Neural Circuit Modeling of Large-Scale Brain Dynamics for Computational Psychiatry

Explore a comprehensive lecture on neural circuit modeling for computational psychiatry, focusing on large-scale brain dynamics. Delve into the critical explanatory gap in clinical neuroscience and learn how systems-level neuroimaging biomarkers emerge from microcircuit-level perturbations associated with disease states. Discover the potential of biophysically-based computational models in understanding resting-state functional connectivity and their integration with clinical and pharmacological neuroimaging. Examine the importance of local circuit properties and regional heterogeneity in shaping emergent functional connectivity. Investigate extensions for clinical neuroscience applications, including model fitting at the individual-subject level and simulation of pharmacological effects on brain dynamics. Gain insights into how these computational modeling approaches can inform the development of personalized therapeutics when combined with data analytic methods linking clinical and neural variation. The lecture covers topics such as cortical hierarchy, gene expression data, cytoarchitecture, interneuron subtypes, synaptic receptors, large-scale modeling, cortical heterogeneity, differential dynamics, and the connection between gene expression and large-scale modeling.