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Temporal coding is a model of neural coding in which a neuron encodes information through the precise timing of action potentials, or spikes, on a millisecond time scale. There is no precise, universal definition of temporal coding; almost any coding scheme that is not rate coding may be referred to as a temporal code. However, distinctions have been made, specifically to differentiate the coding of temporal information (such as phase-locked responses in the auditory system) from the precise timing of spikes in a single neuron that encode information about a stimulus. Both definitions convey information to the brain, though temporal encoding does not necessarily encode a temporally variant stimulus. The term temporal coding is used to refer to relative timing of spikes from separate neurons, but this is better termed correlation coding. For example, the timing of spikes relayed from the left and right ear allow for the brain to identify the location of a sound source. This relies on the correlation of spike arrival time from separate neurons rather than the precise timing of spikes within a spike train. Temporal encoding could be compared to morse code, the dots and dashes representing the time between spikes.
Temporal Coding and the Neural Code Problem
Neurons exhibit high-frequency fluctuations of firing-rates whiceither noise or actually carry information. Rate coding models suggest that these irregularities are noise, but this is perhaps inadequate. If the nervous system used only rate codes to convey information, evolution should have selected for a more consistent, regular firing rate. The theory of temporal coding offers another solution to the "noise" problem by suggesting that the seeming randomness of spikes is not indeed random, but encodes information.
If a neuron is capable of firing at a maximum rate of 100 spikes per second, then a stimulus <10ms would likely elicit only a single spike. This model is especially important for sound localization, which occurs within the brain on the order of milliseconds. Additionally, if low firing rates on the order of 10 spikes per second must be distinguished from arbitrarily close rates coding for different stimuli, then a neuron trying to discriminate these two stimuli may need to wait for a second or more to accumulate enough information.
The discovery of spike timing dependent plasticity, where synaptic efficacy is modulated by the precise timing of spikes, provides strong evidence that temporal codes are used for cortical information transmission.
It should not be confused with the coding of temporal information.
Research on the neural code offer a look inside the way the brain encodes and decodes information. The brain works in patterns of spikes, though we do not concisouly understand these patterns; they must be studied. The idea of "cracking" the neural code would give computer scientists, neurologists, and psychologists a much greater understanding of brain circuitry, and perhaps how to replicate it. Researchers in this field must consider temporal coding in their analysis of spike trains. Averaging spikes across a time window could eliminate relevant information and skew data, thereby misrepresenting the codes used in neural circuitry.
- Vanrullen, R., Guyonneau, R., and Thorpe, S. (2005). Spike times make sense. Trends in Neurosciences, 28(1):1--4.
- Rullen, R. V. and Thorpe, S. J. (2001). Rate Coding Versus Temporal Order Coding: What the Retinal Ganglion Cells Tell the Visual Cortex. Neural Computation, 13(6):1255--1283.
- Dayan P, Abbott LF. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, Massachusetts: The MIT Press; 2001. ISBN 0-262-04199-5
- Rieke F, Warland D, de Ruyter van Steveninck R, Bialek W. Spikes: Exploring the Neural Code. Cambridge, Massachusetts: The MIT Press; 1999. ISBN 0-262-68108-0
- Theunissen F, Miller JP. Temporal Encoding in Nervous Systems: A Rigorous Definition. Journal of Computational Neuroscience, 2, 149—162; 1995.
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