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Across the animal kingdom, neural responses in the auditory cortex are suppressed during vocalization, and humans are no exception. A common hypothesis is that suppression increases sensitivity to auditory feedback, enabling the detection of vocalization errors. This hypothesis has been previously confirmed in non-human primates, however a direct link between auditory suppression and sensitivity in human speech monitoring remains elusive. To address this issue, we obtained intracranial electroencephalography (iEEG) recordings from 35 neurosurgical participants during speech production. We first characterized the detailed topography of auditory suppression, which varied across superior temporal gyrus (STG). Next, we performed a delayed auditory feedback (DAF) task to determine whether the suppressed sites were also sensitive to auditory feedback alterations. Indeed, overlapping sites showed enhanced responses to feedback, indicating sensitivity. Importantly, there was a strong correlation between the degree of auditory suppression and feedback sensitivity, suggesting suppression might be a key mechanism that underlies speech monitoring. Further, we found that when participants produced speech with simultaneous auditory feedback, posterior STG was selectively activated if participants were engaged in a DAF paradigm, suggesting that increased attentional load can modulate auditory feedback sensitivity.

Abstract Contextual embeddings, derived from deep language models (DLMs), provide a continuous vectorial representation of language. This embedding space differs fundamentally from the symbolic representations posited by traditional psycholinguistics. We hypothesize that language areas in the human brain, similar to DLMs, rely on a continuous embedding space to represent language. To test this hypothesis, we densely record the neural activity patterns in the inferior frontal gyrus (IFG) of three participants using dense intracranial arrays while they listened to a 30-minute podcast. From these fine-grained spatiotemporal neural recordings, we derive a continuous vectorial representation for each word (i.e., a brain embedding) in each patient. Using stringent zero-shot mapping we demonstrate that brain embeddings in the IFG and the DLM contextual embedding space have common geometric patterns. The common geometric patterns allow us to predict the brain embedding in IFG of a given left-out word based solely on its geometrical relationship to other non-overlapping words in the podcast. Furthermore, we show that contextual embeddings capture the geometry of IFG embeddings better than static word embeddings. The continuous brain embedding space exposes a vector-based neural code for natural language processing in the human brain.

Abstract Background Eating frequency may affect body weight and cardiometabolic health. Intervention trials and observational studies have both indicated that high- and low-frequency eating can be associated with better health outcomes. There are currently no guidelines to inform how to advise healthy adults about how frequently to consume food or beverages. Aim To establish whether restricted- (≤ three meals per day) frequency had a superior effect on markers of cardiometabolic health (primary outcome: weight change) compared to unrestricted-eating (≥ four meals per day) frequency in adults. Methods We searched Medline (Ovid), Embase, CINAHL (EBSCO), Cochrane Central Register of Controlled Trials (CENTRAL), CAB Direct and Web of Science Core Collection electronic databases from inception to 7 June 2022 for clinical trials (randomised parallel or cross-over trials) reporting on the effect of high or low-frequency eating on cardiometabolic health (primary outcome: weight change). Trial interventions had to last for at least two weeks, and had to have been conducted in human adults. Bias was assessed using the Cochrane Risk of Bias tool 2.0. Standardized mean differences (SMD) and 95% confidence intervals were calculated for all outcomes. Certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Results Seventeen reports covering 16 trials were included in the systematic review. Data from five trials were excluded from meta-analysis due to insufficient reporting. 15 of 16 trials were at high risk of bias. There was very low certainty evidence of no difference between high- and low-frequency eating for weight-change (MD: -0.62 kg, CI95: -2.76 to 1.52 kg, p = 0.57). Conclusions There was no discernible advantage to eating in a high- or low-frequency dietary pattern for cardiometabolic health. We cannot advocate for either restricted- or unrestricted eating frequency to change markers of cardiometabolic health in healthy young to middle-aged adults. Protocol registration CRD42019137938.

Abstract Objective In vitro data prompted U.S Food and Drug Administration warnings that lamotrigine, a common sodium channel modulating anti‐seizure medication (NaM‐ASM), could increase the risk of sudden death in patients with structural or ischaemic cardiac disease, however, its implications for Sudden Unexpected Death in Epilepsy (SUDEP) are unclear. Methods This retrospective, nested case–control study identified 101 sudden unexpected death in epilepsy (SUDEP) cases and 199 living epilepsy controls from Epilepsy Monitoring Units (EMUs) in Australia and the USA. Differences in proportions of lamotrigine and NaM‐ASM use were compared between cases and controls at the time of admission, and survival analyses from the time of admission up to 16 years were conducted. Multivariable logistic regression and survival analyses compared each ASM subgroup adjusting for SUDEP risk factors. Results Proportions of cases and controls prescribed lamotrigine (P = 0.166), one NaM‐ASM (P = 0.80), or ≥2NaM‐ASMs (P = 0.447) at EMU admission were not significantly different. Patients taking lamotrigine (adjusted hazard ratio [aHR] = 0.56; P = 0.054), one NaM‐ASM (aHR = 0.8; P = 0.588) or ≥2 NaM‐ASMs (aHR = 0.49; P = 0.139) at EMU admission were not at increased SUDEP risk up to 16 years following admission. Active tonic–clonic seizures at EMU admission associated with >2‐fold SUDEP risk, irrespective of lamotrigine (aHR = 2.24; P = 0.031) or NaM‐ASM use (aHR = 2.25; P = 0.029). Sensitivity analyses accounting for incomplete ASM data at follow‐up suggest undetected changes to ASM use are unlikely to alter our results. Significance This study provides additional evidence that lamotrigine and other NaM‐ASMs are unlikely to be associated with an increased long‐term risk of SUDEP, up to 16 years post‐EMU admission.

Abstract Objective The objectives of this study were to define the clinical and biochemical spectrum of spinal muscular atrophy with progressive myoclonic epilepsy (SMA‐PME) and to determine if aberrant cellular ceramide accumulation could be normalized by enzyme replacement. Methods Clinical features of 6 patients with SMA‐PME were assessed by retrospective chart review, and a literature review of 24 previously published cases was performed. Leukocyte enzyme activity of acid ceramidase was assessed with a fluorescence‐based assay. Skin fibroblast ceramide content and was assessed by high performance liquid chromatography, electrospray ionization tandem mass spectroscopy. Enzyme replacement was assessed using recombinant human acid ceramidase (rhAC) in vitro. Results The six new patients showed the hallmark features of SMA‐PME, with variable initial symptom and age of onset. Five of six patients carried at least one of the recurrent SMA‐PME variants observed in two specific codons of ASAH1. A review of 30 total cases revealed that patients who were homozygous for the most common c.125C > T variant presented in the first decade of life with limb‐girdle weakness as the initial symptom. Sensorineural hearing loss was associated with the c.456A > C variant. Leukocyte acid ceramidase activity varied from 4.1%–13.1% of controls. Ceramide species in fibroblasts were detected and total cellular ceramide content was elevated by 2 to 9‐fold compared to controls. Treatment with rhAC normalized ceramide profiles in cultured fibroblasts to control levels within 48 h. Interpretation This study details the genotype–phenotype correlations observed in SMA‐PME and shows the impact of rhAC to correct the abnormal cellular ceramide profile in cells.

IntroductionAlzheimer's disease (AD) and epilepsy are reciprocally related. Among sporadic AD patients, clinical seizures occur in 10–22% and subclinical epileptiform abnormalities occur in 22–54%. Cognitive deficits, especially short-term memory impairments, occur in most epilepsy patients. Common neurophysiological and molecular mechanisms occur in AD and epilepsy. The choroid plexus undergoes pathological changes in aging, AD, and epilepsy, including decreased CSF turnover, amyloid beta (Aβ), and tau accumulation due to impaired clearance and disrupted CSF amino acid homeostasis. This pathology may contribute to synaptic dysfunction in AD and epilepsy.MethodsWe evaluated control (n = 8), severe AD (n = 8; A3, B3, C3 neuropathology), and epilepsy autopsy cases (n = 12) using laser capture microdissection (LCM) followed by label-free quantitative mass spectrometry on the choroid plexus adjacent to the hippocampus at the lateral geniculate nucleus level.ResultsProteomics identified 2,459 proteins in the choroid plexus. At a 5% false discovery rate (FDR), 616 proteins were differentially expressed in AD vs. control, 1 protein in epilepsy vs. control, and 438 proteins in AD vs. epilepsy. There was more variability in the epilepsy group across syndromes. The top 20 signaling pathways associated with differentially expressed proteins in AD vs. control included cell metabolism pathways; activated fatty acid beta-oxidation (p = 2.00 x 10−7, z = 3.00), and inhibited glycolysis (p = 1.00 x 10−12, z = −3.46). For AD vs. epilepsy, the altered pathways included cell metabolism pathways, activated complement system (p = 5.62 x 10−5, z = 2.00), and pathogen-induced cytokine storm (p = 2.19 x 10−2, z = 3.61). Of the 617 altered proteins in AD and epilepsy vs. controls, 497 (81%) were positively correlated (p < 0.0001, R2 = 0.27).DiscussionWe found altered signaling pathways in the choroid plexus of severe AD cases and many correlated changes in the protein expression of cell metabolism pathways in AD and epilepsy cases. The shared molecular mechanisms should be investigated further to distinguish primary pathogenic changes from the secondary ones. These mechanisms could inform novel therapeutic strategies to prevent disease progression or restore normal function. A focus on dual-diagnosed AD/epilepsy cases, specific epilepsy syndromes, such as temporal lobe epilepsy, and changes across different severity levels in AD and epilepsy would add to our understanding.

IntroductionPrevious case-control studies of sudden unexpected death in epilepsy (SUDEP) patients failed to identify ECG features (peri-ictal heart rate, heart rate variability, corrected QT interval, postictal heart rate recovery, and cardiac rhythm) predictive of SUDEP risk. This implied a need to derive novel metrics to assess SUDEP risk from ECG.MethodsWe applied Single Spectrum Analysis and Independent Component Analysis (SSA-ICA) to remove artifact from ECG recordings. Then cross-frequency phase-phase coupling (PPC) was applied to a 20-s mid-seizure window and a contour of −3 dB coupling strength was determined. The contour centroid polar coordinates, amplitude (alpha) and angle (theta), were calculated. Association of alpha and theta with SUDEP was assessed and a logistic classifier for alpha was constructed.ResultsAlpha was higher in SUDEP patients, compared to non-SUDEP patients (p < 0.001). Theta showed no significant difference between patient populations. The receiver operating characteristic (ROC) of a logistic classifier for alpha resulted in an area under the ROC curve (AUC) of 94% and correctly classified two test SUDEP patients.DiscussionThis study develops a novel metric alpha, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.

A measurement of PL intensity vs. excitation density, with the help of Raman, is shown capable of determine nearly all pertinent parameters of radiative and nonradiative recombination in a semiconductor.

Abstract Objectives Medical cannabis formulations with cannabidiol (CBD) and delta‐9‐tetrahydrocannabinol (THC) are widely used to treat epilepsy. We studied the safety and efficacy of two formulations. Methods We prospectively observed 29 subjects (12 to 46 years old) with treatment‐resistant epilepsies (11 Lennox–Gastaut syndrome; 15 with focal or multifocal epilepsy; three generalized epilepsy) were treated with medical cannabis (1THC:20CBD and/or 1THC:50CBD; maximum of 6 mg THC/day) for ≥24 weeks. The primary outcome was change in convulsive seizure frequency from the pre‐treatment baseline to the stable optimal dose phase. Results There were no significant differences during treatment on stable maximal doses for convulsive seizure frequency, seizure duration, postictal duration, or use of rescue medications compared to baseline. No benefits were seen for behavioral disorders or sleep duration; there was a trend for more frequent bowel movements compared to baseline. Ten adverse events occurred in 6/29 patients, all were transient and most unrelated to study medication. No serious adverse events were related to study medication. Interpretation Our prospective observational study of two high‐CBD/low‐THC formulations found no evidence of efficacy in reducing seizures, seizure duration, postictal duration, or rescue medication use. Behavioral disorders or sleep duration was unchanged. Study medication was generally well tolerated. The doses of CBD used were lower than prior studies. Randomized trials with larger cohorts are needed, but we found no evidence of efficacy for two CBD:THC products in treating epilepsy, sleep, or behavior in our population.

Priors learnt from lifetime experiences influence perception. The authors show that when perception is congruent with a long-term prior, there is increased top-down input in the ventral visual stream, whereas bottom-up input is enhanced when perception is incongruent with prior.

When listening to a story, humans learn about its structure and content. Here the authors reveal the neural processes behind episodic memory and predictive recall at a fine temporal scale in this naturalistic setting

In analyzing the neural correlates of naturalistic and unstructured behaviors, features of neural activity that are ignored in a trial-based experimental paradigm can be more fully studied and investigated. Here, we analyze neural activity from two patients using electrocorticography (ECoG) and stereo-electroencephalography (sEEG) recordings, and reveal that multiple neural signal characteristics exist that discriminate between unstructured and naturalistic behavioral states such as "engaging in dialogue" and "using electronics". Using the high gamma amplitude as an estimate of neuronal firing rate, we demonstrate that behavioral states in a naturalistic setting are discriminable based on long-term mean shifts, variance shifts, and differences in the specific neural activity's covariance structure. Both the rapid and slow changes in high gamma band activity separate unstructured behavioral states. We also use Gaussian process factor analysis (GPFA) to show the existence of salient spatiotemporal features with variable smoothness in time. Further, we demonstrate that both temporally smooth and stochastic spatiotemporal activity can be used to differentiate unstructured behavioral states. This is the first attempt to elucidate how different neural signal features contain information about behavioral states collected outside the conventional experimental paradigm.

Abstract Objective Ataluren is a compound that reads through premature stop codons and increases protein expression by increasing translation without modifying transcription or mRNA stability. We investigated the safety and efficacy of ataluren in children with nonsense variants causing Dravet Syndrome (DS) and CDKL5 Deficiency Syndrome (CDD). Methods This single‐center double‐blind, placebo‐controlled crossover trial randomized subjects to receive ataluren or placebo for 12 weeks (period 1), a 4‐week washout, then another 12‐week treatment (period 2). The primary outcome was ataluren’s safety profile. The secondary outcome measures were (1) changes in convulsive and/or drop seizure frequency and (2) changes in minor seizure types during ataluren treatment compared to placebo. Exploratory objectives assessed changes in cognitive, motor, and behavioral function as well as quality of life during ataluren therapy. Results We enrolled seven subjects with DS and eight subjects with CDD. Three treatment‐related adverse events (AE) occurred during the blinded phases. Two subjects withdrew due to AE. Ataluren was not effective in reducing seizure frequency or improving cognitive, motor, or behavioral function or quality of life in subjects with either DS or CDD due to nonsense variants. Limitations included a small sample size and 12‐week treatment phase, possibly too short to identify a disease‐modifying effect. Significance There was no difference between ataluren and placebo; ataluren is not an effective therapy for seizures or other disorders in children with DS or CDD due to nonsense variants. There were no drug‐related serious AE during the double‐blind period, consistent with ataluren’s favorable safety profile in larger studies. (Funded by Epilepsy Foundation, Dravet Syndrome Foundation, Finding A Cure for Seizures and Epilepsy and PTC Therapeutics, Inc.; ClinicalTrials.gov number, NCT02758626).

Epilepsy affects more than three million people in the United States. In approximately one-third of this population, anti-seizure medications do not control seizures. Many patients pursue surgical treatment that can include a procedure involving the implantation of electrodes for intracranial monitoring of seizure activity. For these cases, accurate mapping of the implanted electrodes on a patient’s brain is crucial in planning the ultimate surgical treatment. Traditionally, electrode mapping results are presented in static figures that do not allow for dynamic interactions and visualizations. In collaboration with a clinical research team at a Level 4 Epilepsy Center, we developed N-Tools-Browser, a web-based software using WebGL and the X-Toolkit (XTK), to help clinicians interactively visualize the location and functional properties of implanted intracranial electrodes in 3D. Our software allows the user to visualize the seizure focus location accurately and simultaneously display functional characteristics (e.g., results from electrical stimulation mapping). Different visualization modes enable the analysis of multiple electrode groups or individual anatomical locations. We deployed a prototype of N-Tools-Browser for our collaborators at the New York University Grossman School of Medicine Comprehensive Epilepsy Center. Then, we evaluated its usefulness with domain experts on clinical cases.

ObjectiveSudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls.MethodsThis multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve.ResultsThe logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73–0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction.ConclusionsOur results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.

ImportanceNon-communicable chronic diseases (NCDs) such as obesity, type 2 diabetes, heart disease, and cancer were rare among non-western populations with traditional diets and lifestyles. As populations transitioned toward industrialized diets and lifestyles, NCDs developed.ObjectiveWe performed a systematic literature review to examine the effects of diet and lifestyle transitions on NCDs.Evidence ReviewWe identified 22 populations that underwent a nutrition transition, eleven of which had sufficient data. Of these, we chose four populations with diverse geographies, diets and lifestyles who underwent a dietary and lifestyle transition and explored the relationship between dietary changes and health outcomes. We excluded populations with features overlapping with selected populations or with complicating factors such as inadequate data, subgroups, and different study methodologies over different periods. The selected populations were Yemenite Jews, Tokelauans, Tanushimaru Japanese, and Maasai. We also review transition data from seven excluded populations (Pima, Navajo, Aboriginal Australians, South African Natal Indians and Zulu speakers, Inuit, and Hadza) to assess for bias.FindingsThe three groups that replaced saturated fats (SFA) from animal (Yemenite Jews, Maasai) or plants (Tokelau) with refined carbohydrates had negative health outcomes (e.g., increased obesity, diabetes, heart disease). Yemenites reduced SFA consumption by >40% post-transition but men's BMI increased 19% and diabetes increased ~40-fold. Tokelauans reduced fat, dramatically reduced SFA, and increased sugar intake: obesity and diabetes rose. The Tanushimaruans transitioned to more fats and less carbohydrates and used more anti-hypertensive medications; stroke and breast cancer declined while heart disease was stable. The Maasai transitioned to lower fat, SFA and higher carbohydrates and had increased BMI and diabetes. Similar patterns were observed in the seven other populations.ConclusionThe nutrient category most strongly associated with negative health outcomes – especially obesity and diabetes – was sugar (increased 600–650% in Yemenite Jews and Tokelauans) and refined carbohydrates (among Maasai, total carbohydrates increased 39% in men and 362% in women), while increased calories was less strongly associated with these disorders. Across 11 populations, NCDs were associated with increased refined carbohydrates more than increased calories, reduced activity or other factors, but cannot be attributed to SFA or total fat consumption.

BackgroundTuberous sclerosis complex (TSC) and some focal cortical dysplasias (FCDs) are associated with dysfunctional mTOR signaling, resulting in increased cell growth and ribosomal S6 protein phosphorylation (phospho-S6). mTOR inhibitors can reduce TSC tumor growth and seizure frequency, and preclinical FCD studies indicate seizure suppression. This pilot study evaluated safety of mTOR inhibitor everolimus in treatment resistant (failure of >2 anti-seizure medications) TSC and FCD patients undergoing surgical resection and to assess mTOR signaling and molecular pathways.Methods and findingsWe evaluated everolimus in 14 treatment resistant epilepsy patients undergoing surgical resection (4.5 mg/m2 daily for 7 days; n = 4 Active, mean age 18.3 years, range 4-26; n = 10, Control, mean age 13.1, range 3-45). Everolimus was well tolerated. Mean plasma everolimus in Active participants were in target range (12.4 ng/ml). Brain phospho-S6 was similar in Active and Control participants with a lower trend in Active participants, with Ser235/236 1.19-fold (p = 0.67) and Ser240/244 1.15-fold lower (p = 0.66). Histologically, Ser235/236 was 1.56-fold (p = 0.37) and Ser240/244 was 5.55-fold lower (p = 0.22). Brain proteomics identified 11 proteins at ConclusionsShort-term everolimus before epilepsy surgery in TSC and FCD resulted in no adverse events and trending lower mTOR signaling (phospho-S6). Future studies should evaluate implications of our findings, including coagulation system activation and everolimus efficacy in FCD, in larger studies with long-term treatment to better understand molecular and clinical effects.Clinical trials registrationClinicalTrials.gov NCT02451696.

Abstract There have been few studies of agreement between seizure descriptions obtained from patients and observers. We investigated 220 patients and observers who completed structured questionnaires about patients’ semiological seizure features at the initial clinical visit. Inter‐rater reliability was assessed using Cohen’s kappa and indices of positive and negative agreement. Patients and observers had excellent agreement on the presence of memory impairment and generalized shaking and stiffness during seizures. In addition, patients under‐reported seizure descriptions more easily observed externally, whereas observers under‐reported change in patient location at seizure end. These findings may guide interpretation of clinical histories obtain in epilepsy care.

Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (EDA) has been shown effective to detect primarily and secondarily generalized tonic-clonic seizures, here termed as convulsive seizures (CS). A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm. Here we present its performance on pediatric and adult patients in epilepsy monitoring units (EMUs).Methods: Patients diagnosed with epilepsy participated in a prospective multi-center clinical study. Three board-certified neurologists independently labeled CS from video-EEG. The Detection Algorithm was evaluated in terms of Sensitivity and false alarm rate per 24 h-worn (FAR) on all the data and on only periods of rest. Performance were analyzed also applying the Detection Algorithm offline, with a less sensitive but more specific parameters configuration (“Active mode”).Results: Data from 152 patients (429 days) were used for performance evaluation (85 pediatric aged 6–20 years, and 67 adult aged 21–63 years). Thirty-six patients (18 pediatric) experienced a total of 66 CS (35 pediatric). The Sensitivity (corrected for clustered data) was 0.92, with a 95% confidence interval (CI) of [0.85-1.00] for the pediatric population, not significantly different (p > 0.05) from the adult population's Sensitivity (0.94, CI: [0.89–1.00]). The FAR on the pediatric population was 1.26 (CI: [0.87–1.73]), higher (p < 0.001) than in the adult population (0.57, CI: [0.36–0.81]). Using the Active mode, the FAR decreased by 68% while reducing Sensitivity to 0.95 across the population. During rest periods, the FAR's were 0 for all patients, lower than during activity periods (p < 0.001).Conclusions: Performance complies with FDA's requirements of a lower bound of CI for Sensitivity higher than 0.7 and of a FAR lower than 2, for both age groups. The pediatric FAR was higher than the adult FAR, likely due to higher pediatric activity. The high Sensitivity and precision (having no false alarms) during sleep might help mitigate SUDEP risk by summoning caregiver intervention. The Active mode may be advantageous for some patients, reducing the impact of the FAR on daily life. Future work will examine the performance and usability outside of EMUs.

Abstract We report 13 SUDEP cases in the North American SUDEP Registry with both psychogenic nonepileptic seizures (PNES) and epileptic seizures (ES) among a consecutive series of 231 cases (excluding epileptic encephalopathies). On average, cases of PNES + ES died at a younger age (23 ± 11 years) than the ES‐only cohort (30 ± 14 years), and died an average of 3 years after PNES diagnosis. We found no statistically significant confounding cardiac, respiratory, or psychiatric comorbidities and equal rates of anti‐seizure medication adherence, although there was a trend for higher rates of psychiatric disorders in the PNES group. Our findings confirm that patients with comorbid ES and PNES can die from SUDEP and that there may be a high‐risk period after the diagnosis of PNES is made in patients with comorbid ES. Such patients should be closely monitored and provided with coordinated care of both their epilepsy and psychiatric disorder(s).

Rationale: Currently, there is some ambiguity over the role of postictal generalized electro-encephalographic suppression (PGES) as a biomarker in sudden unexpected death in epilepsy (SUDEP). Visual analysis of PGES, known to be subjective, may account for this. In this study, we set out to perform an analysis of PGES presence and duration using a validated signal processing tool, specifically to examine the association between PGES and seizure features previously reported to be associated with visually analyzed PGES.Methods: This is a prospective, multicenter epilepsy monitoring study of autonomic and breathing biomarkers of SUDEP in adult patients with intractable epilepsy. We studied videoelectroencephalogram (vEEG) recordings of generalized convulsive seizures (GCS) in a cohort of patients in whom respiratory and vEEG recording were carried out during the evaluation in the epilepsy monitoring unit. A validated automated EEG suppression detection tool was used to determine presence and duration of PGES.Results: We studied 148 GCS in 87 patients. PGES occurred in 106/148 (71.6%) seizures in 70/87 (80.5%) of patients. PGES mean duration was 38.7 ± 23.7 (37; 1–169) seconds. Presence of tonic phase during GCS, including decerebration, decortication and hemi-decerebration, were 8.29 (CI 2.6–26.39, p = 0.0003), 7.17 (CI 1.29–39.76, p = 0.02), and 4.77 (CI 1.25–18.20, p = 0.02) times more likely to have PGES, respectively. In addition, presence of decerebration (p = 0.004) and decortication (p = 0.02), older age (p = 0.009), and hypoxemia duration (p = 0.03) were associated with longer PGES durations.Conclusions: In this study, we confirmed observations made with visual analysis, that presence of tonic phase during GCS, longer hypoxemia, and older age are reliably associated with PGES. We found that of the different types of tonic phase posturing, decerebration has the strongest association with PGES, followed by decortication, followed by hemi-decerebration. This suggests that these factors are likely indicative of seizure severity and may or may not be associated with SUDEP. An automated signal processing tool enables objective metrics, and may resolve apparent ambiguities in the role of PGES in SUDEP and seizure severity studies.

Rationale: Seizure clusters may be related to Sudden Unexpected Death in Epilepsy (SUDEP). Two or more generalized convulsive seizures (GCS) were captured during video electroencephalography in 7/11 (64%) patients with monitored SUDEP in the MORTEMUS study. It follows that seizure clusters may be associated with epilepsy severity and possibly with SUDEP risk. We aimed to determine if electroclinical seizure features worsen from seizure to seizure within a cluster and possible associations between GCS clusters, markers of seizure severity, and SUDEP risk.Methods: Patients were consecutive, prospectively consented participants with drug-resistant epilepsy from a multi-center study. Seizure clusters were defined as two or more GCS in a 24-h period during the recording of prolonged video-electroencephalography in the Epilepsy monitoring unit (EMU). We measured heart rate variability (HRV), pulse oximetry, plethysmography, postictal generalized electroencephalographic suppression (PGES), and electroencephalography (EEG) recovery duration. A linear mixed effects model was used to study the difference between the first and subsequent seizures, with a level of significance set at p < 0.05.Results: We identified 112 GCS clusters in 105 patients with 285 seizures. GCS lasted on average 48.7 ± 19 s (mean 49, range 2–137). PGES emerged in 184 (64.6%) seizures and postconvulsive central apnea (PCCA) was present in 38 (13.3%) seizures. Changes in seizure features from seizure to seizure such as seizure and convulsive phase durations appeared random. In grouped analysis, some seizure features underwent significant deterioration, whereas others improved. Clonic phase and postconvulsive central apnea (PCCA) were significantly shorter in the fourth seizure compared to the first. By contrast, duration of decerebrate posturing and ictal central apnea were longer. Four SUDEP cases in the cluster cohort were reported on follow-up.Conclusion: Seizure clusters show variable changes from seizure to seizure. Although clusters may reflect epilepsy severity, they alone may be unrelated to SUDEP risk. We suggest a stochastic nature to SUDEP occurrence, where seizure clusters may be more likely to contribute to SUDEP if an underlying progressive tendency toward SUDEP has matured toward a critical SUDEP threshold.

Circular RNAs (circRNAs) regulate mRNA translation by binding to microRNAs (miRNAs), and their expression is altered in diverse disorders, including cancer, cardiovascular disease, and Parkinson’s disease. Here, we compare circRNA expression patterns in the temporal cortex and hippocampus of patients with pharmacoresistant mesial temporal lobe epilepsy (MTLE) and healthy controls. Nine circRNAs showed significant differential expression, including circRNA-HOMER1, which is expressed in synapses. Further, we identified miRNA binding sites within the sequences of differentially expressed (DE) circRNAs; expression levels of mRNAs correlated with changes in complementary miRNAs. Gene set enrichment analysis of mRNA targets revealed functions in heterocyclic compound binding, regulation of transcription, and signal transduction, which maintain the structure and function of hippocampal neurons. The circRNA–miRNA–mRNA interaction networks illuminate the molecular changes in MTLE, which may be pathogenic or an effect of the disease or treatments and suggests that DE circRNAs and associated miRNAs may be novel therapeutic targets.

Our understanding of mesial temporal lobe epilepsy (MTLE), one of the most common form of drug-resistant epilepsy in humans, is derived mainly from clinical, imaging, and physiological data from humans and animal models. High-throughput gene expression studies of human MTLE have the potential to uncover molecular changes underlying disease pathogenesis along with novel therapeutic targets. Using RNA- and small RNA-sequencing in parrallel, we explored differentially expressed genes in the hippocampus and cortex of MTLE patients who had undergone surgical resection and non-epileptic controls. We identified differentially expressed genes in the hippocampus of MTLE patients and differentially expressed small RNAs across both the cortex and hippocampus. We found significant enrichment for astrocytic and microglial genes among up-regulated genes, and down regulation of neuron specific genes in the hippocampus of MTLE patients. The transcriptome profile of the small RNAs reflected disease state more robustly than mRNAs, even across brain regions which show very little pathology. While mRNAs segregated predominately by brain region for MTLE and controls, small RNAs segregated by disease state. In particular, our data suggest that specific miRNAs (e.g., let-7b-3p and let-7c-3p) may be key regulators of multiple pathways related to MTLE pathology. Further, we report a strong association of other small RNA species with MTLE pathology. As such we have uncovered novel elements that may contribute to the establishment and progression of MTLE pathogenesis and that could be leveraged as therapeutic targets.

Reliable posture labels in hospital environments can augment research studies on neural correlates to natural behaviors and clinical applications that monitor patient activity. However, many existing pose estimation frameworks are not calibrated for these unpredictable settings. In this paper, we propose a semi-automated approach for improving upper-body pose estimation in noisy clinical environments, whereby we adapt and build around an existing joint tracking framework to improve its robustness to environmental uncertainties. The proposed framework uses subject-specific convolutional neural network models trained on a subset of a patient's RGB video recording chosen to maximize the feature variance of each joint. Furthermore, by compensating for scene lighting changes and by refining the predicted joint trajectories through a Kalman filter with fitted noise parameters, the extended system yields more consistent and accurate posture annotations when compared with the two state-of-the-art generalized pose tracking algorithms for three hospital patients recorded in two research clinics.

Transcranial alternating current stimulation (tACS) has been proposed to enhance neural rhythms supporting memory. Here, the authors leverage human intracranial recordings to show that low-frequency tACS does not entrain key rhythms in non-REM sleep or resting wakefulness.

Introduction: Peri-ictal breathing dysfunction was proposed as a potential mechanism for SUDEP. We examined the incidence and risk factors for both ictal (ICA) and post-convulsive central apnea (PCCA) and their relationship with potential seizure severity biomarkers (i. e., post-ictal generalized EEG suppression (PGES) and recurrence.Methods: Prospective, multi-center seizure monitoring study of autonomic, and breathing biomarkers of SUDEP in adults with intractable epilepsy and monitored seizures. Video EEG, thoraco-abdominal excursions, capillary oxygen saturation, and electrocardiography were analyzed. A subgroup analysis determined the incidences of recurrent ICA and PCCA in patients with ≥2 recorded seizures. We excluded status epilepticus and obscured/unavailable video. Central apnea (absence of thoracic-abdominal breathing movements) was defined as ≥1 missed breath, and ≥5 s. ICA referred to apnea preceding or occurring along with non-convulsive seizures (NCS) or apnea before generalized convulsive seizures (GCS).Results: We analyzed 558 seizures in 218 patients (130 female); 321 seizures were NCS and 237 were GCS. ICA occurred in 180/487 (36.9%) seizures in 83/192 (43.2%) patients, all with focal epilepsy. Sleep state was related to presence of ICA [RR 1.33, CI 95% (1.08–1.64), p = 0.008] whereas extratemporal epilepsy was related to lower incidence of ICA [RR 0.58, CI 95% (0.37–0.90), p = 0.015]. ICA recurred in 45/60 (75%) patients. PCCA occurred in 41/228 (18%) of GCS in 30/134 (22.4%) patients, regardless of epilepsy type. Female sex [RR 11.30, CI 95% (4.50–28.34), p < 0.001] and ICA duration [RR 1.14 CI 95% (1.05–1.25), p = 0.001] were related to PCCA presence, whereas absence of PGES was related to absence of PCCA [0.27, CI 95% (0.16–0.47), p < 0.001]. PCCA duration was longer in males [HR 1.84, CI 95% (1.06–3.19), p = 0.003]. In 9/17 (52.9%) patients, PCCA was recurrent.Conclusion: ICA incidence is almost twice the incidence of PCCA and is only seen in focal epilepsies, as opposed to PCCA, suggesting different pathophysiologies. ICA is likely to be a recurrent semiological phenomenon of cortical seizure discharge, whereas PCCA may be a reflection of brainstem dysfunction after GCS. Prolonged ICA or PCCA may, respectively, contribute to SUDEP, as evidenced by two cases we report. Further prospective cohort studies are needed to validate these hypotheses.

