Biology subjects

Avraham, G.

Publications and source records attributed to Avraham, G..

14 recordsLinked to original sources

bioRxiv2026

Amplitude-Modulated Kilohertz Stimulation Targeting Beta-Band Activity Disrupts Motor Learning

Sensorimotor learning is associated with the modulation of neural rhythms in the primary motor cortex (M1). Beta-band activity ("beta"; 15-30 Hz) is suppressed during learning, while delta oscillations (1-4 Hz) become increasingly correlated with movement kinematics as skill improves. These observations have been complemented by experimental manipulations designed to perturb oscillatory activity with externally applied electric fields (E-fields). In non-human primates, invasive beta stimulation has been shown to disrupt motor learning whereas delta stimulation enhanced motor recovery in a stroke model. Causal evidence in humans remains limited, partly because established non-invasive methods cannot achieve continuous, narrowband E-fields at sufficient amplitude in the brain. To address this gap, we employed kilohertz transcranial magnetic perturbation (kTMP), a non-invasive magnetic induction technique that delivers continuous narrowband kilohertz E-fields which can be amplitude-modulated (AM) to target cortical rhythms. We applied AM-kTMP to test the functional relevance of beta and delta activity in human motor learning. In a double-blind mixed design, 40 participants performed a force-control task while receiving AM-kTMP at E-field amplitudes of 8 V/m in M1. We targeted either beta or delta, each paired with a sham condition. AM-kTMP influenced motor performance in a frequency-dependent manner: Beta-kTMP suppressed performance gains relative to both delta-kTMP and sham, whereas delta-kTMP showed no effect. These results suggest that increased beta activity in human M1 can interfere with motor learning. More broadly, kTMP offers a novel approach to probe frequency-specific cortical dynamics.

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bioRxiv2024

Interference underlies attenuation upon relearning in sensorimotor adaptation

Savings refers to the gain in performance upon relearning a task. In sensorimotor adaptation, savings is tested by having participants adapt to perturbed feedback and, following a washout block during which the system resets to baseline, presenting the same perturbation again. While savings has been observed with these tasks, we have shown that the contribution from implicit sensorimotor adaptation, a process that uses sensory prediction errors to recalibrate the sensorimotor map, is actually attenuated upon relearning (Avraham et al., 2021). In the present study, we test the hypothesis that this attenuation is due to interference arising from the washout block, and more generally, from experience with a different relationship between the movement and the feedback. In standard adaptation studies, removing the perturbation at the start of the washout block results in a salient error signal in the opposite direction to that observed during learning. As a starting point, we replicated the finding that implicit adaptation is attenuated following a washout period in which the feedback now signals a salient opposite error. When we eliminated visual feedback during washout, implicit adaptation was no longer attenuated upon relearning, consistent with the interference hypothesis. Next, we eliminated the salient error during washout by gradually decreasing the perturbation, creating a scenario in which the perceived errors fell within the range associated with motor noise. Nonetheless, attenuation was still prominent. Inspired by this observation, we tested participants with an extended experience with veridical feedback during an initial baseline phase and found that this was sufficient to cause robust attenuation of implicit adaptation during the first exposure to the perturbation. This effect was context-specific: It did not generalize to movements that were not associated with the interfering feedback. Taken together, these results show that the implicit sensorimotor adaptation system is highly sensitive to memory interference from a recent experience with a discrepant action-outcome contingency.

