Biology subjects

Al-Fawakhiri, N.

Publications and source records attributed to Al-Fawakhiri, N..

6 recordsLinked to original sources

bioRxiv2026

Instrumental-Motor Transfer: The Relative Value of Competing Movement Goals Modulates Implicit Motor Learning

Motor learning depends on the integration of several, often competing signals, including reward and punishment (which guide learning the value of actions via reinforcement learning) and sensorimotor errors (which refine the execution of actions via motor adaptation). If and how these signals interact remains controversial. Here we show that the learned value of actions can fundamentally alter how the motor adaptation system learns from errors. Human participants learned the reward values of different movement targets and subsequently underwent implicit motor learning at those targets. Across several experiments, motor learning was robustly attenuated when it brought the limb toward previously punished movement directions. Moreover, learning was globally suppressed when punished targets were themselves the movement goal. Learning was not reciprocally enhanced when it pushed movements toward previously rewarded directions, revealing a valence asymmetry. Using computational modeling, we present a novel mechanism to explain our effects: the motor adaptation system tunes its error sensitivity according to a movement-specific value gradient. Our findings point to a close interaction between reinforcement learning and motor memory -- a kind of "instrumental-motor transfer" -- where learned action values modulate error-based motor adaptation.

neuroscience↗

bioRxiv2023

Independent Influences of Movement Distance and Visual Distance on Fitts' Law

Fitts Law is one among a small number of psychophysical laws. However, a fundamental variable in Fitts Law - the movement distance, D - confounds two quantities: the physical distance the effector has to move to reach a goal, and the visually perceived distance to that goal. While these two quantities are functionally equivalent in everyday motor behavior, decoupling them might improve our understanding of the factors that shape speed-accuracy tradeoffs. Here we leveraged the phenomenon of visuomotor gain adaptation to de-confound movement and visual distance during goal-directed reaching. We found that movement distance and visual distance can influence movement times, supporting a variant of Fitts Law that considers both. The weighting of movement versus visual distance was modified by restricting movement range and degrading visual feedback. These results may reflect the role of sensory context in early stages of motor planning. Public SignificanceYou will automatically slow your movement when picking up a needle five inches away versus a handkerchief three inches away. This fact is elegantly formalized by Fitts Law, which mathematically relates movement duration to movement difficulty. However, one of the fundamental variables in the law - the distance of a planned movement - is ambiguous: Is it the actual distance the hand must move that biases movement duration, or is it the visually perceived distance? We decoupled these variables, finding that Fitts Law is shaped by both quantities, and that the influence of one versus the other may be related to the relevance of visual information. We believe our "addendum" to Fitts Law is timely, as everyday motor behavior has become increasingly enmeshed with virtual environments that abstract our movements into digital realities.

neuroscience↗

bioRxiv2023

Evidence of an optimal error rate for motor skill learning

When acquiring a motor skill, learners must practice the skill at a difficulty that is challenging but still manageable to gradually improve their performance. In other words, during training, the learner must experience success as well as failure. Does there exist an optimal proportion of successes and failures to promote the fastest improvements in skill? Here, we build on a recent theoretical framework for optimal machine learning, extending it to the learning of motor skills. We then designed a custom task whose difficulty dynamically changed along with human subjects performance, constraining the error rate during training. In a large behavioral dataset (N=192), we observed evidence that learning is greatest at around a [~]30% error rate, matching our theoretical predictions.

neuroscience↗

bioRxiv2023

On the money and right on target: How robust are reward and task success effects on implicit motor adaptation?

While implicit motor adaptation is driven by sensory-prediction errors (SPEs), recent work has shown that task success modulates this process. Task success has typically been defined as hitting a target, which signifies the goal of the movement. Visuomotor adaptation tasks are uniquely situated to experimentally manipulate task success independently from SPE by changing the target size or the location of the target. These two, distinct manipulations may influence implicit motor adaptation in different ways, so, over four experiments, we sought to probe the efficacy of each manipulation. We found that changes in target size which caused the target to fully envelop the cursor only affected implicit adaptation for a narrow range of SPE sizes, while jumping the target to overlap with the cursor more reliably and robustly affected implicit adaptation. Taken together, our data indicate that, while task success exerts a small effect on implicit adaptation, these effects are susceptible to methodological variations. Future investigations of the effect of task success on implicit adaptation could benefit from employing target jump manipulations instead of target size manipulations.

neuroscience↗

bioRxiv2023

Metacognitive Judgments during Visuomotor Learning Reflect the Integration of Error History

People form metacognitive representations of their own abilities across a range of tasks. How these representations are influenced by errors during learning is poorly understood. Here we ask how metacognitive confidence judgments of performance during motor learning are shaped by the learners recent history of errors. Across four motor learning experiments, our computational modeling approach demonstrated that peoples confidence judgments are best explained by a recency-weighted averaging of visually observed errors. Moreover, in the formation of these confidence estimates, people appear to re-weight observed motor errors according to a subjective cost function. Confidence judgments were adaptive, incorporating recent motor errors in a manner that was sensitive to the volatility of the learning environment, integrating a shallower history when the environment was more volatile. Finally, confidence tracked motor errors in the context of both implicit and explicit motor learning, but only showed evidence of influencing behavior in the latter. Our study thus provides a novel descriptive model that successfully approximates the dynamics of metacognitive judgments during motor learning. NEW & NOTEWORTHYThis study examined how, during visuomotor-learning, peoples confidence in their performance is shaped by their recent history of errors. Using computational modeling, we found that confidence incorporated recent error-history, tracked subjective error-costs, was sensitive to environmental volatility, and in some contexts may influence learning. Together, these results provide a novel model of metacognitive judgments during motor-learning that could be applied to future computational and neural studies at the interface of higher-order cognition and motor control.

neuroscience↗

bioRxiv2021

Generalization of motor learning in psychological space

To generate adaptive movements we must generalize what we have previously learned to novel situations. The generalization of adapted movements has typically been framed as a consequence of neural tuning functions that overlap for similar movement kinematics - what might be considered bottom-up generalization. However, as is true in many domains of human behavior, generalization can also be framed as the result of deliberate decisions about how to act (top-down generalization). Here we attempt to broaden the scope of theories about motor generalization, hypothesizing that part of the typical motor generalization function can be characterized as a consequence of top-down decisions concerning the subjective similarity of different movement contexts. We tested this proposal by having participants make explicit similarity ratings over both traditional kinematic contextual dimensions (movement direction) and more abstract contextual dimensions (target shape), and perform a visuomotor adaptation generalization task where trials varied over those dimensions. Across five experiments, we measured the relationship between subjective similarity ratings and motor generalization. In some cases this link was rather strong, though it was determined by both task-relevance and explicit instruction. These results support a broadening of the descriptive framework used to understand the generalization of motor behaviors and support a more careful deployment of instructions in generalization studies. Significance StatementGeneralization describes the transfer of knowledge from one context to another, and is typically thought to result from a higher-order inference process. However, in the motor adaptation domain, generalization is thought to arise from neural representations tuned to low-level kinematics. To bridge these differing views, we measured peoples subjective similarity judgements of different task contexts during sensorimotor adaptation. We found that motor generalization was closely linked to participants subjective judgements, and that explicit instructions about the consequential dimension of different contexts further shaped generalization. These findings emphasize that in addition to low level kinematic considerations, top-down inferences about which action to take in a given context should be considered as another key component of motor generalization.

neuroscience↗