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Beyond Scalar Timing Theory: Integrating Neural Oscillators with Computational Accessibility in Memory

In: Timing & Time Perception
Authors:
Zhuanghua Shi Department of Experimental Psychology, Ludwig Maximilian University of Munich, 80802 Munich, Germany

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Bon-Mi Gu Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA

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Stefan Glasauer Chair of Computational Neuroscience, Brandenburg University of Technology Cottbus, 03046 Cottbus, Germany

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Warren H. Meck Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA

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Abstract

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.

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