrus were the most received nodes in the network. We also found greater interhemispheric connectivity in females compared to males.

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