Drifts in Prefrontal and Parietal Neuronal Activity Influence Working Memory Judgments.

The dorsolateral prefrontal cortex (dlPFC) plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here, we addressed if this predictive ability extends to other working memory tasks and if it is present in other brain areas. We trained monkeys to remember the location of a stimulus and determine whether a second stimulus appeared at the same location or not. Neurophysiological recordings were performed in the dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and toward the location of the second stimulus would result in categorical errors. Indeed, for both areas, in nonmatching trials, when the first stimulus appeared in a neuron's preferred location, the neuron showed significantly higher firing rates in correct than in error trials; and vice versa, when the first stimulus appeared at a nonpreferred location, activity in error trials was higher than in correct. The results indicate that the activity of both dlPFC and PPC neurons is predictive of categorical judgments of information maintained in working memory, and neuronal firing rate deviations are revealing of the contents of working memory.

Heading-sensitive azimuth error analysis and scheme modification for the multi-position alignment of a fiber-optic gyro strapdown inertial navigation system.

As two-position is the most widely used scheme of multi-position alignment, azimuth error analysis regarding the whole alignment procedure as an entity is explicitly discussed. A formula to calculate an equivalent north accelerometer bias drift rate is developed. The effecting extent of each inertial measurement error is also theoretically deduced and validated through simulation. It is pointed out that the main error sources causing heading-sensitive azimuth error are accelerometer triad non-orthogonality and lever arm error. In a Kalman filter alignment algorithm, affected by the equivalent accelerometer bias change rate, extra azimuth error emerges from the mistake estimation of fiber-optic gyroscope drift. A three-sequence scheme and a reciprocating slow-rotation scheme are proposed to achieve the most inertial measurement error self-compensation. Theoretical error comparison and a turntable four-orientation alignment test show the superiority of the reciprocating slow-rotation scheme over the other two schemes. The heading-sensitive azimuth alignment error is reduced from 0.2268° to better than 0.0015° through scheme modification.

C/N0 Estimator Based on the Adaptive Strong Tracking Kalman Filter for GNSS Vector Receivers.

The carrier-to-noise ratio (C/N0) is an important indicator of the signal quality of global navigation satellite system receivers. In a vector receiver, estimating C/N0 using a signal amplitude Kalman filter is a typical method. However, the classical Kalman filter (CKF) has a significant estimation delay if the signal power levels change suddenly. In a weak signal environment, it is difficult to estimate the measurement noise for CKF correctly. This article proposes the use of the adaptive strong tracking Kalman filter (ASTKF) to estimate C/N0. The estimator was evaluated via simulation experiments and a static field test. The results demonstrate that the ASTKF C/N0 estimator can track abrupt variations in C/N0 and the method can estimate the weak signal C/N0 correctly. When C/N0 jumps, the ASTKF estimation method shows a significant advantage over the adaptive Kalman filter (AKF) method in terms of the time delay. Compared with the popular C/N0 algorithms, the narrow-to-wideband power ratio (NWPR) method, and the variance summing method (VSM), the ASTKF C/N0 estimator can adopt a shorter averaging time, which reduces the hysteresis of the estimation results.

High Precision Compensation for a Total Reflection Prism Laser Gyro Bias in Consideration of High Frequency Oscillator Voltage.

Traditional compensation methods based on temperature-related parameters are not effective for complex total reflection prism laser gyro (TRPLG) bias variation. Because the high frequency oscillator voltage (UHFO) fundamentally affects the TRPLG bias, and the UHFO has a stronger correlation with the TRPLG bias when compared with the temperature, an introduction of UHFO into the TRPLG bias compensation can be evaluated. In consideration of the limitations of least squares (LS) regression and multivariate stepwise regression, we proposed a compensation method for TRPLG bias based on iterative re-weighted least squares support vector machine (IR-LSSVM) and compared with LS regression, stepwise regression, and LSSVM algorithm in large temperature cycling experiments. When temperature, slope of temperature variation, and UHFO were selected as inputs, the IR-LSSVM based on myriad weight function improved the TRPLG bias stability by 61.19% to reach the maximum and eliminated TRPLG bias drift. In addition, the UHFO proved to be the most important parameter in the process of TRPLG bias compensation; accordingly, it can alleviate the shortcomings of traditional compensation based on temperature-related parameters and can greatly improve the TRPLG bias stability.

