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      A Unified Model of Time Perception Accounts for Duration-Based and Beat-Based Timing Mechanisms

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          Abstract

          Accurate timing is an integral aspect of sensory and motor processes such as the perception of speech and music and the execution of skilled movement. Neuropsychological studies of time perception in patient groups and functional neuroimaging studies of timing in normal participants suggest common neural substrates for perceptual and motor timing. A timing system is implicated in core regions of the motor network such as the cerebellum, inferior olive, basal ganglia, pre-supplementary, and supplementary motor area, pre-motor cortex as well as higher-level areas such as the prefrontal cortex. In this article, we assess how distinct parts of the timing system subserve different aspects of perceptual timing. We previously established brain bases for absolute, duration-based timing and relative, beat-based timing in the olivocerebellar and striato-thalamo-cortical circuits respectively (Teki et al., 2011). However, neurophysiological and neuroanatomical studies provide a basis to suggest that timing functions of these circuits may not be independent. Here, we propose a unified model of time perception based on coordinated activity in the core striatal and olivocerebellar networks that are interconnected with each other and the cerebral cortex through multiple synaptic pathways. Timing in this unified model is proposed to involve serial beat-based striatal activation followed by absolute olivocerebellar timing mechanisms.

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          Most cited references94

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          Dynamic causal modelling.

          In this paper we present an approach to the identification of nonlinear input-state-output systems. By using a bilinear approximation to the dynamics of interactions among states, the parameters of the implicit causal model reduce to three sets. These comprise (1) parameters that mediate the influence of extrinsic inputs on the states, (2) parameters that mediate intrinsic coupling among the states, and (3) [bilinear] parameters that allow the inputs to modulate that coupling. Identification proceeds in a Bayesian framework given known, deterministic inputs and the observed responses of the system. We developed this approach for the analysis of effective connectivity using experimentally designed inputs and fMRI responses. In this context, the coupling parameters correspond to effective connectivity and the bilinear parameters reflect the changes in connectivity induced by inputs. The ensuing framework allows one to characterise fMRI experiments, conceptually, as an experimental manipulation of integration among brain regions (by contextual or trial-free inputs, like time or attentional set) that is revealed using evoked responses (to perturbations or trial-bound inputs, like stimuli). As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling (cf., psychophysiologic interactions). However, unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
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            What makes us tick? Functional and neural mechanisms of interval timing.

            Time is a fundamental dimension of life. It is crucial for decisions about quantity, speed of movement and rate of return, as well as for motor control in walking, speech, playing or appreciating music, and participating in sports. Traditionally, the way in which time is perceived, represented and estimated has been explained using a pacemaker-accumulator model that is not only straightforward, but also surprisingly powerful in explaining behavioural and biological data. However, recent advances have challenged this traditional view. It is now proposed that the brain represents time in a distributed manner and tells the time by detecting the coincidental activation of different neural populations.
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              Neuroanatomical and neurochemical substrates of timing.

              We all have a sense of time. Yet, there are no sensory receptors specifically dedicated for perceiving time. It is an almost uniquely intangible sensation: we cannot see time in the way that we see color, shape, or even location. So how is time represented in the brain? We explore the neural substrates of metrical representations of time such as duration estimation (explicit timing) or temporal expectation (implicit timing). Basal ganglia (BG), supplementary motor area, cerebellum, and prefrontal cortex have all been linked to the explicit estimation of duration. However, each region may have a functionally discrete role and will be differentially implicated depending upon task context. Among these, the dorsal striatum of the BG and, more specifically, its ascending nigrostriatal dopaminergic pathway seems to be the most crucial of these regions, as shown by converging functional neuroimaging, neuropsychological, and psychopharmacological investigations in humans, as well as lesion and pharmacological studies in animals. Moreover, neuronal firing rates in both striatal and interconnected frontal areas vary as a function of duration, suggesting a neurophysiological mechanism for the representation of time in the brain, with the excitatory-inhibitory balance of interactions among distinct subtypes of striatal neuron serving to fine-tune temporal accuracy and precision.
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                Author and article information

                Journal
                Front Integr Neurosci
                Front. Integr. Neurosci.
                Frontiers in Integrative Neuroscience
                Frontiers Research Foundation
                1662-5145
                07 December 2011
                03 January 2012
                2011
                : 5
                : 90
                Affiliations
                [1] 1simpleWellcome Trust Centre for Neuroimaging, University College London London, UK
                [2] 2simpleInstitute of Neuroscience, Newcastle University Newcastle-upon-Tyne, UK
                Author notes

                Edited by: Warren H. Meck, Duke University, USA

                Reviewed by: Warren H. Meck, Duke University, USA; Michael Schwartze, Max Planck Society, Germany

                *Correspondence: Sundeep Teki, Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London WC1N 3BG, UK. e-mail: sundeep.teki.10@ 123456ucl.ac.uk
                Article
                10.3389/fnint.2011.00090
                3249611
                22319477
                f2395658-6659-4d77-8c18-007210430900
                Copyright © 2012 Teki, Grube and Griffiths.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.

                History
                : 02 December 2011
                : 13 December 2011
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 110, Pages: 7, Words: 6480
                Categories
                Neuroscience
                Perspective Article

                Neurosciences
                time perception,cerebellum,striatum,timing mechanisms,interval timing
                Neurosciences
                time perception, cerebellum, striatum, timing mechanisms, interval timing

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