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This review article focuses on metal–organic framework (MOF) composites and the impact of mixing MOFs with other materials, such as polymers, carbon-based materials, and magnetic particles, to increase their performance to remove metals from water.

During human seizures, organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N = 11 patients, 2 females, N = 31 seizures) from previous human studies to analyze the traveling wave source. We find, inconsistent with both existing theories, a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo. We conclude that combining both existing theories can generate the diversity of ictal traveling waves. SIGNIFICANCE STATEMENT The source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.

Neurons can code for multiple variables simultaneously and neuroscientists are often interested in classifying neurons based on their receptive field properties. Statistical models provide powerful tools for determining the factors influencing neural spiking activity and classifying individual neurons. However, as neural recording technologies have advanced to produce simultaneous spiking data from massive populations, classical statistical methods often lack the computational efficiency required to handle such data. Machine learning (ML) approaches are known for enabling efficient large scale data analyses; however, they typically require massive training sets with balanced data, along with accurate labels to fit well. Additionally, model assessment and interpretation are often more challenging for ML than for classical statistical methods. To address these challenges, we develop an integrated framework, combining statistical modeling and machine learning approaches to identify the coding properties of neurons from large populations. In order to demonstrate this framework, we apply these methods to data from a population of neurons recorded from rat hippocampus to characterize the distribution of spatial receptive fields in this region.

It is increasingly apparent that porous liquids (PLs) have unique use cases due to the combination of ready liquid handling and their inherently high adsorption capacity. Among the PL types, those with permanent porosity are the most promising. Although Type II and III PLs have economic synthetic methods and can be made from a huge variety of metal-organic frameworks (MOFs) and solvents, these nanocomposites still need to be stable to be useful. This work aims to systematically explore the possibilities of creating PLs using different MOF modification methods. This delivered underpinning insights into the molecular-level influence between solvent and MOF on the overall nanocomposite stability. Zirconium-based metal-organic frameworks were combined with two different solvents of varying chemistry to deliver CO

BACKGROUND AND PURPOSE: Transradial access for neurointerventional procedures has been proved a safer and more comfortable alternative to femoral artery access. We present our experience with transradial (distal radial/anatomic snuffbox and radial artery) access for treatment of intracranial aneurysms using all 3 FDA-approved flow diverters. MATERIALS AND METHODS: This was a high-volume, dual-center, retrospective analysis of each institution’s data base between June 2018 and June 2020 and a collection of all patients treated with flow diversion via transradial access. Patient demographic information and procedural and radiographic data were obtained. RESULTS: Seventy-four patients were identified (64 female patients) with a mean age of 57.5 years with a total of 86 aneurysms. Most aneurysms were located in the anterior circulation (93%) and within the intracranial ICA (67.4%). The mean aneurysm size was 5.5 mm. Flow diverters placed included the Pipeline Embolization Device (Flex) (PED, n = 65), the Surpass Streamline Flow Diverter (n = 8), and the Flow-Redirection Endoluminal Device (FRED, n = 1). Transradial access was successful in all cases, but femoral crossover was required in 3 cases (4.1%) due to tortuous anatomy and inadequate support of the catheters in 2 cases and an inability to navigate to the target vessel in a patient with an aberrant right subclavian artery. All 71 other interventions were successfully performed via the transradial approach (95.9%). No access site complications were encountered. Asymptomatic radial artery occlusion was encountered in 1 case (3.7%). CONCLUSIONS: Flow diverters can be successfully placed via the transradial approach with high technical success, low access site complications, and a low femoral crossover rate.

To our knowledge, radial artery catheter entrapment during mechanical thrombectomy for acute ischemic stroke using an 8 F neuro guiding catheter (.088 in ID) and successful use of a brachial plexus block has not been described in the literature. In this technical note, we describe a patient that underwent rapid and successful radial access mechanical thrombectomy for an acute right middle cerebral artery occlusion, however, during withdrawal of the Balt Ballast 0.088 inch long sheath (Balt USA, Irvine, CA, USA), radial/brachial artery entrapment was encountered. We describe a modified step-wise approach to previously published online article by Pitta et al. from 2017 SCAI communication in the management of catheter entrapment and describe the technique for ultrasound guided brachial plexus block, which helped avoid need for surgical removal.

