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BACKGROUND: Essential tremor is a common movement disorder, characterized by 4–12 Hz tremor of the hands and arms that can affect many activities of daily living. It has been reported by patients that when performing tasks bimanually their tremor is reduced, but why this happens is unknown. OBJECTIVES: We measured patients' tremors in different conditions when performed with 1 hand and 2 hands to observe if bimanual task performance changes the characteristics of the tremor. METHODS: A total of 10 patients with essential tremor participated in the study. Electromyographic electrodes were attached bilaterally to the wrist flexor and extensor muscles, and accelerometers were attached to the dorsum of the hands. For each condition, holding a cup, wingbeat, and extending both arms up, data were collected with a single hand and bimanually with the hands touching. RESULTS: When the hands were touching, there was a significant decrease in both accelerometric and electromyographic power at the tremor frequency. In addition, there was a decrease in coherence between accelerometer and electromyography on the same side. There was no change in the tremor frequency. CONCLUSIONS: Tremor amplitude does decrease when the hands are together. Together, the characteristics underlying the decrease in tremor amplitude may indicate a decrease in power of the central oscillator driving the tremor, which we speculate is attributed to the differences in unimanual and bimanual motor control. However, given the small sample size, we note that future hypothesis‐driven studies with an a priori power analysis will be required to further explore this phenomenon.

Background Assessment of essential tremor is often done by a trained clinician who observes the limbs during different postures and actions and subsequently rates the tremor. While this method has been shown to be reliable, the inter- and intra-rater reliability and need for training can make the use of this method for symptom progression difficult. Many limitations of clinical rating scales can potentially be overcome by using inertial sensors, but to date many algorithms designed to quantify tremor have key limitations. Methods We propose a novel algorithm to characterize tremor using inertial sensors. It uses a two-stage approach that 1) estimates the tremor frequency of a subject and only quantifies tremor near that range; 2) estimates the tremor amplitude as the portion of signal power above baseline activity during recording, allowing tremor estimation even in the presence of other activity; and 3) estimates tremor amplitude in physical units of translation (cm) and rotation (°), consistent with current tremor rating scales. We validated the algorithm technically using a robotic arm and clinically by comparing algorithm output with data reported by a trained clinician administering a tremor rating scale to a cohort of essential tremor patients. Results Technical validation demonstrated rotational amplitude accuracy better than ±0.2 degrees and position amplitude accuracy better than ±0.1 cm. Clinical validation revealed that both rotation and position components were significantly correlated with tremor rating scale scores. Conclusion We demonstrate that our algorithm can quantify tremor accurately even in the presence of other activities, perhaps providing a step forward for at-home monitoring.

Highlights • The electrophysiological characterization of tremor is a useful technique. • There has not been much software available for tremor analysis. • We developed a free online platform for tremor analysis., Objective The electrophysiological classification of tremors can be a key element in the diagnosis and can facilitate treatment of a patient with tremor; however, the ability to conduct electrophysiological studies of tremor is not widely available. The purpose of this study was to develop and validate a free online platform for tremor analysis. Methods An online platform for tremor analysis was developed using “R” language; called “Tremoroton”. For validation, we compared the frequency estimation of the tremor obtained with Tremoroton compared with a commercially available software in a cohort of 20 patients (10 with essential tremor and 10 with Parkinson diagnosis), comparing the activity recorded on the accelerometer, extensor carpi radialis and flexor carpi radialis EMG. An intraclass correlation coefficient was used for the comparison. Results The final version of tremoroton is now online. It allows reading up to 6 channels, and will do time, frequency, time-frequency analysis and calculate coherence. We demonstrated a high correlation in frequency measurements (0.97 (0.945–0.984, 95% IC) for the accelerometers, 0.98 (0.977–0.994, 95% IC) for the extensor carpi radialis EMG, and 0.99 (0.987–0.997, 95% IC) for the flexor carpi radialis EMG) when compared to a commercial software. Conclusion We were able to develop and validate a free online platform for tremor analysis. Significance Making this tool available should help expanding tremor analysis techniques from research to the clinical setting.

