Task context determines whether common or separate inhibitory signals underlie the control of eye-hand movements

A global pause generates nonselective response inhibition during selective stopping

Selective response inhibition may be required when stopping a part of a multicomponent action. A persistent response delay (stopping-interference effect) indicates nonselective response inhibition during selective stopping. This study aimed to elucidate whether nonselective response inhibition is the consequence of a global pause process during attentional capture or specific to a nonselective cancel process during selective stopping. Twenty healthy human participants performed a bimanual anticipatory response inhibition paradigm with selective stop and ignore signals. Frontocentral and sensorimotor beta-bursts were recorded with electroencephalography. Corticomotor excitability and short-interval intracortical inhibition in primary motor cortex were recorded with transcranial magnetic stimulation. Behaviorally, responses in the non-signaled hand were delayed during selective ignore and stop trials. The response delay was largest during selective stop trials and indicated that stopping-interference could not be attributed entirely to attentional capture. A stimulus-nonselective increase in frontocentral beta-bursts occurred during stop and ignore trials. Sensorimotor response inhibition was reflected in maintenance of beta-bursts and short-interval intracortical inhibition relative to disinhibition observed during go trials. Response inhibition signatures were not associated with the magnitude of stopping-interference. Therefore, nonselective response inhibition during selective stopping results primarily from a nonselective pause process but does not entirely account for the stopping-interference effect.

Eye-hand coordination during online reach corrections is task dependent

To produce accurate movements, the human motor system needs to deal with errors that can occur due to inherent noise, changes in the body, or disturbances in the environment. Here, we investigated the temporal coupling of rapid corrections of the eye and hand in response to a change in visual target location during the movement. In addition to a "classic" double-step task in which the target stepped to a new position, participants performed a set of modified double-step tasks in which the change in movement goal was indicated by the appearance of an additional target, or by a spatial or symbolic cue. We found that both the absolute correction latencies of the eye and hand and the relative eye-hand correction latencies were dependent on the visual characteristics of the target change, with increasingly longer latencies in tasks that required more visual and cognitive processing. Typically, the hand started correcting slightly earlier than the eye, especially when the target change was indicated by a symbolic cue, and in conditions where visual feedback of the hand position was provided during the reach. Our results indicate that the oculomotor and limb-motor system can be differentially influenced by processing requirements of the task and emphasize that temporal eye-hand coupling is flexible rather than rigid.NEW & NOTEWORTHY Eye movements support hand movements in many situations. Here, we used variations of a double-step task to investigate temporal coupling of corrective hand and eye movements in response to target displacements. Correction latency coupling depended on the visual and cognitive processing demands of the task. The hand started correcting before the eye, especially when the task required decoding a symbolic cue. These findings highlight the flexibility and task dependency of eye-hand coordination.

Computational Mechanisms Mediating Inhibitory Control of Coordinated Eye-Hand Movements

Significant progress has been made in understanding the computational and neural mechanisms that mediate eye and hand movements made in isolation. However, less is known about the mechanisms that control these movements when they are coordinated. Here, we outline our computational approaches using accumulation-to-threshold and race-to-threshold models to elucidate the mechanisms that initiate and inhibit these movements. We suggest that, depending on the behavioral context, the initiation and inhibition of coordinated eye-hand movements can operate in two modes-coupled and decoupled. The coupled mode operates when the task context requires a tight coupling between the effectors; a common command initiates both effectors, and a unitary inhibitory process is responsible for stopping them. Conversely, the decoupled mode operates when the task context demands weaker coupling between the effectors; separate commands initiate the eye and hand, and separate inhibitory processes are responsible for stopping them. We hypothesize that the higher-order control processes assess the behavioral context and choose the most appropriate mode. This computational mechanism can explain the heterogeneous results observed across many studies that have investigated the control of coordinated eye-hand movements and may also serve as a general framework to understand the control of complex multi-effector movements.

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

Action-stopping is a canonical executive function thought to involve top-down control over the motor system. Here we aimed to validate this stopping system using high temporal resolution methods in humans. We show that, following the requirement to stop, there was an increase of right frontal beta (~13 to 30 Hz) at ~120 ms, likely a proxy of right inferior frontal gyrus; then, at 140 ms, there was a broad skeletomotor suppression, likely reflecting the impact of the subthalamic nucleus on basal ganglia output; then, at ~160 ms, suppression was detected in the muscle, and, finally, the behavioral time of stopping was ~220 ms. This temporal cascade supports a physiological model of action-stopping, and partitions it into subprocesses that are isolable to different nodes and are more precise than the behavioral latency of stopping. Variation in these subprocesses, including at the single-trial level, could better explain individual differences in impulse control.