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Leib R, Howard IS, Millard M, Franklin DW. Behavioral Motor Performance. Compr Physiol 2023; 14:5179-5224. [PMID: 38158372 DOI: 10.1002/cphy.c220032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
The human sensorimotor control system has exceptional abilities to perform skillful actions. We easily switch between strenuous tasks that involve brute force, such as lifting a heavy sewing machine, and delicate movements such as threading a needle in the same machine. Using a structure with different control architectures, the motor system is capable of updating its ability to perform through our daily interaction with the fluctuating environment. However, there are issues that make this a difficult computational problem for the brain to solve. The brain needs to control a nonlinear, nonstationary neuromuscular system, with redundant and occasionally undesired degrees of freedom, in an uncertain environment using a body in which information transmission is subject to delays and noise. To gain insight into the mechanisms of motor control, here we survey movement laws and invariances that shape our everyday motion. We then examine the major solutions to each of these problems in the three parts of the sensorimotor control system, sensing, planning, and acting. We focus on how the sensory system, the control architectures, and the structure and operation of the muscles serve as complementary mechanisms to overcome deviations and disturbances to motor behavior and give rise to skillful motor performance. We conclude with possible future research directions based on suggested links between the operation of the sensorimotor system across the movement stages. © 2024 American Physiological Society. Compr Physiol 14:5179-5224, 2024.
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Affiliation(s)
- Raz Leib
- Neuromuscular Diagnostics, TUM School of Medicine and Health, Department of Health and Sport Sciences, Technical University of Munich, Munich, Germany
| | - Ian S Howard
- School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, UK
| | - Matthew Millard
- Institute of Sport and Movement Science, University of Stuttgart, Stuttgart, Germany
- Institute of Engineering and Computational Mechanics, University of Stuttgart, Stuttgart, Germany
| | - David W Franklin
- Neuromuscular Diagnostics, TUM School of Medicine and Health, Department of Health and Sport Sciences, Technical University of Munich, Munich, Germany
- Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich, Munich, Germany
- Munich Data Science Institute (MDSI), Technical University of Munich, Munich, Germany
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Orschiedt J, Franklin DW. Learning context shapes bimanual control strategy and generalization of novel dynamics. PLoS Comput Biol 2023; 19:e1011189. [PMID: 38064495 PMCID: PMC10732368 DOI: 10.1371/journal.pcbi.1011189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 12/20/2023] [Accepted: 11/15/2023] [Indexed: 12/21/2023] Open
Abstract
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. While one group was provided with training movements in which this association was evident, the other group was trained on conditions in which this association was ambiguous. After adaptation, we tested the encoding of the learned motor memory by measuring the generalization to new movement combinations. While both groups adapted to the novel dynamics, the evident group showed a weighted encoding of the learned motor memory based on movements of the other (right) hand, whereas the ambiguous group exhibited mainly same (left) hand encoding in bimanual trials. Despite these differences, both groups demonstrated partial generalization to unimanual movements of the left hand. Our results show that motor memories can be encoded depending on the motion of other limbs, but that the training conditions strongly shape the encoding of the motor memory formation and determine the generalization to novel contexts.
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Affiliation(s)
- Jonathan Orschiedt
- Neuromuscular Diagnostics, Department Health and Sport Sciences, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - David W. Franklin
- Neuromuscular Diagnostics, Department Health and Sport Sciences, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich, Munich, Germany
- Munich Data Science Institute (MDSI), Technical University of Munich, Munich, Germany
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Izadi M, Franklin S, Bellafiore M, Franklin DW. Motor Learning in Response to Different Experimental Pain Models Among Healthy Individuals: A Systematic Review. Front Hum Neurosci 2022; 16:863741. [PMID: 35399361 PMCID: PMC8987932 DOI: 10.3389/fnhum.2022.863741] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 02/28/2022] [Indexed: 12/30/2022] Open
Abstract
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. Despite a number of studies investigating the role of pain on the learning process, there is still no systematic review to summarize and critically assess investigations regarding this topic in the literature. Here in this systematic review, we summarize and critically evaluate studies that examined the influence of experimental pain on motor learning. Seventeen studies that exclusively assessed the effect of experimental pain models on motor learning among healthy human individuals were included for this systematic review, carried out based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. The results of the review revealed there is no consensus regarding the effect of pain on the skill learning acquisition and retention. However, several studies demonstrated that participants who experienced pain continued to express a changed motor strategy to perform a motor task even 1 week after training under the pain condition. The results highlight a need for further studies in this area of research, and specifically to investigate whether pain has different effects on motor learning depending on the type of motor task.