Epilepsy biomarkers from electroencephalogram recordings are routinely used to assess seizure risk and localization. Two widely adopted biomarkers include: (i) interictal spikes, and (ii) high frequency ripple oscillations. The combination of these two biomarkers, ripples co-occurring with spikes (spike ripples), has been proposed as an improved biomarker for the epileptogenic zone and epileptogenicity in humans and rodent models. Whether spike ripples translate to predict seizure risk in rodent seizure models is unknown. Further, recent evidence suggests ictal networks can include deep gray nuclei in humans. Whether pathologic spike ripples and seizures are also observed in the basal ganglia in rodent models has not been explored. We addressed these questions using local field potential recordings from mice with and without striatal seizures after carbachol or 6-hydroxydopamine infusions into the striatum. We found increased spike ripples in the interictal and ictal periods in mice with seizures compared to pre-infusion and post-infusion seizure-free recordings. These data provide evidence of electrographic seizures involving the striatum in mice and support the candidacy of spike ripples as a translational biomarker for seizure risk in mouse models.

Point process generalized linear models (GLMs) provide a powerful tool for characterizing the coding properties of neural populations. Spline basis functions are often used in point process GLMs, when the relationship between the spiking and driving signals are nonlinear, but common choices for the structure of these spline bases often lead to loss of statistical power and numerical instability when the signals that influence spiking are bounded above or below. In particular, history dependent spike train models often suffer these issues at times immediately following a previous spike. This can make inferences related to refractoriness and bursting activity more challenging. Here, we propose a modified set of spline basis functions that assumes a flat derivative at the endpoints and show that this limits the uncertainty and numerical issues associated with cardinal splines. We illustrate the application of this modified basis to the problem of simultaneously estimating the place field and history dependent properties of a set of neurons from the CA1 region of rat hippocampus, and compare it with the other commonly used basis functions. We have made code available in MATLAB to implement spike train regression using these modified basis functions.

Representations related to past experiences play a critical role in memory and decision-making processes. The rat hippocampus expresses these types of representations during sharp-wave ripple (SWR) events, and previous work identified a minority of SWRs that contain ‘replay’ of spatial trajectories at ∼20x the movement speed of the animal. Efforts to understand replay typically make multiple assumptions about which events to examine and what sorts of representations constitute replay. We therefore lack a clear understanding of both the prevalence and the range of representational dynamics associated with replay. Here, we develop a state space model that uses a combination of movement dynamics of different speeds to capture the spatial content and time evolution of replay during SWRs. Using this model, we find that the large majority of replay events contain spatially coherent, interpretable content. Furthermore, many events progress at real-world, rather than accelerated, movement speeds, consistent with actual experiences.

Purpose To report the feasibility and safety of anatomical snuffbox access (distal radial artery, dRA) for carotid artery stenting (CAS). Methods We performed a retrospective review of our prospectively maintained neurointerventional database of CAS cases between May 2019 and February 2021. All CAS cases via the anatomical snuffbox were identified. Patient demographics, clinical information, procedural and radiographic data was collected. Results 24 CAS procedures in 22 patients via the anatomical snuffbox were identified. Patients‘ mean age was 69.5 years (range 53-87 years). 4 patients were female. Mean radial artery diameter was 2.1 mm (range 1.6-2.8 mm). Snuffbox access was achieved in all cases. Sixteen procedures involved the right carotid artery. In 19 cases a Carotid Wallstent (Boston Scientific) was used. In 2 cases a Viabahn stent graft (Gore) was placed and a Precise stent (Cordis) was deployed in 1 case. Conversion to femoral access was required in 2 cases (8.3%) due to persistent radial artery vasospasm resulting in patient discomfort despite multiple additional doses of intraarterial vasodilators and added intravenous sedation as well as tortuous vessel anatomy and limited support of the catheters in a type 3 aortic arch for left CAS. In our cases, dRA access was mainly obtained with a 6F Prelude Ideal hydrophilic sheath introducer (Merit Medical) and procedures were mainly performed using a Benchmark catheter (Penumbra). In 3 cases a Fubuki guide catheter (Asahi Intecc) was directly inserted into the dRA over the exchange length wire (sheath-less or bareback catheter use) after removal of the sheath. In one case, a 6F Benchmark guide catheter was used to gain direct access to the dRA. We did not observe any peri- or postprocedural access site complications. No access site complications were noted. A cerebral protection device was used in all cases. There was no morbidity or mortality associated with any of the CAS interventions. Conclusion Our preliminary experience with anatomical snuffbox access for CAS suggests this approach to be feasible and safe for patients. Preprocedural planning and technical considerations are both important for a successful procedure.Nevertheless, catheter systems and devices specifically designed for radial access are needed and will likely enable more interventionalists to safely perform such procedures via hand/wrist access. Disclosures A. Kuhn: None. J. Singh: None. S. Satti: 2; C; Balt, Stryker Neuromuscular, Cerenovus, Medtronic, Microvention, Terumo. T. Eden: None. V. Moholkar: None. K. de Macedo Rodrigues: None. F. Massari: None. V. Naragum: None. V. Anagnostakou: None. M. Gounis: 1; C; National Institutes of Health (NIH), the United States – Israel Binational Science Foundation, Anaconda, ApicBio, Axovant, Cerenovus, Cook Medical, Gentuity, Imperative Care, InNeuroCo, Magneto. 2; C; Cerenovus, Imperative Care, phenox, Medtronic Neurovascular, Route 92 Medical, Stryker Neurovascular. 4; C; Imperative Care, InNeuroCo and Neurogami. A. Puri: 1; C; NIH, Stryker Neurovascular, Medtronic, Cerenovus. 2; C; Microvention, QApel, Perfuze Medical, Arsenal Medical, Merit Medical, Stryker Neurovascular, Medtronic, Cerenovus. 4; C; InNeuroCo Inc, Galaxy therapeutics, Agile Medical, Perfuze medical and NTI.

