ArticleFrontiers in neuroinformatics2014
A versatile software package for inter-subject correlation based analyses of fMRI.
Article in Frontiers in neuroinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- How Many Is Enough? Effect of Sample Size in Inter-Subject Correlation Analysis of fMRI.Computational intelligence and neuroscience · 2016Trial
- Somatosensory Evoked BOLD-Signals With Ultra-High Temporal Resolution.Human brain mapping · 2026Article
- Movement synchrony among dance performers predicts brain synchrony among dance spectators.Scientific reports · 2024Article
- aXonica: A support package for MRI based Neuroimaging.Biotechnology notes (Amsterdam, Netherlands) · 2024Article
- Article
- Discovering hidden brain network responses to naturalistic stimuli via tensor component analysis of multi-subject fMRI data.NeuroImage · 2022Article
- Intersubject synchrony of viewers during naturalistic observational self-learning of a complex bimanual task.Neuroimage. Reports · 2022Article
- Processing of an Audiobook in the Human Brain Is Shaped by Cultural Family Background.Brain sciences · 2022Article
- A functional magnetic resonance imaging examination of audiovisual observation of a point-light string quartet using intersubject correlation and physical feature analysis.Frontiers in neuroscience · 2022Article
- Sensorimotor Responses in Post-Stroke Hemiplegic Patients Modulated by Acupuncture at Yanglingquan (GB34): A fMRI Study Using Intersubject Functional Correlation (ISFC) Analysis.Frontiers in neurology · 2022Article
- Neural-level associations of non-verbal pragmatic comprehension in young Finnish autistic adults.International journal of circumpolar health · 2021Article
- Review
- Inter-subject phase synchronization differentiates neural networks underlying physical pain empathy.Social cognitive and affective neuroscience · 2020Article
- Brain and behavioral alterations in subjects with social anxiety dominated by empathic embarrassment.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Measuring shared responses across subjects using intersubject correlation.Social cognitive and affective neuroscience · 2019Article
- A drama movie activates brains of holistic and analytical thinkers differentially.Social cognitive and affective neuroscience · 2018Article
- Article
- Effective connectivity of the anterior hippocampus predicts recollection confidence during natural memory retrieval.Nature communications · 2018Article
- Differential inter-subject correlation of brain activity when kinship is a variable in moral dilemma.Scientific reports · 2017Article
- Neural mechanisms for integrating consecutive and interleaved natural events.Human brain mapping · 2017Article
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3 authors.
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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 https://code.google.com/p/isc-toolbox/
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