Noninvasive spinal stimulation improves walking in chronic stroke survivors: a proof-of-concept case series.

BACKGROUND: After stroke, restoring safe, independent, and efficient walking is a top rehabilitation priority. However, in nearly 70% of stroke survivors asymmetrical walking patterns and reduced walking speed persist. This case series study aims to investigate the effectiveness of transcutaneous spinal cord stimulation (tSCS) in enhancing walking ability of persons with chronic stroke. METHODS: Eight participants with hemiparesis after a single, chronic stroke were enrolled. Each participant was assigned to either the Stim group (N = 4, gait training + tSCS) or Control group (N = 4, gait training alone). Each participant in the Stim group was matched to a participant in the Control group based on age, time since stroke, and self-selected gait speed. For the Stim group, tSCS was delivered during gait training via electrodes placed on the skin between the spinous processes of C5-C6, T11-T12, and L1-L2. Both groups received 24 sessions of gait training over 8 weeks with a physical therapist providing verbal cueing for improved gait symmetry. Gait speed (measured from 10 m walk test), endurance (measured from 6 min walk test), spatiotemporal gait symmetries (step length and swing time), as well as the neurophysiological outcomes (muscle synergy, resting motor thresholds via spinal motor evoked responses) were collected without tSCS at baseline, completion, and 3 month follow-up. RESULTS: All four Stim participants sustained spatiotemporal symmetry improvements at the 3 month follow-up (step length: 17.7%, swing time: 10.1%) compared to the Control group (step length: 1.1%, swing time 3.6%). Additionally, 3 of 4 Stim participants showed increased number of muscle synergies and/or lowered resting motor thresholds compared to the Control group. CONCLUSIONS: This study provides promising preliminary evidence that using tSCS as a therapeutic catalyst to gait training may increase the efficacy of gait rehabilitation in individuals with chronic stroke. Trial registration NCT03714282 (clinicaltrials.gov), registration date: 2018-10-18.

Voluntary co-contraction of ankle muscles alters motor unit discharge characteristics and reduces estimates of persistent inward currents.

Motoneuronal persistent inward currents (PICs) are both facilitated by neuromodulatory inputs and highly sensitive to local inhibitory circuits (e.g., Ia reciprocal inhibition). Methods aimed to increase group Ia reciprocal inhibition from the antagonistic muscle have been successful in decreasing PICs, and the diffuse actions of neuromodulators released during activation of remote muscles have increased PICs. However, it remains unknown how motoneurons function in the presence of simultaneous excitatory and inhibitory commands. To probe this topic, we investigated motor unit (MU) discharge patterns and estimated PICs during voluntary co-contraction of ankle muscles, which simultaneously demands the contraction of agonist-antagonist pairs. Twenty young adults randomly performed triangular ramps (10s up and down) of both co-contraction (simultaneous dorsiflexion and plantarflexion) and isometric dorsiflexion to a peak of 30% of their maximum muscle activity from a maximal voluntary contraction. Motor unit spike trains were decomposed from high-density surface electromyography recorded over the tibialis anterior (TA) using blind source separation algorithms. Voluntary co-contraction altered motor unit discharge rate characteristics, decreasing estimates of PICs by 20% (4.47 pulses per second (pps) vs 5.57 pps during isometric dorsiflexion). These findings suggest that, during voluntary co-contraction, the inhibitory input from the antagonist muscle overcomes the additional excitatory and neuromodulatory drive that may occur due to the co-contraction of the antagonist muscle, which constrains PIC behavior.

Estimates of persistent inward currents in lower limb motoneurons are larger in females than in males.

