Computational Neuroscience

Computational Neuroscience (pronunciation: /kəmˌpjuːtəˈreɪʃənəl ˈnʊərəʊˌsaɪəns/) is a branch of Neuroscience that employs mathematical models, theoretical analysis, and abstractions of the brain to understand the principles that govern the development, structure, physiology, and cognitive abilities of the nervous system.

Etymology

The term "Computational Neuroscience" was coined by Eric L. Schwartz, who organized a conference, held in 1985 in Carmel, California, at the request of the Systems Development Foundation to provide a summary of the current status of a field which until that point was referred to by a variety of names, such as neural modeling, brain theory, and neural networks. The proceedings of this definitional meeting were published in 1990 as the book "Computational Neuroscience".

Related Terms

Neural Network: A series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.
Neuroinformatics: A research field concerned with the organization of neuroscience data by the application of computational models and analytical tools.
Cognitive Modeling: A sub-discipline of simulation in artificial intelligence that involves studying how human intelligence can be represented and replicated in machines.
Neurophysiology: The study of the functioning of the nervous system, generally using physiological techniques that include measurement and stimulation with electrodes or optically with ion- or voltage-sensitive dyes or light-sensitive channels.