{{short description|Method by which information is represented in the brain}}
'''Neural coding''' (or '''neural representation''') refers to the relationship between a [[Stimulus (physiology)|stimulus]] and its respective neuronal responses, and the [[Electrophysiology|signalling relationships]] among networks of neurons in aan [[Neuronal ensemble|ensemble]].<ref name="Brown">{{cite journal |vauthors=Brown EN, Kass RE, Mitra PP |title=Multiple neural spike train data analysis: state-of-the-art and future challenges |journal=Nat. Neurosci. |volume=7 |issue=5 |pages=456–61 |date=May 2004 |pmid=15114358 |doi=10.1038/nn1228 |s2cid=562815 }}</ref><ref>{{Cite journal|last=Johnson|first=K. O.|date=June 2000|title=Neural coding|journal=Neuron|volume=26|issue=3|pages=563–566|issn=0896-6273|pmid=10896153|doi=10.1016/S0896-6273(00)81193-9|doi-access=free}}</ref> [[Action potentials]], which act as the primary carrier of information in [[biological neural networks]], are [[Goldman equation|generally]] [[Resting potential|uniform]] regardless of the type of stimulus or the [[Neuron#Classification|specific type of neuron]]. The [[Channel capacity|simplicity]] of action potentials as a methodology of encoding information factored with the indiscriminate process of [[Summation (neurophysiology)|summation]] is seen as discontiguous with the specification capacity that neurons [[Neurotransmission#Cotransmission|demonstrate at the presynaptic terminal]], as well as the broad ability for complex neuronal processing and regional specialisation for which the [[Large-scale brain network|brain-wide integration]] of such is seen as fundamental to complex deriviations; such as [[intellegence]], [[conciousness]], [[Social networkdynamics|complex social interaction]], [[reasoning]] and [[motivation]].
As such, theoretical frameworks that describe encoding mechanisms of action potential sequences in relationship to observed patterns are seen as fundamental to neuroscientific understanding.<ref name="thorpe">{{cite book |first=S.J. |last=Thorpe |chapter=Spike arrival times: A highly efficient coding scheme for neural networks |chapter-url=https://www.researchgate.net/publication/247621744 |format=PDF |pages=91–94 |editor1-first=R. |editor1-last=Eckmiller |editor2-first=G. |editor2-last=Hartmann |editor3-first=G. |editor3-last=Hauske | editor3-link = Gert Hauske |title=Parallel processing in neural systems and computers |url=https://books.google.com/books?id=b9gmAAAAMAAJ |year=1990 |publisher=North-Holland |isbn=978-0-444-88390-2}}</ref>
