The rockefeller university

Event Details

Type

Center for Studies in Physics and Biology Seminars

Speaker(s)

Manish Saggar, Ph.D., associate professor, Stanford University

Speaker bio(s)

Understanding how the brain dynamically coordinates cognition, emotion, and behavior remains a central challenge in neuroscience and psychiatry. Traditional neuroimaging approaches often rely on static or averaged representations of brain activity, which obscure the rich temporal structure and inter-network transitions that may underlie both healthy and pathological states. In this talk, I will introduce a novel framework that combines topological data analysis (TDA) with graph-theoretic modeling to uncover reproducible and interpretable patterns in brain dynamics. Using the Mapper algorithm, we construct individual-level brain-state graphs that reveal flexible or rigid transitions between functional states across resting-state and task-based fMRI. These dynamic motifs not only reflect traits such as rumination and attentional flexibility but also offer new biomarkers for clinical populations. I will also present our recent efforts to integrate deep learning and latent factor modeling with the Research Domain Criteria (RDoC) framework. This work provides a data-driven refinement of mental health constructs by identifying latent “motifs” that better explain individual differences in brain activation across multiple tasks. Together, these approaches highlight the importance of moving beyond summary statistics toward manifold-level insights into brain function, with implications for both precision psychiatry and the development of AI-driven diagnostic tools.

Open to

Public

Phone

(212) 327-8636

Sponsor

Melanie Lee
(212) 327-8636
leem@rockefeller.edu