Promise and Limits of Hierarchical Dynamical RNNs for Individualized Resting-State fMRI
Carlotta B.C. Barkhau, Keyvan Mahjoory, Manuel Brenner, Elias Weber et autres
Abstract Modeling individual brain dynamics from resting-state fMRI (rs-fMRI) remains challenging due to substantial inter-subject variability, noise, and limited data length per subject. Here, we systematically evaluate whether hierarchical shallow piecewise-linear recurrent neural networks (shPLRNNs), recently introduced as interpretable dynamical system reconstruction …
de, rs, ca, us (code pays fourni par la source)
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bioRxiv (Cold Spring Harbor Laboratory)