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dc.contributor.authorLi, Lingge
dc.contributor.authorPluta, Dustin
dc.contributor.authorShahbaba, Babak
dc.contributor.authorFortin, Norbert
dc.contributor.authorOmbao, Hernando
dc.contributor.authorBaldi, Pierre
dc.date.accessioned2019-12-19T12:58:39Z
dc.date.available2019-12-19T12:58:39Z
dc.date.issued2019-05-24
dc.identifier.urihttp://hdl.handle.net/10754/660706
dc.description.abstractDynamic functional connectivity, as measured by the time-varying covariance of neurological signals, is believed to play an important role in many aspects of cognition. While many methods have been proposed, reliably establishing the presence and characteristics of brain connectivity is challenging due to the high dimensionality and noisiness of neuroimaging data. We present a latent factor Gaussian process model which addresses these challenges by learning a parsimonious representation of connectivity dynamics. The proposed model naturally allows for inference and visualization of time-varying connectivity. As an illustration of the scientific utility of the model, application to a data set of rat local field potential activity recorded during a complex non-spatial memory task provides evidence of stimuli differentiation.
dc.description.sponsorshipThis work was supported by NIH award R01-MH115697 (B.S., H.O., N.J.F), NSF award DMS1622490 (B.S.), Whitehall Foundation Award 2010-05-84 (N.J.F.), NSF CAREER award IOS1150292 (N.J.F.), NSF award BSC-1439267 (N.J.F.), and KAUST research fund (H.O.). We would like to thank Michele Guindani (UC-Irvine), Weining Shen (UC-Irvine), and Moo Chung (Univ. of Wisconsin) for their helpful comments regarding this work.
dc.publisherarXiv
dc.relation.urlhttps://arxiv.org/pdf/1905.10413
dc.rightsArchived with thanks to arXiv
dc.titleModeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes
dc.typePreprint
dc.contributor.departmentStatistics Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.eprint.versionPre-print
dc.contributor.institutionUC Irvine
dc.identifier.arxivid1905.10413
kaust.personOmbao, Hernando
refterms.dateFOA2019-12-19T12:59:12Z
display.summary<p>This record has been merged with an existing record at: <a href="http://hdl.handle.net/10754/665497">http://hdl.handle.net/10754/665497</a>.</p>


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