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.
