Temporal Properties Research Articles

High-resolution Cell Transplantation in Embryonic and Larval Zebrafish.

Development and regeneration occur by a process of genetically encoded spatiotemporally dynamic cellular interactions. The use of cell transplantation between animals to track cell fate and to induce mismatches in the genetic, spatial, or temporal properties of donor and host cells is a powerful means of examining the nature of these interactions. Organisms such as chick and amphibians have made crucial contributions to our understanding of development and regeneration, respectively, in large part because of their amenability to transplantation. The power of these models, however, has been limited by low genetic tractability. Likewise, the major genetic model organisms have lower amenability to transplantation. The zebrafish is a major genetic model for development and regeneration, and while cell transplantation is common in zebrafish, it is generally limited to the transfer of undifferentiated cells at the early blastula and gastrula stages of development. In this article, we present a simple and robust method that extends the zebrafish transplantation window to any embryonic or larval stage between at least 1 and 7 days post fertilization. The precision of this approach allows for the transplantation of as little as one cell with near-perfect spatial and temporal resolution in both donor and host animals. While we highlight here the transplantation of embryonic and larval neurons for the study of nerve development and regeneration, respectively, this approach is applicable to a wide range of progenitor and differentiated cell types and research questions.

Abnormal static and dynamic brain network connectivity associated with chronic tinnitus

In order to comprehensively understand the changes of brain networks in patients with chronic tinnitus, this study combined static and dynamic analysis methods to explore the abnormalities of brain networks. Thirty-two patients with chronic tinnitus and 30 age-, sex- and education-matched healthy controls (HC) were recruited. Independent component analysis was used to identify resting-state networks (RSNs). Static and dynamic functional network connectivity (FNC) were performed. The temporal properties of brain network including mean dwell time (MDT), fraction time (FT) and numbers of transitions (NT) were calculated. Two-sample t test and Spearman’s correlation were used for group compares and correlation analysis. Four RSNs showed abnormal FNC including auditory network (AUN), default mode network (DMN), attention network (AN) and sensorimotor network (SMN). For static analysis, tinnitus patients showed significantly decreased FNC in AUN-DMN, AUN-AN, DMN-AN, and DMN-SMN than HC [p < 0.05, false discovery rate (FDR) corrected]. For dynamic analysis, tinnitus patients showed significantly decreased FNC in DMN-AN in state 3 (p < 0.05, FDR corrected). MDT in state 3 was significantly decreased in tinnitus patients (t = 2.039, P = 0.046). In the tinnitus group, the score of tinnitus functional index (TFI) was negatively correlated with MDT and FT in state 4, and the duration of tinnitus was positively correlated with FT in state 1 and NT. Chronic tinnitus causes abnormal brain network connectivity. These abnormal brain networks help to clarify the mechanism of tinnitus generation and chronicity, and provide a potential basis for the treatment of tinnitus.

GRB 180128A: A second magnetar giant flare candidate from the Sculptor Galaxy

Magnetars are slowly rotating neutron stars that possess the strongest magnetic fields known in the cosmos (1014 − 1015 G). They display a range of transient high-energy electromagnetic activity. The brightest and most energetic of these events are the gamma-ray bursts (GRBs) known as magnetar giant flares (MGFs), with isotropic energies Eiso ≈ 1044 − 1046 erg. Only seven MGF detections have been made to date: three unambiguous events occurred in our Galaxy and the Magellanic Clouds, and the other four MGF candidates are associated with nearby star-forming galaxies. As all seven identified MGFs are bright at Earth, additional weaker events likely remain unidentified in archival data. We conducted a search of the Fermi Gamma-ray Burst Monitor database for candidate extragalactic MGFs and, when possible, collected localization data from the Interplanetary Network (IPN) satellites. Our search yielded one convincing event, GRB 180128A. IPN localizes this burst within NGC 253, commonly known as the Sculptor Galaxy. The event is the second MGF in modern astronomy to be associated with this galaxy and the first time two bursts have been associated with a single galaxy outside our own. Here we detail the archival search criteria that uncovered this event and its spectral and temporal properties, which are consistent with expectations for a MGF. We also discuss the theoretical implications and finer burst structures resolved from various binning methods. Our analysis provides observational evidence of an eighth identified MGF.

