Ultrahigh Temporal Resolution Research Articles

Precision fMRI and cluster-failure in the individual brain.

Advances in neuroimaging acquisition protocols and denoising techniques, along with increasing magnetic field strengths, have dramatically improved the temporal signal-to-noise ratio (tSNR) in functional magnetic resonance imaging (fMRI). This permits spatial resolution with submillimeter voxel sizes and ultrahigh temporal resolution and opens a route toward performing precision fMRI in the brains of individuals. Yet ultrahigh spatial and temporal resolution comes at a cost: it reduces tSNR and, therefore, the sensitivity to the blood oxygen level-dependent (BOLD) effect and other functional contrasts across the brain. Here we investigate the potential of various smoothing filters to improve BOLD sensitivity while preserving the spatial accuracy of activated clusters in single-subject analysis. We introduce adaptive-weight smoothing with optimized metrics (AWSOM), which addresses this challenge extremely well. AWSOM employs a local inference approach that is as sensitive as cluster-corrected inference of data smoothed with large Gaussian kernels, but it preserves spatial details across multiple tSNR levels. This is essential for examining whole-brain fMRI data because tSNR varies across the entire brain, depending on the distance of a brain region from the receiver coil, the type of setup, acquisition protocol, preprocessing, and resolution. We found that cluster correction in single subjects results in inflated family-wise error and false positive rates. AWSOM effectively suppresses false positives while remaining sensitive even to small clusters of activated voxels. Furthermore, it preserves signal integrity, that is, the relative activation strength of significant voxels, making it a valuable asset for a wide range of fMRI applications. Here we demonstrate these features and make AWSOM freely available to the research community for download.

Acoustic phonon excitation in gold probed by time-resolved photoemission electron microscopy.

Electron-phonon coupling is an important energy transfer mechanism in solids after ultrafast laser excitation. In this study, we present an extreme ultraviolet (EUV) and infrared (IR) pump-probe photoemission experiment to investigate the electron-phonon coupling in nonequilibrium gold. The energy of IR-laser-emitted photoelectrons is shifted due to the EUV photoemission and oscillates with a ∼4THz frequency. Such oscillation is considered as the effective excitation of the longitudinal acoustic phonon mode in gold through the spectral-dependent electron-phonon coupling. Our study showcases the capability of time-resolved photoemission electron microscopy to monitor the non-equilibrium lattice vibrations with ultrahigh spatial and temporal resolution.

Identification of congenital aortic valve malformations in juvenile natriuretic peptide receptor 2-deficient mice using high-frequency ultrasound.

Mouse models of congenital aortic valve malformations are useful for studying disease pathobiology, but most models have incomplete penetrance [e.g., ∼2 to 77% prevalence of bicuspid aortic valves (BAVs) across multiple models]. For longitudinal studies of pathologies associated with BAVs and other congenital valve malformations, which manifest over months in mice, it is operationally inefficient, economically burdensome, and ethically challenging to enroll large numbers of mice in studies without first identifying those with valvular abnormalities. To address this need, we established and validated a novel in vivo high-frequency (30 MHz) ultrasound imaging protocol capable of detecting aortic valvular malformations in juvenile mice. Fifty natriuretic peptide receptor 2 heterozygous mice on a low-density lipoprotein receptor-deficient background (Npr2+/-;Ldlr-/-; 32 males and 18 females) were imaged at 4 and 8 wk of age. Fourteen percent of the Npr2+/-;Ldlr-/- mice exhibited features associated with aortic valve malformations, including 1) abnormal transaortic flow patterns on color Doppler (recirculation and regurgitation), 2) peak systolic flow velocities distal to the aortic valves reaching or surpassing ∼1,250 mm/s by pulsed-wave Doppler, and 3) putative fusion of cusps along commissures and abnormal movement elucidated by two-dimensional (2-D) imaging with ultrahigh temporal resolution. Valves with these features were confirmed by ex vivo gross anatomy and histological visualization to have thickened cusps, partial fusions, or Sievers type-0 bicuspid valves. This ultrasound imaging protocol will enable efficient, cost effective, and humane implementation of studies of congenital aortic valvular abnormalities and associated pathologies in a wide range of mouse models.NEW & NOTEWORTHY We developed a high-frequency ultrasound imaging protocol for diagnosing congenital aortic valve structural abnormalities in 4-wk-old mice. Our protocol defines specific criteria to distinguish mice with abnormal aortic valves from those with normal tricuspid valves using color Doppler, pulsed-wave Doppler, and two-dimensional (2-D) imaging with ultrahigh temporal resolution. This approach enables early identification of valvular abnormalities for efficient and ethical experimental design of longitudinal studies of congenital valve diseases and associated pathologies in mice.

Thermal imaging can reveal variation in stay-green functionality of wheat canopies under temperate conditions.

Canopy temperature (CT) is often interpreted as representing leaf activity traits such as photosynthetic rates, gas exchange rates, or stomatal conductance. This interpretation is based on the observation that leaf activity traits correlate with transpiration which affects leaf temperature. Accordingly, CT measurements may provide a basis for high throughput assessments of the productivity of wheat canopies during early grain filling, which would allow distinguishing functional from dysfunctional stay-green. However, whereas the usefulness of CT as a fast surrogate measure of sustained vigor under soil drying is well established, its potential to quantify leaf activity traits under high-yielding conditions is less clear. To better understand sensitivity limits of CT measurements under high yielding conditions, we generated within-genotype variability in stay-green functionality by means of differential short-term pre-anthesis canopy shading that modified the sink:source balance. We quantified the effects of these modifications on stay-green properties through a combination of gold standard physiological measurements of leaf activity and newly developed methods for organ-level senescence monitoring based on timeseries of high-resolution imagery and deep-learning-based semantic image segmentation. In parallel, we monitored CT by means of a pole-mounted thermal camera that delivered continuous, ultra-high temporal resolution CT data. Our results show that differences in stay-green functionality translate into measurable differences in CT in the absence of major confounding factors. Differences amounted to approximately 0.8°C and 1.5°C for a very high-yielding source-limited genotype, and a medium-yielding sink-limited genotype, respectively. The gradual nature of the effects of shading on CT during the stay-green phase underscore the importance of a high measurement frequency and a time-integrated analysis of CT, whilst modest effect sizes confirm the importance of restricting screenings to a limited range of morphological and phenological diversity.

Ultra-high temporal resolution images of a homogeneous electric field short air gap negative streamer at overvoltage and atmospheric pressure

Air gap discharge is one of the most basic scientific problems in the field of high-voltage engineering. The homogeneous electric field 1.5 mm air gap negative streamer at overvoltage and atmospheric pressure is observed by a high-speed 4-channel framing camera. The ultra-high temporal resolution images of a single negative stream are captured (the exposure time is 5 ns, and the inter-frame delay is no more than 0.1 ns). It is observed that the negative streamer formed in the middle of the air gap and grew bidirectionally towards both electrodes. At the same time, the electrical measurement is also carried out.

Transient Glimpses: Unveiling Occluded Backgrounds through the Spike Camera

The de-occlusion problem, involving extracting clear background images by removing foreground occlusions, holds significant practical importance but poses considerable challenges. Most current research predominantly focuses on generating discrete images from calibrated camera arrays, but this approach often struggles with dense occlusions and fast motions due to limited perspectives and motion blur. To overcome these limitations, an effective solution requires the integration of multi-view visual information. The spike camera, as an innovative neuromorphic sensor, shows promise with its ultra-high temporal resolution and dynamic range. In this study, we propose a novel approach that utilizes a single spike camera for continuous multi-view imaging to address occlusion removal. By rapidly moving the spike camera, we capture a dense stream of spikes from occluded scenes. Our model, SpkOccNet, processes these spikes by integrating multi-view spatial-temporal information via long-short-window feature extractor (LSW) and employs a novel cross-view mutual attention-based module (CVA) for effective fusion and refinement. Additionally, to facilitate research in occlusion removal, we introduce the S-OCC dataset, which consists of real-world spike-based data. Experimental results demonstrate the efficiency and generalization capabilities of our model in effectively removing dense occlusions across diverse scenes. Public project page: https://github.com/Leozhangjiyuan/SpikeDeOcclusion.

Dynamic X-ray imaging with screen-printed perovskite CMOS array.

High performance X-ray detector with ultra-high spatial and temporal resolution are crucial for biomedical imaging. This study reports a dynamic direct-conversion CMOS X-ray detector assembled with screen-printed CsPbBr3, whose mobility-lifetime product is 5.2 × 10-4 cm2 V-1 and X-ray sensitivity is 1.6 × 104 µC Gyair-1 cm-2. Samples larger than 5 cm[Formula: see text]10 cm can be rapidly imaged by scanning this detector at a speed of 300 frames per second along the vertical and horizontal directions. In comparison to traditional indirect-conversion CMOS X-ray detector, this perovskite CMOS detector offers high spatial resolution (5.0 lp mm-1) X-ray radiographic imaging capability at low radiation dose (260 nGy). Moreover, 3D tomographic images of a biological specimen are also successfully reconstructed. These results highlight the perovskite CMOS detector's potential in high-resolution, large-area, low-dose dynamic biomedical X-ray and CT imaging, as well as in non-destructive X-ray testing and security scanning.

Ultra-rapid, Free-breathing, Real-time Cardiac Cine MRI Using GRASP Amplified with View Sharing and KWIC Filtering.

Purpose To achieve ultra-high temporal resolution (approximately 20 msec) in free-breathing, real-time cardiac cine MRI using golden-angle radial sparse parallel (GRASP) reconstruction amplified with view sharing (VS) and k-space-weighted image contrast (KWIC) filtering. Materials and Methods Fourteen pediatric patients with congenital heart disease (mean age [SD], 9 years ± 2; 13 male) and 10 adult patients with arrhythmia (mean age, 62 years ± 8; nine male) who underwent both standard breath-hold cine and free-breathing real-time cine using GRASP were retrospectively identified. To achieve high temporal resolution, each time frame was reconstructed using six radial spokes, corresponding to acceleration factors ranging from 24 to 32. To compensate for loss in spatial resolution resulting from over-regularization in GRASP, VS and KWIC filtering were incorporated. The blur metric, visual image quality scores, and biventricular parameters were compared between clinical and real-time cine images. Results In pediatric patients, the incorporation of VS and KWIC into GRASP (ie, GRASP + VS + KWIC) produced significantly (P < .05) sharper x-y-t (blur metric: 0.36 ± 0.03, 0.41 ± 0.03, 0.48 ± 0.03, respectively) and x-y-f (blur metric: 0.28 ± 0.02, 0.31 ± 0.03, 0.37 ± 0.03, respectively) component images compared with GRASP + VS and conventional GRASP. Only the noise score differed significantly between GRASP + VS + KWIC and clinical cine; all visual scores were above the clinically acceptable (3.0) cutoff point. Biventricular volumetric parameters strongly correlated (R2 > 0.85) between clinical and real-time cine images reconstructed with GRASP + VS + KWIC and were in good agreement (relative error < 6% for all parameters). In adult patients, the visual scores of all categories were significantly lower (P < .05) for clinical cine compared with real-time cine with GRASP + VS + KWIC, except for noise (P = .08). Conclusion Incorporating VS and KWIC filtering into GRASP reconstruction enables ultra-high temporal resolution (approximately 20 msec) without significant loss in spatial resolution. Keywords: Cine, View Sharing, k-Space-weighted Image Contrast Filtering, Radial k-Space, Pediatrics, Arrhythmia, GRASP, Compressed Sensing, Real-Time, Free-Breathing Supplemental material is available for this article. © RSNA, 2024.

Indoor UWB Positioning and Position Tracking Data Set

Indoor positioning has become a hot topic in various fields, such as industry, healthcare, and commerce. Ultra-wideband (UWB) radio technology provides a cost-effective solution for range-based positioning, offering exceptionally high accuracy and precision. Its ultra-high temporal resolution enables range measurements with accuracy of a few centimeters. To develop and evaluate range-based positioning systems, we collected measurements in four different indoor environments using eight fixed devices and one mobile positioning device. To eliminate the fluctuation of walking speed from the data, we pre-defined a path in each indoor environment, similar to the human walking path, which was sampled at equidistant positions. We collected multiple range measurements and channel impulse response (CIR) data at each tag position on the path. The resulting dataset supports the development of range-based positioning and position tracking algorithms with various combinations of network topologies and anchor-tag combinations. We have also provided a full set of data analysis tools that enable the reproducibility of results and serve as a basis for further development of range-based UWB positioning algorithms.

A selection and targeting framework of cortical locations for line-scanning fMRI.

Depth-resolved functional magnetic resonance imaging (fMRI) is an emerging field growing in popularity given the potential of separating signals from different computational processes in cerebral cortex. Conventional acquisition schemes suffer from low spatial and temporal resolutions. Line-scanning methods allow depth-resolved fMRI by sacrificing spatial coverage to sample blood oxygenated level-dependent (BOLD) responses at ultra-high temporal and spatial resolution. For neuroscience applications, it is critical to be able to place the line accurately to (1) sample the right neural population and (2) target that neural population with tailored stimuli or tasks. To this end, we devised a multi-session framework where a target cortical location is selected based on anatomical and functional properties. The line is then positioned according to this information in a separate second session, and we tailor the experiment to focus on the target location. Anatomically, the precision of the line placement was confirmed by projecting a nominal representation of the acquired line back onto the surface. Functional estimates of neural selectivities in the line, as quantified by a visual population-receptive field model, resembled the target selectivities well for most subjects. This functional precision was quantified in detail by estimating the distance between the visual field location of the targeted vertex and the location in visual cortex (V1) that most closely resembled the line-scanning estimates; this distance was on average ~5.5 mm. Given the dimensions of the line, differences in acquisition, session, and stimulus design, this validates that line-scanning can be used to probe local neural sensitivities across sessions. In summary, we present an accurate framework for line-scanning MRI; we believe such a framework is required to harness the full potential of line-scanning and maximize its utility. Furthermore, this approach bridges canonical fMRI experiments with electrophysiological experiments, which in turn allows novel avenues for studying human physiology non-invasively.

Dissolved organic carbon export in a small, disturbed peat catchment: Insights from long‐term, high‐resolution, sensor‐based monitoring

AbstractUnderstanding dissolved organic carbon (DOC) export dynamics from carbon‐rich environments is critical. Peatlands act as terrestrial carbon stores, and consequently supply substantial amounts of DOC to drainage. This DOC flux is temporally heterogeneous and subject to long‐ and short‐term variability. Ultrahigh temporal resolution sampling (&lt; hourly) is still in‐frequent in peatland catchments. We used a field‐deployable —ultraviolet–visible light spectrometer (Spectro::lyser™) and monitored DOC flux from a temperate peatland over 31 months to examine seasonal and event dynamics. DOC concentration varied from 6.8 to 63.5 mg L−1, in the higher reported range for peatlands and showed clear seasonal (high‐summer, low‐winter) variability coinciding with elevated biological productivity in the peatland. Discharge was an unreliable predictor of instantaneous DOC concentration overall, with antecedent water temperatures proving the most reliable predictor overall. Discharge drove total DOC export in the catchment, where the top 10% of flow events, accounted for 41.3% of all DOC exported—increasing to 84.6% in the top 50% of flow events. Total estimated catchment DOC flux was sensitive to measurement frequency: increasing from every 30 min to daily altered export estimates by &lt; 1%, increasing to &gt; 10% at 1‐week intervals. The variation in estimated flux increased approximately linearly with reduced sampling frequency, reaching &gt; 40% at monthly intervals. High‐resolution data reveal the large amount of within‐site complexity of DOC export dynamics in a temperate peatland and provide evidence on the subsequently recommended sampling frequency for the future elucidation of detailed DOC budgets in these environments.

Asynchronous Event-Based Corner Detection Using Adaptive Time Threshold

Event cameras are novel neuromorphic vision sensors with ultrahigh temporal resolution and low latency, both in the order of microseconds. Instead of image frames, event cameras generate an asynchronous event stream of per-pixel intensity changes with precise timestamps. The resulting sparse data structure impedes applying many conventional computer vision techniques to event streams, and specific algorithms should be designed to leverage the information provided by event cameras. In our work, a motion-and scene-adaptive time threshold for event data is proposed. As a parameter describing the global characteristic of the event stream, this time threshold can be used for low-level visual tasks such as event denoising and feature extraction. Based on this threshold, the normalization method for the surface of active events (SAE) is explored from a new perspective. Differently from the previous speed invariant time surface, this normalized SAE is constructed by adaptive exponential decay (AED-SAE) and can be directly applied to the event-based Harris corner detector. The proposed corner detector is evaluated on real and synthetic datasets with different resolutions. The proposed algorithm exhibits higher accuracy than congeneric algorithms and maintains high computational efficiency on datasets with different resolutions and texture levels.

The Ocean Surface Current in the East China Sea Computed by the Geostationary Ocean Color Imager Satellite

High-frequency observations of surface current field data over large areas and long time series are imperative for comprehending sea-air interaction and ocean dynamics. Nonetheless, neither in situ observations nor polar-orbiting satellites can fulfill the requirements necessary for such observations. In recent years, geostationary satellite data with ultra-high temporal resolution have been increasingly utilized for the computation of surface flow fields. In this paper, the surface flow field in the East China Sea is estimated using maximum cross-correlation, which is the most widely used flow field computation algorithm, based on the total suspended solids (TSS) data acquired from the Geostationary Ocean Color Imager satellite. The inversion results were compared with the modeled tidal current data and the measured tidal elevation data for verification. The results of the verification demonstrated that the mean deviation of the long semiaxis of the tidal ellipse of the inverted M2 tide is 0.0335 m/s, the mean deviation of the short semiaxis is 0.0276 m/s, and the mean deviation of the tilt angle is 6.89°. Moreover, the spatially averaged flow velocity corresponds with the observed pattern of tidal elevation changes, thus showcasing the field’s significant reliability. Afterward, we calculated the sea surface current fields in the East China Sea for the years 2013 to 2019 and created distribution maps for both climatology and seasonality. The resulting current charts provide an intuitive display of the spatial structure and seasonal variations in the East China Sea circulation. Lastly, we performed a diagnostic analysis on the surface TSS variation mechanism in the frontal zone along the Zhejiang coast, utilizing inverted flow data collected on 3 August 2013, which had a high spatial coverage and complete time series. Our analysis revealed that the intraday variation in TSS in the local surface layer was primarily influenced by tide-induced vertical mixing. The research findings of this article not only provide valuable data support for the study of local ocean dynamics but also verify the reliability of short-period surface flow inversion of high-turbidity waters near the coast using geostationary satellites.

Single-shot ultrafast terahertz photography

Multidimensional imaging of transient events has proven pivotal in unveiling many fundamental mechanisms in physics, chemistry, and biology. In particular, real-time imaging modalities with ultrahigh temporal resolutions are required for capturing ultrashort events on picosecond timescales. Despite recent approaches witnessing a dramatic boost in high-speed photography, current single-shot ultrafast imaging schemes operate only at conventional optical wavelengths, being suitable solely within an optically-transparent framework. Here, leveraging on the unique penetration capability of terahertz radiation, we demonstrate a single-shot ultrafast terahertz photography system that can capture multiple frames of a complex ultrafast scene in non-transparent media with sub-picosecond temporal resolution. By multiplexing an optical probe beam in both the time and spatial-frequency domains, we encode the terahertz-captured three-dimensional dynamics into distinct spatial-frequency regions of a superimposed optical image, which is then computationally decoded and reconstructed. Our approach opens up the investigation of non-repeatable or destructive events that occur in optically-opaque scenarios.

Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning

Single-shot coherent diffraction imaging of isolated nanosized particles has seen remarkable success in recent years, yielding in-situ measurements with ultra-high spatial and temporal resolution. The progress of high-repetition-rate sources for intense X-ray pulses has further enabled recording datasets containing millions of diffraction images, which are needed for the structure determination of specimens with greater structural variety and dynamic experiments. The size of the datasets, however, represents a monumental problem for their analysis. Here, we present an automatized approach for finding semantic similarities in coherent diffraction images without relying on human expert labeling. By introducing the concept of projection learning, we extend self-supervised contrastive learning to the context of coherent diffraction imaging and achieve a dimensionality reduction producing semantically meaningful embeddings that align with physical intuition. The method yields substantial improvements compared to previous approaches, paving the way toward real-time and large-scale analysis of coherent diffraction experiments at X-ray free-electron lasers.

