Usefulness of Time-Frequency Patterns of Somatosensory Evoked Potentials in Identification of the Location of Spinal Cord Injury

Tactile Location Perception Encoded by Gamma-Band Power

BACKGROUND

The perception of tactile-stimulation locations is an important function of the human somatosensory system during body movements and its interactions with the surroundings. Previous psychophysical and neurophysiological studies have focused on spatial location perception of the upper body. In this study, we recorded single-trial electroencephalography (EEG) responses evoked by four vibrotactile stimulators placed on the buttocks and thighs while the human subject was sitting in a chair with a cushion.

METHODS

Briefly, 14 human subjects were instructed to sit in a chair for a duration of 1 h or 1 h and 45 min. Two types of cushions were tested with each subject: a foam cushion and an air-cell-based cushion dedicated for wheelchair users to alleviate tissue stress. Vibrotactile stimulations were applied to the sitting interface at the beginning and end of the sitting period. Somatosensory-evoked potentials were obtained using a 32-channel EEG. An artificial neural net was used to predict the tactile locations based on the evoked EEG power.

RESULTS

We found that single-trial beta (13-30 Hz) and gamma (30-50 Hz) waves can best predict the tactor locations with an accuracy of up to 65%. Female subjects showed the highest performances, while males' sensitivity tended to degrade after the sitting period. A three-way ANOVA analysis indicated that the air-cell cushion maintained location sensitivity better than the foam cushion.

CONCLUSION

Our finding shows that tactile location information is encoded in EEG responses and provides insights on the fundamental mechanisms of the tactile system, as well as applications in brain-computer interfaces that rely on tactile stimulation.

Identifying Intraoperative Spinal Cord Injury Location from Somatosensory Evoked Potentials' Time-Frequency Components

Excessive distraction in corrective spine surgery can lead to iatrogenic distraction spinal cord injury. Diagnosis of the location of the spinal cord injury helps in early removal of the injury source. The time-frequency components of the somatosensory evoked potential have been reported to provide information on the location of spinal cord injury, but most studies have focused on contusion injuries of the cervical spine. In this study, we established 19 rat models of distraction spinal cord injury at different levels and collected the somatosensory evoked potentials of the hindlimb and extracted their time-frequency components. Subsequently, we used k-medoid clustering and naive Bayes to classify spinal cord injury at the C5 and C6 level, as well as spinal cord injury at the cervical, thoracic, and lumbar spine, respectively. The results showed that there was a significant delay in the latency of the time-frequency components distributed between 15 and 30 ms and 50 and 150 Hz in all spinal cord injury groups. The overall classification accuracy was 88.28% and 84.87%. The results demonstrate that the k-medoid clustering and naive Bayes methods are capable of extracting the time-frequency component information depending on the spinal cord injury location and suggest that the somatosensory evoked potential has the potential to diagnose the location of a spinal cord injury.

A Prediction Model for Normal Variation of Somatosensory Evoked Potential During Scoliosis Surgery

Somatosensory evoked potential (SEP) has been commonly used as intraoperative monitoring to detect the presence of neurological deficits during scoliosis surgery. However, SEP usually presents an enormous variation in response to patient-specific factors such as physiological parameters leading to the false warning. This study proposes a prediction model to quantify SEP amplitude variation due to noninjury-related physiological changes of the patient undergoing scoliosis surgery. Based on a hybrid network of attention-based long-short-term memory (LSTM) and convolutional neural networks (CNNs), we develop a deep learning-based framework for predicting the SEP value in response to variation of physiological variables. The training and selection of model parameters were based on a 5-fold cross-validation scheme using mean square error (MSE) as evaluation metrics. The proposed model obtained MSE of 0.027[Formula: see text][Formula: see text] on left cortical SEP, MSE of 0.024[Formula: see text][Formula: see text] on left subcortical SEP, MSE of 0.031[Formula: see text][Formula: see text] on right cortical SEP, and MSE of 0.025[Formula: see text][Formula: see text] on right subcortical SEP based on the test set. The proposed model could quantify the affection from physiological parameters to the SEP amplitude in response to normal variation of physiology during scoliosis surgery. The prediction of SEP amplitude provides a potential varying reference for intraoperative SEP monitoring.

Different Time-frequency Distribution Patterns of Somatosensory Evoked Potentials in Dual- and Single-level Spinal Cord Compression

Among patients with cervical myelopathy, the most common level of stenosis at spinal cord of all ages was reported to be between cervical levels C5-6. Previous studies found that time-frequency components (TFCs) of somatosensory evoked potentials (SEPs) possess location information of spinal cord injury (SCI) in single-level deficits in the spinal cord. However, the clinical reality is that there are multiple compressions at multiple spinal cord segments. This study proposed a new algorithm to differentiate distribution patterns of SEP TFCs between the dual-level compression and the corresponding single-level compression, which is potentials in providing precise diagnosis of cervical myelopathy. In the present animal study, a group of rats with dual-level compressive (C5+6) injury to cervical spinal cord was investigated. SEPs were collected at 2 weeks after surgery, while SEP TFCs were calculated. The SEP TFCs under dual-level compression were compared to an existent dataset with one sham control group and three single level compression groups at C4, C5, C6. Behavioral evaluation showed very similar scale of injury severity between individual rats, while histology evaluation confirmed the precise location of injury. According to time-frequency distribution patterns, it showed that the middle-energy components of dual-level showed similar patterns as that of each single-level group. In addition, the low-energy components of the dual-level C5+6 group had the highest correlation with C5 (R=0.3423, p<0.01) and C6 (R=0.4000, p<0.01) groups, but much lower with C4 group (R=0.1071, p=0.012). These results indicated that SEP TFCs components possess information regarding the location of neurological lesion after spinal cord compression. It preliminarily demonstrated that SEP TFCs are likely a useful measure to provide location information of neurological lesions after compression SCI.