Background A reliable biomarker to identify cortical tissue responsible for generating epileptic seizures is required to guide prognosis and treatment in epilepsy. Combined spike ripple events are a promising biomarker for epileptogenic tissue that currently require expert review for accurate identification. This expert review is time consuming and subjective, limiting reproducibility and high-throughput applications. New method To address this limitation, we develop a fully-automated method for spike ripple detection. The method consists of a convolutional neural network trained to compute the probability that a spectrogram image contains a spike ripple. Results We validate the proposed spike ripple detector on expert-labeled data and show that this detector accurately separates subjects with low and high seizure risks. Comparison with Existing Method The proposed method performs as well as existing methods that require manual validation of candidate spike ripple events. The introduction of a fully automated method reduces subjectivity and increases rigor and reproducibility of this epilepsy biomarker. Conclusion We introduce and validate a fully-automated spike ripple detector to support utilization of this epilepsy biomarker in clinical and translational work.

Lead detection for biological environments, aqueous resources, and medicinal compounds, rely mainly on either utilizing bulky lab equipment such as ICP-OES or ready-made sensors, which are based on colorimetry with some limitations including selectivity and low interference. Remote, rapid and efficient detection of heavy metals in aqueous solutions at ppm and sub-ppm levels have faced significant challenges that requires novel compounds with such ability. Here, a UiO-66(Zr) metal-organic framework (MOF) functionalized with SO3H group (SO3H-UiO-66(Zr)) is deposited on the end-face of an optical fiber to detect lead cations (Pb2+) in water at 25.2, 43.5 and 64.0 ppm levels. The SO3H-UiO-66(Zr) system provides a Fabry–Perot sensor by which the lead ions are detected rapidly (milliseconds) at 25.2 ppm aqueous solution reflecting in the wavelength shifts in interference spectrum. The proposed removal mechanism is based on the adsorption of [Pb(OH2)6]2+ in water on SO3H-UiO-66(Zr) due to a strong affinity between functionalized MOF and lead. This is the first work that advances a multi-purpose optical fiber-coated functional MOF as an on-site remote chemical sensor for rapid detection of lead cations at extremely low concentrations in an aqueous system.

Brain rhythms have been proposed to facilitate brain function, with an especially important role attributed to the phase of low frequency rhythms. Understanding the role of phase in neural function requires interventions that perturb neural activity at a target phase, necessitating estimation of phase in real-time. Current methods for real-time phase estimation rely on bandpass filtering, which assumes narrowband signals and couples the signal and noise in the phase estimate, adding noise to the phase and impairing detections of relationships between phase and behavior. To address this, we propose a state space phase estimator for real-time tracking of phase. By tracking the analytic signal as a latent state, this framework avoids the requirement of bandpass filtering, separately models the signal and the noise, accounts for rhythmic confounds, and provides credible intervals for the phase estimate. We demonstrate in simulations that the state space phase estimator outperforms current state-of-the-art real-time methods in the contexts of common confounds such as broadband rhythms, phase resets and co-occurring rhythms. Finally, we show applications of this approach to in vivo data. The method is available as a ready-to-use plug-in for the OpenEphys acquisition system, making it widely available for use in experiments.

