Measuring atmospheric dispersion with WLRS in multiple wavelength mode

The WLRS (Wettzell Laser Ranging System) allows the simultaneous tracking of satellites on two different wavelengths. These are the fundamental frequency of Nd:YAG at 1.064 microns and the second harmonic at 532 nm. Range measurements to the satellite LAGEOS were carried out with different experimental set-ups, after developing a detector unit based on a silicon avalanche photodiode in Geiger mode, which is sufficiently sensitive in the infrared domain. An approach towards a quantitative interpretation of the data is suggested and discussed briefly

Sensorimotor functional connectivity: A neurophysiological factor related to BCI performance

Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. About 20% of potential users of sensorimotor BCIs do not gain reliable control of the system. The inefficiency to decode user's intentions requires the identification of neurophysiological factors determining “good” and “poor” BCI performers. One of the important neurophysiological aspects in BCI research is that the neuronal oscillations, used to control these systems, show a rich repertoire of spatial sensorimotor interactions. Considering this, we hypothesized that neuronal connectivity in sensorimotor areas would define BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in a calibration and an online feedback session recorded on the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post- as well as pre-stimulus connectivity in the calibration recording is significantly correlated to online feedback performance in μ and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study demonstrates that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sensorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance

SPoC: A novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters

Previously, modulations in power of neuronal oscillations have been functionally linked to sensory, motor and cognitive operations. Such links are commonly established by relating the power modulations to specific target variables such as reaction times or task ratings. Consequently, the resulting spatio-spectral representation is subjected to neurophysiological interpretation. As an alternative, independent component analysis (ICA) or alternative decomposition methods can be applied and the power of the components may be related to the target variable. In this paper we show that these standard approaches are suboptimal as the first does not take into account the superposition of many sources due to volume conduction, while the second is unable to exploit available information about the target variable. To improve upon these approaches we introduce a novel (supervised) source separation framework called Source Power Comodulation (SPoC). SPoC makes use of the target variable in the decomposition process in order to give preference to components whose power comodulates with the target variable. We present two algorithms that implement the SPoC approach. Using simulations with a realistic head model, we show that the SPoC algorithms are able extract neuronal components exhibiting high correlation of power with the target variable. In this task, the SPoC algorithms outperform other commonly used techniques that are based on the sensor data or ICA approaches. Furthermore, using real electroencephalography (EEG) recordings during an auditory steady state paradigm, we demonstrate the utility of the SPoC algorithms by extracting neuronal components exhibiting high correlation of power with the intensity of the auditory input. Taking into account the results of the simulations and real EEG recordings, we conclude that SPoC represents an adequate approach for the optimal extraction of neuronal components showing coupling of power with continuously changing behaviorally relevant parameters

Influence of Pacing Mode and Rate on Peripheral Levels of Atrial Natriuretic Peptide (ANP)

The effect of acute modifications of pacing mode and rate on plasma ANP levels was evaluated. ANP was determined in ten resting patients with ODD pacemokers due to binodal disease or intermittent second- and third-degree AV block. At 82/minute pacing rate the ANP plasma levels (normal range 2 to 30 fmol/mL) corresponded to those under AAI (4.05 ± 2.10 fmol/mL) and DDD (4.18 ± 2.02 fmol/mL) pacing, but increased significantly (P < 0.05) during VVI pacing (6.96 ± 3.70 fmol/mL). Acceleration of DDD stimulation frequency from 82 to 113/minutes led to significant increases of ANP levels by the factor of three in all chosen AV delays. The lowest ANP plasma levels were measured of 175 msec AV delay under 82/minute pacing rate in DDD mode. Under 113/minutes the differences of ANP concentration after variations of AV delays were less pronounced. The influences of altered atrial pressure and tension on ANP release are discussed to account for changes in ANP plasma levels following different modes and rates of pacemaker stimulation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75366/1/j.1540-8159.1989.tb01862.x.pd

Open Database of Epileptic EEG with MRI and Postoperational Assessment of Foci—a Real World Verification for the EEG Inverse Solutions

This paper introduces a freely accessible database http://eeg.pl/epi, containing 23 datasets from patients diagnosed with and operated on for drug-resistant epilepsy. This was collected as part of the clinical routine at the Warsaw Memorial Child Hospital. Each record contains (1) pre-surgical electroencephalography (EEG) recording (10–20 system) with inter-ictal discharges marked separately by an expert, (2) a full set of magnetic resonance imaging (MRI) scans for calculations of the realistic forward models, (3) structural placement of the epileptogenic zone, recognized by electrocorticography (ECoG) and post-surgical results, plotted on pre-surgical MRI scans in transverse, sagittal and coronal projections, (4) brief clinical description of each case. The main goal of this project is evaluation of possible improvements of localization of epileptic foci from the surface EEG recordings. These datasets offer a unique possibility for evaluating different EEG inverse solutions. We present preliminary results from a subset of these cases, including comparison of different schemes for the EEG inverse solution and preprocessing. We report also a finding which relates to the selective parametrization of single waveforms by multivariate matching pursuit, which is used in the preprocessing for the inverse solutions. It seems to offer a possibility of tracing the spatial evolution of seizures in time

