DocumentCode
1185132
Title
Analog CMOS synaptic learning circuits adapted from invertebrate biology
Author
Schneider, Christian ; Card, Howard
Author_Institution
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
Volume
38
Issue
12
fYear
1991
fDate
12/1/1991 12:00:00 AM
Firstpage
1430
Lastpage
1438
Abstract
Analog CMOS circuits implementing abstractions of certain biological synaptic processes are presented. In particular, the circuits extract features of synaptic learning observed in the marine mollusk Aplysia. Two types of nonassociative learning, habituation and sensitization, as well as associative learning (classical conditioning), are modeled. The synaptic learning rules used by Aplysia are considerably more complex than those typically used in artificial neural networks (ANNs), leading to the speculation that additional biological detail may be beneficial in ANN models. The synaptic circuitry described is expected to be useful as a basic primitive in ANNs with higher order synapses and learning rules that perform temporal association of multiple inputs
Keywords
CMOS integrated circuits; analogue circuits; learning systems; neural nets; ANNs; Aplysia; analogue CMOS synaptic learning circuits; associative learning; biological synaptic processes; habituation; invertebrate biology; learning rules; marine mollusk; multiple inputs; nonassociative learning; sensitization; synaptic circuitry; temporal association; Artificial neural networks; Biological neural networks; Biological system modeling; Biology computing; CMOS analog integrated circuits; CMOS process; Computational biology; Feature extraction; Semiconductor device modeling; Transconductance;
fLanguage
English
Journal_Title
Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0098-4094
Type
jour
DOI
10.1109/31.108497
Filename
108497
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