Noninvasive recordings of motor unit (MU) spike trains help us understand how the nervous system controls movement and how it adapts to various physiological conditions. The majority of participants in human and nonhuman animal physiology studies are male, and it is assumed that mechanisms uncovered in these studies are shared between males and females. However, sex differences in neurological impairment and physical performance warrant the study of sex as a biological variable in human physiology and performance. To begin addressing this gap in the study of biophysical properties of human motoneurons, we quantified MU discharge rates and estimates of persistent inward current (PIC) magnitude in both sexes. We decomposed MU spike trains from the tibialis anterior (TA), medial gastrocnemius (MG), and soleus (SOL) using high-density surface electromyography and blind source separation algorithms. Ten participants of each sex performed slow triangular (10 s up and down) isometric contractions to a peak of 30% of their maximum voluntary contraction. We then used linear mixed-effects models to determine if peak discharge rate and estimates of PICs were predicted by the fixed effects of sex, muscle, and their interaction. Despite a lack of sex-differences in peak discharge rates across all muscles, estimates of PICs were larger [χ2(1) = 6.26, P = 0.012] in females [4.73 ± 0.242 pulses per second (pps)] than in males (3.81 ± 0.240 pps). These findings suggest that neuromodulatory drive, inhibitory input, and/or biophysical properties of motoneurons differ between the sexes and may contribute to differences in MU discharge patterns.NEW & NOTEWORTHY Sex-related differences in motoneuron analyses have emerged with greater inclusion of female participants, however, mechanisms for these differences remain unclear. Estimates of persistent inward currents (i.e., ΔF) in motoneurons of the lower limb muscles were larger in females than in males. This suggests neuromodulatory drive, monoaminergic signaling, intrinsic motoneuron properties, and/or descending motor commands may differ between the sexes, which provides a potential mechanism underlying previously reported sex-related differences in motoneuron discharge patterns.

Video-Based Pose Estimation for Gait Analysis in Stroke Survivors during Clinical Assessments: A Proof-of-Concept Study.

Recent advancements in deep learning have produced significant progress in markerless human pose estimation, making it possible to estimate human kinematics from single camera videos without the need for reflective markers and specialized labs equipped with motion capture systems. Such algorithms have the potential to enable the quantification of clinical metrics from videos recorded with a handheld camera. Here we used DeepLabCut, an open-source framework for markerless pose estimation, to fine-tune a deep network to track 5 body keypoints (hip, knee, ankle, heel, and toe) in 82 below-waist videos of 8 patients with stroke performing overground walking during clinical assessments. We trained the pose estimation model by labeling the keypoints in 2 frames per video and then trained a convolutional neural network to estimate 5 clinically relevant gait parameters (cadence, double support time, swing time, stance time, and walking speed) from the trajectory of these keypoints. These results were then compared to those obtained from a clinical system for gait analysis (GAITRite®, CIR Systems). Absolute accuracy (mean error) and precision (standard deviation of error) for swing, stance, and double support time were within 0.04 ± 0.11 s; Pearson's correlation with the reference system was moderate for swing times (r = 0.4-0.66), but stronger for stance and double support time (r = 0.93-0.95). Cadence mean error was -0.25 steps/min ± 3.9 steps/min (r = 0.97), while walking speed mean error was -0.02 ± 0.11 m/s (r = 0.92). These preliminary results suggest that single camera videos and pose estimation models based on deep networks could be used to quantify clinically relevant gait metrics in individuals poststroke, even while using assistive devices in uncontrolled environments. Such development opens the door to applications for gait analysis both inside and outside of clinical settings, without the need of sophisticated equipment.

Rapid Screening of Physiological Changes Associated With COVID-19 Using Soft-Wearables and Structured Activities: A Pilot Study.

OBJECTIVE: Controlling the spread of the COVID-19 pandemic largely depends on scaling up the testing infrastructure for identifying infected individuals. Consumer-grade wearables may present a solution to detect the presence of infections in the population, but the current paradigm requires collecting physiological data continuously and for long periods of time on each individual, which poses limitations in the context of rapid screening. Technology: Here, we propose a novel paradigm based on recording the physiological responses elicited by a short (~2 minutes) sequence of activities (i.e. "snapshot"), to detect symptoms associated with COVID-19. We employed a novel body-conforming soft wearable sensor placed on the suprasternal notch to capture data on physical activity, cardio-respiratory function, and cough sounds. RESULTS: We performed a pilot study in a cohort of individuals (n=14) who tested positive for COVID-19 and detected altered heart rate, respiration rate and heart rate variability, relative to a group of healthy individuals (n=14) with no known exposure. Logistic regression classifiers were trained on individual and combined sets of physiological features (heartbeat and respiration dynamics, walking cadence, and cough frequency spectrum) at discriminating COVID-positive participants from the healthy group. Combining features yielded an AUC of 0.94 (95% CI=[0.92, 0.96]) using a leave-one-subject-out cross validation scheme. Conclusions and Clinical Impact: These results, although preliminary, suggest that a sensor-based snapshot paradigm may be a promising approach for non-invasive and repeatable testing to alert individuals that need further screening.

