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Neural Dynamics Based Timing in the Subsecond to Seconds Range

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Neurobiology of Interval Timing

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 829))

Abstract

The brain must solve a wide range of different temporal problems, each of which can be defined by a relevant time scale and specific functional requirements. Experimental and theoretical studies suggest that some forms of timing reflect general and inherent properties of local neural networks. Like the ripples on a pond, neural networks represent rich dynamical systems that can produce time-varying patterns of activity in response to a stimulus. State-dependent network models propose that sensory timing arises from the interaction between incoming stimuli and the internal dynamics of recurrent neural circuits. A wide-variety of time-dependent neural properties, such as short-term synaptic plasticity, are important contributors to the internal dynamics of neural circuits. In contrast to sensory timing, motor timing requires that network actively generate appropriately timed spikes even in the absence of sensory stimuli. Population clock models propose that motor timing arises from internal dynamics of recurrent network capable of self-perpetuating activity.

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Authors and Affiliations

  1. Departments of Neurobiology and Psychology, Integrative Center for Learning and Memory, Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA

    Dean V. Buonomano

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  1. Dean V. Buonomano
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Correspondence to Dean V. Buonomano .

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Editors and Affiliations

  1. Campus Juriquilla, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Queretaro, Querétaro, Mexico

    Hugo Merchant

  2. Campus Juriquilla, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Queretaro, Querétaro, Mexico

    Victor de Lafuente

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Buonomano, D.V. (2014). Neural Dynamics Based Timing in the Subsecond to Seconds Range. In: Merchant, H., de Lafuente, V. (eds) Neurobiology of Interval Timing. Advances in Experimental Medicine and Biology, vol 829. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1782-2_6

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