Principles of Electrophysiological Assessments for Movement Disorders

Surface-electromyography characteristics of clonic seizures with no scalp-EEG correlate: A comparative analysis with tremors

INTRODUCTION

Clonic seizures are characterized by twitching movements at a frequency of 0.2-5 Hz. The clonic "twitch" is produced by a brief synchronized contraction of agonist and antagonist muscles, followed by a synchronized silent period. In this study, we aimed to compare the surface-electromyography (sEMG) characteristics of scalp-EEG negative clonic seizures with those of nonepileptic movements like tremors that can resemble clonic seizures.

METHODS

We retrospectively identified patients who were diagnosed with scalp-EEG negative clonic seizures or tremors. We only included patients (n = 6) who were monitored simultaneously with video-EEG and sEMG electrodes. sEMG was placed on agonist and antagonist muscles of the affected extremity using a standardized placement system developed at our institution. We analyzed the following characteristics of sEMG bursts: the relationship between agonist and antagonist muscles and the temporal evolution of burst duration, burst amplitude, and burst frequency.

RESULTS

The following sEMG characteristics were observed: (i) sEMG bursts and corresponding silent periods were synchronous between agonist and antagonist muscles in clonic seizures. In tremors, an alternating pattern was seen. (ii) sEMG burst amplitude increased during the first 10 s of clonic seizures. There was no significant change in tremors. (iii) sEMG burst duration increased from the beginning to end of clonic seizures. There was no significant change in tremors. (iv) sEMG burst frequency decreased from the beginning to end of clonic seizures due to increased burst and silent period duration. There was no consistent change in burst frequency in tremors. (v) sEMG burst duration of ≥250 ms was indicative of a clonic seizure with a >90% positive predictive value.

CONCLUSIONS

Our study describes characteristic sEMG features of clonic seizures without scalp-EEG correlates, which can be used as an objective biomarker in distinguishing these from nonepileptic movements such as tremors.

Diagnostic Value of Bereitschaftspotential in People With Functional Seizures

PURPOSE

Bereitschaftspotential (BP) or readiness potential in people with functional movement disorders can aid diagnostic workup. We evaluated the diagnostic value of BP as an interictal EEG marker in people with functional seizures (FS).

METHODS

We recorded and analyzed BP interictal before intended movements in 17 adults with FS and 17 controls with alternative diagnoses. We evaluated the signals for the presence of BP, latency, amplitude, and early versus late BP.

RESULTS

Bereitschaftspotential was present in all except one person with FS. We found no significant differences in the latency and amplitude of BP between participants with FS and controls. The early BP showed the most significant variance in amplitude, latency, and presence.

CONCLUSIONS

We found interictal typical BP values in participants with FS and variable semiology, while earlier research found interictal no BP in functional movement disorders. These findings do not support the use of BP as an interictal diagnostic tool for FS. Differences in early BP and focus on FS with pure motor semiology are starting points for further research evaluating potential interictal markers in people with FS.

Utility and Value of Movement Recording with Combined EEG-EMG Monitoring in the Intensive Care Unit

Continuous electroencephalographic (EEG) monitoring has become a standard of care in several contexts in the intensive care unit (ICU), especially for the management of refractory status epilepticus. ICU patients often present movement disorders that may be of epileptic or nonepileptic origin, and their correct identification is crucial for the diagnostic and therapeutic process. Video analysis is often insufficient to precisely detect or characterize movement disorders and the ICU environment is prone to many artifacts. Combined EEG electromyogram (EMG) monitoring can enhance the detection of epileptic seizures with subtle motor expression and help identify nonepileptic movement disorders, such as postanoxic myoclonus, dystonia, or tremor. We will review the various scenarios in which combined EEG-EMG monitoring is useful in routine ICU practice. We also provide a practical guide for easily placing surface EMG electrodes during continuous EEG recording, along with clinical examples to illustrate the significance of this combined approach.

Diagnostic Utility of Clinical Neurophysiology in Jerky Movement Disorders: A Review from the MDS Clinical Neurophysiology Study Group

BACKGROUND

Myoclonus and other jerky movement disorders are hyperkinetic disorders, the diagnosis of which heavily relies on clinical neurophysiological testing. However, formal diagnostic criteria are lacking, and recently the utility and reliability of these tests have been questioned.

