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John Rinzel (NYU, Neural Science and Mathematics)

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Bistable Dynamics of Perceiving Ambiguous Stimuli When experiencing an ambiguous sensory stimulus (e.g., the vase-faces image), subjects may report random alternations (time scale, seconds) between the possible interpretations. I will describe dynamical models with multiple time scales for neuronal populations that compete (fast time scale) through mutual inhibition for dominance - showing alternations (slow time

Cheng Ly (VCU, Department of Mathematics and Applied Mathematics)

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Are differences between Parkinson’s patients and healthy subjects like other brain diseases? The dynamical state of cortical neural activity constrains the complexity of functions it can perform. A marginally stable dynamical state - called criticality - is thought to be beneficial for brain functions that require multiple time scales, broad dynamic range, and large information

Alessandro Selvitella (Purdue University Fort Wayne, Data Science and Applied Statistics)

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A connubio of Machine Learning and PDEs for Scientific Discovery in the Biological Sciences In this talk, I will describe some problems at the intersection of data science and applied mathematics with particular focus on questions emerging in the study of the neuro-musculo-skeletal-environmental system. Many aspects of this system can be studied with (potentially different)