Models of neural computation: Difference between revisions

Revision as of 00:40, 26 September 2016

Revision as of 00:41, 26 September 2016

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===Genetic algorithms===

[[Genetic algorithms]] are used to evolve neural (and sometimes body) properties in a model brain-body-environment system so as to exhibit some desired behavioral performance. The evolved agents can then be subjected to a detailed analysis to uncover their principles of operation. Evolutionary approaches are particularly useful for exploring spaces of possible solutions to a given behavioral task because these approaches minimize a priori assumptions about how a given behavior ought to be instantiated. They can also be useful for exploring different ways to complete a computational neuroethology model when only partial neural circuitry is available for a biological system of interest .<ref>[http://www.scholarpedia.org/article/Computational_neuroethology].</ref>

===MATLAB===

[[MATLAB]] is a programming environment that is used globally in virtually all neuroscience and cognitive psychology laboratories .<ref>[http://www.elsevier.com/wps/find/bookdescription.cws_home/716634/description#descriptiontitle].</ref> MATLAB integrates the modelling and experimental processes by bringing together, under the aegis of an intuitive [[scripting language]], powerful data analysis and mathematical modelling tools.

===NEURON===

NEURON, developed at Duke University, is a simulation environment for modeling individual neurons and networks of neurons .<ref>[http://www.neuron.yale.edu/neuron/].</ref> With the NEURON interface, it is possible to generate publication-quality results without having to write any program code at all. The NEURON simulation engine is based on a Hodgkin–Huxley type model with a Borg–Graham formulation.

==Embodiment in electronic hardware==