From Connectomics to Brain Dynamics

Description

Ordinary Differential Equations (ODEs) have long provided a robust mathematical framework for modeling the dynamic behavior of brain networks. These models are crucial for understanding the temporal evolution of neural activity, capturing how brain states change over time through the complex interplay of structural connectivity and dynamic functional processes. However, understanding the brain’s dynamic activity goes beyond ODEs alone. The evolving nature of brain networks—whether in healthy cognition, neuroplasticity, or pathological conditions—requires interdisciplinary approaches that integrate dynamic modeling with a variety of techniques to capture the richness of brain activity.

This workshop will bridge the gap between traditional ODE-based models and broader approaches to brain dynamics, including advanced neuroimaging methods, network theory, and data-driven models. We will explore how temporal fluctuations in brain activity—ranging from oscillatory behavior to chaotic dynamics—emerge and interact across different brain regions. Through this lens, we aim to foster discussions on how brain dynamics can be modeled in real-time, how perturbations like external stimuli or pathological changes propagate, and how multimodal data can be leveraged to track these changes.

Key topics of discussion will include:

• Brain dynamics and the temporal evolution of neural activity through ODEs and beyond.
• The integration of multimodal data (e.g., structural MRI, functional MRI, electrophysiological recordings) for modeling brain dynamics.
• Causal inference in neuroimaging and brain networks, examining how dynamic interactions shape cognitive processes and dysfunctions.
• Advances in data-driven methods, such as machine learning and generative AI, to model brain dynamics and their relationship to brain structure.
• The role of dynamic systems in understanding neuroplasticity, cognition, and neurological disorders.

This workshop aims to bring together experts from both mathematical modeling and neuroscience research to discuss and share innovative methods for modeling the dynamics of neuroimaging and brain networks. Invited speakers from diverse fields, including neuroimaging, systems neuroscience, and computational modeling, will share their insights on the evolving landscape of brain dynamics. We will discuss how these approaches can be applied to a variety of topics, from basic cognition to the pathophysiology of neurological diseases.