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Affiliation(s)
- Mohammad Izadi
- Sport and Exercise Research Unit, Department of Psychology, Educational Sciences and Human Movement, University of Palermo, Palermo, Italy
| | - Sae Franklin
- Institute for Cognitive Systems, Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany
| | - Marianna Bellafiore
- Sport and Exercise Research Unit, Department of Psychology, Educational Sciences and Human Movement, University of Palermo, Palermo, Italy
- *Correspondence: Marianna Bellafiore,
| | - David W. Franklin
- Neuromuscular Diagnostics, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
- Munich School of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany
- Munich Data Science Institute, Technical University of Munich, Munich, Germany
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Forano M, Schween R, Taylor JA, Hegele M, Franklin DW. Direct and indirect cues can enable dual adaptation, but through different learning processes. J Neurophysiol 2021; 126:1490-1506. [PMID: 34550024 DOI: 10.1152/jn.00166.2021] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
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. We propose that these mixed results may arise from two major classes of cues: "direct" cues, which are part of the dynamic state and "indirect" cues, which are not. We hypothesized that explicit strategies would primarily account for the adaptation of an indirect color cue but would be limited to simple tasks, whereas a direct visual separation cue would allow implicit adaptation regardless of task complexity. To test this idea, we investigated the relative contribution of implicit and explicit learning in relation to contextual cue type (colored or visually shifted workspace) and task complexity (1 or 8 targets) in a dual-adaptation task. We found that the visual workspace location cue enabled adaptation across conditions primarily through implicit adaptation. In contrast, we found that the color cue was largely ineffective for dual adaptation, except in a small subset of participants who appeared to use explicit strategies. Our study suggests that the previously inconclusive role of color cues in dual adaptation may be explained by differential contribution of explicit strategies across conditions.NEW & NOTEWORTHY We present evidence that learning of context-dependent dynamics proceeds via different processes depending on the type of sensory cue used to signal the context. Visual workspace location enabled learning different dynamics implicitly, presumably because it directly enters the dynamic state estimate. In contrast, a color cue was only successful where learners were apparently able to leverage explicit strategies to account for changed dynamics. This suggests a unification for the previously inconclusive role of color cues.
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Affiliation(s)
- Marion Forano
- Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Raphael Schween
- Department of Psychology and Sport Science, Justus Liebig University, Giessen, Germany.,Department of Psychology, Philipps-University, Marburg, Germany
| | - Jordan A Taylor
- Department of Psychology, Princeton University, Princeton, New Jersey
| | - Mathias Hegele
- Department of Psychology and Sport Science, Justus Liebig University, Giessen, Germany.,Center for Mind, Brain and Behavior, Universities of Marburg and Giessen, Marburg and Giessen, Germany
| | - David W Franklin
- Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany.,Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany.,Munich Data Science Institute, Technical University of Munich, Munich, Germany
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Schween R, McDougle SD, Hegele M, Taylor JA. Assessing explicit strategies in force field adaptation. J Neurophysiol 2020; 123:1552-1565. [PMID: 32208878 PMCID: PMC7191530 DOI: 10.1152/jn.00427.2019] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 02/12/2020] [Accepted: 03/19/2020] [Indexed: 02/06/2023] Open
Abstract