OBJECTIVE

The aim of this review was to assess the utilization of clinical neurophysiology testing to identify possible gaps and boundaries that might guide the development of new methods for a more precise diagnosis and in-depth understanding of myoclonus.

METHODS

We reviewed electrophysiological features of cortical myoclonus, subcortical myoclonus (ie, myoclonus associated with dystonia, brainstem myoclonus), excessive startle reflex, spinal myoclonus (ie, spinal segmental and propriospinal myoclonus), peripheral myoclonus and mimics of myoclonus of peripheral origin (hemifacial spasm, minipolymyoclonus, myokymia), functional jerky movements, chorea, and tics.

RESULTS

Electrophysiological features that support the recognition of myoclonus subtypes, such as muscle burst duration, muscle pattern of activation, measures of cortical excitability, or movement-related cortical potentials, have been identified. These significantly contribute to the diagnosis of jerky movement disorders, but their reliability is uncertain. Despite the significant advancements, several unresolved questions persist. Factors contributing to this include the absence of systematic neurophysiological assessment and standardized methods, alongside the limited number of patients investigated using these techniques.

CONCLUSION

Although clinical neurophysiology remains the "gold standard" for defining and diagnosing myoclonus, our review highlighted the need to enhance the quality and reliability of neurophysiological testing in jerky movement disorders. Further studies including larger cohorts of patients recruited from different centers, employing standardized and optimized electrophysiological techniques, are warranted.

Substantiating the Short Burst Duration in Cortical Myoclonus

BACKGROUND

Myoclonus is characterized by involuntary, shock-like movements, of which cortical (CM) and non-cortical myoclonus (NCM) are most common. Electrophysiology can help differentiate between these subtypes; however, the diagnostic value of several features is largely unknown.

OBJECTIVE

This study aims to determine the diagnostic value of the burst duration in distinguishing CM and NCM.

METHODS

We manually identified the burst duration of 8 patients with CM, confirmed by electromyography-electroencephalography registration or somatosensory-evoked potentials, and 19 patients with NCM, suspected due to a myoclonus-dystonia phenotype (MYC/DYT-SGCE positive and negative).

RESULTS

The sensitivity and specificity were calculated to assess the diagnostic value. The burst duration of CM (31.1 ms) was significantly shorter than that of NCM (56.7 ms), with a sensitivity of 100% and a specificity of 89.5% at a threshold of 45.0 ms. A minimum of 10 randomly selected bursts were sufficient for reliable diagnostic accuracy.

CONCLUSION

The burst duration seems a valuable supportive diagnostic criterion for distinguishing CM and NCM.

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

Multimodal imaging and electrophysiological study in the differential diagnosis of rest tremor

Introduction

Distinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data.

Methods

We enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC). RT electrophysiological features (frequency, amplitude, and phase) were calculated using surface electromyography (sEMG). Several MRI morphometric variables (cortical thickness, surface area, cortical/subcortical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a tree-based classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET patients.

Results

Both structural MRI and sEMG data showed acceptable performance in distinguishing the two patient groups. Models based on electrophysiological data performed slightly better than those based on MRI data only (mean AUC: 0.92 and 0.87, respectively; p = 0.0071). The top-performing model used a combination of sEMG features (amplitude and phase) and MRI data (cortical volumes, surface area, and mean curvature), reaching AUC: 0.97 ± 0.03 and outperforming models using separately either MRI (p = 0.0001) or EMG data (p = 0.0231). In the best model, the most important feature was the RT phase.

Conclusion

Machine learning models combining electrophysiological and MRI data showed great potential in distinguishing between tPD and rET patients and may serve as biomarkers to support clinicians in the differential diagnosis of rest tremor syndromes in the absence of expensive and invasive diagnostic procedures such as dopamine imaging.

Surface electromyography for evaluating patients with oromandibular dystonia

OBJECTIVE

To investigate myoelectric signals of dystonic activities in oromandibular dystonia (OMD) subjects using surface electromyography (EMG).

METHODS

Twelve OMD subjects were included in this study. Resting myoelectric activities of the superficial masseter, anterior temporalis, and anterior belly of the digastric muscle on both sides were monitored, and dystonic muscle contractions were recorded using surface EMG. Myoelectric signal amplitude, the type of muscle contraction, and contraction rate for phasic activities were evaluated.

