Encyclopedia of Computational Neuroscience

2015 Edition
| Editors: Dieter Jaeger, Ranu Jung

Software Tools for Modeling in Computational Neuroscience: Overview

Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6675-8_93

Detailed Description

Modelling in computational neuroscience is becoming a crucial tool for understanding how experimentally observed properties of neural systems emerge from lower-level biophysical processes. In the same way that processing of information happens at multiple physical scales in the nervous system, software applications have been created which specialize in modelling different aspects of neurons and networks.

This overview deals primarily with simulators of spiking neural networks, but other applications for modelling at lower levels (e.g., for biochemical signalling networks or reaction–diffusion within spines or whole cells) or higher scale (e.g., models of cognitive processes) have also been developed. There is also a focus on freely available, open-source applications.

Simulators

Abstract Neuron Simulations

The emergent properties of networks are frequently studied using highly simplified neurons with complex network connectivity and synaptic dynamics. NEST (http://www.nest-initiative.org...

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References

  1. Eliasmith C, Stewart TC, Choo X, Bekolay T, DeWolf T, Tang Y, Rasmussen D (2012) A large-scale model of the functioning brain. Science 338(6111):1202–1205. doi:10.1126/science.1225266PubMedGoogle Scholar
  2. Kozloski J, Wagner J (2011) An ultrascalable solution to large-scale neural tissue simulation. Front Neuroinform 5:15. doi:10.3389/fninf.2011.00015PubMedCentralPubMedGoogle Scholar
  3. McDougal R, Hines M, Lytton W (2013) Reaction–diffusion in the NEURON simulator. Front Neuroinform 7:28. doi:10.3389/fninf.2013.00028PubMedCentralPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Neuroscience, Physiology and PharmacologyUniversity College LondonLondonUK