This paper analyzes the dynamic stability of moral codes in a two population trust game. Guided by a moral code, members of one population, the Trustors, are willing to punish members of the other population, the Trustees, who defect. Under replicator dynamics, adherence to the moral code has unstable oscillations around an interior Nash Equilibrium (NE), but under smoothed best response dynamics we obtain convergence to Quantal Response Equilibrium (QRE).

Transcranial electric stimulation aims to stimulate the brain by applying weak electrical currents at the scalp. However, the magnitude and spatial distribution of electric fields in the human brain are unknown. We measured electric potentials intracranially in ten epilepsy patients and estimated electric fields across the entire brain by leveraging calibrated current-flow models. When stimulating at 2 mA, cortical electric fields reach 0.8 V/m, the lower limit of effectiveness in animal studies. When individual whole-head anatomy is considered, the predicted electric field magnitudes correlate with the recorded values in cortical (r = 0.86) and depth (r = 0.88) electrodes. Accurate models require adjustment of tissue conductivity values reported in the literature, but accuracy is not improved when incorporating white matter anisotropy or different skull compartments. This is the first study to validate and calibrate current-flow models with in vivo intracranial recordings in humans, providing a solid foundation to target stimulation and interpret clinical trials.

Environmental stochasticity and climate affect outcomes in evolutionary games, which can thereby affect biological diversity. Our maximum likelihood (ML) estimates of replicator dynamics for morph frequency data from control (25 years) and three experimentally perturbed populations (14 years) of side-blotched lizards yield a 3 × 3 payoff matrix in the generalized Rock-Paper-Scissors family; it has intransitive best replies, and each strategy is its own worst reply. ML estimates indicate significant interactive effects of density and temperature on morph frequency. Implied dynamics feature a powerful interior attractor and recover (for the first time) observed 4-5 year oscillations. Our evolutionary experiment on morph frequency confirms that oscillations are driven by frequency dependent selection, but climate entrains the cycles across the perturbed and control populations within 10 generations. Applying the model across the species range, we find that climate also accounts for morph fixation and mating system diversity, suggesting climate may similarly impact ecosystem diversity.

It has come to our attention that we did not specify whether the stimulation magnitudes we report in this Article are peak amplitudes or peak-to-peak. All references to intensity given in mA in the manuscript refer to peak-to-peak amplitudes, except in Fig. 2, where the model is calibrated to 1 mA peak amplitude, as stated. In the original version of the paper we incorrectly calibrated the computational models to 1 mA peak-to-peak, rather than 1 mA peak amplitude. This means that we divided by a value twice as large as we should have. The correct estimated fields are therefore twice as large as shown in the original Fig. 2 and Supplementary Figure 11. The corrected figures are now properly calibrated to 1 mA peak amplitude. Furthermore, the sentence in the first paragraph of the Results section ‘Intensity ranged from 0.5 to 2.5 mA (current density 0.125–0.625 mA mA/cm2), which is stronger than in previous reports’, should have read ‘Intensity ranged from 0.5 to 2.5 mA peak to peak (peak current density 0.0625–0.3125 mA/cm2), which is stronger than in previous reports.’ These errors do not affect any of the Article’s conclusions.

Exosomes are nanometer-scale, cell-derived vesicles that contain various molecules including nucleic acids, proteins, and lipids. These vesicles can release their cargo into adjacent or distant cells and mediate intercellular communication and cellular function. Here we examined the regulation of epithelial sodium channels in mpkCCD cells and distal tubule Xenopus 2F3 cells by exosomes isolated from proximal tubule LLC-PK1 cells. Cultured mpkCCD cells were stained with CTX coupled to a green fluorophore in order to label the cell membranes and freshly isolated exosomes from LLC-PK1 cells were labeled with the red lipophilic dye PKH26 in order to visualize uptake of exosomes into the cells. Single-channel patch clamp recordings showed the open probability of ENaC in Xenopus 2F3 cells and in freshly isolated split-open tubules decreased in response to exogenous application of exosomes derived from LLC-PK1 proximal tubule cells. Active GAPDH was identified within exosomes derived from proximal tubule LLC-PK1 cells. The effect on ENaC activity in Xenopus 2F3 cells was blunted after application of exosomes transfected with the GAPDH inhibitor heptelidic acid. Also, we show GAPDH and ENaC subunits associate in mpkCCD cells. These studies examine a potential role for exosomes in the regulation of ENaC activity and examine a possible mechanism for communication from proximal tubule cells to distal tubule and collecting duct cells.

Horno psicológicus. Entrevista a Robert Castel