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Poster

Preserving maximal spatial specificity in resting state group analysis at 7 tesla

MPG-Autoren
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Jäger,  Anna-Thekla
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Huntenburg,  Julia M.
Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Tardif,  Christine
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Gauthier,  Claudine
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Steele,  Christopher
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Bazin,  Pierre-Louis
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Zitation

Jäger, A.-T., Huntenburg, J. M., Tardif, C., Gauthier, C., Villringer, A., Steele, C., et al. (2018). Preserving maximal spatial specificity in resting state group analysis at 7 tesla. Poster presented at Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, France.


Zitierlink: https://hdl.handle.net/21.11116/0000-0004-D123-8
Zusammenfassung
Most studies use standard software pipelines for processing and analyzing fMRI data. These pipelines were designed to work with data from 3 Tesla scanners. With more widespread availability of ultra-high field MRI scanners, new processing techniques need to be applied to address the unique demands of high resolution data and to fully take advantage of the high spatial specificity. Here, we propose a novel approach for processing and analysing high resolution resting state fMRI data.