Multiscale modeling of brain disease

Modeling and simulation are widely acknowledged to be essential tools for understanding the brain. and will be increasingly needed as innovative neurotechnologies are developed that add new molecular, cellular and circuit data. However, researchers from traditional neuroscience fields often find it difficult to understand the growing array of modeling approaches available. This perplexity partly arises from disputes within the modeling field, where complementary approaches have at times been presented as being in conflict, largely due to tensions between bottom-up and top-down perspectives. We include speakers from different backgrounds: physics, medicine, and neurobiology, who collectively and individually are attempting to reconcile these disparate intellectual traditions to face the challenges of understanding the brain. The presentations will largely focus on mechanistic multiscale modeling and phenomenological modeling based on neurobiological measures, but discussion will extend to implications for understanding brain disease, for extending deep learning, for developing bioengineering solutions, and for interacting with data-mining.