Anticipatory action planning for stepping onto competing potential targets

Postural strategy for two potential targets considering motor costs for postural stabilization and probabilistic information

When an intended action has multiple potential goals, individuals should consider multiple possibilities about future events to react successfully. Previous studies on arm reaching using a "go-before-you-know" paradigm have found that hand trajectories under multiple potential targets were spatially averaged between targets and biased based on probabilistic information about the targets. Using a target-stepping task while standing, we recently observed that a prestep posture was planned more advantageously for stepping to the target with higher motor costs for postural stabilization. The present study aimed to examine whether such a postural strategy would be selected when the probability of a potential target with higher motor costs being selected as the true target was low. Fourteen participants (mean age 23.2 ± 4.6 yr) initiated stepping movements knowing only the probability of two potential targets and took a step onto a target revealed after step initiation. The results showed that the participants prepared their mediolateral posture state more advantageously to take a step onto the target with higher costs, even when it was selected with a lower probability. Prestep postures were also affected by the probability information, although the effects were small. Our simulations demonstrated that the postural strategy prioritizing motor costs was mechanically beneficial for affording time to take a step toward the true target while maintaining an upright posture. These findings suggest that, when maintaining postural stability is critical, the central nervous system considers the motor costs for postural stabilization in addition to probability information under multiple potential targets.NEW & NOTEWORTHY Recent studies using a target-reaching task under a "go-before-you-know" paradigm have shown that individuals use probabilistic information when planning a motor strategy under multiple potential goals. We introduced this paradigm to a target-stepping task performed while standing and found that motor costs for postural stabilization were considered for initial posture planning under uneven probabilistic targets. These findings indicated that the central nervous system considers motor costs when planning postural strategies to minimize instability.

Motor decision-making under uncertainty and time pressure

Purposeful movement often requires selection of a particular action from a range of alternatives, but how does the brain represent potential actions so that they can be compared for selection, and how are motor commands generated if movement is initiated before the final goal is identified? According to one hypothesis, the brain averages partially prepared motor plans to generate movement when there is goal uncertainty. This is consistent with the idea that motor decision-making unfolds through competition between internal representations of alternative actions. An alternative hypothesis holds that only one movement, which is optimized for task performance, is prepared for execution at any time. Under this conception, decisions about the best motor goal given current information are completed upstream from neural circuits that perform motor planning. To distinguish between these hypotheses, we modified an experiment (Alhussein L, Smith MA. eLife 10: e67019, 2021) in which participants had to start reaching toward targets associated with opposite curl force fields before knowing the correct target to reach. Crucially, we forced the participants to initiate movement immediately after target presentation (i.e., mean reaction times ∼250 ms) so that they had limited opportunity to deliberate between the available alternatives. We found that the reaching dynamics reflected only those learned for the selected reach direction, rather than a combination of those for the alternative targets presented, irrespective of the time available to initiate movement. The data are consistent with the conclusion that reaching dynamics were specified downstream of action selection under the target uncertainty conditions of this study.NEW & NOTEWORTHY Here we found no evidence of "motor averaging" of reach dynamics for multiple potential actions when people had to respond as quickly as possible to uncertain target location cues. People exerted forces appropriate for the specific reach direction they selected irrespective of movement initiation time, suggesting that reaching dynamics were specified downstream of action selection.

Optical mapping of ground reaction force dynamics in freely behaving Drosophila melanogaster larvae

During locomotion, soft-bodied terrestrial animals solve complex control problems at substrate interfaces, but our understanding of how they achieve this without rigid components remains incomplete. Here, we develop new all-optical methods based on optical interference in a deformable substrate to measure ground reaction forces (GRFs) with micrometre and nanonewton precision in behaving Drosophila larvae. Combining this with a kinematic analysis of substrate-interfacing features, we shed new light onto the biomechanical control of larval locomotion. Crawling in larvae measuring ~1 mm in length involves an intricate pattern of cuticle sequestration and planting, producing GRFs of 1-7 µN. We show that larvae insert and expand denticulated, feet-like structures into substrates as they move, a process not previously observed in soft-bodied animals. These 'protopodia' form dynamic anchors to compensate counteracting forces. Our work provides a framework for future biomechanics research in soft-bodied animals and promises to inspire improved soft-robot design.