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ObjectiveSomatic variants are a recognized cause of epilepsy-associated focal malformations of cortical development (MCD). We hypothesized that somatic variants may underlie a wider range of focal epilepsy, including nonlesional focal epilepsy (NLFE). Through genetic analysis of brain tissue, we evaluated the role of somatic variation in focal epilepsy with and without MCD.MethodsWe identified somatic variants through high-depth exome and ultra-high-depth candidate gene sequencing of DNA from epilepsy surgery specimens and leukocytes from 18 individuals with NLFE and 38 with focal MCD.ResultsWe observed somatic variants in 5 cases in SLC35A2, a gene associated with glycosylation defects and rare X-linked epileptic encephalopathies. Nonsynonymous variants in SLC35A2 were detected in resected brain, and absent from leukocytes, in 3 of 18 individuals (17%) with NLFE, 1 female and 2 males, with variant allele frequencies (VAFs) in brain-derived DNA of 2 to 14%. Pathologic evaluation revealed focal cortical dysplasia type Ia (FCD1a) in 2 of the 3 NLFE cases. In the MCD cohort, nonsynonymous variants in SCL35A2 were detected in the brains of 2 males with intractable epilepsy, developmental delay, and magnetic resonance imaging suggesting FCD, with VAFs of 19 to 53%; Evidence for FCD was not observed in either brain tissue specimen.InterpretationWe report somatic variants in SLC35A2 as an explanation for a substantial fraction of NLFE, a largely unexplained condition, as well as focal MCD, previously shown to result from somatic mutation but until now only in PI3K-AKT-mTOR pathway genes. Collectively, our findings suggest a larger role than previously recognized for glycosylation defects in the intractable epilepsies. Ann Neurol 2018.

Animal studies support the hypothesis that in slow-wave sleep, replay of waking neocortical activity under hippocampal guidance leads to memory consolidation. However, no intracranial electrophysiological evidence for replay exists in humans. We identified consistent sequences of population firing peaks across widespread cortical regions during complete waking periods. The occurrence of these "Motifs" were compared between sleeps preceding the waking period ("Sleep-Pre") when the Motifs were identified, and those following ("Sleep-Post"). In all subjects, the majority of waking Motifs (most of which were novel) had more matches in Sleep-Post than in Sleep-Pre. In rodents, hippocampal replay occurs during local sharp-wave ripples, and the associated neocortical replay tends to occur during local sleep spindles and down-to-up transitions. These waves may facilitate consolidation by sequencing cell-firing and encouraging plasticity. Similarly, we found that Motifs were coupled to neocortical spindles, down-to-up transitions, theta bursts, and hippocampal sharp-wave ripples. While Motifs occurring during cognitive task performance were more likely to have more matches in subsequent sleep, our studies provide no direct demonstration that the replay of Motifs contributes to consolidation. Nonetheless, these results confirm a core prediction of the dominant neurobiological theory of human memory consolidation.

Neural responses in visual cortex adapt to prolonged and repeated stimuli. While adaptation occurs across the visual cortex, it is unclear how adaptation patterns and computational mechanisms differ across the visual hierarchy. Here we characterize two signatures of short-term neural adaptation in time-varying intracranial electroencephalography (iEEG) data collected while participants viewed naturalistic image categories varying in duration and repetition interval. Ventral- and lateral-occipitotemporal cortex exhibit slower and prolonged adaptation to single stimuli and slower recovery from adaptation to repeated stimuli compared to V1-V3. For category-selective electrodes, recovery from adaptation is slower for preferred than non-preferred stimuli. To model neural adaptation we augment our delayed divisive normalization (DN) model by scaling the input strength as a function of stimulus category, enabling the model to accurately predict neural responses across multiple image categories. The model fits suggest that differences in adaptation patterns arise from slower normalization dynamics in higher visual areas interacting with differences in input strength resulting from category selectivity. Our results reveal systematic differences in temporal adaptation of neural population responses between lower and higher visual brain areas and show that a single computational model of history-dependent normalization dynamics, fit with area-specific parameters, accounts for these differences. Author summary: Neural responses in visual cortex adapt over time, with reduced responses to prolonged and repeated stimuli. Here, we examine how adaptation patterns differ across the visual hierarchy in neural responses recorded from human visual cortex with high temporal and spatial precision. To identify possible neural computations underlying short-term adaptation, we fit the response time courses using a temporal divisive normalization model. The model accurately predicts prolonged and repeated responses in lower and higher visual areas, and reveals differences in temporal adaptation between visual areas and stimulus categories. Our model suggests that differences in adaptation patterns result from differences in divisive normalization dynamics. Our findings shed light on how information is integrated in the brain on a millisecond-time scale and offer an intuitive framework to study the emergence of neural dynamics across brain areas and stimuli. [ABSTRACT FROM AUTHOR]

