Neural coding: Difference between revisions

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<!-- Image with unknown copyright status removed: [[Image:Distributed Neural Coding.jpg|thumb|400px|'''Figure 1. Distributed neural coding in colour vision'''. In 1802,[[Thomas Young]] introduced the concept of distributed neural coding in his classic [[trichromatic theory]] of colour vision. In his formulation, the combined response profile of only three retinal receptors ('''left'''), tuned to respond to a broad [[spectrum]] of light wavelength ('''right'''), can account for the representation of any color in the visible spectrum. P, Q, R, S, colour stimuli. ]] -->

'''Neural coding''' is a [[neuroscience]]-related field concerned with how [[sensory]] and other information is represented in the [[brain]] by [[neurons]]. The main goal of studying neural coding is to characterize the relationship between the [[Stimulus (physiology)|stimulus]] and the individual or ensemble neuronal responses and the relationship among electrical activity of the neurons in the ensemble <ref name="Brown">Brown EN, Kass RE, and Mitra PP. 2004. Multiple neural spike train data analysis: state-of-the-art and future challenges. ''Nature Neuroscience'' 7:456-61</ref>.

== Overview ==

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Rate coding is a traditional coding scheme, assuming that most, if not all, information about the stimulus is contained in the firing rate of the neuron. Because the sequence of action potentials generated by a given stimulus varies from trial to trial, neuronal responses are typically treated statistically or probabilistically. They may be characterized by firing rates, rather than as specific spike sequences. In most sensory systems, the firing rate increases, generally non-linearly, with increasing stimulus intensity <ref name="Kandel">Kandel, E., Schwartz, J. and Jessel, T.M. 1991. ''Principles of Neural Science''. Elsevier, New York</ref>. Any information possibly encoded in the temporal structure of the spike train is ignored. Consequently, rate coding is inefficient but highly robust with respect to the ISI '[[noise]]' <ref name="Stein"/>.

The concept of firing rates has been successfully applied during the last 80 years. It dates back to the pioneering work of ED Adrian who showed that the firing rate of stretch [[Receptor (biochemistry)|receptor]] neurons in the muscles is related to the force applied to the muscle<ref name="Adrian"> Adrian ED and Zotterman Y. 1926. The impulses produced by sensory nerve endings: Part II: The response of a single end organ. ''Journal of Physiology'' 61: 151-71</ref>. In the following decades, measurement of firing rates became a standard tool for describing the properties of all types of sensory or [[cortical]] neurons, partly due to the relative ease of measuring rates experimentally. However, this approach neglects all the information possibly contained in the exact timing of the spikes. During recent years, more and more experimental evidences have suggested that a straightforward firing rate concept based on temporal averaging may be too simplistic to describe brain activity <ref name="Stein"/>.

During rate coding, precisely calculating firing rate is very important. In fact, the term “firing rate” has a few different definitions, which refer to different averaging procedures, such as an average over time or an average over several repetitions of experiment.