Personalized Virtual Brain Simulations and Vagus Nerve Stimulation Outcomes in Pediatric Epilepsy: A Multicenter...

Area of Science:

• Computational neuroscience
• Epilepsy research
• Neuroimaging analysis

Background:

• Vagus nerve stimulation (VNS) is a common therapy for drug-resistant epilepsy (DRE).
• Predicting VNS treatment response before surgery remains challenging.
• Biophysical brain modeling offers a novel approach to understand individual brain network differences.

Purpose of the Study:

• To assess The Virtual Brain (TVB) model's ability to capture pediatric DRE brain dynamics.
• To evaluate the relationship between TVB model predictability and VNS outcomes.
• To identify regional inhibitory features as potential VNS response biomarkers.

Main Methods:

• Constructed personalized virtual brains using preimplantation fMRI and dMRI data.
• Employed the reduced Wong-Wang neural mass model, optimized for individual participants.
• Compared local and global model parameters between VNS responders and nonresponders.

Main Results:

• Functional connectivity predictability was lower in nonresponders, indicating atypical brain dynamics.
• TVB simulations revealed stronger inhibitory synaptic weights in responders within the vagal afferent network.
• Key regions included the thalamus, cingulate, and frontal cortices.

Conclusions:

• This is the first study to explore TVB in pediatric DRE and VNS.
• Personalized brain dynamics simulations identified distinct inhibitory patterns between responders and nonresponders.
• These findings provide insights into VNS outcome variability and therapeutic mechanisms.