Functional Network Connectivity Analysis In Sensorimotor Area Of Parkinson’s Disease

ObjectiveThis study use functional network connectivity(FNC)analysis and dynamic functional network connectivity(dFNC)analysis to research the sensorimotor network in Parkinson’s disease patients(PD)and healthy control subjects(HC),including comparing connectivity intensity differences in the whole brain and sensorimotor network,verifying the time variability in the instantaneous state,and analyzing the correlation with clinical motor indexes.The purpose is to explore the relationship between abnormal functional connections of sensorimotor network and clinical dyskinesia,so as to reveal the neural mechanism of Parkinson’s disease more deeply.MethodsWe recruited 30 primary Parkinson’s disease patients who have enrolled in the Department of Neurology,affiliated Hospital of Yangzhou University from January 2019 to December 2019,and 30 healthy control subjects.All the subjects performed resting state functional imaging scans.And the images were preprocessed by Restplus software implemented in MATLAB(version R2013b).The whole brain was divided into 53 independent components and classified into seven brain networks by GIFT software package.Functional networks of the whole brain were compared by two-sample t-test.The sensorimotor network was divided the into 18 independent components and classified into six subregions.Functional subregions of the sensorimotor network were compared by two-sample t-test.Then,we evaluated the correlation between connectivity intensity and Unified Parkinson’s Disease Rating Scale Ⅲscores in PD patients.We used sliding window method and k-means clustering method to analysis the dynamic functional connection in all subjects,assess fraction time(FT)、mean dwell time(MDT)and Number of transitions(NT),and calculate the connectivity intensity in each state.Finally,analyzed the correlation between each index and UPDRS-Ⅲ score.Results(1)Compared with HC group,it was found that the connectivity intensity between sensorimotor network and high-level visual network,as well as attention network was decreased(2)In the sensorimotor network,compared with HC group,it was found that the connectivity intensity between left precentral gyrus and right precentral gyrus,as well as paracentral lobule was decreased,but the connectivity intensity was increased between left precentral gyrus and left postcentral gyrus in PD group.Correlation analysis showed that the connectivity intensity between paracentral lobule,left precentral gyrus and left postcentral gyrus was negatively correlated with UPDRS-Ⅲ score.(3)Four kinds of functional connectivity states were identified in the sensorimotor area.compared with the control group,the occurrence rate of state 1,2 and 4 was increased in Parkinson’s disease group,and most connections were tighter,especially in state 1,and it was positively correlated with the score of clinical scale.In sparse connection(state 2),it was found that the connectivity intensity between paracentral lobule and right precentral/postcentral gyrus was decreased significantly.The frequency of state 3 was decreased,and it was negatively correlated with the score of clinical scale.The mean dwell time in state 4 was increased significantly.ConclusionCompared with the healthy control group,there are significant differences in connectivity in whole brain and sensorimotor network in PD patients,and most of them showed a weakening trend of connection strength.In the dynamic analysis,there was significant time variability in functional connectivity in PD patients too.It was suggested that abnormal and unstable brain functional connections may be one of the causes of motor dysfunction in Parkinson’s disease,such as resting tremor,myotonia,bradykinesia and so on.The combination of static and dynamic fMRI technology can provide a new perspective for disease in the future.