Ordinal patterns in epileptic brains: Analysis of intracranial EEG and simultaneous EEG-fMRI

Epileptic seizures are associated with high behavioral stereotypy of the patients. In the EEG of epilepsy patients characteristic signal patterns can be found during and between seizures. Here we use ordinal patterns to analyze EEGs of epilepsy patients and quantify the degree of signal determinism. Besides relative signal redundancy and the fraction of forbidden patterns we introduce the fraction of under-represented patterns as a new measure. Using the logistic map, parameter scans are performed to explore the sensitivity of the measures to signal determinism. Thereafter, application is made to two types of EEGs recorded in two epilepsy patients. Intracranial EEG shows pronounced determinism peaks during seizures. Finally, we demonstrate that ordinal patterns may be useful for improving analysis of non-invasive simultaneous EEG-fMR

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The neuronal correlates of mirror illusion in children with spastic hemiparesis: a study with functional magnetic resonance imaging.

To investigate the neuronal activation pattern underlying the effects of mirror illusion in children/adolescents with normal motor development and in children/adolescents with hemiparesis and preserved contralateral corticospinal organisation. The type of cortical reorganisation was classified according to results of transcranial magnetic stimulation. Only subjects with congenital lesions and physiological contralateral cortical reorganisation were included. Functional magnetic resonance imaging was performed to investigate neuronal activation patterns with and without a mirror box. Each test consisted of a unimanual and a bimanual motor task. Seven children/adolescents with congenital hemiparesis (10-20 years old, three boys and four girls) and seven healthy subjects (8-17 years old, four boys and three girls) participated in this study. In the bimanual experiment, children with hemiparesis showed a significant effect of the mirror illusion (p<0.001 at voxel level, family-wise error corrected at cluster level) in the dorsolateral prefrontal cortex and anterior cingulate cortex of the affected and unaffected hemispheres, respectively. No significant effects of the mirror illusion were observed in unimanual experiments and in healthy participants. Mirror illusion in children/adolescents with hemiparesis leads to activation of brain areas involved in visual conflict detection and cognitive control to resolve this conflict. This effect is observed only in bimanual training. We consider that for mirror therapy in children and adolescents with hemiparesis a bimanual approach is more suitable than a unimanual approach

A finite-volume scheme for modeling compressible magnetohydrodynamic flows at low Mach numbers in stellar interiors

Fully compressible magnetohydrodynamic (MHD) simulations are a fundamental tool for investigating the role of dynamo amplification in the generation of magnetic fields in deep convective layers of stars. The flows that arise in such environments are characterized by low (sonic) Mach numbers (M_son < 0.01 ). In these regimes, conventional MHD codes typically show excessive dissipation and tend to be inefficient as the Courant-Friedrichs-Lewy (CFL) constraint on the time step becomes too strict. In this work we present a new method for efficiently simulating MHD flows at low Mach numbers in a space-dependent gravitational potential while still retaining all effects of compressibility. The proposed scheme is implemented in the finite-volume Seven-League Hydro (SLH) code, and it makes use of a low-Mach version of the five-wave Harten-Lax-van Leer discontinuities (HLLD) solver to reduce numerical dissipation, an implicit-explicit time discretization technique based on Strang splitting to overcome the overly strict CFL constraint, and a well-balancing method that dramatically reduces the magnitude of spatial discretization errors in strongly stratified setups. The solenoidal constraint on the magnetic field is enforced by using a constrained transport method on a staggered grid. We carry out five verification tests, including the simulation of a small-scale dynamo in a star-like environment at M_son ~ 0.001 . We demonstrate that the proposed scheme can be used to accurately simulate compressible MHD flows in regimes of low Mach numbers and strongly stratified setups even with moderately coarse grids

Acute Stress-Induced Blood Lipid Reactivity in Hypertensive and Normotensive Men and Prospective Associations with Future Cardiovascular Risk.

Hyperreactivity to stress may be one explanation for the increased risk of cardiovascular disease (CVD) in individuals with essential hypertension. We investigated blood lipid reactivity to the Montreal Imaging Stress Task (MIST), a psychosocial stressor, in hypertensive and normotensive men and tested for prospective associations with biological risk factors. Fifty-six otherwise healthy and medication-free hypertensive and normotensive men underwent the MIST. We repeatedly measured cortisol and blood lipid profiles (total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG)) immediately before and up to 1 h after stress. Lipid levels were corrected for stress hemoconcentration. Thirty-five participants completed follow-up assessment 2.9 ± 0.12 (SEM) years later. CVD risk was assessed by prospective changes in TC/HDL-C ratio, IL-6, D-dimer, and HbA1c from baseline to follow-up. The MIST induced significant changes in all parameters except TC (p-values ≤ 0.043). Compared with normotensives, hypertensives had higher TC/HDL-C-ratio and TG (p-values ≤ 0.049) stress responses. Blood lipid stress reactivity predicted future cardiovascular risk (p = 0.036) with increases in HbA1c (ß = 0.34, p = 0.046), IL-6 (ß = 0.31, p = 0.075), and D-dimer (ß = 0.33, p = 0.050). Our results suggest that the greater blood lipid reactivity to psychosocial stress in hypertensives, the greater their future biological CVD risk. This points to lipid stress reactivity as a potential mechanism through which stress might increase CVD risk in essential hypertension

Gastroesophageal Junction and Pylorus Distensibility Before and After Sleeve Gastrectomy-pilot Study with EndoFlipTM.