Single-exonuclease nanocircuits reveal the RNA degradation dynamics of PNPase and demonstrate potential for RNA sequencing

The degradation process of RNA is decisive in guaranteeing high-fidelity translation of genetic information in living organisms. However, visualizing the single-base degradation process in real time and deciphering the degradation mechanism at the single-enzyme level remain formidable challenges. Here, we present a reliable in-situ single-PNPase-molecule dynamic electrical detector based on silicon nanowire field-effect transistors with ultra-high temporal resolution. These devices are capable of realizing real-time and label-free monitoring of RNA analog degradation with single-base resolution, including RNA analog binding, single-nucleotide hydrolysis, and single-base movement. We discover a binding event of the enzyme (near the active site) with the nucleoside, offering a further understanding of the RNA degradation mechanism. Relying on systematic analyses of independent reads, approximately 80% accuracy in RNA nucleoside sequencing is achieved in a single testing process. This proof-of-concept sets up a Complementary Metal Oxide Semiconductor (CMOS)-compatible playground for the development of high-throughput detection technologies toward mechanistic exploration and single-molecule sequencing.

Research progress of ultra-high spatiotemporally resolved microscopy

High-resolution microscopy has opened the door to the exploration of the micro-world, while femtosecond laser has provided a measurement method for detecting ultrafast physical/chemical phenomena. Combination of these two techniques can produce new microscopic techniques with both ultra-high spatial resolution and ultra-fast temporal resolution, and thus has great importance in exploring new scientific phenomena and mechanisms on an extremely small spatial scale and temporal scale. This paper reviews the basic principles and properties of main microscopic techniques with ultra-high temporal resolution and spatial resolution, and introduces the latest research progress of their applications in various fields such as characterizing optoelectronic materials and devices, monitoring femtosecond laser micromachining, and detecting surface plasmon excitation dynamics. In order to conduct these researches systematically, we group these techniques based on time dimension and space dimension, including the near-field multi-pulse imaging techniques, the far-field multi-pulse imaging techniques, and the far-field single-pulse imaging techniques. In Section 2, we introduce the principles and characteristics of the ultra-high spatiotemporally resolved microscopic techniques. The near-field multi-pulse spatiotemporally microscopic techniques based on nano-probe are described in Subsection 2.1, in which is shown the combination of common near-field imaging techniques such as atomic force microscopy (AFM), near-field scanning optical microscopy (NSOM), scanning tunneling microscope (STM), and the ultra-fast temporal detection of pump-probe technique. In Subsection 2.2, we introduce the far-field multi-pulse spatiotemporal microscopic techniques. In contrast to near-field cases, the far-field spatiotemporal microscopic techniques have lower spatial resolution but possess more advantages of being non-invasive and non-contact, wider field of view, and faster imaging speed. In Subsection 2.3 we introduce the far-field single-pulse spatiotemporal microscopic techniques, in which is used a single ultrafast light pulse to capture dynamic processes at different moments in time, thereby enabling real-time imaging of ultrafast phenomena. In Section 3 , the advances in the application of the ultra-high spatiotemporal resolved microscopic techniques are introduced in many frontier areas, including the monitoring of femtosecond laser micromachining in Subsection 3.1, the detection of optoelectronic materials/devices in Subsection 3.2, and the characterization of surface plasmon dynamics in Subsection 3.3. Finally, in Section 4, we summarize the features of all above-mentioned spatiotemporal microscopic techniques in a table, including the spatial resolution and temporal resolution, advantages and disadvantages of each technique, and we also provide an outlook on future development trend in this research field. Looking forward to the future, ultra-high spatiotemporally resolved microscopy will develop rapidly toward the goal of "smaller, faster, smarter and more extensive". Its development not only promotes the research of the microscopy technology, but also provides a powerful tool for various practical applications such as precision machining, two-dimensional material dynamics, optoelectronic device design and characterization.

Ultra-High Temporal Resolution Visual Reconstruction From a Fovea-Like Spike Camera via Spiking Neuron Model.

Neuromorphic vision sensor is a new bio-inspired imaging paradigm emerged in recent years. It uses the asynchronous spike signals instead of the traditional frame-based manner to achieve ultra-high speed sampling. Unlike the dynamic vision sensor (DVS) that perceives movement by imitating the retinal periphery, the spike camera was developed recently to perceive fine textures by simulating a small retinal region called the fovea. For this new type of neuromorphic camera, how to reconstruct ultra-high speed visual images from spike data becomes an important yet challenging issue in visual scene perception, analysis, and recognition applications. In this paper, a bio-inspired visual reconstruction framework for the spike camera is proposed for the first time. Its core idea is to use the biologically inspired adaptive adjustment mechanisms, combined with the spatiotemporal spike information extracted by the proposed model, to reconstruct the full texture of natural scenes in an ultra-high temporal resolution. Specifically, the proposed model consists of a motion local excitation layer, a spike refining layer and a visual reconstruction layer motivated by the bio-realistic leaky integrate-and-fire (LIF) neurons and synapse connection with spike-timing dependent plasticity (STDP) rule. To evaluate the performance, a spike dataset was constructed for normal and high-speed scenes in real-world recorded by the spike camera. The experimental results show that the proposed approach can reconstruct the visual images with 40,000 frames per second in both normal and high-speed scenes, while achieving high dynamic range and high image quality.

