Author

Vince D. Calhoun

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Open access Sep 2026

Message in a Bottleneck: Interpretable Deep Learning for Dynamic Effective Brain Connectivity.

Deep learning (DL) approaches find increasingly more applications in medical imaging analysis, where they excel at predictive tasks such as diagnosis classification, but often offer little insight on the underlying mechanisms governing complex systems, a key goal of scientific inquiry. One way to bridge this gap is to...

P. Popov, Cristian Morasso, Giorgio Dolci et al. · IEEE Transactions on Medical... · 0 citations

Open access Aug 2026

Algebraic Connectivity Reveals Modulated High-Order Functional Networks in Alzheimer's Disease.

Functional MRI is a neuroimaging technique that analyzes the functional activity of the brain by measuring blood-oxygen-level-dependent signals throughout the brain. The derived functional features can be used for investigating brain alterations in neurological and psychiatric disorders. In this work, we employed a hyp...

Giorgio Dolci, S. Saglia, Lorenza Brusini et al. · IEEE journal of biomedical a... · 0 citations

Preprint Jul 2026

AdaptICA: Data-Adaptive Transformation Learning for Independent Component Analysis

Independent component analysis (ICA) is widely used to recover latent structure from signal and imaging data, but standard ICA assumes that the observed measurement scale preserves a linear mixing structure. This assumption may fail for features produced through nonlinear preprocessing, such as band-specific power in m...

Lida Jalili, Jingyu Liu, Vince D. Calhoun et al. · 0 citations