Samuel Neymotin, PhD

My primary research in computational neuroscience is aimed at developing computer models of neurons and neuronal networks including laminar models of neocortex, thalamus, and hippocampus, constrained with anatomical and electrophysiology data. I then use the models to predict the microcircuit mechanisms contributing to neural dynamics and function. Collaboration with electrophysiologists has led to development of novel analysis methods and modeling tools used to decipher the origin of the dynamic electrophysiological patterns. Our research strategy offers translational benefits for neuropsychiatric disorders where changes in dynamic activity patterns appear to be key biomarkers.