Influence of Error-Augmentation on the Dynamics of Visuomotor Skill Acquisition: Insights from Proxy-Process Models

Our study addresses the critical question of how learners acquire skills without the constant crutch of feedback, utilizing a specialized training approach with intermittent feedback. Despite recognized benefits in skill retention, the underlying mechanisms of intermittent feedback in motor control neuroscience remain elusive. Leveraging a previously published dataset from visuomotor learning experiments with intermittent feedback, we tested a wide range of proxy-process models that posit the presence of an inferred error signal even when an explicit sensory performance is not present. Furthermore, these proxy-process models investigated the impact of error-augmentation (EA) training on visuomotor learning dynamics. Rigorous cross-validation consistently identified a second-order proxy-process model structure accurately predicting motor learning across subjects and learning tasks. Model parameters elucidated the varying influences of EA settings on the rates of change in error, inter-trial variability, and steady-state performance. We then introduced a dynamic-Proxy support Multi-Rate Motor Learning (dPxMRML) model, which shed light on EA's effects on the fast and slow learning dynamics. The dPxMRML model accurately predicted subjects' performance during and beyond training phases, highlighting EA settings conducive to long-term retention. This research yields crucial insights for personalized training program design, applicable in neuro-rehabilitation, sports, and performance training.

Uncovering clinical rehabilitation technology trends: field observations, mixed methods analysis, and data visualization

Objective

To analyze real-world rehabilitation technology (RT) use, with a view toward enhancing RT development and adoption.

Design

A convergent, mixed-methods study using direct field observations, semi-structured templates, and summative content analysis.

Setting

Ten neurorehabilitation units in a single health system.

Participants

3 research clinicians (1OT, 2PTs) observed ∼60 OTs and 70 PTs in inpatient; ∼18 OTs and 30 PTs in outpatient.

Interventions

Not applicable.

Main Outcome Measures

Characteristics of RT, time spent setting up and using RT, and clinician behaviors.

Results

90 distinct devices across 15 different focus areas were inventoried. 329 RT-uses were documented over 44 hours with 42% of inventoried devices used. RT was used more during interventions (72%) than measurement (28%). Intervention devices used frequently were balance/gait (39%), strength/endurance (30%), and transfer/mobility training (16%). Measurement devices were frequently used to measure vitals (83%), followed by grip strength (7%), and upper extremity function (5%). Device characteristics were predominately AC-powered (56%), actuated (57%), monitor-less (53%), multi-use (68%), and required little familiarization (57%). Set-up times were brief (mean ± SD = 3.8±4.21 and 0.8±1.3 for intervention and measurement, respectively); more time was spent with intervention RT (25.6±15) than measurement RT (7.3±11.2). RT nearly always involved verbal instructions (72%) with clinicians providing more feedback on performance (59.7%) than on results (30%). Therapists' attention was split evenly between direct attention towards the patient during clinician treatment (49.7%) and completing other tasks such as documentation (50%).

Conclusions

Even in a tech-friendly hospital, majority of available RT were observed un-used, but identifying these usage patterns is crucial to predict eventual adoption of new designs from earlier stages of RT development. An interactive data visualization page supplement is provided to facilitate this study.

A highly contiguous genome assembly for the pocket mouse Perognathus longimembris longimembris

The little pocket mouse, Perognathus longimembris, and its nine congeners are small heteromyid rodents found in arid and seasonally arid regions of Western North America. The genus is characterized by behavioral and physiological adaptations to dry and often harsh environments, including nocturnality, seasonal torpor, food caching, enhanced osmoregulation, and a well-developed sense of hearing. Here we present a genome assembly of Perognathus longimembris longimembris generated from PacBio HiFi long read and Omni-C chromatin-proximity sequencing as part of the California Conservation Genomics Project. The assembly has a length of 2.35 Gb, contig N50 of 11.6 Mb, scaffold N50 of 73.2 Mb, and includes 93.8% of the BUSCO Glires genes. Interspersed repetitive elements constitute 41.2% of the genome. A comparison with the highly endangered Pacific pocket mouse, P. l. pacificus, reveals broad synteny. These new resources will enable studies of local adaptation, genetic diversity, and conservation of threatened taxa.

Statistical evaluation of tongue capability with visual feedback

BACKGROUND

Analysis of tongue movement would benefit from a reference showcasing healthy tongue capability. We aimed to develop a reference of tongue capability and evaluated the role of visual feedback on the expression of movement.

METHODS

Using a wireless tracking intraoral wearable device, we composed probability distributions of the tongue tip as subjects were asked to explore the entire sensing surface area. Half of the 32 subjects received live visual feedback of the location of the center of the tongue tip contact.

RESULTS

We observed that the visual feedback group was 51.0% more consistent with each other in the position domain, explored 21.5% more sensing surface area, and was 50.7% more uniformly distributed. We found less consistent results when we evaluated velocity and acceleration.

CONCLUSION

Visual feedback best established a healthy capability reference which can be used for designing new interfaces, quantifying tongue ability, developing new diagnostic and rehabilitation techniques, and studying underlying mechanisms of tongue motor control.

