title: Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.
abstract: Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.
authors.affiliation: School of Information Science and Engineering, Changzhou University, Changzhou, Jiangsu, China.|Changzhou Key Laboratory of Biomedical Information Technology, Changzhou, Jiangsu, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Zou
authors.affiliation: School of Information Science and Engineering, Changzhou University, Changzhou, Jiangsu, China.|Changzhou Key Laboratory of Biomedical Information Technology, Changzhou, Jiangsu, China.
authors.forename: Qian
authors.initials: Q
authors.lastname: Guo
authors.affiliation: School of Information Science and Engineering, Changzhou University, Changzhou, Jiangsu, China.|Changzhou Key Laboratory of Biomedical Information Technology, Changzhou, Jiangsu, China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Xu
authors.affiliation: School of Information Science and Engineering, Changzhou University, Changzhou, Jiangsu, China.|Changzhou Key Laboratory of Biomedical Information Technology, Changzhou, Jiangsu, China.
authors.forename: Biao
authors.initials: B
authors.lastname: Yang
authors.affiliation: School of Information Science and Engineering, Changzhou University, Changzhou, Jiangsu, China.|Changzhou Key Laboratory of Biomedical Information Technology, Changzhou, Jiangsu, China.
authors.forename: Zhuqing
authors.initials: Z
authors.lastname: Jiao
authors.affiliation: Changzhou NO.2 People's Hospital Affiliated with Nanjing Medical University, Changzhou, Jiangsu, China.
authors.forename: Jianbo
authors.initials: J
authors.lastname: Xiang
mesh_terms: D000465:Algorithms; D001921:Brain / Q000378:metabolism*; D001931:Brain Mapping; D016000:Cluster Analysis; D004644:Emotions / Q000502:physiology*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D055815:Young Adult
keywords: Functional connectivity; ICA; cognitive reappraisal; density-based k-means clustering method