To investigate the neuronal elements involved in the activation of corticospinal neurons in the primary motor cortex (M1).We studied 10 healthy subjects. Cortical evoked potentials with different components induced by monophasic transcranial magnetic stimulation (TMS) in anterior-posterior and posterior-anterior currents recorded with electroencephalography (EEG) were analyzed.EEG signatures with P25 and N45 components recorded at the C3 electrode with posterior-anterior current were larger than those with anterior-posterior current, while the signatures with P180 and N280 components recorded at the FC1 electrode with anterior-posterior current were larger than those with posterior-anterior current. The source localization analysis revealed that the cortical evoked potential with anterior-posterior current distributed both in the M1 and premotor cortex while that with posterior-anterior current only located in the M1.We conclude that the activation of corticospinal pyramidal neurons in the M1 is affected by various neuronal elements including the local intracortical circuits in the M1 and inputs from premotor cortex with different sensitivities to TMS in opposite current directions.Our finding helped answer a longstanding question about how the corticospinal pathway from the M1 is functionally organized and activated.

Background: Here we combine clinical, electrophysiological, and genetic findings to phenotype an unusual childhood movement disorder in a patient with a rare form of KCNN2 mutation. Case Report: A 10-year-old male presented with a clinical syndrome of tremor and myoclonus. Electrophysiology demonstrated muscle activity indicative of myoclonus dystonia, an observation that was not appreciated clinically. Genetic testing revealed an abnormality in the KCNN 2 gene, not present in the parents, known to cause dystonia, as the etiology. Discussion: The value of utilizing noninvasive, electrophysiological recording in pediatric movement disorders expands the precision of diagnosis, potentially informing treatment when correlated with clinical and genetic findings.

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In the above article [1] , the following disclosures should have appeared. Dietrich Haubenberger is now employed by Neurocrine Biosciences, Inc., San Diego, CA 92130, USA. James McNames is an employee of APDM, Portland, OR 97201, USA, a company that may have a commercial interest in the results of this research and technology. This potential conflict of interest has been reviewed and managed by OHSU.

Spinocerebellar Ataxia type 7 (SCA7) is a neurodegenerative disease characterized by progressive cerebellar ataxia and retinal degeneration. Increasing loss of visual function complicates the use of clinical scales to track the progression of motor symptoms, hampering our ability to develop accurate biomarkers of disease progression, and thus test the efficacy of potential treatments. In this cross-sectional study, we aimed to identify imaging measures of neurodegeneration, which may more accurately reflect SCA7 severity and progression. We analyzed diffusion tensor imaging (DTI) data collected from a cohort of 13 SCA7 patients and 14 healthy volunteers using two recent methodological advances: 1) a diffusion tensor-based image registration technique, and 2) a dual-compartment DTI model to control for the potential increase in extracellular CSF-like water due to neurodegeneration. These methodologies allowed us to assess both volumetric and microstructural abnormalities in both white and gray matter brain-wide in SCA7 patients for the first time. To measure tissue volume, we performed diffusion tensor-based morphometry (DTBM) using the tensor-based registration. To assess tissue microstructure, we computed the parenchymal mean diffusivity (pMD) and parenchymal fractional anisotropy (pFA) using the dual compartment model. This model also enabled us to estimate the parenchymal volume fraction (pVF), a measure of parenchymal tissue volume within a given voxel. While DTBM and pVF revealed tissue loss primarily in the brainstem, cerebellum, thalamus, and a subset of cerebral white matter tracts in patients, pMD and pFA detected microstructural abnormalities brain-wide (p < 0.05, FWE corrected; Hedge’s g > 1). This distinction was meaningful in terms of motor symptom severity, as we found that patient scores on the Scale for the Assessment and Rating of Ataxia correlated most strongly with cerebellar pVF (r = - 0.66, p = 0.015) and global white matter pFA (r = −0.64, p = 0.018). Since this contrast between focal tissue loss and global microstructural abnormality has previously been described in neuropathology, we believe the approach employed here is well suited for the in-vivo assessment of neurodegeneration. Moving forward, this approach could be applied to characterize the full spatiotemporal pattern of neurodegeneration in SCA7, and potentially develop an accurate imaging biomarker of disease progression.HighlightsDTI study reveals brain-wide differences between SCA7 patients and controls.DTI dual-compartment model controls for increased CSF-like free water in patients.Tensor-based deformations show SCA7 tissue loss extends beyond cerebellum.Focal atrophy, but global microstructural abnormalities were observed in SCA7.Ataxia most correlated with cerebellar atrophy, global microstructural abnormality.

