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Aberrant Brain Network Efficiency in Parkinson's Disease Patients with Tremor: A Multi-Modality Study.

Zhang D, Wang J, Liu X, Chen J, Liu B - Front Aging Neurosci (2015)

Bottom Line: Notably, the global and local efficiency were both significantly increased in the morphological brain network of PD patients.We further found that the global and local network efficiency both worked well on PD classifications (i.e., using MVPA) and clinical performance descriptions (i.e., using MLRM).More importantly, functional and morphological brain networks were highly associated in terms of network local efficiency in PD patients.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine , Guangzhou , China ; Guangzhou University of Chinese Medicine Postdoctoral Mobile Research Station , Guangzhou , China.

ABSTRACT
The coordination of spontaneous brain activity is widely enhanced relative to compensation activity in Parkinson's disease (PD) with tremor; however, the associated topological organization remains unclear. This study collected magnetic resonance imaging data from 36 participants [i.e., 16 PD patients and 20 matched normal controls (NCs)] and constructed wavelet-based functional and morphological brain networks for individual participants. Graph-based network analysis indicated that the information translation efficiency in the functional brain network was disrupted within the wavelet scale 2 (i.e., 0.063-0.125 Hz) in PD patients. Compared with the NCs, the network local efficiency was decreased and the network global efficiency was increased in PD patients. Network local efficiency could effectively discriminate PD patients from the NCs using multivariate pattern analysis, and could also describe the variability of tremor based on a multiple linear regression model (MLRM). However, these observations were not identified in the network global efficiency. Notably, the global and local efficiency were both significantly increased in the morphological brain network of PD patients. We further found that the global and local network efficiency both worked well on PD classifications (i.e., using MVPA) and clinical performance descriptions (i.e., using MLRM). More importantly, functional and morphological brain networks were highly associated in terms of network local efficiency in PD patients. This study sheds lights on network disorganization in PD with tremor and helps for understanding the neural basis underlying this type of PD.

No MeSH data available.


Related in: MedlinePlus

Global parameters of brain networks. (A) functional brain network related to wavelet scale 2; (B) individual morphological brain network. *p < 0.05.
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Figure 1: Global parameters of brain networks. (A) functional brain network related to wavelet scale 2; (B) individual morphological brain network. *p < 0.05.

Mentions: Relative to matched random networks, the network efficiency analysis revealed that a larger local efficiency but approximately equal global efficiency (i.e., small-world organization attribute) was observed in the PD functional brain network. However, statistical comparisons revealed significant differences in the network efficiency between the two groups. The PD patients showed significantly decreased local efficiency (p = 0.02), increased global efficiency (p = 0.01), and normal global efficiency (p = 0.01) in the functional networks (Figure 1A), compared to the NC group.


Aberrant Brain Network Efficiency in Parkinson's Disease Patients with Tremor: A Multi-Modality Study.

Zhang D, Wang J, Liu X, Chen J, Liu B - Front Aging Neurosci (2015)

Global parameters of brain networks. (A) functional brain network related to wavelet scale 2; (B) individual morphological brain network. *p < 0.05.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4553412&req=5

Figure 1: Global parameters of brain networks. (A) functional brain network related to wavelet scale 2; (B) individual morphological brain network. *p < 0.05.
Mentions: Relative to matched random networks, the network efficiency analysis revealed that a larger local efficiency but approximately equal global efficiency (i.e., small-world organization attribute) was observed in the PD functional brain network. However, statistical comparisons revealed significant differences in the network efficiency between the two groups. The PD patients showed significantly decreased local efficiency (p = 0.02), increased global efficiency (p = 0.01), and normal global efficiency (p = 0.01) in the functional networks (Figure 1A), compared to the NC group.

Bottom Line: Notably, the global and local efficiency were both significantly increased in the morphological brain network of PD patients.We further found that the global and local network efficiency both worked well on PD classifications (i.e., using MVPA) and clinical performance descriptions (i.e., using MLRM).More importantly, functional and morphological brain networks were highly associated in terms of network local efficiency in PD patients.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine , Guangzhou , China ; Guangzhou University of Chinese Medicine Postdoctoral Mobile Research Station , Guangzhou , China.

ABSTRACT
The coordination of spontaneous brain activity is widely enhanced relative to compensation activity in Parkinson's disease (PD) with tremor; however, the associated topological organization remains unclear. This study collected magnetic resonance imaging data from 36 participants [i.e., 16 PD patients and 20 matched normal controls (NCs)] and constructed wavelet-based functional and morphological brain networks for individual participants. Graph-based network analysis indicated that the information translation efficiency in the functional brain network was disrupted within the wavelet scale 2 (i.e., 0.063-0.125 Hz) in PD patients. Compared with the NCs, the network local efficiency was decreased and the network global efficiency was increased in PD patients. Network local efficiency could effectively discriminate PD patients from the NCs using multivariate pattern analysis, and could also describe the variability of tremor based on a multiple linear regression model (MLRM). However, these observations were not identified in the network global efficiency. Notably, the global and local efficiency were both significantly increased in the morphological brain network of PD patients. We further found that the global and local network efficiency both worked well on PD classifications (i.e., using MVPA) and clinical performance descriptions (i.e., using MLRM). More importantly, functional and morphological brain networks were highly associated in terms of network local efficiency in PD patients. This study sheds lights on network disorganization in PD with tremor and helps for understanding the neural basis underlying this type of PD.

No MeSH data available.


Related in: MedlinePlus