We propose to investigate the validity and applicability of fuzzy clustering (FCM) for the identification of dynamic functional connectivity (dFC) patterns in resting-state fMRI data, and comparing it with two approaches that have been used in this context (PCA and K-means). For such purpose, all methods were applied to data simulating either the joint or separate expression of dFC patterns, and to empirical data, collected from epilepsy patients. Both clustering methods, particularly FCM, outperformed PCA. Concomitantly, results from empirical data indicated that the occurrence of epileptic activity of patients was separately expressed by the dFC patterns.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords