Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity

dc.contributor.authorWeber, Simon Nikolaus
dc.contributor.authorSprekeler, Henning
dc.date.accessioned2020-01-15T13:09:10Z
dc.date.available2020-01-15T13:09:10Z
dc.date.issued2018-02-21
dc.description.abstractNeurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed spatial tuning patterns – in both their selectivity and their invariance – arise from the same mechanism: Excitatory and inhibitory synaptic plasticity driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. Our proposed model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions.en
dc.description.sponsorshipBMBF, 01GQ1201, Lernen und Gedächtnis in balancierten Systemenen
dc.identifier.issn2050-084X
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/10592
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-9518
dc.language.isoenen
dc.relation.ispartof10.14279/depositonce-8964
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc500 Naturwissenschaftende
dc.subject.ddc600 Technikde
dc.subject.otherneuroscienceen
dc.titleLearning place cells, grid cells and invariances with excitatory and inhibitory plasticityen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumbere34560en
dcterms.bibliographicCitation.doi10.7554/eLife.34560en
dcterms.bibliographicCitation.journaltitleeLifeen
dcterms.bibliographicCitation.originalpublishernameeLife Sciences Publicationsen
dcterms.bibliographicCitation.originalpublisherplaceCambridgeen
dcterms.bibliographicCitation.volume7en
tub.accessrights.dnbfreeen
tub.affiliationFak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatik::FG Modellierung kognitiver Prozessede
tub.affiliation.facultyFak. 4 Elektrotechnik und Informatikde
tub.affiliation.groupFG Modellierung kognitiver Prozessede
tub.affiliation.instituteInst. Softwaretechnik und Theoretische Informatikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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