Temporal coding: Difference between revisions

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{{Merge to|Neural coding|discuss=Talk:Neural coding#Merger possibilities|date=July 2010}}

'''Temporal coding''' is a modeltype of [[neural coding]] in which a neuron encodes information through the precise timing of [[action potential]]s, or spikes, on a millisecond time scale. There is no 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 to differentiate the the precise timing of spikes in a single neuron which encodes information about a stimulus from synchronized firing of neurons within a localized area from . This interaction between neurons is sometimes referred to as [[correlation coding]].<ref> Dayan P, Abbott LF. ''Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems''. Cambridge, Massachusetts: The MIT Press; 2001. p. 35. ISBN 0-262-04199-5</ref> The model of temporal coding is evidenced in the mammalian gustatory system.

==A candidate for the neural code==

Simply put, a neural code can be defined as the minimalminimum number of symbols necessary to express all biologically significant information.<ref> Theunissen F, Miller JP. ''Temporal Encoding in Nervous Systems: A Rigorous Definition''. Journal of Computational Neuroscience, 2, 149—162; 1995.</ref> Many systems of the body utilize a more complex coding system than could be considered reasonable for a rate code. A temporal code could solve this problem.

Neurons exhibit high-frequency fluctuations of firing-rates which arecould either be noise or actually carry information. Rate coding models suggest that these irregularities are noise, but this seems to be an inadequate explanation for a common occurrence. If the nervous system used only rate codes to convey information, evolution should have selected a more consistent, regular firing rate.<ref> J. Leo van Hemmen, TJ Sejnowski. 23 Problems in Systems Neuroscience. Oxford Univ. Press, 2006. p.143-158. </ref> The theory of temporal coding offers another solution to the "noise" problem of noise by suggesting that the seemingapparent randomness of spikes is not completely random, but instead encodes information. This solution supplies an explanation for the “noise” and allows for a more information -rich code. BinaryTo model this idea, binary symbols can be used to mark the spikes,: 1 for a spike, 0 for no spike. Temporal coding allows sequencesa sequence like 000111000111 to mean something different than 001100110011, even though the mean rate of firing is the same for both sequences:, thereat are6 6spikesspikes/10msec10 msec.<ref>Theunissen F, Miller JP. ''Temporal Encoding in Nervous Systems: A Rigorous Definition''. Journal of Computational Neuroscience, 2, 149—162; 1995.</ref>

Until recently, scientists had put the most emphasis on rate encoding, or using the mean frequency of spikes to convey information about the stimulus. However, functions of the brain are more temporally precise than mere rate encoding would seem to allow;. inIn other words, essential information would be lost due to the inability of the rate code to capture all of the available information inof the spike train. In addition, responses are stochastic enough between similar, (but not identical) stimuli to suggest that the different patterns of spikes contain a higher volume of information than is possible to include in a rate code; that is, there is 'extra' information. However, scientists haveare littlenot certaintyconfident ofabout the implications of this additional dimensionality of the temporal code.<ref>{{cite web|last=Zador, Stevens|first=Charles, Anthony|title=The enigma of the brain|url=https://docs.google.com/a/stolaf.edu/viewer?a=v&pid=gmail&attid=0.1&thid=1369b5e1cdf273f9&mt=application/pdf&url=https://mail.google.com/mail/u/0/?ui%3D2%26ik%3D0a436eb2a7%26view%3Datt%26th%3D1369b5e1cdf273f9%26attid%3D0.1%26disp%3Dsafe%26realattid%3Df_h0ty13ea0%26zw&sig=AHIEtbQB4vngr9nDZaMTLUOcrk5DzePKqA|work=© Current Biology 1995, Vol 5 No 12|accessdate=4/08/12}}</ref>

==Evidence==

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===Sensory systems===

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The mammalian gustatory system is useful for studying temporal coding because the stimuli are fairly distinct and it is easy to judge whether or not the coding was successful by looking at an organism's responses.<ref>Hallock, Robert M. and Patricia M. Di Lorenzo. (2006). [http://dx.doi.org/10.1016/j.neubiorev.2006.07.005 "Temporal coding in the gustatory system"]. <i>Neuroscience & Biobehavioral Reviews</i>, 30(8):1145–1160.</ref> Temporally encoded information may help an organism discriminate between different tastants of the same category (sweet, bitter, sour, salty, umami) that elicit very similar responses in terms of spike count. The temporal component of the pattern elicited by each tastant may be used to determine its identity (e.g, tellingthe difference between two bitter tastants, such as quinine fromand denatonium). In this way, both rate coding and temporal coding may be used in the gustatory system – rate for basic tastant type, temporal for more specific differentiation.<ref>Carleton, Alan, Riccardo Accolla, and Sidney A. Simon. (2010). [http://dx.doi.org/10.1016/j.tins.2010.04.002 "Coding in the mammalian gustatory system"]. <i>Trends in Neurosciences</i>, 33(7):326–334.</ref>

Research on mammalian gustatory system has shown that there is an abundance of information present in temporal patterns across populations of neurons, and this information is different than that which is determined by rate coding schemes. Groups of neurons may synchronize in response to a stimulus. In studies regarding the front cortical portion of the brain in primates, precise patterns with short time scales, only a few milliseconds in length, were found across small populations of neurons which correlated with certain information processing behaviors. However, little information could be determined from the patterns; one possible theory is they represented the higher-order processing taking place in the brain.<ref>{{cite web|last=Zador, Stevens|first=Charles, Anthony|title=The enigma of the brain|url=https://docs.google.com/a/stolaf.edu/viewer?a=v&pid=gmail&attid=0.1&thid=1369b5e1cdf273f9&mt=application/pdf&url=https://mail.google.com/mail/u/0/?ui%3D2%26ik%3D0a436eb2a7%26view%3Datt%26th%3D1369b5e1cdf273f9%26attid%3D0.1%26disp%3Dsafe%26realattid%3Df_h0ty13ea0%26zw&sig=AHIEtbQB4vngr9nDZaMTLUOcrk5DzePKqA|work=© Current Biology 1995, Vol 5 No 12|accessdate=4/08/12}}</ref>

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==Implications==

The specificity of temporal coding requires highly refined technology to create informative, reliable experimental data. In 2009, advances made in [[optogenetics]] allowed neurologists to control spikes in individual neurons, offering electrical and spatial single-cell resolution. For example, when it senses blue light, a [[channelrhodopsin]] in pond scum opens when it senses blue light, depolarizes the cell, and produces a spike. When blue light is not sensed, the channel closes, and the neuron ceases to spike. The pattern of the spikes matches the pattern of the blue light stimuli. By inserting channelrhodopsin DNAgene sequences into mouse DNA, researchers can control spikes and therefore certain behaviors of the mouse (i.e., making the mouse turn left).<ref> Karl Diesseroth, Lecture. “Personal Growth Series: Karl Diesseroth on Cracking the Neural Code.” Google Tech Talks. November 21, 2008. http://www.youtube.com/watch?v=5SLdSbp6VjM</ref> Researchers, through optogenetics, have the tools to effect different temporal codes in a neuron while maintaining the same mean firing rate, and thereby can test whether or not temporal coding occurs in specific neural circuits. <ref>Han X, Qian X, Stern P, Chuong AS, Boyden ES. “Informational lesions: optical perturbations of spike timing and neural synchrony via microbial opsin gene fusions.” Cambridge, MA: MIT Media Lad, 2009. PubMed.</ref>

This optogenetic technology has the potential to help researchers crack the neural code and enable the correction of spike abnormalities at the root of several neurological and psychological disorders.<ref>Han X, Qian X, Stern P, Chuong AS, Boyden ES. “Informational lesions: optical pertubatons of spike timing and neural synchrony via microbial opsin gene fusions.” Cambridge, MA: MIT Media Lad, 2009. PubMed.</ref> Researchers must not neglect the possibility that the neuron encodes information in individual spike timing, as key signals could be missed in attempting to crack the code looking only at mean firing-rates. Understanding any temporally encoded aspects of the neural code and being able to replicate these sequences in neurons could allow for greater control and treatment of depression and Parkinson’s.<ref> Karl Diesseroth, Lecture. “Personal Growth Series: Karl Diesseroth on Cracking the Neural Code.” Google Tech Talks. November 21, 2008. http://www.youtube.com/watch?v=5SLdSbp6VjM</ref> Controlling the precise spikes intervals in single cells is much more effective in controlling brain activity than dumping chemicals and neurotransmitters intravenously. Such medical possibilities require scientists and communities to address the ethics of such tight control over the brain. While the benefits could be enormous, so could the abuses. However, understanding where the brain uses a temporal coding system is important and valuable for neuroscientists and patients alike.