Aberrant Brain Network Efficiency in Parkinson’s Disease Patients with Tremor: A Multi-Modality Study
Identifieur interne : 000047 ( Main/Exploration ); précédent : 000046; suivant : 000048Aberrant Brain Network Efficiency in Parkinson’s Disease Patients with Tremor: A Multi-Modality Study
Auteurs : Delong Zhang [République populaire de Chine] ; Jinhui Wang [République populaire de Chine] ; Xian Liu [République populaire de Chine] ; Jun Chen [République populaire de Chine] ; Bo Liu [République populaire de Chine]Source :
- Frontiers in Aging Neuroscience ; 2015.
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.
Url:
DOI: 10.3389/fnagi.2015.00169
PubMed: 26379547
PubMed Central: 4553412
Affiliations:
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<front><div type="abstract" xml:lang="en"><p>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.</p>
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<tree><country name="République populaire de Chine"><noRegion><name sortKey="Zhang, Delong" sort="Zhang, Delong" uniqKey="Zhang D" first="Delong" last="Zhang">Delong Zhang</name>
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<name sortKey="Chen, Jun" sort="Chen, Jun" uniqKey="Chen J" first="Jun" last="Chen">Jun Chen</name>
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<name sortKey="Liu, Xian" sort="Liu, Xian" uniqKey="Liu X" first="Xian" last="Liu">Xian Liu</name>
<name sortKey="Wang, Jinhui" sort="Wang, Jinhui" uniqKey="Wang J" first="Jinhui" last="Wang">Jinhui Wang</name>
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