Sunday, Jun 23: 9:00 AM - 1:00 PM
1357
Educational Course - Half Day (4 hours)
COEX
Room: ASEM Ballroom 203
Brain white matter contains the highly myelinated axons that connect brain regions. These connections, organized in axon bundles, form the anatomic-functional networks that implement brain computations. Diffusion-weighted MRI (dMRI), together with computational tractography, provides in vivo estimates of the trajectory of these tracts through the white matter. In addition, dMRI provides information about the microscopic diffusion of water molecules within the tissue. Because water diffusion is affected by the physical structure of the tissue, this makes dMRI a sensitive probe of brain tissue properties. Taken together, these methods are used for tractometry, which focuses on the measurement of the physical properties of brain tracts. This course will introduce concepts in tractometry, including basic data analysis and processing, segmentation of the white matter into anatomically-defined major tracts, the extraction of tissue properties along the tracts, and the statistical analysis of these properties. The course will also demonstrate the application of these methods to the understanding of the role of brain connections in brain development and aging, as well as in cognition. A broad range of approaches, methodologies and software tools will be presented, with significant hands-on components and interactive elements. This educational course is an updated version of the tractometry course which was very well received and well attended in 2021, 2022 and 2023. This iteration will blend the best of previous sessions, including a lecture devoted to introductory material, aimed primarily at novices to the field.
- Learners will understand the basic concepts of tract-based analysis of the human brain white matter.
- Learners will use software that segments white matter into different major bundles
- Learners will compare different approaches to statistical analysis of white matter tracts.
This course is intended for researchers (from trainees to faculty) with an interest in brain connectivity and the biology of brain connections. Researchers who are using datasets where multi-modal measurements are available (e.g., fMRI and dMRI) will benefit from expanding their analytic tool-set to include modern robust and rigorous tractometry methods.
Presentations
This introductory lecture will cover the fundamentals of diffusion MRI (dMRI) analysis. The principles of dMRI signal formation will be introduced. Analysis methods that are used to make inferences about the microstructure of white matter at the level of individual voxels will be surveyed. Since this is an area of long-standing, but also very active research, we will introduce both classical signal models, as well as newer biophysical tissue models. Finally, we will discuss methods of computational tractography, used to make inferences about brain connections. We will point out some promising applications of tractography, as well as acknowledge challenges and avenues for future research.
Presenter
Ariel Rokem, University of Washington Seattle, WA
United States
There are two broad families of methods for obtaining the white-matter bundles that undergo tractometry analyses. In the supervised approach, the goal is to reconstruct known tracts of interest (TOIs) based on a priori neuroanatomical definitions. In the unsupervised approach, the goal is to group whole-brain tractography data into clusters based on their similarity, without a priori knowledge of pathways of the brain. This presentation will give an overview of the two approaches, discuss how both of them can benefit by use of the underlying anatomy, and end with an interactive tour of white-matter tracts.
Tractography enables quantitative mapping of the brain’s structural connectivity using measures of connectivity or tissue microstructure. This presentation will provide a high-level overview of how tractography is used to perform quantitative analysis in health and disease. We will describe two main types of quantitative analyses of tractography, including: 1) tract-specific analysis that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that is often data-driven and generally studies the structural connectivity of the entire brain. We highlight three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation, and quantification. We then show example studies that have used these quantitative tractography approaches to study the brain’s white matter.
Presenter
Fan Zhang, University of Electronic Science and Technology of China Chengdu, Sichuan
China
The human brain develops most rapidly during the first year of life, making early infancy a particularly exciting period for investigating structural properties of the white matter. Yet, those features that make infants unique, also bring distinct challenges for tractometry. For example, the almost complete lack of myelination in the infant brain results in reduced fractional anisotropy, and gray/white matter contrast compared to the adult brain. In this course, I will go over these challenges and propose specific adjustments that can be made to classical tractometry pipelines to improve the precision of white matter structural assessments in infants.
Presenter
Mareike Grotheer, University of Marburg - Philipps-Universität Marburg Marburg, Hesse
Germany
Postnatal brain development carries through infancy, adolescence, and into early adulthood. Development is varied and complex. Brain regions mature and reach developmental plateaus at differing rates, and microstructural features such as axonal density, diameter, fiber coherence, and myelination often follow different trajectories that are not consistent across tracts. Alongside this complex process, children are learning a vast array of cognitive and behavioral skills as they interact with their world. Together we will explore how the development of white matter relates to cognitive and behavioral outcomes, with a focus on childhood and adolescent development, and the impact of adverse childhood experiences.
Presenter
Bryce Geeraert, University of Calgary Calgary, Alberta
Canada
Neurodegenerative diseases are chronic, progressive disorders marked by gradual neuron loss in the central nervous system. The onset and progression of neurodegeneration are linked to disrupted neural circuits and white matter tracts, possibly involving demyelination and axonal degeneration. Tractometry is vital for detecting and quantifying these disruptions, aiding researchers, and clinicians in understanding affected pathways and their impact on patients' cognitive and motor deficits. This data is crucial for insights into disease pathophysiology. This presentation explores tractometry's utility in the pathological assessment of neurodegenerative diseases.