Temporal cascade of frontal, motor and muscle processes underlying human action-stopping

Abstract

15Action-stopping is a canonical executive function thought to involve top-down control 16 over the motor system. Here we aimed to validate this stopping system using high temporal 17 resolution methods in humans. We show that, following the requirement to stop, there was an 18 increase of right frontal beta (~13 to 30 Hz) at ~120 ms, likely a proxy of right inferior frontal 19 gyrus; then, at 140 ms, there was a broad skeletomotor suppression, likely reflecting the impact 20 of the subthalamic nucleus on basal ganglia output; then, at ~160 ms, suppression was detected 21 in the muscle, and, finally, the behavioral time of stopping was ~220 ms. This temporal cascade 22 confirms a detailed model of action-stopping, and partitions it into subprocesses that are isolable 23 to different nodes and are more precise than the behavioral speed of stopping. Variation in these 24 subprocesses, including at the single-trial level, could better explain individual differences in 25 impulse control. 26 27 28The ability to control one's actions and thoughts is important for our daily lives; for 29 example: changing gait when there is an obstacle in the path 1 , resisting the temptation to eat 30 when on a diet 2 , overcoming the tendency to say something hurtful 3 . While many processes 31 contribute to such forms of control, one important process is response inhibition -the prefrontal 32 (top-down) stopping of initiated response tendencies 4 . In the laboratory, response inhibition is 33 often studied with the stop-signal task 5 . On each trial, the participant initiates a motor response, 34 and then, when a subsequent Stop signal occurs, tries to stop. From the behavioral data one can 35 estimate a latent variable; the speed of stopping known as Stop Signal Reaction Time (SSRT), 36 which is typically 200-250 ms in healthy adults 5 . SSRT has been useful in neuropsychiatry 37where it is often longer for patients vs. controls [6][7][8][9][10][11] . The task has also provided a rich test-bed, 38 3 across species, for mapping out a putative neural architecture of prefrontal-basal-ganglia-regions 39 for rapidly suppressing motor output areas 6,12,13 . Given this rich literature, this task is one of the 40 few paradigms included in the longitudinal Adolescent Brain Cognitive Development study 14 of 41 10,000 adolescents over 10 years. 42Against this background, a puzzle is that the relation between SSRT and 'real-world' 43 self-reported impulsivity is often weak 15-20 . One explanation is that SSRT may not accurately 44 index the brain's true stopping speed. Indeed, recent mathematical modelling of behavior during 45 the stop-signal task suggests that standard calculations of SSRT may overestimate the brain's 46 stopping speed by ~100 ms 15 [also see 21 ]. Further, in a recent study 22 , electromyographic (EMG) 47 recordings revealed an initial increase in EMG activity in response to the Go cue, followed by a 48 sudden decline at ~150 ms after the Stop signal. This decline in EMG could be because of the 49 Stop process 'kicking in'...

Temporally-precise disruption of prefrontal cortex informed by the timing of beta bursts impairs human action-stopping

“…We based our timing for stimulation on recent findings about beta oscillations from putative rIFC. Whereas the above-cited studies refer to average beta band power, we have also recently shown how this is underpinned by transient beta bursts (Jana et al, 2019). Here, we reasoned that the integrity of rIFC at the time of these bursts is critical to the successful implementation of the stop process, and that disrupting it at this time would therefore impair stopping.…”

“…Experiment 1 (EEG). Fifteen participants (9 females; age 21±0.4 years; all right-handed) were recruited as part of a separate study (Jana et al, 2019). Here we present data based on a new set of analyses.…”

“…Following an initial block of practice trials, participants in each experiment completed the Stop Signal Task as follows: (Amassian et al, 1989;Day et al, 1989;Inghilleri et al, 1993;Säisänen et al, 2008;Cash et al, 2017), we estimated that the optimal time to deliver a TMS pulse should be slightly earlier than BurstTime (~125 ms) such that it caught the rise of the burst (burst duration is ~200 ms (Jana et al, 2019). We therefore decided to deliver TMS 80 ms after the stop signal ( Figure 1e).…”

“…The measure relies on the fact that even trials in which participants successfully stop a button-press sometimes contain small bursts of EMG presumably reflecting voluntary commands to move. Importantly, however, these EMG bursts are cut short ~160 ms after the stop signal (Raud and Huster, 2017;Jana et al, 2019), and we proposed that this reflected the timing of the implementation of the stop process at the muscle. The idea was supported by evidence that the time of EMG cancellation (CancelTime) coincides temporally with a widespread, motor system suppression (Jana et al, 2019; see also Coxon et al, 2006;Badry et al, 2009;Wessel et al, 2013), perhaps mediated via the subthalamic nucleus (Wessel et al, 2016), which suggests an active withdrawal/inhibition of motor drive.…”

“…To evaluate the behavioral impact of rIFC disruption we used our recently-developed measure of stopping latency derived from electromyographic (EMG) recordings during the Stop Signal Task (Jana et al, 2019). The measure relies on the fact that even trials in which participants successfully stop a button-press sometimes contain small bursts of EMG presumably reflecting voluntary commands to move.…”