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Computational neuroscience

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Definition

noun

A branch of neuroscience that makes use of computer simulations and theoretical models in an attempt to understand the function of the nervous system


Supplement

Neuroscience is the scientific study of the nervous system and is concerned with the structure, development, function, chemistry, pharmacology, and pathology of the nervous system. Modern tools and technologies (e.g. molecular biology, electrophysiology, computational methods, etc.) led to the advancement of research on nervous system. As a result, neuroscience is now comprised of various branches.

Computational neuroscience is a branch of neuroscience that focuses on the function of the nervous system through the use of computer simulations and theoretical models. Thus, this field of neuroscience that encompasses computer science, mathematics, and physics. It aims to describe physiological and biological aspects of the neural systems using theoretical models and simulations. Its topics of interests are membrane currents, chemical coupling, network oscillations, columnar and topographic architecture, learning, and memory. Some of the major research works in computational neuroscience include single-neuron modeling, axonal patterning and dendrite formation during development, processing of sensory processing, and synaptic plasticity.

The term computational neuroscience was coined by Eric L. Schwartz, a professor in cognitive and neural systems, during a conference in California in 1985.


Synonym(s):

  • theoretical neuroscience

See also: