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A Neural Mechanism for Background Information-Gated Learning Based on Axonal-Dendritic Overlaps

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dc.contributor.author Mainetti, Matteo
dc.contributor.author Ascoli, Giorgio A.
dc.date.accessioned 2015-09-10T18:12:09Z
dc.date.available 2015-09-10T18:12:09Z
dc.date.issued 2015-03-13
dc.identifier.citation Mainetti M, Ascoli GA (2015) A Neural Mechanism for Background Information-Gated Learning Based on Axonal-Dendritic Overlaps. PLoS Comput Biol 11(3): e1004155. doi:10.1371/journal.pcbi.1004155 en_US
dc.identifier.uri https://hdl.handle.net/1920/9834
dc.description.abstract Experiencing certain events triggers the acquisition of new memories. Although necessary, however, actual experience is not sufficient for memory formation. One-trial learning is also gated by knowledge of appropriate background information to make sense of the experienced occurrence. Strong neurobiological evidence suggests that long-term memory storage involves formation of new synapses. On the short time scale, this form of structural plasticity requires that the axon of the pre-synaptic neuron be physically proximal to the dendrite of the post-synaptic neuron. We surmise that such “axonal-dendritic overlap” (ADO) constitutes the neural correlate of background information-gated (BIG) learning. The hypothesis is based on a fundamental neuroanatomical constraint: an axon must pass close to the dendrites that are near other neurons it contacts. The topographic organization of the mammalian cortex ensures that nearby neurons encode related information. Using neural network simulations, we demonstrate that ADO is a suitable mechanism for BIG learning. We model knowledge as associations between terms, concepts or indivisible units of thought via directed graphs. The simplest instantiation encodes each concept by single neurons. Results are then generalized to cell assemblies. The proposed mechanism results in learning real associations better than spurious co-occurrences, providing definitive cognitive advantages.
dc.description.sponsorship This work was supported in part by NIH (www.nih.gov) grant R01 NS39600, Office of Naval Research (www.onr.navy.mil) grant MURI N00014-10-1-0198, and NSF (www.nsf.org) grant RI IIS-1302256. Publication of this article was funded in part by the George Mason University Libraries Open Access Publishing Fund en_US
dc.language.iso en_US en_US
dc.publisher Public Library of Science en_US
dc.rights Attribution 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by/3.0/us/ *
dc.subject graphs en_US
dc.subject neuronal dendrites en_US
dc.subject learning en_US
dc.subject neurons en_US
dc.subject synapses en_US
dc.subject axons en_US
dc.subject neural networks en_US
dc.subject neuronal plasticity en_US
dc.title A Neural Mechanism for Background Information-Gated Learning Based on Axonal-Dendritic Overlaps en_US
dc.type Article en_US
dc.identifier.doi http://dx.doi.org/10.1371/journal.pcbi.1004155


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