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Neurobiology of Interval Timing

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Cover of 'Neurobiology of Interval Timing'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to the neurobiology of interval timing.
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    Chapter 2 About the (Non)scalar Property for Time Perception
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    Chapter 3 Elucidating the Internal Structure of Psychophysical Timing Performance in the Sub-second and Second Range by Utilizing Confirmatory Factor Analysis
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    Chapter 4 Neurocomputational models of time perception.
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    Chapter 5 Dedicated clock/timing-circuit theories of time perception and timed performance.
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    Chapter 6 Neural Dynamics Based Timing in the Subsecond to Seconds Range
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    Chapter 7 Signs of Timing in Motor Cortex During Movement Preparation and Cue Anticipation
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    Chapter 8 Neurophysiology of Timing in the Hundreds of Milliseconds: Multiple Layers of Neuronal Clocks in the Medial Premotor Areas
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    Chapter 9 The Olivo-Cerebellar System as a Neural Clock
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    Chapter 10 From duration and distance comparisons to goal encoding in prefrontal cortex.
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    Chapter 11 Probing Interval Timing with Scalp-Recorded Electroencephalography (EEG)
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    Chapter 12 Searching for the Holy Grail: Temporally Informative Firing Patterns in the Rat
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    Chapter 13 Getting the Timing Right: Experimental Protocols for Investigating Time with Functional Neuroimaging and Psychopharmacology
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    Chapter 14 Motor and Perceptual Timing in Parkinson’s Disease
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    Chapter 15 Music perception: information flow within the human auditory cortices.
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    Chapter 16 Perceiving Temporal Regularity in Music: The Role of Auditory Event-Related Potentials (ERPs) in Probing Beat Perception.
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    Chapter 17 Neural Mechanisms of Rhythm Perception: Present Findings and Future Directions
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    Chapter 18 Neural underpinnings of music: the polyrhythmic brain.
Attention for Chapter 4: Neurocomputational models of time perception.
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Chapter title
Neurocomputational models of time perception.
Chapter number 4
Book title
Neurobiology of Interval Timing
Published in
Advances in experimental medicine and biology, January 2014
DOI 10.1007/978-1-4939-1782-2_4
Pubmed ID
Book ISBNs
978-1-4939-1781-5, 978-1-4939-1782-2
Authors

Joachim Hass, Daniel Durstewitz, Hass, Joachim, Durstewitz, Daniel

Abstract

Mathematical modeling is a useful tool for understanding the neurodynamical and computational mechanisms of cognitive abilities like time perception, and for linking neurophysiology to psychology. In this chapter, we discuss several biophysical models of time perception and how they can be tested against experimental evidence. After a brief overview on the history of computational timing models, we list a number of central psychological and physiological findings that such a model should be able to account for, with a focus on the scaling of the variability of duration estimates with the length of the interval that needs to be estimated. The functional form of this scaling turns out to be predictive of the underlying computational mechanism for time perception. We then present four basic classes of timing models (ramping activity, sequential activation of neuron populations, state space trajectories and neural oscillators) and discuss two specific examples in more detail. Finally, we review to what extent existing theories of time perception adhere to the experimental constraints.

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The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Germany 1 2%
Unknown 39 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 24%
Student > Master 5 12%
Researcher 5 12%
Student > Bachelor 4 10%
Student > Doctoral Student 3 7%
Other 8 20%
Unknown 6 15%
Readers by discipline Count As %
Psychology 11 27%
Neuroscience 8 20%
Computer Science 5 12%
Agricultural and Biological Sciences 2 5%
Biochemistry, Genetics and Molecular Biology 2 5%
Other 5 12%
Unknown 8 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 November 2014.
All research outputs
#6,209,490
of 24,240,330 outputs
Outputs from Advances in experimental medicine and biology
#944
of 5,179 outputs
Outputs of similar age
#69,089
of 314,820 outputs
Outputs of similar age from Advances in experimental medicine and biology
#26
of 144 outputs
Altmetric has tracked 24,240,330 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 5,179 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 314,820 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.