Data-Driven Modeling of Brain Circuits Based on a Systematic Experimental Platform

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The Mindscope project at the Allen Institute aims to elucidate mechanisms underlying cortical function in the mouse, focusing on the visual system. This involves concerted efforts of multiple teams characterizing cell types, connectivity, and neuronal activity in behaving animals. An integral part of these efforts is the construction of models of the cortical tissue and cortical computations. To achieve this, multi-model experimental data are integrated into a highly realistic 230,000-neuron model of the mouse cortical area V1. We perform systematic comparisons of simulated responses to in vivo experiments and investigate the structure-function relationships in the models to make mechanistic predictions for experimental testing. To enable this work, we developed the software suite called Brain Modeling ToolKit (BMTK) and a modeling file format called SONATA. These tools, the models, and simulation results are all being made freely available to the community via the Allen Institute Modeling Portal.

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Anton Arkhipov, Ph.D.

Anton Arkhipov joined the Allen Institute in 2013 as an assistant investigator in the Modeling, Analysis, and Theory group. He is leading efforts to carry out biophysically detailed simulations of individual neurons as well as large-scale neuronal circuits from the mouse visual system. The main focus of his research is on integration of experimental anatomical and physiological data to build sophisticated, highly realistic computational models of cortical circuitry, with the aim of elucidating mechanisms underlying processing of visual information in the cortex. Before joining the Allen Institute he was a Postdoctoral Fellow at D. E. Shaw Research in New York City, where he used a specialized supercomputing architecture to perform computational studies of structure-function relationships in proteins, with the emphasis on cancer-associated cell-surface receptors. Arkhipov received his B.S. and M.S. in Physics from Moscow Institute of Physics and Technology and a Ph.D. in Physics from the University of Illinois at Urbana-Champaign.

Publication Year: 2019

Data-Driven Modeling of Brain Circuits Based on a Systematic Experimental Platform
  • Course Provider: IEEE Brain
  • Course Number: FDBRMAPWEB0001
  • Duration (Hours): 1
  • Credits: None