Extracting slow subspaces from natural videos leads to complex cells

Christoph Kayser, Wolfgang Einhäuser, Olaf Dümmer, Peter König, Konrad Körding

Research output: Chapter in Book/Report/Conference proceedingConference contribution

37 Scopus citations

Abstract

Natural videos obtained from a camera mounted on a cat’s head are used as stimuli for a network of subspace energy detectors. The network is trained by gradient ascent on an objective function defined by the squared temporal derivatives of the cells’ outputs. The resulting receptive fields are invariant to both contrast polarity and translation and thus resemble complex type receptive fields.

Original languageEnglish (US)
Title of host publicationArtificial Neural Networks - ICANN 2001 - International Conference, Proceedings
EditorsKurt Hornik, Georg Dorffner, Horst Bischof
PublisherSpringer Verlag
Pages1075-1080
Number of pages6
ISBN (Print)3540424865, 9783540446682
DOIs
StatePublished - Jan 1 2001
EventInternational Conference on Artificial Neural Networks, ICANN 2001 - Vienna, Austria
Duration: Aug 21 2001Aug 25 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2130
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Artificial Neural Networks, ICANN 2001
CountryAustria
CityVienna
Period8/21/018/25/01

Keywords

  • Computational neuroscience
  • Learning
  • Temporal smothness

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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