Executing memory-guided behavior requires both the storage of information about experience and the later recall of that information to inform choices. Awake hippocampal replay, when hippocampal neural ensembles briefly reactivate a representation related to prior experience, has been proposed to critically contribute to these memory-related processes. However, it remains unclear whether awake replay contributes to memory function by promoting the storage of past experiences, by facilitating planning based on an evaluation of those experiences, or both. We designed a dynamic spatial task which promotes replay before a memory-based choice and assessed how the content of replay related to past and future behavior. We found that replay content was decoupled from subsequent choice and instead was enriched for representations of previously rewarded locations and places that had not been recently visited, indicating a role in memory storage rather than in directly guiding subsequent behavior.

Generalized Linear Models (GLMs) have been used extensively in statistical models of spike train data. However, the maximum likelihood estimates of the model parameters and their uncertainty, can be challenging to compute in situations where response and non-response can be separated by a single predictor or a linear combination of multiple predictors. Such situations are likely to arise in many neural systems due to properties such as refractoriness and incomplete sampling of the signals that influence spiking. In this paper, we describe multiple classes of approaches to address this problem: using an optimization algorithm with a fixed iteration limit, computing the maximum likelihood solution in the limit, Bayesian estimation, regularization, change of basis, and modifying the search parameters. We demonstrate a specific application of each of these methods to spiking data from rat somatosensory cortex and discuss the advantages and disadvantages of each. We also provide an example of a roadmap for selecting a method based on the problem’s particular analysis issues and scientific goals.

Representations related to past experiences play a critical role in memory and decision-making processes. The rat hippocampus expresses these types of representations during sharp-wave ripple (SWR) events, and previous work identified a minority of SWRs that contain “replay” of spatial trajectories at ~20x the movement speed of the animal. Efforts to understand replay typically make multiple assumptions about which events to examine and what sorts of representations constitute replay. We therefore lack a clear understanding of both the prevalence and the range of representational dynamics associated with replay. Here we develop a state space model that uses a combination of movement dynamics of different speeds to capture the spatial content and time evolution of replay during SWRs. Using this model, we find that the large majority of replay events contain spatially coherent, interpretable content. Furthermore, many events progress at real-world, rather than accelerated, movement speeds, consistent with actual experiences.

Marked point process models have recently been used to capture the coding properties of neural populations from multiunit electrophysiological recordings without spike sorting. These clusterless models have been shown in some instances to better describe the firing properties of neural populations than collections of receptive field models for sorted neurons and to lead to better decoding results. To assess their quality, we previously proposed a goodness-of-fit technique for marked point process models based on time rescaling, which for a correct model produces a set of uniform samples over a random region of space. However, assessing uniformity over such a region can be challenging, especially in high dimensions. Here, we propose a set of new transformations in both time and the space of spike waveform features, which generate events that are uniformly distributed in the new mark and time spaces. These transformations are scalable to multidimensional mark spaces and provide uniformly distributed samples in hypercubes, which are well suited for uniformity tests. We discuss the properties of these transformations and demonstrate aspects of model fit captured by each transformation. We also compare multiple uniformity tests to determine their power to identify lack-of-fit in the rescaled data. We demonstrate an application of these transformations and uniformity tests in a simulation study. Proofs for each transformation are provided in the appendix.

Introduction/Purpose Two factors limiting first line radial access for complex cerebrovascular interventions include: radial artery diameter and available catheter technology. Our rule for patient selection is to maintain a radial artery/sheath ratio of ≥.8, which we used as the primary inclusion criteria for all procedures. We have increasingly attempted sheathless radial access allowing for largest inner and smallest outer diameter. We describe a low cost/simplified approach to direct radial access with a commonly available guide catheter. We then present our experience of transradial cerebrovascular interventions comparing outcomes between procedures performed using a 6F Terumo Slender Sheath/Benchmark guide (OD 2.53 mm) versus direct sheathless radial access with the Benchmark (OD 2.0 mm). Materials and Method Single institution retrospective electronic query of all 6F radial access procedures performed between October 2010 and March 2020 access for cerebrovascular intervention using a Penumbra Benchmark 6F guiding catheter. The procedures were divided in Group 1 - 133 pts (sheath) and Group 2- 32 patients (sheathless). Summary Technique for Direct/Sheathless Access 1. Ultrasound guided: Target vessel selection/measurement. *Inclusion: artery diameter/sheath diameter ≥.8) 4F micropuncture/21 g needle: Radial angiogram and Radial cocktail Exchange: Micropuncture sheath/sheathless Benchmark/BER over .035 × 180 cm glidewirePrimary outcomes included: failure of primary access (need to convert to femoral access) and major complications requiring surgery or transfusion. Secondary outcomes included: infection, development of AV fistula, or development of pseudoaneurysm. Results Procedural success (completion of planned procedure) was achieved in 98.2% of patients (average of groups 1 and 2), no significant difference. Procedures performed included a wide spectrum of intracranial pathologies, however, aneurysm treatment represented >60% of procedures. Success with the primary access site cannulation was 100% for both Group 1 and Group 2, when using rule of ≥ .8. No major complications were encountered in either group of patients; no patients required transfusion or emergency vascular surgery for vessel injury/avulsion, digital ischemia, or compartment syndrome. One patient was identified in Group 1 with a symptomatic radial artery-vein fistula underwent successful elective out-patient surgical repair at 12 months. Conclusion Sheathless radial access using a Penumbra Benchmark 071 guiding catheter can be used for cerebrovascular interventions in both anterior and posterior circulation pathology. High technical success completing index procedure, success with arterial cannulation and low complication rates may be attributed to patient selection/technique (maintaining artery/sheath ratio of ≥ .8). Direct radial access requires smaller vessel diameter potentially expanding eligible patients with smaller radial artery diameters. Disclosures S. Satti: None. T. Eden: None.