Direct observations of energy transfer from resonant electrons to whistler-mode waves in magnetosheath of Earth

Electromagnetic whistler-mode waves in space plasmas play critical roles in collisionless energy transfer between the electrons and the electromagnetic field. Although resonant interactions have been considered as the likely generation process of the waves, observational identification has been extremely difficult due to the short time scale of resonant electron dynamics. Here we show strong nongyrotropy, which rotate with the wave, of cyclotron resonant electrons as direct evidence for the locally ongoing secular energy transfer from the resonant electrons to the whistler-mode waves using ultra-high temporal resolution data obtained by NASA’s Magnetospheric Multiscale (MMS) mission in the magnetosheath. The nongyrotropic electrons carry a resonant current, which is the energy source of the wave as predicted by the nonlinear wave growth theory. This result proves the nonlinear wave growth theory, and furthermore demonstrates that the degree of nongyrotropy, which cannot be predicted even by that nonlinear theory, can be studied by observations.

Motion correction and its impact on quantification in dynamic total-body 18F-fluorodeoxyglucose PET

BackgroundThe total-body positron emission tomography (PET) scanner provides an unprecedented opportunity to scan the whole body simultaneously, thanks to its long axial field of view and ultrahigh temporal resolution. To fully utilize this potential in clinical settings, a dynamic scan would be necessary to obtain the desired kinetic information from scan data. However, in a long dynamic acquisition, patient movement can degrade image quality and quantification accuracy.MethodsIn this work, we demonstrated a motion correction framework and its importance in dynamic total-body FDG PET imaging. Dynamic FDG scans from 12 subjects acquired on a uEXPLORER PET/CT were included. In these subjects, 7 are healthy subjects and 5 are those with tumors in the thorax and abdomen. All scans were contaminated by motion to some degree, and for each the list-mode data were reconstructed into 1-min frames. The dynamic frames were aligned to a reference position by sequentially registering each frame to its previous neighboring frame. We parametrized the motion fields in-between frames as diffeomorphism, which can map the shape change of the object smoothly and continuously in time and space. Diffeomorphic representations of motion fields were derived by registering neighboring frames using large deformation diffeomorphic metric matching. When all pairwise registrations were completed, the motion field at each frame was obtained by concatenating the successive motion fields and transforming that frame into the reference position. The proposed correction method was labeled SyN-seq. The method that was performed similarly, but aligned each frame to a designated middle frame, was labeled as SyN-mid. Instead of SyN, the method that performed the sequential affine registration was labeled as Aff-seq. The original uncorrected images were labeled as NMC. Qualitative and quantitative analyses were performed to compare the performance of the proposed method with that of other correction methods and uncorrected images.ResultsThe results indicated that visual improvement was achieved after correction of the SUV images for the motion present period, especially in the brain and abdomen. For subjects with tumors, the average improvement in tumor SUVmean was 5.35 ± 4.92% (P = 0.047), with a maximum improvement of 12.89%. An overall quality improvement in quantitative Ki images was also observed after correction; however, such improvement was less obvious in K1 images. Sampled time–activity curves in the cerebral and kidney cortex were less affected by the motion after applying the proposed correction. Mutual information and dice coefficient relative to the reference also demonstrated that SyN-seq improved the alignment between frames over non-corrected images (P = 0.003 and P = 0.011). Moreover, the proposed correction successfully reduced the inter-subject variability in Ki quantifications (11.8% lower in sampled organs). Subjective assessment by experienced radiologists demonstrated consistent results for both SUV images and Ki images.ConclusionTo conclude, motion correction is important for image quality in dynamic total-body PET imaging. We demonstrated a correction framework that can effectively reduce the effect of random body movements on dynamic images and their associated quantification. The proposed correction framework can potentially benefit applications that require total-body assessment, such as imaging the brain-gut axis and systemic diseases.