Dynamic rewiring of electrophysiological brain networks during learning.

Human learning is an active and complex process. However, the brain mechanisms underlying human skill learning and the effect of learning on the communication between brain regions, at different frequency bands, are still largely unknown. Here, we tracked changes in large-scale electrophysiological networks over a 6-week training period during which participants practiced a series of motor sequences during 30 home training sessions. Our findings showed that brain networks become more flexible with learning in all the frequency bands from theta to gamma ranges. We found consistent increase of flexibility in the prefrontal and limbic areas in the theta and alpha band, and over somatomotor and visual areas in the alpha band. Specific to the beta rhythm, we revealed that higher flexibility of prefrontal regions during the early stage of learning strongly correlated with better performance measured during home training sessions. Our findings provide novel evidence that prolonged motor skill practice results in higher, frequency-specific, temporal variability in brain network structure.

Young children can use their subjective straight-ahead to remap visuo-motor alterations.

Young children and adults process spatial information differently: the former use their bodies as primary reference, while adults seem capable of using abstract frames. The transition is estimated to occur between the 6th and the 12th year of age. The mechanisms underlying spatial encoding in children and adults are unclear, as well as those underlying the transition. Here, we investigated the role of the subjective straight-ahead (SSA), the body antero-posterior half-plane mental model, in spatial encoding before and after the expected transition. We tested 6-7-year-old and 10-11-year-old children, and adults on a spatial alignment task in virtual reality, searching for differences in performance when targets were placed frontally or sideways. The performance differences were assessed both in a naturalistic baseline condition and in a test condition that discouraged using body-centered coordinates through a head-related visuo-motor conflict. We found no differences in the baseline condition, while all groups showed differences between central and lateral targets (SSA effect) in the visuo-motor conflict condition, and 6-7-year-old children showed the largest effect. These results confirm the expected transition timing; moreover, they suggest that children can abstract from the body using their SSA and that the transition underlies the maturation of a world-centered reference frame.

Immersive virtual reality interferes with default head-trunk coordination strategies in young children.

The acquisition of postural control is an elaborate process, which relies on the balanced integration of multisensory inputs. Current models suggest that young children rely on an 'en-block' control of their upper body before sequentially acquiring a segmental control around the age of 7, and that they resort to the former strategy under challenging conditions. While recent works suggest that a virtual sensory environment alters visuomotor integration in healthy adults, little is known about the effects on younger individuals. Here we show that this default coordination pattern is disrupted by an immersive virtual reality framework where a steering role is assigned to the trunk, which causes 6- to 8-year-olds to employ an ill-adapted segmental strategy. These results provide an alternate trajectory of motor development and emphasize the immaturity of postural control at these ages.

A multimodal approach to capture post-stroke temporal dynamics of recovery.

OBJECTIVE: Several training programs have been developed in the past to restore motor functions after stroke. Their efficacy strongly relies on the possibility to assess individual levels of impairment and recovery rate. However, commonly used clinical scales rely mainly on subjective functional assessments and are not able to provide a complete description of patients' neuro-biomechanical status. Therefore, current clinical tests should be integrated with specific physiological measurements, i.e. kinematic, muscular, and brain activities, to obtain a deep understanding of patients' condition and of its evolution through time and rehabilitative intervention. APPROACH: We proposed a multivariate approach for motor control assessment that simultaneously measures kinematic, muscle and brain activity and combines the main physiological variables extracted from these signals using principal component analysis (PCA). We tested it in a group of six sub-acute stroke subjects evaluated extensively before and after a four-week training, using an upper-limb exoskeleton while performing a reaching task, along with brain and muscle measurements. MAIN RESULTS: After training, all subjects exhibited clinical improvements correlating with changes in kinematics, muscle synergies, and spinal maps. Movements were smoother and faster, while muscle synergies increased in numbers and became more similar to those of the healthy controls. These findings were coupled with changes in cortical oscillations depicted by EEG-topographies. When combining these physiological variables using PCA, we found that (i) patients' kinematic and spinal maps parameters improved continuously during the four assessments; (ii) muscle coordination augmented mainly during treatment, and (iii) brain oscillations recovered mostly pre-treatment as a consequence of short-term subacute changes. SIGNIFICANCE: Although these are preliminary results, the proposed approach has the potential of identifying significant biomarkers for patient stratification as well as for the design of more effective rehabilitation protocols.

Motor improvement estimation and task adaptation for personalized robot-aided therapy: a feasibility study.

