Biology subjects

Mawase, F.

Publications and source records attributed to Mawase, F..

8 recordsLinked to original sources

bioRxiv2025

Feedback-Feedforward Dynamics Shape De Novo Motor Learning

Many real-world motor skills require continuous control under substantial sensorimotor delays, necessitating the coordination of reactive feedback and predictive feedforward control. How these complementary control processes emerge and interact during the acquisition of a novel continuous motor skill remains unclear. We addressed this question by examining how feedback and feedforward control evolve over five days of continuous visuomotor mirror reversal learning. To directly dissociate feedback- and feedforward-related contributions during learning, we combined frequency-domain analyses of continuous tracking with independent behavioral probes of online feedback responses (brief cursor perturbations) and predictive feedforward control (initial movement direction during point-to-point reaches). We found that learning exhibited both temporal and frequency-dependent shifts in the relative contributions of feedback and feedforward control. Early improvements were dominated by rapid online feedback corrections expressed primarily at low movement frequencies, whereas predictive feedforward control emerged more gradually and became increasingly important at higher frequencies, where delayed feedback is insufficient for accurate control. A recurrent neural network model, in which an adaptive cerebellar-like feedback controller provides a teaching signal to a recurrent cortical predictive controller, reproduced these key behavioral signatures, supporting a mechanistic framework in which feedback-driven error signals facilitate the gradual emergence of predictive control. Together, these findings demonstrate that continuous motor learning arises through distinct but interacting feedback and feedforward processes that co-evolve across practice under the constraints imposed by sensorimotor delays.

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bioRxiv2024

Cerebellar output shapes cortical preparatory activity during motor adaptation

The cerebellum plays a key role in motor adaptation by driving trial-to-trial recalibration of movements based on previous errors. In primates, cortical correlates of adaptation are encoded already in the pre-movement motor plan, but these early cortical signals could be driven by a cerebellar-to-cortical information flow or evolve independently through intracortical mechanisms. To address this question, we trained female macaque monkeys to reach against a viscous force field (FF) while blocking cerebellar outflow. The cerebellar block led to impaired FF adaptation and a compensatory, re-aiming-like shift in motor cortical preparatory activity. In the null-field conditions, the cerebellar block altered neural preparatory activity by increasing task-representation dimensionality and impeding generalization. A computational model indicated that low-dimensional (cerebellar-like) feedback is sufficient to replicate these findings. We conclude that cerebellar signals carry task structure information that constrains the dimensionality of the cortical preparatory manifold and promotes generalization. In the absence of these signals, cortical mechanisms are harnessed to partially restore adaptation.

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bioRxiv2023

Motivation upregulates the adaptive response in sensorimotor learning

Motivational state plays a critical role in our ability to learn new motor skills; however, the mechanisms by which motivation influences motor learning are poorly understood. Using a motor learning paradigm in which motivation was varied in a trial-by-trial manner, we found that motivation affects learning by upregulating the rate of the adaptive response, increasing individuals speed of learning. This unveils previously unidentified evidence for a mechanism through which motivation shapes error-based motor learning.

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bioRxiv2023

Direction-dependent neural control of finger dexterity in humans

Humans, more than all other species, skillfully flex and extend their fingers to perform delicate motor tasks. This unique dexterous ability is a product of the complex anatomical properties of the human hand and the neural mechanisms that control it. Yet, the neural basis that underlies human dexterous hand movement remains unclear. Here we characterized individuation (fine control) and strength (gross control) during flexion and extension finger movements, isolated the peripheral passive mechanical coupling component from the central neuromuscular activity involved in dexterity and then applied voxel-based lesion mapping in first-event sub-acute stroke patients to investigate the causal link between the neural substrates and the behavioral aspects of finger dexterity. We found substantial differences in dexterous behavior, favoring finger flexion over extension. These differences were not caused by peripheral factors but were rather driven by central origins. Lesion-symptom mapping identified a critical brain region for finger individuation within the primary sensory-motor cortex (M1, S1), the premotor cortex (PMC), and the corticospinal (CST) fibers that descend from them. Although there was a great deal of overlap between individuated flexion and extension, we were able to identify distinct areas within this region that were associated exclusively with finger flexion. This flexion-biased differential premotor and motor cortical organization was associated with the finger individuation component, but not with finger strength. Conversely, lesion mapping revealed slight extension-biases in finger strength within descending tracts of M1. From these results we propose a model that summarizes the distinctions between individuation and strength and between finger movement in flexion and extension, revealed in human manual dexterity.