Interhemispheric differences in time-frequency representation of motor evoked potentials in brain tumor patients

OBJECTIVE

Conventional time-series parameters are unreliable descriptors of motor-evoked potentials (MEPs) in brain tumor patients. Frequency domain analysis is suggested to provide additional information about the status of the cortico-spinal motor system. Aim of the present study was to describe the time-frequency representation of MEPs and its relation to the motor performance.

METHODS

This study enrolled 17 consecutive brain tumor patients with impaired dexterity. After brain mapping of the affected (AH) and non-affected (NAH) hemisphere, TMS was applied to the hotspots of the abductor pollicis brevis muscles (APB). Using a Morlet wavelet approach, event-related spectral perturbation (ERSP) and inter-trial coherence (ITC) of the MEPs were calculated and compared to the Grooved Pegboard Test (GPT). Additionally, inter- and intra-subject reliability was assessed by the intraclass correlation coefficient (ICC).

RESULTS

MEPs were projecting to a frequency band between 30 and 400 Hz with a local maximum between 100 and 150 Hz. There was a significant ERSP and ITC reduction of the AH in comparison to the NAH. In contrast, no interhemispheric differences were depicted in the conventional time-series analysis. ERSP and ITC values correlated significantly with GPT results (r = 0.35 and r = 0.50). Time-frequency MEP description had good inter-and intra-subject reliability (ICC = 0.63).

CONCLUSIONS

Brain tumors affect corticospinal transmission resulting in a reduction of temporal and spectral MEP synchronization correlating with the dexterity performance.

SIGNIFICANCE

Time-frequency representation of MEPs provide additional information beyond conventional time-domain features.

Time-Frequency Representation of Motor Evoked Potentials in Brain Tumor Patients

Background: The integrity of the motor system can be examined by applying navigated transcranial magnetic stimulation (nTMS) to the cortex. The corresponding motor-evoked potentials (MEPs) in the target muscles are mirroring the status of the human motor system, far beyond corticospinal integrity. Commonly used time domain features of MEPs (e.g., peak-to-peak amplitudes and onset latencies) exert a high inter-subject and intra-subject variability. Frequency domain analysis might help to resolve or quantify disease-related MEP changes, e.g., in brain tumor patients. The aim of the present study was to describe the time-frequency representation of MEPs in brain tumor patients, its relation to clinical and imaging findings, and the differences to healthy subject.

Methods: This prospective study compared 12 healthy subjects with 12 consecutive brain tumor patients (with and without a paresis) applying nTMS mapping. Resulting MEPs were evaluated in the time series domain (i.e., amplitudes and latencies). After transformation into the frequency domain using a Morlet wavelet approach, event-related spectral perturbation (ERSP), and inter-trial coherence (ITC) were calculated and compared to diffusion tensor imaging (DTI) results.

Results: There were no significant differences in the time series characteristics between groups. MEPs were projecting to a frequency band between 30 and 300 Hz with a local maximum around 100 Hz for both healthy subjects and patients. However, there was ERSP reduction for higher frequencies (>100 Hz) in patients in contrast to healthy subjects. This deceleration was mirrored in an increase of the inter-peak MEP latencies. Patients with a paresis showed an additional disturbance in ITC in these frequencies. There was no correlation between the CST integrity (as measured by DTI) and the MEP parameters.

Conclusion: Time-frequency analysis may provide additional information above and beyond classical MEP time domain features and the status of the corticospinal system in brain tumor patients. This first evaluation indicates that brain tumors might affect cortical physiology and the responsiveness of the cortex to TMS resulting in a temporal dispersion of the corticospinal transmission.

Exploration of Cervical Myelopathy Location From Somatosensory Evoked Potentials Using Random Forests Classification

Studies using time-frequency analysis have reported that somatosensory evoked potentials provide information regarding the location of spinal cord injury. However, a better understanding of the time-frequency components derived from somatosensory evoked potentials is essential for developing more reliable algorithms that can diagnosis level (location) of cervical injury. In the present study, we proposed a random forests machine learning approach, for separating somatosensory evoked potentials depending on spinal cord state. For data acquisition, we established rat models of compression spinal cord injury at the C4, C5, and C6 levels to induce cervical myelopathy. After making the compression injury, we collected somatosensory evoked potentials and extracted their time-frequency components. We then used the random forests classification system to analyze the evoked potential dataset that was obtained from the three groups of model rats. Evaluation of the classifier performance revealed an overall classification accuracy of 84.72%, confirming that the random forests method was able to separate the time-frequency components of somatosensory evoked potentials from rats under different conditions. Features of the time-frequency components contained information that could identify the location of the cervical spinal cord injury, demonstrating the potential benefits of using time-frequency components of somatosensory evoked potentials to diagnose the level of cervical injury in cervical myelopathy.

