MRI Assessment of Intrinsic Neural Timescale and Gray Matter Volume in Parkinson's Disease

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Abstract
Background: Numerous studies have indicated altered temporal features of the brain function in Parkinson's disease (PD), and the autocorrelation magnitude of intrinsic neural signals, called intrinsic neural timescales, were often applied to estimate how long neural information stored in local brain areas. However, it is unclear whether PD patients at different disease stages exhibit abnormal timescales accompanied with abnormal gray matter volume (GMV).Purpose: To assess the intrinsic timescale and GMV in PD.Study Type: Prospective.Population: 74 idiopathic PD patients (44 early stage (PD‐ES) and 30 late stage (PD‐LS), as determined by the Hoehn and Yahr (HY) severity classification scale), and 73 healthy controls (HC).Field Strength/Sequence: 3.0 T MRI scanner; magnetization prepared rapid acquisition gradient echo and echo planar imaging sequences.Assessment: The timescales were estimated by using the autocorrelation magnitude of neural signals. Voxel‐based morphometry was performed to calculate GMV in the whole brain. Severity of motor symptoms and cognitive impairments were assessed using the unified PD rating scale, the HY scale, the Montreal cognitive assessment, and the mini‐mental state examination.Statistical Test: Analysis of variance; two‐sample t‐test; Spearman rank correlation analysis; Mann–Whitney U test; Kruskal‐Wallis' H test. A P value ρ = −0.265, P = 0.022) and GMV (ρ = 0.254, P = 0.029). Compared to the HC group, the PD‐ES group had significantly longer timescales in anterior cortical regions, whereas the PD‐LS group had significantly shorter timescales in posterior cortical regions.Conclusion: This study suggested that PD patients have abnormal timescales in multisystem and distinct patterns of timescales and GMV in cerebral cortex at different disease stages. This may provide new insights for the neural substrate of PD.Level of Evidence: 2Technical Efficacy Stage: 1
Funding Information
  • National Natural Science Foundation of China (81601467, 81871327)

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