Implications of Hemispheric Shift of Sensory Feedback during Post-stroke Motor Control on Personalized Stroke Rehabilitation.

Sensory feedback is of vital importance in motor control, yet is rarely studied in diseases which frequently result in motor deficiency, such as hemiparetic stroke. This study employs the laterality index (LI) of somatosensory evoked potentials (SEPs) to investigate whether sensory feedback is altered in hemiparetic stroke during movements of the paretic arm, with a hemispheric shift from the lesioned hemisphere toward contralesional hemisphere. Through experimental design involving the isometric lifting of the paretic arms during tactile finger stimulation and the analysis of LI in SEPs P50 and N100, we found: 1) increased contralesional sensory activity in stroke participants when they are receiving sensory input in their paretic hand for both P50 and N100 and 2) the contralesional N100 activity is enhanced when stroke participants are performing an isometric arm lifting task. These results indicate a timedependent shifting of sensory feedback from the sensorimotor areas in the lesioned side to the contralesional side of the stroke brain.

BackgroundVarious robotic technologies have been developed recently for objective and quantitative assessment of movement. Among them, robotic measures derived from a reaching task in the KINARM Exoskeleton device are characterized by their potential to reveal underlying motor control in reaching movements. The aim of this study was to examine the clinical usefulness and validity of these robot-derived measures in hemiparetic stroke patients.MethodsFifty-six participants with a hemiparetic arm due to chronic stroke were enrolled. The robotic assessment was performed using the Visually Guided Reaching (VGR) task in the KINARM Exoskeleton, which allows free arm movements in the horizontal plane. Twelve parameters were derived based on motor control theory. The following clinical assessments were also administered: the proximal upper limb section in the Fugl-Meyer Assessment (FMA-UE(A)), the proximal upper limb part in the Stroke Impairment Assessment Set (SIAS-KM), the Modified Ashworth Scale for the affected elbow flexor muscles (MAS elbow), and seven proximal upper limb tasks in the Wolf Motor Function Test (WMFT). To explore which robotic measures represent deficits of motor control in the affected arm, the VGR parameters in the paretic arm were compared with those in the non-paretic arm using the Wilcoxon signed rank test. Then, to explore which VGR parameters were related to overall motor control regardless of the paresis, correlations between the paretic and non-paretic arms were examined. Finally, to investigate the relationships between the robotic measures and the clinical scales, correlations between the VGR parameters and clinical scales were investigated. Spearman’s rank correlation coefficients were used for all correlational analyses.ResultsEleven VGR parameters on the paretic side were significantly different from those on the non-paretic side with large effect sizes (|effect size| = 0.76–0.87). Ten VGR parameters correlated significantly with FMA-UE(A) (|r| = 0.32–0.60). Eight VGR parameters also showed significant correlations with SIAS-KM (|r| = 0.42–0.49), MAS elbow (|r| = 0.44–0.48), and the Functional Ability Scale of the WMFT (|r| = 0.52–0.64).ConclusionsThe robot-derived measures could successfully differentiate between the paretic arm and the non-paretic arm and were valid in comparison to the well-established clinical scales.

The cortical motor system can be reorganized following a stroke, with increased recruitment of the contralesional hemisphere. However, it is unknown whether a similar hemispheric shift occurs in the somatosensory system to adapt to this motor change, and whether this is related to movement impairments. This proof-of-concept study assessed somatosensory evoked potentials (SEPs), P50 and N100, in hemiparetic stroke participants and age-matched controls using high-density electroencephalograph (EEG) recordings during tactile finger stimulation. The laterality index was calculated to determine the hemispheric dominance of the SEP and re-confirmed with source localization. The study found that latencies of P50 and N100 were significantly delayed in stroke brains when stimulating the paretic hand. The amplitude of P50 in the contralateral (to stimulated hand) hemisphere was negatively correlated with the Fügl–Meyer upper extremity motor score in stroke. Bilateral cortical responses were detected in stroke, while only contralateral cortical responses were shown in controls, resulting in a significant difference in the laterality index. These results suggested that somatosensory reorganization after stroke involves increased recruitment of ipsilateral cortical regions, especially for the N100 SEP component. This reorganization delays the latency of somatosensory processing after a stroke. This research provided new insights related to the somatosensory reorganization after stroke, which could enrich future hypothesis-driven therapeutic rehabilitation strategies from a sensory or sensory-motor perspective.

