Distinctive Waveform Research Articles

Probing kaon meson condensations through gravitational waves during neutron star inspiral phases

Gravitational waves from binary neutron star merger events have shown unparalleled advantages in deciphering the stellar internal structure, yet it remains underexplored to seek clues about kaon meson condensations inside massive neutron stars through these events. To address this gap, this study examines the binary star inspiral processes with kaon meson condensations, employing various kaon meson potential wells to probe unique imprints in the inspiral gravitational waves. Our analysis reveals that the inspiral process of kaon meson condensation binary stars exhibits lower gravitational wave frequencies and shorter retarded times compared to traditional neutron stars. Furthermore, a deeper kaon meson potential well in these systems further shortens the inspiral duration time, resulting in distinctive gravitational waveforms and notable orbital phase deviations. These findings underscore the pivotal role of kaon meson condensations in modulating the inspiral gravitational waves, suggesting the inspiral gravitational waves could serve as a powerful tool for probing potential signals of kaon mesons within neutron stars.

Fault mechanism and dynamic two-phase flow behavior of liquid slugging in reciprocating compressors

Liquid slugging is a fatal fault for large process compressors, leading to transient overpressure, the deformation and fracture of vital pressure-bearing parts, and even gas leakage or explosion. In the study reported here, to reveal the mechanism of overpressure formation, numerical simulations were conducted by means of the volume-of-fluid method to explore the dynamic evolution characteristics of the two-phase flow pattern. Then, high-speed photography was applied to capture the dynamic changes of the liquid boundary in the modified cylinder from different views, thus realizing the validation of the numerical model. This study reveals the significant influence of increased rotational speed on fluid flow patterns, impeding liquid discharge and exacerbating overpressure events. Additionally, changes in pressure waveform and a distinctive waveform feature were identified as effective diagnostic indicators for detecting fluid slugging. Next, a nondestructive pressure monitoring reconstruction method based on measuring bolt strain was proposed. The strain-based pressure showed good agreement with the simulated results, thereby validating its effectiveness and feasibility as an early warning indicator for liquid slugging. This study offers new perspectives on the failure mechanism of liquid slugging in reciprocating compressors by delving into the behavior of two-phase flow, with the potential to enhance the theoretical foundation of compressor condition monitoring and fault diagnosis.

What makes low-frequency earthquakes low frequency.

Low-frequency earthquakes, atypical seismic events distinct from regular earthquakes, occur downdip of the seismogenic megathrust where an aseismic rheology dominates the subduction plate boundary. Well situated to provide clues on the slip regime of this unique faulting environment, their distinctive waveforms reflect either an unusual rupture process or unusually strong attenuation in their source zone. We take advantage of the unique geometry of seismicity in the Nankai Trough to isolate the spectral signature of low-frequency earthquakes after correcting for empirically derived attenuation. We observe that low-frequency earthquake spectra are consistent with the classical earthquake model, yet their rupture duration and stress drop are orders of magnitude different from ordinary earthquakes. We conclude their low-frequency nature primarily results from an atypical seismic rupture process rather than near-source attenuation.

Study on signal decomposition-based pump noise cancellation method for continuous-wave mud pulse telemetry

Continuous mud pulse telemetry is an advanced downhole data transmission technology in measurement while drilling (MWD) systems. However, various noise interference during transmission has resulted in continuous mud pulse telemetry often encountering difficulties in decoding under harsh working conditions, with the influence of pump noise being the most severe. On the bases of the narrowband signal characteristics of pump noise harmonics and a deep study of the variational mode decomposition (VMD) algorithm, this study proposes an improved version called constant center frequency VMD (CVMD), the mode function center frequencies of which are fixed in the initial state. The denoising performance of the proposed algorithm is thoroughly analyzed by simulating a series of continuous mud pulse signals with different noise intensities under stable/unstable mud pump conditions. Results demonstrate that the CVMD algorithm has an advantage over conventional filters because the former can maximize the preservation of useful information within the critical frequency band. Compared with the Kalman filter based on the same pump noise model, the CVMD algorithm has a higher signal-to-noise ratio, smaller mean square error, higher correlation with the ideal signal, and is also applicable when the pump state is unstable. In addition, the proposed method has been successfully applied to the processing of real-field experimental data transmitted over thousands of meters and disturbed by complex noise. Consequently, a distinctive waveform of the transmitted pulse is obtained, and powerful technical support is provided for the realization of continuous mud pulse downhole data transmission in harsh mud circulation environments.

