Healthy adults favor stable left/right hand choices over performance at an unconstrained reach-to-grasp task

Abstract

Reach-to-grasp actions are fundamental to the daily activities of human life, but few methods exist to assess individuals' reaching and grasping actions in unconstrained environments. The Block Building Task (BBT) provides an opportunity to directly observe and quantify these actions, including left/right hand choices. Here we sought to investigate the motor and non-motor causes of left/right hand choices, and optimize the design of the BBT, by manipulating motor and non-motor difficulty in the BBT's unconstrained reach-to-grasp task. We hypothesized that greater motor and non-motor (e.g. cognitive/perceptual) difficulty would drive increased usage of the dominant hand. To test this hypothesis, we modulated block size (large vs. small) to influence motor difficulty, and model complexity (10 vs. 5 blocks per model) to influence non-motor difficulty, in healthy adults (n = 57). Our data revealed that increased motor and non-motor difficulty led to lower task performance (slower task speed), but participants only increased use of their dominant hand only under the most difficult combination of conditions: in other words, participants allowed their performance to degrade before changing hand choices, even though participants were instructed only to optimize performance. These results demonstrate that hand choices during reach-to grasp actions are more stable than motor performance in healthy right-handed adults, but tasks with multifaceted difficulties can drive individuals to rely more on their dominant hand.

Keywords: (4 to6): hand choice; Block-building task; Reaching and grasping; Task difficulty.

Fig. 1:

Age distribution of participants.

Fig 2:

Block Building Task. Figure reproduced with permission from Philip et al (2022). Participants build 4 models (bottom center) from 40 Lego bricks. Participants are instructed to build quickly and accurately, but receive no instructions about hand use.

Fig 3:

Example models, illustrating 2 x 2 design of motor and non-motor difficulty. Motor difficulty was modulated via Block Size (Large vs. Small), and non-motor difficulty Model Complexity (10 vs 5 blocks per model).

Fig 4:

Effects of Block Size and Model Complexity on hand usage and task speed. A: Hand usage showed no main effects, but an interaction effect: DH usage increased only under the combination of small blocks and high complexity. B: Task speed showed main effects of Block Size and Model Complexity, with an interaction effect such that Block Size only influenced speed under high complexity.

Fig 5:

No significant correlations between precision drawing task and BBT. For each hand (DH and NDH), and all four BBT conditions (rows), none of the four precision drawing variables correlated significantly with (A) hand usage or (B) task speed.

Fig 6:

Hand usage and task speed were only weakly correlated (r ≤ 0.37), for all variants of the BBT. One outlier in the large blocks, 10/model condition, not shown (Task speed = 1.11, Hand usage = 0.6); this outlier is also not shown in Figures 4B.