Suppression of synaptic transmission may allow combination of associative feedback and self-organizing feedforward connections in the neocortex.
Selective suppression of synaptic transmission during learning is proposed as a physiological mechanism for combining associative memory function at feedback synapses with self-organization of feedforward synapses in neocortical structures. A computational model demonstrates how selective suppression of feedback transmission allows this combination of synaptic function. During learning, sensory stimuli and the desired response are simultaneously presented as input to the network. Feedforward connections form self-organized representations of input, while suppressed feedback connections learn the transpose of the feedforward connectivity. During recall, suppression of transmission is removed, input activates the self-organized representation, and activity settles into a learned solution to the problem. This computational model can be used for learning of problems which are not linearly separable, including the negative patterning task (the XOR problem). Experiments in brain slice preparations of the rat somatosensory cortex tested whether the combination of self-organization and associative memory function could be provided by cholinergic suppression selective for feedback versus feedforward synapses. The cholinergic agonist carbachol selectively suppressed synaptic potentials elicited by stimulation of layer I (which contains a high percentage of feedback synapses), while having no effect on synaptic potentials elicited by stimulation of layer IV (with a high percentage of afferent and feedforward synapses).
Hasselmo
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ME
Department of Psychology, Harvard University, Cambridge, MA 02138, USA. hasselmo@katla.harvard.edu
Cekic
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D000818:Animals; D002217:Carbachol / Q000494:pharmacology; D002540:Cerebral Cortex / Q000502:physiology*; D004558:Electric Stimulation; D005246:Feedback / Q000502:physiology; D005260:Female; D066298:In Vitro Techniques; D008564:Membrane Potentials / Q000187:drug effects / Q000502:physiology; D008959:Models, Neurological; D018721:Muscarinic Agonists / Q000494:pharmacology; D016571:Neural Networks, Computer; D051381:Rats; D017207:Rats, Sprague-Dawley; D009435:Synaptic Transmission / Q000502:physiology*
D018721:Muscarinic Agonists; D002217:Carbachol