Motor Preparation Disrupts Proactive Control in the Stop Signal Task

Wuyi Wang,Simon Zhornitsky,Jaime S Ide,Angela J Yu,Sien Hu,Sheng Zhang,Chiang-Shan R Li

doi:10.3389/fnhum.2018.00151

Abstract

In a study of the stop signal task (SST) we employed Bayesian modeling to compute the estimated likelihood of stop signal or P(Stop) trial by trial and identified regional processes of conflict anticipation and response slowing. A higher P(Stop) is associated with prolonged go trial reaction time (goRT)—a form of sequential effect—and reflects proactive control of motor response. However, some individuals do not demonstrate a sequential effect despite similar go and stop success (SS) rates. We posited that motor preparation may disrupt proactive control more in certain individuals than others. Specifically, the time interval between trial and go signal onset—the fore-period (FP)—varies across trials and a longer FP is associated with a higher level of motor preparation and shorter goRT. Greater motor preparatory activities may disrupt proactive control. To test this hypothesis, we compared brain activations and Granger causal connectivities of 81 adults who demonstrated a sequential effect (SEQ) and 35 who did not (nSEQ). SEQ and nSEQ did not differ in regional activations to conflict anticipation, motor preparation, goRT slowing or goRT speeding. In contrast, SEQ and nSEQ demonstrated different patterns of Granger causal connectivities. P(Stop) and FP activations shared reciprocal influence in SEQ but FP activities Granger caused P(Stop) activities unidirectionally in nSEQ, and FP activities Granger caused goRT speeding activities in nSEQ but not SEQ. These findings support the hypothesis that motor preparation disrupts proactive control in nSEQ and provide direct neural evidence for interactive go and stop processes.

Highlights

We combined computational modeling and fMRI of a stop signal task (SST) to characterize the neural processes linking conflict anticipation or Bayesian estimate of the likelihood of an upcoming stop signal—P(Stop)—and go trial reaction time
Individuals who demonstrated a sequential effect (SEQ) and those who did not were indistinguishable in the magnitude of FP effect. Both showed a significant negative correlation between FP and go trial RT and the magnitude of correlation did not differ between the two groups
The two groups did not differ in regional activations to P(Stop), FP, go trial reaction time (goRT) slowing or goRT speeding, even when the results of two-sample t tests were examined at a very liberal threshold, suggesting that P(Stop) is represented in both SEQ and nSEQ, with shared regional activities for proactive control

Summary

Introduction

We combined computational modeling and fMRI of a stop signal task (SST) to characterize the neural processes linking conflict anticipation or Bayesian estimate of the likelihood of an upcoming stop signal—P(Stop)—and go trial reaction time (goRT; Ide et al, 2013; Hu et al, 2015a). A higher P(Stop) is associated with prolonged goRT, a behavioral finding related to ‘‘sequential effect’’ (Yu and Cohen, 2008). The anterior pre-supplementary motor area (preSMA) along with the inferior parietal cortex (IPC) respond to higher P(Stop) and the posterior preSMA and bilateral anterior insula (AI) respond to prolonged goRT. Granger causality analyses showed directional influence of anterior preSMA on posterior preSMA and bilateral insula, suggesting proactive control of motor response (Hu et al, 2015a). A sequential effect reflects trial by trial monitoring and learning to update the current expectation of the stop signal

Methods

Results

Conclusion