Multimodal virtual brain: when hd-EEG drives simulations of brain dynamics closer to patients’ reality

Motivation: The creation of virtual brain models able to fit individual resting-state fMRI (rs-fMRI) time series is needed, aiming to obtain digital twins of patients useful for clinical translation. Goal(s): In this work we develop a multimodal virtual brain for a group of mild cognitive impairment patients, a new step towards the creation of patients' digital twins. Approach: For each subject hd-EEG data were integrated in the multimodal virtual brain together with structural connectivity to drive brain dynamics simulations. Results: Multimodal virtual brain revealed its superior ability to fit rs-fMRI time series recorded in patients. Impact: With its capacity to perform simulations closer to reality, this new model opens new prospectives in the use of virtual brains as digital representations of patients, a crucial tool for the development of personalized interventions.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/3142
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00
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article

Multimodal virtual brain: when hd-EEG drives simulations of brain dynamics closer to patients’ reality

Anna Pichiecchio, Lisa Maria Farina, Fulvia Palesi, Alfredo Costa et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
EEG and Brain-Computer Interfaces
article

Multimodal virtual brain: when hd-EEG drives simulations of brain dynamics closer to patients’ reality

Anna Pichiecchio, Lisa Maria Farina, Fulvia Palesi, Alfredo Costa, Stefano Francesco Cappa, Francesca Conca, Claudia A. M. Gandini Wheeler‐Kingshott, Michele Terzaghi, Anna Castelnovo, Egidio D’Angelo, Elena Capriglia, Paolo Antonino Grasso, Matteo Cotta Ramusino, Agnese Augello, Anita Monteverdi, Giuseppe Calia, Chiara Totaro
article en

Abstract

Motivation: The creation of virtual brain models able to fit individual resting-state fMRI (rs-fMRI) time series is needed, aiming to obtain digital twins of patients useful for clinical translation. Goal(s): In this work we develop a multimodal virtual brain for a group of mild cognitive impairment patients, a new step towards the creation of patients' digital twins. Approach: For each subject hd-EEG data were integrated in the multimodal virtual brain together with structural connectivity to drive brain dynamics simulations. Results: Multimodal virtual brain revealed its superior ability to fit rs-fMRI time series recorded in patients. Impact: With its capacity to perform simulations closer to reality, this new model opens new prospectives in the use of virtual brains as digital representations of patients, a crucial tool for the development of personalized interventions.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 75%
EEG and Brain-Computer Interfaces
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