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Updated: Oct 13, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Disrupted dynamic pattern of regional neural activity in early-stage cognitively normal Parkinson's disease
Yi Zhang1, Xiulan Wang1, Yuan Li1
1Department of Radiology, Taizhou People's Hospital, Fifth Affiliated Hospital of Nantong University, Taizhou, PR China.
Background:
Neuroimaging studies on Parkinson's disease (PD) mainly focus on static neural activity. However, the dynamic pattern of regional brain activity in early-stage cognitively normal PD has rarely been elucidated.
Purpose:
To identify altered dynamic amplitude of low-frequency fluctuation (dALFF) in PD before the onset of cognitive impairment and verify its differentiating ability between patients with PD and healthy controls (HC).
Material And Methods:
dALFF and static ALFF (sALFF) derived from functional magnetic resonance imaging data of 51 patients with PD and 50 matched HCs were analyzed. The correlations between aberrant regions and clinical performance were investigated using Spearman correlation analysis. Multivariate pattern analysis was conducted to detect the differentiating ability of both ALFF features.
Results:
Compared with HCs, patients with PD demonstrated reduced dALFF variance in bilateral lingual gyrus, left middle occipital gyrus, left postcentral gyrus (PcG), and right supplementary motor area (SMA); and increased dALFF variability in bilateral parahippocampal gyrus. Besides overlapping with these distributions of altered dALFF, the aberrant regions of sALFF were more extensive with decreased sALFF in the right middle temporal gyrus and right PcG, and increased sALFF in the left inferior temporal gyrus and left thalamus were observed in patients with PD. dALFF values in right SMA and left PcG were correlated with UPDRS-III scores (ρ = -0.29, P = 0.041; ρ = -0.33, P = 0.018, respectively).
Conclusion:
This study provides novel insights into the neural basis underlying PD as well as the potential role of dynamic neural activity in the diagnosis and prediction of the disease.
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