Automatic Estimation of Dynamic Lever Arms for a Position and Orientation System.

An inertially stabilized platform (ISP) is generally equipped with a position and orientation system (POS) to isolate attitude disturbances and to focus surveying sensors on interesting targets. However, rotation of the ISP will result in a time-varying lever arm between the measuring center of the inertial measurement unit (IMU) and the phase center of the Global Positioning System (GPS) antenna, making it difficult to measure and provide compensation. To avoid the complexity of manual measurement and improve surveying efficiency, we propose an automatic estimation method for the dynamic lever arm. With the aid of the ISP encoder data, we decompose the variable lever arm into two constant lever arms to be estimated on line. With a complete 21-dimensional state Kalman filter, we accurately and simultaneously accomplish navigation and dynamic lever arm calibration. Our observability analysis provides a valuable insight into the conditions under which the lever arms can be estimated, and we use the error distribution method to reveal which error sources are the most influential. The simulation results demonstrate that the dynamic lever arm can be estimated to within [0.0104; 0.0110; 0.0178] m, an accuracy that is equivalent to the positioning accuracy of Carrier-phase Differential GPS (CDGPS).

Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System.

In the face of emerging Global Navigation Satellite System (GNSS) spoofing attacks, there is a need to give a comprehensive analysis on how the inertial navigation system (INS)/GNSS integrated navigation system responds to different kinds of spoofing attacks. A better understanding of the integrated navigation system’s behavior with spoofed GNSS measurements gives us valuable clues to develop effective spoofing defenses. This paper focuses on an impact assessment of GNSS spoofing attacks on the integrated navigation system Kalman filter’s error covariance, innovation sequence and inertial sensor bias estimation. A simple and straightforward measurement-level trajectory spoofing simulation framework is presented, serving as the basis for an impact assessment of both unsynchronized and synchronized spoofing attacks. Recommendations are given for spoofing detection and mitigation based on our findings in the impact assessment process.

Phenylephrine enhances glutamate release in the medial prefrontal cortex through interaction with N-type Ca2+ channels and release machinery.

α1 -adrenoceptors (α1 -ARs) stimulation has been found to enhance excitatory processes in many brain regions. A recent study in our laboratory showed that α1 -ARs stimulation enhances glutamatergic transmission via both pre- and post-synaptic mechanisms in layer V/VI pyramidal cells of the rat medial prefrontal cortex (mPFC). However, a number of pre-synaptic mechanisms may contribute to α1 -ARs-induced enhancement of glutamate release. In this study, we blocked the possible post-synaptic action mediated by α1 -ARs to investigate how α1 -ARs activation regulates pre-synaptic glutamate release in layer V/VI pyramidal neurons of mPFC. We found that the α1 -ARs agonist phenylephrine (Phe) induced a significant enhancement of glutamatergic transmission. The Phe-induced potentiation was mediated by enhancing pre-synaptic glutamate release probability and increasing the number of release vesicles via a protein kinase C-dependent pathway. The mechanisms of Phe-induced potentiation included interaction with both glutamate release machinery and N-type Ca(2+) channels, probably via a pre-synaptic Gq /phospholipase C/protein kinase C pathway. Our results may provide a cellular and molecular mechanism that helps explain α1 -ARs-mediated influence on PFC cognitive functions. Alpha1 -adrenoceptor (α1 -ARs) stimulation has been reported to enhance glutamatergic transmission in layer V/VI pyramidal neurons of the rat medial prefrontal cortex (mPFC). We found that α1 -ARs agonist phenylephrine (Phe) increases pre-synaptic glutamate release probability and the number of released vesicles via interaction with both glutamate release machinery and N-type Ca(2+) channels. Our results may provide a cellular and molecular mechanism that helps explain α1 -ARs-mediated influence on PFC cognitive functions. Gq, Gq protein; PLC, phospholipase C; PKC, protein kinase C; AMPA, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid; NMDA, N-methyl-d-aspartate; Glu, glutamate; Phe, phenylephrine.

