A versatile software package for inter-subject correlation based analyses of fMRI

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Kauppi, Jukka-Pekka
dc.contributor.author Pajula, Juha
dc.contributor.author Tohka, Jussi
dc.date.accessioned 2017-05-11T07:31:53Z
dc.date.available 2017-05-11T07:31:53Z
dc.date.issued 2014-01-31
dc.identifier.citation Kauppi , J-P , Pajula , J & Tohka , J 2014 , ' A versatile software package for inter-subject correlation based analyses of fMRI ' FRONTIERS IN NEUROINFORMATICS , vol 8 , 2 , pp. 1-13 . DOI: 10.3389/fninf.2014.00002 en
dc.identifier.other PURE UUID: 60e78bcf-94b6-46d9-af33-34dcb63a8ade
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/a-versatile-software-package-for-intersubject-correlation-based-analyses-of-fmri(60e78bcf-94b6-46d9-af33-34dcb63a8ade).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=84933045949&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/12957805/fninf_08_00002.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/25549
dc.description.abstract In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in en
dc.format.extent 1-13
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries FRONTIERS IN NEUROINFORMATICS en
dc.relation.ispartofseries Volume 8 en
dc.rights openAccess en
dc.subject.other Neuroscience (miscellaneous) en
dc.subject.other Biomedical Engineering en
dc.subject.other Computer Science Applications en
dc.subject.other 3112 Neurosciences en
dc.title A versatile software package for inter-subject correlation based analyses of fMRI en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department O.V.Lounasmaa-laboratorio
dc.contributor.department Tampere University of Technology
dc.contributor.department Department of Neuroscience and Biomedical Engineering en
dc.subject.keyword Functional magnetic resonance imaging
dc.subject.keyword Grid-computing
dc.subject.keyword GUI
dc.subject.keyword Matlab
dc.subject.keyword Naturalistic stimulus
dc.subject.keyword Re-sampling test
dc.subject.keyword Neuroscience (miscellaneous)
dc.subject.keyword Biomedical Engineering
dc.subject.keyword Computer Science Applications
dc.subject.keyword 3112 Neurosciences
dc.identifier.urn URN:NBN:fi:aalto-201705113933
dc.identifier.doi 10.3389/fninf.2014.00002
dc.type.version publishedVersion


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