The Bayesian state-space neural encoder-decoder modeling framework is an established solution to reveal how changes in brain dynamics encode physiological covariates like movement or cognition. Although the framework is increasingly being applied to progress the field of neuroscience, its application to modeling high-dimensional neural data continues to be a challenge. Here, we propose a novel solution that avoids the complexity of encoder models that characterize high-dimensional data as a function of the underlying state processes. We build a discriminative model to estimate state processes as a function of current and previous observations of neural activity. We then develop the filter and parameter estimation solutions for this new class of state-space modeling framework called the “direct decoder” model. We applied the model to decode movement trajectories of a rat in a W-shaped maze from the ensemble spiking activity of place cells and achieve comparable performance to modern decoding solutions, without needing an encoding step in the model development. We further demonstrate how a dynamical auto-encoder can be built using the direct decoder model; where the underlying state process links the high-dimensional neural activity to the behavioral readout. We applied the dynamical auto-encoder model in estimating the intention to verbally communicate of an epileptic participant and their companions. The result shows that the dynamical auto-encoder can optimally estimate the low-dimensional dynamical manifold which represents the relationship between the brain and behavior.

As neuronal data accumulates worldwide, accessible - yet rigorous - resources to develop hands-on experience with modern data analysis techniques are required. We present here an online educational resource for neural data analysis (https://mark-kramer.github.io/Case-Studies-Python). To reach the biologists, psychologists, and clinicians collecting neuronal data, we assume only a basic mathematics background, common to those trained in biological sciences. Through an interdisciplinary case-study approach, we use real-world data to motivate the study of modern quantitative analysis methods in Python. A modular format provides multiple coherent learning paths through the material, and thereby allows personalized learning for individuals with varying quantitative backgrounds and research interests, and flexible curation of material for redeployment in other curricula. Developed using Jupyter notebooks, the material supports fully interactive environments in most web browsers, and hosted on GitHub, the material is freely available for reuse, modification, and further development by the community.

Cognitive control is the ability to withhold a default, prepotent response in favor of a more adaptive choice. Control deficits are common across mental disorders, including depression, anxiety, and addiction. Thus, a method for improving cognitive control could be broadly useful in disorders with few effective treatments. Here, we demonstrate closed-loop enhancement of one aspect of cognitive control by direct brain stimulation in humans. We stimulated internal capsule/striatum in participants undergoing intracranial epilepsy monitoring as they performed a cognitive control/conflict task. Stimulation enhanced performance, with the strongest effects from dorsal capsule/striatum stimulation. We then developed a framework to detect control lapses and stimulate in response. This closed-loop approach produced larger behavioral changes than open-loop stimulation, with a slight improvement in performance change per unit of energy delivered. Finally, we decoded task performance directly from activity on a small number of electrodes, using features compatible with existing closed-loop brain implants. Our findings are proof of concept for a new approach to treating severe mental disorders, based on directly remediating underlying cognitive deficits.

