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Remove section titled: "Neural Self-Information Theory for Neural Coding of Real-Time Cognition". This is a particular theory that does not fit in the context of this article which provides basic fundamental and well accepted principles and concepts of neural coding theory. The presence of this section disrupts the flow of the article and gives undue credence to a particular theory out of context from the broader field. A separate Wiki page would be more appropriate for the theory. |
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== Overview ==
Neurons have an ability uncommon among the cells of the body to propagate signals rapidly over large distances by generating characteristic electrical pulses called [[action potentials]]: voltage spikes that can travel down axons. Sensory neurons change their activities by firing sequences of action potentials in various temporal patterns, with the presence of external sensory stimuli, such as [[light]], [[sound]], [[taste]], [[Olfaction|smell]] and [[touch]]. Information about the stimulus is encoded in this pattern of action potentials and transmitted into and around the brain. Beyond this, specialized neurons, such as those of the retina, can communicate more information through [[graded potential]]s. These differ from action potentials because information about the strength of a stimulus directly correlates with the strength of the neurons' output. The signal decays much faster for graded potentials, necessitating short inter-neuron distances and high neuronal density. The advantage of graded potentials
Although action potentials can vary somewhat in duration, [[amplitude]] and shape, they are typically treated as identical stereotyped events in neural coding studies. If the [[Brief-spike|brief duration]] of an action potential (about 1 ms) is ignored, an action potential sequence, or spike train, can be characterized simply by a series of [[all-or-none law|all-or-none]] point events in time.<ref name="Gerstner">{{cite book|author-link1=Wulfram Gerstner |first1=Wulfram |last1=Gerstner |first2=Werner M. |last2=Kistler |title=Spiking Neuron Models: Single Neurons, Populations, Plasticity |url=https://books.google.com/books?id=Rs4oc7HfxIUC |year=2002 |publisher=Cambridge University Press |isbn=978-0-521-89079-3}}</ref> The lengths of interspike intervals ([[Temporal coding|ISI]]s) between two successive spikes in a spike train often vary, apparently randomly.<ref name="Stein">{{cite journal |vauthors=Stein RB, Gossen ER, Jones KE |title=Neuronal variability: noise or part of the signal? |journal=Nat. Rev. Neurosci. |volume=6 |issue=5 |pages=389–97 |date=May 2005 |pmid=15861181 |doi=10.1038/nrn1668 |s2cid=205500218 }}</ref> The study of neural coding involves measuring and characterizing how stimulus attributes, such as light or sound intensity, or motor actions, such as the direction of an arm movement, are represented by neuron action potentials or spikes. In order to describe and analyze neuronal firing, [[statistical methods]] and methods of [[probability theory]] and stochastic [[point process]]es have been widely applied.
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