Background: Prior work indicates that 50–75% of individuals post-hemiparetic stroke have upper-extremity weakness and, in turn, inaccurately judge the relative torques that their arms generate during a bimanual task. Recent findings also reveal that these individuals judge the relative torques their arms generate differently depending on whether they reference their paretic vs. non-paretic arm.Objective: Our goal was to determine whether individuals with hemiparetic stroke inaccurately matched torques between arms, regardless of the arm that they referenced.Methods: Fifteen participants with hemiparetic stroke and 10 right-hand dominant controls matched torques between arms. Participants performed this task with their right arm referencing their left arm, and vice versa. Participants generated (1) 5 Nm and (2) 25% of their reference elbow's maximum voluntary torque (MVT) in flexion and extension using their reference arm while receiving audiovisual feedback. Then, participants matched the reference torque using their opposite arm without receiving feedback on their matching performance.Results: Participants with stroke had greater magnitudes of error in matching torques than controls when referencing their paretic arm (p < 0.050), yet not when referencing their non-paretic arm (p > 0.050). The mean magnitude of error when participants with stroke referenced their paretic and non-paretic arm and controls referenced their dominant and non-dominant arm to generate 5 Nm in flexion was 9.4, 2.6, 4.2, and 2.5 Nm, respectively, and in extension was 5.3, 2.8, 2.5, and 2.3 Nm, respectively. However, when the torques generated at each arm were normalized by the corresponding MVT, no differences were found in matching errors regardless of the arm participants referenced (p > 0.050).Conclusions: Results demonstrate the importance of the arm referenced, i.e., paretic vs. non-paretic, on how accurately individuals post-hemiparetic stroke judge their torques during a bimanual task. Results also indicate that individuals with hemiparetic stroke judge torques primarily based on their perceived effort. Finally, findings support the notion that training individuals post-hemiparetic stroke to accurately perceive their self-generated torques, with a focus of their non-paretic arm in relation to their paretic arm, may lead to an improved ability to perform bimanual activities of daily living.

Motor prediction

In this study, we investigated the somatosensory evoked potentials (SEPs) during the preparatory period of self-initiated plantar flexion at different force levels of muscle contraction and elucidated the mechanism behind the centrifugal gating effect on somatosensory information processing. We recorded SEPs following stimulation of the tibial nerve at the popliteal fossa during the preparatory period of a 20% maximal voluntary contraction (MVC) and 50% MVC. The preparatory period was divided into two sub-periods based on the components of movement-related cortical potentials, the negative slope (NS sub-period) and the Bereitschaftspotential (BP sub-period). The subjects were instructed to concentrate on the movement and not to pay attention to the continuous electrical stimulation. Pre-movement SEPs were averaged separately during the two sub-periods under each MVC condition. The mean amplitudes of BP and NS were larger during the 50% MVC than the 20% MVC. As for the components of SEPs, during the NS sub-period the amplitude of P30 under the 50% MVC and N40 under both conditions were significantly smaller than that in the stationary sequence, and N40 amplitude was significantly smaller during the 50% MVC than the 20% MVC. During the BP sub-period, the amplitude of P30 and N40 during the 50% MVC was significantly smaller than during the stationary sequence, while it was not significantly different between the 20% and 50% MVCs. In conclusion, the extent of the centrifugal gating effect on SEPs was dependent on the activities of motor-related areas, which generated the NS and BP.

Sensory feedback is critical in fine motor control, learning, and adaptation. However, robotic prosthetic limbs currently lack the feedback segment of the communication loop between user and device. Sensory substitution feedback can close this gap, but sometimes this improvement only persists when users cannot see their prosthesis, suggesting the provided feedback is redundant with vision. Thus, given the choice, users rely on vision over artificial feedback. To effectively augment vision, sensory feedback must provide information that vision cannot provide or provides poorly. Although vision is known to be less precise at estimating speed than position, no work has compared speed precision of biomimetic arm movements. In this study, we investigated the uncertainty of visual speed estimates as defined by different virtual arm movements. We found that uncertainty was greatest for visual estimates of joint speeds, compared to absolute rotational or linear endpoint speeds. Furthermore, this uncertainty increased when the joint reference frame speed varied over time, potentially caused by an overestimation of joint speed. Finally, we demonstrate a joint-based sensory substitution feedback paradigm capable of significantly reducing joint speed uncertainty when paired with vision. Ultimately, this work may lead to improved prosthesis control and capacity for motor learning.

