Learning receptive fields using predictive feedback.

Published

Journal Article

Previously, it was suggested that feedback connections from higher- to lower-level areas carry predictions of lower-level neural activities, whereas feedforward connections carry the residual error between the predictions and the actual lower-level activities [Rao, R.P.N., Ballard, D.H., 1999. Nature Neuroscience 2, 79-87.]. A computational model implementing the hypothesis learned simple cell receptive fields when exposed to natural images. Here, we use predictive feedback to explain tuning properties in medial superior temporal area (MST). We implement the hypothesis using a new, biologically plausible, algorithm based on matching pursuit, which retains all the features of the previous implementation, including its ability to efficiently encode input. When presented with natural images, the model developed receptive field properties as found in primary visual cortex. In addition, when exposed to visual motion input resulting from movements through space, the model learned receptive field properties resembling those in MST. These results corroborate the idea that predictive feedback is a general principle used by the visual system to efficiently encode natural input.

Full Text

Duke Authors

Cited Authors

  • Jehee, JFM; Rothkopf, C; Beck, JM; Ballard, DH

Published Date

  • July 2006

Published In

Volume / Issue

  • 100 / 1-3

Start / End Page

  • 125 - 132

PubMed ID

  • 17067787

Pubmed Central ID

  • 17067787

International Standard Serial Number (ISSN)

  • 0928-4257

Digital Object Identifier (DOI)

  • 10.1016/j.jphysparis.2006.09.011

Language

  • eng

Conference Location

  • France