A low-activity cortical network selectively encodes syntax.

Syntax, the abstract structure of language, is a hallmark of human cognition. Despite its importance, its neural underpinnings remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover three syntactic networks that are broadly distributed across traditional language regions, but with focal concentrations in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, these networks process syntax mostly to the exclusion of words and meaning, supporting a cognitive architecture with a distinct syntactic system. Most strikingly, our data reveal an unexpected property of syntax: it is encoded independent of neural activity levels. We propose that this "low-activity coding" scheme represents a novel mechanism for encoding information, reserved for higher-order cognition more broadly.

T4 DNA polymerase prevents deleterious on-target DNA damage and enhances precise CRISPR editing.

Unintended on-target chromosomal alterations induced by CRISPR/Cas9 in mammalian cells are common, particularly large deletions and chromosomal translocations, and present a safety challenge for genome editing. Thus, there is still an unmet need to develop safer and more efficient editing tools. We screened diverse DNA polymerases of distinct origins and identified a T4 DNA polymerase derived from phage T4 that strongly prevents undesired on-target damage while increasing the proportion of precise 1- to 2-base-pair insertions generated during CRISPR/Cas9 editing (termed CasPlus). CasPlus induced substantially fewer on-target large deletions while increasing the efficiency of correcting common frameshift mutations in DMD and restored higher level of dystrophin expression than Cas9-alone in human cardiomyocytes. Moreover, CasPlus greatly reduced the frequency of on-target large deletions during mouse germline editing. In multiplexed guide RNAs mediating gene editing, CasPlus repressed chromosomal translocations while maintaining gene disruption efficiency that was higher or comparable to Cas9 in primary human T cells. Therefore, CasPlus offers a safer and more efficient gene editing strategy to treat pathogenic variants or to introduce genetic modifications in human applications.

Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language.

Recent research has used large language models (LLMs) to study the neural basis of naturalistic language processing in the human brain. LLMs have rapidly grown in complexity, leading to improved language processing capabilities. However, neuroscience researchers haven't kept up with the quick progress in LLM development. Here, we utilized several families of transformer-based LLMs to investigate the relationship between model size and their ability to capture linguistic information in the human brain. Crucially, a subset of LLMs were trained on a fixed training set, enabling us to dissociate model size from architecture and training set size. We used electrocorticography (ECoG) to measure neural activity in epilepsy patients while they listened to a 30-minute naturalistic audio story. We fit electrode-wise encoding models using contextual embeddings extracted from each hidden layer of the LLMs to predict word-level neural signals. In line with prior work, we found that larger LLMs better capture the structure of natural language and better predict neural activity. We also found a log-linear relationship where the encoding performance peaks in relatively earlier layers as model size increases. We also observed variations in the best-performing layer across different brain regions, corresponding to an organized language processing hierarchy.

Comprehensive scoping review of fenfluramine's role in managing generalized tonic-clonic seizures in developmental and epileptic encephalopathies.

Developmental and epileptic encephalopathies (DEEs) are characterized by pharmacoresistant seizures and developmental delay. Patients with DEEs experience multiple seizure types, including tonic-clonic seizures (TCS) that can be generalized tonic-clonic (GTCS) or focal evolving to bilateral tonic-clonic (FBTCS). Fenfluramine (FFA) has demonstrated efficacy in reduction of TCS in patients with Dravet syndrome (DS), Lennox-Gastaut syndrome (LGS), and other DEEs. Using the PRISMA-ScR (Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Review) guidelines, we performed a scoping review to describe changes in TCS in patients treated with FFA. A comprehensive search of five literature databases was conducted up to February 14, 2023. Studies were included if they reported change in GTCS or TCS (but not FBTCS) after treatment with FFA in patients with DEEs. Duplicate patients and studies with unclear efficacy data were excluded. Fourteen of 422 studies met the eligibility criteria. Data extracted and evaluated by expert clinicians identified 421 unique patients with DS (in nine studies), CDKL5 deficiency disorder, SCN8A-related disorder, LGS, SCN1B-related disorder, and other DEEs. The median percent reduction in GTCS or TCS from baseline was available in 10 studies (n = 328) and ranged from 47.2% to 100%. Following FFA treatment, 10 studies (n = 144) reported ≥50% reduction in GTCS or TCS from baseline in 72% of patients; in nine of those (n = 112), 54% and 29% of patients achieved ≥75% and 100% reduction in GTCS or TCS from baseline, respectively. Overall, this analysis highlighted improvements in GTCS or TCS frequency when patients were treated with FFA regardless of the DEE evaluated. Future studies may confirm the impact of FFA on TCS reduction and on decreased premature mortality risk (including sudden unexpected death in epilepsy), improvement in comorbidities and everyday executive function, decreased health care costs, and improvement in quality of life.