The Peculiar Precursor of a Gamma-Ray Burst from a Binary Merger Involving a Magnetar

The milestone discovery of GW170817-GRB 170817A-AT 2017gfo has shown that gravitational waves (GWs) could be produced during the merger of a neutron star–neutron star/black hole and that in electromagnetic (EM) waves, a gamma-ray burst (GRB) and a kilonova (KN) are generated in sequence after the merger. Observationally, however, EM properties before the merger phase are still unclear. Here we report a peculiar precursor in a KN-associated long-duration GRB 211211A, providing evidence of the EM before the merger. This precursor lasts ∼0.2 s, and the waiting time between the precursor and the main burst is ∼1 s, comparable to that between GW170817 and GRB 170817A. The spectrum of the precursor could be well fit with a nonthermal cutoff power-law model instead of a blackbody. In particular, a ∼22 Hz quasiperiodic oscillation candidate (∼3σ) is detected in the precursor. These temporal and spectral properties indicate that this precursor is probably produced by a catastrophic flare accompanied with magnetoelastic or crustal oscillations of a magnetar in a binary compact merger. The strong magnetic field of the magnetar can also account for the prolonged duration of GRB 211211A. However, it poses a challenge to reconcile the rather short lifetime of a magnetar with the rather long spiraling time of a binary neutron star system only by the GW radiation before the merger.

Formation kinetics and thermodynamic stability of the Aurivillius compounds in Bi4Ti3O12–BiFeO3 system

AbstractThe Aurivillius compounds in the Bi2O3–Fe2O3–TiO2 system, combining ferroelectric, semiconducting, and ferromagnetic properties, have attracted particular interest. Formation kinetics and thermodynamic stability are the fundamental knowledge needed for modeling and predicting the temporal microstructure and property evolution during materials processing but have not yet been addressed by quantitative experimental measurement. This article focuses on the Bin+1Fen–3Ti3O3n+3 Aurivillius compounds on the Bi4Ti3O12–BiFeO3 tie‐line to elucidate the mechanisms and thermodynamic controls responsible for phase formation of compounds with various perovskite‐like layers. Five high‐purity Aurivillius compounds Bi4Ti3O12, Bi5FeTi3O15, Bi6Fe2Ti3O18, Bi7Fe3Ti3O21, and Bi8Fe4Ti3O24 with integer n = 3–7 values were synthesized and their phase transformation properties and enthalpies of formation were studied by X‐ray diffraction in situ, high temperature differential scanning calorimetry, and high temperature oxide melt solution calorimetry. Thermodynamic stability of the compounds decreases with increasing n, and formation kinetics gradually slow down, demonstrating the inherent difficulty to synthesize pure Aurivillius compounds with n larger than 8. This difficulty was confirmed by an impurity phase coexisting with Bi9Fe5Ti3O27.

GRB 231115A: A Nearby Magnetar Giant Flare or a Cosmic Short Gamma-Ray Burst?

There are two classes of gamma-ray transients with a duration shorter than 2 s. One consists of cosmic short gamma-ray bursts (GRBs) taking place in the deep Universe via the neutron star mergers, and the other is the magnetar giant flares (GFs) with energies of ∼1044 − 1046 erg from “nearby” galaxies. Though the magnetar GFs and the short GRBs have rather similar temporal and spectral properties, their energies (E γ,iso) are different by quite a few orders of magnitude and hence can be distinguished supposing the host galaxies have been robustly identified. The newly observed GRB 231115A has been widely discussed as a new GF event for its high probability of being associated with M82. Here we conduct a detailed analysis of its prompt emission observed by Fermi-GBM and compare the parameters with existing observations. The prompt gamma-ray emission properties of GRB 231115A, if associated with M82, nicely follow the E p,z–E γ,iso relation of the GFs, where E p,z is the peak energy of the gamma-ray spectrum after the redshift (z) correction. To be a short GRB, the redshift needs to be ∼1. Though such a chance is low, the available X-ray/GeV observation upper limits are not stringent enough to further rule out this possibility. We have also discussed the prospect of convincingly establishing the magnetar origin of GRB 231115A-like events in the future.

