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Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons
Published on: October 31, 2020
A simple Hebbian/anti-Hebbian network learns the sparse, independent components of natural images
Michael S Falconbridge1, Robert L Stamps, David R Badcock
1School of Psychology, University of Western Australia, Nedlands WA 6009, Australia. michaelf@psy.uwa.edu.au
Abstract:
Slightly modified versions of an early Hebbian/anti-Hebbian neural network are shown to be capable of extracting the sparse, independent linear components of a prefiltered natural image set. An explanation for this capability in terms of a coupling between two hypothetical networks is presented. The simple networks presented here provide alternative, biologically plausible mechanisms for sparse, factorial coding in early primate vision.
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