Specimen collection is essential for modern science

Natural history museums are vital repositories of specimens, samples and data that inform about the natural world; this Formal Comment revisits a Perspective that advocated for the adoption of compassionate collection practices, querying whether it will ever be possible to completely do away with whole animal specimen collection.

Error Fields: Personalized robotic movement training that augments one's more likely mistakes

Control of movement is learned and uses error feedback during practice to predict actions for the next movement. We have shown that augmenting error can enhance learning, but while such findings are encouraging the methods need to be refined to accommodate a person's individual reactions to error. The current study evaluates error fields (EF) method, where the interactive robot tempers its augmentation when the error is less likely. 22 healthy participants were asked to learn moving with a visual transformation, and we enhanced the training with error fields. We found that training with error fields led to greatest reduction in error. EF training reduced error 264% more than controls who practiced without error fields, but subjects learned more slowly than our previous error magnification technique. We also found a relationship between the amount of learning and how much variability was induced by the error augmentation treatments, most likely leading to better exploration and discovery of the causes of error. These robotic training enhancements should be further explored in combination to optimally leverage error statistics to teach people how to move better.

Taxonomic reassessment of the Little pocket mouse, Perognathus longimembris (Rodentia, Heteromyidae) of southern California and northern Baja California

The Little pocket mouse (Perognathus longimembris) encompasses 15 to 16 currently recognized subspecies, six of which are restricted to southern California and adjacent northern Baja California.  Using cranial geomorphometric shape parameters and dorsal color variables we delineate six regional groups of populations from this area that we recognize as valid, but these differ in name combination and geographic range from the current taxonomy.  We resurrect two names from their current placement in synonymies, synonymize two currently recognized subspecies, and we reassign a third.  Importantly, we restrict the U. S. Federally endangered Pacific pocket mouse (P. l. pacificus Mearns) to the vicinity of its type locality at the mouth of the Tijuana River in the southwestern corner of San Diego County and resurrect P. l. cantwelli von Bloeker for the other two population segments along the coast, those that span the northwestern corner of San Diego County and adjacent Orange County and that in coastal Los Angeles County.  The name cantwelli would now apply to the only extant populations of the Pacific pocket mouse, a reassignment with obvious management implications.  Our taxonomic decisions also reconfigure the ranges of other subspecies of conservation concern, notably P. l. bangsi Mearns and P. l. brevinasus Osgood.

Thermal adaptation of pelage in desert rodents balances cooling and insulation

Phenotypic convergence across distantly related taxa can be driven by similar selective pressures from the environment or intrinsic constraints. The roles of these processes on physiological strategies, such as homeothermy, are poorly understood. We studied the evolution of thermal properties of mammalian pelage in a diverse community of rodents inhabiting the Mojave Desert, USA. We used a heat flux device to measure the thermal insulation of museum specimens and determined whether thermal properties were associated with habitat preferences while assessing phylogenetic dependence. Species that prefer arid habitats exhibited lower conductivity and thinner pelage relative to species with other habitat preferences. Despite being thinner, the pelage of arid species exhibited comparable insulation to the pelage of the other species due to its lower conductivity. Thus, arid species have insulative pelage while simultaneously benefitting from thin pelage that promotes convective cooling. We found no evidence of intrinsic constraints or phylogenetic dependence, indicating pelage readily evolves to environmental pressures. Thermoregulatory simulations demonstrated that arid specialists reduced energetic costs required for homeothermy by 14.5% by evolving lower conductivity, providing support for adaptive evolution of pelage. Our study indicates that selection for lower energetic requirements of homeothermy has shaped evolution of pelage thermal properties.

Electro-prosthetic E-skin Successfully Delivers Finger Aperture Distance by Electro-Prosthetic Proprioception (EPP)

Electronic skin (E-skin) is an emerging wearable device typically used to mimic the function of the human skin, mainly by replicating the role of tactile sensory receptors in the skin. This study showed an interesting modification of the E-skin, called an electro-prosthetic E-skin, which adds the functionality of distance sensing and stimulation of the palmar digital nerve. The electro-prosthetic E-skin operates as a closed loop to deliver the finger aperture distance information to the nervous system. This E-skin was implemented as an additional layer mounted to the original human skin, to be worn on the fingertip with a thin silicone substrate. The E-skin was designed to be mounted onto the index fingertip, to deliver the distance information between the fingertips and to enhance the finger aperture distance control. In this study, we demonstrated that electro-prosthetic proprioception (EPP), implemented with the electro-prosthetic E-skin, successfully delivered the distance information between the fingertips and enhanced the finger aperture distance control accuracy. Clinical Relevance- Presented electro-prosthetic E-skin delivering finger aperture distance via electro-prosthetic proprioception (EPP) will enhance accuracy of the finger aperture distance control. This technology can be applied to the neurosurgery to minimize unforced errors caused by the limited human control accuracy over the fingertip.