H.E.S.S. observations of the 2021 periastron passage of PSR B1259-63/LS 2883

PSR B1259–63/LS 2883 is a gamma-ray binary system that hosts a pulsar in an eccentric orbit, with a 3.4 yr period, around an O9.5Ve star (LS 2883). At orbital phases close to periastron passages, the system radiates bright and variable non-thermal emission, for which the temporal and spectral properties of this emission are, for now, poorly understood. In this regard, very high-energy (VHE) emission is especially useful to study and constrain radiation processes and particle acceleration in the system. We report on an extensive VHE observation campaign conducted with the High Energy Stereoscopic System, comprised of approximately 100 h of data taken over five months, from tp − 24 days to tp + 127 days around the system’s 2021 periastron passage (where tp is the time of periastron). We also present the timing and spectral analyses of the source. The VHE light curve in 2021 is consistent overall with the stacked light curve of all previous observations. Within the light curve, we report a VHE maximum at times coincident with the third X-ray peak first detected in the 2021 X-ray light curve. In the light curve – although sparsely sampled in this time period – we see no VHE enhancement during the second disc crossing. In addition, we see no correspondence to the 2021 GeV flare in the VHE light curve. The VHE spectrum obtained from the analysis of the 2021 dataset is best described by a power law of spectral index Γ = 2.65 ± 0.04stat ± 0.04sys, a value consistent with the spectral index obtained from the analysis of data collected with H.E.S.S. during the previous observations of the source. We report spectral variability with a difference of ΔΓ = 0.56 ± 0.18stat ± 0.10sys at 95% confidence intervals, between sub-periods of the 2021 dataset. We also detail our investigation into X-ray/TeV and GeV/TeV flux correlations in the 2021 periastron passage. We find a linear correlation between contemporaneous flux values of X-ray and TeV datasets, detected mainly after tp + 25 days, suggesting a change in the available energy for non-thermal radiation processes. We detect no significant correlation between GeV and TeV flux points, within the uncertainties of the measurements, from ∼tp − 23 days to ∼tp + 126 days. This suggests that the GeV and TeV emission originate from different electron populations.

The primate cortical LFP exhibits multiple spectral and temporal gradients and widespread task dependence during visual short-term memory.

Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3 and 80 Hz that differ between the two monkeys. The LFP power in each band, as well as the sample entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in cortical pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task-dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread, and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.NEW & NOTEWORTHY We recorded extracellular electrophysiological signals from roughly the breadth and depth of a cortical hemisphere in nonhuman primates (NHPs) performing a visual memory task. Analyses of the band-limited local field potential (LFP) power displayed widespread, frequency-dependent cortical gradients in spectral power. Using a machine learning classifier, these features allowed robust cortical area decoding. Further task dependence in LFP power were found to be widespread, indicating large-scale gradients of LFP activity, and task-related activity.

THz Generation by Two-Color Plasma: Time Shaping and Ultra-Broadband Polarimetry.