Introduction: For drug resistant epilepsy patients who are either not candidates for resective surgery or have already failed resective surgery, neuromodulation is a promising option. Neuromodulatory approaches include responsive neurostimulation (RNS), deep brain stimulation (DBS), and vagal nerve stimulation (VNS). Thalamocortical circuits are involved in both generalized and focal onset seizures. This paper explores the use of RNS in the centromedian nucleus of the thalamus (CMN) and in the anterior thalamic nucleus (ANT) of patients with drug resistant epilepsy. Methods: This is a retrospective multicenter study from seven different epilepsy centers in the United States. Patients that had unilateral or bilateral thalamic RNS leads implanted in the CMN or ANT for at least 6 months were included. Primary objectives were to describe the implant location and determine changes in the frequency of disabling seizures at 6 months, 1 year, 2 years, and > 2 years. Secondary objectives included documenting seizure free periods, anti-seizure medication regimen changes, stimulation side effects, and serious adverse events. In addition, the global clinical impression scale was completed. Results: Twelve patients had at least one lead placed in the CMN, and 13 had at least one lead placed in the ANT. The median baseline seizure frequency was 15 per month. Overall, the median seizure reduction was 33% at 6 months, 55% at 1 year, 65% at 2 years, and 74% at >2 years. Seizure free intervals of at least 3 months occurred in nine patients. Most patients (60%, 15/25) did not have a change in anti-seizure medications post RNS placement. Two serious adverse events were recorded, one related to RNS implantation. Lastly, overall functioning seemed to improve with 88% showing improvement on the global clinical impression scale. Discussion: Meaningful seizure reduction was observed in patients who suffer from drug resistant epilepsy with unilateral or bilateral RNS in either the ANT or CMN of the thalamus. Most patients remained on their pre-operative anti-seizure medication regimen. The device was well tolerated with few side effects. There were rare serious adverse events. Most patients showed an improvement in global clinical impression scores. [ABSTRACT FROM AUTHOR]

BackgroundDespite the increasing interest in sex differences in disease manifestations and responses to treatment, very few data are available on sex differences in seizure types and semiology. The Epilepsy Phenome/Genome Project (EPGP) is a large-scale, multi-institutional, collaborative study that aims to create a comprehensive repository of detailed clinical information and DNA samples from a large cohort of people with epilepsy. We used this well-characterized cohort to explore differences in seizure types as well as focal seizure symptoms between males and females.MethodsWe reviewed the EPGP database and identified individuals with generalized epilepsy of unknown etiology (GE) (n = 760; female: 446, male: 314), nonacquired focal epilepsy (NAFE) (n = 476; female: 245, male: 231), or both (n = 64; female: 33, male: 31). Demographic data along with characterization of seizure type and focal seizure semiologies were examined.ResultsIn GE, males reported atonic seizures more frequently than females (6.5% vs. 1.7%; p < 0.001). No differences were observed in other generalized seizure types. In NAFE, no sex differences were seen for seizure types with or without alteration of consciousness or progression to secondary generalization. Autonomic (16.4% vs. 26.6%; p = 0.005), psychic (26.7% vs. 40.3%; p = 0.001), and visual (10.3% vs. 19.9%; p = 0.002) symptoms were more frequently reported in females than males. Specifically, of psychic symptoms, more females than males endorsed déjà vu (p = 0.001) but not forced thoughts, derealization/depersonalization, jamais vu, or fear. With corrections for multiple comparisons, there were no significant differences in aphasic, motor, somatosensory, gustatory, olfactory, auditory, vertiginous, or ictal headache symptoms between sexes.ConclusionsSignificant differences between the sexes were observed in the reporting of atonic seizures, which were more common in males with GE, and for autonomic, visual, and psychic symptoms associated with NAFE, which were more common in females.