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bioRxiv2022

Cortically-evoked movement in humans reflects history of prior executions, not plan for upcoming movement

Human motor behavior involves planning and execution, but we often perform some actions more frequently. Experimentally manipulating the probability distribution of a movement through intensive repetition toward a certain direction causes physiological bias toward that direction, which can be cortically-evoked by transcranial magnetic stimulation (TMS). However, because movement execution and plan histories were indistinguishable to date, to what extent TMS-evoked biases are due to more frequently executed movement, or recent planning of movement, is unclear. Here, we use novel experimentation to separately manipulate recent history of movement plans and execution, and probe the effects of this on physiological biases using TMS, and on default plan for goal-directed actions using a behavioral timed-response task. At baseline, physiological biases shared similar low-level kinematic properties (direction) to default plan for upcoming movement. However, when recent movement execution history was manipulated via thumb movement repetitions toward a specific direction, we found a significant effect on physiological biases, but not plan-based goal-directed movement. To further determine if physiological biases reflect ongoing motor planning, we biased movement plan history by increasing the likelihood of a specific target location, and found a significant effect on the default plan for goal-directed movements. However, TMS-evoked movement during the preparation period did not become biased toward the most frequent plan. This suggests that physiological biases provide a readout of the default state of M1 population activity in the movement-related space, but not ongoing neural activation in the planning-related space, potentially ruling out relevance of cortically-evoked physiological biases to voluntary movements. HighlightsO_LIStimulating the human motor cortex selectively evoked thumb movements toward a specific direction (physiological bias) C_LIO_LIAt baseline, these physiological biases shared similar low-level kinematics with default plan for voluntary goal-directed movements C_LIO_LIModulating the probability distribution of prior movements had a significant effect on physiological biases C_LIO_LIHowever, biasing history of plans for upcoming movement toward a specific direction had no effect on evoked movement direction C_LIO_LIDuring ongoing planning of voluntary movement, evoked movements maintained the distinct and robust baseline bias, regardless of change in probability distribution of history of upcoming plans C_LI

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bioRxiv2022

Generalization reveals asymmetric and history-dependent control networks for multi-finger dexterous movements

Finger dexterity, fundamental in our daily lives, is manifested by the generation of multi-finger and multi-directional patterns of muscles activity during various motor tasks, and further, by the generalization of learning in one context to other contexts. Tying shoelaces, for example, requires precise coordination of multiple fingers, some active primarily in the flexion direction, others in the extension direction, and some immobile. Nevertheless, whether the control processes of these actions are independent or interact and potentially generalize across each other, remains unclear. In a set of experiments, we sought to characterize the behavioral principles underlying the control process, learning and generalization of dexterous extension and flexion movements. We developed an isometric dexterity task that precisely measures dexterity in terms of finger individuation, force accuracy and temporal synchronization during finger flexion and extension. First, we investigated learning and generalization abilities across flexion and extension directions, both within and across hands. To do so, two groups of participants were trained for 3 days in either the flexion or extension direction. We found improvement in all dexterity measures in both groups following training, though finger extension generally exhibited inferior dexterity. Surprisingly, while the newly acquired finger extension abilities generalized to the untrained flexion direction, the newly acquired finger flexion abilities did not generalize to the untrained extension direction. Generalization biases of the finger flexion direction were also evident in the untrained hand. Next, we examined whether the asymmetric generalization pattern of multi-finger dexterous movements was history dependent. We thus recruited skilled musicians who showed increased baseline levels of dexterity in both directions and found that the degree to which learning generalizes between two contexts was affected by prior experience. Overall, our data indicate that control of multi-digit dexterous patterns is direction-specific in humans, supporting the hypothesis that control circuits for learning of finger flexion and extension are overlapped in that they partially, but asymmetrically, transfer between directions. This ability, however, is modular as it depends on hand use and the history of prior training.