In recent years, it has become increasingly clear that a number of learning processes are at play in visuomotor adaptation tasks. In addition to implicitly adapting to a perturbation, learners can develop explicit knowledge allowing them to select better actions in responding to it. Advances in visuomotor rotation experiments have underscored the important role of such "explicit learning" in shaping adaptation to kinematic perturbations. Yet, in adaptation to dynamic perturbations, its contribution has been largely overlooked. We therefore sought to approach the assessment of explicit learning in adaptation to dynamic perturbations, by developing two novel modifications of a force field experiment. First, we asked learners to abandon any cognitive strategy before selected force channel trials to expose consciously accessible parts of overall learning. Here, learners indeed reduced compensatory force compared with standard Catch channels. Second, we instructed a group of learners to mimic their right hand's adaptation by moving with their naïve left hand. While a control group displayed negligible left hand force compensation, the mimicking group reported forces that approximated right hand adaptation but appeared to under-report the velocity component of the force field in favor of a more position-based component. Our results highlight the viability of explicit learning as a potential contributor to force field adaptation, though the fraction of learning under participants' deliberate control on average remained considerably smaller than that of implicit learning, despite task conditions favoring explicit learning. The methods we employed provide a starting point for investigating the contribution of explicit strategies to force field adaptation.NEW & NOTEWORTHY While the contribution of explicit learning has been increasingly studied in visuomotor adaptation, its contribution to force field adaptation has not been studied extensively. We employed two novel methods to assay explicit learning in a force field adaptation task and found that learners can voluntarily control aspects of compensatory force production and manually report it with their untrained limb. This supports the general viability of the contribution of explicit learning also in force field adaptation.
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Affiliation(s)
- Raphael Schween
- Neuromotor Behavior Laboratory, Department of Psychology & Sport Science, Justus-Liebig-University Giessen, Giessen, Germany
| | - Samuel D McDougle
- Department of Psychology, University of California, Berkeley, California
| | - Mathias Hegele
- Neuromotor Behavior Laboratory, Department of Psychology & Sport Science, Justus-Liebig-University Giessen, Giessen, Germany
- Center for Mind, Brain and Behavior, Universities of Marburg and Giessen, Marburg, Germany
| | - Jordan A Taylor
- Intelligent Performance and Adaptation Laboratory, Department of Psychology, Princeton University, Princeton, New Jersey
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Howard IS, Franklin S, Franklin DW. Asymmetry in kinematic generalization between visual and passive lead-in movements are consistent with a forward model in the sensorimotor system. PLoS One 2020; 15:e0228083. [PMID: 31995588 PMCID: PMC6988934 DOI: 10.1371/journal.pone.0228083] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 01/07/2020] [Indexed: 11/18/2022] Open
Abstract
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. Purely visual or purely passive lead-in movements exhibit different angular generalization functions of this motor memory as the lead-in movements are modified, suggesting different neural representations. However, we currently have no understanding of how different movement kinematics (distance, speed or duration) affect this recall process and the formation of independent motor memories. Here we investigate such kinematic generalization for both passive and visual lead-in movements to probe their individual characteristics. After participants adapted to opposing force fields using training lead-in movements, the lead-in kinematics were modified on random trials to test generalization. For both visual and passive modalities, recalled compensation was sensitive to lead-in duration and peak speed, falling off away from the training condition. However, little reduction in force was found with increasing lead-in distance. Interestingly, asymmetric transfer between lead-in movement modalities was also observed, with partial transfer from passive to visual, but very little vice versa. Overall these tuning effects were stronger for passive compared to visual lead-ins demonstrating the difference in these sensory inputs in regulating motor memories. Our results suggest these effects are a consequence of state estimation, with differences across modalities reflecting their different levels of sensory uncertainty arising as a consequence of dissimilar feedback delays.