Strain Differences in Responsiveness to Repeated Restraint Stress Affect Remote Contextual Fear Memory and Blood Transcriptomics.

The role of stress in altering fear memory is not well understood. Since individual variations in stress reactivity exist, and stress alters fear memory, exposing individuals with differing stress-reactivity to repeated stress would affect their fear memory to various degrees. We explored this question using the average stress-reactive Fisher 344 (F344) rat strain and the Wistar-Kyoto (WKY) strain with its heightened stress-reactivity. Male F344 and WKY rats were exposed to the contextual fear conditioning (CFC) paradigm and then chronic restraint stress (CRS) or no stress (NS) was administered for two weeks before a second CFC. Both recent and reinstated fear memory were greater in F344s than WKYs, regardless of the stress status. In contrast, remote memory was attenuated only in F344s after CRS. In determining whether this strain-specific response to CRS was mirrored by transcriptomic changes in the blood, RNA sequencing was carried out. Overlapping differentially expressed genes (DEGs) between NS and CRS in the blood of F344 and WKY suggest a convergence of stress-related molecular mechanisms, independent of stress-reactivity. In contrast, DEGs unique to the F344 and the WKY stress responses are divergent in their functionality and networks, beyond that of strain differences in their non-stressed state. These results suggest that in some individuals chronic or repeated stress, different from the original fear memory-provoking stress, can attenuate prior fear memory. Furthermore, the novel blood DEGs can report on the general state of stress of the individual, or can be associated with individual variation in stress-responsiveness.

Genetic Model to Study the Co-Morbid Phenotypes of Increased Alcohol Intake and Prior Stress-Induced Enhanced Fear Memory.

Posttraumatic Stress Disorder (PTSD) is a complex illness, frequently co-morbid with depression, caused by both genetics, and the environment. Alcohol Use Disorder (AUD), which also co-occurs with depression, is often co-morbid with PTSD. To date, very few genes have been identified for PTSD and even less for PTSD comorbidity with AUD, likely because of the phenotypic heterogeneity seen in humans, combined with each gene playing a relatively small role in disease predisposition. In the current study, we investigated whether a genetic model of depression-like behavior, further developed from the depression model Wistar Kyoto (WKY) rat, is a suitable vehicle to uncover the genetics of co-morbidity between PTSD and AUD. The by-now inbred WKY More Immobile (WMI) and the WKY Less Immobile (WLI) rats were generated from the WKY via bidirectional selective breeding using the forced swim test, a measure of despair-like behavior, as the functional selector. The colonies of the WMIs that show despair-like behavior and the control strain showing less or no despair-like behavior, the WLI, are maintained with strict inbreeding over 40 generations to date. WMIs of both sexes intrinsically self-administer more alcohol than WLIs. Alcohol self-administration is increased in the WMIs without sucrose fading, water deprivation or any prior stress, mimicking the increased voluntary alcohol-consumption of subjects with AUD. Prior Stress-Enhanced Fear Learning (SEFL) is a model of PTSD. WMI males, but not females, show increased SEFL after acute restraint stress in the context-dependent fear conditioning paradigm, a sexually dimorphic pattern similar to human data. Plasma corticosterone differences between stressed and not-stressed WLI and WMI male and female animals immediately prior to fear conditioning predict SEFL results. These data demonstrate that the WMI male and its genetically close, but behaviorally divergent control the WLI male, would be suitable for investigating the underlying genetic basis of comorbidity between SEFL and alcohol self-administration.