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Author

Shakiba Moradi

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Open access Sep 2026

Cross-Modal Learning from fMRI to DOT: Leveraging Large-Scale Neuroimaging for fNIRS Decoding.

Functional near-infrared spectroscopy (fNIRS) and its tomographic extension, diffuse optical tomography (DOT), offer portable and non-invasive measures of functional brain hemodynamics with great potential for everyday neuroimaging. However, the present scarcity of publicly available DOT data hinders deep learning mode...

Shakiba Moradi, Theekshana Dissanayake, Nils Harmening et al. · 2 citations
#machine learning Preprint Sep 2026

Representational and Functional Robustness to Electrode Montages in EEG Foundation Models

This work investigates the effects of different electrode montages through a joint functional and representational analysis of four EEG foundation models selected to span distinct montage-handling designs, and shows that aggregation, not the encoder alone, determines functional robustness.

Jakob Steglich, Justus Meyer zu Bexten, Shakiba Moradi et al. · 0 citations
Review Open access Jan 2026

Cedalion tutorial: a Python-based framework for comprehensive analysis of multimodal fNIRS and DOT from the lab to the everyday world

Cedalion is a Python-based open-source framework designed to unify advanced model-based and data-driven analysis of multimodal fNIRS and DOT data within a reproducible, extensible, and community-driven environment.

E. Middell, Laura B. Carlton, Shakiba Moradi et al. · 3 citations

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