Keywords: Data Analysis, fMRI (resting state)Functional MRI (fMRI) experiments serve a key role in advancing our understanding of human brain function during normal and disease states. Analysis of high-dimensional fMRI data can significantly benefit from recent deep learning approaches, yet existing methods are insufficiently sensitive to the contextual representations in fMRI data across diverse time scales. Here, we present a novel transformer model for fMRI analysis that effectively captures local and global dependencies in fMRI data. Comprehensive demonstrations are provided that show the superior performance of BolT in gender and disease detection against state-of-the-art learning-based methods.
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