Kernels of Motor Memory Formation: Temporal Generalization in Bimanual Adaptation.

In daily life, we coordinate both simultaneous and sequential bimanual movements to manipulate objects. Our ability to rapidly account for different object dynamics suggests there are neural mechanisms to quickly deal with them. Here we investigate how actions of one arm can serve as a contextual cue for the other arm and facilitate adaptation.

A three filament mechanistic model of musculotendon force and impedance.

The force developed by actively lengthened muscle depends on different structures across different scales of lengthening. For small perturbations, the active response of muscle is well captured by a linear-time-invariant (LTI) system: a stiff spring in parallel with a light damper. The force response of muscle to longer stretches is better represented by a compliant spring that can fix its end when activated.

Finding the rhythm: Humans exploit nonlinear intrinsic dynamics of compliant systems in periodic interaction tasks.

Activities like ball bouncing and trampoline jumping showcase the human ability to intuitively tune to system dynamics and excite motions that the system prefers intrinsically. This human sensitivity to resonance has been experimentally supported for interactions with simple linear systems but remains a challenge to validate in more complex scenarios where nonlinear dynamics cannot be predicted analytically. However, it has been found that many nonlinear systems exhibit periodic orbits similar to the eigenmodes of linear systems.

Reward actively engages both implicit and explicit components in dual force field adaptation.

Motor learning occurs through multiple mechanisms, including unsupervised, supervised (error based), and reinforcement (reward based) learning. Although studies have shown that reward leads to an overall better motor adaptation, the specific processes by which reward influences adaptation are still unclear. Here, we examine how the presence of reward affects dual adaptation to novel dynamics and distinguish its influence on implicit and explicit learning.

Learning context shapes bimanual control strategy and generalization of novel dynamics.

Bimanual movements are fundamental components of everyday actions, yet the underlying mechanisms coordinating adaptation of the two hands remain unclear. Although previous studies highlighted the contextual effect of kinematics of both arms on internal model formation, we do not know how the sensorimotor control system associates the learned memory with the experienced states in bimanual movements. More specifically, can, and if so, how, does the sensorimotor control system combine multiple states from different effectors to create and adapt a motor memory? Here, we tested motor memory formation in two groups with a novel paradigm requiring the encoding of the kinematics of the right hand to produce the appropriate predictive force on the left hand.

Explicit learning based on reward prediction error facilitates agile motor adaptations.

Error based motor learning can be driven by both sensory prediction error and reward prediction error. Learning based on sensory prediction error is termed sensorimotor adaptation, while learning based on reward prediction error is termed reward learning. To investigate the characteristics and differences between sensorimotor adaptation and reward learning, we adapted a visuomotor paradigm where subjects performed arm movements while presented with either the sensory prediction error, signed end-point error, or binary reward.

Goal-directed modulation of stretch reflex gains is reduced in the non-dominant upper limb.

Most individuals experience their dominant arm as being more dexterous than the non-dominant arm, but the neural mechanisms underlying this asymmetry in motor behaviour are unclear. Using a delayed-reach task, we have recently demonstrated strong goal-directed tuning of stretch reflex gains in the dominant upper limb of human participants. Here, we used an equivalent experimental paradigm to address the neural mechanisms that underlie the preparation for reaching movements with the non-dominant upper limb.

Congruent visual cues speed dynamic motor adaptation.

Motor adaptation to novel dynamics occurs rapidly using sensed errors to update the current motor memory. This adaption is strongly driven by proprioceptive and visual signals that indicate errors in the motor memory. Here, we extend this previous work by investigating whether the presence of additional visual cues could increase the rate of motor adaptation, specifically when the visual motion cue is congruent with the dynamics.

Musculotendon Parameters in Lower Limb Models: Simplifications, Uncertainties, and Muscle Force Estimation Sensitivity.

Musculotendon parameters are key factors in the Hill-type muscle contraction dynamics, determining the muscle force estimation accuracy of a musculoskeletal model. Their values are mostly derived from muscle architecture datasets, whose emergence has been a major impetus for model development. However, it is often not clear if such parameter update indeed improves simulation accuracy.

Assistive Loading Promotes Goal-Directed Tuning of Stretch Reflex Gains.

Voluntary movements are prepared before they are executed. Preparatory activity has been observed across the CNS and recently documented in first-order neurons of the human PNS (i.e.

Bimanual Manipulation of a Complex Object with Internal Dynamics.

Object manipulation often requires coordination between hands and adaption to the dynamic characteristics of the object. When manipulating the same object, the two hands can have either symmetric or asymmetric impact on the object's trajectory. In this work, we used a bimanual manipulation task of a complex object with internal dynamics to examine how symmetric or scaled-down control of one of the hands affects the coordination between hands.

