Research On Motor Impairment-related Brain Network In Parkinson’s Disease Based On FMRI

Motor impairment is a core clinical feature of Parkinson’s disease（PD）.Although the decoupled striatal functional connectivity（FC）has been widely reported in previous neuroimaging studies,how the functional connectome is involved in motor dysfunction has not been well elucidated in PD patients.The objective of this thesis is to develop a reliable brain signature to reflect motor dysfunction in PD.Tesing on independent samples,this thesis aims to validate the sensitivity to predict clinical motor scores,the predicted generalizability across different centers,and the represented specificity of the motor-related signature.This thesis firstly decomposed the Pearson’s correlation into accordance and discordance via a temporal discrete procedure,which can capture coupling and anti-coupling respectively.Using different profiles of FC,candidate predictive models were discovered on the training sample（n₁=71）and then the predictive generalizability was tested on three independent samples（n₂=45,n₃=60,n₄=60）.The antagonistic model measured by discordance had the best sensitivity and generalizability in all validations and it was dubbed as Parkinson’s antagonistic motor signature（PAMS）.The PAMS was dominated by the subcortical,somatomotor,visual,cerebellum,default-mode,and frontoparietal networks,and the motor-visual stream accounted for the most part of predictive weights among network-pairs.Stage-specific analysis showed that the predicted scores generated from the antagonistic model tended to be higher than the observed scores in the early course of PD,indicating that the functional signature may vary more sensitively with the neurodegenerative process than clinical behaviors.Additionally,a naive Bayes classifier on the basis of PAMS was trained on another demographics-matched sample,which consisted of 73 PD patients and 79 healthy controls.The mean accuracy of the classifier was 78%,and the area under Receiver Operating Characteristic curve was 0.84.Together,these findings suggest that motor dysfunction of PD can be represented as antagonistic interactions within multi-level brain systems.The signature shows great potential in the early motor evaluation and developing new therapeutic approaches for PD in the clinical realm.