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Updated: Jun 27, 2025

Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

Published on: May 10, 2024

Virtual brain twins: from basic neuroscience to clinical use.

Huifang E Wang¹, Paul Triebkorn¹, Martin Breyton^1,2

¹Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France.

National Science Review

|May 3, 2024

Summary

This summary is machine-generated.

Virtual brain twins are personalized brain models that use an individual's brain data to advance scientific and clinical understanding. These adaptive models show promise for healthy aging and various neurological and psychiatric disorders.

Keywords:

brain disorder inference neuroscience personalized modeling virtual brain twin

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Published on: May 12, 2019

Area of Science:

Computational Neuroscience
Neuroimaging
Personalized Medicine

Background:

Virtual brain twins are advanced, individualized brain models.
These models are crucial for both scientific research and clinical applications.
They offer a personalized, generative, and adaptive approach to understanding the brain.

Purpose of the Study:

To present a standard model for personalized whole-brain network models.
To detail the methods for personalizing these models using individual brain imaging data.
To demonstrate the application of these models in healthy aging and various clinical conditions.

Main Methods:

Personalization involves assembling subject-specific brain networks.
Connectivity is mapped directly into models and generalized to other parameters.
Model inversion using probabilistic machine learning estimates relevant parameters.

Main Results:

Personalized whole-brain network models were applied to healthy aging.
The models were utilized for epilepsy, Alzheimer's disease, multiple sclerosis, Parkinson's disease, and psychiatric disorders.
Spatial masks were introduced for parameter relevance, guided by physiological hypotheses.

Conclusions:

Virtual brain twins offer a powerful framework for personalized neuroscience.
These models have significant potential in understanding and treating brain disorders.
Further research is needed to address key challenges and explore future directions.