Duration-tuned neurons from the inferior colliculus of the big brown bat (Aubie et al. 2009)

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dtnet is a generalized neural network simulator written in C++ with an easy to use XML description language to generate arbitrary neural networks and then run simulations covering many different parameter values. For example, you can specify ranges of parameter values for several different connection weights and then automatically run simulations over all possible parameters. Graphing ability is built in as long as the free, open-source, graphing application GLE (http://glx.sourceforge.net/) is installed. Included in the examples folder are simulation descriptions that were used to generate the results in Aubie et al. (2009). Refer to the README file for instructions on compiling and running these examples. The most recent source code can be obtained from GitHub: <a href="https://github.com/baubie/dtnet">https://github.com/baubie/dtnet</a>
1 . Aubie B, Becker S, Faure PA (2009) Computational models of millisecond level duration tuning in neural circuits. J Neurosci 29:9255-70 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Inferior Colliculus;
Cell Type(s):
Gap Junctions:
Receptor(s): GabaA; AMPA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: C or C++ program;
Model Concept(s): Coincidence Detection; Simplified Models; Delay; Rebound firing;
Implementer(s): Aubie, Brandon [aubiebn at mcmaster.ca];
Search NeuronDB for information about:  GabaA; AMPA; Gaba; Glutamate;
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