BI 148 Gaute Einevoll: Brain Simulations

Brain Inspired - A podcast by Paul Middlebrooks

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Check out my free video series about what's missing in AI and Neuroscience Support the show to get full episodes and join the Discord community. Gaute Einevoll is a professor at the University of Oslo and Norwegian University of Life Sciences. Use develops detailed models of brain networks to use as simulations, so neuroscientists can test their various theories and hypotheses about how networks implement various functions. Thus, the models are tools. The goal is to create models that are multi-level, to test questions at various levels of biological detail; and multi-modal, to predict that handful of signals neuroscientists measure from real brains (something Gaute calls "measurement physics"). We also discuss Gaute's thoughts on Carina Curto's "beautiful vs ugly models", and his reaction to Noah Hutton's In Silico documentary about the Blue Brain and Human Brain projects (Gaute has been funded by the Human Brain Project since its inception). Gaute's website.Twitter: @GauteEinevoll.Related papers:The Scientific Case for Brain Simulations.Brain signal predictions from multi-scale networks using a linearized framework.Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortexLFPy: a Python module for calculation of extracellular potentials from multicompartment neuron models.Gaute's Sense and Science podcast. 0:00 - Intro 3:25 - Beautiful and messy models 6:34 - In Silico 9:47 - Goals of human brain project 15:50 - Brain simulation approach 21:35 - Degeneracy in parameters 26:24 - Abstract principles from simulations 32:58 - Models as tools 35:34 - Predicting brain signals 41:45 - LFPs closer to average 53:57 - Plasticity in simulations 56:53 - How detailed should we model neurons? 59:09 - Lessons from predicting signals 1:06:07 - Scaling up 1:10:54 - Simulation as a tool 1:12:35 - Oscillations 1:16:24 - Manifolds and simulations 1:20:22 - Modeling cortex like Hodgkin and Huxley