Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation

Neomi Singer, Gilad Poker, Netta Dunsky-Moran, Shlomi Nemni, Shira Reznik Balter, Maayan Doron, Travis Baker, Alain Dagher, Robert J. Zatorre, Talma Hendler*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music – a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation.

Original languageEnglish
Article number120183
StatePublished - 1 Aug 2023


FundersFunder number
Bloomfield family TAU-McGill
European Union's Horizon 2020 Framework Program for Research and Innovation945539
Quebec and Israel on Biomedical Imaging0102180
Tel-Aviv University BrainBoost
Canadian Institute for Advanced Research
McGill University
Eldee Foundation
Canadian Institutes of Health Research
Canada First Research Excellence Fund
Israel Innovation Authority67951


    • Electrical finger-print
    • Musical pleasure
    • One-class EEG model
    • Reward
    • Simultaneous EEG-fMRI
    • Ventral striatum


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