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Conference Paper

Different brain areas require different analysis models: fMRI observations in Parkinson's disease

MPS-Authors
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Torrecuso,  Renzo
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Mueller,  Karsten
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Method and Development Group Neural Data Science and Statistical Computing, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Holiga,  Štefan
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Roche Pharma Research and Early Development, Roche Innovation Center;

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Schroeter,  Matthias L.
Clinic for Cognitive Neurology, University Hospital Leipzig;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Möller,  Harald E.       
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Torrecuso, R., Mueller, K., Holiga, Š., Urgosik, D., Vymazal, J., Sieger, T., et al. (2022). Different brain areas require different analysis models: fMRI observations in Parkinson's disease. In Proceedings of the ISMRM 31st Annual Meeting & Exhibition.


Cite as: https://hdl.handle.net/21.11116/0000-000B-1222-A
Abstract
Foreseeing how specific brain areas respond in time to a stimulus can be a prerequisite for a successfully conceived fMRI experiment. We demonstrate that in medicated Parkinson’s disease patients, putamen's activation peaks around the onset of tapping but does not persist throughout the tapping block, whereas sustained activation is observed in the motor cortex. Consequently, in the widely used tapping paradigm “On vs. Off L-DOPA”, the drug effect remains undetected if statistical analysis apply a block design instead of an event-related one. Ignoring this information can lead to fallacious conclusions which suggests using different models to investigate different brain regions.