Automated sleep detection reveals differences in sleep patterns in an animal model of neocortical epilepsy

Sleep in epilepsy is best studied in longitudinal preclinical animal models, where state changes can have significant effects on epileptic activities. Voluminous data makes it very difficult to mark sleep stages manually. This demands an automated way to detect sleep and wake states. We developed an approach to characterize sleep-wake states in continuous video-electroencephalography (EEG) recordings in animals. We compared brute force approach based on frequency band-power based thresholding with machine learning algorithms to detect sleep in 600 hours of EEG data from 4 epileptic and 2 control animals. We found that conventional delta and theta band-powers were prominent in sleep; however, this was not sufficient to detect sleep algorithmically. We therefore extracted a set of novel frequency bands to robustly differentiate individual sleep states by using brute-force algorithm and machine learning models, among which k-nearest neighbors (KNN) was the best predictor of sleep with 94% accuracy. We subsequently characterized sleep patterns in animals with chronically induced epileptic spiking in the neocortex from tetanus toxin injections using brute-force algorithm. We found that epileptic spiking animals (without seizures) sleep more frequently, with significantly longer sleep segments and overall daily sleep time, as compared to control animals. This automated algorithm could help expedite sleep studies and help us understand the relationship between sleep and patients with epilepsy.

Electro-prosthetic E-skin Successfully Delivers Elbow Joint Angle Information by Electro-prosthetic Proprioception (EPP)

Neurotraumas and neurological diseases often result in compromised proprioceptive feedback, which plays a critical role in motor control by delivering real-time position information. Electro-prosthetic proprioception (EPP) using frequency-modulated electrotactile feedback is a promising solution, as it can deliver proprioceptive information such as a joint angle via tactile channel. Prior works demonstrated that EPP successfully delivered distance information between the end effector and the target object. In this study, we implemented the electronic skin (E-skin) monitoring the elbow joint angle and delivering it to the nervous system via tactile channel. We also demonstrated that EPP improved both accuracy and precision of the elbow joint angle control. The gyroscope measuring the elbow joint angle and electrodes delivering electrotactile feedback were integrated together as a skin using thin silicon coating and polyurethane film. We call this novel E-skin, monitoring and delivering joint angle information, as an electro-prosthetic E-skin. Elbow joint angle matching test with two healthy human subjects showed that the EPP, via electro-prosthetic E-skin, enhanced 101.7% accuracy and 63.8% precision in elbow joint angle control. Clinical Relevance-Presented electro-prosthetic E-skin will address the compromised proprioceptive feedback by delivering joint angle information by electro-prosthetic proprioception (EPP) via tactile channel. This novel E-skin will open up a new path to assist and rehabilitative motor control problems after neurotraumas and neurological diseases.

Upper Extremity Functional Rehabilitation for Stroke Survivors Using Error-Augmented Visual Feedback: Interim Results

Stroke rehabilitation is often terminated once a plateau in motor recovery is observed, but new training modalities have demonstrated that further functional improvement is possible after the onset of the chronic phase. In particular, feedback technologies augmenting error proved to foster the relearning process. Here we explore the possibility of a robot-free implementation of Error-Augmentation (EA), where only visual feedback is distorted. We present the interim results from our ongoing blinded, randomized, controlled clinical trial testing the efficacy of parallel bimanual reaching with visual EA. Subjects trained in the virtual environment in 45-minute sessions, three times a week, for three weeks, half with and half without EA. A blinded therapist performed clinical evaluations before, 1 week after, and two months after training. Available results showed that both groups significantly improved. An advantage in the treatment group could be tracked at all time points, but no statistical significance was detectable between groups. Gains in the two groups were found to be compatible with the results of previous studies using robots and may prove to have similar effectiveness without the need for a costly and complicated robotic device. One new finding was that EA caused significantly higher inter-trial variability.

Human-Human Connected Dyads Learning a Visuomotor Rotation in a Targeted Reaching Task

Little is known about how two people physically coupled together (a dyad) can accomplish tasks. In a pilot study we tested how healthy inexperienced and experienced dyads learn to repeatedly reach to a target and stop while challenged with a 30 degree visuomotor rotation. We employed the Pantograph investigational device that haptically couples partners movements while providing cursor feedback, and we measured the amount and speed of learning to test a prevailing hypothesis: dyads with no experience learn faster than an experienced person coupled with a novice. We found significant straightening of movements for dyads in terms of amount of learning (2.662±0.102 cm and 2.576±0.024 cm for the novice-novice and novice-experienced groups) at rapid rates (time constants of 17.83 ± 2.85 and 18.17.17±6.72 movements), which was nearly half the learning time as solo individuals' studies. However, we found no differences between the novice-novice and experienced-novice groups, though retrospectively our power was only 3 percent. This pilot study demonstrates new opportunities to investigate the advantages of partner-facilitated learning with solely haptic communication which and can lead to insights on control in human physical interactions and can guide the design of future human-robot-human interaction systems.

Direction-Specific Iterative Tuning of Motor Commands With Local Generalization During Randomized Reaching Practice Across Movement Directions

During motor learning, people often practice reaching in variety of movement directions in a randomized sequence. Such training has been shown to enhance retention and transfer capability of the acquired skill compared to the blocked repetition of the same movement direction. The learning system must accommodate such randomized order either by having a memory for each movement direction, or by being able to generalize what was learned in one movement direction to the controls of nearby directions. While our preliminary study used a comprehensive dataset from visuomotor learning experiments and evaluated the first-order model candidates that considered the memory of error and generalization across movement directions, here we expanded our list of candidate models that considered the higher-order effects and error-dependent learning rates. We also employed cross-validation to select the leading models. We found that the first-order model with a constant learning rate was the best at predicting learning curves. This model revealed an interaction between the learning and forgetting processes using the direction-specific memory of error. As expected, learning effects were observed at the practiced movement direction on a given trial. Forgetting effects (error increasing) were observed at the unpracticed movement directions with learning effects from generalization from the practiced movement direction. Our study provides insights that guide optimal training using the machine-learning algorithms in areas such as sports coaching, neurorehabilitation, and human-machine interactions.

