Modeling the process of rate selection in neuronal activity.
We present the elements of a mathematical computational model that reflects the experimental finding that the time-scale of a neuron is not fixed; but rather varies with the history of its stimulus. Unlike most physiological models, there are no pre-determined rates associated with transitions between states of the system nor are there pre-determined constants associated with adaptation rates; instead, the model is a kind of "modulating automata" where the rates emerge from the history of the system itself. We focus in this paper on the temporal dynamics of a neuron and show how a simple internal structure will give rise to complex temporal behavior. The internal structure modeled here is an abstraction of a reasonably well-understood physiological structure. We also suggest that this behavior can be used to transform a "rate" code into a "temporal one".
Department of Computer Science, University of Haifa, Haifa, Israel. manevitz@cs.haifa.ac.il
Larry M
LM
Manevitz
Shimon
S
Marom
D000200:Action Potentials / Q000502:physiology; D000818:Animals; D003198:Computer Simulation; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D013997:Time Factors