Remapping Auditory-Motor Representations in Voice Production

Single-Arm Torque Perceptual Deficits in Individuals with Chronic Hemiparetic Stroke BACKGROUND: To perform activities of daily living safely and efficiently, an individual with hemiparetic stroke needs to accurately perceive how much force is generated about their joints, i.e., torque perception. We know that individuals with moderate to severe motor impairments post hemiparetic stroke have between-arms torque perceptual impairments. However, a question that has yet to be addressed is whether these individuals have a torque perceptual impairment within their paretic arm and/or non-paretic arm. OBJECTIVE: To compare single-arm torque perception between individuals with chronic hemiparetic stroke and individuals without neurological impairments (i.e., controls). METHODS: Nine individuals with chronic hemiparetic stroke and five similarly-aged individuals without neurological impairments (i.e., controls) partook in the study. By following automated audiovisual cues, each participant generated 25% of their maximum voluntary elbow extension torque for three seconds, relaxed for two seconds, and then matched the remembered torque for one second without receiving feedback on their torque-matching ability. This torque-matching task was performed in each arm. RESULTS: The mean ± standard deviation of the normalized absolute torque matching error was 26.5±18.3% and 28.2±23.3% for the participants with chronic hemiparetic stroke in their paretic and non-paretic arm, respectively, and 19.8±7.1% and 20.1±11.3% for the controls in their dominant and non-dominant arm, respectively. Absolute error was not found to significantly differ depending on the arm tested (p=0.53). CONCLUSIONS: Our participants with chronic hemiparetic stroke and controls matched torques similarly in each arm. This result supports the notion that unilateral torque perceptual deficits may not occur in individuals with chronic hemiparetic stroke who exhibit motor impairments during unimanual activities.

ABSTRACTObjective:This study aimed to characterize reaching movements of the paretic arm in differentdirections within the reachable workspace in post-stroke patients. Methods:A total of 12 post-stroke patients participated in this study. Each held a ball with atracking marker and performed back-and-forth reaching movements from near the middle ofthe body to one of two targets in front of them located on the ipsilateral andcontralateral sides of the arm performing the movement. We recorded and analyzed thetrajectories of the tracking marker. The stability of arm movements was evaluated usingareas and minimum Feret diameters to assess the trajectories of both the paretic andnon-paretic arms. The speed of the arm movement was also calculated. Results:For the paretic arm, contralateral movement was more impaired than ipsilateralmovement, whereas for the non-paretic arm, no difference was observed between thedirections. The maximum speed of the contralateral movement was significantly slowerthan that of the ipsilateral movement in both the paretic and non-paretic arms. Conclusion:The paretic arm shows direction-specific instability in movement toward thecontralateral side of the arm.

An important factor for optimal sensorimotor control is how well we are able to predict sensory feedback from internal and external sources during movement. If predictability decreases due to external disturbances, the brain is able to adjust muscle activation and the filtering of incoming sensory inputs. However, little is known about sensorimotor adjustments when predictability is increased by availability of additional internal feedback. In the present study we investigated how modifications of internal and external sensory feedback influence the control of muscle activation and gating of sensory input. Co-activation of forearm muscles, somatosensory evoked potentials (SEP) and short afferent inhibition (SAI) were assessed during three object manipulation tasks designed to differ in the predictability of sensory feedback. These included manipulation of a shared object with both hands (predictable coupling), manipulation of two independent objects without (uncoupled) and with external interference on one of the objects (unpredictable coupling). We found a task-specific reduction in co-activation during the predictable coupling compared to the other tasks. Less sensory gating, reflected in larger subcortical SEP amplitudes, was observed in the unpredictable coupling task. SAI behavior was closely linked to the subcortical SEP component indicating an important function of subcortical sites in predictability related SEP gating and their direct influence on M1 inhibition. Together, these findings suggest that the unpredictable coupling task cannot only rely on predictive forward control and is compensated by enhancing co-activation and increasing the saliency for external stimuli by reducing sensory gating at subcortical level. This behavior might serve as a preparatory step to compensate for external disturbances and to enhance processing and integration of all incoming external stimuli to update the current sensorimotor state. In contrast, predictive forward control is accurate in the predictable coupling task due to the integrated sensory feedback from both hands where sensorimotor resources are economized by reducing muscular co-activation and increasing sensory gating.

