Encyclopedia of Computational Neuroscience

2015 Edition
| Editors: Dieter Jaeger, Ranu Jung

Decision-Making: Overview

Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6675-8_248

Detailed Description

Much of computational neuroscience begins and ends with the responses of individual neurons. The field itself sprang from work in the 1950s aimed at uncovering the biophysical mechanisms underlying spike generation (Hodgkin and Huxley 1952), and other classic studies focus on the computational capabilities of dendritic trees and on how neural activity encodes sensory stimuli or statistical information about the world, to mention a couple of well-known examples (Dayan and Abbott 2001). A different point of view, however, is one in which neurons are the intermediaries between a subject and its environment. As the engines of behavior, neurons need to be computationally powerful for the express purpose of giving the subject an advantage, and hence their efficiency or performance should be measured with respect to the subject’s success. So the computational neuroscience of decision making is computational neuroscience in this context; it is the quest to understand how...

This is a preview of subscription content, log in to check access.

References

  1. Dayan P, Abbott LF (2001) Theoretical neuroscience. MIT Press, Cambridge, MAGoogle Scholar
  2. Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117:500–544PubMedCentralPubMedGoogle Scholar
  3. Parker AJ, Newsome WT (1998) Sense and the single neuron: probing the physiology of perception. Annu Rev Neurosci 21:227–277PubMedGoogle Scholar
  4. Romo R, Salinas E (2003) Flutter discrimination: neural codes, perception, memory and decision making. Nat Rev Neurosci 4:203–218PubMedGoogle Scholar
  5. Salzman CD, Murasugi CM, Britten KH, Newsome WT (1992) Microstimulation in visual area MT: effects on direction discrimination performance. J Neurosci 12:2331–2355PubMedGoogle Scholar
  6. Talbot WH, Darian-Smith I, Kornhuber HH, Mountcastle VB (1968) The sense of flutter-vibration: comparison of the human capacity with response patterns of mechanoreceptive afferents from the monkey hand. J Neurophysiol 31:301–334PubMedGoogle Scholar
  7. Werner G, Mountcastle V (1963) The variability of central neural activity in a sensory system, and its implications for the central reflection of sensory events. J Neurophysiol 26:958–977PubMedGoogle Scholar
  8. Werner G, Mountcastle VB (1965) Neural activity in mechanoreceptive cutaneous afferents: stimulus–response relations, Weber functions, and information transmission. J Neurophysiol 28:359–397PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Neurobiology and AnatomyWake Forest School of MedicineWinston-SalemUSA