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bioRxiv2023

Artificial Tactile Stimulation Provides Haptic Cuing in Force Field Adaptation

When interacting with objects with unfamiliar dynamics, the sensorimotor system uses haptic information to develop internal representations of the new dynamics. These representations are subsequently used to manipulate the objects by applying predictive forces that comply with the mechanical properties of the objects. In a recent study (Farajian et al. 2020), we showed that when participants evaluated the stiffness of elastic objects, adding artificial tactile stimulation created an illusion of higher stiffness, increasing the grip force control used to interact with the object. Here, we took a step further in understanding how kinesthetic and tactile information is integrated into the control of objects. Specifically, we examined how added skin stretch influenced the learning of novel forces. We found that the extent of force compensation that the participants exhibited depended on the direction of the artificial skin stretch applied simultaneously with the force; learning was enhanced when the skin was stretched in the opposite direction to the external force and diminished when the skin was stretched in the same direction. Strikingly, when the skin stretch stimulation was delivered during probe trials in which the force perturbation was absent, the behavior pattern was flipped, with an increase in force compensation for the same-direction skin stretch stimulation and vice versa. Modeling suggests that these results reflect a unique effect of tactile stimulation during the learning of novel forces; rather than becoming integrated with the dynamic information, it is used by the sensorimotor system as a guidance cue, possibly through explicit mechanisms, providing information on the way to compensate for the forces and optimize movements. We believe that these findings propose a novel instructive role of tactile stimulation during interaction with a dynamic object. This provides a significant potential to leverage these effects in the development of devices aiming to assist and guide users in many human-in-the-loop applications, such as rehabilitation and surgical robotics.

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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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bioRxiv2022

Advanced Feedback Enhances Sensorimotor Adaptation

It is widely recognized that sensorimotor learning is enhanced when the feedback is provided throughout the movement compared to when it is provided at the end of the movement. However, the source of this advantage is unclear: Continuous feedback is more ecological, dynamic, and available earlier than endpoint feedback. Here we assess the relative merits of these factors using a method that allows us to manipulate feedback timing independent of actual hand position. By manipulating the onset time of endpoint feedback, we found that adaptation was modulated in a non-monotonic manner, with the peak of the function occurring in advance of the hand reaching the target. Moreover, at this optimal time, learning was of similar magnitude as that observed with continuous feedback. By varying movement duration, we demonstrate that this optimal time occurs at a relatively fixed time after movement onset, an interval we hypothesize corresponds to when the comparison of the sensory prediction and feedback generates the strongest error signal.

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bioRxiv2022

The Effect of Perturbation Variability on Sensorimotor Adaptation Does Not Require an Implicit Memory of Errors

In a recent paper1 entitled, "An implicit memory of errors limits human sensorimotor adaptation" Albert and colleagues presented a model in which the adaptive response of the sensorimotor system is flexibly modulated by recent experience, or what they refer to as a "memory of errors". This hypothesis stands in contrast to prevailing models in which automatic and implicit responses to movement errors are relatively insensitive to the statistical properties of the environment2-6. A prime example of this rigidity is that the adaptation system exhibits a saturated response to large errors, resulting in a non-linear motor correction function, a feature that is independent of experience4,5,7. Here we show that the key results reported in Albert et al. are fully explained by presupposing this rigid "motor correction" function without reference to memory-dependent changes in error sensitivity. As such, the evidence presented in Albert et. al. does not support the claim that the history of errors modulates implicit adaptation.

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bioRxiv2021

Moving outside the lab: The viability of conducting sensorimotor learning studies online

Collecting data online via crowdsourcing platforms has proven to be a very efficient way to recruit a large and diverse sample. Studies of motor learning, however, have been largely confined to the lab due to the need for special equipment to record movement kinematics and, as such, are typically only accessible to specific participants (e.g., college students). As a first foray to make motor learning studies accessible to a larger and more diverse audience, we developed an online, web-based platform (OnPoint) to collect kinematic data, serving as a template for researchers to create their own online sensorimotor control and learning experiments. As a proof-of-concept, we asked if fundamental motor learning phenomena discovered in the lab could be replicated online. In a series of three experiments, we observed a close correspondence between the results obtained online with those previously reported from research conducted in the laboratory. This web-based platform paired with online crowdsourcing can serve as a powerful new method for the study of motor control and learning.