We quantified prosthesis embodiment and phantom pain reduction associated with motor control and sensory feedback from a prosthetic hand in one human with a long-term transradial amputation. Microelectrode arrays were implanted in the residual median and ulnar arm nerves and intramuscular electromyography recording leads were implanted in residual limb muscles to enable sensory feedback and motor control. Objective measures (proprioceptive drift) and subjective measures (survey answers) were used to assess prosthesis embodiment. For both measures, there was a significant level of embodiment of the physical prosthetic limb after open-loop motor control of the prosthesis (i.e., without sensory feedback), open-loop sensation from the prosthesis (i.e., without motor control), and closed-loop control of the prosthesis (i.e., motor control with sensory feedback). There was also a statistically significant reduction in reported phantom pain after experimental sessions that included open-loop nerve microstimulation, open-loop prosthesis motor control, or closed-loop prosthesis motor control. The closed-loop condition provided no additional significant improvements in phantom pain reduction or prosthesis embodiment relative to the open-loop sensory condition or the open-loop motor condition. This study represents the first long-term (14-month), systematic report of phantom pain reduction and prosthesis embodiment in a human amputee across a variety of prosthesis use cases.

Well-executed case studies can offer invaluable insights into mechanisms underlying the effects of rehabilitation interventions. Functional electrical stimulation (FES) therapy is one intervention aimed at restoring function following a stroke. The work of Kawashima and colleagues provides clues that may help explain the functional benefits seen with FES therapy.1 Their case study reports the effects of FES therapy in a person 2 years post stroke, when natural recovery is expected to have plateaued, whose enduring stroke-related impairments included impaired arm movement and function.1 Although the client had voluntary muscle activity in the wrist flexors/extensors and biceps brachii, she showed very little voluntary activity in the rest of the shoulder and wrist muscles and none in the triceps brachii (TB) and first distal interosseous (FDI) muscles. The therapeutic intervention included a combination of intensive FES (incorporating voluntary movements assisted with FES) and manual assistance. The client was also asked to imagine the movement to be performed. A variety of different stimulation methods exist, including focal stimulation of muscles at the wrist joint only.2 It is important to note that multiple muscles in the shoulder, elbow, and wrist (but no hand muscles) were stimulated in the study by Kawashima and colleagues.1 The exercises performed were guided by the therapist to provide important sensory feedback related to naturally occurring movement. Thus, the elements of FES therapy used in this study were unique in the literature.2,3 It is significant that while FES therapy resulted in functional improvements, specifically a significantly improved ability to draw a circle and improved joint range of motion, these changes were not robust enough to alter the motor impairment level as measured by the Motricity Index (MI) and the Chedoke–McMaster stages of motor recovery (CMSMR). Significant improvement on the Fugl–Meyer Assessment, a scale of motor impairment that has strong positive correlation with the MI,4 has been reported in response to a similar protocol of FES therapy.3 In that study, however, it was the acute stroke group that showed robust changes; the chronic stroke group did not show significant changes in function or motor impairment.3 Kawashima and colleagues used sensitive measures to assess the smallest of changes in function, as well as measures to assess the mechanisms of change.1 Their case study of a person with chronic stroke (expected to be less amenable to therapy3) demonstrated improvements using sensitive measures such as the circle-drawing test and joint kinematics during movements; they also found that the size of the flexor carpi radialis H-reflex was almost halved and that this change was accompanied by improved ability to voluntarily contract and relax muscles. It is remarkable to see that their client was able to voluntarily activate previously paralyzed muscles (TB, FDI) after 12 weeks of training. Although improvement in muscle strength in response to FES has previously been reported in people with acute stroke,2 Kawashima and colleagues found no change in muscle strength, maximum M wave, or maximum voluntary contraction (MVC). This may be because they stimulated multiple muscles and the voluntary movement repetitions focused on movement quality rather than on strength. Muscle strength may also improve with higher FES intensity, or when FES is combined with resistance training. Indeed, muscle weakness in people with stroke can be overcome with high-intensity resistance training exercises that have been shown to have no adverse effect on spasticity.5 The decrease in spinal excitability (H-reflex depression) that Kawashima and colleagues observed, combined with the absence of change in muscle strength or MVC post training, suggests improved cortical mechanisms of motor control. Another possibility is retraining of the spinal contributions to arm movements following stroke,6 especially since the FES therapy in this case study focused on accurate movement-related sensory feedback of a repetitive nature. A more obvious example of the spinal contributions to leg movements was reported in a case study of a child with spinal-cord injury who began taking independent steps after locomotor training on a treadmill with body-weight support and manual assistance, while at the same time the child's voluntary motor capacity remained very low and unchanged.7 Future studies will need to discriminate cortical- and spinal-level excitability changes using transcranial magnetic stimulation and H-reflexes. Finally, there is a need for terminology that accurately describes the nature of therapy delivered. Key training variables of the type of FES used in the study by Kawashima and colleagues were stimulation of multiple muscles, movement repetition, manual assistance, voluntary effort, and motor imagery. The broad term “FES therapy,” therefore, does not do justice to other important elements of the therapeutic intervention that may have contributed, to varying degrees, to the patient's functional improvement. Future studies should use more descriptive terminology that encompasses all elements of the training regimen.

