Non-invasive Conduction Velocity Mapping in Brain Networks: A novel imaging framework for axonal fingerprinting of brain connections in health and disease

Introduction

Axonal bundles in cerebral white matter form the structural basis of functional brain networks, enabling effective integration of neural activity. The axonal connections are not homogenous structures. Axons differ in diameter and myelination, enabling signal conduction at different velocities.

Axonal Diversity

This axonal diversity is a clinically relevant microstructural feature, as neurodegenerative or neuroinflammatory processes can affect axon diameters differently.

Advances in Imaging

Recent advances in Magnetic Resonance Imaging (MRI) have enabled the non-invasive mapping of the microstructural properties of brain network connections in live brains. However, attempts to correlate these structural features with brain function have not yet been successful.

Pioneering Research

I have pioneered the mapping of axon diameters that are directly linked to the conductive properties of axonal connections by using diffusion MRI in living human brains. Additionally, I have established a unique cross-disciplinary validation setup for such methods by combining nanoscopic 3D Synchrotron Radiation Imaging and functional cell-specific targeting techniques.

CoM-BraiN Framework

By Conduction Velocity Mapping in Brain Networks (CoM-BraiN), I will be able to unravel the altered functional dynamics of the microstructural connections in the diseased brain. Methodologically, I will push the frontiers of MRI by creating a new translational CoM-BraiN framework for non-invasive and in-vivo studies in animals and humans.

Clinical Implications

Clinically, CoM-BraiN will provide a new window into the characterization of neuropathological changes in the diseased brain. It will also contribute to the identification of structure-function fingerprints of psychiatric and neurodegenerative disorders that are thought to be a major pathogenic factor in many brain diseases.