RESULTS

Surface EMG revealed that eight subjects had dystonic muscle activities in the phasic contraction pattern, three subjects had a tonic contraction pattern, and one subject had a mixed pattern. Synchronous contraction of dystonic muscles was frequently observed. Many of the monitored muscles showed high resting amplitudes.

CONCLUSION

Surface EMG detects abnormal muscle activities related to oromandibular dystonia. Surface EMG can serve as an objective method for diagnosing oromandibular dystonia.

Clinical neurophysiology of functional motor disorders: IFCN Handbook Chapter

Functional Motor Disorders are common and disabling. Clinical diagnosis has moved from one of exclusion of other causes for symptoms to one where positive clinical features on history and examination are used to make a "rule in" diagnosis wherever possible. Clinical neurophysiological assessments have developed increasing importance in assisting with this positive diagnosis, not being used simply to demonstrate normal sensory-motor pathways, but instead to demonstrate specific abnormalities that help to positively diagnose these disorders. Here we provide a practical review of these techniques, their application, interpretation and pitfalls. We also highlight particular areas where such tests are currently lacking in sensitivity and specificity, for example in people with functional dystonia and functional tic-like movements.

Electrophysiology in Functional Movement Disorders: An Update

Background

Functional movement disorders (FMD) are a diagnostic and therapeutic challenge, both to the neurologist and psychiatrists. The phenomenology is varied and can present as tremors, dystonia, jerks/myoclonus, gait disorder, other abnormal movements or a combination. There has been an increase in the use of electrophysiological studies that are an important tool in the evaluation of FMDs.

Methods

We searched the database platforms of MEDLINE, Google scholar, Web of Sciences, Scopus using the Medical Subject Heading terms (MeSH) for all the articles from 1st January 1970 till November 2022. A total of 658 articles were obtained by the search mechanism. A total of 79 relevant articles were reviewed thoroughly, of which 26 articles that had electrophysiological data were included in the present review.

Results

Variability, distractibility and entertainability can be demonstrated in functional tremors by using multichannel surface electromyography. Voluntary ballistic movements tend to decrease the tremor, while loading the tremulous limb with weight causes the tremor amplitude to increase in functional tremor. Presence of Bereitschaftspotential demonstrates the functional nature of palatal tremor and myoclonus. Co-contraction testing may be helpful in differentiating functional from organic dystonia. The R2 blink reflex recovery cycle has been found to be abnormally enhanced in organic blepharospasm, whereas it is normal in presumed functional blepharospasm. Plasticity is found to be abnormally high in organic dystonia and normal in functional dystonia, in addition to enhanced facilitation in patients with organic dystonia.

Conclusions

Electrophysiological tests supplement clinical examination and helps in differentiating FMD from organic movement disorders.

Utility of Neurophysiological Evaluation in Movement Disorders Clinical Practice

Background

Quantitative and objective neurophysiological assessment can help to define the predominant phenomenology and provide diagnoses that have prognostic and therapeutic implications for movement disorders.

Objectives

Evaluate the agreement between initial indications and final diagnoses after neurophysiological evaluations in a specialized movement disorders center.

Methods

Electrophysiological studies conducted for movement disorders from 2003 to 2021 were reviewed. The indications were classified according to predominant phenomenology and the diagnoses categorized in subgroups of phenomenology.

Results

A total of 509 studies were analyzed. 51% (259) of patients were female, with a mean age of 51 years (ranges 5 to 89 years). The most common reasons for referral were evaluation of functional movement disorders (FMD), followed by jerky movements, tremor and postural instability. Regarding FMD referrals, there was a diagnostic change in 13% of the patients after electrophysiological assessment. The patients with jerky movements as indication had a diagnosis other than myoclonus in 27% of them, and tremor was not confirmed in 20% of the cases. In patients with an electrophysiological diagnosis of FMD, it was not suspected in 30% of the referrals. Similarly, tremor was not mentioned in the referral of 17% of the patients with this electrophysiological diagnosis and myoclonus was not suspected in 13% of the cases.

Conclusions

Electrophysiological assessment has utility in the evaluation of movement disorders, even in patients evaluated by movement disorders neurologists. More studies are needed to standardize the protocols between centers and to promote the availability and use of these techniques among movement disorders clinics.

Development of a New Wearable Device for the Characterization of Hand Tremor

Rest tremor (RT) is observed in subjects with Parkinson's disease (PD) and Essential Tremor (ET). Electromyography (EMG) studies have shown that PD subjects exhibit alternating contractions of antagonistic muscles involved in tremors, while the contraction pattern of antagonistic muscles is synchronous in ET subjects. Therefore, the RT pattern can be used as a potential biomarker for differentiating PD from ET subjects. In this study, we developed a new wearable device and method for differentiating alternating from a synchronous RT pattern using inertial data. The novelty of our approach relies on the fact that the evaluation of synchronous or alternating tremor patterns using inertial sensors has never been described so far, and current approaches to evaluate the tremor patterns are based on surface EMG, which may be difficult to carry out for non-specialized operators. This new device, named "RT-Ring", is based on a six-axis inertial measurement unit and a Bluetooth Low-Energy microprocessor, and can be worn on a finger of the tremulous hand. A mobile app guides the operator through the whole acquisition process of inertial data from the hand with RT, and the prediction of tremor patterns is performed on a remote server through machine learning (ML) models. We used two decision tree-based algorithms, XGBoost and Random Forest, which were trained on features extracted from inertial data and achieved a classification accuracy of 92% and 89%, respectively, in differentiating alternating from synchronous tremor segments in the validation set. Finally, the classification response (alternating or synchronous RT pattern) is shown to the operator on the mobile app within a few seconds. This study is the first to demonstrate that different electromyographic tremor patterns have their counterparts in terms of rhythmic movement features, thus making inertial data suitable for predicting the muscular contraction pattern of tremors.

Neurophysiology of Brain Networks Underlies Symptoms of Parkinson's Disease: A Basis for Diagnosis and Management

Parkinson's disease (PD) is one of the leading neurodegenerative disorders. It is considered a movement disorder, although it is accepted that many nonmotor symptoms accompany the classic motor symptoms. PD exhibits heterogeneous and overlaying clinical symptoms, and the overlap of motor and nonmotor symptoms complicates the clinical diagnosis and management. Loss of modulation secondary to the absence of dopamine due to degeneration of the substantia nigra compacta produces changes in firing rates and patterns, oscillatory activity, and higher interneuronal synchronization in the basal ganglia-thalamus-cortex and nigrovagal network involvement in motor and nonmotor symptoms. These neurophysiological changes can be monitored by electrophysiological assessment. The purpose of this review was to summarize the results of neurophysiological changes, especially in the network oscillation in the beta-band level associated with parkinsonism, and to discuss the use of these methods to optimize the diagnosis and management of PD.

Moving Beyond Movement: Diagnosing Functional Movement Disorder

Functional movement disorder (FMD) is a complex neuropsychiatric syndrome, encompassing abnormal movements and weakness, and is a common cause of potentially disabling neurological symptoms. It is vital to recognize that FMD is a syndrome, with nonmotor manifestations negatively affecting a patient's quality of life. This review highlights a diagnostic algorithm, where a history suggestive of FMD is combined with the presence of positive signs on examination and appropriate investigations to make the diagnosis. Positive signs indicate internal inconsistency such as variability and distractibility, and clinical findings that are incongruent with other known neurological disease. Importantly, the clinical assessment acts as the first opportunity to allow patients to understand FMD as the cause for their symptoms. Accurate and early diagnosis of FMD is necessary given that it is a treatable and potentially reversible cause of disability, with significant risk of iatrogenic harm associated with misdiagnosis.

Myoclonus and other jerky movement disorders

Myoclonus and other jerky movements form a large heterogeneous group of disorders. Clinical neurophysiology studies can have an important contribution to support diagnosis but also to gain insight in the pathophysiology of different kind of jerks. This review focuses on myoclonus, tics, startle disorders, restless legs syndrome, and periodic leg movements during sleep. Myoclonus is defined as brief, shock-like movements, and subtypes can be classified based the anatomical origin. Both the clinical phenotype and the neurophysiological tests support this classification: cortical, cortical-subcortical, subcortical/non-segmental, segmental, peripheral, and functional jerks. The most important techniques used are polymyography and the combination of electromyography-electroencephalography focused on jerk-locked back-averaging, cortico-muscular coherence, and the Bereitschaftspotential. Clinically, the differential diagnosis of myoclonus includes tics, and this diagnosis is mainly based on the history with premonitory urges and the ability to suppress the tic. Electrophysiological tests are mainly applied in a research setting and include the Bereitschaftspotential, local field potentials, transcranial magnetic stimulation, and pre-pulse inhibition. Jerks due to a startling stimulus form the group of startle syndromes. This group includes disorders with an exaggerated startle reflex, such as hyperekplexia and stiff person syndrome, but also neuropsychiatric and stimulus-induced disorders. For these disorders polymyography combined with a startling stimulus can be useful to determine the pattern of muscle activation and thus the diagnosis. Assessment of symptoms in restless legs syndrome and periodic leg movements during sleep can be performed with different validated scoring criteria with the help of electromyography.

Speech-induced action myoclonus

BACKGROUND

Speech-induced action myoclonus may occur as a component of a generalized myoclonus syndrome. However, it may also present in isolation, or with a paucity of other findings, and be diagnostically challenging.

OBJECTIVES

To report a retrospective case series of restricted speech-induced action myoclonus.

METHODS

We reviewed cases of speech-induced action myoclonus evaluated at Mayo Clinic Rochester from 1989 to 2020. We eliminated cases where a more generalized myoclonic disorder was also present. Clinical, imaging, and electrophysiologic data were extracted.

RESULTS

Four cases were identified in which speech-induced action myoclonus of craniofacial muscles was the predominant clinical presentation. All described cranial muscle twitching induced by speaking, and two cases also reported speech interruptions. Diagnosis was confirmed by expert speech pathologists in all cases. Diagnostic aids included modulation with different speech tasks and speaking rates, and surface electrophysiology which confirmed craniofacial myoclonus induced by speaking tasks (three cases). Previous misdiagnosis included functional, dystonic, neuromuscular junction pathology, or hemifacial spasm. Two cases had isolated speech-induced myoclonus, and the other two had coexistent upper limb tremor. Potential etiologic factors were identified in three cases - medication (2), epilepsy (1) - while in one patient no cause was identified. One patient partially improved with anti-myoclonic medication and speech therapy.

CONCLUSIONS

Speech-induced action myoclonus may occur in isolation and is frequently misdiagnosed. Diagnostic aids include modulation with different speech tasks and speaking rates, and surface electrophysiology.

Evaluation of movement and brain activity

Clinical neurophysiology studies can contribute important information about the physiology of human movement and the pathophysiology and diagnosis of different movement disorders. Some techniques can be accomplished in a routine clinical neurophysiology laboratory and others require some special equipment. This review, initiating a series of articles on this topic, focuses on the methods and techniques. The methods reviewed include EMG, EEG, MEG, evoked potentials, coherence, accelerometry, posturography (balance), gait, and sleep studies. Functional MRI (fMRI) is also reviewed as a physiological method that can be used independently or together with other methods. A few applications to patients with movement disorders are discussed as examples, but the detailed applications will be the subject of other articles.

Wearable monitoring of positive and negative myoclonus in progressive myoclonic epilepsy type 1

OBJECTIVE

To develop and test wearable monitoring of surface electromyography and motion for detection and quantification of positive and negative myoclonus in patients with progressive myoclonic epilepsy type 1 (EPM1).

METHODS

Surface electromyography and three-dimensional acceleration were measured from 23 EPM1 patients from the biceps brachii (BB) of the dominant and the extensor digitorum communis (EDC) of the non-dominant arm for 48 hours. The patients self-reported the degree of myoclonus in a diary once an hour. Severity of myoclonus with action was evaluated by using video-recorded Unified Myoclonus Rating Scale (UMRS). Correlations of monitored parameters were quantified with the UMRS scores and the self-reported degrees of myoclonus.

RESULTS

The monitoring-based myoclonus index correlated significantly (p < 0.001) with the UMRS scores (ρ = 0.883 for BB and ρ = 0.823 for EDC) and with the self-reported myoclonus degrees (ρ = 0.483 for BB and ρ = 0.443 for EDC). Ten patients were assessed as probably having negative myoclonus in UMRS, while our algorithm detected that in twelve patients.

CONCLUSIONS

Wearable monitoring was able to detect both positive and negative myoclonus in EPM1 patients.

SIGNIFICANCE

Our method is suitable for quantifying objective, real-life treatment effects at home and progression of myoclonus.

The diagnostic value of clinical neurophysiology in hyperkinetic movement disorders: A systematic review

INTRODUCTION

To guide the neurologist and neurophysiologist with interpretation and implementation of clinical neurophysiological examinations, we aim to provide a systematic review on evidence of electrophysiological features used to differentiate between hyperkinetic movement disorders.

METHODS

A PRISMA systematic search and QUADAS quality evaluation has been performed in PubMed to identify diagnostic test accuracy studies comparing electromyography and accelerometer features. We included papers focusing on tremor, dystonia, myoclonus, chorea, tics and ataxia and their functional variant. The features were grouped as 1) basic features (e.g., amplitude, frequency), 2) the influence of tasks on basic features (e.g., entrainment, distraction), 3) advanced analyses of multiple signals, 4) and diagnostic tools combining features.

RESULTS

Thirty-eight cross-sectional articles were included discussing tremor (n = 28), myoclonus (n = 5), dystonia (n = 5) and tics (n = 1). Fifteen were rated as 'high quality'. In tremor, the basic and task-related features showed great overlap between clinical tremor syndromes, apart from rubral and enhanced physiological tremor. Advanced signal analyses were best suited for essential, parkinsonian and functional tremor, and cortical, non-cortical and functional jerks. Combinations of electrodiagnostic features could identify essential, enhanced physiological and functional tremor.

CONCLUSION

Studies into the diagnostic accuracy of electrophysiological examinations to differentiate between hyperkinetic movement disorders have predominantly been focused on clinical tremor syndromes. No single feature can differentiate between them all; however, a combination of analyses might improve diagnostic accuracy.

Tremor Syndromes: An Updated Review

Tremor is the most commonly encountered movement disorder in clinical practice. A wide range of pathologies may manifest with tremor either as a presenting or predominant symptom. Considering the marked etiological and phenomenological heterogeneity, it would be desirable to develop a classification of tremors that reflects their underlying pathophysiology. The tremor task force of the International Parkinson Disease and Movement Disorders Society has worked toward this goal and proposed a new classification system. This system has remained a prime topic of scientific communications on tremor in recent times. The new classification is based on two axes: 1. based on the clinical features, history, and tremor characteristics and 2. based on the etiology of tremor. In this article, we discuss the key aspects of the new classification, review various tremor syndromes, highlight some of the controversies in the field of tremor, and share the potential future perspectives.

Factors Influencing the Surgical Decision in Dystonia Patients Referred for Deep Brain Stimulation

There is no available data on the journey of dystonia patients once referred to a tertiary center to undergo deep brain stimulation (DBS). We hypothesized that some patients might be incorrectly diagnosed while others might decline the procedure or experience significant benefit with switching to a different botulinum neurotoxin (BoNT). This is a single-center, retrospective study of dystonia patients who were referred to the DBS program between January 2014 and December 2018. We collected data on the surgical decision as well as factors influencing this decision. Sixty-seven patients were included (30 males, mean age: 48.3 ± 20.1 years, disease duration: 16.9 ± 15.3 years). Thirty-three (49%) patients underwent DBS. Four (6%) patients were awaiting the procedure while the remaining 30 patients (45%) did not undergo DBS. Reasons for DBS decline were patient refusal (17, 53%), functional dystonia (6, 20%), and successful use of AbobotulinumtoxinA (3, 10%) in patients who had failed other BoNTs. Our study highlights the importance of structured patient education to increase acceptance of DBS, as well as careful patient evaluation, particularly with respect to functional dystonia. Finally, changing BoNT formulation might be beneficial in some patients.

Suggestibility as a valuable criterion for laboratory-supported definite functional movement disorders

OBJECTIVE

To evaluate the application of suggestibility in electrophysiologic studies as a tool to increase the diagnostic certainty of "laboratory-supported definite" FMD.

METHODS

We retrospectively reviewed the electrophysiologic studies performed in our center on patients with FMD. Recordings where suggestibility was included in the test battery were then selected.

RESULTS

We present three cases with equivocal clinical features, but with findings on electrophysiologic studies that were consistent with "laboratory-supported definite" FMD.

CONCLUSION

When combined with other tests, demonstration of suggestibility in electrophysiologic studies may increase the accuracy in differentiating functional from organic movement disorders.

SIGNIFICANCE

This case series is an essential first step in evaluating the applicability of suggestibility as an electrophysiologic criterion to aid in the diagnosis of FMD. Application in a larger cohort, incorporation in a test battery, and validation studies, including quantitative evaluation of suggestibility, are required to assess the reliability and the added value of this test.

Contemporary clinical neurophysiology applications in dystonia

The complex phenomenological understanding of dystonia has transcended from the clinics to genetics, imaging and neurophysiology. One way in which electrophysiology will impact into the clinics are cases wherein a dystonic clinical presentation may not be typical or a "forme fruste" of the disorder. Indeed, the physiological imprints of dystonia are present regardless of its clinical manifestation. Underpinnings in the understanding of dystonia span from the peripheral, segmental and suprasegmental levels to the cortex, and various electrophysiological tests have been applied in the course of time to elucidate the origin of dystonia pathophysiology. While loss of inhibition remains to be the key finding in this regard, intricacies and variabilities exist, thus leading to a notion that perhaps dystonia should best be gleaned as network disorder. Interestingly, the complex process has now spanned towards the understanding in terms of networks related to the cerebellar circuitry and the neuroplasticity. What is evolving towards a better and cohesive view will be neurophysiology attributes combined with structural dynamic imaging. Such a sound approach will significantly lead to better therapeutic modalities in the future.

Minimum Electromyographic Burst Duration in Healthy Controls: Implications for Electrodiagnosis in Movement Disorders

Background

Electromyogram (EMG) burst duration can provide additional diagnostic information when investigating hyperkinetic movement disorders, particularly when a functional movement disorder is suspected. It is generally accepted that EMG bursts <50 milliseconds are pathological.

Objective

To reassess minimum physiological EMG burst duration.

Methods

Surface EMG was recorded from face, trunk, and limb muscles in controls (n = 60; ages 19–85). Participants were instructed to generate the briefest possible ballistic movements involving each muscle (40 repetitions) or, in muscles spanning joints, to generate rapid rhythmic alternating movements (20–30 seconds), or both.

Results

We found no effect of age on EMG burst duration. However, EMG burst duration varied significantly between body regions. Rhythmic EMG bursts were shorter than ballistic bursts but only significantly so for lower limbs (P < 0.001). EMG bursts of duration <50 milliseconds were frequently observed, particularly in appendicular muscles.

Conclusion

We present normal reference data for minimum EMG burst duration, which may assist clinical interpretation when investigating hyperkinetic movement disorders.

Physiology-Based Treatment of Myoclonus

Myoclonus can cause significant disability for patients. Myoclonus has a strikingly diverse array of underlying etiologies, clinical presentations, and pathophysiological mechanisms. Treatment of myoclonus is vital to improving the quality of life of patients with these disorders. The optimal treatment strategy for myoclonus is best determined based upon careful evaluation and consideration of the underlying etiology and neurophysiological classification. Electrophysiological testing including EEG (electroencephalogram) and EMG (electromyogram) data is helpful in determining the neurophysiological classification of myoclonus. The neurophysiological subtypes of myoclonus include cortical, cortical-subcortical, subcortical-nonsegmental, segmental, and peripheral. Levetiracetam, valproic acid, and clonazepam are often used to treat cortical myoclonus. In cortical-subcortical myoclonus, treatment of myoclonic seizures is prioritized, valproic acid being the mainstay of therapy. Subcortical-nonsegmental myoclonus may be treated with clonazepam, though numerous agents have been used depending on the etiology. Segmental and peripheral myoclonus are often resistant to treatment, but anticonvulsants and botulinum toxin injections may be of utility depending upon the case. Pharmacological treatments are often hampered by scarce evidence-based knowledge, adverse effects, and variable efficacy of medications.