Sleeve gastrectomy (SG) is the most frequently performed bariatric surgical intervention worldwide. Gastroesophageal reflux disease (GERD) is frequently observed after SG and is a relevant clinical problem. This prospective study investigated the gastroesophageal junction (GEJ) and pyloric sphincter by impedance planimetry (EndoFlipTM) and their association with GERD at a tertiary university hospital center. Between January and December 2018, patients undergoing routine laparoscopic SG had pre-, intra-, and postoperative assessments of the GEJ and pyloric sphincter by EndoFlipTM. The distensibility index (DI) was measured at different volumes and correlated with GERD (in accordance with the Lyon consensus guidelines). Nine patients were included (median age 48 years, preoperative BMI 45.1 kg/m2, 55.6% female). GERD (de novo or stable) was observed in 44.4% of patients one year postoperatively. At a 40-ml filling volume, DI increased significantly pre- vs. post-SG of the GEJ (1.4 mm2/mmHg [IQR 1.1-2.6] vs. 2.9 mm2/mmHg [2.6-5.3], p VALUE=0.046) and of the pylorus (6.0 mm2/mmHg [4.1-10.7] vs. 13.1 mm2/mmHg [7.6-19.2], p VALUE=0.046). Patients with postoperative de novo or stable GERD had a significantly increased preoperative DI at 40 ml of the GEJ (2.6 mm2/mmHg [1.9-3.5] vs. 0.5 mm2/mmHg [0.5-1.1], p VALUE=0.031). There was no significant difference in DI at 40 mL filling in the preoperative pylorus and postoperative GEJ or pylorus. In this prospective study, the DI of the GEJ and the pylorus significantly increased after SG. Postoperative GERD was associated with a significantly higher preoperative DI of the GEJ but not of the pylorus

A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images.

Collateral circulation results from specialized anastomotic channels which are capable of providing oxygenated blood to regions with compromised blood flow caused by arterial obstruction. The quality of collateral circulation has been established as a key factor in determining the likelihood of a favorable clinical outcome and goes a long way to determining the choice of a stroke care model. Though many imaging and grading methods exist for quantifying collateral blood flow, the actual grading is mostly done through manual inspection. This approach is associated with a number of challenges. First, it is time-consuming. Second, there is a high tendency for bias and inconsistency in the final grade assigned to a patient depending on the experience level of the clinician. We present a multi-stage deep learning approach to predict collateral flow grading in stroke patients based on radiomic features extracted from MR perfusion data. First, we formulate a region of interest detection task as a reinforcement learning problem and train a deep learning network to automatically detect the occluded region within the 3D MR perfusion volumes. Second, we extract radiomic features from the obtained region of interest through local image descriptors and denoising auto-encoders. Finally, we apply a convolutional neural network and other machine learning classifiers to the extracted radiomic features to automatically predict the collateral flow grading of the given patient volume as one of three severity classes - no flow (0), moderate flow (1), and good flow (2). Results from our experiments show an overall accuracy of 72% in the three-class prediction task. With an inter-observer agreement of 16% and a maximum intra-observer agreement of 74% in a similar experiment, our automated deep learning approach demonstrates a performance comparable to expert grading, is faster than visual inspection, and eliminates the problem of grading bias

Neuroimaging of Epilepsy: Lesions, Networks, Oscillations

While analysis and interpretation of structural epileptogenic lesion is an essential task for the neuroradiologist in clinical practice, a substantial body of epilepsy research has shown that focal lesions influence brain areas beyond the epileptogenic lesion, across ensembles of functionally and anatomically connected brain areas. In this review article, we aim to provide an overview about altered network compositions in epilepsy, as measured with current advanced neuroimaging techniques to characterize the initiation and spread of epileptic activity in the brain with multimodal noninvasive imaging techniques. We focus on resting-state functional magnetic resonance imaging (MRI) and simultaneous electroencephalography/fMRI, and oppose the findings in idiopathic generalized versus focal epilepsies. These data indicate that circumscribed epileptogenic lesions can have extended effects on many brain systems. Although epileptic seizures may involve various brain areas, seizure activity does not spread diffusely throughout the brain but propagates along specific anatomic pathways that characterize the underlying epilepsy syndrome. Such a functionally oriented approach may help to better understand a range of clinical phenomena such as the type of cognitive impairment, the development of pharmacoresistance, the propagation pathways of seizures, or the success of epilepsy surgery