Computational neuroscience employs computational simulations[5] to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous.[6] The term mathematical neuroscience is also used sometimes, to stress the quantitative nature of the field.[7]
Models in theoretical neuroscience are aimed at capturing the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, and chemical coupling via network oscillations, columnar and topographic architecture, nuclei, all the way up to psychological faculties like memory, learning and behavior. These computational models frame hypotheses that can be directly tested by biological or psychological experiments.
^Patricia S. Churchland; Christof Koch; Terrence J. Sejnowski (1993). "What is computational neuroscience?". In Eric L. Schwartz (ed.). Computational Neuroscience. MIT Press. pp. 46–55. Archived from the original on 2011-06-04. Retrieved 2009-06-11.
^Paolo, E. D., "Organismically-inspired robotics: homeostatic adaptation and teleology beyond the closed sensorimotor loop", Dynamical Systems Approach to Embodiment and Sociality, S2CID15349751