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Risperidone Effects on Brain Dynamic Connectivity—A Prospective Resting-State fMRI Study in Schizophrenia

機(jī)譯：利培酮對大腦動態(tài)連通性的影響—精神分裂癥的前瞻性靜息態(tài)fMRI研究

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Resting-state functional connectivity studies in schizophrenia evaluating average connectivity over the entire experiment have reported aberrant network integration, but findings are variable. Examining time-varying (dynamic) functional connectivity may help explain some inconsistencies. We assessed dynamic network connectivity using resting-state functional MRI in patients with schizophrenia, while unmedicated (n = 34), after 1 week (n = 29) and 6 weeks of treatment with risperidone (n = 24), as well as matched controls at baseline (n = 35) and after 6 weeks (n = 19). After identifying 41 independent components (ICs) comprising resting-state networks, sliding window analysis was performed on IC timecourses using an optimal window size validated with linear support vector machines. Windowed correlation matrices were then clustered into three discrete connectivity states (a relatively sparsely connected state, a relatively abundantly connected state, and an intermediately connected state). In unmedicated patients, static connectivity was increased between five pairs of ICs and decreased between two pairs of ICs when compared to controls, dynamic connectivity showed increased connectivity between the thalamus and somatomotor network in one of the three states. State statistics indicated that, in comparison to controls, unmedicated patients had shorter mean dwell times and fraction of time spent in the sparsely connected state, and longer dwell times and fraction of time spent in the intermediately connected state. Risperidone appeared to normalize mean dwell times after 6 weeks, but not fraction of time. Results suggest that static connectivity abnormalities in schizophrenia may partly be related to altered brain network temporal dynamics rather than consistent dysconnectivity within and between functional networks and demonstrate the importance of implementing complementary data analysis techniques.
機(jī)譯：精神分裂癥的靜息狀態(tài)功能連接性研究評估了整個實驗的平均連接性，報告了異常的網(wǎng)絡(luò)整合，但是發(fā)現(xiàn)是可變的。檢查時變（動態(tài)）功能連接可能有助于解釋某些不一致之處。我們在未接受藥物治療（n assessed = 34），1周（none = 29）和6周利培酮治療（n（= 24）以及相匹配的對照組的精神分裂癥患者中使用靜息狀態(tài)功能MRI評估了動態(tài)網(wǎng)絡(luò)連通性在基線（n = 35）和6周后（n = 19）。在確定了包括靜止?fàn)顟B(tài)網(wǎng)絡(luò)的41個獨立組件（IC）之后，使用經(jīng)過線性支持向量機(jī)驗證的最佳窗口大小在IC時間線上執(zhí)行滑動窗口分析。然后，將窗口相關(guān)矩陣聚類為三個離散的連接狀態(tài)（相對稀疏的連接狀態(tài)，相對豐富的連接狀態(tài)和中間連接狀態(tài)）。在未接受藥物治療的患者中，與對照組相比，五對IC之間的靜態(tài)連通性增加，而兩對IC之間的靜態(tài)連通性下降，動態(tài)連通性顯示丘腦和軀體運動網(wǎng)絡(luò)之間處于三種狀態(tài)之一的連通性增加。州統(tǒng)計數(shù)據(jù)表明，與對照組相比，未接受藥物治療的患者在稀疏連接狀態(tài)下的平均停留時間和花費的時間較短，在中間連接狀態(tài)下的停留時間和花費的時間較長。利培酮似乎可以使6周后的平均駐留時間正常化，但不是時間的一部分。結(jié)果表明，精神分裂癥中的靜態(tài)連接異常可能部分與大腦網(wǎng)絡(luò)時間動態(tài)變化有關(guān)，而不是與功能網(wǎng)絡(luò)內(nèi)部和功能網(wǎng)絡(luò)之間持續(xù)的不連通相關(guān)，并且證明了實施補(bǔ)充數(shù)據(jù)分析技術(shù)的重要性。

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