Incidence and Types of Cardiac Arrhythmias in the Peri-Ictal Period in Patients Having a Generalized Convulsive Seizure.

BACKGROUND AND OBJECTIVES: Generalized convulsive seizures (GCSs) are the main risk factor of sudden unexpected death in epilepsy (SUDEP), which is likely due to peri-ictal cardiorespiratory dysfunction. The incidence of GCS-induced cardiac arrhythmias, their relationship to seizure severity markers, and their role in SUDEP physiopathology are unknown. The aim of this study was to analyze the incidence of seizure-induced cardiac arrhythmias, their association with electroclinical features and seizure severity biomarkers, as well as their specific occurrences in SUDEP cases. METHODS: This is an observational, prospective, multicenter study of patients with epilepsy aged 18 years and older with recorded GCS during inpatient video-EEG monitoring for epilepsy evaluation. Exclusion criteria were status epilepticus and an obscured video recording. We analyzed semiologic and cardiorespiratory features through video-EEG (VEEG), electrocardiogram, thoracoabdominal bands, and pulse oximetry. We investigated the presence of bradycardia, asystole, supraventricular tachyarrhythmias (SVTs), premature atrial beats, premature ventricular beats, nonsustained ventricular tachycardia (NSVT), atrial fibrillation (Afib), ventricular fibrillation (VF), atrioventricular block (AVB), exaggerated sinus arrhythmia (ESA), and exaggerated sinus arrhythmia with bradycardia (ESAWB). A board-certified cardiac electrophysiologist diagnosed and classified the arrhythmia types. Bradycardia, asystole, SVT, NSVT, Afib, VF, AVB, and ESAWB were classified as arrhythmias of interest because these were of SUDEP pathophysiology value. The main outcome was the occurrence of seizure-induced arrhythmias of interest during inpatient VEEG monitoring. Moreover, yearly follow-up was conducted to identify SUDEP cases. Binary logistic generalized estimating equations were used to determine clinical-demographic and peri-ictal variables that were predictive of the presence of seizure-induced arrhythmias of interest. The z-score test for 2 population proportions was used to test whether the proportion of seizures and patients with postconvulsive ESAWB or bradycardia differed between SUDEP cases and survivors. RESULTS: This study includes data from 249 patients (mean age 37.2 ± 23.5 years, 55% female) who had 455 seizures. The most common arrhythmia was ESA, with an incidence of 137 of 382 seizures (35.9%) (106/224 patients [47.3%]). There were 50 of 352 seizure-induced arrhythmias of interest (14.2%) in 41 of 204 patients (20.1%). ESAWB was the commonest in 22 of 394 seizures (5.6%) (18/225 patients [8%]), followed by SVT in 18 of 397 seizures (4.5%) (17/228 patients [7.5%]). During follow-up (48.36 ± 31.34 months), 8 SUDEPs occurred. Seizure-induced bradycardia (3.8% vs 12.5%, z = -16.66, p < 0.01) and ESAWB (6.6% vs 25%; z = -3.03, p < 0.01) were over-represented in patients who later died of SUDEP. There was no association between arrhythmias of interest and seizure severity biomarkers (p > 0.05). DISCUSSION: Markers of seizure severity are not related to seizure-induced arrhythmias of interest, suggesting that other factors such as occult cardiac abnormalities may be relevant for their occurrence. Seizure-induced ESAWB and bradycardia were more frequent in SUDEP cases, although this observation was based on a very limited number of SUDEP patients. Further case-control studies are needed to evaluate the yield of arrhythmias of interest along with respiratory changes as potential SUDEP biomarkers.