Source Localization of Normal Variants Seen on EEG.

The EEG is an essential neurological diagnostic tool. EEG abnormalities can guide diagnosis and management of epilepsy. There are also distinctive EEG waveforms that are seen in healthy individuals. It is critical not to misinterpret these as abnormal. To emphasize the importance of these waveforms, we analyzed different normal variants via the source localization technology. This is a retrospective analysis of EEGs performed at the Duke University Hospital between June 2014 and Dec 2019. We selected samples of vertex waves, Mu, lambda, POSTS, wickets, and sleep spindles for analysis. EEG were imported to Curry 8 (Compumedics) to calculate the dipole and current density. The averaged head model from the Montreal Neurological Institute database was used for reconstruction. Thirty-four patient EEG samples were selected including five vertex, six Mu, four wicket, seven lambda, five POSTS, and seven spindles. Results from source localization showed that vertex waves are localized in the frontocentral area, whereas spindles in the deep midline central region. Mu were identified in the ipsilateral somatosensory cortex. Lambda and POSTS, on the other hand, had maximum results over the bilateral occipital region and wickets in the ipsilateral temporal lobe. Our results confirm and expand previous hypotheses. This allows us to speculate on the origin of these normal EEG variants. Although this study is limited by small sample size, lack of high-density EEG, and patient-specific MRI, our analysis provides an easily replicable three-dimensional visualization of these waveforms.

Analog transmission of action potential fine structure in spiral ganglion axons.

Action potential waveforms generated at the axon initial segment (AIS) are specialized between and within neuronal classes. But is the fine structure of each electrical event retained when transmitted along myelinated axons or is it rapidly and uniformly transmitted to be modified again at the axon terminal? To address this issue, action potential axonal transmission was evaluated in a class of primary sensory afferents that possess numerous types of voltage-gated ion channels underlying a complex repertoire of endogenous firing patterns. In addition to their signature intrinsic electrophysiological heterogeneity, spiral ganglion neurons are uniquely designed. The bipolar, myelinated somata of type I neurons are located within the conduction pathway, requiring that action potentials generated at the first heminode must be conducted through their electrically excitable membrane. We used this unusual axonal-like morphology to serve as a window into action potential transmission to compare locally evoked action potential profiles to those generated peripherally at their glutamatergic synaptic connections with hair cell receptors. These comparisons showed that the distinctively shaped somatic action potentials were highly correlated with the nodally generated, invading ones for each neuron. This result indicates that the fine structure of the action potential waveform is maintained axonally, thus supporting the concept that analog signaling is incorporated into each digitally transmitted action potential in the specialized primary auditory afferents.NEW & NOTEWORTHY Diverse action potential shapes and kinetics resulting from dynamic heterogeneity in spiral ganglion neurons are axonally transmitted as multiplexed signals that retain the fine structure of each distinctive waveform within a digital code.

Can We Distinguish Triphasic Waves From Other Generalized Periodic Discharges? Do We Need to?

Triphasic waves are intuitively distinctive waveforms that fall under the umbrella of generalized periodic discharges. The ability to distinguish these waveforms consistently could be helpful if a specific underlying pathophysiology could be identified. However, scalp EEG and clinical observation have been limited in their ability to elucidate the underlying cortical physiology that leads to triphasic waves. Evidence from intracranial physiologic data and computational modeling suggest that these and other periodic discharges should be viewed not as strictly ictal nor non-ictal but rather on the spectrum between these two. Triphasic waves in particular appear to result from an abnormal balance between cortical excitation and synaptic transmission with input from functionally connected brain networks, such as the thalamocortical pathways involved in arousal. The practical implication of triphasic waves begins with acknowledgement of uncertainty and a rational approach should ask whether the pattern-or its treatment-might be creating harm.

Behavioral arrest and a characteristic slow waveform are hallmark responses to selective 5-HT2A receptor activation

Perception, emotion, and mood are powerfully modulated by serotonin receptor (5-HTR) agonists including hallucinogens. The 5-HT2AR subtype has been shown to be central to hallucinogen action, yet the precise mechanisms mediating the response to 5-HT2AR activation remain unclear. Hallucinogens induce the head twitch response (HTR) in rodents, which is the most commonly used behavioral readout of hallucinogen pharmacology. While the HTR provides a key behavioral signature, less is known about the meso level changes that are induced by 5-HT2AR activation. In response to administration of the potent and highly selective 5-HT2AR agonist 25I-NBOH in mice, we observe a disorganization of behavior which includes frequent episodes of behavioral arrest that consistently precede the HTR by a precise interval. By combining behavioral analysis with electroencephalogram (EEG) recordings we describe a characteristic pattern composed of two distinctive EEG waveforms, Phase 1 and Phase 2, that map onto behavioral arrest and the HTR respectively, with the same temporal separation. Phase 1, which underlies behavioral arrest, is a 3.5–4.5 Hz waveform, while Phase 2 is slower at 2.5–3.2 Hz. Nicotine pretreatment, considered an integral component of ritualistic hallucinogen practices, attenuates 25I-NBOH induced HTR and Phase 2 waveforms, yet increases behavioral arrest and Phase 1 waveforms. Our results suggest that in addition to the HTR, behavioral arrest and characteristic meso level slow waveforms are key hallmarks of the response to 5-HT2AR activation. Increased understanding of the response to serotonergic hallucinogens may provide mechanistic insights into perception and hallucinations, as well as regulation of mood.

Evaluation of Extreme Bradyarrhythmias in Symptomatic Adults.

Scenario: This 12-lead electrocardiogram (ECG) was obtained by paramedics on an 81-year-old man with chief complaints of dizziness, weakness, nausea, and vomiting for 2 days. The patient reported that he had experienced 2 similar near-syncopal episodes the preceding week. The patient denied chest pain or shortness of breath. He had a complex medical history that included coronary artery disease, arrhythmias, and renal failure. During the prehospital evaluation, the patient was lethargic, had a weak pulse at 28 beats per minute, and his blood pressure was undetectable.Atrial flutter with complete heart block and 4 ventricular escape beats of multifocal origin. Although the fourth beat looks narrow, it is unlikely to be of supraventricular origin given the lack of distinctive waveform morphology in leads V4 through V6.The 4 QRS complexes (ie, heartbeats) seen in this rhythm (arrows) are mostly of ventricular origin, as indicated by the characteristic bizarrely shaped QRS complexes that are wide, not related to a P wave, and have a discordant T wave (opposite direction to the QRS deflection). All of the escape beats have different QRS morphologies, suggesting that they are multifocal in origin; that explains the lack of a detectable heart rate, which is why the term beats is used rather than escape rhythm. An escape rhythm typically sustains some cardiac output and therefore is usually lifesaving and is common when atrial activity is not propagated through the normal conduction pathway. Complete heart block can be caused by acute myocardial infarction, structural heart disease, electrolyte imbalance, or atrioventricularnodal blocking medications (eg, calcium channel blockers). The absence of a sustainable escape rhythm despite supraventricular activation is usually referred to as ventricular standstill and should be treated as an asystole equivalent. The rapid atrial flutter combined with the infrequent random escape beats explains the patient’s slow, weak pulse. In addition, these escape beats were not sufficient to maintain a detectable blood pressure, which explains the patient’s syncopal symptoms.Remarkably, he was able to survive this extreme bradycardia event. Because this rhythm was an asystole equivalent, the patient was given a bolus of intravenous epinephrine and multifunction pads were applied to the torso in case transcutaneous pacing was needed. On arrival at the emergency department, the patient was oriented, with a heart rate of ~50/min. Initial cardiac workup was negative for acute myocardial infarction, and serum electrolyte levels were normal. However, a repeat 12-lead ECG showed atrial flutter with left bundle branch block, a potentially life-threatening combination usually seen in patients with progressive conduction system disease due to structural cardiac remodeling (eg, necrosis due to atherosclerotic disease as in this scenario). The patient was admitted to the intensive care unit for intravenous dopamine infusion, later received a permanent biventricular implantable cardiac defibrillator, and was eventually discharged home.

Using the First-Order Perturbation Equation from Quantum Mechanics to Predict the Postprandial Plasma Glucose Data and Waveforms for Solid and Liquid Egg Meals from a Neuro-Scientific Viewpoint Based on GH-Method: Math-Physical Medicine (No. 470)

The author has applied the first-order interpolation perturbation equation from quantum mechanics in his medical research work, which he has written numerous articles on this topic. This equation is the simplest application using one selected “perturbation factor” to generate perturbed results with high prediction accuracy. He investigates this type of problem using a chosen pperturbation factor such as carbs/sugar for postprandial plasma glucose (PPG), body weight for fasting plasma glucose (FPG), or metabolism index (MI) in predicting a stroke or heart attack along with achieving longevity in the geriatric research area. In this particular article, he uses carbs/sugar amount of one large egg as the perturbation factor to predict his perturbed PPG results. The mixed egg meals include the solid and liquid egg data based on two measured PPG waveforms using solid and liquid egg meals, separately. The two types of egg meals provide different PPG values and distinctive waveforms despite having identical food ingredients with the same 3 grams of carbs/sugar amount from one large egg. For example, the solid egg meal has higher PPG values than the liquid egg meal with a difference of 23 mg/dL for the peak PPG and 18 mg/dL for the average PPG. In his published neuroscience papers, he described the remarkable physical phenomenon from a neuro-scientific viewpoint.

