Myelin plays a crucial role in how reliably the signal travels from one neuron to another. Many neurological diseases affect myelin and cause disturbed signal transmission in the brain network. A convenient way to better understand not just pathology, but also how the brain works, is through connectomics. Connectomics provides a unique way to model the brain as a network of interconnected regions. Additionally, it is common to assign weights to the connections that could represent some underlying microstructural property. However, the well-established standard diffusion-derived measures (such as the fractional anisotropy (FA) and the number of streamlines) lack specificity. Therefore, the connectomes weighted with the standard diffusion-derived metrics may not be able to fully characterize the underlying changes caused by a specific pathology.
This talk focuses on the myelin-weighted connectome, a novel method that complements the brain networks with a myelin-sensitive measure. A wide range of myelin-sensitive MRI-derived metrics can be used to weigh the connectome, including the longitudinal relaxation rate and the Magnetization Transfer Ratio. But the question is which one is better? After establishing the myelin-weighted connectome in healthy individuals, it was employed to study the alterations of myelin in individuals with Parkinson’s Disease and Multiple Sclerosis. Generally, the studies show that the myelin-weighted connectome can offer a more comprehensive understanding of brain microstructure and the white matter myeloarchitecture. Moreover, it could potentially lead to the development of new biomarkers that can capture the early microstructural changes caused by pathologies affecting the myelin.
Speaker(s): Tommy Boshkovski, PhD,
Virtual: https://events.vtools.ieee.org/m/338343
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