Hypothalamic-Pituitary-Adrenal Axis Dysfunction Elevates SUDEP Risk in a Sex-Specific Manner.

Epilepsy is often comorbid with psychiatric illnesses, including anxiety and depression. Despite the high incidence of psychiatric comorbidities in people with epilepsy, few studies address the underlying mechanisms. Stress can trigger epilepsy and depression. Evidence from human and animal studies supports that hypothalamic-pituitary-adrenal (HPA) axis dysfunction may contribute to both disorders and their comorbidity ( Kanner, 2003). Here, we investigate if HPA axis dysfunction may influence epilepsy outcomes and psychiatric comorbidities. We generated a novel mouse model (Kcc2/Crh KO mice) lacking the K+/Cl- cotransporter, KCC2, in corticotropin-releasing hormone (CRH) neurons, which exhibit stress- and seizure-induced HPA axis hyperactivation ( Melon et al., 2018). We used the Kcc2/Crh KO mice to examine the impact on epilepsy outcomes, including seizure frequency/burden, comorbid behavioral deficits, and sudden unexpected death in epilepsy (SUDEP) risk. We found sex differences in HPA axis dysfunction's effect on chronically epileptic KCC2/Crh KO mice seizure burden, vulnerability to comorbid behavioral deficits, and SUDEP. Suppressing HPA axis hyperexcitability in this model using pharmacological or chemogenetic approaches decreased SUDEP incidence, suggesting that HPA axis dysfunction may contribute to SUDEP. Altered neuroendocrine markers were present in SUDEP cases compared with people with epilepsy or individuals without epilepsy. Together, these findings implicate HPA axis dysfunction in the pathophysiological mechanisms contributing to psychiatric comorbidities in epilepsy and SUDEP.

Epilepsy as a Novel Phenotype of BPTF-Related Disorders.

BACKGROUND: Neurodevelopmental disorder with dysmorphic facies and distal limb anomalies (NEDDFL) is associated to BPTF gene haploinsufficiency. Epilepsy was not included in the initial descriptions of NEDDFL, but emerging evidence indicates that epileptic seizures occur in some affected individuals. This study aims to investigate the electroclinical epilepsy features in individuals with NEDDFL. METHODS: We enrolled individuals with BPTF-related seizures or interictal epileptiform discharges (IEDs) on electroencephalography (EEG). Demographic, clinical, genetic, raw EEG, and neuroimaging data as well as response to antiseizure medication were assessed. RESULTS: We studied 11 individuals with a null variant in BPTF, including five previously unpublished ones. Median age at last observation was 9 years (range: 4 to 43 years). Eight individuals had epilepsy, one had a single unprovoked seizure, and two showed IEDs only. Key features included (1) early childhood epilepsy onset (median 4 years, range: 10 months to 7 years), (2) well-organized EEG background (all cases) and brief bursts of spikes and slow waves (50% of individuals), and (3) developmental delay preceding seizure onset. Spectrum of epilepsy severity varied from drug-resistant epilepsy (27%) to isolated IEDs without seizures (18%). Levetiracetam was widely used and reduced seizure frequency in 67% of the cases. CONCLUSIONS: Our study provides the first characterization of BPTF-related epilepsy. Early-childhood-onset epilepsy occurs in 19% of subjects, all presenting with a well-organized EEG background associated with generalized interictal epileptiform abnormalities in half of these cases. Drug resistance is rare.

Temporal dynamics of short-term neural adaptation across human visual cortex.

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.

The influence of risk factors, biomarkers and care settings on SUDEP counseling.

Although sudden unexpected death in epilepsy (SUDEP) is the most feared epilepsy outcome, there is a dearth of SUDEP counseling provided by neurologists. This may reflect limited time, as well as the lack of guidance on the timing and structure for counseling. We evaluated records from SUDEP cases to examine frequency of inpatient and outpatient SUDEP counseling, and whether counseling practices were influenced by risk factors and biomarkers, such as post-ictal generalized EEG suppression (PGES). We found a striking lack of SUDEP counseling despite modifiable SUDEP risk factors; counseling was limited to outpatients despite many patients having inpatient visits within a year of SUDEP. PGES was inconsistently documented and was never included in counseling. There is an opportunity to greatly improve SUDEP counseling by utilizing inpatient settings and prompting algorithms incorporating risk factors and biomarkers.

A left-lateralized dorsolateral prefrontal network for naming.

The ability to connect the form and meaning of a concept, known as word retrieval, is fundamental to human communication. While various input modalities could lead to identical word retrieval, the exact neural dynamics supporting this convergence relevant to daily auditory discourse remain poorly understood. Here, we leveraged neurosurgical electrocorticographic (ECoG) recordings from 48 patients and dissociated two key language networks that highly overlap in time and space integral to word retrieval. Using unsupervised temporal clustering techniques, we found a semantic processing network located in the middle and inferior frontal gyri. This network was distinct from an articulatory planning network in the inferior frontal and precentral gyri, which was agnostic to input modalities. Functionally, we confirmed that the semantic processing network encodes word surprisal during sentence perception. Our findings characterize how humans integrate ongoing auditory semantic information over time, a critical linguistic function from passive comprehension to daily discourse.

Placebo response in patients with Dravet syndrome: Post-hoc analysis of two clinical trials.

OBJECTIVE: Dravet syndrome is a rare, early childhood-onset epileptic and developmental encephalopathy. Responses to placebo in clinical trials for epilepsy therapies range widely, but factors influencing placebo response remain poorly understood. This study explored placebo response and its effects on safety, efficacy, and quality of life outcomes in patients with Dravet syndrome. METHODS: We performed exploratory post-hoc analyses of pooled data from placebo-treated patients from the GWPCARE 1B and GWPCARE 2 randomized controlled phase III trials, comparing cannabidiol and matched placebo in 2-18 year old Dravet syndrome patients. All patients had ≥4 convulsive seizures during a baseline period of 4 weeks. RESULTS: 124 Dravet syndrome-treated patients were included in the analysis (2-5 years: n = 35; 6-12 years: n = 52; 13-18 years: n = 37). Convulsive seizures were experienced by all placebo group patients at all timepoints, with decreased median convulsive seizure frequency during the treatment period versus baseline; the number of convulsive seizure-free days was similar to baseline. Convulsive seizure frequency had a nominally significant positive correlation with age and a nominally significant negative correlation with body mass index. Most placebo-treated patients experienced a treatment-emergent adverse event; however, most resolved quickly, and serious adverse events were infrequent. Placebo treatment had very little effect on reported Caregiver Global Impression of Change outcomes versus baseline. INTERPRETATION: Placebo had little impact on convulsive seizure-free days and Caregiver Global Impression of Change versus baseline, suggesting that these metrics may help differentiate placebo and active treatment effects in future studies. However, future research should further assess placebo responses to confirm these results.

Subject-Agnostic Transformer-Based Neural Speech Decoding from Surface and Depth Electrode Signals.