Introduction: Patients harboring brain AVMs associated with moderate-high surgical morbidity (large lesions, deep location and eloquent cortex) are increasingly undergoing hypofractionated stereotactic radiosurgery (SRS) at our institution. Most published literature is based on a single fraction SRS technique. In this review we sought to evaluate/present our hypofractionated SRS experience using the Accuray Cyberknife device. Hypothesis: Cyberknife Stereotactic Radiosurgery (C-SRS) can be used for a high risk brain arteriovenous malformations (AVMs) with high rates of successful complete obliteration and low rates of hemorrhagic, death and major disability. Methods: We performed a retrospective analysis of all patients having undergone Cyberknife SRS for brain AVMs between 2013-2019 at a large community based tertiary care health system and identified 33 patients. Of these patients 12 had a minimum of 2 year follow-up. We divided the patients into hemorrhagic and non-hemorrhagic presentations, prior endovascular treatment with embolization and based on Spetzler Martin grades. Results: 58% males with median age of 44 and 9% presenting with hemorrhage. Median planning target volume (PTV) was 7.2 cc (range 1.25-15.56 cc) and median HFSRT dose was three fractions (range 3-5) of 10.25 Gy (range 8.5-11 Gy) each. Complete obliteration was achieved in 100% of patients after salvage SRS 21 Gy x1 fraction to a residual AVM volume in 2 patients. The median time to obliteration was 747 days. 3 of 12 patients suffered radiation necrosis1 patient with a large AVM (maximum diameter of 4 cm and PTV of 12.6 cc) suffered re-hemorrhage and radiation necrosis, but ultimately completely obliterated after 402 days and was left with mRS ≤2). Conclusion: Although we have a small sample size, fractionated SRS with Cyberknife resulted in 100% obliteration, low rates recurrent hemorrhage and low morbidity (no mortality). These outcomes are superior to published single fraction radiosurgery results in high risk patients. Further study with a prospective multicenter registry or as part of a larger RCT is warranted.

Summary Objective Benign epilepsy with centrotemporal spikes (BECTS) is a common, self‐limited epilepsy syndrome affecting school‐age children. Classic interictal epileptiform discharges (IEDs) confirm diagnosis, and BECTS is presumed to be pharmacoresponsive. As seizure risk decreases in time with this disease, we hypothesize that the impact of IEDs and anticonvulsive drug (ACD) treatment on the risk of subsequent seizure will differ based on disease duration. Methods We calculate subsequent seizure risk following diagnosis in a large retrospective cohort of children with BECTS (n = 130), evaluating the impact of IEDs and ACD treatment in the first, second, third, and fourth years of disease. We use a Kaplan–Meier survival analysis and logistic regression models. Patients were censored if they were lost to follow‐up or if they changed group status. Results Two‐thirds of children had a subsequent seizure within 2 years of diagnosis. The majority of children had a subsequent seizure within 3 years despite treatment. The presence of IEDs on electroencephalography (EEG) did not impact subsequent seizure risk early in the disease. By the fourth year of disease, all children without IEDs remained seizure free, whereas one‐third of children with IEDs at this stage had a subsequent seizure. Conversely, ACD treatment corresponded with lower risk of seizure early in the disease but did not impact seizure risk in later years. Significance In this cohort, the majority of children with BECTS had a subsequent seizure despite treatment. In addition, ACD treatment and IEDs predicted seizure risk at specific points of disease duration. Future prospective studies are needed to validate these exploratory findings.

Citronella is a source of essential oil obtained from steam distillation. The production of citronella oil is quite high; therefore, it can be applied in various fields. One of its applications is as an active substance in mosquito repellent creams. The citronella oil used in this study contained 11.59% citronellol content at a retention time of 16.544 minutes and citronellol content of 14.78% at a retention time of 27.165 minutes using the Gas Chromatography Mass Spectrometry method. In the manufacture of mosquito repellent creams, there are still mismatches in the composition between variables, so there is a need for optimization in this study. Optimization in this study using Response Surface Methodology model Central Composite Design on Statistica 10 software with 19 treatments. The method used was the addition of independent variables, citronella oil (2-4%), stearic acid (10-16%) and cetyl alcohol (4-6%) processed using the RSM-CCD method to determine the optimum pH. Optimization results with RSM at pH resulted in optimum conditions for citronella oil content of 2.1591%, stearic acid 18.045% and cetyl alcohol 6.6818% with a pH of 6.1.

Summary Executing memory-guided behavior requires storage of information about experience and later recall of that information to inform choices. Awake hippocampal replay, when hippocampal neural ensembles briefly reactivate a representation related to prior experience, has been proposed to critically contribute to these memory-related processes. However, it remains unclear whether awake replay contributes to memory function by promoting the storage of past experiences, facilitating planning based on evaluation of those experiences, or both. We designed a dynamic spatial task that promotes replay before a memory-based choice and assessed how the content of replay related to past and future behavior. We found that replay content was decoupled from subsequent choice and instead was enriched for representations of previously rewarded locations and places that had not been visited recently, indicating a role in memory storage rather than in directly guiding subsequent behavior.

