Effects of an Additional Sequence of Color Stimuli on Visuomotor Sequence Learning

Through practice, people are able to integrate a secondary sequence (e.g., a stimulus-based sequence) into a primary sequence (e.g., a response-based sequence), but it is still controversial whether the integrated sequences lead to better learning than only the primary sequence. In the present study, we aimed to investigate the effects of a sequence that integrated space and color sequences on early and late learning phases (corresponding to effector-independent and effector-dependent learning, respectively) and how the effects differed in the integrated and primary sequences in each learning phase. In the task, the participants were required to learn a sequence of button presses using trial-and-error and to perform the sequence successfully for 20 trials (m × n task). First, in the baseline task, all participants learned a non-colored sequence, in which the response button always turned red. Then, in the learning task, the participants were assigned to two groups: a colored sequence group (i.e., space and color) or a non-colored sequence group (i.e., space). In the colored sequence, the response button turned a pre-determined color and the participants were instructed to attend to the sequences of both location and color as much as they could. The results showed that the participants who performed the colored sequence acquired the correct button presses of the sequence earlier, but showed a slower mean performance time than those who performed the non-colored sequence. Moreover, the slower performance time in the colored sequence group remained in a subsequent transfer task in which the spatial configurations of the buttons were vertically mirrored from the learning task. These results indicated that if participants explicitly attended to both the spatial response sequence and color stimulus sequence at the same time, they could develop their spatial representations of the sequence earlier (i.e., early development of the effector-independent learning), but might not be able to enhance their motor representations of the sequence (i.e., late development of the effector-dependent learning). Thus, the undeveloped effector-dependent representations in the colored sequence group directly led to a long performance time in the transfer sequence

The influence of eye movements on sequence learning

The aim of the dissertation is the systematic investigation of the role of eye movements in motor sequence learning. The literature offers contradictory findings on the question of whether eye movements are necessary for learning a motor sequence. For a closer look, three experiments were performed using two different movement sequences: a 16-element movement sequence, one-dimensionally presented on a horizontal plane (Experiment 1) and a simple motor sequence task, presented in two dimensions on a horizontal and vertical plane (Experiment 2 & 3). All sequences were performed via an extension and flexion motion in the elbow joint of the arm. Experiment 1 explored the role eye movements play in sequence learning and whether free eye movements improve sequence learning. The aim of Experiment 2 was to determine the role eye movements in movement sequence learning when the visual angle of the target information is systematically varied and eye movements are minimized by the instruction to fixate. Experiment 3 utilized both a physical practice group as well as a group acquired by observational learning. The purpose was to investigate the role of eye movements in observational learning in comparison to physical learning as well as the influence of eye movements on the development of a movement sequence representation following physical or observational practice. In all three experiments, an eye-tracking system was used to record and analyze eye movements. The dissertation provides five main results. First, movement sequences can be learned without eye movements; however, permitting the use of eye movements supports sequence learning. Second, eye movements facilitate sequence learning, especially when they are used in an early stage of learning, and third, eye movements facilitate sequence learning when the visual information is increased. Fourth, the results from physical practice can be extended to observational practice. Fifth, eye movements play an important role in developing a visual-spatial and motor representation.Das Ziel der Dissertation ist die systematische Untersuchung der Rolle von Augenbewegungen beim motorischen Sequenzlernen. Die Literatur liefert kontroverse Befunde zu der Frage, ob Augenbewegungen zum Erlernen einer motorischen Sequenz notwendig sind. Zur näheren Betrachtung wurden drei Experimente mit zwei verschiedene Bewegungssequenzen durchgeführt: eine 16-elementige Bewegungssequenz, eindimensional auf einer horizontalen Ebene präsentiert (Experiment 1) und eine einfache motorische Sequenzaufgabe, zweidimensional, präsentiert auf einer horizontalen und vertikalen Ebene (Experimente 2 & 3). Alle Sequenzen wurden mittels einer Extensions- und Flexionsbewegung im Ellenbogengelenk des Armes ausgeführt. In Experiment 1 wurde untersucht, welche Rolle Augenbewegungen beim Sequenzlernen spielen und ob freie Augenbewegungen das Sequenzlernen verbessern. Ziel von Experiment 2 war herauszufinden, welche Rolle Augenbewegungen beim Sequenzlernen spielen, wenn der visuelle Winkel der Zielinformation systematisch variiert wird und die Augenbewegungen durch die Anweisung zum Fixieren minimiert werden. In Experiment 3 wurde sowohl eine physische Übungsgruppe also auch eine Gruppe, die durch Beobachtung aneignete, genutzt. Die Intension war zu untersuchen, welche Rolle Augenbewegungen beim Beobachtungslernen im Vergleich zu physischem Lernen spielen. Des Weiteren wurde der Frage nachgegangen, welchen Einfluss Augenbewegungen nach den jeweiligen Übungsformen (physisch/beobachten) auf die Entwicklung einer Bewegungsrepräsentation haben. In allen Experimenten wurde ein Eye-Tracking System verwendet, um Augenbewegungen aufzuzeichnen und zu analysieren. Die Dissertation liefert fünf Hauptergebnisse. Erstens, Bewegungssequenzen können ohne Augenbewegungen gelernt werden, jedoch unterstützen freie Augenbewegungen das Sequenzlernen. Zweitens, Augenbewegungen unterstützen Sequenzlernen vor allem dann, wenn sie im frühen Lernverlauf genutzt werden. Drittens, Augenbewegungen unterstützen Sequenzlernen, wenn die visuelle Information vergrößert wird. Viertens, die Ergebnisse können von physischem Üben auf Üben durch Beobachtung erweitert werden. Fünftens, Augenbewegungen spielen eine wichtige Rolle bei der Entwicklung einer visuell-räumlichen und motorischen Repräsentation