BACKGROUND: In the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients' individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches. METHODS: Here, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients' motor improvement for a series of point-to-point reaching movements in different directions. Additionally, it comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper-limb exoskeleton. The implementation was tested with 17 healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test undergoing rehabilitative motor training. RESULTS: The results of the exploratory study with healthy subjects showed that the participants divided into fast and slow adapters. The model was able to correctly estimate distinct motor improvement progressions between the two groups of participants while proposing individual training protocols. For the two pilot patients, an analysis of the selected motor performance measures showed that both patients were able to retain the improvements gained during training when reaching movements were reintroduced at a later stage. These results suggest that the automated training adaptation was appropriately timed and specifically tailored to the abilities of each individual. CONCLUSIONS: The results of our exploratory study demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing encouraging results for the applicability in clinical settings. Trial registration This study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300).

Data-driven body-machine interface for the accurate control of drones.

The accurate teleoperation of robotic devices requires simple, yet intuitive and reliable control interfaces. However, current human-machine interfaces (HMIs) often fail to fulfill these characteristics, leading to systems requiring an intensive practice to reach a sufficient operation expertise. Here, we present a systematic methodology to identify the spontaneous gesture-based interaction strategies of naive individuals with a distant device, and to exploit this information to develop a data-driven body-machine interface (BoMI) to efficiently control this device. We applied this approach to the specific case of drone steering and derived a simple control method relying on upper-body motion. The identified BoMI allowed participants with no prior experience to rapidly master the control of both simulated and real drones, outperforming joystick users, and comparing with the control ability reached by participants using the bird-like flight simulator Birdly.

Closed-loop control of trunk posture improves locomotion through the regulation of leg proprioceptive feedback after spinal cord injury.

After spinal cord injury (SCI), sensory feedback circuits critically contribute to leg motor execution. Compelled by the importance to engage these circuits during gait rehabilitation, assistive robotics and training protocols have primarily focused on guiding leg movements to reinforce sensory feedback. Despite the importance of trunk postural dynamics on gait and balance, trunk assistance has comparatively received little attention. Typically, trunk movements are either constrained within bodyweight support systems, or manually adjusted by therapists. Here, we show that real-time control of trunk posture re-established dynamic balance amongst bilateral proprioceptive feedback circuits, and thereby restored left-right symmetry, loading and stepping consistency in rats with severe SCI. We developed a robotic system that adjusts mediolateral trunk posture during locomotion. This system uncovered robust relationships between trunk orientation and the modulation of bilateral leg kinematics and muscle activity. Computer simulations suggested that these modulations emerged from corrections in the balance between flexor- and extensor-related proprioceptive feedback. We leveraged this knowledge to engineer control policies that regulate trunk orientation and postural sway in real-time. This dynamical postural interface immediately improved stepping quality in all rats regardless of broad differences in deficits. These results emphasize the importance of trunk regulation to optimize performance during rehabilitation.

Axotomized Corticospinal Neurons Increase Supra-Lesional Innervation and Remain Crucial for Skilled Reaching after Bilateral Pyramidotomy.

Skilled upper limb function heavily depends on the corticospinal tract. After bilateral lesions to this tract, motor control is disrupted but can be partially substituted by other motor systems to allow functional recovery. However, the remaining roles of motor cortex and especially of axotomized corticospinal neurons (CSNs) are not well understood. Using the single pellet retrieval task in adult rats, we induced significant recovery of skilled reaching after bilateral pyramidotomy by rehabilitative reaching training, and show that reach-related motor cortex activity, recorded in layer V, topographically reappeared shortly after axotomy. Using a chemogenetic neuronal silencing technique, we found that axotomized CSNs retained a crucial role for the recovered pellet retrieval success. The axotomized CSNs sprouted extensively in the red nucleus supplying new innervation to its magnocellular and parvocellular parts. Specific silencing of the rubrospinal tract (RST) also strongly abolished the recovered pellet retrieval success, suggesting a role of this cervically projecting nucleus in relaying cortical motor control. In summary, our results show that after bilateral corticospinal axotomy, motor cortex still actively engages in forelimb motor control and axotomized CSNs are crucially involved in the recovered reaching movement, potentially by relaying motor control via the RST.

Accurate internal-external rotation measurement in total knee prostheses: A magnetic solution.

In this work we tackled the problem of accurate measurement of internal-external (IE) rotations in the prosthetic knee. We presented a magnetic measurement system to be implanted in the knee prostheses in order to measure IE without soft tissue artifacts. The measurement system consisted of a permanent magnet attached under the tibial plate of the prosthesis and a combination of magnetic sensors in the polyethylene insert. Two different sensor configurations were designed, and five different angle estimators for measurement of IE angles were defined and tested based on several static and dynamic measurements toward a stereophotogrammetry motion capture system. Also a noise analysis was done to see which estimators are less sensitive to measurement noise. One-sensor configuration provided lower power budget with dynamic RMS error of 0.49° and a noise range of ±0.53°. Two-sensor configuration doubles the power consumption but provided slightly lower dynamic RMS error (0.37°) and a noise range of ±0.42°, and offers the possibility of having redundancy in case of damaged sensor.