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dc.contributor.authorRodríguez Álvarez, María Xosé
dc.contributor.authorCadarso-Suárez, Carmen
dc.contributor.authorGonzález, Francisco
dc.identifier.citationRodríguez Álvarez, María Xosé; Cadarso-Suárez, Carmen; González, Francisco. Analysing visual receptive fields through generalised additive models with interactions. "SORT", vol. 36, núm. 1, p. 3-32.
dc.description.abstractVisual receptive fields (RFs) are small areas of the visual fie ld where a stimulus induces a re- sponses of a particular neuron from the visual system. RFs ca n be mapped using reverse cross- correlation technique, which produces raw matrices contai ning both spatial and temporal informa- tion about the RF. Though this technique is frequently used i n electrophysiological experiments, it does not allow formal comparisons between RFs obtained un der different experimental condi- tions. In this paper we propose the use of Generalised Additi ve Models (GAM) including com- plex interactions, to obtain smoothed spatio-temporal ver sions of RFs. Moreover, the proposed methodology also allow for the statistical comparisons of t he RFs obtained across various experi- mental conditions. Data analysed here derive from studies o f neurons’ activity in the visual cortex of behaving monkeys. Our results suggest that the GAM-based technique proposed in this paper can be a flexible and powerful tool for assessing receptive fie ld properties
dc.format.extent42 p.
dc.publisherInstitut d'Estadística de Catalunya
dc.relation.ispartofSORT. 2012, vol. 36, núm. 1
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica
dc.subject.lcshNumerical analysis
dc.subject.otherVisual receptive fields
dc.subject.otherreverse cross-correlation
dc.subject.othervisual cortex
dc.subject.otherP-splines, tensor product splines
dc.subject.othertensor product splines
dc.titleAnalysing visual receptive fields through generalised additive models with interactions
dc.subject.lemacAnàlisi numèrica
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::65 Numerical analysis::65D Numerical approximation and computational geometry
dc.subject.amsClassificació AMS::62 Statistics::62P Applications
dc.rights.accessOpen Access
upcommons.citation.authorRodríguez Álvarez, María Xosé; Cadarso-Suárez, Carmen; González, Francisco

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Llevat que s'hi indiqui el contrari, els continguts d'aquesta obra estan subjectes a la llicència de Creative Commons: Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya