Short-Term Immobilization Promotes a Rapid Loss of Motor Evoked Potentials and Strength That Is Not Rescued by rTMS Treatment.
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ABSTRACT:
SUBMITTER: Gaffney CJ
PROVIDER: S-EPMC8107283 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Motor Evoked Potentials (MEPs) are used to monitor disability progression in multiple sclerosis (MS). Their morphology plays an important role in this process. Currently, however, there is no clear definition of what constitutes a normal or abnormal morphology. To address this, five experts independently labeled the morphology (normal or abnormal) of the same set of 1,000 MEPs. The intra- and inter-rater agreement between the experts indicates they agree on the concept of morphology, but differ in their choice of threshold between normal and abnormal morphology. We subsequently performed an automated extraction of 5,943 time series features from the MEPs to identify a valid proxy for morphology, based on the provided labels. To do this, we compared the cross-validation performances of one-dimensional logistic regression models fitted to each of the features individually. We find that the approximate entropy (ApEn) feature can accurately reproduce the majority-vote labels. The performance of this feature is evaluated on an independent test set by comparing to the majority vote of the neurologists, obtaining an AUC score of 0.92. The model slightly outperforms the average neurologist at reproducing the neurologists consensus-vote labels. We can conclude that MEP morphology can be consistently defined by pooling the interpretations from multiple neurologists and that ApEn is a valid continuous score for this. Having an objective and reproducible MEP morphological abnormality score will allow researchers to include this feature in their models, without manual annotation becoming a bottleneck. This is crucial for large-scale, multi-center datasets. An exploratory analysis on a large single-center dataset shows that ApEn is potentially clinically useful. Introducing an automated, objective, and reproducible definition of morphology could help overcome some of the barriers that are currently obstructing broad adoption of evoked potentials in daily care and patient follow-up, such as standardization of measurements between different centers, and formulating guidelines for clinical use.
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Project description:The vertex potential is the largest response that can be recorded in the electroencephalogram of an awake, healthy human. It is elicited by sudden and intense stimuli, and is composed by a negative-positive deflection. The stimulus properties that determine the vertex potential amplitude have been well characterized. Nonetheless, its functional significance remains elusive. The dominant interpretation is that it reflects neural activities related to the detection of salient stimuli. However, given that threatening stimuli elicit both vertex potentials and defensive movements, we hypothesized that the vertex potential is related to the execution of defensive actions. Here, we directly compared the salience and motoric interpretations by investigating the relationship between the amplitude of laser-evoked potentials (LEPs) and the response time of movements with different defensive values. First, we show that a larger LEP negative wave (N2 wave) predicts faster motor response times. Second, this prediction is significantly stronger when the motor response is defensive in nature. Third, the relation between the N2 wave and motor response time depends not only on the kinematic form of the movement, but also on whether that kinematic form serves as a functional defense of the body. Therefore, the N2 wave of the LEP encodes key defensive reactions to threats.
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Project description:The rat spinal cord isolated from supraspinal control via a complete low- to midthoracic spinal cord transection produces locomotor-like patterns in the hindlimbs when facilitated pharmacologically and/or by epidural electrical stimulation. To evaluate the role of epidural electrical stimulation in enabling motor control (eEmc) for locomotion and posture, we recorded potentials evoked by epidural spinal cord stimulation in selected hindlimb muscles during stepping and standing in adult spinal rats. We hypothesized that the temporal details of the phase-dependent modulation of these evoked potentials in selected hindlimb muscles while performing a motor task in the unanesthetized state would be predictive of the potential of the spinal circuitries to generate stepping. To test this hypothesis, we characterized soleus and tibialis anterior (TA) muscle responses as middle response (MR; 4-6 ms) or late responses (LRs; >7 ms) during stepping with eEmc. We then compared these responses to the stepping parameters with and without a serotoninergic agonist (quipazine) or a glycinergic blocker (strychnine). Quipazine inhibited the MRs induced by eEmc during nonweight-bearing standing but facilitated locomotion and increased the amplitude and number of LRs induced by eEmc during stepping. Strychnine facilitated stepping and reorganized the LRs pattern in the soleus. The LRs in the TA remained relatively stable at varying loads and speeds during locomotion, whereas the LRs in the soleus were strongly modulated by both of these variables. These data suggest that LRs facilitated electrically and/or pharmacologically are not time-locked to the stimulation pulse but are highly correlated to the stepping patterns of spinal rats.
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Project description:Background: Hereditary Spastic Paraplegia (HSP) is a slowly progressive neurodegenerative disorder with no disease modifying treatment. Potential therapeutic approaches are emerging and large-scale clinical drug trials for patients with HSP are imminent. A sensitive biomarker to measure the drug efficacy in these trials is required. Motor evoked potentials (MEPs) are a potential biomarker for HSP as they assess the central motor pathways and can be standardized with set protocols and guidelines. Objectives: We performed a systematic review to investigate the utility of MEPs as a diagnostic and disease severity biomarker for HSP. Search Methods: Systematic searches of PubMed, Embase, Medline, and Scopus were performed. Selection Criteria: Studies reporting on central motor conduction time measured with MEPs in adult and pediatric patients with HSP were included. We excluded studies in non-HSP patient cohorts, not in English, not original research, and unpublished journal articles. Data Collection and analysis: Search results were de-duplicated and screened according to the inclusion and exclusion criteria. The included papers were reviewed independently by two reviewers and data was collected on patient cohorts, test methods, results, and study quality. Results were analyzed using descriptive methods. Results: Of the 882 search results, 32 studies were included in the review. The most common finding was absent or prolonged lower limb (LL) central motor conduction time (CMCT) in patients with HSP (78% of patients studied). Quality assessment revealed variability in study methodology and reporting of results. Variations included patient cohorts of various genotypes as well as variations in equipment and techniques used. Aside from CMCT, none of the MEP parameter measures correlated with disease severity and many did not show significant difference between HSP patients and controls. Conclusion: Systematic review of MEP studies in HSP patient cohorts demonstrated mixed findings. Lower limb CMCT was the most promising parameter in terms of differentiating HSP patients from controls, with one study demonstrating a weak correlation with clinical disease severity. It is possible that the lack of consistency in study methodologies and small patient cohorts have contributed to the variable findings. A longitudinal study of MEPs in a large cohort of HSP patients with the same genotype will help clarify the utility of MEPs as a biomarker for disease severity and use in clinical trials.
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Project description:Objective. Motor-evoked potentials (MEPs) are among the most prominent responses to brain stimulation, such as supra-threshold transcranial magnetic stimulation and electrical stimulation. Understanding of the neurophysiology and the determination of the lowest stimulation strength that evokes responses requires the detection of even smaller responses, e.g. from single motor units. However, available detection and quantization methods suffer from a large noise floor. This paper develops a detection method that extracts MEPs hidden below the noise floor. With this method, we aim to estimate excitatory activations of the corticospinal pathways well below the conventional detection level.Approach. The presented MEP detection method presents a self-learning matched-filter approach for improved robustness against noise. The filter is adaptively generated per subject through iterative learning. For responses that are reliably detected by conventional detection, the new approach is fully compatible with established peak-to-peak readings and provides the same results but extends the dynamic range below the conventional noise floor.Main results. In contrast to the conventional peak-to-peak measure, the proposed method increases the signal-to-noise ratio by more than a factor of 5. The first detectable responses appear to be substantially lower than the conventional threshold definition of 50µV median peak-to-peak amplitude.Significance. The proposed method shows that stimuli well below the conventional 50µV threshold definition can consistently and repeatably evoke muscular responses and thus activate excitable neuron populations in the brain. As a consequence, the input-output (IO) curve is extended at the lower end, and the noise cut-off is shifted. Importantly, the IO curve extends so far that the 50µV point turns out to be closer to the center of the logarithmic sigmoid curve rather than close to the first detectable responses. The underlying method is applicable to a wide range of evoked potentials and other biosignals, such as in electroencephalography.
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Project description:Muscle motor-evoked potentials are commonly monitored during brain tumour surgery in motor areas, as these are assumed to reflect the integrity of descending motor pathways, including the corticospinal tract. However, while the loss of muscle motor-evoked potentials at the end of surgery is associated with long-term motor deficits (muscle motor-evoked potential-related deficits), there is increasing evidence that motor deficit can occur despite no change in muscle motor-evoked potentials (muscle motor-evoked potential-unrelated deficits), particularly after surgery of non-primary regions involved in motor control. In this study, we aimed to investigate the incidence of muscle motor-evoked potential-unrelated deficits and to identify the associated brain regions. We retrospectively reviewed 125 consecutive patients who underwent surgery for peri-Rolandic lesions using intra-operative neurophysiological monitoring. Intraoperative changes in muscle motor-evoked potentials were correlated with motor outcome, assessed by the Medical Research Council scale. We performed voxel-lesion-symptom mapping to identify which resected regions were associated with short- and long-term muscle motor-evoked potential-associated motor deficits. Muscle motor-evoked potentials reductions significantly predicted long-term motor deficits. However, in more than half of the patients who experienced long-term deficits (12/22 patients), no muscle motor-evoked potential reduction was reported during surgery. Lesion analysis showed that muscle motor-evoked potential-related long-term motor deficits were associated with direct or ischaemic damage to the corticospinal tract, whereas muscle motor-evoked potential-unrelated deficits occurred when supplementary motor areas were resected in conjunction with dorsal premotor regions and the anterior cingulate. Our results indicate that long-term motor deficits unrelated to the corticospinal tract can occur more often than currently reported. As these deficits cannot be predicted by muscle motor-evoked potentials, a combination of awake and/or novel asleep techniques other than muscle motor-evoked potentials monitoring should be implemented.