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bioRxiv2021

Computational neural network provides naturalistic solution for recovery of finger dexterity after stroke

Finger dexterity is a fundamental movement skill of humans and the ability to individuate fingers imparts high motor flexibility. Disruption of dexterity due to brain injury reduces quality of life. Thus, understanding the neurological mechanisms responsible for recovery is critical to effective neurorehabilitation. Two neuronal pathways have been proposed to play crucial roles in finger individuation: the corticospinal tract, originating from primary motor cortex and premotor areas, and the subcortical reticulospinal tract, originating from the reticular formation in the brainstem. Finger individuation in patients with lesions to these pathways may recover. However, it remains an open question how the cortical-reticular network reorganizes and contributes to this recovery following a stroke. We hypothesized that interactive connections between cortical and subcortical neurons reflect dynamics appropriate for generating outgoing commands for finger movement. To test this hypothesis, we developed an Artificial Neural Network (ANN) representing a premotor planning input layer, a cortical layer including excitatory and inhibitory neurons and, a reticular layer that control motoneurons eliciting unilateral flexion of two fingers. The ANN was trained to reproduce "normal" activity of finger individuation and strength. Analysis of the trained ANN revealed that the natural dynamical solution was a near-linear relationship between the force of the instructed and uninstructed finger, resembling individuation patterns in humans. A simulated stroke lesion was then applied to the ANN and the resulting finger dexterity was assessed at multiple stages post stroke. Analysis revealed: (1) increased unintended force produced by uninstructed fingers (i.e., enslaving) and (2) weakening of the force in the instructed finger immediately after stroke, (3) improved finger control during recovery that typically occurs early after stroke, and (4) association of this behavior with increased neural plasticity of the residual neurons, as reflected by strengthening of connectivity weights between premotor and focal cortical excitatory and inhibitory neurons, but reduction in connectivity in shared cortical neurons. Interestingly, the network solution predicted that the reticulospinal pathway also contributed to the improved behavior. Lastly, the ANN also predicts the effect of cortical lesion size on finger individuation. Our model provides a framework by which to understand a number of experimental findings. The model solution suggests that a key mechanism of finger individuation is establishment of an interactive relationship between cortical and subcortical regions, appropriate to produce desired finger movement.

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bioRxiv2021

Separation of multiple motor memories through implicit and explicit processes

Acquisition of multiple motor skills without interference is a remarkable ability in sport and daily life. During adaptation to opposing perturbations, a common paradigm to study this ability, each perturbation can be successfully learned when a dynamical contextual cue, such as a follow-through movement, is associated with the direction of the perturbation. It is still unclear, however, to what extent this context-dependent learning engages the cognitive strategy-based explicit process and the implicit process that occurs without conscious awareness. Here, we designed four reaching experiments to untangle the individual contributions of the explicit and implicit components while participants learned opposing visuomotor perturbations, with a second unperturbed follow-through movement that served as a contextual cue. In Exp. 1 we replicated previous adaptation results and showed that follow-through movements also allow learning for opposing visuomotor rotations. For one group of participants in Exp. 2 we isolated strategic explicit learning by inducing a 2-sec time delay between movement and end-point feedback, while for another group we isolated the implicit component using the task-irrelevant error-clamp paradigm, in which participants were firmly instructed to aim their reaches directly to the target. Our data showed that opposing perturbations could be fully learned by explicit strategies; but when strategy was restricted, distinct implicit processes contributed to learning. In Exp.3, we examined whether the learned motor behaviors are influenced by the disparity between the follow-through contexts. We found that the location of follow-through targets had little effect on total learning, yet it led to more instances in which participants failed to learn the task. In Exp. 4, we explored the generalization capability to untrained novel targets. Participants showed near-flat generalization of the implicit and explicit processes to adjacent targets. Overall, our results indicate that follow-through contextual cues influence activity of both implicit and explicit processes during separation of motor memories. Furthermore, the follow-through context might activate, in part, top-down cognitive factors that influence not only the dynamics of the explicit learning but also the implicit process.

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