tDCS effects on pointing task learning in young and old adults

Skill increase in motor performance can be defined as explicitly measuring task success but also via more implicit measures of movement kinematics. Even though these measures are often related, there is evidence that they represent distinct concepts of learning. In the present study, the effect of multiple tDCS-sessions on both explicit and implicit measures of learning are investigated in a pointing task in 30 young adults (YA) between 27.07 ± 3.8 years and 30 old adults (OA) between 67.97 years ± 5.3 years. We hypothesized, that OA would show slower explicit skill learning indicated by higher movement times/lower accuracy and slower implicit learning indicated by higher spatial variability but profit more from anodal tDCS compared with YA. We found age-related differences in movement time but not in accuracy or spatial variability. TDCS did not skill learning facilitate learning neither in explicit nor implicit parameters. However, contrary to our hypotheses, we found tDCS-associated higher accuracy only in YA but not in spatial variability. Taken together, our data shows limited overlapping of tDCS effects in explicit and implicit skill parameters. Furthermore, it supports the assumption that tDCS is capable of producing a performance-enhancing brain state at least for explicit skill acquisition

Vision-based Manipulation In-the-Wild

Deploying robots in real-world environments involves immense engineering complexity, potentially surpassing the resources required for autonomous vehicles due to the increased dimensionality and task variety. To maximize the chances of successful real-world deployment, finding a simple solution that minimizes engineering complexity at every level, from hardware to algorithm to operations, is crucial. In this dissertation, we consider a vision-based manipulation system that can be deployed in-the-wild when trained to imitate sufficient quantity and diversity of human demonstration data on the desired task. At deployment time, the robot is driven by a single diffusion-based visuomotor policy, with raw RGB images as input and robot end-effector pose as output. Compared to existing policy representations, Diffusion Policy handles multimodal action distributions gracefully, being scalable to high-dimensional action spaces and exhibiting impressive training stability. These properties allow a single software system to be used for multiple tasks, with data collected by multiple demonstrators, deployed to multiple robot embodiments, and without significant hyper-parameter tuning. We developed a Universal Manipulation Interface (UMI), a portable, low-cost, and information-rich data collection system to enable direct manipulation skill learning from in-the-wild human demonstrations. UMI provides an intuitive interface for non-expert users by using hand-held grippers with mounted GoPro cameras. Compared to existing robotic data collection systems, UMI enables robotic data collection without needing a robot, drastically reducing the engineering and operational complexity. Trained with UMI data, the resulting diffusion policies can be deployed across multiple robot platforms in unseen environments for novel objects and to complete dynamic, bimanual, precise, and long-horizon tasks. The Diffusion Policy and UMI combination provides a simple full-stack solution to many manipulation problems. The turn-around time of building a single-task manipulation system (such as object tossing and cloth folding) can be reduced from a few months to a few days