The generation of terahertz radiation via laser-induced plasma from two-color femtosecond pulses in air has been extensively studied due to its broad emission spectrum and significant pulse energy. However, precise control over the temporal properties of these ultra-broadband terahertz pulses, as well as the measurement of their polarization state, remain challenging. In this study, we review our latest findings on these topics and present additional results not previously reported in our earlier works. First, we investigate the impact of chirping on the fundamental wave and the effect of manipulating the phase difference between the fundamental wave and the second-harmonic wave on the properties of generated terahertz pulses. We demonstrate that we can tune the time shape of terahertz pulses, causing them to reverse polarity or become bipolar by carefully selecting the correct combination of chirp and phase. Additionally, we introduce a novel technique for polarization characterization, termed terahertz unipolar polarimetry, which utilizes a weak probe beam and avoids the systematic errors associated with traditional methods. This technique is effective for detecting polarization-structured terahertz beams and the longitudinal component of focused terahertz beams. Our findings contribute to the improved control and characterization of terahertz radiation, enhancing its application in fields such as nonlinear optics, spectroscopy, and microscopy.

Topic modelling for spatial insights: Uncovering space use from movement data

We present a novel approach to understanding space use by moving entities based on repeated patterns of place visits and transitions. Our approach represents trajectories as text documents consisting of sequences of place visits or transitions and applies topic modelling to the corpus of these documents. The resulting topics represent combinations of places or transitions, respectively, that repeatedly co-occur in trips. Visualisation of the results in the spatial context reveals the regions of place connectivity through movements and the major channels used to traverse the space. This enables understanding of the use of space as a medium for movement. We compare the possibilities provided by topic modelling to alternative approaches exploiting a numeric measure of pairwise connectedness. We have extensively explored the potential of utilising topic modelling by applying our approach to multiple real-world movement data sets with different data collection procedures and varying spatial and temporal properties: GPS road traffic of cars, unconstrained movement on a football pitch, and episodic movement data reflecting social media posting events. The approach successfully demonstrated the ability to uncover meaningful patterns and interesting insights. We thoroughly discuss different aspects of the approach and share the knowledge and experience we have gained with people who might be potentially interested in analysing movement data by means of topic modelling methods.

Fermi GBM Observations of the Galactic Magnetar SGR 1935+2154 during Its 2022 January Activity

The X-ray and radio burst-emitting soft gamma-ray repeater SGR 1935+2154 has been the most active magnetar during the past decade, with at least one active episode each year since 2019. We report on the 2022 January activity as observed by the Fermi Gamma-Ray Burst Monitor and present the temporal and time-integrated spectral properties of the observed 112 X-ray bursts. No radio bursts were reported during the activity. The mean burst duration is comparable to most of the previous activities but is shorter than that of 2020, during which the magnetar emitted radio bursts. The mean burst spectrum is softer than the earlier activities and a long-term softening trend since 2016 is evident and is accompanied by a rise in the mean burst fluence and blackbody emission radii. The power-law indices of the RBB2−kTBB correlation also show an evolution during 2019–2022, where the soft component started becoming steeper, whereas the hard component shows a less steep trend. The burst properties show no significant evolution within the activity, which lasted for ∼ 45 days, and none of the observed bursts showed properties reminiscent of those of the hard, long X-ray counterpart to the 2020 fast radio burst FRB 200428 from the source. We discuss the results comparatively with the 8 yr history of the source since its discovery in 2014.

Assessing dynamic congestion risks of flood-disrupted transportation network systems through time-variant topological analysis and traffic demand dynamics

Amid escalating climate change and extreme weather events, urban road networks face increasingly severe flood risks. Current congestion risk analyses on transportation systems, largely grounded in static network characteristics, fall short of capturing the dynamic impacts of evolving flood events on network topology. A notable gap in integrating dynamic flood models with detailed temporal network property measurements impedes a deep understanding of the cascading mechanisms of traffic disruptions caused by floods. The research introduces an innovative framework for assessing dynamic congestion risks within transportation networks under flooding conditions. This framework comprises four distinct layers. The Data and Context layer collates and contextualizes primary data, encompassing road networks, commuter behaviour patterns and hydrological risks. This layer establishes a baseline for understanding the structure of the transportation system and its environmental vulnerabilities. The Computation layer focuses on calculating context-based betweenness centrality values to capture the importance of road segments within the network, setting a static indicator. Concurrently, this layer examines the dynamic exposure flag under flood conditions, providing a dynamic indicator that accounts for the fluctuating susceptibility of road networks to flooding. The Integration layer bridges the topological analysis and the functional performance of the transportation system. It creates a dynamic series that describes the topological properties of the network, reflecting its vulnerability to disruptions. Simultaneously, the time-variant traffic demand series are tracked to capture the system’s operational response to flood-induced conditions. Finally, the Evaluation layer synthesizes data and analyses from the previous modules. This synthesis involves a novel dual assessment: generating a time-variant vulnerability index series and evaluating the time-variant congestion risk map on the transportation system under flooding. The London case study is developed based on this proposed framework to identify critical areas of congestion risks. This study offers valuable data-driven insights for urban planning and disaster management, aiding policymakers, planners and emergency teams to enhance urban resilience against flood-induced transport disruptions.