The correlation between hypoxia-inducible factor-1α, matrix metalloproteinase-9 and functional recovery following chronic spinal cord compression

The molecular mechanisms underlying cervical spondylotic myelopathy (CSM) are poorly understood. To assess the correlation between HIF-1α, MMP-9 and functional recovery following chronic cervical spinal cord compression (CSCI). Rats in the sham group underwent C5 semi-laminectomy, while a water-absorbable polyurethane polymer was implanted into the C6 epidural space in the chronic CSCI group. Basso, Beattie and Bresnahan score and somatosensory evoked potentials were used to evaluate neurological function. Hematoxylin and eosin staining was performed to assess pathological changes in the spinal cord, while immunohistochemical analysis was used to examine HIF-1α and MMP-9 expression on days 7, 28, 42 and 70 post-surgery. Normal rats were only used for HE staining. The BBB score was significantly reduced on day 28 following CSCI, while SEPs exhibited decreased amplitude and increased latency. In chronic CSCI group, the BBB score and SEPs significantly improved on day 70 compared with day 28. HE staining revealed different level of spinal cord edema after chronic CSCI. Compared with the sham group, immunohistochemical analyses revealed that HIF-1α- and MMP-9-positive cells were increased on day 7 and peaked on day 28. HIF-1α and MMP-9 expression were demonstrated to be significantly positively correlated, whereas HIF-1α expression and BBB score were significantly negatively correlated, as well MMP-9 expression and BBB score. HIF-1α and MMP-9 expression are increased following chronic spinal cord compression and are positively correlated with one another. Decreased expression of HIF-1α and MMP-9 may contribute to functional recovery following CSCI. This expression pattern of HIF-1α and MMP-9 may give a new perspective on the molecular mechanisms of CSM.

Component analysis of somatosensory evoked potentials for identifying spinal cord injury location

This study aims to determine whether the time-frequency components (TFCs) of somatosensory evoked potentials (SEPs) can be used to identify the specific location of a compressive spinal cord injury using a classification technique. Waveforms of SEPs after compressive injuries at various locations (C4, C5 and C6) in rat spinal cords were decomposed into a series of TFCs using a high-resolution time-frequency analysis method. A classification method based on support vector machine (SVM) was applied to the distributions of these TFCs among different pathological locations. The difference among injury locations manifests itself in different categories of SEP TFCs. High-energy TFCs of normal-state SEPs have significantly higher power and frequency than those of injury-state SEPs. The location of C5 is characterized by a unique distribution pattern of middle-energy TFCs. The difference between C4 and C6 is evidenced by the distribution pattern of low-energy TFCs. The proposed classification method based on SEP TFCs offers a discrimination accuracy of 80.2%. In this study, meaningful information contained in various SEP components was investigated and used to propose a new application of SEPs for identification of the location of pathological changes in the cervical spinal cord.

Topography of Synchronization of Somatosensory Evoked Potentials Elicited by Stimulation of the Sciatic Nerve in Rat

Purpose: Traditionally, the topography of somatosensory evoked potentials (SEPs) is generated based on amplitude and latency. However, this operation focuses on the physical morphology and field potential-power, so it suffers from difficulties in performing identification in an objective manner. In this study, measurement of the synchronization of SEPs is proposed as a method to explore brain functional networks as well as the plasticity after peripheral nerve injury.

Method: SEPs elicited by unilateral sciatic nerve stimulation in twelve adult male Sprague-Dawley (SD) rats in the normal group were compared with SEPs evoked after unilateral sciatic nerve hemisection in four peripheral nerve injured SD rats. The characterization of synchronized networks from SEPs was conducted using equal-time correlation, correlation matrix analysis, and comparison to randomized surrogate data. Eigenvalues of the correlation matrix were used to identify the clusters of functionally synchronized neuronal activity, and the participation index (PI) was calculated to indicate the involvement of each channel in the cluster. The PI value at the knee point of the PI histogram was used as a threshold to demarcate the cortical boundary.

Results: Ten out of the twelve normal rats showed only one synchronized brain network. The remaining two normal rats showed one strong and one weak network. In the peripheral nerve injured group, only one synchronized brain network was found in each rat. In the normal group, all network shapes appear regular and the network is largely contained in the posterior cortex. In the injured group, the network shapes appear irregular, the network extends anteriorly and posteriorly, and the network area is significantly larger. There are considerable individual variations in the shape and location of the network after peripheral nerve injury.

Conclusion: The proposed method can detect functional brain networks. Compared to the results of the traditional SEP-morphology-based analysis method, the synchronized functional network area is much larger. Furthermore, the proposed method can also characterize the rapid cortical plasticity after a peripheral nerve is acutely injured.