Objective: This study investigates speech decoding from neural signals captured by intracranial electrodes. Most prior works can only work with electrodes on a 2D grid (i.e., Electrocorticographic or ECoG array) and data from a single patient. We aim to design a deep-learning model architecture that can accommodate both surface (ECoG) and depth (stereotactic EEG or sEEG) electrodes. The architecture should allow training on data from multiple participants with large variability in electrode placements and the trained model should perform well on participants unseen during training. Approach: We propose a novel transformer-based model architecture named SwinTW that can work with arbitrarily positioned electrodes, by leveraging their 3D locations on the cortex rather than their positions on a 2D grid. We train both subject-specific models using data from a single participant as well as multi-patient models exploiting data from multiple participants. Main Results: The subject-specific models using only low-density 8x8 ECoG data achieved high decoding Pearson Correlation Coefficient with ground truth spectrogram (PCC=0.817), over N=43 participants, outperforming our prior convolutional ResNet model and the 3D Swin transformer model. Incorporating additional strip, depth, and grid electrodes available in each participant (N=39) led to further improvement (PCC=0.838). For participants with only sEEG electrodes (N=9), subject-specific models still enjoy comparable performance with an average PCC=0.798. The multi-subject models achieved high performance on unseen participants, with an average PCC=0.765 in leave-one-out cross-validation. Significance: The proposed SwinTW decoder enables future speech neuroprostheses to utilize any electrode placement that is clinically optimal or feasible for a particular participant, including using only depth electrodes, which are more routinely implanted in chronic neurosurgical procedures. Importantly, the generalizability of the multi-patient models suggests the exciting possibility of developing speech neuroprostheses for people with speech disability without relying on their own neural data for training, which is not always feasible.

Novelty preference assessed by eye tracking: A sensitive measure of impaired recognition memory in epilepsy.

OBJECTIVE: Epilepsy patients often report memory deficits despite normal objective testing, suggesting that available measures are insensitive or that non-mnemonic factors are involved. The Visual Paired Comparison Task (VPCT) assesses novelty preference, the tendency to fixate on novel images rather than previously viewed items, requiring recognition memory for the "old" images. As novelty preference is a sensitive measure of hippocampal-dependent memory function, we predicted impaired VPCT performance in epilepsy patients compared to healthy controls. METHODS: We assessed 26 healthy adult controls and 31 epilepsy patients (16 focal-onset, 13 generalized-onset, 2 unknown-onset) with the VPCT using delays of 2 or 30 s between encoding and recognition. Fifteen healthy controls and 17 epilepsy patients (10 focal-onset, 5 generalized-onset, 2 unknown-onset) completed the task at 2-, 5-, and 30-minute delays. Subjects also performed standard memory measures, including the Medical College of Georgia (MCG) Paragraph Test, California Verbal Learning Test-Second Edition (CVLT-II), and Brief Visual Memory Test-Revised (BVMT-R). RESULTS: The epilepsy group was high functioning, with greater estimated IQ (p = 0.041), greater years of education (p = 0.034), and higher BVMT-R scores (p = 0.024) compared to controls. Both the control group and epilepsy cohort, as well as focal- and generalized-onset subgroups, had intact novelty preference at the 2- and 30-second delays (p-values ≤ 0.001) and declined at 30 min (p-values > 0.05). Only the epilepsy patients had early declines at 2- and 5-minute delays (controls with intact novelty preference at p = 0.003 and p ≤ 0.001, respectively; epilepsy groups' p-values > 0.05). CONCLUSIONS: Memory for the "old" items decayed more rapidly in overall, focal-onset, and generalized-onset epilepsy groups. The VPCT detected deficits while standard memory measures were largely intact, suggesting that the VPCT may be a more sensitive measure of temporal lobe memory function than standard neuropsychological batteries.

Dravet syndrome seizure frequency and clustering: Placebo-treated patients in clinical trials.

OBJECTIVE: Dravet syndrome is a rare developmental epilepsy syndrome associated with severe, treatment-resistant seizures. Since seizures and seizure clusters are linked to morbidity, reduced quality of life, and premature mortality, a greater understanding of these outcomes could improve trial designs. This analysis explored seizure types, seizure clusters, and factors affecting seizure cluster variability in Dravet syndrome patients. METHODS: Pooled post-hoc analyses were performed on data from placebo-treated patients in GWPCARE 1B and GWPCARE 2 randomized controlled phase III trials comparing cannabidiol and placebo in Dravet syndrome patients aged 2-18 years. Multivariate stepwise analysis of covariance of log-transformed convulsive seizure cluster frequency was performed, body weight and body mass index z-scores were calculated, and incidence of adverse events was assessed. Data were summarized in three age groups. RESULTS: We analyzed 124 placebo-treated patients across both studies (2-5 years: n = 35; 6-12 years: n = 52; 13-18 years: n = 37). Generalized tonic-clonic seizures followed by myoclonic seizures were the most frequent seizure types. Mean and median convulsive seizure cluster frequency overall decreased between baseline and maintenance period but did not change significantly during the latter; variation in convulsive seizure cluster frequency was observed across age groups. Multivariate analysis suggested correlations between convulsive seizure cluster frequency and age (positive), and body mass index (BMI) (negative). INTERPRETATION: Post-hoc analyses suggested that potential relationships could exist between BMI, age and convulsive seizure cluster variation. Results suggested that seizure cluster frequency may be a valuable outcome in future trials. Further research is needed to confirm our findings.

Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns.

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.

Clinical outcomes among initial survivors of cryptogenic new-onset refractory status epilepsy (NORSE).

OBJECTIVE: New-onset refractory status epilepticus (NORSE) is a rare but severe clinical syndrome. Despite rigorous evaluation, the underlying cause is unknown in 30%-50% of patients and treatment strategies are largely empirical. The aim of this study was to describe clinical outcomes in a cohort of well-phenotyped, thoroughly investigated patients who survived the initial phase of cryptogenic NORSE managed in specialist centers. METHODS: Well-characterized cases of cryptogenic NORSE were identified through the EPIGEN and Critical Care EEG Monitoring Research Consortia (CCEMRC) during the period 2005-2019. Treating epileptologists reported on post-NORSE survival rates and sequelae in patients after discharge from hospital. Among survivors >6 months post-discharge, we report the rates and severity of active epilepsy, global disability, vocational, and global cognitive and mental health outcomes. We attempt to identify determinants of outcome. RESULTS: Among 48 patients who survived the acute phase of NORSE to the point of discharge from hospital, 9 had died at last follow-up, of whom 7 died within 6 months of discharge from the tertiary care center. The remaining 39 patients had high rates of active epilepsy as well as vocational, cognitive, and psychiatric comorbidities. The epilepsy was usually multifocal and typically drug resistant. Only a minority of patients had a good functional outcome. Therapeutic interventions were heterogenous during the acute phase of the illness. There was no clear relationship between the nature of treatment and clinical outcomes. SIGNIFICANCE: Among survivors of cryptogenic NORSE, longer-term outcomes in most patients were life altering and often catastrophic. Treatment remains empirical and variable. There is a pressing need to understand the etiology of cryptogenic NORSE and to develop tailored treatment strategies.

Timing and location of speech errors induced by direct cortical stimulation.

Cortical regions supporting speech production are commonly established using neuroimaging techniques in both research and clinical settings. However, for neurosurgical purposes, structural function is routinely mapped peri-operatively using direct electrocortical stimulation. While this method is the gold standard for identification of eloquent cortical regions to preserve in neurosurgical patients, there is lack of specificity of the actual underlying cognitive processes being interrupted. To address this, we propose mapping the temporal dynamics of speech arrest across peri-sylvian cortices by quantifying the latency between stimulation and speech deficits. In doing so, we are able to substantiate hypotheses about distinct region-specific functional roles (e.g. planning versus motor execution). In this retrospective observational study, we analysed 20 patients (12 female; age range 14-43) with refractory epilepsy who underwent continuous extra-operative intracranial EEG monitoring of an automatic speech task during clinical bedside language mapping. Latency to speech arrest was calculated as time from stimulation onset to speech arrest onset, controlling for individual speech rate. Most instances of motor-based arrest (87.5% of 96 instances) were in sensorimotor cortex with mid-range latencies to speech arrest with a distributional peak at 0.47 s. Speech arrest occurred in numerous regions, with relatively short latencies in supramarginal gyrus (0.46 s), superior temporal gyrus (0.51 s) and middle temporal gyrus (0.54 s), followed by relatively long latencies in sensorimotor cortex (0.72 s) and especially long latencies in inferior frontal gyrus (0.95 s). Non-parametric testing for speech arrest revealed that region predicted latency; latencies in supramarginal gyrus and in superior temporal gyrus were shorter than in sensorimotor cortex and in inferior frontal gyrus. Sensorimotor cortex is primarily responsible for motor-based arrest. Latencies to speech arrest in supramarginal gyrus and superior temporal gyrus (and to a lesser extent middle temporal gyrus) align with latencies to motor-based arrest in sensorimotor cortex. This pattern of relatively quick cessation of speech suggests that stimulating these regions interferes with the outgoing motor execution. In contrast, the latencies to speech arrest in inferior frontal gyrus and in ventral regions of sensorimotor cortex were significantly longer than those in temporoparietal regions. Longer latencies in the more frontal areas (including inferior frontal gyrus and ventral areas of precentral gyrus and postcentral gyrus) suggest that stimulating these areas interrupts a higher-level speech production process involved in planning. These results implicate the ventral specialization of sensorimotor cortex (including both precentral and postcentral gyri) for speech planning above and beyond motor execution.

An iPSC line (FINi003-A) from a male with late-onset developmental and epileptic encephalopathy caused by a heterozygous p.E1211K variant in the SCN2A gene encoding the voltage-gated sodium channel Nav1.2.

Many developmental and epileptic encephalopathies (DEEs) result from variants in cation channel genes. Using mRNA transfection, we generated and characterised an induced pluripotent stem cell (iPSC) line from the fibroblasts of a male late-onset DEE patient carrying a heterozygous missense variant (E1211K) in Nav1.2(SCN2A) protein. The iPSC line displays features characteristic of the human iPSCs, colony morphology and expression of pluripotency-associated marker genes, ability to produce derivatives of all three embryonic germ layers, and normal karyotype without SNP array-detectable abnormalities. We anticipate that this iPSC line will aid in the modelling and development of precision therapies for this debilitating condition.

Closed-loop electrical stimulation to prevent focal epilepsy progression and long-term memory impairment.

Interictal epileptiform discharges (IEDs) are ubiquitously expressed in epileptic networks and disrupt cognitive functions. It is unclear whether addressing IED-induced dysfunction could improve epilepsy outcomes as most therapeutics target seizures. We show in a model of progressive hippocampal epilepsy that IEDs produce pathological oscillatory coupling which is associated with prolonged, hypersynchronous neural spiking in synaptically connected cortex and expands the brain territory capable of generating IEDs. A similar relationship between IED-mediated oscillatory coupling and temporal organization of IEDs across brain regions was identified in human subjects with refractory focal epilepsy. Spatiotemporally targeted closed-loop electrical stimulation triggered on hippocampal IED occurrence eliminated the abnormal cortical activity patterns, preventing spread of the epileptic network and ameliorating long-term spatial memory deficits in rodents. These findings suggest that stimulation-based network interventions that normalize interictal dynamics may be an effective treatment of epilepsy and its comorbidities, with a low barrier to clinical translation. One-Sentence Summary: Targeted closed-loop electrical stimulation prevents spread of the epileptic network and ameliorates long-term spatial memory deficits.