You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

A model of the summation pools within the layer 4 (area 17)

Fulltext:


Authors:

Baran Çürüklü, Anders Lansner

Research group:


Publication Type:

Journal article

Venue:

Neurocomputing

Publisher:

Elsevier


Abstract

We propose a developmental model of the summation pools within the layer 4. The model is based on the modular structure of the neocortex and captures some of the known properties of layer 4. Connections between the orientation minicolumns are developed during exposure to visual input. Excitatory local connections are dense and biased towards the iso-orientation domain. Excitatory long-range connections are sparse and target all orientation domains equally. Inhibition is local. The summation pools are elongated along the orientation axis. These summation pools can facilitate weak LGN input and explain improved visibility as an effect of enlargement of a stimulus.

Bibtex

@article{Curuklu577,
author = {Baran {\c{C}}{\"u}r{\"u}kl{\"u} and Anders Lansner},
title = {A model of the summation pools within the layer 4 (area 17)},
number = {65-66},
pages = {167--172},
month = {June},
year = {2005},
journal = {Neurocomputing},
publisher = {Elsevier},
url = {http://www.es.mdu.se/publications/577-}
}