Modeling functional difference between gyri and sulci within intrinsic connectivity networks

Author:

Wang Qiyu12ORCID,Zhao Shijie12,He Zhibin12,Zhang Shu32,Jiang Xi45,Zhang Tuo12,Liu Tianming67,Liu Cirong89ORCID,Han Junwei12ORCID

Affiliation:

1. School of Automation , , Xi’an, Shaanxi 710072 , China

2. Northwestern Polytechnical University , , Xi’an, Shaanxi 710072 , China

3. School of Computer Science , , Xi’an, Shaanxi 710072 , China

4. School of Life Science and Technology , MOE Key Lab for Neuroinformation, , Chengdu, Sichuan 611731 , China

5. University of Electronic Science and Technology of China , MOE Key Lab for Neuroinformation, , Chengdu, Sichuan 611731 , China

6. Cortical Architecture Imaging and Discovery Lab , Department of Computer Science and Bioimaging Research Center, , Athens, GA 30605 , United States

7. The University of Georgia , Department of Computer Science and Bioimaging Research Center, , Athens, GA 30605 , United States

8. CAS Center for Excellence in Brain Science and Intelligence Technology , Institute of Neuroscience, , Shanghai 200031 , China

9. Chinese Academy of Sciences , Institute of Neuroscience, , Shanghai 200031 , China

Abstract

Abstract Recently, the functional roles of the human cortical folding patterns have attracted increasing interest in the neuroimaging community. However, most existing studies have focused on the gyro-sulcal functional relationship on a whole-brain scale but possibly overlooked the localized and subtle functional differences of brain networks. Actually, accumulating evidences suggest that functional brain networks are the basic unit to realize the brain function; thus, the functional relationships between gyri and sulci still need to be further explored within different functional brain networks. Inspired by these evidences, we proposed a novel intrinsic connectivity network (ICN)-guided pooling-trimmed convolutional neural network (I-ptFCN) to revisit the functional difference between gyri and sulci. By testing the proposed model on the task functional magnetic resonance imaging (fMRI) datasets of the Human Connectome Project, we found that the classification accuracy of gyral and sulcal fMRI signals varied significantly for different ICNs, indicating functional heterogeneity of cortical folding patterns in different brain networks. The heterogeneity may be contributed by sulci, as only sulcal signals show heterogeneous frequency features across different ICNs, whereas the frequency features of gyri are homogeneous. These results offer novel insights into the functional difference between gyri and sulci and enlighten the functional roles of cortical folding patterns.

Funder

Key-Area Research and Development Program of Guangdong Province

National Natural Science Foundation of China

National Key Research and Development Program of China

National Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Fundamental Research Funds for the Central Universities

Sichuan Science and Technology Program

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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