The eyes reflect an internal cognitive state hidden in the population activity of cortical neurons.

Decades of research have shown that global brain states such as arousal can be indexed by measuring the properties of the eyes. The spiking responses of neurons throughout the brain have been associated with the pupil, small fixational saccades, and vigor in eye movements, but it has been difficult to isolate how internal states affect the eyes, and vice versa. While recording from populations of neurons in the visual and prefrontal cortex (PFC), we recently identified a latent dimension of neural activity called "slow drift," which appears to reflect a shift in a global brain state. Here, we asked if slow drift is correlated with the action of the eyes in distinct behavioral tasks. We recorded from visual cortex (V4) while monkeys performed a change detection task, and PFC, while they performed a memory-guided saccade task. In both tasks, slow drift was associated with the size of the pupil and the microsaccade rate, two external indicators of the internal state of the animal. These results show that metrics related to the action of the eyes are associated with a dominant and task-independent mode of neural activity that can be accessed in the population activity of neurons across the cortex.

Sociodemographic and Clinical Profiles of Patients with Irritable Bowel Syndrome: A Cross-sectional, Multi-centric, Epidemiological Study in India.

AIMS: Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder characterized by impaired gut-brain interaction. Considering the paucity of evidence in the Indian setting, the current study was conducted to determine the sociodemographics, clinical profiles, management practices, and patients' perception among newly diagnosed patients with IBS. METHODS: This was a cross-sectional, single-visit, observational, non-interventional, epidemiological study conducted across 12 centres. The primary objective was evaluation of sociodemographic and clinical profiles. The key secondary objective was assessment of gastrointestinal symptom severity including evaluation of anxiety and depression using the hospital anxiety and depression scale (HADS) scores. Knowledge, attitude, and practices (KAP) were evaluated as an exploratory objective. RESULTS: Out of 300 enrolled patients, 120 (40%) were aged 31-45 years (mean age: 38.55±12.45 years), and 204 were men (68%). Overall, 40% of patients belonged to the upper-middle-class, with a Kuppuswamy score of 16-25. Most patients (91%) did not work in night shifts. Only 13% of patients performed more than recommended physical activity. Stress and food were the leading triggers for IBS (29%). Abdominal pain and diarrhoea as cardinal symptoms were reported by 43.3% and 33.0% patients, respectively. Borderline abnormal anxiety and depression were reported by 21.3% and 26.7% of patients, respectively. KAP assessment revealed that 56.0% of patients had poor knowledge, 26.3% had moderate knowledge, and 17.7% had good knowledge about IBS; nevertheless, 43% of patients maintained high levels of precaution towards managing symptoms. CONCLUSION: Given the limited knowledge about IBS in India among newly diagnosed patients, strategies to enhance awareness about the condition are warranted.

Distinct Sources of Variability Affect Eye Movement Preparation.

The sequence of events leading to an eye movement to a target begins the moment visual information has reached the brain, well in advance of the eye movement itself. The process by which visual information is encoded and used to generate a motor plan has been the focus of substantial interest partly because of the rapid and reproducible nature of saccadic eye movements, and the key role that they play in primate behavior. Signals related to eye movements are present in much of the primate brain, yet most neurophysiological studies of the transition from vision to eye movements have measured the activity of one neuron at a time. Less is known about how the coordinated action of populations of neurons contribute to the initiation of eye movements. One cortical area of particular interest in this process is the frontal eye fields, a region of prefrontal cortex that has descending projections to oculomotor control centers. We recorded from populations of frontal eye field neurons in macaque monkeys engaged in a memory-guided saccade task. We found a variety of neurons with visually evoked responses, saccade-aligned responses, and mixtures of both. We took advantage of the simultaneous nature of the recordings to measure variability in individual neurons and pairs of neurons from trial-to-trial, as well as the moment-to-moment population activity structure. We found that these measures were related to saccadic reaction times, suggesting that the population-level organization of frontal eye field activity is important for the transition from perception to movement.SIGNIFICANCE STATEMENT The transition from perception to action involves coordination among neurons across the brain. In the case of eye movements, visual and motor signals coexist in individual neurons as well as in neighboring neurons. We used a task designed to compartmentalize the visual and motor aspects of this transition and studied populations of neurons in the frontal eye fields, a key cortical area containing neurons that are implicated in the transition from vision to eye movements. We found that the time required for subjects to produce an eye movement could be predicted from the statistics of the neuronal response of populations of frontal eye field neurons, suggesting that these neurons coordinate their activity to optimize the transition from perception to action.

Dynamic shifts of visual and saccadic signals in prefrontal cortical regions 8Ar and FEF.

