Investigates neural mechanisms of real-time error correction during force control using EEG.
Effective motor control depends on the ability to monitor performance and make continuous corrections. While many studies focus on discrete errors, everyday actions often require ongoing feedback-based adjustments. Here, we used an isometric force control task with EEG to investigate the neural dynamics supporting real-time error correction. Participants (13 females, 10 males) maintained a constant grip force with or without continuous visual feedback. With feedback, behavior showed ∼6 Hz rhythmic fluctuations, consistent with active correction. These fluctuations were statistically linked to EEG activity across theta, beta, and alpha bands—oscillations linked to performance monitoring, updating, and attentional control. Without feedback, performance decayed linearly, and the corresponding neural signatures were reduced. These findings suggest that continuous sensory feedback engages a dynamic feedback loop involving distinct neural processes that support adaptive behavior. Our results highlight the importance of oscillatory activity in tracking and correcting moment-to-moment fluctuations in force, offering insight into the neural basis of feedback-loop force control. Significant Statement Most research on error correction has focused on discrete actions, yet everyday behaviors require continuous, fine-grained adjustments. In this study, we show that when people use visual feedback to maintain a stable force output, their behavior fluctuates rhythmically around 6 Hz, a signature mirrored in brain oscillations across theta, beta, and alpha bands. These patterns reflect a temporal cascade of neural processes that monitor performance and initiate correction. In the absence of visual feedback, performance decays. Our findings reveal how continuous sensory feedback drives a dynamic neural feedback loop that supports real-time motor control. This work advances our understanding of how the brain sustains goal-directed action and highlights the functional role of oscillations in guiding adaptive behavior during continuous tasks.
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Menghi et al. (2026) studied this question.
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