Meeting Banner
Abstract #1111

Integration of myelin-sensitive biophysical features in virtual brain models: towards healthy and pathological Brain Digital Twins

Eleonora Lupi1, Anita Monteverdi2, Marta Gaviraghi1, Elena Grosso1, Alessandro Marinelli1, Marco Battiston3, Francesco Grussu3,4, Baris Kanber3,5, Ferran Prados Carrasco3,5,6, Antonio Ricciardi3, Nicolò Rolandi1,3,7, Rebecca S Samson3, Madiha Shatila3, Jed Wingrove3, Marios C Yiannakas3, Claudia Casellato1,2, Egidio D’Angelo1,2, Claudia A. M. Gandini Wheeler-Kingshott1,2,3, and Fulvia Palesi1,2
1Department of Brain & Behavioral Sciences, University of Pavia, Pavia, Italy, 2Digital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy, 3NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, 4Radiomics Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, 5Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, United Kingdom, 6E-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain, 7Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom

Synopsis

Keywords: Functional Connectivity, Brain Connectivity, Brain modeling, The Virtual Brain, conduction velocity

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.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Abstract

Keywords