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bioRxiv2020

An associative learning account of sensorimotor adaptation

Traditional associative learning tasks focus on the formation of associations between salient events and arbitrary stimuli that predict those events. This is exemplified in cerebellar-dependent delay eyeblink conditioning, where arbitrary cues such as a light or tone act as conditioning stimuli that predict aversive sensations at the cornea. Here we ask if a similar framework could be applied to another type of cerebellar-dependent sensorimotor learning - sensorimotor adaptation. Models of sensorimotor adaptation posit that the introduction of an environmental perturbation results in an error signal that is used to update an internal model of a sensorimotor map for motor planning. Here we take a step towards an integrative account of these two forms of cerebellar-dependent learning, examining the relevance of core concepts from associative learning for sensorimotor adaptation. Using a visuomotor adaptation reaching task, we paired movement-related feedback with neutral auditory or visual contextual cues that served as conditioning stimuli (CSs). Trial-by trial changes in feedforward movement kinematics exhibited three key signatures of associative learning: Differential conditioning, sensitivity to the CS-US interval, and compound conditioning. Moreover, after compound conditioning, a robust negative correlation was observed between responses to the two elemental CSs of the compound (i.e., overshadowing), consistent with the additivity principle posited by theories of associative learning. The existence of associative learning effects in sensorimotor adaptation provides a proof-of-concept for linking cerebellar- dependent learning paradigms within a common theoretical framework.

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bioRxiv2020

Re-exposure to a sensorimotor perturbation produces opposite effects on explicit and implicit learning processes

The motor system demonstrates an exquisite ability to adapt to changes in the environment, and to quickly reset when these changes prove transient. If similar environmental changes are encountered in the future, learning may be faster, a phenomenon known as savings. In studies of sensorimotor learning, a central component of savings is attributed to the explicit recall of the task structure and appropriate compensatory strategies. Whether implicit adaptation also contributes to savings remains subject to debate (Leow et al., 2020; Yin and Wei, 2020). We tackled this question by measuring, in parallel, explicit and implicit adaptive responses in a visuomotor rotation task, employing a protocol that typically elicits savings. While the initial rate of learning was faster in the second exposure to the perturbation, an analysis decomposing the two processes showed the benefit to be solely associated with explicit re-aiming. Surprisingly, we found a significant decrease after relearning in aftereffect magnitudes during no-feedback trials, a direct measure of implicit adaptation. In a second experiment, we isolated implicit adaptation using clamped visual feedback, a method known to eliminate the contribution of explicit learning processes. Consistent with the results of the first experiment, participants exhibited a marked reduction in the adaptation function, as well as an attenuated aftereffect when re-learning from the clamped feedback. Motivated by these results, we re-analyzed data from prior studies and observed a consistent, yet unappreciated pattern of attenuation of implicit adaptation during relearning. These results indicate that explicit and implicit sensorimotor processes exhibit opposite effects upon relearning: Explicit learning shows savings, while implicit adaptation becomes attenuated.

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bioRxiv2020

The Effect of Visual Uncertainty on Implicit Motor Adaptation

Sensorimotor adaptation is driven by sensory prediction errors, the difference between the predicted and actual feedback. When the position of the feedback is made uncertain, adaptation is attenuated. This effect, in the context of optimal sensory integration models, has been attributed to a weakening of the error signal driving adaptation. Here we consider an alternative hypothesis, namely that uncertainty alters the perceived location of the feedback. We present two visuomotor adaptation experiments to compare these hypotheses, varying the size and uncertainty of a visual error signal. Uncertainty attenuated learning when the error size was small but had no effect when the error size was large. This pattern of results favors the hypothesis that uncertainty does not impact the strength of the error signal, but rather, leads to mis-localization of the error. We formalize these ideas to offer a novel perspective on the effect of visual uncertainty on implicit sensorimotor adaptation. SIGNIFICANCE STATEMENTCurrent models of sensorimotor adaptation assume that the rate of learning will be related to properties of the error signal (e.g., size, consistency, relevance). Recent evidence has challenged this view, pointing to a rigid, modular system, one that automatically recalibrates the sensorimotor map in response to movement errors, with minimal constraint. In light of these developments, this study revisits the influence of feedback uncertainty on sensorimotor adaptation. Adaptation was attenuated in response to a noisy feedback signal, but the effect was only manifest for small errors and not for large errors. This interaction suggests that uncertainty does not weaken the error signal. Rather, it may influence the perceived location of the feedback and thus the change in the sensorimotor map induced by that error. These ideas are formalized to show how the motor system remains exquisitely calibrated, even if adaptation is largely insensitive to the statistics of error signals.

