Decomposing Decision Components in the Stop-signal Task: A Model-based Approach to Individual Differences in Inhibitory Control

Abstract

The Stop-signal task (SST), in which participants must inhibit prepotent responses, has been used to identify neural systems that vary with individual differences in inhibitory control. To explore how these differences relate to other aspects of decision-making, a drift diffusion model of simple decisions was fitted to SST data from Go trials to extract measures of caution, motor execution time, and stimulus processing speed for each of 123 participants. These values were used to probe fMRI data to explore individual differences in neural activation. Faster processing of the Go stimulus correlated with greater activation in the right frontal pole for both Go and Stop trials. On Stop trials stimulus processing speed also correlated with regions implicated in inhibitory control, including the right inferior frontal gyrus, medial frontal gyrus, and basal ganglia. Individual differences in motor execution time correlated with activation of the right parietal cortex. These findings suggest a robust relationship between the speed of stimulus processing and inhibitory processing at the neural level. This model-based approach provides novel insight into the interrelationships among decision components involved in inhibitory control, and raises interesting questions about strategic adjustments in performance and inhibitory deficits associated with psychopathology.

Enhancing frontal top-down inhibitory control with Go/NoGo training

“…In line with previous reports, we assume that the participants managed to decrease their RT to Go trials because they became faster at inhibiting their responses when unexpected NoGo stimuli were presented (Manuel et al 2010;Verbruggen et al 2012;Manuel et al 2013;White et al 2014). According to this hypothesis, IC proficiency was achieved via a speeding up of inhibition processes, but manifested as decreased RTs to Go trials with no change in false alarms rate.…”

“…A few studies, however, did not find such a decrease (e.g., Cohen and Poldrack, 2008), or only in some conditions (Ditye et al 2012). These patterns of behavioral improvements have been hypothesized to follow from improvements in the speed of inhibition processes (White et al 2014;Chavan et al 2015).…”

The Right Superior Frontal Gyrus and Individual Variation in Proactive Control of Impulsive Response

“…The data were highpass filtered (1/128 Hz cutoff) to remove low-frequency signal drifts. In the first-level analysis, a contrast ϩ1 and Ϫ1 on the parametric modulator p(Stop) of GS trials each examined how positive and negative deviations from the average BOLD amplitude are modulated by trial-by-trial estimate of the likelihood of a stop signal (Wilson et al, 2009;St Jacques et al, 2011). That is, the contrasts identified voxels each with activation increasing and decreasing to p(Stop).…”

“…In the realm of cognitive motor control, for instance, urgency as a dimensional index of impulsivity trait is associated with prolonged SSRT in the SST and negatively correlated with activation of the right inferior frontal cortex and anterior insula during stop versus go trials (Wilbertz et al, 2014). Our earlier work showed that Barratt impulsivity is associated with decreased activation and connectivity in the right middle frontal cortex and anterior insula during stop versus go trials, but is only marginally correlated with the SSRT (Farr et al, 2012).…”

Decision-Making Style in Leaders: Uncovering Cognitive Motivation Using Signature Movement Patterns

“…Given this prominent attention to utilizing new methods that elicit, rather than inhibit, individual differences (see Connors et al, 2013), it is perhaps not surprising that we see an accumulation of robust evidence supporting the variability of decision-making strategies (e.g., Mishra, 2014;White et al, 2014), including more precision in identifying specific stages in movement cognitive processing that best reveal decision-making style.…”