Midfrontal mechanisms of performance monitoring continuously adapt to incoming information during outcome anticipation

Abstract

Performance monitoring is essential for successful action execution and previous studies have suggested that frontomedial theta (FMT) activity in scalp-recorded EEG reflects need for control signaling in response to negative outcomes. However, these studies have overlooked the fact that anticipating the most probable outcome is often possible. To optimize action execution, it is necessary for the time-critical performance monitoring system to utilize continuously updated information to adjust actions in time. This study used a combination of mobile EEG and virtual reality to investigate how the performance monitoring system adapts to continuously updated information during brief phases of outcome evaluation that follow action execution. In two virtual shooting tasks, participants were either able to observe the projectile and hence anticipate the outcome or not. We found that FMT power increased in response to missing shots in both tasks, but this effect was suppressed when participants were able to anticipate the outcome. Specifically, the suppression was linearly related to the duration of the anticipatory phase. Our results suggest that the performance monitoring system dynamically integrates incoming information to evaluate the most likely outcome of an action as quickly as possible. This dynamic mode of performance monitoring provides significant advantages over idly waiting for an action outcome before getting engaged. Early and adaptive performance monitoring not only helps prevent negative outcomes but also improves overall performance. Our findings highlight the crucial role of dynamic integration of incoming information in the performance monitoring system, providing insights for real-time decision-making and action control.

Keywords: FMT; Frontomedial theta; Midfrontal theta; Performance monitoring; VR.

Fig. 1

Screenshots of the virtual environment. A: Balloon before shot. B: Green fragments after hitting the balloon. C: Red fragments after missing the balloon. The number to the right displays the number of trials remaining in the given block. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2

Time-frequency activity for the differences of miss minus hit trials per experimental condition. Time-frequency plots display dB-transformed Δpower at FCz.

Fig. 3

Regression-based ERSPs (rERSPs) for the theta-band (4 Hz–8 Hz) at channel FCz. The ERSPs are based on non dB-transformed theta power. Shaded areas reflect time windows with statistically significant effects of the corresponding regression coefficient on theta power (p < .01).