Dynamic causal modeling of spontaneous fluctuations in skin conductance
Dynamic causal modeling of spontaneous fluctuations in skin conductance
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DOI：
10.1111/j.1469-8986.2010.01052.x
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发表时间：
2011-02-01
期刊：
影响因子：
3.7
通讯作者：
Dolan, Raymond J.
中科院分区：
文献类型：
--
作者：
Bach, Dominik R.;Daunizeau, Jean;Dolan, Raymond J.
皮肤电导的自发波动（SF）通常用于指示交感神经唤醒和情绪状态。SF是由催汗神经活动（SNA）引起的，其是交感神经唤醒的直接指标。在这里，我们描述了一个动态因果模型（DCM）SNA如何导致SF，并应用变分贝叶斯模型反演来推断SNA，经验观察SF。估计的SNA与从常规（半视觉）分析得出的SF数量有关系。至关重要的是，我们表明，在公众演讲引起的焦虑，SNA突发的估计数量是一个更好的预测（已知）的心理状态比SF的数量。我们建议SF的动态因果模型可能允许一个更精确和更明智的推理比纯粹的描述性方法的觉醒。
Spontaneous fluctuations (SF) in skin conductance are often used to index sympathetic arousal and emotional states. SF are caused by sudomotor nerve activity (SNA), which is a direct indicator of sympathetic arousal. Here, we describe a dynamic causal model (DCM) of how SNA causes SF, and apply variational Bayesian model inversion to infer SNA, given empirically observed SF. The estimated SNA bears a relationship to the number of SF as derived from conventional (semi-visual) analysis. Crucially, we show that, during public speaking induced anxiety, the estimated number of SNA bursts is a better predictor of the (known) psychological state than the number of SF. We suggest dynamic causal modeling of SF potentially allows a more precise and informed inference about arousal than purely descriptive methods.