A new living species of degu, genus Octodon (Hystricomorpha: Octodontidae)

We combine morphological (qualitative and quantitative data) and genetic (one mitochondrial and one nuclear gene) data from a large set of specimens of Octodon from the four currently recognized living species of the genus. The integration of the results (qualitative assessment, multivariate analysis of cranial measurements, and gene trees) allows us to state that 1) the current taxonomic scheme does not reflect the species diversity of Octodon; 2) in particular, as currently understood O. bridgesii likely is a complex of three species; 3) one of these, encompassing the southern populations of the genus, in the Araucanía Region (Chile) and Neuquén Province (Argentina), is named and described here as a new species; and 4) the mitochondrial gene tree departs from the nuclear gene tree with respect to O. pacificus and the new species here described.

Effects of robot viscous forces on arm movements in chronic stroke survivors: a randomized crossover study

Background

Our previous work showed that speed is linked to the ability to recover in chronic stroke survivors. Participants moving faster on the first day of a 3-week study had greater improvements on the Wolf Motor Function Test.

Methods

We examined the effects of three candidate speed-modifying fields in a crossover design: negative viscosity, positive viscosity, and a “breakthrough” force that vanishes after speed exceeds an individualized threshold.

Results

Negative viscosity resulted in a significant speed increase when it was on. No lasting after effects on movement speed were observed from any of these treatments, however, training with negative viscosity led to significant improvements in movement accuracy and smoothness.

Conclusions

Our results suggest that negative viscosity could be used as a treatment to augment the training process while still allowing participants to make their own volitional motions in practice.

Trial registration

This study was approved by the Institutional Review Boards at Northwestern University (STU00206579) and the University of Illinois at Chicago (2018-1251).

A review of Euryoryzomys legatus (Rodentia, Sigmodontinae): morphological redescription, cytogenetics, and molecular phylogeny

The taxonomic history of Euryoryzomys legatus has been complex and controversial, being either included in the synonymy of other oryzomyine species or considered as a valid species, as in the most recent review of the genus. Previous phylogenetic analyses segregated E. legatus from E. russatus, its putative senior synonym, but recovered it nested within E. nitidus. A general lack of authoritative evaluation of morphological attributes, details of the chromosome complement, or other data types has hampered the ability to choose among alternative taxonomic hypotheses, and thus reach a general consensus for the status of the taxon. Herein we revisit the status of E. legatus using an integrated approach that includes: (1) a morphological review, especially centered on specimens from northwestern Argentina not examined previously, (2) comparative cytogenetics, and (3) phylogenetic reconstruction, using mitochondrial genes. Euryoryzomys legatus is morphologically and phylogenetically distinct from all other species-level taxa in the genus, but its 2n=80, FN=86 karyotype is shared with E. emmonsae, E. nitidus, and E. russatus. Several morphological and morphometric characters distinguish E. legatus from other species of Euryoryzomys, and we provide an amended diagnosis for the species. Morphological characters useful in distinguishing E. legatus from E. nitidus, its sister taxon following molecular analyses, include: larger overall size, dorsal fur with a strong yellowish brown to orange brown tinge, flanks and cheeks with an orange lateral line, ventral color grayish-white with pure white hairs present only on the chin, presence of a thin blackish eye-ring, tail bicolored, presence of an alisphenoid strut and a well-developed temporal and lambdoid crests in the skull, and a labial cingulum on M3. Molecular phylogenetic analyses recovered E. legatus as a monophyletic group with high support nested within a paraphyletic E. nitidus; genetic distances segregated members of both species, except for an exemplar of E. nitidus. Our integrated analyses reinforce E. legatus as a full species, but highlight that E. macconnelli, E. emmonsae, and E. nitidus each may be a species complex and worthy of systematic attention. Finally, we also evaluated the chromosome evolution of the genus within a phylogenetic context.

Haptic Coupling in Dyads Improves Motor Learning in a Simple Force Field

In dyadic motor learning, pairs of people learn the same motion while their limbs are loosely coupled together using haptic devices. Such coupled learning has been shown to outperform solo learning (including robot-guided learning) for simple one-degree-of-freedom tasks. However, results from more complex tasks are limited and sometimes conflicting. We thus evaluated coupled learning in a two-degree-of-freedom tracking task where participants also had to compensate for a simple force field. Participant pairs were split into two groups: an experiment group that experienced a compliant haptic coupling between participants' hands and a control group that did not. The study protocol consisted of 70 repetitions of 18.9-second tracking trials: 10 initial solo trials with no coupling, 50 "learning" trials (where participants in the experiment group were coupled), and 10 final solo trials with no coupling. The experiment group (coupled) improved their solo tracking performance both in the presence (p = 0.008) and absence (p <; 0.001) of the force field; however, the control group (no coupling) only improved their solo performance in the absence of the force field (p <; 0.001) but not in the presence of the field (p = 0.81). This suggests that dyadic motor learning can outperform solo learning for two-dimensional tracking motions in the presence of a simple force field, though the mechanism by which learning is improved is not yet clear.Clinical Relevance-As motor learning is critical for applications such as motor rehabilitation, dyadic training could be used to achieve a better overall outcome and a faster learning speed in these applications compared to solo training.

