Neuro Next Seminar
"Computing With a Mess: How Complex, Heterogeneous and Noisy Components Contribute to the Brain’s Computational Power"
Stefan Mihalas, Ph.D.
Investigator, Allen Institute for Brain Science
Affiliate Professor of Applied Mathematics
University of Washington
To participate virtually, CLICK HERE
*Lunch provided for in-person attendees
Speaker Bio
Mihalas joined the Allen Institute in 2011 from Johns Hopkins University, where he was a postdoctoral fellow in neuroscience and subsequently an associate research scientist. As a computational neuroscientist, Mihalas has worked on models of both molecular and systems neuroscience including nervous system development, synaptic plasticity, minimalistic spiking neuron models, self-organized criticality, visual attention and figure ground segregation. His current research interests are aimed at building models to elucidate how large networks of interacting neurons produce cognitive behaviors. At the Allen Institute, Mihalas integrates anatomical and physiological connectivity data to generate models of visual perception in the mouse. To this end, he works to build a series of models of increasing complexity for both individual components, i.e., neurons, synapses, and microcircuits, as well as for large portions of the entire system. This series of models will be compared to the simplified theoretical predictions from statistical physics, information theory and computer vision. Mihalas received his Diploma in physics and M.S. in mathematics from West University of Timisoara in Romania. He received his Ph.D. in physics from the California Institute of Technology.
Faculty Host: Hannah Choi, Ph.D.
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