Antagonistic behavior of brain networks mediated by low-frequency oscillations: electrophysiological dynamics during internal-external attention switching.

Antagonistic activity of brain networks likely plays a fundamental role in how the brain optimizes its performance by efficient allocation of computational resources. A prominent example involves externally/internally oriented attention tasks, implicating two anticorrelated, intrinsic brain networks: the default mode network (DMN) and the dorsal attention network (DAN). To elucidate electrophysiological underpinnings and causal interplay during attention switching, we recorded intracranial EEG (iEEG) from 25 epilepsy patients with electrode contacts localized in the DMN and DAN. We show antagonistic network dynamics of activation-related changes in high-frequency (> 50 Hz) and low-frequency (< 30 Hz) power. The temporal profile of information flow between the networks estimated by functional connectivity suggests that the activated network inhibits the other one, gating its activity by increasing the amplitude of the low-frequency oscillations. Insights about inter-network communication may have profound implications for various brain disorders in which these dynamics are compromised.

Risk of Seizure Recurrence Due to Autoimmune Encephalitis With NMDAR, LGI1, CASPR2, and GABABR Antibodies: Implications for Return to Driving.

BACKGROUND AND OBJECTIVES: Patients with ongoing seizures are usually not allowed to drive. The prognosis for seizure freedom is favorable in patients with autoimmune encephalitis (AIE) with antibodies against NMDA receptor (NMDAR), leucine-rich glioma-inactivated 1 (LGI1), contactin-associated protein-like 2 (CASPR2), and the gamma-aminobutyric-acid B receptor (GABABR). We hypothesized that after a seizure-free period of 3 months, patients with AIE have a seizure recurrence risk of <20% during the subsequent 12 months. This would render them eligible for noncommercial driving according to driving regulations in several countries. METHODS: This retrospective multicenter cohort study analyzed follow-up data from patients aged 15 years or older with seizures resulting from NMDAR-, LGI1-, CASPR2-, or GABABR-AIE, who had been seizure-free for ≥3 months. We used Kaplan-Meier (KM) estimates for the seizure recurrence risk at 12 months for each antibody group and tested for the effects of potential covariates with regression models. RESULTS: We included 383 patients with NMDAR-, 440 with LGI1-, 114 with CASPR2-, and 44 with GABABR-AIE from 14 international centers. After being seizure-free for 3 months after an initial seizure period, we calculated the probability of remaining seizure-free for another 12 months (KM estimate) as 0.89 (95% confidence interval [CI] 0.85-0.92) for NMDAR, 0.84 (CI 0.80-0.88) for LGI1, 0.82 (CI 0.75-0.90) for CASPR2, and 0.76 (CI 0.62-0.93) for GABABR. DISCUSSION: Taking a <20% recurrence risk within 12 months as sufficient, patients with NMDAR-AIE and LGI1-AIE could be considered eligible for noncommercial driving after having been seizure-free for 3 months.

Social cognition in Idiopathic generalised epilepsies.

Social cognition is a set of mental skills necessary to create satisfactory interpersonal relationships and feel a sense of belonging to a social group. Its deficits significantly reduce the quality of life in people with epilepsy. Studies on social cognition and its impairments focus predominantly on people with focal epilepsies. Idiopathic generalised epilepsies are a group of diseases that share similar clinical, prognostic and electrographic characteristics. Despite their typically normal intelligence, people with Idiopathic generalised epilepsies can suffer from learning disabilities and executive dysfunctions. Current studies also suggest social cognition impairments, but their results are inconsistent. This review offers the latest knowledge of social cognition in adults with Idiopathic generalised epilepsies. In addition, we provide an overview of the most frequently used assessment methods. We explain possible reasons for different outcomes and discuss future research perspectives.

Low prevalence of neural autoantibodies in perioperative cerebrospinal fluid samples of epilepsy surgery patients: A multicenter prospective study.

OBJECTIVE: Refractory epilepsy may have an underlying autoimmune etiology. Our aim was to assess the prevalence of neural autoantibodies in a multicenter national prospective cohort of patients with drug-resistant epilepsy undergoing epilepsy surgery utilizing comprehensive clinical, serologic, and histopathological analyses. METHODS: We prospectively recruited patients undergoing epilepsy surgery for refractory focal epilepsy not caused by a brain tumor from epilepsy surgery centers in the Czech Republic. Perioperatively, we collected cerebrospinal fluid (CSF) and/or serum samples and performed comprehensive commercial and in-house assays for neural autoantibodies. Clinical data were obtained from the patients' medical records, and histopathological analysis of resected brain tissue was performed. RESULTS: Seventy-six patients were included, mostly magnetic resonance imaging (MRI)-lesional cases (74%). Mean time from diagnosis to surgery was 21 ± 13 years. Only one patient (1.3%) had antibodies in the CSF and serum (antibodies against glutamic acid decarboxylase 65) in relevant titers; histology revealed focal cortical dysplasia (FCD) III (FCD associated with hippocampal sclerosis [HS]). Five patients' samples displayed CSF-restricted oligoclonal bands (OCBs; 6.6%): three cases with FCD (one with FCD II and two with FCD I), one with HS, and one with negative histology. Importantly, eight patients (one of them with CSF-restricted OCBs) had findings on antibody testing in individual serum and/or CSF tests that could not be confirmed by complementary tests and were thus classified as nonspecific, yet could have been considered specific without confirmatory testing. Of these, two had FCD, two gliosis, and four HS. No inflammatory changes or lymphocyte cuffing was observed histopathologically in any of the 76 patients. SIGNIFICANCE: Neural autoantibodies are a rare finding in perioperatively collected serum and CSF of our cohort of mostly MRI-lesional epilepsy surgery patients. Confirmatory testing is essential to avoid overinterpretation of autoantibody-positive findings.