Key components of mechanical work predict outcomes in robotic stroke therapy

Background

Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots allow comprehensive methods for measuring practice behaviors, including the energetic input of the learner. Using data from our previous study of robot-assisted therapy, we examined how separate components of mechanical work contribute to predicting training outcomes.

Methods

Stroke survivors (n = 11) completed six sessions in two-weeks of upper extremity motor exploration (self-directed movement practice) training with customized forces, while a control group (n = 11) trained without assistance. We employed multiple regression analysis to predict patient outcomes with computed mechanical work as independent variables, including separate features for elbow versus shoulder joints, positive (concentric) and negative (eccentric), flexion and extension.

Results

Our analysis showed that increases in total mechanical work during therapy were positively correlated with our final outcome metric, velocity range. Further analysis revealed that greater amounts of negative work at the shoulder and positive work at the elbow as the most important predictors of recovery (using cross-validated regression, R² = 52%). However, the work features were likely mutually correlated, suggesting a prediction model that first removed shared variance (using PCA, R² = 65–85%).

Conclusions

These results support robotic training for stroke survivors that increases energetic activity in eccentric shoulder and concentric elbow actions.

Trial registration

ClinicalTrials.gov, Identifier: NCT02570256. Registered 7 October 2015 – Retrospectively registered,

Post-stroke motor deficits are most evident at frequencies near 125 Hz in EMG multivariate probability distributions

Muscle activity is widely measured to assess muscle condition in post-stroke patients. While many clinical researchers have relied on time-series analysis of muscle activity, the frequency domain could offer additional insight on motor impairment. Our previous work has characterized movement capabilities in stroke survivors across endpoint and joint kinematic variables while performing a self-directed motor exploration task. Our solution to managing such large volumes of data is to create personalized statistical profiles using multivariate probability distributions. In this study, we present frequency domain analysis of EMG distributions for chronic post-stroke survivors (N = 6) and healthy subjects (N = 5) to identify between group differences in muscle activity. Comparing probability density of muscle activity magnitudes, differences from healthy were most evident at 275 Hz. Unique aspects of each patient's deficits were most evident at 125 Hz. This is the first study to explore distributions of EMG in specific frequency bands for this patient population. Such identifiability could pinpoint specific motor deficits and track progress in neurologically impaired individuals that often have widely differing disease states.

Models of Motor Learning Generalization

This study used evidence from trial-by-trial errors to understand how humans can generalize what they learn across different movement directions while reaching. We trained 15 healthy subjects to reach in six directions in the presence of challenging visuomotor distortions. We then tested a number of candidate models suggested by the literature of how the brain might use error to improve performance. Our cross-validated results point to a discrete affine model whose generalization, or influence of practice in one direction to neighboring directions, is reduced nearly to zero by 60 degrees away, and the subjects learned 6.25 times more from the error that was observed at a movement direction than neighboring directions.

Geographic variation and evolutionary history of Dipodomys nitratoides (Rodentia: Heteromyidae), a species in severe decline

We examined geographic patterns of diversification in the highly impacted San Joaquin kangaroo rat, Dipodomys nitratoides, throughout its range in the San Joaquin Valley and adjacent basins in central California. The currently recognized subspecies were distinct by the original set of mensural and color variables used in their formal diagnoses, although the Fresno kangaroo rat (D. n. exilis) is the most strongly differentiated with sharp steps in character clines relative to the adjacent Tipton (D. n. nitratoides) and short-nosed (D. n. brevinasus) races. The latter two grade more smoothly into one another but still exhibit independent, and different, character clines within themselves. At the molecular level, as delineated by mtDNA cytochrome b sequences, most population samples retain high levels of diversity despite significant retraction in the species range and severe fragmentation of local populations in recent decades due primarily to landscape conversion for agriculture and secondarily to increased urbanization. Haplotype apportionment bears no relationship to morphologically defined subspecies boundaries. Rather, a haplotype network is shallow, most haplotypes are single-step variants, and the time to coalescence is substantially more recent than the time of species split between D. nitratoides and its sister taxon, D. merriami. The biogeographic history of the species within the San Joaquin Valley appears tied to mid-late Pleistocene expansion following significant drying of the valley resulting from the rain shadow produced by uplift of the Central Coastal Ranges.

Stroke Rehabilitation with Distorted Vision Perceived as Forces

The concept of augmenting error in interactive reaching training has shown promise, but the possibility of doing this robot-free, with only visual feedback, has not been tested. Here we present very early results from a visual distortion environment that shifts the subject's cursor in the direction of instantaneous error as if it is being pushed by a robot. This clinical test asked chronic stroke survivors to visit the laboratory three times a week for three weeks as they practiced a bimanual virtual reality task for approximately 40 minutes. Results show that both treatment and control patients improved from the practice (Fugyl Meyer average increase of 4.2), and a slight advantage is seen at this point in the treatment group. These vision-only results may prove compelling because removing the robot reduces expenses, intimidation, complexity, confounding effects, and failure modes.