Electrocardiogram-based Parameters for the Prediction of Sudden Cardiac Death: A Review

There has recently been a resurgence of interest in electrocardiogram-based (ECG-based) parameters in predicting Sudden Cardiac Death (SCD) risk. Accurate and timely SCD predictions are essential clinical practice for physicians to provide effective prevention and treatment. An ECG is a non-invasive and inexpensive diagnostic test, and has been firmly established as a clinical tool for assessing the risk of cardiac disease. The electrocardiographic signal derived from the ECG recording consists of a distinctive waveform that depicts the electrical activity of the heart, which can be analyzed for the identification of abnormalities in the heart rhythm. The parameter or characteristic found in the ECG signal might be important for predicting the SCD. A number of systematic reports by expert meetings and review articles in indexed journals identified ECG-based parameters as QRS duration, QT interval, Signal Average ECG (SAECG), T-wave alternan (TWA), Heart Rate Variability (HRV), Heart Rate Turbulence (HRT), T-peak to T-end (Tpe), fragmented QRS complexes (fQRS), and Early Repolarization (ER). This article reviews the mechanism and morphology of these parameters, which may potentially have a role to play in a future algorithm designed to identify early signs of SCD. As of now, none of the ECG-based parameters have been found to be sufficiently stable to predict the SCD risk. Nevertheless, the combination of two or more of the parameters listed, as suggested in many studies, may become a useful component for predicting SCD in the future.

Towards Automatic Landslide-Quake Identification Using a Random Forest Classifier

Landslide-generated seismic waves (landslide-quakes), exhibiting distinctive waveforms and frequency characteristics, can be recorded by nearby seismometers. Implementing an automatic classifier for landslide-quakes could help provide objective and accurate initiation times of landslides with efficiency. This study collected and analyzed the time information of 214 landslide seismic records due to 33 documented landslide events, from the Broadband Array in Taiwan for Seismology (BATS). In addition, equal numbers of earthquake and noise signals were also incorporated. The 642 seismic signals and time information were carefully examined using the random forest algorithm to create an automatic landslide-quake classifier. By validating the signal attributes of the landslide, earthquake, and noise events, specifically in the time and frequency domains, it was shown that the proposed classifier can reach an accuracy (the proportion of all correctly classified events to the total number of events) of 91.3%. To further evaluate the applicability of the automatic classifier, landslide-quakes generated during the devastating Typhoon Morakot (2009) and Typhoon Soudelor (2015) were also verified, showing that the sensitivity of the classifier is higher than 98%.

WiFace: Facial Expression Recognition Using Wi-Fi Signals

Facial expression is an important form of human nonverbal communication. Recognition of this nonverbal sign may enable developers to understand the feedback of the servers of smart devices or advertising. Existing approaches for facial expression recognition are mainly based on cameras or on-body sensors, which are either sensitive to lighting conditions or require users to wear cumbersome devices on their faces. In this paper, we propose a new facial expression recognition system based on Wi-Fi signals, named WiFace. Our key intuition is that facial muscle movements in different expressions will induce distinctive waveform patterns in the time-series of Channel State Information (CSI) in Wi-Fi signals. We develop a series of algorithms to process the CSI signals and extract the most representative waveform patterns for facial expression classification. We build a fully-functional prototype of WiFace using commercial off-the-shelf devices, which can recognize 6 typical facial expressions. We conduct extensive experiments to evaluate the performance of WiFace, and the experimental results show that the average recognition accuracy is 94.0%.

Passive Localization Through Light Flicker Fingerprinting

In this paper, we show that the flicker waveforms of various CFL and LED lamp models exhibit distinctive waveform patterns due to harmonic distortions of rectifiers and voltage regulators, the key components of modern lamp drivers. We then propose a passive localization technique based on fingerprinting these distortions that occur naturally in indoor environments and thus requires no infrastructure or additional equipment. The novel technique uses principal component analysis (PCA) to extract the most important signal features from the flicker frequency spectra followed by $k$ NN clustering and neural network classifiers to identify a light source based on its flicker signature. The evaluation on 39 flicker patterns collected from 8 residential locations demonstrates that the technique can identify a location within a house with up to 90% accuracy and identify an individual house from a set of houses with an average accuracy of 86.3%.

