Abstract

Mounting studies have demonstrated that brain functions are determined by its external functional connectivity patterns. However, how to characterize the voxel-wise similarity of whole brain functional connectivity pattern is still largely unknown. In this study, we introduced a new method called functional connectivity homogeneity (FcHo) to delineate the voxel-wise similarity of whole brain functional connectivity patterns. FcHo was defined by measuring the whole brain functional connectivity patterns similarity of a given voxel with its nearest 26 neighbors using Kendall’s coefficient concordance (KCC). The robustness of this method was tested in four independent datasets selected from a large repository of MRI. Furthermore, FcHo mapping results were further validated using the nearest 18 and six neighbors and intra-subject reproducibility with each subject scanned two times. We also compared FcHo distribution patterns with local regional homogeneity (ReHo) to identify the similarity and differences of the two methods. Finally, FcHo method was used to identify the differences of whole brain functional connectivity patterns between professional Chinese chess players and novices to test its application. FcHo mapping consistently revealed that the high FcHo was mainly distributed in association cortex including parietal lobe, frontal lobe, occipital lobe and default mode network (DMN) related areas, whereas the low FcHo was mainly found in unimodal cortex including primary visual cortex, sensorimotor cortex, paracentral lobule and supplementary motor area. These results were further supported by analyses of the nearest 18 and six neighbors and intra-subject similarity. Moreover, FcHo showed both similar and different whole brain distribution patterns compared to ReHo. Finally, we demonstrated that FcHo can effectively identify the whole brain functional connectivity pattern differences between professional Chinese chess players and novices. Our findings indicated that FcHo is a reliable method to delineate the whole brain functional connectivity pattern similarity and may provide a new way to study the functional organization and to reveal neuropathological basis for brain disorders.

Highlights

  • Resting-state functional magnetic resonance imaging which primarily reflects the ongoing spontaneous fluctuations in the human brain is a task-independent approach to detect intrinsic neural activity related to self-initiated behavior (Fox and Raichle, 2007)

  • We introduced a voxel-wise manner to characterize the whole brain functional connectivity homogeneity (FcHo) for a specific voxel with its nearest 26 voxels in four independent Resting-state functional magnetic resonance imaging (rs-fMRI) datasets using Kendall’s coefficient concordance (KCC)

  • The higher FcHo values than whole brain mean was mainly observed in default mode network (DMN), parietal lobe, lateral prefrontal cortex, dorsomedial prefrontal cortex, occipital cortex, cuneus, and dorsal anterior insula (Figure 1A)

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Summary

Introduction

Resting-state functional magnetic resonance imaging (rs-fMRI) which primarily reflects the ongoing spontaneous fluctuations in the human brain is a task-independent approach to detect intrinsic neural activity related to self-initiated behavior (Fox and Raichle, 2007). Based on different whole brain functional connectivity patterns, many researches were performed to parcellate the human brain areas into different functional subareas (Yeo et al, 2011; Wang et al, 2015b, 2016b, 2017b). Li et al (2002) proposed cross-correlation coefficients of spontaneous low frequency (COSLOF) to measure the functional synchrony between possible pairs of voxel time courses in a brain region. Tomasi and Volkow (2010) proposed functional connectivity density (FCD) to further characterize regionally functional homogeneity in the human brain. Different measurements have been proposed to characterize the similarities of functional activities and regionally functional connectivities, how to map the voxel-wise whole brain functional connectivity pattern similarity is still largely unknown. To map voxel-wise whole brain functional connectivity patterns similarity will provide an important approach to investigate the functional architecture of the brain

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