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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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Gleeson, P. (2015). Software Tools for Modeling in Computational Neuroscience: Overview. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6675-8_93
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DOI: https://doi.org/10.1007/978-1-4614-6675-8_93
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6674-1
Online ISBN: 978-1-4614-6675-8
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