Abstract
COVER ILLUSTRATION Paroxysmal kinesigenic dyskinesia (PKD) is a rare movement disorder characterized by transient dystonic or choreoathetoid attacks (illustrated as “cartoon-figures” which imitate the dystonic or choreoathetoid attacks). Combining brain structural network (illustrated as the stereoscopic brain) and machine learning (illustrated as the number of “0” and “1” and technological screen) techniques can successfully discriminate PKD patients from healthy controls. We get the highest accuracy of 87.8% in the classification of PKD patients and healthy controls by using gray matter morphological networks matrices, which suggest that gray matter morphological network matrices may have potential as neuroimaging biomarkers to assist in clinical PKD diagnosis.
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