A neurocomputational model of classical conditioning phenomena (Moustafa et al. 2009)


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Accession:138634
"... Here, we show that the same information-processing function proposed for the hippocampal region in the Gluck and Myers (1993) model can also be implemented in a network without using the backpropagation algorithm. Instead, our newer instantiation of the theory uses only (a) Hebbian learning methods which match more closely with synaptic and associative learning mechanisms ascribed to the hippocampal region and (b) a more plausible representation of input stimuli. We demonstrate here that this new more biologically plausible model is able to simulate various behavioral effects, including latent inhibition, acquired equivalence, sensory preconditioning, negative patterning, and context shift effects. ..."
Reference:
1 . Moustafa AA, Myers CE, Gluck MA (2009) A neurocomputational model of classical conditioning phenomena: a putative role for the hippocampal region in associative learning. Brain Res 1276:180-95 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism: Neocortex; Hippocampus;
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Simulation Environment: MATLAB (web link to model);
Model Concept(s): Learning; Sensory processing;
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