ObjectiveWe studied the frequency of auras in generalized epilepsy (GE) using a detailed semistructured diagnostic interview.MethodsIn this cross-sectional study, participants with GE were drawn from the Epilepsy Phenome/Genome Project (EPGP). Responses to the standardized diagnostic interview regarding tonic-clonic (grand mal) seizures were then examined. This questionnaire initially required participants to provide their own description of any subjective phenomena before their "grand mal seizures." Participants who provided answers to these questions were considered to have an aura. All participants were then systematically queried regarding a list of specific symptoms occurring before grand mal seizures, using structured (closed-ended) questions.ResultsSeven hundred ninety-eight participants with GE were identified, of whom 530 reported grand mal seizures. Of these, 112 (21.3%) reported auras in response to the open-ended question. Analysis of responses to the closed-ended questions suggested that 341 participants (64.3%) experienced at least one form of aura.ConclusionsAuras typically associated with focal epilepsy were reported by a substantial proportion of EPGP subjects with GE. This finding may support existing theories of cortical and subcortical generators of GE with variable spread patterns. Differences between responses to the open-ended question and closed-ended questions may also reflect clinically relevant variation in patient responses to history-taking and surveys. Open-ended questions may underestimate the prevalence of specific types of auras and may be in part responsible for the underrecognition of auras in GE. In addition, structured questions may influence participants, possibly leading to a greater representation of symptoms.

Objective: This study was undertaken to conduct external validation of previously published epilepsy surgery prediction tools using a large independent multicenter dataset and to assess whether these tools can stratify patients for being operated on and for becoming free of disabling seizures (International League Against Epilepsy stage 1 and 2). Methods: We analyzed a dataset of 1562 patients, not used for tool development. We applied two scales: Epilepsy Surgery Grading Scale (ESGS) and Seizure Freedom Score (SFS); and two versions of Epilepsy Surgery Nomogram (ESN): the original version and the modified version, which included electroencephalographic data. For the ESNs, we used calibration curves and concordance indexes. We stratified the patients into three tiers for assessing the chances of attaining freedom from disabling seizures after surgery: high (ESGS = 1, SFS = 3–4, ESNs > 70%), moderate (ESGS = 2, SFS = 2, ESNs = 40%–70%), and low (ESGS = 2, SFS = 0–1, ESNs < 40%). We compared the three tiers as stratified by these tools, concerning the proportion of patients who were operated on, and for the proportion of patients who became free of disabling seizures. Results: The concordance indexes for the various versions of the nomograms were between.56 and.69. Both scales (ESGS, SFS) and nomograms accurately stratified the patients for becoming free of disabling seizures, with significant differences among the three tiers (p <.05). In addition, ESGS and the modified ESN accurately stratified the patients for having been offered surgery, with significant difference among the three tiers (p <.05). Significance: ESGS and the modified ESN (at thresholds of 40% and 70%) stratify patients undergoing presurgical evaluation into three tiers, with high, moderate, and low chance for favorable outcome, with significant differences between the groups concerning having surgery and becoming free of disabling seizures. Stratifying patients for epilepsy surgery has the potential to help select the optimal candidates in underprivileged areas and better allocate resources in developed countries. [ABSTRACT FROM AUTHOR]

Speech production is a complex human function requiring continuous feedforward commands together with reafferent feedback processing. These processes are carried out by distinct frontal and temporal cortical networks, but the degree and timing of their recruitment and dynamics remain poorly understood. We present a deep learning architecture that translates neural signals recorded directly from the cortex to an interpretable representational space that can reconstruct speech. We leverage learned decoding networks to disentangle feedforward vs. feedback processing. Unlike prevailing models, we find a mixed cortical architecture in which frontal and temporal networks each process both feedforward and feedback information in tandem. We elucidate the timing of feedforward and feedback-related processing by quantifying the derived receptive fields. Our approach provides evidence for a surprisingly mixed cortical architecture of speech circuitry together with decoding advances that have important implications for neural prosthetics. [ABSTRACT FROM AUTHOR]