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How do we tell time?

Dean V Buonomano¹, Uma R Karmarkar

¹Department of Neurobiology, Brain Research Institute, University of California, Los Angeles 90095, USA. dbuono@ucla.edu

The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry

|February 15, 2002

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This review explores neural timing mechanisms for sensory and motor tasks occurring within tens to hundreds of milliseconds. Population clock models, involving dynamic neural interactions, are better suited for this temporal processing range.

Area of Science:

Neuroscience
Cognitive Science
Psychophysics

Background:

Animals perceive time across vast scales, from microseconds to days.
The review specifically examines neural timing in the tens to hundreds of milliseconds range.
This temporal scale is critical for speech discrimination, sensory processing, and fine motor control.

Purpose of the Study:

To review psychophysical and experimental data on timing mechanisms within the tens to hundreds of milliseconds range.
To discuss proposed models of neural timing, including labeled-line and population clock models.
To evaluate the suitability of different timing models for processing temporal cues in sensory and motor tasks.

Main Methods:

Review of existing psychophysical data on interval discrimination.

Related Experiment Videos

Analysis of experimental findings on generalization of timing-based training across modalities.

Comparison of theoretical models: labeled-line versus population clocks.

Main Results:

Psychophysical data suggest a centralized timing mechanism with separate networks for different intervals.
Training on interval discrimination generalizes across sensory modalities but not across different intervals.
Population clock models, relying on dynamic neural interactions, are more likely to explain timing in the tens to hundreds of milliseconds range.

Conclusions:

Neural timing in the tens to hundreds of milliseconds range is crucial for complex cognitive and motor functions.
Population clock models offer a more plausible framework for understanding neural timing at this scale compared to labeled-line models.
Further research is needed to elucidate the precise mechanistic underpinnings of neural timing.