Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-9522
For citation please use:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorWeber, Simon Nikolaus-
dc.contributor.authorSprekeler, Henning-
dc.date.accessioned2020-01-15T13:13:39Z-
dc.date.available2020-01-15T13:13:39Z-
dc.date.issued2019-02-07-
dc.identifier.issn1553-734X-
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/10596-
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-9522-
dc.description.abstractGrid cells have attracted broad attention because of their highly symmetric hexagonal firing patterns. Recently, research has shifted its focus from the global symmetry of grid cell activity to local distortions both in space and time, such as drifts in orientation, local defects of the hexagonal symmetry, and the decay and reappearance of grid patterns after changes in lighting condition. Here, we introduce a method that allows to visualize and quantify such local distortions, by assigning both a local grid score and a local orientation to each individual spike of a neuronal recording. The score is inspired by a standard measure from crystallography, which has been introduced to quantify local order in crystals. By averaging over spikes recorded within arbitrary regions or time periods, we can quantify local variations in symmetry and orientation of firing patterns in both space and time.en
dc.description.sponsorshipBMBF, 01GQ1201, Lernen und Gedächtnis in balancierten Systemenen
dc.language.isoenen
dc.relation.ispartof10.14279/depositonce-8964-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc570 Biowissenschaften; Biologiede
dc.subject.ddc004 Datenverarbeitung; Informatikde
dc.subject.ddc610 Medizin und Gesundheitde
dc.subject.otherneuroscienceen
dc.subject.othercomputational neuroscienceen
dc.titleA local measure of symmetry and orientation for individual spikes of grid cellsen
dc.typeArticleen
tub.accessrights.dnbfreeen
tub.publisher.universityorinstitutionTechnische Universität Berlinen
dc.identifier.eissn1553-7358-
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.doi10.1371/journal.pcbi.1006804en
dcterms.bibliographicCitation.journaltitlePLOS Computational Biologyen
dcterms.bibliographicCitation.originalpublisherplaceSan Francisco, Califen
dcterms.bibliographicCitation.volume15en
dcterms.bibliographicCitation.originalpublishernamePublic Library of Scienceen
dcterms.bibliographicCitation.issue2en
dcterms.bibliographicCitation.articlenumbere1006804en
Appears in Collections:FG Modellierung kognitiver Prozesse » Publications

Files in This Item:
Weber2019_article_local.pdf
Format: Adobe PDF | Size: 4.84 MB
DownloadShow Preview
Thumbnail

Item Export Bar

This item is licensed under a Creative Commons License Creative Commons