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.
Mak AK, , Hu ZG, , Zhang JX, , Xiao ZW, , Lee TM. Neural correlates of regulation of positive and negative emotions: An fMRI study. Neurosci Lett. 2009; 457(2): 101.
Koch K, , Pauly K, , Kellermann T, , Seiferth NY, , Reske M, , Backes V, et al. Gender differences in the cognitive control of emotion: An fMRI study. Neuropsychologia. 2007; 45(12): 2744.
Ertl M, , Hildebrandt M, , Ourina K, , Leicht G, , Mulert C. Emotion regulation by cognitive reappraisal - The role of frontal theta oscillations. NeuroImage. 2013; 81: 412.
Li XB, , Luo YJ. The Emotion Effects in the Spatial and Verbal Working Memory: ERP and fMRI Evidence. Advances in Psychological Science. 2011; 19(2): 166.
Suma HN, , Murali S. Principal Component Analysis for Analysis and Classification of fMRI activation maps. IJCSNS. 2007; 7(11): 235.
Bai P, , Shen HP, , Huang XM, , Truong Y. A supervised singular value decomposition for independent component analysis of fMRI. Stat Sin. 2008; 18(4): 1233.
Rashid B, , Damargju E, , Pearlson GD, , Callhoun VD. Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects. Front Hum Neurosci. 2014; 8: 897.
Windischberger C, , Barht M, , Lamm C, , Schroeder L, , Bauer H, , Gur RC, et al. Fuzzy cluster analysis of high-field functional MRI data. Artif Intell Med. 2003; 29(3): 203.
Liu X, , Zhu XH, , Qiu PH, , Chen W. A correlation-matrix-based hierarchical clustering method for functional connectivity analysis. J Neurosci Methods. 2012; 211(1): 94.
Jing YS, , Zeng WM, , Wang NZ, , Ren TL, , Shi YC, , Yin J, et al. GPU-based parallel group ICA for functional magnetic resonance data. Comput Methods Programs Biomed. 2015; 119(1): 9.
Sui J, , Adali T, , Pearlson GD, , Calhoun VD. An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques. NeuroImage. 2009; 46(1): 73.
Wang JY, , Zhang F, , Zhou XZ, , Shi YC, , Luo W. Segmentation of caption region using wavelet transform and K-mean clustering. Journal of Computer-Aided Design & Computer Graphics. 2006; 18(10): 1508.
Fu DS, , Zhou C. Improved K-means algorithm and its implementation based on density. Journal of Computer Applications. 2011; 31(2): 432.
Yedla M, , Pathakota SR, , Srinivasa TM. Enhancing K-means Clustering Algorithm with Improved Initial Center. IJCSIT. 2010; 1(2): 121.
Salman R, , Kecman V, , Li Q, , Strack R, , Test E. Fast K-means algorithm clustering. IJCNC. 2011; 3(4): 17.
He HS, , DeZonia BE, , Mladenoff DJ. An aggregation index (AI) to quantify spatial patterns of landscapes. Landscape Ecology. 2000; 15(7): 591.
Nelson BD, , Fitzgerald DA, , Klumpp H, , Shankmana SA, , Phana KL. Prefrontal engagement by cognitive reappraisal of negative faces Original Research Article. Behav Brain Res. 2015; 279: 218.
Wessing I, , Rehbein MA, , Postert C, , Fürniss T, , Junghöfer M. The neural basis of cognitive change: Reappraisal of emotional faces modulates neural source activity in a frontoparietal attention network. NeuroImage. 2013; 81: 15.
Belden AC, , Luby JL, , Pagliaccio D, , Barch DM. Neural activation associated with the cognitive emotion regulation of sadness in healthy children. Dev Cogn Neurosci. 2014; 9: 136.