[Treating Elderly Coronary Heart Disease Patients by Different Approaches of Percutaneous Coronary Intervention: an Observation of Clinical Efficacy].

OBJECTIVE: To observe thee efficacy of different ways of percutaneous coronary intervention (PCI) for treating elderly coronary heart disease (CHD) patients. METHODS: Totally 470 elderly CHD patients were classified to three age brackets (equal to or more than 85 years old, 60 to 74 years old, 75 to 84 years old). They were assigned to the transradial intervention (TRI) group (236 cases) and the transfemoral intervention (TFI) group (234 cases) according to different intervention pathways. Correlated indices and postoperative clinical efficacy were compared between the two groups. RESULTS: A higher successful rate of surgery was obviously got in patients 85 years old or older than 85 than in those 60 to 74 years old and 75 to 84 years old (P <0. 05). The incidence of major cardiovascular events (MACE) was reduced at post-operative 12 and 24 months in patients 85 years old or older than 85 (P <0. 05). The case number for changing intervention pathway were increased in the TRI group with statistical difference (P <0. 05). Compared with the TFI group, the case number for changing intervention pathway was increased; the time for arteriopuncture, the time for catheterization, and the time for X-ray exposure were prolonged; the time for postoperative bedding were obviously shortened; the incidence of vascular complications at the puncture site were lowered. The incidence of postoperative 12-month MACE was lowered, all with statistical difference (all P <0. 05). The incidence of MACE within postoperative 24-month MACE decreased in patients 60 to 74 years old and 75 to 84 years old (P <0. 05). The incidence of MACE within postoperative 24 months increased in patients 85 years old or older than 85 of the TRI group with statistical difference (P <0. 05). CONCLUSION: TRI can be preferably chosen for PC in treating elderly CHD patients.

Activation of α1-adrenoceptors enhances excitatory synaptic transmission via a pre- and postsynaptic protein kinase C-dependent mechanism in the medial prefrontal cortex of rats.

The physiological effects of α1-adrenoceptors (α1-ARs) have been examined in many brain regions. However, little is known about the mechanism of modulation on synaptic transmission by α1-ARs in the medial prefrontal cortex (mPFC). The present study investigated how α1-AR activation regulates glutamatergic synaptic transmission in layer V/VI pyramidal cells of the rat mPFC. We found that the α1-AR agonist phenylephrine (Phe) induced a significant enhancement of the amplitude and frequency of miniature excitatory postsynaptic currents (mEPSCs). The facilitation effect of Phe on the frequency of mEPSCs involved a presynaptic protein kinase C-dependent pathway. Phe produced a significant enhancement on the amplitude of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA-R)- and N-methyl-D-aspartic acid receptor (NMDA-R)-mediated evoked excitatory postsynaptic currents (eEPSCs). Phe enhanced inward currents evoked by puff application of glutamate or NMDA. The Phe-induced facilitation of AMPA-R- and NMDA-R-mediated eEPSCs required, in part, postsynaptic Gq , phospholipase C and PKC. These findings suggest that α1-AR activation facilitates excitatory synaptic transmission in mPFC pyramidal cells via both pre- and post-synaptic PKC-dependent mechanisms.

Lung adenocarcinoma identification based on hybrid feature selections and attentional convolutional neural networks.