Sparse Identification Of Motor Learning Using Proxy Process Models

Enhanced neurorehabilitation using robotic and virtual-reality technologies requires a computational framework that can readily assess the time course of motor learning in order to recommend optimal training conditions. Error-feedback plays an important role in the acquisition of motor skills for goal-directed movements by facilitating the learning of internal models. In this study, we investigated changes in movement errors during sparse and intermittent "catch" (no-vision) trials, which served as a "proxy" of the underlying process of internal model formations. We trained 15 healthy subjects to reach for visual targets under eight distinct visuomotor distortions, and we removed visual feedback (novision) intermittently. We tested their learning data from novision trials against our so-called proxy process models, which assumed linear, affine, and second-order model structures. In order to handle sparse (no-vision) observations, we allowed the proxy process models to either update trial-to-trial, predicting across voids of sparse samples or update sample-to-sample, disregarding the trial gaps. We exhaustively cross-validated our models across subjects and across learning tasks. The results revealed that the second-order model with trial-to-trial update best predicted the proxy process of visuomotor learning.

Temporal genomic contrasts reveal rapid evolutionary responses in an alpine mammal during recent climate change

Many species have experienced dramatic changes in their abundance and distribution during recent climate change, but it is often unclear whether such ecological responses are accompanied by evolutionary change. We used targeted exon sequencing of 294 museum specimens (160 historic, 134 modern) to generate independent temporal genomic contrasts spanning a century of climate change (1911-2012) for two co-distributed chipmunk species: an endemic alpine specialist (Tamias alpinus) undergoing severe range contraction and a stable mid-elevation species (T. speciosus). Using a novel analytical approach, we reconstructed the demographic histories of these populations and tested for evidence of recent positive directional selection. Only the retracting species showed substantial population genetic fragmentation through time and this was coupled with positive selection and substantial shifts in allele frequencies at a gene, Alox15, involved in regulation of inflammation and response to hypoxia. However, these rapid population and gene-level responses were not detected in an analogous temporal contrast from another area where T. alpinus has also undergone severe range contraction. Collectively, these results highlight that evolutionary responses may be variable and context dependent across populations, even when they show seemingly synchronous ecological shifts. Our results demonstrate that temporal genomic contrasts can be used to detect very recent evolutionary responses within and among contemporary populations, even in the face of complex demographic changes. Given the wealth of specimens archived in natural history museums, comparative analyses of temporal population genomic data have the potential to improve our understanding of recent and ongoing evolutionary responses to rapidly changing environments.

Modeling Nerve Compression in Carpal Tunnel Syndrome

Nerve function loss can result from a variety of conditions that are either sudden onset like head and spinal cord trauma or slowly develop from chronic pressure as in the case of carpal tunnel syndrome. In either case we see compression ofthe nerve ultimately resulting in axon demyelination and loss of signal conduction. For chronic conditions such as carpal tunnel syndrome, treatments focus on alleviating symptoms. Some patients undergo surgery which can be successful in relieving pressure on the median nerve by inflamed surrounding tendons. Symptoms of classical carpal tunnel syndrome have been debated and sometimes patients experiencing similar numbness and pain in the hand do not necessarily have the underlying condition of a compressed median nerve. Therefore, better markers are needed for determining true cases of nerve compression as well as clinical measures to indicate the need for surgical treatment. We have demonstrated a correlation between clinically observed nerve compression derived from MRI slides and clinically observed increases in conduction delay. We have done this by computationally modeling a myelinated axon with various levels of compression and finding the increase in conduction delay from a normal control with no compression. We show that conduction delay measurements could be used as a clinical tool to determine the amount of nerve compression present in a patient of mild carpal tunnel syndrome although further data is required to create a fully predictive model.

Error-augmented bimanual therapy for stroke survivors

BACKGROUND

Stroke recovery studies have shown the efficacy of bimanual training on upper limb functional recovery and others have shown the efficacy of feedback technology that augments error.

OBJECTIVE

In a double-blinded randomized controlled study (N = 26), we evaluated the short-term effects of bilateral arm training to foster functional recovery of a hemiparetic arm, with half of our subjects unknowingly also receiving error augmentation (where errors were visually and haptically enhanced by a robot).

METHODS

Twenty-six individuals with chronic stroke were randomly assigned to practice an equivalent amount of bimanual reaching either with or without error augmentation. Participants were instructed to coordinate both arms while reaching to two targets (one for each arm) in three 45-minute treatments per week for two weeks, with a follow-up visit after one week without treatment.

RESULTS

Subjects' 2-week gains in Fugl-Meyer score averaged 2.92, and we also observed improvements Wolf Motor Functional Ability Scale average 0.21, and Motor Activity Log of 0.58 for quantity and 0.63 for quality of life scores. The extra benefit of error augmentation over the three weeks became apparent in Fugl-Meyer score only after removing an outlier from consideration.

