Connectomics, Non-Euclidean data, and Statistics: Tutorial and Hands-on

Description

This workshop serves as the opening session of the program, providing an overview of connectomics and its integration with functional and imaging data analysis. Designed to highlight the transformative potential of connectomics in neuroscience, the session will explore how non-Euclidean data representations like graphs and networks facilitate a deeper understanding of brain network organization and its role in health and disease. Researchers will discuss pressing medical challenges, such as early detection of neurological disorders and the development of targeted treatments, while introducing advanced methodologies tailored to the analysis of complex neural data.

The workshop will feature a combination of tutorials and hands-on sessions, offering participants practical insights into statistical techniques and computational tools for analyzing functional and imaging datasets. Topics will include connectomics, functional data analysis, imaging data analysis, and non-Euclidean data analysis, with real-world case studies illustrating applications in conditions such as ADHD, autism, and Alzheimer’s disease. Attendees will leave equipped with a robust understanding of key concepts and actionable skills to process, analyze, and interpret brain connectivity data effectively.

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