Lung adenocarcinoma, a chronic non-small cell lung cancer, needs to be detected early. Tumor gene expression data analysis is effective for early detection, yet its challenges lie in a small sample size, high dimensionality, and multi-noise characteristics. In this study, we propose a lung adenocarcinoma convolutional neural network (LATCNN), a deep learning model tailored for accurate lung adenocarcinoma prediction and identification of key genes. During the feature selection stage, we introduce a hybrid algorithm. Initially, the fast correlation-based filter (FCBF) algorithm swiftly filters out irrelevant features, followed by applying the k-means-synthetic minority over-sampling technique (k-means-SMOTE) method to address category imbalance. Subsequently, we enhance the particle swarm optimization (PSO) algorithm by incorporating fast-decay dynamic inertia weights and utilizing the classification and regression tree (CART) as the fitness function for the second stage of feature selection, aiming to further eliminate redundant features. In the classifier construction stage, we present an attention convolutional neural network (atCNN) that incorporates an attention mechanism. This improved model conducts feature selection post lung adenocarcinoma gene expression data analysis for classification and prediction. The results show that LATCNN effectively reduces the feature dimensions and accurately identifies 12 key genes with accuracy, recall, F1 score, and MCC of 99.70%, 99.33%, 99.98%, and 98.67%, respectively. These performance metrics surpass those of other comparative models, highlighting the significance of this research for advancing lung adenocarcinoma treatment.

Contributions of narrow- and broad-spiking prefrontal and parietal neurons on working memory tasks.

Neurons that generate persistent activity in the primate dorsolateral prefrontal and posterior parietal cortex have been shown to be predictive of behavior in working memory tasks, though subtle differences between them have been observed in how information is represented. The role of different neuron types in each of these areas has not been investigated at depth. We thus compared the activity of neurons classified as narrow-spiking, putative interneurons, and broad-spiking, putative pyramidal neurons, recorded from the dorsolateral prefrontal and posterior parietal cortex of male monkeys, to analyze their role in the maintenance of working memory. Our results demonstrate that narrow-spiking neurons are active during a range of tasks and generate persistent activity during the delay period over which stimuli need to be maintained in memory. Furthermore, the activity of narrow-spiking neurons was predictive of the subject's recall no less than that of broad-spiking neurons, which are exclusively projection neurons in the cortex. Our results show that putative interneurons play an active role during the maintenance of working memory and shed light onto the fundamental neural circuits that determine subjects' memories and judgments.

Alterations of neural activity in the prefrontal cortex associated with deficits in working memory performance.

Working memory (WM), a core cognitive function, enables the temporary holding and manipulation of information in mind to support ongoing behavior. Neurophysiological recordings conducted in nonhuman primates have revealed neural correlates of this process in a network of higher-order cortical regions, particularly the prefrontal cortex (PFC). Here, we review the circuit mechanisms and functional importance of WM-related activity in these areas. Recent neurophysiological data indicates that the absence of these neural correlates at different stages of WM is accompanied by distinct behavioral deficits, which are characteristic of various disease states/normal aging and which we review here. Finally, we discuss emerging evidence of electrical stimulation ameliorating these WM deficits in both humans and non-human primates. These results are important for a basic understanding of the neural mechanisms supporting WM, as well as for translational efforts to developing therapies capable of enhancing healthy WM ability or restoring WM from dysfunction.

Primate superior colliculus is engaged in abstract higher-order cognition.

Categorization is a fundamental cognitive process by which the brain assigns stimuli to behaviorally meaningful groups. Investigations of visual categorization in primates have identified a hierarchy of cortical areas that are involved in the transformation of sensory information into abstract category representations. However, categorization behaviors are ubiquitous across diverse animal species, even those without a neocortex, motivating the possibility that subcortical regions may contribute to abstract cognition in primates. One candidate structure is the superior colliculus (SC), an evolutionarily conserved midbrain region that, although traditionally thought to mediate only reflexive spatial orienting, is involved in cognitive tasks that require spatial orienting. Here, we reveal a novel role of the primate SC in abstract, higher-order visual cognition. We compared neural activity in the SC and the posterior parietal cortex (PPC), a region previously shown to causally contribute to category decisions, while monkeys performed a visual categorization task in which they report their decisions with a hand movement. The SC exhibits stronger and shorter-latency category encoding than the PPC, and inactivation of the SC markedly impairs monkeys' category decisions. These results extend SC's established role in spatial orienting to abstract, non-spatial cognition.

