Subjective tactile sensitivity
For each of the three body locations, i.e., the tip of the little finger, the forearm, and the calf, subjective tactile sensitivity was assessed using Von Frey synthetic monofilaments (North Coast Medical; model: Touch Test) with a force ranging from 0.008 g to 300 g, starting at 2.0 g (Keizer et al., 2012; Weinstein, 1968). Participants were blindfolded and instructed to report whether they felt a stimulus at a given location. The experimenter applied tactile stimulation according to a forced-choice one up/one down staircase procedure (resulting in 5 subthreshold and 5 suprathreshold reversals), pseudo-randomly intermixed with sham trials in which no stimulation was applied. The tactile sensitivity threshold was calculated as the geometric mean of all reversal points, ranging from 0.008 g (high sensitivity) to 300 g (low sensitivity).
Data processing
Python 3.9 scripts were used to process eye-tracking data and statistics (using the statsmodels, scipy.stats, pingouin, and researchpy packages). Data pre-processing for the sound detection task and the subjective tactile sensitivity task was performed in Excel (version 2208).
Pupil size data were subtractively baseline corrected using the average of the last 50 ms of the baseline period and downsampled to 100 Hz. Negative values indicate pupil constriction and positive values indicate pupil dilation.
To minimise the effects of slower frequency trends/drifts in pupil size, the first derivative of pupil size was calculated, indicating the velocity of pupil size changes. Note that the first derivative contains broadly similar information compared to relative pupil size changes (Strauch et al., 2021). The pupil size derivative data were filtered using a low pass Butterworth filter, with a critical frequency of 18 Hz and an order of 3 to remove high frequency noise.