Outcome of Epilepsy Surgery in MRI-Negative Patients Without Histopathologic Abnormalities in the Resected Tissue.

BACKGROUND AND OBJECTIVE: Patients with presumed nonlesional focal epilepsy-based on either MRI or histopathologic findings-have a lower success rate of epilepsy surgery compared with lesional patients. In this study, we aimed to characterize a large group of patients with focal epilepsy who underwent epilepsy surgery despite a normal MRI and had no lesion on histopathology. Determinants of their postoperative seizure outcomes were further studied. METHODS: We designed an observational multicenter cohort study of MRI-negative and histopathology-negative patients who were derived from the European Epilepsy Brain Bank and underwent epilepsy surgery between 2000 and 2012 in 34 epilepsy surgery centers within Europe. We collected data on clinical characteristics, presurgical assessment, including genetic testing, surgery characteristics, postoperative outcome, and treatment regimen. RESULTS: Of the 217 included patients, 40% were seizure-free (Engel I) 2 years after surgery and one-third of patients remained seizure-free after 5 years. Temporal lobe surgery (adjusted odds ratio [AOR]: 2.62; 95% CI 1.19-5.76), shorter epilepsy duration (AOR for duration: 0.94; 95% CI 0.89-0.99), and completely normal histopathologic findings-versus nonspecific reactive gliosis-(AOR: 4.69; 95% CI 1.79-11.27) were significantly associated with favorable seizure outcome at 2 years after surgery. Of patients who underwent invasive monitoring, only 35% reached seizure freedom at 2 years. Patients with parietal lobe resections had lowest seizure freedom rates (12.5%). Among temporal lobe surgery patients, there was a trend toward favorable outcome if hippocampectomy was part of the resection strategy (OR: 2.94; 95% CI 0.98-8.80). Genetic testing was only sporadically performed. DISCUSSION: This study shows that seizure freedom can be reached in 40% of nonlesional patients with both normal MRI and histopathology findings. In particular, nonlesional temporal lobe epilepsy should be regarded as a relatively favorable group, with almost half of patients achieving seizure freedom at 2 years after surgery-even more if the hippocampus is resected-compared with only 1 in 5 nonlesional patients who underwent extratemporal surgery. Patients with an electroclinically identified focus, who are nonlesional, will be a promising group for advanced molecular-genetic analysis of brain tissue specimens to identify new brain somatic epilepsy genes or epilepsy-associated molecular pathways.

The brain dynamics of visuospatial perspective-taking captured by intracranial EEG.

Visuospatial perspective-taking (VPT) is the ability to imagine a scene from a position different from the one used in self-perspective judgments (SPJ). We typically use VPT to understand how others see the environment. VPT requires overcoming the self-perspective, and impairments in this process are implicated in various brain disorders, such as schizophrenia and autism. However, the underlying brain areas of VPT are not well distinguished from SPJ-related ones and from domain-general responses to both perspectives. In addition, hierarchical processing theory suggests that domain-specific processes emerge over time from domain-general ones. It mainly focuses on the sensory system, but outside of it, support for this hypothesis is lacking. Therefore, we aimed to spatiotemporally distinguish brain responses domain-specific to VPT from the specific ones to self-perspective, and domain-general responses to both perspectives. In particular, we intended to test whether VPT- and SPJ specific responses begin later than the general ones. We recorded intracranial EEG data from 30 patients with epilepsy who performed a task requiring laterality judgments during VPT and SPJ, and analyzed the spatiotemporal features of responses in the broad gamma band (50-150 Hz). We found VPT-specific processing in a more extensive brain network than SPJ-specific processing. Their dynamics were similar, but both differed from the general responses, which began earlier and lasted longer. Our results anatomically distinguish VPT-specific from SPJ-specific processing. Furthermore, we temporally differentiate between domain-specific and domain-general processes both inside and outside the sensory system, which serves as a novel example of hierarchical processing.

Yield of exome sequencing in patients with developmental and epileptic encephalopathies and inconclusive targeted gene panel.

