Physics and engineering of cognition: dynamical models of the ordered and disordered brain

Prof. Dr. Hamidreza Jamalabadi (Marburg University)

Abstract:
Recent advances in neuroscience have significantly deepened our understanding of the brain, yet our ability to model complex cognitive functions—such as memory and emotion—for personalized clinical interventions remains limited. This talk explores the potential of dynamical systems theory (DST) and complexity science in creating foundational models of cognition that can support predictive and personalized treatment in psychiatry. We will examine the challenges and prospects of translating neuroscientific knowledge into clinical applications, addressing questions such as: How close are we to establishing fundamental "laws" of cognition akin to those in physics? And how can these principles guide clinical practice in mental health? A focus will be placed on the interplay between biological and artificial neural networks, considering the divergence of AI models from neuroscience-informed principles. As generative models and data-driven DST techniques progress, they open new avenues for modeling cognitive processes and psychiatric symptom evolution over time. By combining insights from fMRI, electrophysiology, and behavioral data, I aim to showcase how advanced computational tools—machine learning, control theory, and deep learning—can model both neurotypical and disordered cognition. This talk seeks to foster dialogue on bridging theoretical understanding with practical applications, advancing a foundational framework for translational neuroscience.
About:
Training: B.Sc. and M.Sc. Electrical Engineering, University of Tehran.  PhD Neuroscience (Neural Information Processing) Tübingen.
Current position: Assistant Professor of Computational Psychiatry and Data Science, University of Marburg
Past Positions: Research Scientists at the University of Tübingen
(Medical Psychology, Psychiatry), MPI for Biological Cybernetics, LMU
Munich (Computational Biology, Psychology), University of Tehran (Cognitive Robotics)
Major Roles: Co-lead Machine Learning Infrastructure CRC/TRR 393,
Lead: Machine Learning EU project BRAWO, Associate PI The Adaptive Mind, Associate PI DYNAMIC
Research interest: Cognitive Systems, Machine Learning, Dynamical Systems, Neuroimaging, Mental Health