Abstract

Background: Abnormal spontaneous neural activity is often found in patients with Parkinson’s disease with mild cognitive impairment (PD-MCI). However, the frequency dependence of neuronal interaction activities, especially the fractional amplitude of low-frequency fluctuation (fALFF) and degree centrality (DC), in PD-MCI is still unclear. Thus, this study aimed to explore the frequency dependence of PD-MCI based on fALFF and DC maps.Methods: Twenty-four patients with PD-MCI, 42 PD patients with normal cognition (PD-NC), and 33 healthy controls (HCs) were enrolled. Neuropsychological assessments and resting-state functional MRI (rs-fMRI) were performed. The fALFF and DC values in the conventional, slow4 and slow5 frequency bands were compared among the groups.Results: In the conventional frequency band, the DC value in the left precentral area was decreased in PD-MCI patients, while that in the right fusiform area was increased in PD-NC patients compared with HCs. Regarding fALFFs, both the PD-MCI and PD-NC patients had decreased values in the right precentral area compared with those of the HCs. The fALFFs did not differ between PD-MCI and PD-NC patients. The fALFF results in the slow4 subfrequency band were consistent with those in the conventional frequency band. In the slow5 band, the DC value in the left middle temporal lobe was higher in PD-MCI patients than in PD-NC patients and was positively correlated with the performance of the PD-MCI patients on the Montreal Cognitive Assessment (MoCA). Additionally, both PD-MCI and PD-NC patients showed lower fALFF values in the bilateral putamen than the HCs, and the fALFF in the bilateral putamen was negatively correlated with the Hoehn and Yahr stages of PD-MCI. The fALFF in the left putamen was negatively correlated with the scores of PD-MCI patients on the Movement Disorder Society-Unified Parkinson Disease Rating Scale Part III (MDS-UPRDS-III).Conclusion: Our results suggested that abnormal neuronal activities, such as fALFF and DC, are dependent on frequency in PD-MCI. Some subfrequency bands could distinguish PD-MCI from PD. Our findings may be helpful for further revealing the frequency-dependent resting functional disruption in PD-MCI.

Highlights

  • Parkinson’s disease (PD), a neurodegenerative disease characterized by typical motor symptoms such as bradykinesia, resting tremors, and rigidity, is accompanied by nonmotor symptoms, including cognitive impairment, anxiety, depression, and sleep disorders (Postuma et al, 2015)

  • Most previous studies focused on the use of amplitude of low-frequency fluctuations (ALFFs) to investigate the disruption of neural activity in PD with mild cognitive impairment (PD-MCI), while fewer studies have focused on fractional amplitude of low-frequency fluctuation and degree centrality (DC) values

  • The Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA) scores were higher in the PD-MCI and PD with normal cognition (PD-NC) groups than in the healthy controls (HCs) group, and the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores of the PD-MCI group were lower than those of the PD-NC and HC groups

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Summary

Introduction

Parkinson’s disease (PD), a neurodegenerative disease characterized by typical motor symptoms such as bradykinesia, resting tremors, and rigidity, is accompanied by nonmotor symptoms, including cognitive impairment, anxiety, depression, and sleep disorders (Postuma et al, 2015). Several methods of characterizing the local properties of rs-fMRI signals, including the amplitude of low-frequency fluctuations (ALFFs), the fractional amplitude of low-frequency fluctuations (fALFFs), and degree centrality (DC), have not been fully used to investigate abnormal functional patterns in PD. Most previous studies focused on the use of ALFF to investigate the disruption of neural activity in PD-MCI, while fewer studies have focused on fractional amplitude of low-frequency fluctuation (fALFF) and DC values. These voxelwise metrics can define different brain function characteristics in the resting state and highlight disease features. This study aimed to explore the frequency dependence of PD-MCI based on fALFF and DC maps

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