Data-driven multisubject neuroimaging analyses for naturalistic stimuli

Felix Biessmann; Michael Gaebler; Jan Peter Lamke; Ui Jong Ju; Stefan Hetzer; Christian Wallraven; Klaus Muller

doi:10.1109/PRNI.2014.6858511

Data-driven multisubject neuroimaging analyses for naturalistic stimuli

Felix Biessmann, Michael Gaebler, Jan Peter Lamke, Ui Jong Ju, Stefan Hetzer, Christian Wallraven, Klaus Muller

Department of Brain and Cognitive Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014
Publisher	IEEE Computer Society
ISBN (Print)	9781479941506
DOIs	https://doi.org/10.1109/PRNI.2014.6858511
Publication status	Published - 2014 Jan 1
Event	4th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014 - Tubingen, Germany Duration: 2014 Jun 4 → 2014 Jun 6

Other

Other	4th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014
Country/Territory	Germany
City	Tubingen
Period	14/6/4 → 14/6/6

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Biomedical Engineering

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10.1109/PRNI.2014.6858511

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Biessmann, F, Gaebler, M, Lamke, JP, Ju, UJ, Hetzer, S, Wallraven, C & Muller, K 2014, Data-driven multisubject neuroimaging analyses for naturalistic stimuli. in Proceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014., 6858511, IEEE Computer Society, 4th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014, Tubingen, Germany, 14/6/4. https://doi.org/10.1109/PRNI.2014.6858511

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title = "Data-driven multisubject neuroimaging analyses for naturalistic stimuli",

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.",

keywords = "Canonical Correlation Analysis, CCA, Hyperscanning, Intersubject Correlation, Multisubject Neuroimaging",

author = "Felix Biessmann and Michael Gaebler and Lamke, {Jan Peter} and Ju, {Ui Jong} and Stefan Hetzer and Christian Wallraven and Klaus Muller",

year = "2014",

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doi = "10.1109/PRNI.2014.6858511",

language = "English",

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booktitle = "Proceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014",

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AU - Biessmann, Felix

AU - Gaebler, Michael

AU - Lamke, Jan Peter

AU - Ju, Ui Jong

AU - Hetzer, Stefan

AU - Wallraven, Christian

AU - Muller, Klaus

PY - 2014/1/1

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N2 - 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.

AB - 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.

KW - Canonical Correlation Analysis

KW - CCA

KW - Hyperscanning

KW - Intersubject Correlation

KW - Multisubject Neuroimaging

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BT - Proceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014

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Y2 - 4 June 2014 through 6 June 2014

ER -

Data-driven multisubject neuroimaging analyses for naturalistic stimuli

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