Evaluation of an inkless method for fingerprint recordings using hand sanitizer gel on thermal paper (Part II): Effect of time, temperature, and biological sex.

This article further investigates the suitability of an inkless method to obtain and maintain exemplar fingerprint recordings on thermal paper; in this case, stored for 1.5 years at different temperatures. Inkless impressions were (re-)examined by optical means via two independent methods. First, an automated metric from the FBI's Universal Latent Workstation (ULW) was adapted (i.e., BlueGreen color-coded maps) to evaluate visual differences among inkless fingerprint sets with respect to storage time, temperature, relative humidity, and biological sex. Additionally, a conventional assessment system was applied, a categorical quality score (QS) metric that ranges on a grading scale from 1 to 4. Results revealed that storage time (72 weeks), as well as a colder temperature (~ 3 ºC) and lower relative humidity (~ 12 %), had little impact on the preservation of ridge clarity when compared to freshly deposited counterparts. A biological sex effect was again detected, but its influence was not significant under certain conditions. Despite minor visual differences, the ridge clarity of the inkless impressions remained stable for the duration of the experiment. The stability and durability of the proposed inkless method were proven, becoming a potential alternative to the conventional black ink method.

More Prominent Nonlinear Mixed Selectivity in the Dorsolateral Prefrontal than Posterior Parietal Cortex.

Neurons in the dorsolateral prefrontal cortex (dlPFC) and posterior parietal cortex (PPC) are activated by different cognitive tasks and respond differently to the same stimuli depending on task. The conjunctive representations of multiple tasks in nonlinear fashion in single neuron activity, is known as nonlinear mixed selectivity (NMS). Here, we compared NMS in a working memory task in areas 8a and 46 of the dlPFC and 7a and lateral intraparietal cortex (LIP) of the PPC in macaque monkeys. NMS neurons were more frequent in dlPFC than in PPC and this was attributed to more cells gaining selectivity in the course of a trial. Additionally, in our task, the subjects' behavioral performance improved within a behavioral session as they learned the session-specific statistics of the task. The magnitude of NMS in the dlPFC also increased as a function of time within a single session. On the other hand, we observed minimal rotation of population responses and no appreciable differences in NMS between correct and error trials in either area. Our results provide direct evidence demonstrating a specialization in NMS between dlPFC and PPC and reveal mechanisms of neural selectivity in areas recruited in working memory tasks.

Evaluation of an inkless method for fingerprint recordings using hand sanitizer gel on thermal paper.

The main objective of this project was to assess an inkless method to collect reference (exemplar) fingerprints as a low-cost, portable, and hygienic technique; for temporary storage and as an alternative to the conventional black ink method. The tested inkless approach requires alcohol-based hand sanitizer gel as the medium and thermal paper as the substrate. The final quality and clarity of fingerprints were examined and compared between the two methods, especially on the basis of medium/substrate and biological sex effects. Two different evaluation systems of visual quality (clarity) were conducted to provide more reliable results: a quality score scheme (QS) and metrics from the FBI's Universal Latent Workstation (ULW). Fingerprints were obtained from 20 individuals (11 males and 9 females) between the ages of 20 and 40; a total of 240 impressions were evaluated. The results provide evidence that the inkless method produces identifiable fingerprints of equivalent quality to the standard ink method, although significantly better for males. The potential of the proposed technique as an alternative to the conventional ink method is proven and corroborated by the two independent systems of visual quality assessments.

Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother.

The shearer positioning method with an inertial measurement unit and the odometer is feasible in the longwall coal-mining process. However, the positioning accuracy will continue to decrease, especially for the micro-electromechanical inertial measurement unit (MIMU). In order to further improve the positioning accuracy of the shearer without adding other external sensors, the positioning method of the Rauch-Tung-Striebel (RTS) smoother-aided MIMU and odometer is proposed. A Kalman filter (KF) with the velocity and position measurements, which are provided by the odometer and closing path optimal estimation model (CPOEM), respectively, is established. The observability analysis is discussed to study the possible conditions under which the error states of KF can be estimated. A RTS smoother with the above-mentioned KF as the forward filter is built. Finally, the experiments of simulating the movement of the shearer through a mobile carrier were carried out, with a longitudinal movement distance of 44.6 m and a lateral advance distance of 1.2 m. The results show that the proposed method can effectively improve the positioning accuracy. In addition, the odometer scale factor and mounting angles can be estimated in real time.

