Abstract
Autonomic arousal is often indexed by spontaneous fluctuations in skin conductance. Here, we derive a simple measure of sympathetic arousal, using a convolution model of how sudomotor bursting causes fluctuations in skin conductivity. Under this model, the time-integral of measured conductance is proportional to the frequency and amplitude of sudomotor bursts. We demonstrate the validity of this measure in relation to finite impulse response models, and show that it is a better predictor of autonomic arousal, relative to conventional measures.
Highlights
Autonomic arousal is often indexed by spontaneous fluctuations in skin conductance
We quantified the validity of our linear time-invariant (LTI) assumptions (implicit in Eq (1)) by ensuring we could account for the majority of observed variance with a simple LTI convolution model
The statistic we derive, namely the area under the curve AUC, or skin conductance level (SCL)-corrected time-integral, is closely related to number and amplitude of spontaneous fluctuations (SF) as scored by an independent, conventional method. It predicts experimentally manipulated autonomic arousal in a public speaking paradigm and is a significantly better predictor than the amplitude and number of SF estimated conventionally and may provide a less noisy estimate of sudomotor activity. This is not surprising, as we show that SFs seem to be largely timeinvariant and only differ in amplitude, rather than in their shape
Summary
Autonomic arousal is often indexed by spontaneous fluctuations in skin conductance. Here, we derive a simple measure of sympathetic arousal, using a convolution model of how sudomotor bursting causes fluctuations in skin conductivity. We develop a simple measure of autonomic arousal based on linear time-invariant [LTI] assumptions and validate it on a previously published dataset in the context of anxiety aroused by public speaking anticipation.
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