The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA

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• 作者：Victor M. Vergara^a ; ^{vvergara@mrn.org} ; Andrew R. Mayer^a ; ^d ; ^e ; Eswar Damaraju^a ; ^b ; Kent Hutchison^c ; Vince D. Calhoun^a ; ^b
• 刊名：NeuroImage
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：145
• 期：part_PB
• 页码：365-376
• 全文大小：1542 K
• 卷排序：145

文摘

We analyze different preprocessing pipelines for group independent component analysis (gICA). Pipelines were evaluated using classification algorithms, cross validation and statistical methods. The data pinpoint a strategy that best seems to prepare fMRI data for gICA.