Motor learning during reaching movements: model acquisition and recalibration

This thesis marks a departure from the traditional task-based distinction between sensorimotor adaptation and skill learning by focusing on the mechanisms that underlie adaptation and skill learning. I argue that adaptation is a recalibration of an existing control policy, whereas skill learning is the acquisition and subsequent automatization of a new control policy. A behavioral criterion to distinguish the two mechanisms is offered. The first empirical chapter contrasts learning in visuomotor rotations of 40° with learning left-right reversals during reaching movements. During left-right reversals, speed-accuracy trade-offs increased and offline gains emerged, whereas during visual rotations, speed-accuracy trade-offs remained constant and instead of offline gains, there was offline forgetting. I argue that these dissociations reflect differences in the underlying learning mechanisms: acquisition and recalibration. The second empirical chapter tests whether the dissociation based on time-accuracy trade-offs reveals a general property of recalibration or whether instead the interpretation is limited to the specific contrast between left-right reversals and visuomotor rotations. When the size of the prediction error– the difference between intended and perceived movement – was gradually increased participants switched from recalibration to control policy acquisition. This switching point can be derived by considering the role of internal models in recalibration: If the internal model that learns from errors and the environment are too dissimilar – e.g. in left-right reversal and large rotations– recalibration would cause the system to learn from errors in the wrong way, such that prediction errors would increase further. To address this problem the final empirical chapter explores if the way the system learns from errors can be reversed. In conclusion, the results provide behavioral criteria to differentiate between adaptation and skill learning. By exploring the boundaries of recalibration this thesis contributes to a more principled understanding of the mechanisms involved in adaptation and skill learning

Motor Adaptation and Automaticity in People with Parkinson’s Disease and Freezing of Gait

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by cell death in the substantia nigra pars compacta, resulting in motor symptoms of tremor, rigidity, bradykinesia and gait impairment. Freezing of gait (FOG) is one serious gait disturbance, characterized by a transient inability produce effective stepping during walking and turning, and affects roughly half of people with PD at some point during their disease. Despite the ongoing research on the behavioral, neurological, and cognitive characteristics of people with FOG (PD+FOG), the mechanisms underlying freezing are still poorly understood. The overall aim of this work was to further investigate motor behavior in PD+FOG to provide insight into its potential mechanisms. The first experiment investigated possible cerebellar dysfunction in PD+FOG by examining visuomotor adaptation, a well-known cerebellar-dependent process. We found that there were no differences in reaching or walking adaptation between freezers and non-freezers, however non-freezers exhibited smaller after-effects compared to freezers and healthy older adults. Furthermore, adults with PD, as well as older and younger adults adapt walking patterns slower than reaching patterns, indicating walking is a more complex task requiring greater sensorimotor processing to modify. Overall, this study showed that cerebellar function, in terms of its role in sensorimotor adaptation, is relatively preserved in PD and FOG. In the second experiment, we examined motor automaticity of saccadic eye movements and reaching. Reduced automaticity is a likely motor-cognitive mechanism that contributes to freezing behavior, however automaticity in other motor systems has yet to fully described. Using an anti-saccade task, we found that PD+FOG participants were slower to respond to both automatic and non-automatic eye movements, and had increased saccade velocity variability compared to PD-FOG and controls. These changes were not related to disease severity or general cognition. In contrast, both PD groups were slower to execute (greater latency) reaching movements during both pro- and anti-reaching, but no freezer non-freezer differences were noted. PD+FOG reached with lower peak velocity compared to older adults but were similar to PD-FOG during both automatic and non-automatic conditions. These data show that changes in automaticity and control exist outside locomotor centers, indicating freezing may be a global motor disturbance. Altogether, the work in this dissertation furthers our knowledge on motor control in PD+FOG and provides additional evidence that freezing affects non-gait motor function

