Non-parametric bootstrapping method for measuring the temporal discrimination threshold for movement disorders

Recent studies have proposed that the temporal discrimination threshold (TDT), the shortest detectable time period between two stimuli, is a possible endophenotype for adult onset idiopathic isolated focal dystonia (AOIFD). Patients with AOIFD, the third most common movement disorder, and their first-degree relatives have been shown to have abnormal visual and tactile TDTs. For this reason it is important to fully characterize each participant's data. To date the TDT has only been reported as a single value.

Here, we fit individual participant data with a cumulative Gaussian to extract the mean and standard deviation of the distribution. The mean represents the point of subjective equality (PSE), the inter-stimulus interval at which participants are equally likely to respond that two stimuli are one stimulus (synchronous) or two different stimuli (asynchronous). The standard deviation represents the just noticeable difference (JND) which is how sensitive participants are to changes in temporal asynchrony around the PSE. We extended this method by submitting the data to a non-parametric bootstrapped analysis to get 95% confidence intervals on individual participant data.

Both the JND and PSE correlate with the TDT value but are independent of each other. Hence this suggests that they represent different facets of the TDT. Furthermore, we divided groups by age and compared the TDT, PSE, and JND values. The analysis revealed a statistical difference for the PSE which was only trending for the TDT.

The analysis method will enable deeper analysis of the TDT to leverage subtle differences within and between control and patient groups, not apparent in the standard TDT measure.