Functional magnetic resonance imaging (fMRI) has great potential to evaluate how networks respond and compensate for network dysfunction caused by traumatic brain injury (TBI). In this study, sparse dictionary learning (sDL) and independent component analysis (ICA) were applied to resting-state fMRI (rs-fMRI) data, collected from a group of piglets 1-day (D1) and 7-days (D7) after TBI. Activation maps were generated using group ICA and group sDL, both with dual regression. Voxel-wise permutation tests were then applied to identify changes to six resting-state networks (RSNs). Consistency was observed through the two methods, indicating functional network activity changes after injury.
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