Computational Neuroscience is an interdisciplinary science that links the diverse fields of neuroscience, computer science, physics and applied mathematics together.
It serves as the primary theoretical method for investigating the function and mechanism of the nervous system.
Computational neuroscience is distinct from psychological connectionism and theories of learning from disciplines such as machine learning, neural networks and statistical learning theory in that it emphasizes descriptions of functional and biologically realistic neurons and their physiology and dynamics.
These models capture the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, protein and chemical coupling to network oscillations and learning and memory.
These computational models are used to test hypotheses that can be directly verified by current or future biological experiments.