CortexMAE adapts Vision Transformers to fMRI via cortical flat maps, shows power-law scaling on 2.1K hours of data, and outperforms priors on cognitive state decoding while failing to beat a simple functional connectivity baseline on subject-level trait prediction.
Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity mri.Cerebral cortex, 28(9):3095–3114, 2018
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BrainDyn is a sheaf neural ODE model that encodes brain region activity history via LSTMs, projects states through restriction maps, and uses a sheaf Laplacian for message passing to generate continuous-time dynamics on brain graphs.
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Scaling Vision Transformers for Functional MRI with Flat Maps
CortexMAE adapts Vision Transformers to fMRI via cortical flat maps, shows power-law scaling on 2.1K hours of data, and outperforms priors on cognitive state decoding while failing to beat a simple functional connectivity baseline on subject-level trait prediction.
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BrainDyn: A Sheaf Neural ODE for Generative Brain Dynamics
BrainDyn is a sheaf neural ODE model that encodes brain region activity history via LSTMs, projects states through restriction maps, and uses a sheaf Laplacian for message passing to generate continuous-time dynamics on brain graphs.