Atrial Natriuretic Peptide Levels Reflect Hemodynamic Changes Under Pacemaker Stimulation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73244/1/j.1540-8159.1990.tb02142.x.pd

Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI

A variety of psychiatric, behavioral and cognitive phenotypes have been linked to brain ‘’functional connectivity’’ -- the pattern of correlation observed between different brain regions. Most commonly assessed using functional magnetic resonance imaging (fMRI), here, we investigate the connectivity-phenotype associations with functional connectivity measured with electroencephalography (EEG), using phase-coupling. We analyzed data from the publicly available Healthy Brain Network Biobank. This database compiles a growing sample of children and adolescents, currently encompassing 1657 individuals. Among a variety of assessment instruments we focus on ten phenotypic and additional demographic measures that capture most of the variance in this sample. The largest effect sizes are found for age and sex for both fMRI and EEG. We replicate previous findings of an association of Intelligence Quotient (IQ) and Attention Deficit Hyperactivity Disorder (ADHD) with the pattern of fMRI functional connectivity. We also find an association with socioeconomic status, anxiety and the Child Behavior Checklist Score. For EEG we find a significant connectivity-phenotype relationship with IQ. The actual spatial patterns of functional connectivity are quite different between fMRI and source-space EEG. However, within EEG we observe clusters of functional connectivity that are consistent across frequency bands. Additionally we analyzed reproducibility of functional connectivity. We compare connectivity obtained with different tasks, including resting state, a video and a visual flicker task. For both EEG and fMRI the variation between tasks was smaller than the variability observed between subjects. We also found an increase of reliability with increasing frequency of the EEG, and increased sampling duration. We conclude that, while the patterns of functional connectivity are distinct between fMRI and phase-coupling of EEG, they are nonetheless similar in their robustness to the task, and similar in that idiosyncratic patterns of connectivity predict individual phenotypes

Developing cardiac and skeletal muscle share fast-skeletal myosin heavy chain and cardiac troponin-I expression

Skeletal muscle derived stem cells (MDSCs) transplanted into injured myocardium can differentiate into fast skeletal muscle specific myosin heavy chain (sk-fMHC) and cardiac specific troponin-I (cTn-I) positive cells sustaining recipient myocardial function. We have recently found that MDSCs differentiate into a cardiomyocyte phenotype within a three-dimensional gel bioreactor. It is generally accepted that terminally differentiated myocardium or skeletal muscle only express cTn-I or sk-fMHC, respectively. Studies have shown the presence of non-cardiac muscle proteins in the developing myocardium or cardiac proteins in pathological skeletal muscle. In the current study, we tested the hypothesis that normal developing myocardium and skeletal muscle transiently share both sk-fMHC and cTn-I proteins. Immunohistochemistry, western blot, and RT-PCR analyses were carried out in embryonic day 13 (ED13) and 20 (ED20), neonatal day 0 (ND0) and 4 (ND4), postnatal day 10 (PND10), and 8 week-old adult female Lewis rat ventricular myocardium and gastrocnemius muscle. Confocal laser microscopy revealed that sk-fMHC was expressed as a typical striated muscle pattern within ED13 ventricular myocardium, and the striated sk-fMHC expression was lost by ND4 and became negative in adult myocardium. cTn-I was not expressed as a typical striated muscle pattern throughout the myocardium until PND10. Western blot and RT-PCR analyses revealed that gene and protein expression patterns of cardiac and skeletal muscle transcription factors and sk-fMHC within ventricular myocardium and skeletal muscle were similar at ED20, and the expression patterns became cardiac or skeletal muscle specific during postnatal development. These findings provide new insight into cardiac muscle development and highlight previously unknown common developmental features of cardiac and skeletal muscle. © 2012 Clause et al

Contamination Control and Assay Results for the Majorana Demonstrator Ultra Clean Components

The MAJORANA DEMONSTRATOR is a neutrinoless double beta decay experiment utilizing enriched Ge-76 detectors in 2 separate modules inside of a common solid shield at the Sanford Underground Research Facility. The DEMONSTRATOR has utilized world leading assay sensitivities to develop clean materials and processes for producing ultra-pure copper and plastic components. This experiment is now operating, and initial data provide new insights into the success of cleaning and processing. Post production copper assays after the completion of Module 1 showed an increase in U and Th contamination in finished parts compared to starting bulk material. A revised cleaning method and additional round of surface contamination studies prior to Module 2 construction have provided evidence that more rigorous process control can reduce surface contamination. This article describes the assay results and discuss further studies to take advantage of assay capabilities for the purpose of maintaining ultra clean fabrication and process design.Comment: Proceedings of Low Radioactivity Techniques (LRT May 2017, Seoul