Highlights • DTI study reveals brain-wide differences between SCA7 patients and controls. • DTI dual-compartment model controls for increased CSF-like free water in patients. • Tensor-based deformations show SCA7 tissue loss extends beyond cerebellum. • Focal atrophy, but global microstructural abnormalities were observed in SCA7., Spinocerebellar Ataxia type 7 (SCA7) is a neurodegenerative disease characterized by progressive cerebellar ataxia and retinal degeneration. Increasing loss of visual function complicates the use of clinical scales to track the progression of motor symptoms, hampering our ability to develop accurate biomarkers of disease progression, and thus test the efficacy of potential treatments. We aimed to identify imaging measures of neurodegeneration, which may more accurately reflect SCA7 severity and progression. While common structural MRI techniques have been previously used for this purpose, they can be biased by neurodegeneration-driven increases in extracellular CSF-like water. In a cross-sectional study, we analyzed diffusion tensor imaging (DTI) data collected from a cohort of 13 SCA7 patients and 14 healthy volunteers using: 1) a diffusion tensor-based image registration technique, and 2) a dual-compartment DTI model to control for the potential increase in extracellular CSF-like water. These methodologies allowed us to assess both volumetric and microstructural abnormalities in both white and gray matter brain-wide in SCA7 patients for the first time. To measure tissue volume, we performed diffusion tensor-based morphometry (DTBM) using the tensor-based registration. To assess tissue microstructure, we computed the parenchymal mean diffusivity (pMD) and parenchymal fractional anisotropy (pFA) using the dual compartment model. This model also enabled us to estimate the parenchymal volume fraction (pVF), a measure of parenchymal tissue volume within a given voxel. While DTBM and pVF revealed tissue loss primarily in the brainstem, cerebellum, thalamus, and major motor white matter tracts in patients (p 1), pMD and pFA detected microstructural abnormalities in virtually all tissues brain-wide (p 1). The Scale for the Assessment and Rating of Ataxia trended towards correlation with cerebellar pVF (r = −0.66, p = 0.104, FDR corrected) and global white matter pFA (r = −0.64, p = 0.104, FDR corrected). These results advance our understanding of neurodegeneration in living SCA7 patients by providing the first voxel-wise characterization of white matter volume loss and gray matter microstructural abnormalities. Moving forward, this comprehensive approach could be applied to characterize the full spatiotemporal pattern of neurodegeneration in SCA7, and potentially develop an accurate imaging biomarker of disease progression.

Colton Smith’s 2017 essay provides an informative history of transcranial direct current stimulation (tDCS) and its use in research and clinical settings. More importantly, he also discusses a grow...

Highlights • Back-averaging is a useful technique to correlate the activity of the motor cortex with a muscle jerk. • Back-averaging is a tool for the diagnosis of conditions such as functional movement disorders and cortical myoclonus. • BacAv, a new online platform, can be used for back-average analysis., Objective The back-average technique is very useful to study the relation between the activity in the cortex and the muscles. It has two main clinical applications, Bereitschaftspotential (BP) recording and myoclonus studies. The BP is a slow wave negativity originating in the supplementary motor cortex and premotor cortex that precedes voluntary movements. This wave also precedes involuntary movements in functional movement disorders (FMD), and it can be used as a helpful diagnostic tool. For the myoclonus studies, the back-average technique is very important to help localizing the source of the myoclonus. The hardware needed to do BP or myoclonus studies is standard and available in any electrophysiology lab, but there are not many software solutions to do the analysis. In this article together with describing the methodology that we use for recording clinical BPs and myoclonus, we present BacAv, an online free application that we developed for the purpose of doing back-average analysis. Methods BacAv was developed in “R” language using Rstudio, a free integrated development environment. The recommended parameters for the data acquisition for BP recording and myoclonus studies are given in this section. Results The platform was successfully developed, is able to read txt files, look for muscle bursts, segment the data, and plot the average. The parameters of the algorithm that look for the muscle bursts can be adapted according to the characteristics of the dataset. Conclusion We have developed software for clinicians who do not have sophisticated equipment to do back-averaging. Significance This tool will make this useful analysis method more available in a clinical environment.

Background: There is little published work describing the electrophysiological characteristics of essential palatal tremor, a condition now believed by many to be a functional (psychogenic) movement disorder. Case Report: Here we combine electroencephalography and electromyography with time-locked video recordings to document two cases of essential palatal tremor in which a definitive diagnosis is achieved using these electrophysiological tools. Discussion: We believe that sharing how these objective tools can be used to diagnose a functional movement disorder, as well as providing more published evidence to support the functional origin of essential palatal myoclonus, will help to diagnose this condition in the future.