A New MIMU/GNSS Ultra-Tightly Coupled Integration Architecture for Mitigating Abrupt Changes of Frequency Tracking Errors.

We present a new ultra-tightly coupled (UTC) integration architecture of a micro-electromechanical inertial measurement unit (MIMU) and global navigation satellite system (GNSS) to reduce the performance degradation caused by abrupt changes of frequency tracking errors. A large frequency error will lead to a decrease in the carrier-to-noise ratio (C/N0) estimate and an increase in the code discriminator estimation error. The disruptive effects of frequency errors on the estimation of C/N0 and on the code discriminator are quantitatively evaluated via theoretical analyses and Monte Carlo simulations. The new MIMU/GNSS UTC architecture introduces a large frequency error detector and a refined frequency processor based on a retuned frequency in each tracking channel. In addition, an adaptive channel prefilter with multiple fading factors is introduced as an alternate to the conventional prefilter. Numerical simulations based on a highly dynamic trajectory are used to assess performance. The simulation results show that when there is an abrupt step change in the frequency tracking error, the new UTC architecture can effectively suppress the divergence of navigation solutions and the loss of tracking lock, and can significantly reduce the deviation of the C/N0 estimation.

Plasticity of Persistent Activity and Its Constraints.

Stimulus information is maintained in working memory by action potentials that persist after the stimulus is no longer physically present. The prefrontal cortex is a critical brain area that maintains such persistent activity due to an intrinsic network with unique synaptic connectivity, NMDA receptors, and interneuron types. Persistent activity can be highly plastic depending on task demands but it also appears in naïve subjects, not trained or required to perform a task at all. Here, we review what aspects of persistent activity remain constant and what factors can modify it, focusing primarily on neurophysiological results from non-human primate studies. Changes in persistent activity are constrained by anatomical location, with more ventral and more anterior prefrontal areas exhibiting the greatest capacity for plasticity, as opposed to posterior and dorsal areas, which change relatively little with training. Learning to perform a cognitive task for the first time, further practicing the task, and switching between learned tasks can modify persistent activity. The ability of the prefrontal cortex to generate persistent activity also depends on age, with changes noted between adolescence, adulthood, and old age. Mean firing rates, variability and correlation of persistent discharges, but also time-varying firing rate dynamics are altered by these factors. Plastic changes in the strength of intrinsic network connections can be revealed by the analysis of synchronous spiking between neurons. These results are essential for understanding how the prefrontal cortex mediates working memory and intelligent behavior.

Interplay between persistent activity and activity-silent dynamics in the prefrontal cortex underlies serial biases in working memory.

Persistent neuronal spiking has long been considered the mechanism underlying working memory, but recent proposals argue for alternative 'activity-silent' substrates. Using monkey and human electrophysiology data, we show here that attractor dynamics that control neural spiking during mnemonic periods interact with activity-silent mechanisms in the prefrontal cortex (PFC). This interaction allows memory reactivations, which enhance serial biases in spatial working memory. Stimulus information was not decodable between trials, but remained present in activity-silent traces inferred from spiking synchrony in the PFC. Just before the new stimulus, this latent trace was reignited into activity that recapitulated the previous stimulus representation. Importantly, the reactivation strength correlated with the strength of serial biases in both monkeys and humans, as predicted by a computational model that integrates activity-based and activity-silent mechanisms. Finally, single-pulse transcranial magnetic stimulation applied to the human PFC between successive trials enhanced serial biases, thus demonstrating the causal role of prefrontal reactivations in determining working-memory behavior.