Meekes, Joost and Debener, Stefan and Zich, Catharina and Bleichner, Martin G. and Kranczioch, Cornelia (2019) Does Fractional Anisotropy Predict Motor Imagery Neurofeedback Performance in Healthy Older Adults? Frontiers in Human Neuroscience, 13. ISSN 1662-5161

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Motor imagery neurofeedback training has been proposed as a potential add-on therapy for motor impairment after stroke, but not everyone benefits from it. Previous work has used white matter integrity to predict motor imagery neurofeedback aptitude in healthy young adults. We set out to test this approach with motor imagery neurofeedback that is closer to that used for stroke rehabilitation and in a sample whose age is closer to that of typical stroke patients. Using shrinkage linear discriminant analysis with fractional anisotropy values in 48 white matter regions as predictors, we predicted whether each participant in a sample of 21 healthy older adults (48–77 years old) was a good or a bad performer with 84.8% accuracy. However, the regions used for prediction in our sample differed from those identified previously, and previously suggested regions did not yield significant prediction in our sample. Including demographic and cognitive variables which may correlate with motor imagery neurofeedback performance and white matter structure as candidate predictors revealed an association with age but also led to loss of statistical significance and somewhat poorer prediction accuracy (69.6%). Our results suggest cast doubt on the feasibility of predicting the benefit of motor imagery neurofeedback from fractional anisotropy. At the very least, such predictions should be based on data collected using the same paradigm and with subjects whose characteristics match those of the target case as closely as possible.

Item Type: Article
Additional Information: Publiziert mit Hilfe des DFG-geförderten Open Access-Publikationsfonds der Carl von Ossietzky Universität Oldenburg.
Uncontrolled Keywords: motor imagery, EEG, neurofeedback, white matter, fractional anisotropy, MRI, shrinkage linear discriminant analysis
Subjects: Technology, medicine, applied sciences > Medicine and health
Divisions: Faculty of Medicine and Health Sciences > Department of Neuro Sciences
Faculty of Medicine and Health Sciences > Department of Psychology
Date Deposited: 18 Mar 2020 08:51
Last Modified: 18 Mar 2020 08:51
URN: urn:nbn:de:gbv:715-oops-45506
DOI: 10.3389/fnhum.2019.00069

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