Hebbian Crosstalk Prevents Nonlinear Unsupervised Learning

dc.creatorCox, Kingsley J. A.
dc.creatorAdams, Paul R.
dc.date2008-02-21
dc.date.accessioned2026-07-07T09:22:15Z
dc.date.available2026-07-07T09:22:15Z
dc.descriptionLearning is thought to occur by localized, experience-induced changes in the strength of synaptic connections between neurons. Recent work has shown that activity-dependent changes at one connection can affect changes at others (crosstalk). We studied the role of such crosstalk in nonlinear Hebbian learning using a neural network implementation of Independent Components Analysis (ICA). We find that there is a sudden qualitative change in the performance of the network at a critical crosstalk level and discuss the implications of this for nonlinear learning from higher-order correlations in the neocortex.
dc.identifierhttps://arxiv.org/abs/0802.2967
dc.identifierhttp://arxiv.org/abs/0802.2967
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/155312
dc.subjectNeurons and Cognition
dc.titleHebbian Crosstalk Prevents Nonlinear Unsupervised Learning
dc.typetext

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