Can Simple Cells Learn Curves? a Hebbian Model in a Structured Environment

Abstract

In the mammalian visual cortex, orientation-selective 'simple cells' which detect straight lines may be adapted to detect curved lines instead. We test a biologically plausible, Hebbian, single-neuron model, which learns oriented receptive fields upon exposure to un(cid:173) structured (noise) input and maintains orientation selectivity upon exposure to edges or bars of all orientations and positions. This model can also learn arc-shaped receptive fields upon exposure to an environment of only circular rings. Thus, new experiments which try to induce an abnormal (curved) receptive field may pro(cid:173) vide insight into the plasticity of simple cells. The model suggests that exposing cells to only a single spatial frequency may induce more striking spatial frequency and orientation dependent effects than heretofore observed.

Cite

Text

Softky and Kammen. "Can Simple Cells Learn Curves? a Hebbian Model in a Structured Environment." Neural Information Processing Systems, 1989.

Markdown

[Softky and Kammen. "Can Simple Cells Learn Curves? a Hebbian Model in a Structured Environment." Neural Information Processing Systems, 1989.](https://mlanthology.org/neurips/1989/softky1989neurips-simple/)

BibTeX

@inproceedings{softky1989neurips-simple,
  title     = {{Can Simple Cells Learn Curves? a Hebbian Model in a Structured Environment}},
  author    = {Softky, William R. and Kammen, Daniel M.},
  booktitle = {Neural Information Processing Systems},
  year      = {1989},
  pages     = {125-132},
  url       = {https://mlanthology.org/neurips/1989/softky1989neurips-simple/}
}