Do Interictal Epileptiform Discharges and Brain Responses to Electrical Stimulation Come from the Same Location? An Advanced Source Localization Solution.

Identification of seizure sources in the brain is of paramount importance, particularly for drug-resistant epilepsy patients who may require surgical operation. Interictal epileptiform discharges (IEDs), which may or may not be frequent, are known to originate from seizure networks. Delayed responses (DRs) to brain electrical stimulation have been recently discovered. If DRs and IEDs come from the same location and the DRs can be accurately localized, there will be a significant step in identification of the seizure sources. The solution to this important question has been investigated in this paper. For this, we have exploited the morphology of these spike-type events, as well as the variability in their temporal locations, to develop new constraints for an adaptive Bayesian beamformer that outperforms the conventional and recently proposed beamformers even for identifying correlated sources. This beamformer is applied to an array (a.k.a mat) of cortical EEG electrodes. The developed approach has been tested on 300 data segments from five epileptic patients included in this study, which clinically represent a large population of candidates for surgical treatment. As the significant outcome of applying this beamformer, it is very likely (if not certain) that for an epileptic subject, the IEDs and DRs originate from the same location in the brain. This paves the way for a quick identification of the source(s) of seizure in the brain.

A review of signal processing and machine learning techniques for interictal epileptiform discharge detection.

Brain interictal epileptiform discharges (IEDs), as one of the hallmarks of epileptic brain, are transient events captured by electroencephalogram (EEG). IEDs are generated by seizure networks, and they occur between seizures (interictal periods). The development of a robust method for IED detection could be highly informative for clinical treatment procedures and epileptic patient management. Since 1972, different machine learning techniques, from template matching to deep learning, have been developed to automatically detect IEDs from scalp EEG (scEEG) and intracranial EEG (iEEG). While the scEEG signals suffer from low information details and high attenuation of IEDs due to the high skull electrical impedance, the iEEG signals recorded using implanted electrodes enjoy higher details and are more suitable for identifying the IEDs. In this review paper, we group IED detection techniques into six categories: (1) template matching, (2) feature representation (mimetic, time-frequency, and nonlinear features), (3) matrix decomposition, (4) tensor factorization, (5) neural networks, and (6) estimation of the iEEG from the concurrent scEEG followed by detection and classification. The methods are compared quantitatively (e.g., in terms of accuracy, sensitivity, and specificity), and their general advantages and limitations are described. Finally, current limitations and possible future research paths related to this field are mentioned.

Rotavirus-mediated DGAT1 degradation: A pathophysiological mechanism of viral-induced malabsorptive diarrhea.

Gastroenteritis is among the leading causes of mortality globally in infants and young children, with rotavirus (RV) causing ~258 million episodes of diarrhea and ~128,000 deaths annually in infants and children. RV-induced mechanisms that result in diarrhea are not completely understood, but malabsorption is a contributing factor. RV alters cellular lipid metabolism by inducing lipid droplet (LD) formation as a platform for replication factories named viroplasms. A link between LD formation and gastroenteritis has not been identified. We found that diacylglycerol O-acyltransferase 1 (DGAT1), the terminal step in triacylglycerol synthesis required for LD biogenesis, is degraded in RV-infected cells by a proteasome-mediated mechanism. RV-infected DGAT1-silenced cells show earlier and increased numbers of LD-associated viroplasms per cell that translate into a fourfold-to-fivefold increase in viral yield (P < 0.05). Interestingly, DGAT1 deficiency in children is associated with diarrhea due to altered trafficking of key ion transporters to the apical brush border of enterocytes. Confocal microscopy and immunoblot analyses of RV-infected cells and DGAT1-/- human intestinal enteroids (HIEs) show a decrease in expression of nutrient transporters, ion transporters, tight junctional proteins, and cytoskeletal proteins. Increased phospho-eIF2α (eukaryotic initiation factor 2 alpha) in DGAT1-/- HIEs, and RV-infected cells, indicates a mechanism for malabsorptive diarrhea, namely inhibition of translation of cellular proteins critical for nutrient digestion and intestinal absorption. Our study elucidates a pathophysiological mechanism of RV-induced DGAT1 deficiency by protein degradation that mediates malabsorptive diarrhea, as well as a role for lipid metabolism, in the pathogenesis of gastroenteritis.

An embedded intracranial seizure monitor for objective outcome measurements and rhythm identification.

Providing clinicians with objective outcomes of neuromodulation therapy is a key unmet need, especially in emerging areas such as epilepsy and mood disorders. These diseases have episodic behavior and circadian/multidien rhythm characteristics that are difficult to capture in short clinical follow-ups. This work presents preliminary validation evidence for an implantable neuromodulation system with integrated physiological event monitoring, with an initial focus on seizure tracking for epilepsy. The system was developed to address currently unmet requirements for patients undergoing neuromodulation therapy for neurological disorders, specifically the ability to sense physiological data during stimulation and track events with seconds-level granularity. The system incorporates an interactive software tool to enable optimal configuration of the signal processing chain on an embedded implantable device (the Picostim-DyNeuMo Mk-2) including data ingestion from the device loop recorder, event labeling, generation of filter and classification parameters, as well as summary statistics. When the monitor parameters are optimized, the user can wirelessly update the system for chronic event tracking. The simulated performance of the device was assessed using an in silico model with human data to predict the real-time device performance at tracking recorded seizure activity. The in silico performance was then compared against its performance in an in vitro model to capture the full environmental constraints such as sensing during stimulation at the tissue electrode interface. In vitro modeling demonstrated comparable results to the in silico model, providing verification of the software tool and model. This study provides validation evidence of the suitability of the proposed system for tracking longitudinal seizure activity. Given its flexibility, the event monitor can be adapted to track other disorders with episodic and rhythmic symptoms represented by bioelectrical behavior.Clinical relevance-An implantable neuromodulation system is presented that enables chronic tracking of physiological events in disease. This physiological monitor provides the basis for longitudinal assessments of therapy outcomes for patients, such as those with epilepsy where objective identification of patient seizure activity and rhythms might help guide therapy optimization. The system is configurable for other disease states such as Parkinson's disease and mood disorders.

Neuromodulation Techniques in Children with Super-Refractory Status Epilepticus.

Status epilepticus (SE) is a life-threatening condition and medical emergency which can have lifelong consequences, including neuronal death and alteration of neuronal networks, resulting in long-term neurologic and cognitive deficits in children. When standard pharmacological treatment for SE is not successful in controlling seizures, the condition evolves to refractory SE (rSE) and finally to super-refractory SE (srSE) if it exceeds 24 h despite using anaesthetics. In this systematic review, we present literature data on the potential uses of clinical neuromodulation techniques for the management of srSE in children, including electroconvulsive therapy, vagus nerve stimulation, and deep brain stimulation. The evaluation of these techniques is limited by the small number of published paediatric cases (n = 25, one with two techniques) in peer-reviewed articles (n = 18). Although neuromodulation strategies have not been tested through randomised, prospective controlled clinical trials, this review presents the existing data and the potential benefits of neuromodulation therapy, suggesting that these techniques, when available, could be considered at earlier stages within the course of srSE intending to prevent long-term neurologic complications. Clinical trials aiming to establish whether early intervention can prevent long-term sequelae are necessary in order to establish the potential clinical value of neuromodulation techniques for the treatment of srSE in children.

Vagus nerve stimulation in refractory idiopathic generalised epilepsy: An Irish retrospective observational study.

OBJECTIVE: Refractory idiopathic generalised epilepsy (IGE; also known as genetic generalised epilepsy) is a clinical challenge due to limited available therapeutic options. While vagus nerve stimulation (VNS) is approved as an adjunctive treatment for drug-resistant focal epilepsy, there is limited evidence supporting its efficacy for refractory IGE. METHODS: We conducted a single-centre retrospective analysis of adult IGE patients treated with VNS between January 2003 and January 2022. We analysed the efficacy, safety, tolerability, stimulation parameters and potential clinical features of VNS response in this IGE cohort. RESULTS: Twenty-three IGE patients were implanted with VNS between January 2003 and January 2022. Twenty-two patients (95.65%) were female. The median baseline seizure frequency was 30 per month (interquartile range [IQR]= 140), including generalised tonic-clonic seizures (GTCS), absences, myoclonus, and eyelid myoclonia with/without absences. The median number of baseline anti-seizure medications (ASM) was three (IQR= 2). Patients had previously failed a median of six ASM (IQR= 5). At the end of the study period, VNS therapy remained active in 17 patients (73.9%). amongst patients who continued VNS, thirteen (56.5% of the overall cohort) were considered responders (≥50% seizure frequency reduction). Amongst the clinical variables analysed, only psychiatric comorbidity correlated with poorer seizure outcomes, but was non-significant after applying the Bonferroni correction. Although 16 patients reported side-effects, none resulted in the discontinuation of VNS therapy. SIGNIFICANCE: Over half of the patients with refractory IGE experienced a positive response to VNS therapy. VNS represents a viable treatment option for patients with refractory IGE, particularly for females, when other therapeutic options have been exhausted.

Mental Imagery in Dreams of Congenitally Blind People.

It is unclear to what extent the absence of vision affects the sensory sensitivity for oneiric construction. Similarly, the presence of visual imagery in the mentation of dreams of congenitally blind people has been largely disputed. We investigate the presence and nature of oneiric visuo-spatial impressions by analysing 180 dreams of seven congenitally blind people identified from the online database DreamBank. A higher presence of auditory, haptic, olfactory, and gustatory sensation in dreams of congenitally blind people was demonstrated, when compared to normally sighted individuals. Nonetheless, oneiric visual imagery in reports of congenitally blind subjects was also noted, in opposition to some previous studies, and raising questions about the possible underlying neuro-mechanisms.

Localization of Epileptic Brain Responses to Single-Pulse Electrical Stimulation by Developing an Adaptive Iterative Linearly Constrained Minimum Variance Beamformer.

Delayed responses (DRs) to single pulse electrical stimulation (SPES) in patients with severe refractory epilepsy, from their intracranial recordings, can help to identify regions associated with epileptogenicity. Automatic DR localization is a large step in speeding up the identification of epileptogenic focus. Here, for the first time, an adaptive iterative linearly constrained minimum variance beamformer (AI-LCMV) is developed and employed to localize the DR sources from intracranial electroencephalogram (EEG) recorded using subdural electrodes. The prime objective here is to accurately localize the regions for the corresponding DRs using an adaptive localization method that exploits the morphology of DRs as the desired sources. The traditional closed-form linearly constrained minimum variance (CF-LCMV) solution is meant for tracking the sources with dominating power. Here, by incorporating the morphology of DRs, as a constraint, to an iterative linearly constrained minimum variance (LCMV) solution, the array of subdural electrodes is used to localize the low-power DRs, some not even visible in any of the electrode signals. The results from the cases included in this study also indicate more distinctive locations compared to those achievable by conventional beamformers. Most importantly, the proposed AI-LCMV is able to localize the DRs invisible over other electrodes.

Aortic valve Replacement compared to Transcatheter Implant and its relationship with COgnitive Impairment (ARTICO) evaluated with neuropsychological and advanced neuroimaging: a longitudinal cohort study.

BACKGROUND: Aortic stenosis is the most common valvulopathy in Western countries. The treatment of choice had been surgery aortic valve replacement (SAVR), but the improvement in endovascular approaches as transcatheter aortic valve implantation (TAVI), initially reserved for patients with very high surgical risk, has been extended to high and intermediate, and recently also to low-risk patients. Stroke and vascular cognitive impairment are the most important complications. It is not entirely clear which technique is best to avoid these complications as well as their impact. Our goal is to evaluate changes in cognitive performance in the early (1-month) and late (1-year) postoperative period in patients undergoing SAVR or TAVI, by extensive neuropsychological study (NRP) and advanced Magnetic Resonance Imaging (MRI). Specifically, to compare early and late cognitive changes after the intervention between both groups, the occurrence of stroke during follow-up and to compare the appearance of silent vascular lesions and changes in brain activity and functional connectivity with functional MRI during follow-up between both groups. METHODS/DESIGN: Prospective longitudinal cohort study. A non-selected representative sample of 80 subjects, 40 SAVR and 40 TAVI to obtain a final sample of 36 eligible subjects in each group, ranging from 70 to 85 years old, with indication for aortic replacement and intermediate or high surgical risk will be studied. At baseline, within one month before the treatment, all individuals will undergo an extensive NRP and advanced MRI study. These studies will also be performed 1-month and 1-year after treatment, to assess the appearance of new vascular lesions, as well as changes in cognitive performance with respect to baseline. DISCUSSION: This study aims to evaluate changes in cognitive performance as well as both clinical and silent vascular events occurring in the early (1-month) and late (1-year) periods after SAVR and TAVI. We will also analyze the correlation between neuropsychological and neuroimaging approaches in order to evaluate cognition. Therefore, it may provide high-quality data of cognitive changes and vascular events for both techniques, and be useful to tailor interventions to individual characteristics and ultimately aiding in decision-making. TRIAL REGISTRATION: This study is register in Clinicaltrials.gov (NCT05235529) on 11th February 2022.

