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23 Problems in Systems Neuroscience$
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J. Leo van Hemmen and Terrence J. Sejnowski

Print publication date: 2006

Print ISBN-13: 9780195148220

Published to Oxford Scholarship Online: May 2009

DOI: 10.1093/acprof:oso/9780195148220.001.0001

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Which Computation Runs in Visual Cortical Columns?

Which Computation Runs in Visual Cortical Columns?

(p.215) 11 Which Computation Runs in Visual Cortical Columns?
23 Problems in Systems Neuroscience

Steven W. Zucker

Oxford University Press

There is a substantial divide in computational neuroscience, separating the modeling of neurons at a biophysical level from the modeling of function at an information processing level. This chapter focuses on the second, information processing level, and raises a series of questions about it. It considers early vision, and representational structure emerged regarding tangents, curvatures, and continuity. That is, problem instances were formulated using the structure of differential geometry. This is not unexpected, given that differential geometry is the natural mathematics of surfaces and objects. For computation, linear complementarity emerged as a generalization of columnar operations. Algorithms for solving linear complementarity problems provided new insight into finding fast solutions by neural mechanisms. In all of the above cases, it was clear that the resulting networks are quite plausible; but starting only with network components, it seems implausible that all of the above abstract functions would have been inferred.

Keywords:   neurons, information processing, function, vision

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