A Comparative Analysis of Two Peculiar Gamma-Ray Bursts: GRB 230307A and GRB 211211A

GRB 211211A is a peculiar long gamma-ray burst (GRB) with very high brightness and short burst properties. Its full light curve consists of three emission episodes, i.e., a precursor, a main burst, and an extended emission. We find that a recently detected long-duration GRB 230307A also includes the three consistent emission episodes. Furthermore, the two bursts have similar redshifts, 0.076 and 0.065, respectively. We perform a detailed temporal and spectral analysis of the two GRBs to compare their temporal and spectral properties. Our analysis shows that the two bursts share great similarities for both the whole emission and the three corresponding emission phases, which are listed as follows: (1) they have near zero spectral lag; (2) they have very short minimum variability timescale (MVT); (3) they lie in the same region of in the MVT–T 90, Amati relation and hardness–T 90 planes; (4) the three phases are quasi-thermal spectra; (5) both the peak energy and the low-energy index track the flux; (6) the time-resolved spectra are much wider than those of the blackbody predicted by the model; (7) there are strong correlations between thermal flux and total flux and the correlation coefficients, and the slopes for the corresponding stages are very consistent; and (8) the photosphere emission properties are very consistent. Other investigations and observations suggest that the two GRBs indeed belong to a short burst with a compact star merger origin. Therefore, we think that GRB 230307A and GRB 211211A are rare and similar GRBs, and the photospheric radiation can interpret their radiation mechanisms.

Specification and Verification of Multi-Clock Systems Using a Temporal Logic with Clock Constraints

The polychronous or multi-clock paradigm is adequate to model large distributed systems where achieving a full timed synchronization is not only very costly but also often not necessary. It concerns systems made of a set of components with loose synchronization constraints. We study an approach where those components are orchestrated using logical clocks , made popular by L. Lamport and synchronous languages. The temporal and causal specification of those systems is built by defining a set of clock relations that would constrain the instant when clocks can tick or must not tick, thus defining families of valid schedules . In this article, we propose a specification language, called \(\mathit {LTL}_c/\mathit {CCSL}\) , for specifying temporal properties of multi-clock systems. While traditional temporal logics (LTL, MTL, CTL*), whether linear or branching, rely on a global step, our language, \(\mathit {LTL}_c/\mathit {CCSL}\) , builds a partial order on logical clocks, thus allowing both a hierarchical approach based on refinement of clock hierarchies and compositionality, as what happens in one clock domain may remain largely independent of what may happen in other domains. This good property helps preserve the properties without requiring to perform the proofs again. An \(\mathit {LTL}_c/\mathit {CCSL}\) specification consists of a clock temporal logic \(\mathit {LTL}_c\) , accompanied by a clock calculus called CCSL for specifying clock relations. We build the syntax and semantics of \(\mathit {LTL}_c\) and link its semantics with CCSL. After that, we mainly focus on the verification aspect of \(\mathit {LTL}_c/\mathit {CCSL}\) specifications using a model checking technique. We show how \(\mathit {LTL}_c/\mathit {CCSL}\) can be used for specifying multi-clock systems with an example.