CONCLUSIONS

This modest advantage of error augmentation was detectable over a short interval encouraging further research in interactive self-rehabilitation systems that can enhance error motor recovery.

Regression techniques employing feature selection to predict clinical outcomes in stroke

It is not fully clear which measurable factors can reliably predict chronic stroke patients’ recovery of motor ability. In this analysis, we investigate the impact of patient demographic characteristics, movement features, and a three-week upper-extremity intervention on the post-treatment change in two widely used clinical outcomes—the Upper Extremity portion of the Fugl-Meyer and the Wolf Motor Function Test. Models based on LASSO, which in validation tests account for 65% and 86% of the variability in Fugl-Meyer and Wolf, respectively, were used to identify the set of salient demographic and movement features. We found that age, affected limb, and several measures describing the patient’s ability to efficiently direct motions with a single burst of speed were the most consequential in predicting clinical recovery. On the other hand, the upper-extremity intervention was not a significant predictor of recovery. Beyond a simple prognostic tool, these results suggest that focusing therapy on the more important features is likely to improve recovery. Such validation-intensive methods are a novel approach to determining the relative importance of patient-specific metrics and may help guide the design of customized therapy.

Reshaping Movement Distributions With Limit-Push Robotic Training

High-cost situations need to be avoided. However, occasionally, cost may only be learned by experience. Here, we tested whether an artificially induced unstable and invisible high-cost region, a "limit-push" force field, might reshape people's motion distributions. Healthy and neurologically impaired (chronic stroke) populations attempted 600 interceptions of a projectile while holding a robot handle that could render forces to the hand. The "limit-push," in the middle of the study, pushed the hand outward unless the hand stayed within a box-shaped region. Both healthy and some stroke survivors adapted through selection of safer actions, avoiding the high-cost regions (outside the box); they stayed more inside and even kept a greater distance from the box's boundaries. This was supported by other measures that showed subjects distributed their hand movements within the box more uniformly. These effects lasted a very short time after returning to the no-force condition. Although most robotic teaching approaches focus on shifting the mean, this limit-push treatment demonstrates how both mean and variance might be reshaped in motor training and neurorehabilitation.

Energetics during robot-assisted training predicts recovery in stroke

Clinical investigators have asserted patients should be active participants in the therapy process in stroke rehabilitation. While robotics introduces new tools for measurement and treatment of motor impairments, it also presents challenges for evaluating how much a patient contributes to observed movements during training. Our approach employs established methods of inverse dynamics combined with measurements of human motion and interaction forces between the human and robot. Here, we investigated whether measures of patient active involvement predict the level of upper limb recovery due to robot-assisted therapy. Stroke survivors (n=11) completed "exploration" training with customizable forces that increased their velocities (i.e., negative damping). While our results showed a mild trend between mechanical work during training and expanded velocity capability (Pearson r = 0.57), we found significant correlations with the amount of positive work (i.e., propulsion; r = 0.77), but not negative work (i.e., braking; r = 0.41). This work supports robotic tools that encourage more positive work.

Visual Limit-Push Training Alters Movement Variability

In both movement training and neurorehabilitation, there have been numerous examples of how average performance can be manipulated through practice using enhanced visual feedback.

OBJECTIVE

Rather than just influencing the mean, our objective was to use a novel feedback technique called limit-push to influence the trial-to-trial variability of motion by distorting vision.

METHOD

Limit-push was previously done using robotic forces; the present study employed only visual distortions that imitated the limit-push approach.

RESULTS

Like the robotic force treatment, our results showed how subjects significantly shifted the distributions of their motions. This effect was even greater than that of the original limit-push experiment that used robotic forces.

SIGNIFICANCE

Such visual distortion interventions do not require a robot for enhanced training.

CONCLUSION

The visual limit-push technique appears to be able to selectively alter both the central tendency and variability in performance training applications.

How a diverse research ecosystem has generated new rehabilitation technologies: Review of NIDILRR's Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a "total approach to rehabilitation", combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970's, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program.

Robot Training With Vector Fields Based on Stroke Survivors' Individual Movement Statistics

The wide variation in upper extremity motor impairments among stroke survivors necessitates more intelligent methods of customized therapy. However, current strategies for characterizing individual motor impairments are limited by the use of traditional clinical assessments (e.g., Fugl-Meyer) and simple engineering metrics (e.g., goal-directed performance). Our overall approach is to statistically identify the range of volitional movement capabilities, and then apply a robot-applied force vector field intervention that encourages under-expressed movements. We investigated whether explorative training with such customized force fields would improve stroke survivors' (n = 11) movement patterns in comparison to a control group that trained without forces (n = 11). Force and control groups increased Fugl-Meyer UE scores (average of 1.0 and 1.1, respectively), which is not considered clinically meaningful. Interestingly, participants from both groups demonstrated dramatic increases in their range of velocity during exploration following only six days of training (average increase of 166.4% and 153.7% for the Force and Control group, respectively). While both groups showed evidence of improvement, we also found evidence that customized forces affected learning in a systematic way. When customized forces were active, we observed broader distributions of velocity that were not present in the controls. Second, we found that these changes led to specific changes in unassisted motion. In addition, while the shape of movement distributions changed significantly for both groups, detailed analysis of the velocity distributions revealed that customized forces promoted a greater proportion of favorable changes. Taken together, these results provide encouraging evidence that patient-specific force fields based on individuals' movement statistics can be used to create new movement patterns and shape them in a customized manner. To the best of our knowledge, this paper is the first to directly link engineering assessments of stroke survivors' exploration movement behaviors to the design of customized robot therapy.

