Connectomics

Description

Brain connectomics offers a transformative approach to understanding the brain’s complex network of neural connections.  By mapping how different brain areas interact and collaborate to support cognition, connectomics provides a comprehensive perspective on both normal and impaired brain function. This integrative approach is essential for studying brain development in children and aging-related physiological changes. Moreover, disruptions in neural connectivity play a central role in neurological and psychiatric conditions, including ADHD, autism and neurodegenerative diseases such as Alzheimer’s disease. 

The Connectomics: Non-Euclidean Data Analysis for Brain Structure and Function long program will focus on cutting-edge methodologies for analyzing brain structure and function. These include the application of Ordinary Differential Equations (ODEs) to model dynamic interactions between different brain regions and temporal changes in brain activity and system stability; the study of time-varying networks under various longitudinal designs and sampling scenarios; uncertainty quantification, inference and conformal prediction regions for networks and other brain characteristics; and assessing association between brain BOLD signals, aiming at a  mathematical framework that leads to a better  understanding of both normal development and pathological changes.

More generally, the program will address the challenges of analyzing increasingly complex brain data, which often exist in non-Euclidean spaces such as networks, graphs, and high-dimensional data objects. Traditional statistical methods fall short when handling these types of data, making the advancement of non-Euclidean statistics crucial. By developing new tools and methodologies for metric statistics, this program will enable more accurate and interpretable analysis of brain connectivity and its impact on cognition and behavior.

Aligning with the goals of the Brain Initiative, which seeks to accelerate neurotechnology development and enhance data science research, this program will explore the latest advancements in brain imaging, data integration, and personalized medicine. By bringing together experts from mathematics, statistics, neuroscience, and engineering, the program aims to foster interdisciplinary collaborations and push the boundaries of brain research.

Through a series of lectures, workshops, and collaborative research projects, the program will provide participants with the tools and knowledge necessary to advance the understanding of brain function, improve disease diagnosis, and develop more targeted therapeutic interventions.

General Information on Long Programs

Long program participants spend time (generally, anywhere from a few days up to the full length of the program) in-person at IMSI with other researchers, creating new collaborations and generating new research in the program’s focus area. Participants who are only intending to apply for a workshop should not apply for the long program but should apply for the relevant workshop(s) instead. Long program participants can be PhD students, Postdocs, Faculty, or Researchers outside of academia such as national labs, industry, government, etc. There is some funding available, and funding can be requested in the application.