James A. Bednar, Yoonsuck Choe, Judah De Paula, Risto Miikkulainen, and Jefferson Provost. The Topographica Cortical Map Simulator. Perception, 2005. Poster and abstract presented at the European Conference on Visual Perception (A Coruna, Spain)
(unavailable)
The goal of the Topographica project is to makelarge-scale computational modeling of cortical maps practical. Theproject consists of a set of software tools for computational modelingof the structure, development, and function of cortical maps, such asthose in the visual cortex. These tools are designed to support:(1) Rapid prototyping of multiple, large cortical maps, with specific afferent, lateral, and feedback connectivity patterns, and adaptation and competitive self-organization, using firing rate and spiking neuron models;(2) Automatic generation of inputs for self-organization and testing, allowing user control of the statistical environment, based on natural or computer-generated inputs;(3) A graphical user interface for designing networks and experiments, with integrated visualization and analysis tools for understanding the results, as well as for validating models through comparison with experimental results.The simulator is user programmable, generalizes to different networkarrangements and phenomena at different scales, is interoperable withgeneral-purpose analysis and visualization tools and low-level neuronsimulators, and runs on widely available computing hardware. WithTopographica, models can be built that focus on structural,functional, or integrative phenomena, either in the visual cortex orin other sensory cortices. The first full release of Topographica isscheduled for late 2005, and it will be freely available over theinternet at topographica.org. We invite cortical map researchers inall fields to begin using Topographica, to help establish a communityof researchers who can share code, models, and approaches. Support: This research was supported in part by the U.S. National Institute of Mental Health under Human Brain Project grant R01-MH66991.
@Article{bednar:ecvp05,
author = "James A. Bednar and Yoonsuck Choe and Judah {De~Paula} and Risto Miikkulainen and Jefferson Provost",
title = "The {Topographica} Cortical Map Simulator",
journal = "Perception",
note = "Poster and abstract presented at the European
Conference on Visual Perception (A Coruna,
Spain)",
year = 2005,
missing = "pages",
abstract = { The goal of the Topographica project is to make
large-scale computational modeling of cortical maps practical. The
project consists of a set of software tools for computational modeling
of the structure, development, and function of cortical maps, such as
those in the visual cortex. These tools are designed to support:
(1) Rapid prototyping of multiple, large cortical maps, with specific
afferent, lateral, and feedback connectivity patterns, and
adaptation and competitive self-organization, using firing rate
and spiking neuron models;
(2) Automatic generation of inputs for self-organization and testing,
allowing user control of the statistical environment, based on
natural or computer-generated inputs;
(3) A graphical user interface for designing networks and experiments,
with integrated visualization and analysis tools for understanding
the results, as well as for validating models through comparison
with experimental results.
The simulator is user programmable, generalizes to different network
arrangements and phenomena at different scales, is interoperable with
general-purpose analysis and visualization tools and low-level neuron
simulators, and runs on widely available computing hardware. With
Topographica, models can be built that focus on structural,
functional, or integrative phenomena, either in the visual cortex or
in other sensory cortices. The first full release of Topographica is
scheduled for late 2005, and it will be freely available over the
internet at topographica.org. We invite cortical map researchers in
all fields to begin using Topographica, to help establish a community
of researchers who can share code, models, and approaches.
Support: This research was supported in part by the U.S. National
Institute of Mental Health under Human Brain Project grant
R01-MH66991.
},
}
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