What is all the noise about in interval timing?
Cognitive processes such as decision-making, rate calculation and planning require an accurate estimation of durations in the supra-second range-interval timing. In addition to being accurate, interval timing is scale invariant: the time-estimation errors are proportional to the estimated duration. The origin and mechanisms of this fundamental property are unknown. We discuss the computational properties of a circuit consisting of a large number of (input) neural oscillators projecting on a small number of (output) coincidence detector neurons, which allows time to be coded by the pattern of coincidental activation of its inputs. We showed analytically and checked numerically that time-scale invariance emerges from the neural noise. In particular, we found that errors or noise during storing or retrieving information regarding the memorized criterion time produce symmetric, Gaussian-like output whose width increases linearly with the criterion time. In contrast, frequency variability produces an asymmetric, long-tailed Gaussian-like output, that also obeys scale invariant property. In this architecture, time-scale invariance depends neither on the details of the input population, nor on the distribution probability of noise.
Department of Physics and Astronomy, College of Charleston, , 66 George Street, Charleston, SC 29624, USA.
Sorinel A
SA
Oprisan
Catalin V
CV
Buhusi
D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D003342:Corpus Striatum / Q000378:metabolism; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008568:Memory / Q000502:physiology*; D008959:Models, Neurological; D009474:Neurons / Q000378:metabolism; D051381:Rats; D013997:Time Factors
interval timing; noise; striatal beat frequency