Author

Victoria Shevchenko

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#artificial intelligence Preprint Sep 2026

Flattening the Connectome Spectrum: A Spectral Filter for FC Induces a Pretraining Target for fMRI Encoders

Self-supervised pretraining reshaped prediction in language and vision, and brain foundation models (BFMs) inherited its promise. Representations learned from large unlabelled corpora should capture individual functional dynamics and generalise across cohorts. However, kernel ridge regression (KRR) fitted on functional...

G. Marraffini, Victoria Shevchenko, Carlo Alberto Barbano et al. · 0 citations

Preprint Jul 2026

CoCoT-EEG: Contrastive-Pretrained Multiscale Convolutional Transformer for EEG Decoding

Self-supervised pretrained foundation models (FM) have shown early promise for non-invasive electroencephalogram (EEG) decoding applications. Many recent large-scale models converged on the approach of tokenizing raw EEG followed by masked reconstruction pretraining. However, this recipe has been shown to be suboptimal...

Gabriel Mahuas, Victoria Shevchenko, Ugo Tanielian et al. · 0 citations