Mathematical descriptions of "dead time", or refractoriness, have long traditions dating back at least to mid sixties. In particular, at that time special attention was devoted to the description of the evolution of networks of switching elements whose behaviour was meant to simulate that of physiological neurons on the grounds of certain rather drastic simplifications. In the present paper we shall discuss this problem and point out quantitatively the effect of dead time magnitude on mean, variance and coefficient of variation of the output distribution. A similar attempt is also made when dead time is not fixed but undergoes random fluctuations described by a probability distribution independent of the input process.
Towards dead time inclusion in neuronal modeling / Buonocore, Aniello; C., Valerio; V., Giorno; A. G., Nobile. - STAMPA. - (2002), pp. 43-43. (Intervento presentato al convegno BIOCOMP2002 tenutosi a Vietri sul Mare (SA) nel 3-9 June 2002).
Towards dead time inclusion in neuronal modeling
BUONOCORE, ANIELLO;
2002
Abstract
Mathematical descriptions of "dead time", or refractoriness, have long traditions dating back at least to mid sixties. In particular, at that time special attention was devoted to the description of the evolution of networks of switching elements whose behaviour was meant to simulate that of physiological neurons on the grounds of certain rather drastic simplifications. In the present paper we shall discuss this problem and point out quantitatively the effect of dead time magnitude on mean, variance and coefficient of variation of the output distribution. A similar attempt is also made when dead time is not fixed but undergoes random fluctuations described by a probability distribution independent of the input process.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
