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

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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 . https://doi.org/10.3389/fninf.2014.00002

Title: A versatile software package for inter-subject correlation based analyses of fMRI
Author: Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi
Contributor organization: Helsinki Institute for Information Technology
Department of Computer Science
Neuroinformatics research group / Aapo Hyvärinen
Date: 2014-01-31
Language: eng
Number of pages: 13
Belongs to series: Frontiers in neuroinformatics
ISSN: 1662-5196
DOI: https://doi.org/10.3389/fninf.2014.00002
URI: http://hdl.handle.net/10138/160076
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 resampling 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.
Subject: functional magnetic resonance imaging
naturalistic stimulus
re-sampling test
113 Computer and information sciences
3112 Neurosciences
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion

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