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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

Discriminative regions that classify PD patients from NCs. FgE, functional network global efficiency; FlocE, functional network local efficiency; SgE, structure network global efficiency; SlocE, structure network local efficiency.
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Figure 3: Discriminative regions that classify PD patients from NCs. FgE, functional network global efficiency; FlocE, functional network local efficiency; SgE, structure network global efficiency; SlocE, structure network local efficiency.

Mentions: We also found that the local nodal efficiency in the morphological network could significantly discriminate the two groups (accuracy = 0.77, sensitivity = 0.81, specificity = 0.74) (z = 2.53). The regions were located at the right inferior (arbitral part)/medial (arbitral part)/superior/frontal gyrus, and the bilateral middle frontal gyrus. Nodal global efficiency could also discriminate the two groups (accuracy = 0.89, sensitivity = 0.94, and specificity = 0.84) (z = 3.51). The discriminative regions were found at the right lingual, rectus, and inferior (arbitral part)/medial (arbitral part)/superior/middle frontal gyrus, and the left postcentral gyrus. Figure 3 shows the details of these regions.


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)

Discriminative regions that classify PD patients from NCs. FgE, functional network global efficiency; FlocE, functional network local efficiency; SgE, structure network global efficiency; SlocE, structure network local efficiency.
© Copyright Policy
Related In: Results  -  Collection

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

Figure 3: Discriminative regions that classify PD patients from NCs. FgE, functional network global efficiency; FlocE, functional network local efficiency; SgE, structure network global efficiency; SlocE, structure network local efficiency.
Mentions: We also found that the local nodal efficiency in the morphological network could significantly discriminate the two groups (accuracy = 0.77, sensitivity = 0.81, specificity = 0.74) (z = 2.53). The regions were located at the right inferior (arbitral part)/medial (arbitral part)/superior/frontal gyrus, and the bilateral middle frontal gyrus. Nodal global efficiency could also discriminate the two groups (accuracy = 0.89, sensitivity = 0.94, and specificity = 0.84) (z = 3.51). The discriminative regions were found at the right lingual, rectus, and inferior (arbitral part)/medial (arbitral part)/superior/middle frontal gyrus, and the left postcentral gyrus. Figure 3 shows the details of these regions.

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