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A nonparametric quantication of neural response eld structures

Summary: A nonparametric quanti˘cation of neural response
˘eld structures
Marina BrozovicL and Richard A. Andersen
Division of Biology,California Institute of Technology, Pasadena,California,USA
Correspondence and request for reprints to Dr Marina BrozovicL ,California Institute of Technology, Division of Biology,1200 E.California Blvd.,
Mail Code 216-76, Pasadena,CA 91125,USA
Tel: +1626 395 8337; fax: +1626 795 2397; e-mail: brozovic@vis.caltech.edu
Sponsorship:This work was supported by the James G.Boswell Foundation, the Sloan-Swartz Center forTheoretical Neurobiology and the National
Eye Institute.
Received 30 March 2006; accepted 3 April 2006
The response ˘elds of higher cortical neurons are usually approxi-
mated with smooth mathematical functions for the purpose of
population parameterization or theoretical modeling. We used
instead two nonparametric methods (principalcomponent analysis
and independent component analysis), which provided a basis for
the response ˘eld clustering. Although both methods performed
satisfactorily, the principal component analysis space is more
straightforward to calculate.It also gave a clear preference toward
the smallest number of functionalresponse ˘eld classes.Clustering
was performed with both K-means and superparamagnetic clus-


Source: Andersen, Richard - Division of Biology, California Institute of Technology


Collections: Biology and Medicine