| Popis: |
Parkinson’s disease manifests principally as resting tremor, rigidity, akinesia and postural instability and exhibits deficits in information-processing tasks and abnormalities in the striatum. Human brain is one of the most complex information processing systems and resting-state fMRI signals, which possess complex nonlinear dynamic properties, have been extensively applied to study changes in brain function. However, it remains unclear whether patients with Parkinson’s disease and prodromal Parkinson’s disease have an abnormal complexity in resting-state fMRI signals and whether the abnormalities are frequency band dependent. Therefore, we investigated the complexity of signals in 47 patients with Parkinson’s disease, 26 patients with prodromal Parkinson’s disease and 21 normal controls within four frequency bands with Fuzzy Entropy. After preprocessing, entropy maps of the whole brain were extracted within four different frequency bands. Then we performed a one-way analysis of variance and results in slow-2 and slow-3 bands revealed that Parkinson’s disease patients exhibited higher complexity than those with prodromal Parkinson’s disease and normal controls. Prodromal Parkinson’s disease patients exhibited lower complexity than normal controls. Significant differences were observed mainly in the precentral gyrus , precuneus, caudate, thalamus and superior frontal gyrus. Significant correlations were found between the Fuzzy Entropy and clinical characteristics, regional homogeneity, gray matter volume and gray matter density. The results indicated that Parkinson’s disease and prodromal Parkinson’s disease patients had abnormal intrinsic neural oscillations, mainly in slow-3 and slow-2 bands, depending on frequency bands. Complexity analysis of resting-state fMRI signals in multiple bands can help probe brain activity and pathophysiology of neurodegenerative diseases. |