Movement therapy without moving - First results on isometric movement training for post-stroke rehabilitation of arm function

This study explores the use of isometric movement training for arm rehabilitation after stroke. The aim of this approach is to enhance movement skill even when the person training is not moving. This is accomplished by deceptively displaying virtual motions, exploiting known cross-modal sensory interactions between vision and proprioception. This approach can be advantageous in situations where actual movement is prohibitive due to weakness, spasticity, instability, or unsafe conditions. We present early insights on usability of and tolerance to this training approach and quantitative results that can power future clinical trials.

Dissociating two sources of variability using a safety-margin model

Neurological trauma can have a devastating effect on activities of daily living. One of the consequences is an increased amount of variability in the system, which can challenge individuals to stay within safe and stable regions of operation. There are multiple sources of movement variability; two of these are neuromotor noise and action-tolerance variability. The amount of neuromotor noise that is uncontrollable can impose limitations on reshaping variability. Action-tolerance variability, which can be reshaped through experience, and neuromotor noise, a certain amount of which cannot be altered, are often conflated when discussing motor variability. We attempted to disambiguate the two using an adaptive model, producing distinct "signatures" of neuromotor noise and action-tolerance variability within a task and compare with experimental data on stroke and healthy. Not all stroke survivors could adapt to the task, as predicted for those with greater neuromotor noise. Possible applications of this model can inform us of potential to influence distributions in stroke survivors and other individuals who have had a neurological injury. Additionally, we could design new training environments specifically tailored to the needs of the individual. This technique may also help disambiguate the type of brain injury suffered by stroke survivors.

Customized therapy using distributions of reaching errors

While there has been recent success with robotic therapy approaches, individual differences in motor impairments motivate the need for customized therapy. Our latest work with healthy participants considered the likelihood of one's error to construct a customized force field training environment, which we termed an error field. We believe error statistics could characterize individual motor impairments for stroke survivors. Here we present preliminary results from a pilot study testing this therapy technique on individuals following stroke. We tracked the changes in error for three stroke survivors across multiple days using error field training, and found that participants' errors reduced for all target directions across sessions. We also used a modeling approach to test whether the changes in error reflected the specific mathematical structure of the intervention. These results provide encouraging preliminary evidence that error field training can be valuable for both characterizing deficits and custom-tailoring therapy.

Transfer of dynamic motor skills acquired during isometric training to free motion

Recent studies have explored the prospects of learning to move without moving, by displaying virtual arm movement related to exerted force. However, it has yet to be tested whether learning the dynamics of moving can transfer to the corresponding movement. Here we present a series of experiments that investigate this isometric training paradigm. Subjects were asked to hold a handle and generate forces as their arms were constrained to a static position. A precise simulation of reaching was used to make a graphic rendering of an arm moving realistically in response to the measured interaction forces and simulated environmental forces. Such graphic rendering was displayed on a horizontal display that blocked their view to their actual (statically constrained) arm and encouraged them to believe they were moving. We studied adaptation of horizontal, planar, goal-directed arm movements in a velocity-dependent force field. Our results show that individuals can learn to compensate for such a force field in a virtual environment and transfer their new skills to the actual free motion condition, with performance comparable to practice while moving. Such nonmoving techniques should impact various training conditions when moving may not be possible.NEW & NOTEWORTHY This study provided early evidence supporting that training movement skills without moving is possible. In contrast to previous studies, our study involves 1) exploiting cross-modal sensory interactions between vision and proprioception in a motionless setting to teach motor skills that could be transferable to a corresponding physical task, and 2) evaluates the movement skill of controlling muscle-generated forces to execute arm movements in the presence of external forces that were only virtually present during training.

Evolutionary processes and its environmental correlates in the cranial morphology of western chipmunks (Tamias)

The importance of the environment in shaping phenotypic evolution lies at the core of evolutionary biology. Chipmunks of the genus Tamias (subgenus Neotamias) are part of a very recent radiation, occupying a wide range of environments with marked niche partitioning among species. One open question is if and how those differences in environments affected phenotypic evolution in this lineage. Herein we examine the relative importance of genetic drift versus natural selection in the origin of cranial diversity exhibited by clade members. We also explore the degree to which variation in potential selective agents (environmental variables) are correlated with the patterns of morphological variation presented. We found that genetic drift cannot explain morphological diversification in the group, thus supporting the potential role of natural selection as the predominant evolutionary force during Neotamias cranial diversification, although the strength of selection varied greatly among species. This morphological diversification, in turn, was correlated with environmental conditions, suggesting a possible causal relationship. These results underscore that extant Neotamias represent a radiation in which aspects of the environment might have acted as the selective force driving species' divergence.

Directional selection effects on patterns of phenotypic (co)variation in wild populations

Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient.