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  Data-driven multisubject neuroimaging analyses for naturalistic stimuli

Biessmann, F., Gaebler, M., Lamke, J.-P., Ju, U. J., Hetzer, S., Wallraven, C., et al. (2014). Data-driven multisubject neuroimaging analyses for naturalistic stimuli. In Proceedings of the 2014 International Workshop on Pattern Recognition in Neuroimaging. Piscataway: IEEE.

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 Creators:
Biessmann, Felix, Author
Gaebler, Michael1, Author           
Lamke, Jan-Peter, Author
Ju, Ui Jong, Author
Hetzer, Stefan2, Author           
Wallraven, Christian, Author
Muller, Klaus-Robert, Author
Affiliations:
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              

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 Abstract: A central question in neuroscience is how the brain reacts to real world sensory stimuli. Naturalistic and complex (e.g. movie) stimuli are increasingly used in empirical research but their analysis often relies on considerable human efforts to label or extract stimulus features. Here we present data-driven analysis strategies that help to obtain interpretable results from multisubject neuroimaging data when complex movie stimuli are used. These analyses a) enable localization and visualization of brain activity using standard statistical parametric maps in the subspace of brain activity shared between subjects and b) facilitate interpretation of intersubject correlations. We show experimental results obtained from 50 subjects.

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Language(s): eng - English
 Dates: 2014
 Publication Status: Issued
 Pages: 4
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1109/PRNI.2014.6858511
 Degree: -

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Title: 2014 International Workshop on Pattern Recognition in Neuroimaging
Place of Event: Tübingen, Germany
Start-/End Date: 2014-06-04 - 2014-06-06

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Title: Proceedings of the 2014 International Workshop on Pattern Recognition in Neuroimaging
Source Genre: Proceedings
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Publ. Info: Piscataway : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISBN: 978-1-4799-4150-6