A Simplified Model of Communication Between Time Cells: Accounting for the Linearly Increasing Timing Imprecision - Zeki, Mustafa; Balcı, Fuat (Frontiers in Computational Neuroscience, 2019)
Many organisms can time arbitrary time intervals flexibly with high accuracy but substantial variability between trials. One of the core psychophysical properties of interval timing function is the proportionality of the standard deviation of timed responses to their mean (time scale invariance). Recent experimental evidence show the existence of time cells that fire sequentially with progressing time. The time interval between consecutively firing time cell ensembles is shown to increase with the progressing time. When time is calculated by adding distributions of time intervals between time cell ensembles firing one after another, the noise is compressed by the square root function because of the way the standard deviation is calculated. So, how should the communication between successive time cell ensembles be so that noise increases linearly with progressing time? We came up with a simplified model of time cells that proposes a mechanism for the synaptic communication of time cells that fire one after another. When the model is simulated with noisy conductances multiple times, the standard deviation of spike times of the time cells increases with mean spike-times. In addition, the model is shown to remain robust with respect to the changes in the key model parameters.