BACKGROUND: Whilst a growing body of research has examined dissociation and other psychiatric symptoms in severe dissociative disorders (DDs), there has been no systematic examination of shame and sense of self in relationships in DDs. Chronic child abuse often associated with severe DDs, like dissociative identity disorder, is likely to heighten shame and relationship concerns. This study investigated complex posttraumatic stress disorder (PTSD), borderline and Schneiderian symptoms, dissociation, shame, child abuse, and various markers of self in relationships (e.g., relationship esteem, relationship depression, fear of relationships). METHODS: Participants were assessed via clinical interview with psychometrically sound questionnaires. They fell into three diagnostic groups, dissociative disorder (n=39; primarily dissociative identity disorder), chronic PTSD (Chr-PTSD; n=13) or mixed psychiatric presentations (MP; n=21; primarily mood and anxiety disorders). All participants had a history of child abuse and/or neglect, and the groups did not differ on age and gender. RESULTS: The DD group was higher on nearly all measured variables than the MP group, and had more severe dissociative, borderline and Schneiderian symptoms than the Chr-PTSD sample. Shame and complex PTSD symptoms fell marginally short of predicting reductions in relationship esteem, pathological dissociative symptoms predicted increased relationship depression, and complex PTSD symptoms predicted fear of relationships. LIMITATIONS: The representativeness of the samples was unknown. CONCLUSION: Severe psychiatric symptoms differentiate DDs from chronic PTSD, while dissociation and shame have a meaningful impact on specific markers of relationship functioning in psychiatric patients with a history of child abuse and neglect. Language: en

Background Theories of addiction suggest that chronic smoking may be associated with both hypersensitivity to smoking and related cues and hyposensitivity to alternative reinforcers. However, neural responses to smoking and nonsmoking rewards are rarely evaluated within the same paradigm, leaving the extent to which both processes operate simultaneously uncertain. Behavioral evidence and theoretical models suggest that dysregulated reward processing may be more pronounced during deprivation from nicotine, but neuroimaging evidence on the effects of deprivation on reward processing is limited. The current study examined the impact of deprivation from smoking on neural processing of both smoking and monetary rewards. Methods Two separate functional magnetic resonance imaging scans were performed in 38 daily smokers, one after smoking without restriction and one following 24 hours of abstinence. A rewarded guessing task was conducted during each scan to evaluate striatal blood oxygen level–dependent response during anticipation of both smoking and monetary rewards. Results A significant reward type by abstinence interaction was observed in the bilateral caudate and medial prefrontal cortex during reward anticipation. The blood oxygen level–dependent response to anticipation of smoking reward was significantly higher and anticipation of monetary rewards was significantly lower during abstinence compared with nonabstinence. Attenuation of monetary reward–related activation during abstinence was significantly correlated with abstinence-induced increases in craving and withdrawal. Conclusions These results provide the first direct evidence of dissociated effects of smoking versus monetary rewards as a function of abstinence. The findings suggest an important neural pathway that may underlie the choice to smoke in lieu of alternative reinforcement during a quit attempt.

Control of digit forces for grasping relies on sensorimotor memory gained from prior experience with the same or similar objects and on online sensory feedback. However, little is known about neural mechanisms underlying digit force planning. We addressed this question by quantifying the temporal evolution of corticospinal excitability (CSE) using single-pulse transcranial magnetic stimulation (TMS) during two reach-to-grasp tasks. These tasks differed in terms of the magnitude of force exerted on the same points on the object to isolate digit force planning from reach and grasp planning. We also addressed the role of intracortical circuitry within primary motor cortex (M1) by quantifying the balance between short intracortical inhibition and facilitation using paired-pulse TMS on the same tasks. Eighteen right-handed subjects were visually cued to plan digit placement at predetermined locations on the object and subsequently to exert either negligible force (“low-force” task, LF) or 10% of their maximum pinch force (“high-force” task, HF) on the object. We found that the HF task elicited significantly smaller CSE than the LF task, but only when the TMS pulse coincided with the signal to initiate the reach. This force planning-related CSE modulation was specific to the muscles involved in the performance of both tasks. Interestingly, digit force planning did not result in modulation of M1 intracortical inhibitory and facilitatory circuitry. Our findings suggest that planning of digit forces reflected by CSE modulation starts well before object contact and appears to be driven by inputs from frontoparietal areas other than M1.