Altered Inter‐Network Functional Integration Underlies Speech Impairment in Parkinson's Disease: A Resting‐State fMRI Analysis
Shan Deng, Yongqing Xiao, Zimei Dong, Cai Zhong, Yu Yu, Chunxiao Yang, Liya Pan, Baohui Weng, Yuan Chen, Ziming Ye, Ying Liu, Chao QinABSTRACT
Background
Speech impairment is common in Parkinson's disease (PD) and lacks effective clinical interventions due to poorly understood underlying mechanisms. Therefore, this study aimed to explore the relationship between altered brain functional networks and speech impairments in PD, identifying neural correlates of abnormal brain activity linked to PD‐related speech disorders (SD).
Methods
Baseline clinical characteristics, neurobehavioral assessments, and resting‐state functional magnetic resonance imaging (rs‐fMRI) data were collected from three groups: PD individuals with SD (PD‐SD group), PD individuals without SD (PD‐NON‐SD group), and healthy controls (HC group). Independent component analysis (ICA) was performed to identify resting‐state networks (RSNs) using the Group ICA of fMRI Toolbox (GIFT) implemented in MATLAB. Functional network connectivity (FNC) was subsequently quantified by calculating Pearson correlation coefficients between the extracted RSNs. One‐way analysis of variance (ANOVA) was used to assess group differences in FNC, followed by post hoc pairwise comparisons for networks showing significant effects. Given the reported association between speech impairment and cognitive impairment in PD, correlation analyses were further performed to investigate the relationships between FNC alterations and clinical measures, including speech performance and cognitive function assessed by the Montreal Cognitive Assessment (MoCA).
Results
Significant differences in FNC were observed between the left frontoparietal network (LFPN) and auditory network (AUN) across the three groups ( p = 0.0280). In particular, the FNC between LFPN and AUN was significantly stronger in the PD‐SD group compared to the PD‐NON‐SD group ( p = 0.0221) and the HC group ( p = 0.0047). Spearman correlation analysis revealed significant positive correlation between LFPN‐AUN functional connectivity and Unified Parkinson's Disease Rating Scale part III (UPDRS‐III) speech subscores ( r s = 0.2624, p = 0.0466), as well as a significant negative correlation with MoCA scores ( r s = −0.2847, p = 0.0249).
Conclusion
This study identifies disrupted functional connectivity between the LFPN and AUN in individuals with PD‐SD. These findings suggest that altered integration of RSNs involved in motor, cognitive, and auditory processing may contribute to speech impairment in PD. Hyperconnectivity between LFPN and AUN may thus serve as a neural substrate for speech impairment in PD. Specifically, increased connectivity between the LFPN and AUN may represent a neural signature associated with speech dysfunction in PD. These results provide potential mechanistic insights and highlight candidate neural targets for future neuromodulation strategies aimed at improving speech function.