Active vision is a fundamental process by which primates gather information about the external world. Multiple brain regions have been studied in the context of simple active vision tasks in which a visual target's appearance is temporally separated from saccade execution. Most neurons have tight spatial registration between visual and saccadic signals, and in areas such as prefrontal cortex (PFC), some neurons show persistent delay activity that links visual and motor epochs and has been proposed as a basis for spatial working memory. Many PFC neurons also show rich dynamics, which have been attributed to alternative working memory codes and the representation of other task variables. Our study investigated the transition between processing a visual stimulus and generating an eye movement in populations of PFC neurons in macaque monkeys performing a memory guided saccade task. We found that neurons in two subregions of PFC, the frontal eye fields (FEF) and area 8Ar, differed in their dynamics and spatial response profiles. These dynamics could be attributed largely to shifts in the spatial profile of visual and motor responses in individual neurons. This led to visual and motor codes for particular spatial locations that were instantiated by different mixtures of neurons, which could be important in PFC's flexible role in multiple sensory, cognitive, and motor tasks.NEW & NOTEWORTHY A central question in neuroscience is how the brain transitions from sensory representations to motor outputs. The prefrontal cortex contains neurons that have long been implicated as important in this transition and in working memory. We found evidence for rich and diverse tuning in these neurons, which was often spatially misaligned between visual and saccadic responses. This feature may play an important role in flexible working memory capabilities.

A neural network for online spike classification that improves decoding accuracy.

Separating neural signals from noise can improve brain-computer interface performance and stability. However, most algorithms for separating neural action potentials from noise are not suitable for use in real time and have shown mixed effects on decoding performance. With the goal of removing noise that impedes online decoding, we sought to automate the intuition of human spike-sorters to operate in real time with an easily tunable parameter governing the stringency with which spike waveforms are classified. We trained an artificial neural network with one hidden layer on neural waveforms that were hand-labeled as either spikes or noise. The network output was a likelihood metric for each waveform it classified, and we tuned the network's stringency by varying the minimum likelihood value for a waveform to be considered a spike. Using the network's labels to exclude noise waveforms, we decoded remembered target location during a memory-guided saccade task from electrode arrays implanted in prefrontal cortex of rhesus macaque monkeys. The network classified waveforms in real time, and its classifications were qualitatively similar to those of a human spike-sorter. Compared with decoding with threshold crossings, in most sessions we improved decoding performance by removing waveforms with low spike likelihood values. Furthermore, decoding with our network's classifications became more beneficial as time since array implantation increased. Our classifier serves as a feasible preprocessing step, with little risk of harm, that could be applied to both off-line neural data analyses and online decoding.NEW & NOTEWORTHY Although there are many spike-sorting methods that isolate well-defined single units, these methods typically involve human intervention and have inconsistent effects on decoding. We used human classified neural waveforms as training data to create an artificial neural network that could be tuned to separate spikes from noise that impaired decoding. We found that this network operated in real time and was suitable for both off-line data processing and online decoding.

Context cue-dependent saccadic adaptation in rhesus macaques cannot be elicited using color.

When the head does not move, rapid movements of the eyes called saccades are used to redirect the line of sight. Saccades are defined by a series of metrical and kinematic (evolution of a movement as a function of time) relationships. For example, the amplitude of a saccade made from one visual target to another is roughly 90% of the distance between the initial fixation point (T0) and the peripheral target (T1). However, this stereotypical relationship between saccade amplitude and initial retinal error (T1-T0) may be altered, either increased or decreased, by surreptitiously displacing a visual target during an ongoing saccade. This form of motor learning (called saccadic adaptation) has been described in both humans and monkeys. Recent experiments in humans and monkeys have suggested that internal (proprioceptive) and external (target shape, color, and/or motion) cues may be used to produce context-dependent adaptation. We tested the hypothesis that an external contextual cue (target color) could be used to evoke differential gain (actual saccade/initial retinal error) states in rhesus monkeys. We did not observe differential gain states correlated with target color regardless of whether targets were displaced along the same vector as the primary saccade or perpendicular to it. Furthermore, this observation held true regardless of whether adaptation trials using various colors and intrasaccade target displacements were randomly intermixed or presented in short or long blocks of trials. These results are consistent with hypotheses that state that color cannot be used as a contextual cue and are interpreted in light of previous studies of saccadic adaptation in both humans and monkeys.

Investigation into features of fracture toughness of a transparent E-glass fiber reinforced polyester composites at extreme temperatures.

In recent years, several investigators have made efforts to satisfy industrial and transportation demands with respect to high mechanical properties. Moreover, the transparent composites are needed for automotive and aircraft applications. Thus, developing more efficient and advanced transparent composite techniques has recently got more attention but seldom studied in harsh conditions. The main goal of the present study is to investigate the impact of exposing a transparent polyester composite to different temperatures ranging from high to very low (60, room temperature, 0, -30, -60, and -80 °C) and 50% humidity. The study of the effect on both fibers and matrix upon exposure to the different conditions and the composite represents an attempt towards climate resistance. In this research, fracture toughness of E-glass fiber reinforced unsaturated polyester composite at high and very low temperatures and humid environments were investigated. The investigation deals with the characterization of fracture strength properties according to the ASTM standards and mechanism of fracture by scanning electron microscopy. The transparent composite was fabricated from the unsaturated polyester matrix and E-glass fibers. Using of E-glass fiber for reinforcing with 15% volume percent for preparation of the transparent composite exhibits fracture toughness at very low temperatures. It was also noted that the technique of giving an excellent transparent polyester composite can be utilized confidently to architect and aircraft structures.

