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  Improving fMRI in Parkinson's disease by accounting for realistic motor output

Torrecuso, R., Jech, R., Mueller, K., Holiga, Š., Sieger, T., Vymazal, J., et al. (2021). Improving fMRI in Parkinson's disease by accounting for realistic motor output. Poster presented at 10th IMPRS NeuroCom Summer School, Virtual.

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poster_NMR2_torrecuso_SUMMER_SCHOOL.pdf (Abstract), 8MB
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poster_NMR2_torrecuso_SUMMER_SCHOOL.pdf
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poster for the 10th IMPRS Summer School
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 Creators:
Torrecuso, Renzo1, Author           
Jech, Robert2, 3, Author
Mueller, Karsten1, 4, Author           
Holiga, Štefan1, Author           
Sieger, Tomas2, Author
Vymazal, Josef2, 3, Author
Růžička, Filip2, 3, Author
Roth, Jan2, 3, Author
Růžička, Evzen2, Author
Schroeter, Matthias L.5, 6, Author           
Möller, Harald E.1, Author           
Affiliations:
1Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              
2Department of Neurology and Center of Clinical Neuroscience, Charles University in Prague, Prague, Czech Republic, ou_persistent22              
3Department of Radiology, Na Homolce Hospital, Prague, Czech Republic, ou_persistent22              
4Method and Development Group Neural Data Science and Statistical Computing, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_3282987              
5Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany, ou_persistent22              
6Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Free keywords: fMRI, GLM, kinematic modeling, Parkinson, basal ganglia
 Abstract: In Parkinson's disease (PD), the motor loop functioning and the patients’ motor output are unpredictable, due to brain compensatory mechanisms initiated up to decades before diagnosis.
Consequently, the accuracy of motor tasks during fMRI is impeded, and deviations of the movement performance affect results.
Kinematic modeling based on simultaneous measurements with MR-compatible gloves has been previously proposed as means to address this problem and outperform conventional boxcar modeling (Standard).
Here, we adopted this approach in a larger cohort along with conservative statistics employing family-wise error (FWE) correction at the voxel level (p< 0.05) to be less prone to produce false positives.

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 Dates: 2021-07
 Publication Status: Not specified
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Title: 10th IMPRS NeuroCom Summer School
Place of Event: Virtual
Start-/End Date: 2021-07-05 - 2021-07-08

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