Current advances and pressing problems in studies of stopping

Abstract

The stop-signal task probes agents' ability to inhibit responding. A well-known race model affords estimation of the duration of the inhibition process. This powerful approach has yielded numerous insights into the neural circuitry underlying response control, the specificity of inhibition across effectors and response strategies, and executive processes such as performance monitoring. Translational research between human and non-human primates has been particularly useful in this venture. Continued progress with the stop-signal paradigm is contingent upon appreciating the dynamics of entire cortical and subcortical neural circuits and obtaining neurophysiological data from each node in the circuit. Progress can also be anticipated on extensions of the race model to account for selective stopping; we expect this will entail embedding behavioral inhibition in the broader context of executive control.

Figure 1

The stop-signal task measures response inhibition. Two trial types are randomly interleaved. "No stop signal", "No signal, or simply "Go" trials do not contain stop signals (top). A GO signal instructs subjects to initiate a response. The times between GO signals and responses are the subject's reaction times (RTs). "Stop signal", "Signal", or "Stop" trials are randomly interleaved (middle and bottom). With some delay after the GO signal (stop-signal delay or SSD), a stop signal is presented. This cues subjects to cancel impending responses, which they are able to do with varying success. Short SSDs increase the probability of cancelation (middle) while long SSDs decrease the probability of cancelation (bottom). If responses are elicited in spite of the stop signal, trials are classified as "Signal respond", "Noncanceled", or "Stop failure" trials. If no response is elicited, trials are classified as "Signal inhibit", "Canceled", or "Stop success" trials. Stop-signal reaction time (SSRT) measures the time necessary for the covert inhibitory process to cancel responses. RTs faster than SSD plus SSRT will result in Signal respond trials, while RTs slower than the stop process will lead to Signal inhibit trials.

Figure 2

Neural and computational mechanisms of movement inhibition. (A) Normalized activity of FEF gaze-shifting (left) and gaze-holding (right) neurons. Activity on trials in which movements were produced but would have been canceled if the stop signal had been presented (thin line) are compared with activity on trials when the planned saccade was canceled because the stop signal appeared (thick line). Presentation of the stop signal is indicated by the solid vertical line. The time needed to cancel the planned movement - stop signal reaction time (SSRT) - is indicated by the dashed vertical line. When the movement was canceled, gaze-holding activity increased and gaze-shifting activity decreased abruptly immediately before SSRT. The timing of this modulation demonstrates that FEF neurons convey signals sufficient to control the initiation of the movement. (B) The interactive race model elucidates how a network of mutually inhibitory GO and STOP units (left inset) can produce behavior consistent with the Logan race model. With proper parameters, the network produces error rates (left) and RT distributions (right) that are indistinguishable from observed values. Moreover, using the same parameters, GO and STOP unit modulation (right inset) correspond quantitatively to the form of actual neural activation. Movement inhibition can be accomplished only by late, potent interruption of the GO process by the STOP process. (Adapted from [37])

Figure 3

Performance monitoring signals in and over medial frontal cortex of macaque monkeys during the stop-signal task. Schematized coronal section on top left illustrates location of intracranial recordings from SEF, ACC, and cranial surface recordings. Intracranial signals from microelectrodes were amplified and filtered to provide spikes or LFP, and cranial signal was processed as typical EEG (right panels). Solid lines plot activity on no-stop (correct) trials, and broken lines plot activity on noncanceled (error) trials. In both SEF and ACC, many neurons show increased activity following noncanceled error responses. Simultaneously, the LFP at some sites in SEF and most sites in ACC exhibit greater polarization after errors. These LFPs contribute to the greater polarization recorded on the surface, corresponding to the ERN, as indicated by the current sources calculated from the surface voltage distribution projected onto dorsal and medial surfaces of structural MRI data (lower left). Adapted from [36,78,79,84,85].