Energy Absorption Behavior of Al-SiC-Graphene Composite Foam under a High Strain Rate.

The present work was addressed to the closed-cell aluminum (Al)-silicon carbide (SiC) particles (15 wt.%) with graphene (0.5 wt.%) reinforced hybrid composite foam, which was produced through the melt route process. Under the strain rates ranging from 500 s-1 to 2760 s-1, the compression deformation behavior of hybrid composite foam was executed. The compression results disclosed that plateau stress along with energy absorption of produced hybrid composite foam are heightened with strain rates and is also discovered to be responsive to the relative density under the confront domain of experiments. Analysis of Variance was deployed for optimizing parameters such as strain rates, mass, density, relative density, and pore size. Furthermore, the contribution of each optimized parameters on plateau stress and energy absorption were observed.

Efficient enumeration of phylogenetically informative substrings.

We study the problem of enumerating substrings that are common amongst genomes that share evolutionary descent. For example, one might want to enumerate all identical (therefore conserved) substrings that are shared between all mammals and not found in non-mammals. Such collection of substrings may be used to identify conserved subsequences or to construct sets of identifying substrings for branches of a phylogenetic tree. For two disjoint sets of genomes on a phylogenetic tree, a substring is called a tag if it is found in all of the genomes of one set and none of the genomes of the other set. We present a near-linear time algorithm that finds all tags in a given phylogeny; and a sublinear space algorithm (at the expense of running time) that is more suited for very large data sets. Under a stochastic model of evolution, we show that a simple process of tag-generation essentially captures all possible ways of generating tags. We use this insight to develop a faster tag discovery algorithm with a small chance of error. However, since tags are not guaranteed to exist in a given data set, we generalize the notion of a tag from a single substring to a set of substrings. We present a linear programming-based approach for finding approximate generalized tag sets. Finally, we use our tag enumeration algorithm to analyze a phylogeny containing 57 whole microbial genomes. We find tags for all nodes in the phylogeny except the root for which we find generalized tag sets.

StreamQRE: Modular Specification and Efficient Evaluation of Quantitative Queries over Streaming Data.

Real-time decision making in emerging IoT applications typically relies on computing quantitative summaries of large data streams in an efficient and incremental manner. To simplify the task of programming the desired logic, we propose StreamQRE, which provides natural and high-level constructs for processing streaming data. Our language has a novel integration of linguistic constructs from two distinct programming paradigms: streaming extensions of relational query languages and quantitative extensions of regular expressions. The former allows the programmer to employ relational constructs to partition the input data by keys and to integrate data streams from different sources, while the latter can be used to exploit the logical hierarchy in the input stream for modular specifications. We first present the core language with a small set of combinators, formal semantics, and a decidable type system. We then show how to express a number of common patterns with illustrative examples. Our compilation algorithm translates the high-level query into a streaming algorithm with precise complexity bounds on per-item processing time and total memory footprint. We also show how to integrate approximation algorithms into our framework. We report on an implementation in Java, and evaluate it with respect to existing high-performance engines for processing streaming data. Our experimental evaluation shows that (1) StreamQRE allows more natural and succinct specification of queries compared to existing frameworks, (2) the throughput of our implementation is higher than comparable systems (for example, two-to-four times greater than RxJava), and (3) the approximation algorithms supported by our implementation can lead to substantial memory savings.

Complexities of MRI and false positive findings.

MRI is a robust technology that allows for superior contrast of muscles, tissues, and bones within the body, which enables visualization of soft tissue pathology that cannot be seen with CT or plain film radiography. In order to appreciate the subtle (and sometimes not so subtle) intricacies of MRI, one must have a basic knowledge of the MRI physics involved to acquire an image, which leads to better recognition and a clearer understanding of some of the more important artifacts seen with MRI, including incomplete fat suppression, chemical shift, magnetic susceptibility, magic angle, partial volume, wraparound, and motion artifact. There are, however, many complexities and pitfalls in imaging the rheumatoid wrist. Normal anatomy such as capsular insertion sites and nutrient vessels can mimic erosion sites. The magic angle phenomenon can mimic tendon tears. Alignment abnormalities can be simulated based on wrist positioning. By having a solid understanding of the physics of magnetic resonance, anatomy, and the disease processes involved, many of these pitfalls can be avoided.