• Open Access

Dynamic causal modeling of spontaneous fluctuations in skin conductance


  • We are grateful to Prof. Gisela Erdmann who provided us with two datasets from her laboratory for reanalysis, and to Guillaume Flandin for stimulating comments on this work. This research was funded by a Programme Grant to R.J.D. from the Wellcome Trust and in part by a Personal Grant to D.R.B. from the Swiss National Science Foundation.
    The data reanalyzed in this article were acquired while D.R.B. and N.K. were pursuing an MSc degree at the Institute for Psychology and Ergonomics, Technical University of Berlin, Germany.

  • Re-use of this article is permitted in accordance with the Terms and Conditions set out at http://wileyonlinelibrary.com/onlineopen#OnlineOpen_Terms

Address correspondence to: Dominik R. Bach, Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London WC1N 3BG, United Kingdom. E-mail: d.bach@fil.ion.ucl.ac.uk


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.