An investigation of cardiac vagal tone over time and its relation to vigilance performance: a growth curve modeling approach

Figures

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  Figure 1. Visual representation of non-target pressure gauge (left) and target pressure gauge (right). Adapted from Greenlee et al. (2015).

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  Figure 2. Diagram demonstrating accurate placement of ECG electrodes.

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  Figure 3. Schematic of the experiment.

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  Figure 4. Spaghetti plot of all 32 participants across both low and high task load. Just as detailed in Figure 3, T1 was the 5-min baseline, T2–T7 are the six, 5-min time periods in the vigilance task (two time periods per block), T8 was the first 5 min of the break, and T9–T10 were the two, 5-min timepoints in the post-break vigilance task.

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  Figure 5. Estimated marginal means of a saturated means, unstructured variance model for cardiac vagal tone. It is estimating a non-monotonic increase in cardiac vagal tone, on average, over the course of the vigilance task, break, and post-break vigilance task.

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  Figure 6. Estimated means of each unconditional growth curve model that was compared to the saturated means, unstructured variance model for cardiac vagal tone (i.e., the natural log of RMSSD). All models estimate an increase in cardiac vagal tone, on average, but the rate and timing at which it increases differs.

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  Figure 7. The estimated unconditional growth curves for (A) three participants whose estimated unconditional growth curve model are particularly different than (B) all participants.

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  Figure 8. The estimated conditional growth curve for the average vigilance decrement observed, as well as 1 standard deviation above and below it, respectively.