Biological, Medical, and Soft Matter Physics session of the ANPA conference,  July 24-26, 2026, serves as a premier interdisciplinary forum for exploring the physical foundations of living systems. By merging the mechanical insights of biological physics with the clinical applications of medical physics and the material science of soft matter, this session examines how fundamental principles govern everything from molecular self-assembly to advanced diagnostic imaging and radiation therapies. We invite researchers, clinicians, and theorists to present their latest experimental and computational findings on topics ranging from liquid crystals and polymers to the complex dynamics of cells and tissues. Join us to share your research, foster new collaborations, and push the boundaries of how we understand and treat the human body; we look forward to receiving your abstracts and seeing you at the conference.

Epilepsy is increasingly recognized as a disorder of large-scale brain dynamics rather than a purely focal pathology. Seizures emerge when interactions among neuronal populations drive the brain across critical dynamical transitions that produce abrupt changes in network activity. In this lecture, I will present research from our group aimed at uncovering the dynamical principles underlying seizure generation, propagation, and localization in the human brain. Using extra- and intracranial electrophysiological recordings (EEG, iEEG/sEEG) from patients with drug-resistant epilepsy, we combine tools from nonlinear dynamics, network science, and statistical physics to track seizure-related brain activity. These approaches include Granger causality methods to map directed interactions among brain regions, node volatility to identify dynamically unstable network nodes associated with seizure onset, scale-free spectral analysis to characterize excitation–inhibition imbalance in epileptogenic cortex, and differential phase-space topology revealing catastrophic dynamical ruptures in neural activity. Together, these approaches help identify regions of cortical instability and improve seizure onset localization, which is critical for epilepsy surgery and other treatments. More broadly, this work highlights how nonlinear dynamics and statistical physics can illuminate mechanisms underlying pathological brain activity.