Neuromodulation in new-onset refractory status epilepticus.

Background: New-onset refractory status epilepticus (NORSE) and its subset of febrile infection-related epilepsy syndrome (FIRES) are devastating clinical presentations with high rates of mortality and morbidity. The recently published consensus on the treatment of these conditions includes anesthetics, antiseizure drugs, antivirals, antibiotics, and immune therapies. Despite the internationally accepted treatment, the outcome remains poor for a significant percentage of patients. Methods: We conducted a systematic review of the use of neuromodulation techniques in the treatment of the acute phase of NORSE/FIRES using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Our search strategy brought up 74 articles of which 15 met our inclusion criteria. A total of 20 patients were treated with neuromodulation. Thirteen cases represented FIRES and in 17 cases the NORSE remained cryptogenic. Ten had electroconvulsive therapy (ECT), seven had vagal nerve stimulation (VNS), and four had deep brain stimulation (DBS); one patient had initially VNS and later DBS. Eight patients were female and nine were children. In 17 out of 20 patients, the status epilepticus was resolved after neuromodulation, while three patients died. Conclusion: NORSE can have a catastrophic course and the first treatment goal should be the fastest possible termination of status epilepticus. The data presented are limited by the small number of published cases and the variability of neuromodulation protocols used. However, they show some potential clinical benefits of early neuromodulation therapy, suggesting that these techniques could be considered within the course of FIRES/NORSE.

Influence of Strict Lockdown on Vitamin D Deficiency in Pregnant Women: A Word of Caution.

The main source of vitamin D results from skin sunlight exposure. Vitamin D deficiency (VDD) is linked to several adverse events during pregnancy. While performing a cross-sectional study with 886 pregnant women in Elda (Spain) from September 2019 to July 2020 to determine the association of VDD with gestational diabetes mellitus in relation to body mass index, a strict lockdown (SL) due to the COVID-19 pandemic was declared from 15 March 2020 to 15 May 2020. To determine if VDD prevalence in the local population of pregnant women was influenced by SL, a retrospective cross-sectional study was conducted to estimate the prevalence odds ratio (POR) for the association of VDD and SL. A crude logistic regression model was calculated, and then further adjusted by the biweekly measured vitamin D-specific UVB dose in our geographical area. The POR during SL was 4.0 (95%CI = 2.7-5.7), with a VDD prevalence of 77.8% in the quarantine period. Our results revealed that VDD prevalence in pregnant women was influenced by SL. This valuable information could guide us in future if public officials order the population to stay indoors for any given reason.

Step-dose IL-7 treatment promotes systemic expansion of T cells and alters immune cell landscape in blood and lymph nodes.

We employed a dose-escalation regimen in rhesus macaques to deliver glycosylated IL-7, a cytokine critical for development and maintenance of T lymphocytes. IL-7 increased proliferation and survival of T cells and triggered several chemokines and cytokines. Induction of CXCL13 in lymph nodes (LNs) led to a remarkable increase of B cells in the LNs, proliferation of germinal center follicular T helper cells and elevated IL-21 levels suggesting an increase in follicle activity. Transcriptomics analysis showed induction of IRF-7 and Flt3L, which was linked to increased frequency of circulating plasmacytoid dendritic cells (pDCs) on IL-7 treatment. These pDCs expressed higher levels of CCR7, homed to LNs, and were associated with upregulation of type-1 interferon gene signature and increased production of IFN-α2a on TLR stimulation. Superior effects and dose-sparing advantage was observed by the step-dose regimen. Thus, IL-7 treatment leads to systemic effects involving both lymphoid and myeloid compartments.

