Biology subjects

Abram, S. J.

Publications and source records attributed to Abram, S. J..

5 recordsLinked to original sources

bioRxiv2024

Motor adaptation is reduced by symbolic compared to sensory feedback

Motor adaptation - the process of reducing motor errors through feedback and practice - is an essential feature of human competence, allowing us to move accurately in dynamic and novel environments. Adaptation typically results from sensory feedback, with most learning driven by visual and proprioceptive feedback that arises with the movement. In humans, motor adaptation can also be driven by symbolic feedback. In the present study, we examine how implicit and explicit components of motor adaptation are modulated by symbolic feedback. We conducted three reaching experiments involving over 400 human participants to compare sensory and symbolic feedback using a task in which both types of learning processes could be operative (Experiment 1) or tasks in which learning was expected to be limited to only an explicit process (Experiments 2 and 3). Adaptation with symbolic feedback was dominated by explicit strategy use, with minimal evidence of implicit recalibration. Even when matched in terms of information content, adaptation to rotational and mirror reversal perturbations was slower in response to symbolic feedback compared to sensory feedback. Our results suggest that the abstract and indirect nature of symbolic feedback disrupts strategic reasoning and/or refinement, deepening our understanding of how feedback type influences the mechanisms of sensorimotor learning.

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bioRxiv2023

Implicit reward-based motor learning

Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can induce explicit adjustments in movement strategy, it remains unclear if this type of feedback also induce implicit learning. We examined this question in a center-out reaching task by gradually moving an invisible reward zone away from a visual target to a final rotation of 7.5{degrees} or 25{degrees} in a between-group design. Participants received binary feedback, indicating if the movement intersected the reward zone. By the end of the training, both groups modified their reach angle by about 95% of the rotation. We quantified implicit learning by measuring performance in a subsequent no-feedback aftereffect phase, in which participants were told to forgo any adopted movement strategies and reach directly to the visual target. The results showed a small, but robust (2-3{degrees}) aftereffect in both groups, highlighting that binary feedback elicits implicit learning. Notably, for both groups, reaches to two flanking generalization targets were biased in the same direction as the aftereffect. This pattern is at odds with the hypothesis that implicit learning is a form of use-dependent learning. Rather, the results suggest that binary feedback can be sufficient to recalibrate a sensorimotor map.

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bioRxiv2023

Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation

Cerebellar-dependent implicit adaptation has been regarded as a rigid process that automatically operates in response to movement errors in order to keep the sensorimotor system calibrated. This hypothesis has been challenged by recent evidence suggesting flexibility in this learning process. One compelling line of evidence comes from work suggesting that this form of learning is context-dependent, with the rate of learning modulated by error history. Specifically, learning was attenuated in the presence of perturbations exhibiting high variance compared to when the perturbation is fixed. However, these findings are confounded by the fact that the adaptation system corrects for errors of different magnitudes in a non-linear manner, with the adaptive response increasing in a proportional manner to small errors and saturating to large errors. Through simulations, we show that this non-linear motor correction function is sufficient to explain the effect of perturbation variance without referring to an experience-dependent change in error sensitivity. Moreover, by controlling the distribution of errors experienced during training, we provide empirical evidence showing that there is no measurable effect of perturbation variance on implicit adaptation. As such, we argue that the evidence to date remains consistent with the rigidity assumption.

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bioRxiv2020

Increasing the gradient of energetic cost does not initiate adaptation in human walking

When in a new situation, the nervous system may benefit from adapting its control policy. In determining whether or not to initiate this adaptation, the nervous system may rely on some features of the new situation. Here we tested whether one such feature is salient cost savings. We changed cost saliency by manipulating the gradient of participants energetic cost landscape during walking. We hypothesized that steeper gradients would cause participants to spontaneously adapt their step frequency to lower costs. To manipulate the gradient, a mechatronic system applied controlled fore-aft forces to the waist of participants as a function of their step frequency as they walked on a treadmill. These forces increased the energetic cost of walking at high step frequencies and reduced it at low step frequencies. We successfully created three cost landscapes of increasing gradients, where the natural variability in participants step frequency provided cost changes of 3.6% (shallow), 7.2% (intermediate) and 10.2% (steep). Participants did not spontaneously initiate adaptation in response to any of the gradients. Using metronome-guided walking-- a previously established protocol for eliciting initiation of adaptation--participants next experienced a step frequency with a lower cost. Participants then adapted by -1.41{+/-}0.81 (p=0.007) normalized units away from their originally preferred step frequency obtaining cost savings of 4.80{+/-}3.12%. That participants would adapt under some conditions, but not in response to steeper cost gradients, suggests that the nervous system does not solely rely on the gradient of energetic cost to initiate adaptation in novel situations.

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bioRxiv2018

Energy Optimization is a Major Objective in the Real-Time Control of Step Width in Human Walking

People prefer to move in energetically optimal ways during walking. We have recently found that this preference arises not just through evolution and development, but that the nervous system will continuously optimize step frequency in response to new energetic cost landscapes. Here we test whether energy optimization is also a major objective in the nervous system s real-time control of step width. To accomplish this, we use a device that can reshape the relationship between step width and energetic cost, shifting the energy optimal width wider than that initially preferred. We find that the nervous system doesn t spontaneously initiate energy optimization, but instead requires experience with a lower energetic cost step width. After initiating optimization, people converge towards their new energy optimal width within hundreds of steps and update this as their new preferred width, rapidly returning to it when perturbed away. However, energy optimization was incomplete as this new preferred width was slightly narrower than the energetically optimal width. This suggests that the nervous system may determine its preferred width by optimizing energy simultaneously with other objectives such as stability or maneuverability. Collectively, these findings indicate that the nervous systems of able-bodied people continuously optimize energetic cost to determine preferred step width.

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