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Project description:Stimulating the nervous system and measuring muscle response offers a unique opportunity to interrogate motor system function. Often, this is performed by stimulating motor cortex and recording muscle activity with electromyography; the evoked response is called the motor evoked potential (MEP). To understand system dynamics, MEPs are typically recorded through a range of motor cortex stimulation intensities. The MEPs increase with increasing stimulation intensities, and these typically produce a sigmoidal response curve. Analysis of MEPs is often complex and analysis of response curves is time-consuming. We created an MEP analysis software, called Motometrics, to facilitate analysis of MEPs and response curves. The goal is to combine robust signal processing algorithms with a simple user interface. Motometrics first enables the user to annotate data files acquired from the recording system so that the responses can be extracted and labeled with the correct subject and experimental condition. The software enables quick visual representations of entire datasets, to ensure uniform quality of the signal. It then enables the user to choose a variety of response curve analyses and to perform near real time quantification of the MEPs for quick feedback during experimental procedures. This is a modular open source tool that is compatible with several popular electrophysiological systems. Initial use indicates that Motometrics enables rapid, robust, and intuitive analysis of MEP response curves by neuroscientists without programming or signal processing expertise.
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Project description:ObjectiveMotor evoked potentials (MEPs) play a pivotal role in transcranial magnetic stimulation (TMS), e.g., for determining the motor threshold and probing cortical excitability. Sampled across the range of stimulation strengths, MEPs outline an input-output (IO) curve, which is often used to characterize the corticospinal tract. More detailed understanding of the signal generation and variability of MEPs would provide insight into the underlying physiology and aid correct statistical treatment of MEP data.MethodsA novel regression model is tested using measured IO data of twelve subjects. The model splits MEP variability into two independent contributions, acting on both sides of a strong sigmoidal nonlinearity that represents neural recruitment. Traditional sigmoidal regression with a single variability source after the nonlinearity is used for comparison.ResultsThe distribution of MEP amplitudes varied across different stimulation strengths, violating statistical assumptions in traditional regression models. In contrast to the conventional regression model, the dual variability source model better described the IO characteristics including phenomena such as changing distribution spread and skewness along the IO curve.ConclusionsMEP variability is best described by two sources that most likely separate variability in the initial excitation process from effects occurring later on. The new model enables more accurate and sensitive estimation of the IO curve characteristics, enhancing its power as a detection tool, and may apply to other brain stimulation modalities. Furthermore, it extracts new information from the IO data concerning the neural variability-information that has previously been treated as noise.
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Project description:The evaluation of transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEPs) promises valuable information about fundamental brain related mechanisms and may serve as a diagnostic tool for clinical monitoring of therapeutic progress or surgery procedures. However, reports about spontaneous fluctuations of MEP amplitudes causing high intra-individual variability have led to increased concerns about the reliability of this measure. One possible cause for high variability of MEPs could be neuronal oscillatory activity, which reflects fluctuations of membrane potentials that systematically increase and decrease the excitability of neuronal networks. Here, we investigate the dependence of MEP amplitude on oscillation power and phase by combining the application of single pulse TMS over the primary motor cortex with concurrent recordings of electromyography and electroencephalography. Our results show that MEP amplitude is correlated to alpha phase, alpha power as well as beta phase. These findings may help explain corticospinal excitability fluctuations by highlighting the modulatory effect of alpha and beta phase on MEPs. In the future, controlling for such a causal relationship may allow for the development of new protocols, improve this method as a (diagnostic) tool and increase the specificity and efficacy of general TMS applications.
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Project description:Background. After stroke, recovery of movement in proximal and distal upper extremity (UE) muscles appears to follow different time courses, suggesting differences in their neural substrates. Objective. We sought to determine if presence or absence of motor evoked potentials (MEPs) differentially influences recovery of volitional contraction and strength in an arm muscle versus an intrinsic hand muscle. We also related MEP status to recovery of proximal and distal interjoint coordination and movement fractionation, as measured by the Fugl-Meyer Assessment (FMA). Methods. In 45 subjects in the year following ischemic stroke, we tracked the relationship between corticospinal tract (CST) integrity and behavioral recovery in the biceps (BIC) and first dorsal interosseous (FDI) muscle. We used transcranial magnetic stimulation to probe CST integrity, indicated by MEPs, in BIC and FDI. We used electromyography, dynamometry, and UE FMA subscores to assess muscle-specific contraction, strength, and inter-joint coordination, respectively. Results. Presence of MEPs resulted in higher likelihood of muscle contraction, greater strength, and higher FMA scores. Without MEPs, BICs could more often volitionally contract, were less weak, and had steeper strength recovery curves than FDIs; in contrast, FMA recovery curves plateaued below normal levels for both the arm and hand. Conclusions. There are shared and separate substrates for paretic UE recovery. CST integrity is necessary for interjoint coordination in both segments and for overall recovery. In its absence, alternative pathways may assist recovery of volitional contraction and strength, particularly in BIC. These findings suggest that more targeted approaches might be needed to optimize UE recovery.
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