Epilepsy—the propensity toward recurrent, unprovoked seizures—is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms—namely, the effects of an increased extracellular potassium concentration diffusing in space—that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures—and connecting these dynamics to specific biological mechanisms—promises new insights to treat this devastating disease., The authors record both local and long-range neural activity during human epileptic seizures to study the underlying multi-scale dynamics. They find that coupling of activity across spatial scales increases during seizures through propagating waves that are fit by a model that combines neural activity and potassium concentration dynamics.

Introduction Sleep-disordered breathing (SDB) is a dynamic process in which the rate of respiratory events is highly influenced by numerous covariates, such as sleep stage, body position dominance, time of night, and overall instability of sleep architecture. Additionally, respiratory event rate likely has history dependence, such that the likelihood of a respiratory event is influenced by the timing of previous events. Despite its dynamic nature, clinical diagnosis collapses the complex process of SDB to a single number measuring the average rate of respiratory event occurrence— the apnea-hypopnea index (AHI). Thus, potentially valuable information is being lost by ignoring SDB temporal dynamics and history dependence. Methods We apply a general point process framework to sleep apnea events to develop parametric models of a time-varying instantaneous apnea rate given clinical covariates (e.g. EEG power, sleep stage, body position). Develop models of apnea history dependence, describing the likelihood of events given past event times. In doing so, we are able to compute an “instantaneous AHI”, which measures the moment-by-moment event rate, which evolves temporally as a function of other clinical observations as well as event history. We apply our model to data from the MESA cohort (include number of subjects, male/female here). We then applied dimensionality-reduction methods to assess any population phenotypes. Results For every subject, we computed a time-varying AHI for each time point in their polysomnogram and estimated the influence of each of the measured covariates on the instantaneous rate. Results showed that the greatest predictor of apnea events were related to history dependence. Clustering analysis showed no distinct clusters, but rather a constant gradient of changes in history dependence. Conclusion These results suggest that the greatest predictor of an apnea event onset is the timing previous event. Moreover, the way in which previous events influence subsequent events can be used as a means of phenotyping, paving the way towards identifying optimal personalized treatment. Support National Institute of Neurological Disorders and Stroke Grant R01 NS-096177

Marked-point process models have recently been used to capture the coding properties of neural populations from multi-unit electrophysiological recordings without spike sorting. These ‘clusterless’ models have been shown in some instances to better describe the firing properties of neural populations than collections of receptive field models for sorted neurons and to lead to better decoding results. To assess their quality, we previously proposed a goodness-of-fit technique for marked-point process models based on time-rescaling, which for a correct model, produces a set of uniform samples over a random region of space. However, assessing uniformity over such a region can be challenging, especially in high dimensions. Here, we propose a set of new transformations both in time and in the space of spike waveform features, which generate events that are uniformly distributed in the new mark and time spaces. These transformations are scalable to multi-dimensional mark spaces and provide uniformly distributed samples in hypercubes, which are well suited for uniformity tests. We discuss properties of these transformations and demonstrate aspects of model fit captured by each transformation. We also compare multiple uniformity tests to determine their power to identify lack-of-fit in the rescaled data. We demonstrate an application of these transformations and uniformity tests in a simulation study. Proofs for each transformation are provided in the Appendix section. We have made the MATLAB code used for the analyses in this paper publicly available through our Github repository at https://github.com/YousefiLab/Marked-PointProcess-Goodness-of-Fit

The Geostationary Operational Environmental Satellite R (GOES-R) series of four satellites are the next generation NOAA GOES satellites. Once on orbit and commissioned, they are renamed GOES 16-19, making critical terrestrial and space weather measurements through 2035. GOES 16 and 17 are currently on orbit, having been launched in 2016 and 2018, respectively. The GOES-R satellites include the EUV and X-ray Irradiance Sensors (EXIS) instrument suite, which measures calibrated solar irradiance in 8 lines or bands between 25 and 285 nm with the Extreme Ultraviolet Sensors (EUVS) instrument. EXIS also includes the X-Ray Sensor (XRS) instrument, which measures solar soft X-ray irradiance at the legacy GOES bands. The EUVS measurements are used as inputs to the EUVS Model, a solar spectral irradiance model for space weather operations that predicts irradiance in twenty-two 5 nm wide intervals from 5 nm to 115 nm, and one 10 nm wide interval from 117 to 127 nm at 30 second cadence. Once fully operational, NOAA will distribute the EUVS Model irradiance with 1 minute latency as a primary space weather data product, ushering in a new era of rapid dissemination and measurement continuity of EUV irradiance spectra. This paper describes the EUVS Model algorithms, data sources, calibration methods and associated uncertainties. Typical model (relative) uncertainties are less than $\sim$5\% for variability at time-scales longer than 6 hours, and are $\sim$25\% for solar flare induced variability. The absolute uncertainties, originating from the instruments used to calibrate the EUVS Model, are $\sim$10\%. Examples of model results are presented at both sub-daily and multi-year timescales to demonstrate the model's capabilities and limitations. Example solar flare irradiances are also modeled., Accepted by Journal of Space Weather and Space Climate on 20 November 2019

