The Medical Research Ethics Committee at St. Vincent's University Hospital, Dublin gave approval for the recruitment of patients with cervical dystonia, their siblings (unaffected by dystonia), and healthy controls, to participate in the protocol described below.

1. Hardware & Software Solutions

Note: Two hardware options have been developed to display visual stimuli with precise inter-stimulus intervals. Both were designed and built in-house at the Trinity Centre for Bioengineering, Trinity College Dublin, and have been previously described^5,16. Those wishing to replicate the exact hardware solutions used herein may request same by contacting the Trinity Centre for Bioengineering directly. Alternatively, a full set of instructions including 3D printing files for the headset, instructions for the accompanying Arduino microcontroller, etc. can be downloaded from http://www.dystoniaresearch.ie/temporal-discrimination-threshold/. The stimuli presented in the table top approach may be generated using custom programs in Presentation (e.g., Neurobehavioural Systems), installed on a desktop computer and programmed to control the light-emitting diodes (LED) via the parallel port of the computer. Alternatively, as described below, the table top LEDs may be controlled via an Arduino microcontroller. Both the Presentation code and Arduino files are also available to download from the above link.

1. TDT hardware: Table-Top Method
   1. Mark an 'X', as a fixation point, on a black mat or sheet placed on the table in front of the participant.
   2. Ask the participant to position themselves so that they are sitting directly in front of the fixation point.
   3. Place the yellow light-emitting diode (LED) pairs (5 mm diameter, 90 cd/m² luminance), encased in a box, on the table in front of the participant.
   4. Orient the box such that the LEDs are vertically aligned and positioned 7 ° from the subject's center point on the left and right side, as needed.
   5. Conduct this experiment in a darkened room. A small amount of background luminance may be required to enable the operator to see enough to run the experiment.
   6. Instruct the participant to focus on the fixation point at all times and not to look directly at the flashing LEDs.
   7. Connect the microcontroller to the LED box and follow the on-screen instructions displayed on the liquid crystal display of the microcontroller box, e.g., select presentation method: 'random' or 'staircase', and select mode: 'left top first', etc.
   8. Ask the participant to respond "same" or "different" following presentation of each stimulus pair, depending on whether they perceive the stimuli to be synchronous or asynchronous.
   9. Inform the participant when each trial is about to commence, by vocalizing the on-screen countdown from 5 – 0 s.

Figure 1: (a) Schematic of the design of the headset. A pair of yellow LEDs (5 mm diameter),and the red fixation LED (3 mm diameter), are placed on the left and right side of the participant via a head-mounted unit and made visible by way of reflection in the mirrors in front of the user. (b) Schematic 3D model of the headset. The headset was developed from laser-sintered nylon plastic, weighs 0.70 kg, has a low transparency index and is black in color to minimize light penetrance. (a and b) are reproduced, with slight modification, from Butler et al.¹⁶ with permission from IOP Publishing. (c) The LED stimulus box for table-top presentation.

2. TDT Hardware: Portable TDT Headset
   1. Conduct the experiment in any suitable location.
   2. Connect the microcontroller to the headset and follow the on-screen instructions displayed on the liquid crystal display of the microcontroller box, e.g., select presentation method: 'random' or 'staircase', and mode: 'left top first', etc.
   3. Direct the participant to position themselves with their elbows on a table in front of them. Then, holding the device in their hands, direct them to gently press their face into the rubber sealant surrounding the eyepiece, thereby sealing out ambient light.
   4. Instruct the participant to focus on the red fixation LED at all times and not to look directly at the flashing LEDs.
   5. Ask the participant to respond "same" or "different" following presentation of each stimulus pair, depending on whether they perceive the stimuli to be synchronous or asynchronous.
   6. Inform the participant when each trial is about to commence, by vocalizing the on-screen countdown from 5 – 0 s.

2. Stimulus Presentation

Note: Two approaches to stimulus presentation have been employed.