ConvLSNet: A lightweight architecture based on ConvLSTM model for the classification of pulmonary conditions using multichannel lung sound recordings

Characterization of lung sounds (LS) is indispensable for diagnosing respiratory pathology. Although conventional neural networks (NNs) have been widely employed for the automatic diagnosis of lung sounds, deep neural networks can potentially be more useful than conventional NNs by allowing accurate classification without requiring preprocessing and feature extraction. Utilizing the long short-term memory (LSTM) layers to reveal the sequence-based properties of the LS time series, a novel architecture consisting of a cascade of convolutional long short-term memory (ConvLSTM) and LSTM layers, namely ConvLSNet is developed, which permits highly accurate diagnosis of pulmonary disease states. By modeling the multichannel lung sounds through the ConvLSTM layer, the proposed ConvLSNet architecture can concurrently deal with the spatial and temporal properties of the six-channel LS recordings without heavy preprocessing or data transformation. Notably, the proposed model achieves a classification accuracy of 97.4 % based on LS data corresponding to three pulmonary conditions, namely asthma, COPD, and the healthy state. Compared with architectures consisting exclusively of CNN or LSTM layers, as well as those employing a cascade integration of 2DCNN and LSTM layers, the proposed ConvLSNet architecture exhibited the highest classification accuracy, while imposing the lowest computational cost as quantified by the number of parameters, training time, and learning rate.

Transfer learning-based updating method of transient stability assessment model

An updating method for data-driven based transient stability assessment model of power systems is proposed in this paper. To cope with potential faults in the real-time operation of power systems, the parameters of models can be modified online through the proposed method. Firstly, according to the long-short term memory (LSTM) network, transient stability assessment models are initially trained offline by expected faults. Then, the feature distribution differences between expected faults and potential faults are evaluated by the time-sequence maximum mean discrepancy (TMMD). Compared with the traditional maximum mean discrepancy (MMD), the proposed TMMD approach takes the temporal properties of transient stability into account, which can reflect the relationship between fault samples and time series better. Finally, the parameters of models are adjusted by transfer learning to reduce the feature distribution differences, by which the updated models can be more suitable for the different but related potential faults. Therefore, through the proposed model updating method, the extensibility of evaluation models is greatly enhanced, which is more in line with the practical conditions of power systems. In this paper, the effectiveness of the proposed method has been demonstrated by the evaluation results in the IEEE 39-bus system and a realistic power system.

Frontal Cortex Hyperactivation and Gamma Desynchrony in Fragile X Syndrome: Correlates of Auditory Hypersensitivity.

Fragile X syndrome (FXS) is an X-linked disorder that often leads to intellectual disability, anxiety, and sensory hypersensitivity. While sound sensitivity (hyperacusis) is a distressing symptom in FXS, its neural basis is not well understood. It is postulated that hyperacusis may stem from temporal lobe hyperexcitability or dysregulation in top-down modulation. Studying the neural mechanisms underlying sound sensitivity in FXS using scalp electroencephalography (EEG) is challenging because the temporal and frontal regions have overlapping neural projections that are difficult to differentiate. To overcome this challenge, we conducted EEG source analysis on a group of 36 individuals with FXS and 39 matched healthy controls. Our goal was to characterize the spatial and temporal properties of the response to an auditory chirp stimulus. Our results showed that males with FXS exhibit excessive activation in the frontal cortex in response to the stimulus onset, which may reflect changes in top-down modulation of auditory processing. Additionally, during the chirp stimulus, individuals with FXS demonstrated a reduction in typical gamma phase synchrony, along with an increase in asynchronous gamma power, across multiple regions, most strongly in temporal cortex. Consistent with these findings, we observed a decrease in the signal-to-noise ratio, estimated by the ratio of synchronous to asynchronous gamma activity, in individuals with FXS. Furthermore, this ratio was highly correlated with performance in an auditory attention task. Compared to controls, males with FXS demonstrated elevated bidirectional frontotemporal information flow at chirp onset. The evidence indicates that both temporal lobe hyperexcitability and disruptions in top-down regulation play a role in auditory sensitivity disturbances in FXS. These findings have the potential to guide the development of therapeutic targets and back-translation strategies.

