Graph theory analysis of resting-state functional magnetic resonance imaging in essential tremor.

Essential tremor (ET) is a neurological disease with both motor and non-motor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting-state functional MRI data, in 23 ET patients vs. 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small-world values than healthy controls - less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo-occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus. In addition, ET patients showed significant higher local efficiency and clustering coefficient values in the frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.pre-print1168 K

Optimal Control of Underactuated Mechanical Systems: A Geometric Approach

In this paper, we consider a geometric formalism for optimal control of underactuated mechanical systems. Our techniques are an adaptation of the classical Skinner and Rusk approach for the case of Lagrangian dynamics with higher-order constraints. We study a regular case where it is possible to establish a symplectic framework and, as a consequence, to obtain a unique vector field determining the dynamics of the optimal control problem. These developments will allow us to develop a new class of geometric integrators based on discrete variational calculus.Comment: 20 pages, 2 figure

The phase difference between neural drives to antagonist muscles in essential tremor is associated with the relative strength of supraspinal and afferent input

The pathophysiology of essential tremor (ET), the most common movement disorder, is not fully understood. We investigated which factors determine the variability in the phase difference between neural drives to antagonist muscles, a long-standing observation yet unexplained. We used a computational model to simulate the effects of different levels of voluntary and tremulous synaptic input to antagonistic motoneuron pools on the tremor. We compared these simulations to data from 11 human ET patients. In both analyses, the neural drive to muscle was represented as the pooled spike trains of several motor units, which provides an accurate representation of the common synaptic input to motoneurons. The simulations showed that, for each voluntary input level, the phase difference between neural drives to antagonist muscles is determined by the relative strength of the supraspinal tremor input to the motoneuron pools. In addition, when the supraspinal tremor input to one muscle was weak or absent, Ia afferents provided significant common tremor input due to passive stretch. The simulations predicted that without a voluntary drive (rest tremor) the neural drives would be more likely in phase, while a concurrent voluntary input (postural tremor) would lead more frequently to an out-of-phase pattern. The experimental results matched these predictions, showing a significant change in phase difference between postural and rest tremor. They also indicated that the common tremor input is always shared by the antagonistic motoneuron pools, in agreement with the simulations. Our results highlight that the interplay between supraspinal input and spinal afferents is relevant for tremor generation

A data mining approach using cortical thickness for diagnosis and characterization of essential tremor.

Essential tremor (ET) is one of the most prevalent movement disorders. Being that it is a common disorder, its diagnosis is considered routine. However, misdiagnoses may occur regularly. Over the past decade, several studies have identified brain morphometric changes in ET, but these changes remain poorly understood. Here, we tested the informativeness of measuring cortical thickness for the purposes of ET diagnosis, applying feature selection and machine learning methods to a study sample of 18 patients with ET and 18 age- and sex-matched healthy control subjects. We found that cortical thickness features alone distinguished the two, ET from controls, with 81% diagnostic accuracy. More specifically, roughness (i.e., the standard deviation of cortical thickness) of the right inferior parietal and right fusiform areas was shown to play a key role in ET characterization. Moreover, these features allowed us to identify subgroups of ET patients as well as healthy subjects at risk for ET. Since treatment of tremors is disease specific, accurate and early diagnosis plays an important role in tremor management. Supporting the clinical diagnosis with novel computer approaches based on the objective evaluation of neuroimage data, like the one presented here, may represent a significant step in this direction.post-print1720 K

A data mining approach for classification of orthostatic and essential tremor based on MRI‐derived brain volume and cortical thickness

[Abstract] Objective - Orthostatic tremor (OT) is an extremely rare, misdiagnosed, and underdiagnosed disorder affecting adults in midlife. There is debate as to whether it is a different condition or a variant of essential tremor (ET), or even, if both conditions coexist. Our objective was to use data mining classification methods, using magnetic resonance imaging (MRI)‐derived brain volume and cortical thickness data, to identify morphometric measures that help to discriminate OT patients from those with ET. Methods - MRI‐derived brain volume and cortical thickness were obtained from 14 OT patients and 15 age‐, sex‐, and education‐matched ET patients. Feature selection and machine learning methods were subsequently applied. Results - Four MRI features alone distinguished the two, OT from ET, with 100% diagnostic accuracy. More specifically, left thalamus proper volume (normalized by the total intracranial volume), right superior parietal volume, right superior parietal thickness, and right inferior parietal roughness (i.e., the standard deviation of cortical thickness) were shown to play a key role in OT and ET characterization. Finally, the left caudal anterior cingulate thickness and the left caudal middle frontal roughness allowed us to separate with 100% diagnostic accuracy subgroups of OT patients (primary and those with mild parkinsonian signs). Conclusions - A data mining approach applied to MRI‐derived brain volume and cortical thickness data may differentiate between these two types of tremor with an accuracy of 100%. Our results suggest that OT and ET are distinct conditions.National Institutes of Health (United States); #R01, NS39422National Institutes of Health (United States), #R01, NS094607National Institutes of Health (United States); #R01, NS085136National Institutes of Health (United States); #R01, NS073872National Institutes of Health (United States); #R01, NS085136National Institutes of Health (United States); #R01, NS088257European Commission; ICT‐2011‐287739Ministerio de Economía y Competitividad; RTC‐2015‐3967‐1Agencia Española de Investigación de la Salud; FIS PI12/01602Agencia Española de Investigación de la Salud; FIS PI16/00451Madrid Robotics Digital Innovation Hub; S2018/NMT‐433

