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In: Timing & Time Perception


One of the major challenges for computational models of timing and time perception is to identify a neurobiological plausible implementation that predicts various behavioral properties, including the scalar property and retrospective timing. The available timing models primarily focus on the scalar property and prospective timing, while virtually ignoring the computational accessibility. Here, we first selectively review timing models based on ramping activity, oscillatory pattern, and time cells, and discuss potential challenges for the existing models. We then propose a multifrequency oscillatory model that offers computational accessibility, which could account for a much broader range of timing features, including both retrospective and prospective timing.

In: Timing & Time Perception

Interval timing behavior and its sensitivity to both temporal context and changes in dopamine (DA) levels has recently received considerable attention. Nevertheless, the exact manner in which those interactions occur is far from clear. We examined temporal reproduction with feedback in the supra-seconds range as a function of DA levels using two well-studied timing procedures. Healthy young and aged participants were studied as well as Parkinson’s disease (PD) patients tested ON and OFF their dopaminergic medication. The findings confirm the hypothesis that the ‘migration effect’ (e.g., ‘short’ durations are over-produced and ‘long’ durations are under-produced) in PD patients and the closely related Vierordt’s effect are largely influenced by the effective level of DA and in the case of the ‘migration effect’ by the probability of feedback as well. Using a Bayesian model seeking optimal timing under conditions of uncertainty, we were able to accurately simulate the distorted patterns of temporal reproduction in all groups of participants. As DA levels decrease across groups, optimal timing behavior shifts towards a greater reliance on a statistical representation of all of the durations reproduced within a specific temporal context rather than on the representation of a single duration being timed on any one trial. This analysis demonstrates the utility of Bayesian models of interval timing and highlights the importance of DA levels on clock speed and the associated uncertainty that contributes to temporal distortions.

In: Timing & Time Perception