Suppressing a pending action is an essential ability when someone must cope with an unpredictable situation. To investigate the response inhibition, a wide-used experimental paradigm is the stop-signal paradigm. In the above-mentioned paradigm, the main task is a choice reaction time task, where subjects are requested responding with a movement to a specific stimulus (go stimulus; go trials). Occasionally, the go stimulus is followed by a second stimulus (stop signal), which instructs the subject to withhold the response (stop trials). The time needed to react to the stop signal could be computed and is known as stop signal reaction time (SSRT). Although difficulties arise as successfully cancelled stop signal trials don't produce any observable behavior, SSRT can be still estimated through the premise of the race model. Currently very few studies approached an empirically trial-by-trial estimation of SSRT, while recent works succeeded in obtaining trial by trial SSRT estimates that are EMG-based. Even if these methods provide consistent empirical measures of the trial-by-trial SSRT, measures obtained with single-trial EMG are noisy, requiring complex algorithms to detect EMG burst onset or offset and to separate signal from noise. In addition, an experimental setup is required, that is designed to force the participant to perform standardized movements across the different trials.
Starting from this background, in this project we propose a complementary method for measuring the SSRT at the single trial level, based on the recording of the perturbation of the force applied on a force sensing resistor that can overcome the limitations of the EMG-based recording approach. Indeed, adopting a method with an easier experimental setup, could help especially in the studies that investigate disorders in which deficits in response inhibition occur, like attention deficit hyperactivity disorder, obsessive-compulsive disorder, substance abuse disorders and Parkinson's disease.
The innovative measure of SSRT, if it could be obtained, would be valuable in different settings. First, as available at the single trial level, it could serve as a regressor in functional imaging studies to help differentiate whether there are multiple types of movement cancellation (see Verbruggen and Logan 2008 for review). Second, it would be valuable in clinical settings, where an increased variability in SSRT is one of the indicators of dysfunction (Schachar and Logan 1990). Third, it would be useful for neurophysiological studies in studying inhibition as activity from a candidate neuron would necessarily have to precede the within-trial measure by a consistent interval to be involved in movement cancellation.
Furthermore, adopting a method that would result in a easier experimental setup, both for the researchers and the subjects, could help especially in the studies that investigate disorders in which deficits in response inhibition occur, like attention deficit hyperactivity disorder (ADHD) (Schachar et al., 1990; Oosterlaan et al., 1998; Nigg, 2001), obsessive-compulsive disorder (OCD) (Monterosso et al., 2005; Chamberlain et al., 2006; Menzies et al., 2007; Penades et al., 2007), and substance abuse disorders (Nigg et al., 2006;), together with Parkinson's disease.
Finally, we are convinced, as stated in the introduction, that a trial-by-trial method could be much more accurate for calculating SSRT, as it takes into account the variability that occur between trials. This, together with the previous expected results, could help us to progress in the field of research on inhibition of the movement, trying to shed light on different controversies currently present.