Virtual Reality on Stroke Rehabilitation Paolo Tonin About six hundred million people live with disabilities of various types all around the world. The majority of these disabilities originate from neurological lesions and the process of recovery emerges as one of the most relevant topic in the World Health Organization. A new or recurrent stroke is the main cause of disability in the industrial world, affecting the ability of a wide population to perform daily activities independently. Rehabilitation interventions are of utmost importance for this population. Recent studies in motor control, motor learning, and in the mechanisms of recovery after stroke produced a major impact in the field of neurorehabilitation. These acquisitions may lead to the development of scientifically based therapies, hopefully, more effective than current ones. Although, little is known about the mechanisms by which therapeutic measures influence motor recovery, some neuro-physiological studies on healthy subjects have reported that appropriate feedback on the nature of the movement pattern (knowledge of performance) and some variables of outcome (knowledge of results) may help to temporarily or permanently improve motor performance. Virtual Reality (VR) is a computer simulation which gives the user the impression of being and interacting in a real three-dimensional environment. Virtual Environments are a three-dimensional data set describing an artificial environment based on real world that the user interacts with. VR could be immersive or not immersive. The immersive VR systems may produce negative effects (Motion sickness syndrome, Photic seizures, Migraines, Hearing loss, Trauma, Eyestrain), not found during not immersive experiences. Virtual Reality (VR) systems have been proposed as useful tools in post stroke rehabilitation for both, motor rehabilitation, of upper limb particularly and cognitive rehabilitation. To create a virtual motor task, the therapist moves the handling object (for instance an envelope, a hammer, or a glass) connected to a receiver, inside the VE. The raw data are recorded by the tracking system. A dedicate software transforms the raw data in the movement of a virtual object that changes position corresponding to the real object motion. The motor task is automatically adapted to the patient's anthropomorphic characteristics. According to the patient's arm motor deficit, the therapist may orient the target. The location of the starting position, the target and the other objects, virtually represented in the arm workspace, determines the type and the difficulty of movement requested; the therapist could add virtual obstacles to increase the task complexity. VR may be exploited to provide the CNS with artificially generated information about the arm movement and the context, particularly showing: the patient's motor performance in the VE in real time (in the same frame of reference); the representation of the whole arm; the correct movement to the patients; a real-time feedback of the mismatch between desired and actual movement; the result of patient's performance, supplied via a reward based method with a numeric score; trace of the patient trajectory and repeated animation of trajectory after the task. Using treatment interventions created in virtual environments, practice conditions can be manipulated to explicitly engage motivation, cognitive processes, motor control, and sensory feedback- based learning mechanisms. The presentation will be focused on principles of motor learning underlying the VR systems for post-stroke patients; on the results of recent meta-analysis on the effects of VR; on the efficacy of systems specifically created for rehabilitation and of the commercial gaming systems.

P2-97. Different information processing in primary somatosensory area during force generation and relaxation