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Modeling The Self-Organization Of Directional Selectivity In The Primary Visual Cortex (1999)
Igor Farkas
and
Risto Miikkulainen
A model is proposed to demonstrate how neurons in the primary visual cortex could self-organize to represent the direction of motion. The model is based on a temporal extension of the Self-Organizing Map where neurons act as leaky integrators. The map is trained with moving Gaussian inputs, and it develops a retinotopic map with orientation columns that divide into areas of opposite direction selectivity, as found in the visual cortex.
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Citation:
In Erkki Oja and Samuel Kaski, editors,
Proceedings of the Ninth International Conference on Artificial Neural Networks
, 251-256, Amsterdam, 1999. Elsevier.
Bibtex:
@InProceedings{miikkulainen:wsom99, title={Modeling The Self-Organization Of Directional Selectivity In The Primary Visual Cortex}, author={Igor Farkas and Risto Miikkulainen}, booktitle={Proceedings of the Ninth International Conference on Artificial Neural Networks}, editor={Erkki Oja and Samuel Kaski}, address={Amsterdam}, publisher={Elsevier}, key={ICANN}, pages={251-256}, url="http://nn.cs.utexas.edu/?farkaš:icann99", year={1999} }
People
Igor Farkas
Postdoctoral Alumni
farkas [at] fmph uniba sk
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
Projects
Self-Organization of Directional Selectivity
1999 - 2002
Areas of Interest
Visual Cortex
Computational Neuroscience