Association between Parkinson's disease and diabetes: Data from NEDICES study

Background: Despite growing evidence showing an association between Parkinson's disease (PD) and diabetes, epidemiological studies have shown conflicting results. Aims of the study: To evaluate the association between PD and diabetes and the impact of diabetes duration in this association in an elderly (≥65 years) Spanish population. Methods: Data for this cross-sectional population-based analysis were obtained from NEDICES study. Subjects were identified from census list. Diagnosis of PD was confirmed by neurological examination. Diabetes was defined by self-report, being on antidiabetic medication or diagnosis on medical records. Logistic regression analysis adjusted by potential confounders was performed to estimate the association between both conditions and also after dividing patients into short-duration (<10 years) and long-duration (≥10 years) diabetes. Results: A total of 4998 subjects were included (79 PD and 4919 controls). Univariate analysis did not show any association between prevalence of PD and diabetes (OR 1.89, 95% CI 0.90-3.98, P=.09), although subgroup analysis showed a positive association in those with long-duration diabetes (3.27, 95% CI 1.21-8.85, P=.02). Conclusions: Diabetes duration might be an important factor in the association between PD and diabetes, and the risk might be limited to those with longer disease duration

Unambiguous Formalism for Higher-Order Lagrangian Field Theories

The aim of this paper is to propose an unambiguous intrinsic formalism for higher-order field theories which avoids the arbitrariness in the generalization of the conventional description of field theories, which implies the existence of different Cartan forms and Legendre transformations. We propose a differential-geometric setting for the dynamics of a higher-order field theory, based on the Skinner and Rusk formalism for mechanics. This approach incorporates aspects of both, the Lagrangian and the Hamiltonian description, since the field equations are formulated using the Lagrangian on a higher-order jet bundle and the canonical multisymplectic form on its dual. As both of these objects are uniquely defined, the Skinner-Rusk approach has the advantage that it does not suffer from the arbitrariness in conventional descriptions. The result is that we obtain a unique and global intrinsic version of the Euler-Lagrange equations for higher-order field theories. Several examples illustrate our construction.Comment: 21 pages; 4 diagrams; (this version) corrected typos; moved paragraphs; publishe

High Levels of Proinflammatory Cytokines, but Not Markers of Tissue Injury, in Unaffected Intestinal Areas from Patients with IBD

Intestinal alterations in IBD are triggered and maintained by an overexpression of proinflammatory cytokines. Additionally, increased immune activation has been found in the adjacent intestinal areas without displaying any apparent histological alterations, however, the regulatory environment is not well established. Biopsy specimens from patients with ulcerative colitis (UC) and Crohn's disease (CD), from both affected and unaffected areas, and also from a group of colonic biopsies from healthy controls, were included in our study. Cytokines and markers of mucosal damage were analyzed by real-time PCR, and some of the results confirmed by western-blot and ELISA. Levels of IFNγ, TNFα, IL-6, IL-15, IL-18, and IL-23 were increased (above healthy controls) in both affected and unaffected areas from IBD. IL-1β, IL-6, IL-12, and IL-27 were higher in affected areas compared to unaffected ones in UC but not CD. In general, a correlation was observed between mRNA levels of these cytokines and both iNOS and Granzyme B. SOCS-2 and SOCS-3 were also increased in the affected areas. In conclusion, the unaffected areas from IBD show increased levels of a restricted set of cytokines that may exert immune activating roles in these areas without being able to trigger tissue damage

Tremor severity in Parkinson’s disease and cortical changes of areas controlling movement sequencing: a preliminary study.

. There remains much to learn about the changes in cortical anatomy that are associated with tremor severity in Parkinson’s disease (PD). For this reason, we used a combination of structural neuroimaging to measure cortical thickness and neurophysiological studies to analyze whether PD tremor was associated with cortex integrity. Magnetic resonance imaging and neurophysiological assessment were performed in 13 nondemented PD patients (9 women, 69.2%) with a clearly tremor-dominant phenotype. Cortical reconstruction and volumetric segmentation was performed with the Freesurfer image analysis software. Assessment of tremor was performed by means of high-density surface electromyography (hdEMG) and inertial measurement units (IMUs). Individual motor unit discharge patterns were identified from surface hdEMG and tremor metrics quantifying motor unit synchronization from IMUs were defined. Increased motor unit synchronization (i.e., more severe tremor) was associated with cortical changes (i.e., atrophy) in dorsal premotor cortices, left posterior parietal cortex, left lateral orbitofrontal cortex, cingulate cortex bilaterally, left posterior and transverse temporal cortex, and left occipital lobe, as well as reduced left middle temporal volume. Given that the majority of these areas are involved in controlling movement sequencing, our results support Albert’s classic hypothesis that PD tremor may be the result of an involuntary activation of a program of motor behavior used in the genesis of rapid voluntary alternating movements.pre-print670 K