Doctor in Philosophy

dissertationPreparing the nervous system prior to practicing a new task may be a viable way to augment motor learning. This approach, known as priming, attempts to make the nervous system more effective during practice by preparing it prior to practice. The development and adaptation of motor behavior occurs through a process of error-based learning. An error response in a cognitive task elicits an amplified neurophysiological response within the prefrontal cortex that is thought to indicate activation of the error monitoring system. This amplified neurophysiological response is indicative of an increase in error detection as a means to improve performance. Priming the error detection system might make error detection in a subsequent motor task easier and faster than if the system were not primed. This ultimately might result in improved learning. If successful, priming error detection may prove to effectively improve learning of new skills (or relearning of previously-learned motor skills) in rehabilitation. We evaluated the effect of priming error detection on learning a motor task. We hypothesized that priming error detection would result in improved motor performance throughout the learning process (up to one week) on the trained task and untrained tasks when compared to a group who was not primed for error detection. Thirty healthy young adults were randomized into two groups. Each group trained on a functional reaching task following completion of their respective priming task. Motor performance on the trained task and two other untrained tasks were assessed one day after training and one week after training. Another group was recruited as a no-training group to determine if improvements on the untrained tasks were due to motor skill transfer. Results of this study demonstrated that priming error detection just prior to training may increase the rate, but not the amount, of motor task learning. Further, the groups improvement on the untrained tasks (i.e., transfer tasks) was not due to motor skill transfer as the no-training group improved a similar amount. Collectively, priming error detection prior to motor training may be a viable method for augmenting learning of a motor task. Further, the results suggesting that transfer did not occur should be interpreted cautiously as our testing conditions may have caused sufficient repetitions of the transfer tasks throughout the protocol that a learning effect occurred

Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy

© 2018 The Author(s) It is uncertain how vision and proprioception contribute to adaptation of voluntary arm movements. In normal participants, adaptation to imposed forces is possible with or without vision, suggesting that proprioception is sufficient; in participants with proprioceptive loss (PL), adaptation is possible with visual feedback, suggesting that proprioception is unnecessary. In experiment 1 adaptation to, and retention of, perturbing forces were evaluated in three chronically deafferented participants. They made rapid reaching movements to move a cursor toward a visual target, and a planar robot arm applied orthogonal velocity-dependent forces. Trial-by-trial error correction was observed in all participants. Such adaptation has been characterized with a dual-rate model: a fast process that learns quickly, but retains poorly and a slow process that learns slowly and retains well. Experiment 2 showed that the PL participants had large individual differences in learning and retention rates compared to normal controls. Experiment 3 tested participants’ perception of applied forces. With visual feedback, the PL participants could report the perturbation’s direction as well as controls; without visual feedback, thresholds were elevated. Experiment 4 showed, in healthy participants, that force direction could be estimated from head motion, at levels close to the no-vision threshold for the PL participants. Our results show that proprioceptive loss influences perception, motor control and adaptation but that proprioception from the moving limb is not essential for adaptation to, or detection of, force fields. The differences in learning and retention seen between the three deafferented participants suggest that they achieve these tasks in idiosyncratic ways after proprioceptive loss, possibly integrating visual and vestibular information with individual cognitive strategies