Quantification of the Influence of Deep Basin Effects on Structural Collapse Using SCEC CyberShake Earthquake Ground Motion Simulations

This paper examines the effects of earthquake ground motions in deep sedimentary basins on structural collapse risk using physics-based earthquake simulations of the Los Angeles basin developed through the Southern California Earthquake Center's CyberShake project. Distinctive waveform characteristics of deep basin seismograms are used to classify the ground motions into several archetype groups, and the damaging influence of the basin effects are evaluated by comparing nonlinear structural responses under spectrum and significant duration equivalent basin and nonbasin ground motions. The deep basin ground motions are observed to have longer period-dependent durations and larger sustained spectral intensities than nonbasin motions for vibration periods longer than about 1.5 s, which can increase structural collapse risk by up to 20% in ground motions with otherwise comparable peak spectral accelerations and significant durations. Two new metrics are proposed to quantify period-dependent duration effects that are not otherwise captured by conventional ground motion intensity measures. The proposed sustained amplitude response spectra and significant duration spectra show promise for characterizing the damaging effects of long duration features of basin ground motions on buildings and other structures.

A multi-technology analysis of the 2017 North Korean nuclear test

Abstract. On 3 September 2017 official channels of the Democratic People's Republic of Korea announced the successful test of a thermonuclear device. Only seconds to minutes after the alleged nuclear explosion at the Punggye-ri nuclear test site in the mountainous region in the country's northeast at 03:30:02 (UTC), hundreds of seismic stations distributed all around the globe picked up strong and distinct signals associated with an explosion. Different seismological agencies reported body wave magnitudes of well above 6.0, consequently estimating the explosive yield of the device on the order of hundreds of kT TNT equivalent. The 2017 event can therefore be assessed as being multiple times larger in energy than the two preceding North Korean events in January and September 2016. This study provides a multi-technology analysis of the 2017 North Korean event and its aftermath using a wide array of geophysical methods. Seismological investigations locate the event within the test site at a depth of approximately 0.6 km below the surface. The radiation and generation of P- and S-wave energy in the source region are significantly influenced by the topography of the Mt. Mantap massif. Inversions for the full moment tensor of the main event reveal a dominant isotropic component accompanied by significant amounts of double couple and compensated linear vector dipole terms, confirming the explosive character of the event. The analysis of the source mechanism of an aftershock that occurred around 8 min after the test in the direct vicinity suggest a cavity collapse. Measurements at seismic stations of the International Monitoring System result in a body wave magnitude of 6.2, which translates to an yield estimate of around 400 kT TNT equivalent. The explosive yield is possibly overestimated, since topography and depth phases both tend to enhance the peak amplitudes of teleseismic P waves. Interferometric synthetic aperture radar analysis using data from the ALOS-2 satellite reveal strong surface deformations in the epicenter region. Additional multispectral optical data from the Pleiades satellite show clear landslide activity at the test site. The strong surface deformations generated large acoustic pressure peaks, which were observed as infrasound signals with distinctive waveforms even at distances of 401 km. In the aftermath of the 2017 event, atmospheric traces of the fission product 133Xe were detected at various locations in the wider region. While for 133Xe measurements in September 2017, the Punggye-ri test site is disfavored as a source by means of atmospheric transport modeling, detections in October 2017 at the International Monitoring System station RN58 in Russia indicate a potential delayed leakage of 133Xe at the test site from the 2017 North Korean nuclear test.

P13.03: Pulmonary artery waveforms preceding lethal pulmonary hypoplasia: the “flash sign”

To present an observed distinctive waveform pattern of the fetal main proximal pulmonary artery branch (bPA) in cases with lethal pulmonary hypoplasia secondary to bilateral renal agenesis. The longitudinal follow up of the bPA has been acquired on 2 cases with congenital bilateral renal agenesis. The bPA was sampled at its origin as it branches from the main pulmonary trunk. Pulse waves were acquired when the fetus is quiescent and with no breathing movements. In comparison to normal bPA waveform, there is a qualitative pattern that progresses as the gestational age advances with the presence and development of three main findings: First, the absence of the normal diastolic flow. Second is the progression of a deeper reversed velocity wave (RV). Lastly, there is increased systolic peak velocity. The combination of these wave represent a change from the normal recognized waveform of the bPA to a pattern that we described as the “flash sign”. Assessment of the bPA Doppler waveform and the presence of the “flash sign” could represent a tool for the prediction of the lethal pulmonary hypoplasia for which future research is needed. Supporting information can be found in the online version of this abstract Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Modelling spiky acceleration response of dilative sand deposits during earthquakes with emphasis on large post-liquefaction deformation

