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Медицинская библиотека · Sheng li xue bao : [Acta physiologica Sinica] · 2016

[Effective connectivity within the default mode network modulated by methylphenidate using dynamic causal modeling on resting-state functional magnetic resonance imaging].

Xu Fang-Fang, Han Lu, He Hong-Jian, Zhu Yi-Hong, Zhong Jian-Hui

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Аннотация

The effective connectivity of default mode network (DMN) and its change after taking methylphenidate (MPH) were investigated in this study based on resting-state functional magnetic resonance imaging. Dynamic causal modeling (DCM) was applied to compare the effective connectivity between the conditions of taking MPH and placebo for 18 healthy male volunteers. Started with the network structural basis provided by a recent literature, endogenous low frequency fluctuation signals (0.01-0.08 Hz) of each node of DMN were taken as the driving input, and thirty-two possible models were designed according to the modulation effect of MPH on different connections between nodes. Model fitting and Bayesian model selection were performed to find the winning model and corresponding parameters. Our results indicated that the effective connectivity from medial prefrontal cortex (MPFC) to posterior cingulated cortex (PCC), from left/right inferior parietal lobule (L/RIPL) to MPFC, and from RIPL to PCC were excitatory, whereas the connectivity from LIPL to PCC was inhibitory. Further t-test statistics on connectivity parameters found that MPH significantly reduced the link from RIPL to MPFC in DMN (t = 2.724, P = 0.016) and changed the weak excitatory state to inhibitory state. However, it had no significant effect on other connections. In all, our results demonstrated that MPH modulates the effective connectivity within DMN in resting state.

Для цитирования: Xu Fang-Fang, Han Lu, He Hong-Jian, Zhu Yi-Hong, Zhong Jian-Hui. [Effective connectivity within the default mode network modulated by methylphenidate using dynamic causal modeling on resting-state functional magnetic resonance imaging].. Sheng li xue bao : [Acta physiologica Sinica]. 2016.

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