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Affiliation(s)
- Ian S. Howard
- Centre for Robotics and Neural Systems, School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, England, United Kingdom
| | - Sae Franklin
- Department of Electrical and Computer Engineering, Institute for Cognitive Systems, Technical University of Munich, Munich, Germany
| | - David W. Franklin
- Neuromuscular Diagnostics, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
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Schween R, Taylor JA, Hegele M. Plan-based generalization shapes local implicit adaptation to opposing visuomotor transformations. J Neurophysiol 2018; 120:2775-2787. [PMID: 30230987 PMCID: PMC6442918 DOI: 10.1152/jn.00451.2018] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The human ability to use different tools demonstrates our capability of forming and maintaining multiple, context-specific motor memories. Experimentally, this has been investigated in dual adaptation, where participants adjust their reaching movements to opposing visuomotor transformations. Adaptation in these paradigms occurs by distinct processes, such as strategies for each transformation or the implicit acquisition of distinct visuomotor mappings. Although distinct, transformation-dependent aftereffects have been interpreted as support for the latter, they could reflect adaptation of a single visuomotor map, which is locally adjusted in different regions of the workspace. Indeed, recent studies suggest that explicit aiming strategies direct where in the workspace implicit adaptation occurs, thus potentially serving as a cue to enable dual adaptation. Disentangling these possibilities is critical to understanding how humans acquire and maintain motor memories for different skills and tools. We therefore investigated generalization of explicit and implicit adaptation to untrained movement directions after participants practiced two opposing cursor rotations, which were associated with the visual display being presented in the left or right half of the screen. Whereas participants learned to compensate for opposing rotations by explicit strategies specific to this visual workspace cue, aftereffects were not cue sensitive. Instead, aftereffects displayed bimodal generalization patterns that appeared to reflect locally limited learning of both transformations. By varying target arrangements and instructions, we show that these patterns are consistent with implicit adaptation that generalizes locally around movement plans associated with opposing visuomotor transformations. Our findings show that strategies can shape implicit adaptation in a complex manner. NEW & NOTEWORTHY Visuomotor dual adaptation experiments have identified contextual cues that enable learning of separate visuomotor mappings, but the underlying representations of learning are unclear. We report that visual workspace separation as a contextual cue enables the compensation of opposing cursor rotations by a combination of explicit and implicit processes: Learners developed context-dependent explicit aiming strategies, whereas an implicit visuomotor map represented dual adaptation independent from arbitrary context cues by local adaptation around the explicit movement plan.
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Affiliation(s)
- Raphael Schween
- Neuromotor Behavior Laboratory, Department of Sport Science, Justus Liebig University , Giessen , Germany
| | - Jordan A Taylor
- Intelligent Performance and Adaptation Laboratory, Department of Psychology, Princeton University , Princeton, New Jersey
| | - Mathias Hegele
- Neuromotor Behavior Laboratory, Department of Sport Science, Justus Liebig University , Giessen , Germany
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Howard IS, Ford C, Cangelosi A, Franklin DW. Active lead-in variability affects motor memory formation and slows motor learning. Sci Rep 2017; 7:7806. [PMID: 28798355 PMCID: PMC5552870 DOI: 10.1038/s41598-017-05697-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 06/19/2017] [Indexed: 11/09/2022] Open
Abstract
Rapid learning can be critical to ensure elite performance in a changing world or to recover basic movement after neural injuries. Recently it was shown that the variability of follow-through movements affects the rate of motor memory formation. Here we investigate if lead-in movement has a similar effect on learning rate. We hypothesized that both modality and variability of lead-in movement would play critical roles, with simulations suggesting that only changes in active lead-in variability would exhibit slower learning. We tested this experimentally using a two-movement paradigm, with either visual or active initial lead-in movements preceeding a second movement performed in a force field. As predicted, increasing active lead-in variability reduced the rate of motor adaptation, whereas changes in visual lead-in variability had little effect. This demonstrates that distinct neural tuning activity is induced by different lead-in modalities, subsequently influencing the access to, and switching between, distinct motor memories.
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Affiliation(s)
- Ian S Howard
- Centre for Robotics and Neural Systems, School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, United Kingdom.
| | - Christopher Ford
- Centre for Robotics and Neural Systems, School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, United Kingdom
| | - Angelo Cangelosi
- Centre for Robotics and Neural Systems, School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, United Kingdom
| | - David W Franklin
- Neuromuscular Diagnostics, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
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