DocumentCode :
2050223
Title :
Modeling cortical function starting with minimal connectivity
Author :
Towsey, Michael ; Diederich, Joachim
Author_Institution :
Machine Learning Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
Volume :
2
fYear :
1999
fDate :
1999
Firstpage :
783
Abstract :
Neural models of cortical function frequently assume initial profuse connectivity and ignore issues of cortical development. There is increasing interest in cortical models that minimise pre-specification of architecture and instead allow input and learning rules to sculpt connectivity. We describe a model of cortical development that begins with minimal connectivity but arrives at useful functionality through a variety of mechanisms, including Hebbian learning, volume learning, synaptic sprouting and structured input. We discuss some of the issues pertinent to the building of neural structure
Keywords :
Hebbian learning; brain models; content-addressable storage; neural nets; Hebbian learning; cortical development; cortical function modeling; learning rules; minimal connectivity; neural models; neural structure; pre-specification; structured input; synaptic sprouting; volume learning; Australia; Brain modeling; Neurons; Retina;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
Type :
conf
DOI :
10.1109/ICONIP.1999.845695
Filename :
845695
Link To Document :
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