Abstract
We have built a neuronal model of decision making. Our model performs a decision based on an imperfect discrimination between highly mixed stimuli, and expresses it with a saccadic eye movement, like real living beings. We use populations of integrate-and-fire neurons.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Amit N Brunel DJ (1997) Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cereb Cortex 7:237–252.
Britten KH, Shadlen MN, Newsome WT, Movshon JA (1992) The analysis of visual motion :a comparison of neuronal and psychophysical performance. J Neurosci 12:2331–2355.
Deng Y, Williams P, Liu F, Feng J (2003) Discriminating between different input signals via single neuron activity. J Physics A:Math and Gen 36(50):12379–12398.
Feng J (2001) Is the integrate-and-fire model good enough?-A review. Neural Networks 14:955–975.
Feng J, Liu F (2002) A modeling study on discrimination tasks. Biosystems 67:67–73.
Gaillard B, Feng J (2005) Modelling a visual discrimination task. Neurocomputing 65–66:203–209.
Gaillard B, Feng J, Buxton H (2005) Population approach to a neural discrimination task. Biol Cybernet 94(3):180–191.
Gerstner W, Kistler W (2002) Spiking Neuron Models, Single Neurons, Populations, Plasticity. Cambridge University Press, Cambridge, UK.
Glimcher PW (2003) The neurobiology of visual-saccadic decision making. Annu Rev Neurosci 26:133–179.
Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J Physiol (Lond) 148:574–591.
Mountcastle VB (1957) Modality and topographic properties of single neurons of cat's somatosensory cortex. J Neurophysiol 20:408–434.
Platt ML, Glimcher PW (1999) Neural correlates of decision variables in parietal cortex. Nature 400:233–238.
Salinas E (2003) Background synaptic activity as a switch between dynamical states in a network. Neural Comput 15:1439–1475.
Shadlen MN, Gold JI (2004) The neurophysiology of decision making as a window on cognition. In:Gazzaniga (ed), The Cognitive Neurosciences, 3rd ed. MIT Press, Cambridge, MA.
Shadlen MN, Newsome WT (2001) Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J Neurophysiol 86:1916–1935.
Shadlen MN, Newsome WT (1996) Motion perception :seeing and deciding. Proc Nat Acad Sci 93:628–633.
Townsend JT, Ashby F (1983) The stochastic modeling of elementary psychological processes. Cambridge University Press, Cambridge, MA.
Tuckwell H (1988) Introduction to Theoretical Neurobiology, vol. 2. Cambridge University Press, Cambridge, MA.
VanRullen R, Koch C (2003) Is perception discrete or continuous? Trends Cog Sci 7(5):207–213.
Wang XJ (2002) Probabilistic decision making by slow reverberation in cortical circuits. Neuron 36:955–968.
Zohary E, Shadlen MN, Newsome WT (1994) Correlated neuronal discharge rate and its implications for psychophysical performance. Nature 370:140–143.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer
About this chapter
Cite this chapter
Gaillard, B., Feng, J., Buxton, H. (2007). Neuronal Model of Decision Making. In: Feng, J., Jost, J., Qian, M. (eds) Networks: From Biology to Theory. Springer, London. https://doi.org/10.1007/978-1-84628-780-0_5
Download citation
DOI: https://doi.org/10.1007/978-1-84628-780-0_5
Publisher Name: Springer, London
Print ISBN: 978-1-84628-485-4
Online ISBN: 978-1-84628-780-0
eBook Packages: Computer ScienceComputer Science (R0)