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Neural Coding

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Encyclopedia of Computational Neuroscience

Definition

Neural coding encapsulates the concept that neurons act as information-processing channels that take incoming information, integrate it, and produce a signal that contains information encoded in the neuronal (Akil and Lewis 1993) electrical activity pattern.

Detailed Description

The brain can be regarded as an information-processing machine. It takes sensory information from both the external world and our internal state, compares it with stored representations, be they genetically encoded or learned, and produces directed behavior. The basic units for information processing are single neurons. Single neurons act as information channels, taking inputs impinging upon them from other neurons (or sensory organs at the periphery), integrating those inputs, and emitting a response. The step from input to output, both in single neurons and across populations, gives rise to what has been called the neural code, where a code is a signal that carries an abstract representation of...

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References

  • Abeles M (1991) Corticonics. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Akil M, Lewis DA (1993) The dopaminergic innervation of monkey entorhinal cortex. Cereb Cortex 3(6):533–550

    Article  CAS  PubMed  Google Scholar 

  • Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J Physiol 160:106–154

    CAS  PubMed Central  PubMed  Google Scholar 

  • Kobayashi S, Pinto de Carvalho O, Schultz W (2010) Adaptation of reward sensitivity in orbitofrontal neurons. J Neurosci 30:534–544

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Optican LM, Richmond BJ (1987) Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. III. Information theoretic analysis. J Neurophysiol 57:162–178

    CAS  PubMed  Google Scholar 

  • Richmond BJ (2009) Stochasticity, spikes and decoding: sufficiency and utility of order statistics. Biol Cybern 100:447–457

    Article  PubMed Central  PubMed  Google Scholar 

  • Staude B, Rotter S, Grün S (2008) Can spike coordination be differentiated from rate covariation? Neural Comput 20:1973–1999

    Article  PubMed  Google Scholar 

  • Wiener MC, Richmond BJ (2003) Decoding spike trains instant by instant using order statistics and the mixture-of-poissons model. J Neurosci 23:2394–2406

    CAS  PubMed  Google Scholar 

Further Reading

  • Doya K, Ishii S, Pouget A, Rao RPN (eds) (2007) Bayesian brain: probabilistic approaches to neural coding. MIT Press, Cambridge, MA

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  • Quiroga RQ, Panzeri S (eds) (2013) Principles of neural coding. CRC Press, Boca Raton

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  • Rieke F, Warland D, de Ruyter van Steveninck R, Bialek W (1997) Spikes: exploring the neural code. MIT Press, Cambridge, MA

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Correspondence to Barry Richmond .

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Richmond, B. (2014). Neural Coding. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_398-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_398-1

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