Abstract

Motivation: The Virtual Brain (TVB) is a neuroinformatic platform used to perform brain dynamic simulations integrating subject-specific imaging data. In standard TVB the input conduction velocity is fixed, making it insensitive to local effective measures of myelin content. Goal(s): Here we parameterized signal conduction velocity for TVB simulations. Approach: Considering myelin role in efficient neural conduction, myelin measures were integrated into TVB. Results: Making TVB sensitive to myelin content highlights variations in simulation outcomes with potential improvements in capturing spatiotemporal dynamics of brain activity. This advancement opens perspectives for realizing more accurate subject-specific simulations, representing a new step towards brain digital twinning. Impact: Brain Digital Twin technologies will transform personalized medicine, providing a better understanding of pathophysiological underpinnings of diseases. Our study demonstrates how simulating brain activity with The Virtual Brain model improves when integrating subject-specific neural conduction values, calculated from myelin measures.