|Appears in Collections:||Psychology Journal Articles|
|Peer Review Status:||Refereed|
|Title:||A Biologically Supported Error-Correcting Learning Rule|
|Author(s):||Hancock, Peter J B|
|Citation:||Hancock PJB, Smith L & Phillips W (1991) A Biologically Supported Error-Correcting Learning Rule. Neural Computation, 3 (2), pp. 201-212. http://www.mitpressjournals.org/doi/abs/10.1162/neco.19188.8.131.52|
|Abstract:||We show that a form of synaptic plasticity recently discovered in slices of the rat visual cortex (Artola et al. 1990) can support an error-correcting learning rule. The rule increases weights when both pre- and postsynaptic units are highly active, and decreases them when pre-synaptic activity is high and postsynaptic activation is less than the threshold for weight increment but greater than a lower threshold. We show that this rule corrects false positive outputs in feedforward associative memory, that in an appropriate opponent-unit architecture it corrects misses, and that it performs better than the optimal Hebbian learning rule reported by Willshaw and Dayan (1990).|
|Rights:||Publisher policy allows this work to be made available in this repository. Published as Hancock PJB, Smith LS, Phillips WA (1991) A Biologically Supported Error-Correcting Learning Rule, Neural Computation, Vol. 3, No. 2, Pages 201-212 by MIT Press: http://www.mitpressjournals.org/doi/abs/10.1162/neco.19184.108.40.206#.V-vDFYgrJpg|
|Hancock-etal-NeuralComputation-1991.pdf||Fulltext - Published Version||599.45 kB||Adobe PDF||View/Open|
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