Computational Modeling of Cortical Maps

University Of Texas Austin, Austin TX

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Abstract

DESCRIPTION (provided by applicant): This project aims at advancing neuroscience in two ways: by providing software tools for large-scale computational modeling of the structure, development, and function of cortical maps, and by testing specific computational hypotheses about the development and function of the visual cortex. First, a Phase H version of map modeling software called Topographica will be developed, including tools for: (1) Rapid prototyping of multiple, large cortical maps, with specific afferent and lateral connectivity patterns, Hebbian adaptation and competitive self- organization, and firing rate and spiking neuron models; (2) Automatic generation of inputs for self-organization, allowing user control of the statistical environment, based on natural or computer-generated inputs; (3) Graphical user interface for designing networks and experiments, and integrated visualization and analysis tools for understanding the results, as well as for validating models through comparison with experimental results. The goal is to create a simulator that is user programmable, generalizes to different network arrangements and phenomena of different sizes, is interoperable with general-purpose analysis and visualization tools and low- level neuron simulators, and runs on PCs as well as parallel supercomputers'. Models can be built that focus on structural, functional, or integrative phenomena, either in the visual cortex or in other sensory cortices. The simulator will be available freely through the Internet; licensing and distribution of the software will be handled in accordance with University intellectual property policy. Second, in parallel with the software development effort, we propose to continue our research into computational modeling of the visual cortex, using Topographica as the platform. This work will focus on three main topics: (1) The role of self-organization and synchronized neural activity in perceptual grouping, including contour integration and illusory contours; (2) The role of internally-generated neural activity in the development of the visual cortex, including orientation maps and face processing; (3) The role of visual input in the development of motion and directional selectivity maps. Together these two components of the project aim at making computational modeling of cortical maps a viable research focus in behavioral neuroscience.