Separating Inhibitory and Excitatory Responses of Epileptic Brain to Single-Pulse Electrical Stimulation.

To enable an accurate recognition of neuronal excitability in an epileptic brain for modeling or localization of epileptic zone, here the brain response to single-pulse electrical stimulation (SPES) has been decomposed into its constituent components using adaptive singular spectrum analysis (SSA). Given the response at neuronal level, these components are expected to be the inhibitory and excitatory components. The prime objective is to thoroughly investigate the nature of delayed responses (elicited between 100[Formula: see text]ms-1 s after SPES) for localization of the epileptic zone. SSA is a powerful subspace signal analysis method for separation of single channel signals into their constituent uncorrelated components. The consistency in the results for both early and delayed brain responses verifies the usability of the approach.

Life expectancy after surgical aortic valve replacement for low-gradient aortic stenosis with preserved ejection fraction.

INTRODUCTION AND OBJECTIVES: Surgical aortic valve replacement (SAVR) can modify the natural history of severe aortic stenosis (SAS). However, compared with the general population, these patients have a loss of life expectancy. The life expectancy of patients who undergo SAVR due to low-gradient SAS with preserved left ventricular ejection fraction (LVEF) is unknown. METHODS: We included all patients between 50 and 65 years who underwent isolated SAVR in 27 Spanish centers during an 18-year period. We analyzed observed and expected survival at 18 years in patients with low-gradient SAS with preserved LVEF and all other types of SAS. We used propensity score matching to compare the life expectancy of patients with low-gradient SAS with preserved LVEF vs those with high-gradient SAS with preserved LVEF. RESULTS: We analyzed 5084 patients, of whom 413 had low-gradient SAS with preserved LVEF. For these patients, observed survival at 10, 15 and 18 years was 86.6% (95%CI, 85.3-87.8), 75% (95%CI, 72.7-77.2), and 63.5% (95%CI, 58.8-67.8). Expected survival at 10, 15 and 18 years was 90.2%, 82.1%, and 75.7%. In the matched sample, survival of patients with low-gradient SAS with preserved LVEF was similar to that of patients with high-gradient with preserved LVEF, log-rank test, P=.95; HR=1 (95%CI, 0.7-1.4; P=.95). CONCLUSIONS: There is a loss of life expectancy in patients with all types of SAS undergoing SAVR. This loss is higher in patients with left ventricular dysfunction and lower in patients with low-gradient or high-gradient aortic stenosis with preserved LVEF. The benefit of surgery is similar between these last 2 groups.

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl- d -Aspartate Receptor Antibody Encephalitis.

PURPOSE: Anti-N-methyl- d -aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis. METHODS: A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4-8 Hz), alpha (8 - 13 Hz), and beta (13-30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors. RESULTS: Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2-6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ 2 (1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R2 ) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated ( P = 0.04) with an increased likelihood of poor outcome. CONCLUSIONS: In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated.

Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy.

This work explores the potential utility of neural network classifiers for real- time classification of field-potential based biomarkers in next-generation responsive neuromodulation systems. Compared to classical filter-based classifiers, neural networks offer an ease of patient-specific parameter tuning, promising to reduce the burden of programming on clinicians. The paper explores a compact, feed - forward neural network architecture of only dozens of units for seizure-state classification in refractory epilepsy. The proposed classifier offers comparable accuracy to filter- classifiers on clinician-labeled data, while reducing detection latency. As a trade-off to classical methods, the paper focuses on keeping the complexity of the architecture minimal, to accommodate the on-board computational constraints of implantable pulse generator systems. Clinical relevance-A neural network-based classifier is presented for responsive neurostimulation, with comparable accuracy to classical methods at reduced latency.