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bioRxiv2019

Environmental Consistency Modulation of Error Sensitivity During Motor Adaptation is Explicitly Controlled

Motor adaptation, the adjustment of sensorimotor representations in face of changes in the environment, may operate at different rates. When human participants encounter repeated or consistent perturbations, their corrections for the experienced errors are larger compared to when the perturbations are new or inconsistent. Such modulations of error sensitivity were traditionally considered to be an implicit process that does not require attentional resources. In recent years, the implicit view of motor adaptation is challenged by evidence showing a contribution of explicit strategies to learning. These findings raise a fundamental question regarding the nature of the error sensitivity modulation processes. We tested the effect of explicit control on error sensitivity in a series of experiments, in which participants controlled a screen cursor to virtual targets. We manipulated environmental consistency by presenting rotations in random (low consistency) or random walk (high consistency) sequences, and illustrated that perturbation consistency affects the rate of adaptation, corroborating previous studies. When participants were instructed to ignore the cursor and move directly to the target, thus, eliminating the contribution of explicit strategies, consistency-driven error sensitivity modulation was abolished. In addition, delaying the visual feedback, a manipulation that affects implicit learning, did not influence error sensitivity under consistent perturbations. These results suggest that increases of learning rate in consistent environments are attributable to an explicit rather than implicit process in sensorimotor adaptation. Significant Statement When experiencing an error in a motor task (e.g., missing a basketball shot in a windy day), the motor system modifies its next action based on environmental consistency (how frequent the changes in winds direction and strength are). It is unknown whether this process is driven by an implicit and automatic process, or by an explicit process that employs cognitive strategies. We examined these possibilities in a simple visuomotor task by perturbing the feedback in each trial with different consistency levels, and manipulating the use of implicit and explicit processes. We found that participants increase their sensitivity to errors in consistent environments when employing explicit strategies, and do not change their behavior when the implicit process is operating alone.

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bioRxiv2017

State-Based Delay Representation and Its Transfer from a Game of Pong to Reaching and Tracking

To accurately estimate the state of the body, the nervous system needs to account for delays between signals from different sensory modalities. To investigate how such delays may be represented in the sensorimotor system, we asked human participants to play a virtual pong game in which the movement of the virtual paddle was delayed with respect to their hand movement. We tested the representation of this new mapping between the hand and the delayed paddle by examining transfer of adaptation to blind reaching and blind tracking tasks. These blind tasks enabled to capture the representation in feedforward mechanisms of movement control. A Time Representation of the delay is an estimation of the actual time lag between hand and paddle movements. A State Representation is a representation of delay using current state variables: the distance between the paddle and the ball originating from the delay may be considered as a spatial shift; the low sensitivity in the response of the paddle may be interpreted as a minifying gain; and the lag may be attributed to a mechanical resistance that influences paddles movement. We found that the effects of prolonged exposure to the delayed feedback transferred to blind reaching and tracking tasks and caused participants to exhibit hypermetric movements. These results, together with simulations of our representation models, suggest that delay is not represented based on time, but rather as a spatial gain change in visuomotor mapping.\n\nSignificance StatementIt is known that the brain copes with sensory feedback delays to control movements, but it is unclear whether it does so using a representation of the actual time lag. We addressed this question by exposing participants to a visuomotor delay during a dynamic game of pong. Following the game, participants exhibited hypermetric reaching and tracking movements that indicate that delay is represented as a visuomotor gain rather than as a temporal shift.

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bioRxiv2017

Adaptation to a Space-variant Visuomotor Delay can Cause Neglect-like Effects on Drawing Symmetry

In daily interactions, our sensorimotor system accounts for spatial and temporal discrepancies between the senses. Functional lateralization between hemispheres causes differences in attention and control of action. In addition, differences in transmission delays between modalities affects motor control. Studies on hemispatial neglect syndrome suggest a link between temporal processing and lateral spatial biases. To understand this link, we studied participants who performed lateral reaching, and adapted to delayed visual feedback in either left, right, or both workspaces. We tested transfer of adaptation to blind drawing, and found that adaptation to left or both delay caused selective leftward elongation. In contrast, adaptation to right delay caused elongation in both directions. Arm dynamics alone cannot explain these findings, but a model of a combined attentional-motor asymmetry across the hemispheres explains our observations. This suggests a possible connection between laterality in delay processing and motor performances observed in cases of hemispatial neglect.

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