No abstract

Spinal cord injury disrupts the communication between the brain and the spinal circuits that orchestrate movement. To bypass the lesion, brain–computer interfaces1–3 have directly linked cortical activity to electrical stimulation of muscles, which have restored grasping abilities after hand paralysis1,4. Theoretically, this strategy could also restore control over leg muscle activity for walking5. However, replicating the complex sequence of individual muscle activation patterns underlying natural and adaptive locomotor movements poses formidable conceptual and technological challenges6,7. Recently, we showed in rats that epidural electrical stimulation of the lumbar spinal cord can reproduce the natural activation of synergistic muscle groups producing locomotion8–10. Here, we interfaced leg motor cortex activity with epidural electrical stimulation protocols to establish a brain–spinal interface that alleviated gait deficits after a spinal cord injury in nonhuman primates. Rhesus monkeys were implanted with an intracortical microelectrode array into the leg area of motor cortex; and a spinal cord stimulation system composed of a spatially selective epidural implant and a pulse generator with real-time triggering capabilities. We designed and implemented wireless control systems that linked online neural decoding of extension and flexion motor states with stimulation protocols promoting these movements. These systems allowed the monkeys to behave freely without any restrictions or constraining tethered electronics. After validation of the brain–spinal interface in intact monkeys, we performed a unilateral corticospinal tract lesion at the thoracic level. As early as six days post-injury and without prior training of the monkeys, the brain–spinal interface restored weight-bearing locomotion of the paralyzed leg on a treadmill and overground. The implantable components integrated in the brain–spinal interface have all been approved for investigational applications in similar human research, suggesting a practical translational pathway for proof-of-concept studies in people with spinal cord injury.

Epidural electrical stimulation (EES) of the spinal cord restores locomotion in animal models of spinal cord injury (SCI) but is less effective in humans. Here, we hypothesized that this inter-species discrepancy is due to interference between EES and proprioceptive information in humans. Computational simulations, preclinical and clinical experiments reveal that EES blocks a significant amount of proprioceptive input in humans, but not in rats. This transient deafferentation prevents the modulation of reciprocal inhibitory networks involved in locomotion and reduces or abolishes the conscious perception of leg position. Consequently, continuous EES can only facilitate locomotion within a narrow range of stimulation parameters and is unable to provide meaningful locomotor improvements in humans without rehabilitation. Simulations showed that burst stimulation and spatiotemporal stimulation profiles mitigate the cancellation of proprioceptive information, enabling robust control over motoneuron activity. This demonstrates the importance of stimulation protocols that preserve proprioceptive information to facilitate walking with EES.

BackgroundThis study investigated the effects of obesity on attentional resources allocated to postural control in seating and unipedal standing.MethodsTen non obese adults (BMI = 22.4±1.3, age = 42.4±15.1) and 10 obese adult patients (BMI = 35.2±2.8, age = 46.2±19.6) maintained postural stability on a force platform in two postural tasks (seated and unipedal). The two postural tasks were performed (1) alone and (2) in a dual-task paradigm in combination with an auditory reaction time task (RT). Performing the RT task together with the postural one was supposed to require some attentional resources that allowed estimating the attentional cost of postural control. 4 trials were performed in each condition for a total of 16 trials.Findings(1) Whereas seated non obese and obese patients exhibited similar centre of foot pressure oscillations (CoP), in the unipedal stance only obese patients strongly increased their CoP sway in comparison to controls. (2) Whatever the postural task, the additional RT task did not affect postural stability. (3) Seated, RT did not differ between the two groups. (4) RT strongly increased between the two postural conditions in the obese patients only, suggesting that body schema and the use of internal models was altered with obesity.InterpretationObese patients needed more attentional resources to control postural stability during unipedal stance than non obese participants. This was not the case in a more simple posture such as seating. To reduce the risk of fall as indicated by the critical values of CoP displacement, obese patients must dedicate a strong large part of their attentional resources to postural control, to the detriment of non-postural events. Obese patients were not able to easily perform multitasking as healthy adults do, reflecting weakened psycho-motor abilities.

These findings identified the bounding limits of COP velocity as a hallmark feature of cognitive impairment-related changes in postural sway, in particular for MMAD. This point is of special interest for clinical balance assessment and fall prevention in MMAD patients in order to plan long-term targeted fall-prevention programs.

No abstract

Gait recovery after neurological disorders requires remastering the interplay between body mechanics and gravitational forces. Despite the importance of gravity-dependent gait interactions and active participation for promoting this learning, these essential components of gait rehabilitation have received comparatively little attention. To address these issues, we developed an adaptive algorithm that personalizes multidirectional forces applied to the trunk based on patient-specific motor deficits. Implementation of this algorithm in a robotic interface reestablished gait dynamics during highly participative locomotion within a large and safe environment. This multidirectional gravity-assist enabled natural walking in nonambulatory individuals with spinal cord injury or stroke and enhanced skilled locomotor control in the less-impaired subjects. A 1-hour training session with multidirectional gravity-assist improved locomotor performance tested without robotic assistance immediately after training, whereas walking the same distance on a treadmill did not ameliorate gait. These results highlight the importance of precise trunk support to deliver gait rehabilitation protocols and establish a practical framework to apply these concepts in clinical routine.

Falls are common in the elderly, and potentially result in injury and disability. Thus, preventing falls as soon as possible in older adults is a public health priority, yet there is no specific marker that is predictive of the first fall onset. We hypothesized that gait features should be the most relevant variables for predicting the first fall. Clinical baseline characteristics (e.g., gender, cognitive function) were assessed in 259 home-dwelling people aged 66 to 75 that had never fallen. Likewise, global kinetic behavior of gait was recorded from 22 variables in 1036 walking tests with an accelerometric gait analysis system. Afterward, monthly telephone monitoring reported the date of the first fall over 24 months. A principal components analysis was used to assess the relationship between gait variables and fall status in four groups: non-fallers, fallers from 0 to 6 months, fallers from 6 to 12 months and fallers from 12 to 24 months. The association of significant principal components (PC) with an increased risk of first fall was then evaluated using the area under the Receiver Operator Characteristic Curve (ROC). No effect of clinical confounding variables was shown as a function of groups. An eigenvalue decomposition of the correlation matrix identified a large statistical PC1 (termed “Global kinetics of gait pattern”), which accounted for 36.7% of total variance. Principal component loadings also revealed a PC2 (12.6% of total variance), related to the “Global gait regularity.” Subsequent ANOVAs showed that only PC1 discriminated the fall status during the first 6 months, while PC2 discriminated the first fall onset between 6 and 12 months. After one year, any PC was associated with falls. These results were bolstered by the ROC analyses, showing good predictive models of the first fall during the first six months or from 6 to 12 months. Overall, these findings suggest that the performance of a standardized walking test at least once a year is essential for fall prevention.