Sean Hill
Speaker of Workshop 1
Will talk about: Challenges for Multi-scale Modeling Languages
Sean Hill is the Blue Brain Project Manager for Computational Neuroscience. Dr. Hill received his Ph.D. in Computational Neuroscience from the University of Lausanne, Switzerland where he investigated the computational role of the auditory thalamocortical circuitry in the rat. He subsequently held postdoctoral positions at The Neurosciences Institute in La Jolla, California and the University of Wisconsin, Madison. In the course of his research, Hill has developed numerous large-scale models of neural systems and is the designer/developer of the general-purpose neural simulator Synthesis. As part of his research, he developed the first large-scale model of the cat visual thalamocortical system that replicates neural activity during wakefulness and sleep. He began his work with the Blue Brain project as a member of the Computational Biology Group at the IBM T.J. Watson Research Center in 2006 and became a Blue Brain employee in 2008. His research interests include the use of biologically-realistic models to study the role of emergent phenomena in information processing, network connectivity and synaptic plasticity in the central nervous system, from the neocortical column to the whole brain, and across different arousal conditions including waking and sleep.
Understanding the effect of a disease or a treatment on individual brains requires understanding the link between the genetic, subcellular, electric and whole brain scales. Relevant phenomena within the brain span a remarkable range of physical and temporal scales. This includes subcellular activity ranging from the level of individual molecules, protein folding and gene expression to physiological networks governing transcription, signaling and metabolism. Electrical activity ranges from local voltage-gated ion channels and neuron firing behavior to collective network effects, oscillations and whole brain activity. Brain connectivity itself ranges from synapses placed with submicron precision on specific portions of individual neurons to local microcircuitry, mesoscale axonal patterning and long-ranging fiber tracts that connect brain regions across the brain. Other phenomena including plasticity, homeostasis and development occur across timescales ranging from milliseconds to hours, days or years. Mathematical approaches are often already available to model interactions within each scale, however the challenge remains to develop mathematical approaches to describe relationships across scales. Modeling languages also, must be extended to facilitate the description of models within and across spatial and temporal scales. Exploring examples such as linking a molecular-scale synapse model with an electrical-scale neuron model, I will present some of the challenges posed by describing multiscale relationships relevant to brain function and dysfunction.
