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7 - Neurobiologically Plausible Computational Models

Published online by Cambridge University Press:  05 February 2021

Gabriel Kreiman
Gabriel Kreiman
Affiliation:
Harvard University, Massachusetts
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Summary

We have been traveling through the wonderful territory of the visual cortex, examining the properties of different brain areas and neural circuits, learning about how animals and their neurons respond to visual stimuli and what happens when different parts of the visual cortex are lesioned or artificially stimulated. It is now time to put all this biological knowledge into a theory of visual recognition and to instantiate this theory through a computational model that can see and interpret the world. En route toward this goal, here we start by discussing how scientists describe neural circuits using computational models and define the basic properties of neural networks.

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Chapter
Information
Biological and Computer Vision , pp. 133 - 151
Publisher: Cambridge University Press
Print publication year: 2021

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References

Further Reading

• Dayan, P., and Abbott, L. (2001). Theoretical neuroscience. Cambridge: MIT Press.Google Scholar
• Gabbiani, F., and Cox, S. (2010). Mathematics for neuroscientists. London: Academic Press.Google Scholar
• Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. PNAS 79: 2554–2558.Google Scholar
• Koch, C. (1999). Biophysics of computation. New York: Oxford University Press.Google Scholar
• Markram, H. (2006). The blue brain project. Nat Rev Neurosci 7: 153–160.CrossRefGoogle ScholarPubMed

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