The acceleration records at some liquefied sand deposits exhibit a distinctive spiky waveform, characterized by strong amplification and high-frequency components. A comprehensive constitutive model was used to analyze the mechanism of such spiky acceleration responses. An idealized single-degree-of-freedom (SDF) system was constructed, in which the force-displacement relation of the spring follows the stress-strain behavior of saturated sand during undrained shearing. The SDF system demonstrated that the spikes are directly related to the strain-hardening behavior of sand during post-liquefaction cyclic shearing. Furthermore, there exists a threshold shear strain length, which is in accordance with the limited amplitude of the fluid-like shear strain generated at instantaneous zero effective stress state during the post-liquefaction stage. The spiky acceleration can only occur when the cyclic shear strain exceeds the threshold shear strain length. It is also revealed that the time intervals between the acceleration spikes increase gradually along with the continuation of shaking because the threshold shear strain length increases gradually and then more time is needed to generate larger shear strain to cause strain hardening. Records at the Kushiro Port site and Port Island site during past earthquakes are simulated through the fully coupled method to validate the presented mechanism.

Non-invasive, MRI-based estimation of patient-specific aortic blood pressure using one-dimensional blood flow modelling

Background and objectivesClinical evidence shows that central (aortic) blood pressure (CBP) is a better marker of cardiovascular risk than brachial pressure [1]. However, CBP can only be accurately measured invasively, through catheterisation. We propose a novel approach to estimate CBP non-invasively from aortic MRI data and a non-invasive peripheral (brachial) pressure measurement, using a one-dimensional (1-D) model of aortic blood flow.MethodsWe created a population of virtual (computed) subjects, each with distinctive arterial pulse waveforms available at multiple arterial locations, to assess our approach. This was achieved by varying cardiac (stroke volume, cardiac period, time of systole) and arterial (pulse wave velocity, peripheral vascular resistance) parameters of a distributed 1-D model of the larger systemic arteries [2] within a wide range of physiologically plausible values. After optimising our algorithm for the aortic 1-D model in silico, we tested its accuracy in a clinical population of 8 post-coarctation repair patients.ResultsResults from our in silico study, after varying cardiac and arterial parameters by ± 30%, showed maximum relative errors for systolic, mean and diastolic CBP of 4.5%, 3.6% and 4.2%, respectively. Average relative errors for systolic, mean and diastolic CBP were 2.7%, 0.9% and 1.2%, respectively. Corresponding average relative errors from our clinical study were 5.4%, 1.5% and 8.0%.Figure 1CBP estimation using the aortic 1-D model for a given virtual patient.Figure 2Systolic CBP estimated using the aortic 1-D model against reference systolic CBP values from in silico and in vivo data.ConclusionsWe have provided a proof of concept for the non-invasive estimation of patient-specific central blood pressure using computational aortic blood flow modelling in combination with MRI data and a non-invasive peripheral pressure measurement.

Four alpha ganglion cell types in mouse retina: Function, structure, and molecular signatures.

The retina communicates with the brain using ≥30 parallel channels, each carried by axons of distinct types of retinal ganglion cells. In every mammalian retina one finds so-called "alpha" ganglion cells (αRGCs), identified by their large cell bodies, stout axons, wide and mono-stratified dendritic fields, and high levels of neurofilament protein. In the mouse, three αRGC types have been described based on responses to light steps: On-sustained, Off-sustained, and Off-transient. Here we employed a transgenic mouse line that labels αRGCs in the live retina, allowing systematic targeted recordings. We characterize the three known types and identify a fourth, with On-transient responses. All four αRGC types share basic aspects of visual signaling, including a large receptive field center, a weak antagonistic surround, and absence of any direction selectivity. They also share a distinctive waveform of the action potential, faster than that of other RGC types. Morphologically, they differ in the level of dendritic stratification within the IPL, which accounts for their response properties. Molecularly, each type has a distinct signature. A comparison across mammals suggests a common theme, in which four large-bodied ganglion cell types split the visual signal into four channels arranged symmetrically with respect to polarity and kinetics.