The ability to regulate emotions in the service of meeting ongoing goals and task demands is a key aspect of adaptive human behavior in our volatile social world. Consequently, difficulties in processing and responding to emotional stimuli underlie many psychiatric diseases ranging from depression to anxiety, the common thread being effects on behavior. Behavior, which is made up of shifting, difficult to measure hidden states such as attention and emotion reactivity, is a product of integrating external input and latent mental processes. Directly measuring, and differentiating, separable hidden cognitive, emotional, and attentional states contributing to emotion conflict resolution, however, is challenging, particularly when only using task-relevant behavioral measures such as reaction time. State-space representations are a powerful method for investigating hidden states underlying complex systems. Using state-space modeling of behavior, we identified relevant hidden cognitive states and predicted behavior in a standardized emotion regulation task. After identifying and validating models which best fit the behavior and narrowing our focus to one model, we used targeted intracranial stimulation of the emotion regulation-relevant neurocircuitry, including prefrontal structures and the amygdala, to causally modulate separable states. Finally, we focused on this one validated state-space model to perform real-time, bidirectional closed-loop adaptive stimulation in a subset of participants. These approaches enable an improved understanding of how to sample and understand emotional processing in a way which could be leveraged in neuromodulatory therapy for disorders of emotional regulation.

Cross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate examples of CFC during a seizure and in response to electrical stimuli.

Background and objective New large bore aspiration catheters are being used as first line therapy for mechanical thrombectomy in patients with emergent large vessel occlusions. We present the largest combined experience with the new Stryker Neurovascular Vecta 071/074 aspiration catheters. Vecta 074 represents the largest available aspiration catheter in the U.S. We sought to assess the safety, efficacy, direct aspiration first pass success, need for rescue with stent retriever, and clinical improvement. Methods Multi-institution retrospective review of all Vecta aspiration catheter cases performed at 2 comprehensive stroke centers between January 1, 2019 and March 25, 2019 yielded 26 patients. Key metrics were recorded including pre-procedure ASPECTS score, presenting NIHSS score, last seen normal to groin access, groin access to first device deployment, time to recanalization, revascularization TICI grading, thrombectomy technique (successful direct aspiration, need for rescue stent retriever and number of passes), and outcomes (NIHSS at discharge, rate of symptomatic intracranial hemorrhage sICH, and death prior to discharge). Results Eighteen 071 and six 074 Vecta aspiration catheters were used (figures.1/2). The average pre-procedure ASPECTS, NIHSS, and time from last seen normal were 8, 17.7, and 5.3 hours, respectively. Time from vascular access to first device delivery was 25.9 minutes. Direct aspiration was attempted as first line technique in all cases and was successful in 72% of cases. 28% of cases required use of a stent retriever to deliver the aspiration catheter (grappling hook technique-figure.3), or for rescue thrombectomy (direct aspiration unsuccessful or to target residual small, distal emboli). TICI 3 revascularization was achieved in 46%, TICI 2C in 23%, TICI 2B in 26%, and 5% with unsuccessful TICI 2A revascularization. The average NIHSS on discharge was 6.1 with two patients expiring prior to discharge (withdrawal of care in two patients with basilar artery occlusion). Complications included one intracranial/extradural non-flow limiting dissection and one sICH. Limitations included: Small sample size, retrospective review, variation in data collection due to differences in institutional records and short time to follow up. Conclusion Initial experience with the new Stryker Neurovascular Vecta 071/074 aspiration catheters suggests that high TICI 2C/3 reperfusion rates can safely be obtained using direct aspiration in a majority of cases. Stent retrievers can be reserved for cases where grappling hook technique is necessary to deliver the aspiration catheter to the clot or for rescue thrombectomy. Disclosures S. Satti: 2; C; Stryker Neurovascular, Medtronic Neurovascular, Penumbra Neurovascular, Cerenovus Neurovascular, Terumo. T. Sivapatham: 2; C; Penumbra Neurovascular. E. Almallouhi: None. T. Eden: None. A. Spiotta: 2; C; Minnetronix Neurovascular, Cerenovus Neurovascular, Penumbura Neurovascular.