Mild acute stress improves response speed without impairing accuracy or interference control in two selective attention tasks: Implications for theories of stress and cognition

Abstract

Acute stress is generally thought to impair performance on tasks thought to rely on selective attention. This effect has been well established for moderate to severe stressors, but no study has examined how a mild stressor-the most common type of stressor-influences selective attention. In addition, no study to date has examined how stress influences the component processes involved in overall selective attention task performance, such as controlled attention, automatic attentional activation, decision-making, and motor abilities. To address these issues, we randomly assigned 107 participants to a mild acute stress or control condition. As expected, the mild acute stress condition showed a small but significant increase in cortisol relative to the control condition. Following the stressor, we assessed attention with two separate flanker tasks. One of these tasks was optimized to investigate component attentional processes using computational cognitive modeling, whereas the other task employed mouse-tracking to illustrate how response conflict unfolded over time. The results for both tasks showed that mild acute stress decreased response time (i.e., increased response speed) without influencing accuracy or interference control. Further, computational modeling and mouse-tracking analyses indicated that these effects were due to faster motor action execution time for chosen actions. Intriguingly, however, cortisol responses were unrelated to any of the observed effects of mild stress. These results have implications for theories of stress and cognition, and highlight the importance of considering motor processes in understanding the effects of stress on cognitive task performance.

Keywords: Acute stress; Attention; Motor control; Reaction time; Response speed; Stress severity.

Figure 1.

Graphical illustration of the study procedure. Post-manipulation and after saliva collection, participants completed two separate implementations of the Flanker task: the classic flanker, wherein only a single behavioral response was assessed for each trial, followed by the MouseTracker flanker, wherein mouse trajectories in responses were assessed.

Figure 2.

Response time by trial by condition. Participants in the stress condition responded faster than participants in the control condition at the beginning of the task, but the groups converged to statistical equivalence by the end of the task. Bars for each trial represent mean ± SE for each condition on each trial. Lines are loess smooths fit to each condition’s trial data.

Figure 3.

Model fits for the average diffusion model for conflict (DMC) to the Vincent average cumulative distribution function (CDF) and conditional accuracy function (CAF). The DMC was an excellent fit to the data.

Figure 4.

Effects of the stress manipulation on nondecision time (i.e., selected motor action execution time) as fit by the DMC. Participants in the stress condition showed faster nondecision times, indicating a faster execution of chosen motor actions. No other model parameter differed between groups.*p < .05.

Figure 5.

Significant group differences from MouseTracker analyses. Although there were no differences in indices of response conflict (e.g., area under the curve) or in the time taken to begin moving the mouse, participants in the stress condition showed shorter response times to the entire trial and a faster time to maximum deviation than participants in the control condition. *p < .05, **p < .01.