Abstract
Objective: This study aimed to explore alterations in the topological properties of the functional brain network in primary Parkinson’s disease (PD) patients with freezing of gait (PD-FOG).Methods: Resting-state functional magnetic resonance imaging (Rs-fMRI) data were obtained in 23 PD-FOG patients, 33 PD patients without FOG (PD-nFOG), and 24 healthy control (HC) participants. The whole-brain functional connectome was constructed by thresholding the Pearson correlation matrices of 90 brain regions, and topological properties were analyzed by using graph theory approaches. The network-based statistics (NBS) method was used to determine the suprathreshold connected edges (P < 0.05; threshold T = 2.725), and statistical significance was estimated by using the non-parametric permutation method (5,000 permutations). Statistically significant topological properties were further evaluated for their relationship with clinical neurological scales.Results: The topological properties of the functional brain network in PD-FOG and PD-nFOG showed no abnormalities at the global level. However, compared with HCs, PD-FOG patients showed decreased nodal local efficiency in several brain regions, including the bilateral striatum, frontoparietal areas, visual cortex, and bilateral superior temporal gyrus, increased nodal local efficiency in the left gyrus rectus. When compared with PD-nFOG patients and HCs, PD-FOG showed increased betweenness centrality in the left hippocampus. Moreover, compared to HCs, both PD-FOG and PD-nFOG patients displayed reduced network connections by using the NBS method, mainly involving the sensorimotor cortex (SM), visual network (VN), default mode network (DMN), auditory network (AN), dorsal attention network (DAN), subcortical regions, and limbic network (LIM). The local node efficiency of the right temporal pole: superior temporal gyrus in PD-FOG patients was positively correlated with the Freezing of Gait Questionnaire (FOGQ) scores.Conclusions: This study demonstrates the disrupted regional topological organization in PD-FOG patients, especially associated with damage to the subcortical regions and multiple cortical regions. Our results provide insights into the dysfunctional mechanisms of the relevant networks and indicate potential neuroimaging biomarkers of PD-FOG.
Highlights
Freezing of gait (FOG) is considered one of the most common motor symptoms in Parkinson’s disease (PD) characterized by a brief, episodic absence or unsuccessful attempts to start or turn despite the intention to walk and is often characterized as the patient having a foot ‘‘glued’’ to the floor
The Freezing of Gait Questionnaire (FOGQ) and GFQ scales are evaluated under the OFF medication state, and Unified Parkinson’s Disease Rating Scale (UPDRS)-III is evaluated under the ON medication state
No significant differences were detected among the groups for gender, age or Mini-Mental State Examination (MMSE) scores (P > 0.05)
Summary
Freezing of gait (FOG) is considered one of the most common motor symptoms in Parkinson’s disease (PD) characterized by a brief, episodic absence or unsuccessful attempts to start or turn despite the intention to walk and is often characterized as the patient having a foot ‘‘glued’’ to the floor. Several mechanisms, including motor (i.e., postural instability), cognitive (i.e., abnormal executive and visuospatial functions) as well as behavioral disorders (i.e., anxiety), have been proposed to explain FOG (Nutt et al, 2011; Factor et al, 2014). The currently available data indicate that widespread functional disruptions in cortical and subcortical brain structures involving multiple brain networks are responsible for FOG in PD. We noticed that these studies detected coupling between symptoms and abnormal regional spontaneous neural activity or aberrant within-network intrinsic activity, rather than integrating the specificity of brain regions and connectivity of different brain regions into one framework for analysis in FOG patients. There may be new discoveries on the mechanism of FOG from the perspective of the brain’s functional network
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