Learning of Dexterous Object Manipulation in a Virtual Reality Environment.

Humans have unrivalled abilities to perform dexterous object manipulation. This requires the sensorimotor system to quickly adapt to environmental changes and predictively counter act the external disturbances. Many studies have focused on the anticipatory control of digits with real-world experiments.

Stability of inverted pendulum reveals transition between predictive control and impedance control in grip force modulation.

During object manipulation, our sensorimotor sys-tem needs to represent the objects dynamics in order to better control it. This is especially important in the case of grip force control where small forces can cause the object to slip from our fingers, and excessive forces can cause fatigue or even damage the object. While the tradeoff between these two constraints is clear for stable objects, such as lifting a soda can, it is less clear how the sensorimotor system adjusts the grip force for unstable objects.

Contextual cues are not unique for motor learning: Task-dependant switching of feedback controllers.

The separation of distinct motor memories by contextual cues is a well known and well studied phenomenon of feedforward human motor control. However, there is no clear evidence of such context-induced separation in feedback control. Here we test both experimentally and computationally if context-dependent switching of feedback controllers is possible in the human motor system.

Motor Learning in Response to Different Experimental Pain Models Among Healthy Individuals: A Systematic Review.

Learning new movement patterns is a normal part of daily life, but of critical importance in both sport and rehabilitation. A major question is how different sensory signals are integrated together to give rise to motor adaptation and learning. More specifically, there is growing evidence that pain can give rise to alterations in the learning process.

Active strategies for multisensory conflict suppression in the virtual hand illusion.

The perception of our body in space is flexible and manipulable. The predictive brain hypothesis explains this malleability as a consequence of the interplay between incoming sensory information and our body expectations. However, given the interaction between perception and action, we might also expect that actions would arise due to prediction errors, especially in conflicting situations.

Direct and indirect cues can enable dual adaptation, but through different learning processes.

Switching between motor tasks requires accurate adjustments for changes in dynamics (grasping a cup) or sensorimotor transformations (moving a computer mouse). Dual-adaptation studies have investigated how learning of context-dependent dynamics or transformations is enabled by sensory cues. However, certain cues, such as color, have shown mixed results.

Nanomesh pressure sensor for monitoring finger manipulation without sensory interference.

Monitoring of finger manipulation without disturbing the inherent functionalities is critical to understand the sense of natural touch. However, worn or attached sensors affect the natural feeling of the skin. We developed nanomesh pressure sensors that can monitor finger pressure without detectable effects on human sensation.

Timescales of motor memory formation in dual-adaptation.

The timescales of adaptation to novel dynamics are well explained by a dual-rate model with slow and fast states. This model can predict interference, savings and spontaneous recovery, but cannot account for adaptation to multiple tasks, as each new task drives unlearning of the previously learned task. Nevertheless, in the presence of appropriate contextual cues, humans are able to adapt simultaneously to opposing dynamics.

Time-to-Target Simplifies Optimal Control of Visuomotor Feedback Responses.

Visuomotor feedback responses vary in intensity throughout a reach, commonly explained by optimal control. Here, we show that the optimal control for a range of movements with the same goal can be simplified to a time-to-target dependent control scheme. We measure our human participants' visuomotor responses in five reaching conditions, each with different hand or cursor kinematics.

Asymmetry in kinematic generalization between visual and passive lead-in movements are consistent with a forward model in the sensorimotor system.

In our daily life we often make complex actions comprised of linked movements, such as reaching for a cup of coffee and bringing it to our mouth to drink. Recent work has highlighted the role of such linked movements in the formation of independent motor memories, affecting the learning rate and ability to learn opposing force fields. In these studies, distinct prior movements (lead-in movements) allow adaptation of opposing dynamics on the following movement.

Controller Gains of an Inverted Pendulum are Influenced by the Visual Feedback Position.

In this study we experimentally test and model the control behavior of human participants when controlling inverted pendulums of different dynamic lengths, and with visual feedback of varying congruence to these dynamic lengths. Participants were asked to stabilize the inverted pendulum of L = 1 m and L = 4 m, with visual feedback shown at various distances along the pendulum. We fit a family of linear models to the control input (cart velocity) applied by participants.

LQG framework explains performance of balancing inverted pendulum with incongruent visual feedback.

Successful manipulation of objects requires forming internal representations of the object dynamics. To do so, the sensorimotor system uses visual feedback of the object movement allowing us to estimate the object state and build the representation. One way to investigate this mechanism is by introducing a discrepancy between the visual feedback about the object's movement and the actual movement.