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
Link To Document :
بازگشت