1. Staircase method
   1. Select 'staircase' presentation; stimuli are presented every 5 s with the inter-stimulus interval starting at 0 and becoming progressively more asynchronous (increasing by 5 ms) each time.
   2. Select any of the four presentation modalities: (i) left top LED first (ii) left bottom LED first (iii) right top LED first, or (iv) right bottom LED first.
   3. Repeat step 2.1.2 so that each modality is run twice, resulting in a total of eight runs.
   4. Terminate the trial when a participant responds "different" for three consecutive pairs of stimuli.
2. Random Presentation Method
   1. Select 'Random' presentation; stimuli pairs are presented every 5 s. The inter-stimulus interval varies, in a randomized fashion, from 0-100 ms.
   2. Select any of the four presentation modalities: (i) left top LED first (ii) left bottom LED first (iii) right top LED first, or (iv) right bottom LED first.
   3. Repeat step 2.2.2 so that each modality is run twice, resulting in a total of eight runs.
      Note: Each run is the same length and will complete automatically.

3. Data Analysis

1. Single TDT value
   1. Using the data from the staircase method, highlight the first of the final three "different" responses for each of the eight runs. These are the threshold values for each run.
   2. Calculate the temporal discrimination threshold (TDT) for each participant by taking the median of the thresholds from each of their eight runs; resulting in a single TDT value (in milliseconds) per individual.
   3. Calculate the Z_score for each participant. Define the Z_score as the difference between the participant's TDT, and the mean TDT from an age-matched control population (, divided by the standard deviation of the TDT values for that control population .
      
   4. Determine if the individual has a normal or abnormal TDT. A Z_score ≥ 2.5 is deemed to reflect an abnormal TDT.
2. Distribution Analysis
   1. Using the data from the staircase method, encode the response data such that '0' corresponds to "same" and '1' corresponds to "different", Table 1.
   2. Download a free MATLAB.exe to perform the distribution analysis described below from http://www.dystoniaresearch.ie/temporal-discrimination-threshold/. See Butler et al.¹⁶ for a full description of this method. Alternatively, proceed as described below.
   3. Pad out the data to ensure all runs are the same length as the longest run. This is done by assuming all subsequent responses, following termination of a run, are "different", Table 1(b).
   4. Average responses across trials for each participant, Table 1(c). This can be plotted as a function of stimulus asynchrony.
   5. Fit this averaged or representative data with a cumulative Gaussian function. The mean of this distribution represents the point at which participants are equally likely to respond “same” or “different”. This point is referred to as the ‘point of subjective equality’ (PSE). The standard deviation of the Gaussian distribution, also referred to as the ‘just noticeable difference’ (JND), indicates how sensitive participants are to changes in temporal asynchrony around their mean.
   6. Extend the analysis by submitting the data to a non-parametric bootstrapping procedure in order to estimate the 95% confidence intervals for the TDT and the PSE and JND of the psychometric, cumulative Gaussian function. To do this, generate new representative data sets by random sampling with replacement from the original responses, Table 1(b), for each time step. Calculate the TDT and fit a new psychometric function for each representative data set¹⁶.
   7. Calculate the goodness of fit, or deviance (D), for each participant using the log-likelihood ratio,^16,17
      
      where K is the number of time points, n_i is the number of repetitions at that time point, generally eight repetitions (four right and four left), y_i is the observed proportion of asynchronous responses, p_i is the proportion of asynchronous responses predicted by the fitted curve. A deviance value of 0 means a perfect fit.
   8. Plot the results.
      Note: Data from the random presentation approach can be analyzed to determine the single or distributed TDT as described in section 3 above for data arising from the staircase presentation method. However, due to the random presentation order of inter-stimuli intervals, these data must first be ordered (from smallest to largest inter-stimulus interval), prior to commencing the analysis described above, Table 2. In addition, it is not necessary to pad the data following random presentation as, by default, all runs are of equal length.