Juxtacellular recordings from identified neurons in the mouse locus coeruleus.

The locus coeruleus (LC) is the primary source of noradrenergic transmission in the mammalian central nervous system. This small pontine nucleus consists of a densely packed nuclear core-which contains the highest density of noradrenergic neurons-embedded within a heterogeneous surround of non-noradrenergic cells. This local heterogeneity, together with the small size of the LC, has made it particularly difficult to infer noradrenergic cell identity based on extracellular sampling of in vivo spiking activity. Moreover, the relatively high cell density, background activity and synchronicity of LC neurons have made spike identification and unit isolation notoriously challenging. In this study, we aimed at bridging these gaps by performing juxtacellular recordings from single identified neurons within the mouse LC complex. We found that noradrenergic neurons (identified by tyrosine hydroxylase, TH, expression; TH-positive) and intermingled putatively non-noradrenergic (TH-negative) cells displayed similar morphologies and responded to foot shock stimuli with excitatory responses; however, on average, TH-positive neurons exhibited more prominent foot shock responses and post-activation firing suppression. The two cell classes also displayed different spontaneous firing rates, spike waveforms and temporal spiking properties. A logistic regression classifier trained on spontaneous electrophysiological features could separate the two cell classes with 76% accuracy. Altogether, our results reveal in vivo electrophysiological correlates of TH-positive neurons, which can be useful for refining current approaches for the classification of LC unit activity.

Field-resolved space–time characterization of few-cycle structured light pulses

Accompanied by the rapid development of ultrafast laser platforms in recent decades, the spatiotemporal manipulation of ultrashort laser pulses has attracted much attention due to the potential for cutting-edge applications of structured light, including optical tweezers, optical communications, super-resolution imaging, time-resolved spectroscopy in molecules and quantum materials, and strong-field physics. Today, techniques capable of characterizing the full spatial, temporal, and polarization state properties of structured light are strongly desired. Here, we demonstrate a technique, termed 3D TIPTOE, for characterizing structured mid-infrared waveforms, which uses only a two-dimensional silicon-based image sensor as both the detector and the nonlinear medium. By combining the advantages of the sub-cycle time resolution afforded by nonlinear excitation and the spatial resolution inherent to the two-dimensional sensor, the 3D TIPTOE technique allows full characterization of structured electric fields, significantly reducing the complexity of detection compared to other techniques. The validity of the technique is established by measuring both few-cycle Bessel–Gaussian pulses and radially polarized femtosecond vector beams.

Spatio-temporal deep recurrent convolutional neural network for infrared focal plane arrays non-uniformity correction

The inherent non-uniformity generated in infrared focal plane arrays (IRFPA) due to inconsistent responses of detectors, and it significantly degrades the performance of infrared imaging systems. Traditional Non-Uniformity Correction (NUC) methods mainly leverage the temporal low-frequency property of non-uniformity to remove it. In recent years, Convolutional Neural Network (CNN) has gained attention as a powerful tool for conducting NUC using solely spatial information from a single frame. In this study, we propose a deep neural network with a recurrent spatio-temporal feature fusion module to enhance CNN performance using inter-frame information. Initially, the proposed network uses CNN to coarsely extract FPN features solely from the spatial domain. Subsequently, the network merges it with the historical estimation under the guidance of two gating signals, which calculated from spatio-temporal information with gated convolutional layers. Both stages are jointly trained to ensure that the entire network operates end-to-end and adapts to different scenarios, eliminating complex parameter tuning efforts. Experiments demonstrated that the proposed network shows both the advantages of traditional and CNN-based NUC methods. It has a higher convergence starting point, faster convergence speed, and a 1 ∼ 2 dB improvement in PSNR compared to both types of methods.