Spasticity Predicts Motor Recovery for Patients with Subacute Motor Complete Spinal Cord Injury

The discharge characteristics of motor units innervating functionally paralyzed muscles

For individuals with motor complete spinal cord injury (SCI), previous works have shown that spared motor neurons below the injury level can still be voluntarily controlled. In this study, we investigated the behavior of these neurons after SCI by analyzing neural and spatial properties of individual motor units using high-density surface electromyography (HDsEMG) and ultrasound imaging. The dataset for this study is based on motor unit data from our previous work (Oliveira et al. Brain 147: 3583-3595, 2024). Eight participants with chronic motor complete SCI and twelve uninjured controls attempted multiple hand movements, guided by a virtual hand, while we recorded forearm muscle activity. We analyzed the common synaptic input to motor neurons with a factorization method and found two dominant motor unit modes in both the SCI and control groups. Each mode was strongly correlated with the virtual hand's flexion or extension movements. The delay between flexion and extension movements and the motor unit modes was similar between groups, suggesting preserved common input to motor neurons after SCI. We classified motor units into task-modulated or nonmodulated (i.e., tonic or irregularly firing) based on their discharge patterns and phase difference with virtual hand kinematics and found a higher proportion of nonmodulated motor units in the SCI group. At the motor unit action potential level, we found larger motor unit territories after SCI. Finally, we observed distinct movements of paralyzed muscles with concurrent HDsEMG and ultrasound imaging, indicating the presence of highly functional motor units with distinct spared territories after SCI.NEW & NOTEWORTHY Here, we observed a similar pattern of motor unit activation during attempted hand movements in individuals with complete SCI, who cannot move their fingers, and in a control group, who performed the prescribed movements. Despite differences in individual motor unit behavior between these groups, such as a higher proportion of nonmodulated motor units in SCI, movement intention can still be decoded from paralyzed muscles.

The 4S of spinal astrocytoma: specific location, syrinx, spasticity and score on Modified Mccormick Scale (MMS) predict long term outcomes in patients undergoing surgical resection of intramedullary spinal astrocytomas

OBJECTIVES

The aim of this study was to explore the factors that could predict long term clinical outcomes in SA.

METHODS

A retrospective study was conducted wherein SA patients undergoing surgical resection with a minimum follow up of 12 months were included in this study. Modified Mccormick Scale (MMS) was utilized to record the neurological status of the patients both preoperatively and at last follow up. Outcomes were assessed as: long term neurological status, that is final MMS grade and neurological deterioration, defined as increase in MMS score as compared to preoperative MMS score. Survival analysis was performed using the kaplan meier curves.

RESULTS

71 patients were included in this study with mean age of 33.07years. At a mean follow up of 57 months, preoperative MMS was the single independent predictor for moderate-severe neurological deficit (MMS III to V) on multivariate analysis (OR: 30.2, p < 0.001) and had an outstanding AUC of 0.91. Six patients had neurological deterioration at long term follow up. Absence of spasticity (p = 0.028), thoracic-thoracolumbar tumors (p = 0.006), low MMS score (p = 0.01) and hypointense T1 weighted MRI (p = 0.009) were significant predictors of long term neurological deterioration. The median overall survival was 48 months and was significantly higher in low grade tumors (p < 0.001).

CONCLUSION

The study highlights the efficacy of clinical features as a predictor of long term functional outcomes in SA patients. Role of spasticity as a prognostic factor was explored for the first time in this study.

Altered Dynamic Brain Functional Network Connectivity Related to Visual Network in Spinal Cord Injury

Visual feedback training (VFT) plays an important role in the motor rehabilitation of patients with spinal cord injury (SCI). However, the neural mechanisms are unclear. We aimed to investigate the changes in dynamic functional network connectivity (FNC) related to visual networks (VN) in patients with SCI and to reveal the neural mechanism of VFT promoting motor function rehabilitation. Dynamic FNC and the sliding window method were performed in 18 complete SCI (CSCI), 16 patients with incomplete SCI (ISCI), and 42 healthy controls (HCs). Then, k-mean clustering was implemented to identify discrete FNC states, and temporal properties were computed. The correlations between these dynamic features and neurological parameters in all patients with SCI were calculated. The majority of aberrant FNC was manifested between VN and executive control network (ECN). In addition, compared with HCs, temporal metrics derived from state transition vectors were decreased in patients with CSCI including the mean dwell time and the fraction of time spent in state 3. Furthermore, the disrupted FNC between salience network and ECN in state 2 and the number of transitions were all positively correlated with neurological scores in patients with SCI. Our findings indicated that SCI could result in VN-related FNC alterations, revealing the possible mechanism for VFT in rehabilitation of patients with SCI and increasing the training efficacy and promoting rehabilitation for SCI.

Identification of Spared and Proportionally Controllable Hand Motor Dimensions in Motor Complete Spinal Cord Injuries Using Latent Manifold Analysis

The loss of bilateral hand function is a debilitating challenge for millions of individuals that suffered a motor-complete spinal cord injury (SCI). We have recently demonstrated in eight tetraplegic individuals the presence of highly functional spared spinal motor neurons in the extrinsic muscles of the hand that are still capable of generating proportional flexion and extension signals. In this work, we hypothesized that an artificial intelligence (AI) system could automatically learn the spared electromyographic (EMG) patterns that encode the attempted movements of the paralyzed digits. We constrained the AI to continuously output the attempted movements in the form of a digital hand so that this signal could be used to control any assistive system (e.g. exoskeletons, electrical stimulation). We trained a convolutional neural network using data from 13 uninjured (control) participants and 8 tetraplegic participants (7 motor-complete, 1 incomplete) to study the latent space learned by the AI. Our model can automatically differentiate between eight different hand movements, including individual finger flexions, grasps, and pinches, achieving a mean accuracy of 98.3% within the SCI group. Analysis of the latent space of the model revealed that proportionally controllable movements exhibited an elliptical path, while movements lacking proportional control followed a chaotic trajectory. We found that proportional control of a movement can only be correctly estimated if the latent space embedding of the movement follows an elliptical path (correlation =0.73; p <0.001). These findings emphasize the reliability of the proposed system for closed-loop applications that require an accurate estimate of spinal cord motor output.

Sensory Information Modulates Voluntary Movement in an Individual with a Clinically Motor- and Sensory-Complete Spinal Cord Injury: A Case Report

Motor recovery following a complete spinal cord injury is not likely. This is partially due to insurance limitations. Rehabilitation strategies for individuals with this type of severe injury focus on the compensation for the activities of daily living in the home and community and not on the restoration of function. With limited time in therapies, the initial goals must focus on getting the patient home safely without the expectation of recovery of voluntary movement below the level of injury. In this study, we report a case of an individual with a chronic, cervical (C3)-level clinically motor- and sensory-complete injury who was able to perform voluntary movements with both upper and lower extremities when positioned in a sensory-rich environment conducive to the specific motor task. We show how he is able to intentionally perform push-ups, trunk extensions and leg presses only when appropriate sensory information is available to the spinal circuitry. These data show that the human spinal circuitry, even in the absence of clinically detectable supraspinal input, can generate motor patterns effective for the execution of various upper and lower extremity tasks, only when appropriate sensory information is present. Neurorehabilitation in the right sensory-motor environment that can promote partial recovery of voluntary movements below the level of injury, even in individuals diagnosed with a clinically motor-complete spinal cord injury.