Corresponding anatomical and coactivation architecture of the human precuneus showing similar connectivity patterns with macaques.

Neuroimage

Key Laboratory for Neurolnformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; National Laboratory

Published: October 2019


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Article Abstract

The precuneus (PCun) is one of the most expanded areas of the association cortex and plays an important role in integrating information from different modalities. However, whether the functional architecture of PCun is shared by humans and macaques is an open question. We used both anatomical connectivity and task-dependent coactivation patterns to parcellate the human PCun and consistently identified three subregions in the human PCun using two independent datasets. Two subregions were located in the dorsal PCun and one subregion was located in the ventral PCun. This parcellation scheme for the PCun was supported by identifying the subregion-specific networks and by functional characterization. Then, the absolute and relative gray matter volume of precuneus in human and macaque was calculated and significantly smaller absolute and relative gray matter volume in macaque was identified. Next, three macaque PCun subregions were defined based on our tractographic atlas. Finally, the whole brain anatomical connectivity patterns and connectivity fingerprints with 17 predefined homologous target brain areas were mapped for each PCun subregion and revealed that the PCun shares similar anatomical connectivity patterns in humans and macaques. The similar anatomical connectivity patterns of PCun were validated by an independent in-house dataset. Our findings demonstrated that anatomical connectivity patterns can reflect the functional architecture of the PCun in humans and that the functional architecture of the PCun is similar in humans and macaques.

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http://dx.doi.org/10.1016/j.neuroimage.2019.07.001DOI Listing

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