In everyday life, we frequently have to decide which hand to use for a certain action. It has been suggested that for this decision the brain calculates expected costs based on action values, such as expected biomechanical costs, expected success rate, handedness, and skillfulness. Although these conclusions were based on experiments in stationary subjects, we often act while the body is in motion. We investigated how hand choice is affected by passive body motion, which directly affects the biomechanical costs of the arm movement due to its inertia. With the use of a linear motion platform, 12 right-handed subjects were sinusoidally translated (0.625 and 0.5 Hz). At 8 possible motion phases, they had to reach, using either their left or right hand, to a target presented at 1 of 11 possible locations. We predicted hand choice by calculating the expected biomechanical costs under different assumptions about the future acceleration involved in these computations, being the forthcoming acceleration during the reach, the instantaneous acceleration at target onset, or zero acceleration as if the body were stationary. Although hand choice was generally biased to use of the dominant hand, it also modulated sinusoidally with the motion, with the amplitude of the bias depending on the motion's peak acceleration. The phase of hand choice modulation was consistent with the cost model that took the instantaneous acceleration signal at target onset. This suggests that the brain relies on the bottom-up acceleration signals, and not on predictions about future accelerations, when deciding on hand choice during passive whole body motion. Decisions of hand choice are a fundamental aspect of human behavior. Whereas these decisions are typically studied in stationary subjects, this study examines hand choice while subjects are in motion. We show that accelerations of the body, which differentially modulate the biomechanical costs of left and right hand movements, are also taken into account when deciding which hand to use for a reach, possibly based on bottom-up processing of the otolith signal.

For the brain to decide on a reaching movement, it needs to select which hand to use. A number of body-centered factors affect this decision, such as the anticipated movement costs of each arm, recent choice success, handedness, and task demands. While the position of each hand relative to the target is also known to be an important spatial factor, it is unclear which reference frames coordinate the spatial aspects in the decisions of hand choice. Here we tested the role of gaze- and head-centered reference frames in a hand selection task. With their head and gaze oriented in different directions, we measured hand choice of 19 right-handed subjects instructed to make unimanual reaching movements to targets at various directions relative to their body. Using an adaptive procedure, we determined the target angle that led to equiprobable right/left hand choices. When gaze remained fixed relative to the body this balanced target angle shifted systematically with head orientation, and when head orientation remained fixed this choice measure shifted with gaze. These results suggest that a mixture of head- and gaze-centered reference frames is involved in the spatially guided decisions of hand choice, perhaps to flexibly bind this process to the mechanisms of target selection. NEW & NOTEWORTHY Decisions of target and hand choice are fundamental aspects of human reaching movements. While the reference frames involved in target choice have been identified, it is unclear which reference frames are involved in hand selection. We tested the role of gaze- and head-centered reference frames in a hand selection task. Findings emphasize the role of both spatial reference frames in the decisions of hand choice, in addition to known body-centered computations such anticipated movement costs and handedness.

In daily life, we frequently reach toward objects while our body is in motion. We have recently shown that body accelerations influence the decision of which hand to use for the reach, possibly by modulating the body-centered computations of the expected reach costs. However, head orientation relative to the body was not manipulated, and hence it remains unclear whether vestibular signals contribute in their head-based sensory frame or in a transformed body-centered reference frame to these cost calculations. To test this, subjects performed a preferential reaching task to targets at various directions while they were sinusoidally translated along the lateral body axis, with their head either aligned with the body (straight ahead) or rotated 18° to the left. As a measure of hand preference, we determined the target direction that resulted in equiprobable right/left-hand choices. Results show that head orientation affects this balanced target angle when the body is stationary but does not further modulate hand preference when the body is in motion. Furthermore, reaction and movement times were larger for reaches to the balanced target angle, resembling a competitive selection process, and were modulated by head orientation when the body was stationary. During body translation, reaction and movement times depended on the phase of the motion, but this phase-dependent modulation had no interaction with head orientation. We conclude that the brain transforms vestibular signals to body-centered coordinates at the early stage of reach planning, when the decision of hand choice is computed. NEW & NOTEWORTHY The brain takes inertial acceleration into account in computing the anticipated biomechanical costs that guide hand selection during whole body motion. Whereas these costs are defined in a body-centered, muscle-based reference frame, the otoliths detect the inertial acceleration in head-centered coordinates. By systematically manipulating head position relative to the body, we show that the brain transforms otolith signals into body-centered coordinates at an early stage of reach planning, i.e., before the decision of hand choice is computed.

Visually guided finger movements include online feedback of current effector position to guide target approach. This visual feedback may be scaled or otherwise distorted by unpredictable perturbations. Although adjustments to visual feedback scaling have been studied before, the underlying brain activation differences between upscaling (visual feedback larger than real movement) and downscaling (feedback smaller than real movement) are currently unknown. Brain activation differences between upscaling and downscaling might be expected because within-trial adjustments during upscaling require corrective backwards accelerations, whereas correcting for downscaling requires forward accelerations. In this behavioural and fMRI study we investigated adjustments during up- and downscaling in a target-directed finger flexion-extension task with real-time visual feedback. We found that subjects made longer and more complete within-trial corrections for downscaling perturbations than for upscaling perturbations. The finger task activated primary motor (M1) and somatosensory (S1) areas, premotor and parietal regions, basal ganglia, and cerebellum. General scaling effects were seen in the right pre-supplementary motor area, dorsal anterior cingulate cortex, inferior parietal lobule, and dorsolateral prefrontal cortex. Stronger activations for down- than for upscaling were observed in M1, supplementary motor area (SMA), S1 and anterior cingulate cortex. We argue that these activation differences may reflect differing online correction for upscaling vs. downscaling during finger flexion-extension.