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  Improving fMRI in Parkinson's disease by accounting for brain region-specific activity patterns

Torrecuso, R., Mueller, K., Holiga, Š., Sieger, T., Vymazal, J., Růžička, F., et al. (2023). Improving fMRI in Parkinson's disease by accounting for brain region-specific activity patterns. NeuroImage: Clinical, 38: 103396. doi:10.1016/j.nicl.2023.103396.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000B-0D91-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-651E-F
Genre: Journal Article

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 Creators:
Torrecuso, Renzo1, Author           
Mueller, Karsten1, 2, 3, Author           
Holiga, Štefan1, 4, Author           
Sieger, T.2, Author
Vymazal, J.5, Author
Růžička, F.2, 5, Author
Roth, J.2, 5, Author
Růžička, E. F.2, Author
Schroeter, Matthias L.6, 7, Author           
Jech, R.2, 5, 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, First Faculty of Medicine, Charles University, Prague, Czech Republic, ou_persistent22              
3Method and Development Group Neural Data Science and Statistical Computing, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_3282987              
4Roche Pharma Research and Early Development, Roche Innovation Center, Basel, Switzerland, ou_persistent22              
5Na Homolce Hospital, Prague, Czech Republic, ou_persistent22              
6Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              
7Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Free keywords: Basal ganglia; Experimental design; fMRI; Motor circuit; Parkinson’s disease; Treatment effect
 Abstract: In functional magnetic imaging (fMRI) in Parkinson’s disease (PD), a paradigm consisting of blocks of finger tapping and rest along with a corresponding general linear model (GLM) is often used to assess motor activity. However, this method has three limitations: (i) Due to the strong magnetic field and the confined environment of the cylindrical bore, it is troublesome to accurately monitor motor output and, therefore, variability in the performed movement is typically ignored. (ii) Given the loss of dopaminergic neurons and ongoing compensatory brain mechanisms, motor control is abnormal in PD. Therefore, modeling of patients’ tapping with a constant amplitude (using a boxcar function) and the expected Parkinsonian motor output are prone to mismatch. (iii) The motor loop involves structures with distinct hemodynamic responses, for which only one type of modeling (e.g., modeling the whole block of finger tapping) may not suffice to capture these structure’s temporal activation. The first two limitations call for considering results from online recordings of the real motor output that may lead to significant sensitivity improvements. This was shown in previous work using a non-magnetic glove to capture details of the patients' finger movements in a so-called kinematic approach. For the third limitation, modeling motion initiation instead of the whole tapping block has been suggested to account for different temporal activation signatures of the motor loop’s structures. In the present study we propose improvements to the GLM as a tool to study motor disorders. For this, we test the robustness of the kinematic approach in an expanded cohort (n = 31), apply more conservative statistics than in previous work, and evaluate the benefits of an event-related model function. Our findings suggest that the integration of the kinematic approach offers a general improvement in detecting activations in subcortical structures, such as the basal ganglia. Additionally, modeling motion initiation using an event-related design yielded superior performance in capturing medication-related effects in the putamen. Our results may guide adaptations in analysis strategies for functional motor studies related to PD and also in more general applications.

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Language(s): eng - English
 Dates: 2023-03-262022-08-082023-04-012023-04-072023
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.nicl.2023.103396
Other: epub 2023
PMID: 37037118
PMC: PMC10120395
 Degree: -

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Project name : -
Grant ID : -
Funding program : Programme EXCELES (LX22NPO5107)
Funding organization : National Institute for Neurological Research, Czech Republic
Project name : -
Grant ID : -
Funding program : NextGenerationEU
Funding organization : European Union
Project name : -
Grant ID : -
Funding program : Cooperatio Program in Neuroscience
Funding organization : Charles University
Project name : 2020 call “Novel imaging and brain stimulation methods and technologies related to Neurodegenerative Diseases”-Neuripides project
Grant ID : -
Funding program : -
Funding organization : European Joint Programme Neurodegenerative Disease Research (JPND)
Project name : -
Grant ID : SCHR 774/5-1
Funding program : -
Funding organization : Deutsche Forschungsgemeinschaft (DFG)
Project name : eHealthSax Initiative
Grant ID : -
Funding program : -
Funding organization : Sächsische Aufbaubank (SAB)
Project name : -
Grant ID : -
Funding program : -
Funding organization : International Max Planck Research School on Neuroscience of Communication: Structure, Function, and Plasticity (IMPRS NeuroCom)

Source 1

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Title: NeuroImage: Clinical
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Elsevier
Pages: - Volume / Issue: 38 Sequence Number: 103396 Start / End Page: - Identifier: ISSN: 2213-1582
CoNE: https://pure.mpg.de/cone/journals/resource/2213-1582