Individual connectivity-based parcellations reflect functional properties of human auditory cortex

基于个体连接性的分区反映了人类听觉皮层的功能特性

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Abstract

Neuroimaging studies of the functional organization of human auditory cortex have focused on group-level analyses to identify tendencies that represent the typical brain. Here, we mapped auditory areas of the human superior temporal cortex (STC) in 30 participants (15 women) by combining functional network analysis and 1-mm isotropic resolution 7T functional magnetic resonance imaging (fMRI). Two resting-state fMRI sessions, and one or two auditory and audiovisual speech localizer sessions, were collected on 3-4 separate days. We generated a set of functional network-based parcellations from these data. Solutions with 4, 6, and 11 networks were selected for closer examination based on local maxima of the Dice coefficients and Silhouette values. The resulting parcellation of auditory cortices showed intraindividual reproducibility of 69-78% between resting-state sessions and 62-73% between resting-state and task sessions, indicating moderate reproducibility. The interindividual variability was significantly larger than intraindividual variability (Dice coefficient: 57%-68%, p < 0.001), indicating that the parcellations also captured meaningful interindividual variability. The individual-specific parcellations yielded the highest alignment with task response topographies, suggesting that individual variability in parcellations reflects individual variability in auditory function. Connectional homogeneity within networks was also highest for the individual-specific parcellations. Furthermore, the similarity in the functional parcellations was not explainable by the similarity of macroanatomical properties of the auditory cortex. Together, our results show that auditory areas in STC can be segmented into functional subareas based on functional connectivity. Our findings also suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.

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