OBJECTIVE: Developmental and epileptic encephalopathies (DEEs) are a group of severe, early-onset epilepsies characterised by refractory seizures, developmental delay, or regression and generally poor prognosis. DEE are now known to have an identifiable molecular genetic basis and are usually examined using a gene panel. However, for many patients, the genetic cause has still not been identified. The aims of this study were to identify causal variants for DEE in patients for whom the previous examination with a gene panel did not determine their genetic diagnosis. It also aims for a detailed description and broadening of the phenotypic spectrum of several rare DEEs. METHODS: In the last five years (2015-2020), 141 patients from all over the Czech Republic were referred to our department for genetic testing in association with their diagnosis of epilepsy. All patients underwent custom-designed gene panel testing prior to enrolment into the study, and their results were inconclusive. We opted for whole exome sequencing (WES) to identify the cause of their disorder. If a causal or potentially causal variant was identified, we performed a detailed clinical evaluation and phenotype-genotype correlation study to better describe the specific rare subtypes. RESULTS: Explanatory causative variants were detected in 20 patients (14%), likely pathogenic variants that explain the epilepsy in 5 patients (3.5%) and likely pathogenic variants that do not fully explain the epilepsy in 11 patients (7.5%), and variants in candidate genes in 4 patients (3%). Variants were mostly de novo 29/40 (72.5%). SIGNIFICANCE: WES enables us to identify the cause of the disease in additional patients, even after gene panel testing. It is very important to perform a WES in DEE patients as soon as possible, since it will spare the patients and their families many years of a diagnostic odyssey. In particular, patients with rare epilepsies might significantly benefit from this approach, and we propose using WES as a new standard in the diagnosis of DEE instead of targeted gene panel testing.

Usage and impact of patient-reported outcomes in epilepsy.

BACKGROUND: The use of patient-reported outcomes (PRO) in clinical practice is gaining increasing attention. This study aimed to provide a critical assessment of the current state-of-the-art and beliefs about the use of PRO in the management of people with epilepsy across some European countries. METHODS: Structured interviews were conducted with European experts to collect insights about (I) the personal experience with PRO; (II) the value and impact of PRO in the decision-making process at the national level; and (III) the interest for and use of PRO by national health authorities. RESULTS: Nine neurologists (Austria, Belgium, Czechia, Denmark, France, Greece, Italy, Poland, and United Kingdom), three health economists (Portugal, Romania, and Sweden), and one epidemiologist (Slovakia) participated. They all stated that PRO are collected at their own countries in the context of clinical trials and/or specific projects. During everyday clinical practice, PRO are collected routinely/almost routinely in Austria and Sweden and only at the discretion of the treating physicians in Czechia, Denmark, France, Greece, and Portugal. There was complete consensus about the favorable impact that the PRO can have in terms of clinical outcomes, healthcare resources utilization, and general patient satisfaction. Only participants from Portugal and Sweden answered that the PRO are perceived as very important by the National Health Authorities of their respective countries. CONCLUSIONS: Differences exist in attitudes and perspectives about PRO in epilepsy across Europe. An active plan is warranted to harmonize the measurement of PRO and ensure they can be relevant to people with epilepsy and health services.

Antibody-Negative Autoimmune Encephalitis: A Single-Center Retrospective Analysis.

BACKGROUND AND OBJECTIVES: Autoimmune encephalitis (AE) refers to a heterogenous group of inflammatory CNS diseases. Subgroups with specified neural autoantibodies are more homogeneous in presentation, trigger factors, outcome, and response to therapy. However, a considerable fraction of patients has AE features but does not harbor detectable autoantibodies and is referred to as antibody-negative AE. Our aim was to describe clinical features, trigger factors, treatments, and outcome of a cohort of comprehensively tested antibody-negative AE patients. METHODS: This retrospective monocentric study recruited adult patients whose serum and/or CSF was sent to our tertiary center for neural antibody testing between 2011 and 2020, who entered the diagnostic algorithm as possible antibody-negative AE and had the following: (1) probable antibody-negative AE, definite antibody-negative acute disseminated encephalomyelitis (ADEM), or definite autoimmune limbic encephalitis (LE) according to diagnostic criteria; (2) available data on MRI of the brain, CSF, and EEG; and (3) stored serum and/or CSF samples. These samples were reanalyzed using a comprehensive combination of cell-based and tissue-based assays. RESULTS: Of 2,250 patients tested, 33 (1.5%) were classified as possible antibody-negative AE. Of these, 5 were found to have antibodies by comprehensive testing, 5 fulfilled the criteria of probable AE (3F:2M, median age 67, range 42-67), 4 of definite autoimmune LE (2F:2M, median age 45.5, range 27-60 years), one of definite antibody-negative ADEM, 2 of Hashimoto encephalopathy, one had no samples available for additional testing, and 15 had no further categorization. Of 10 probable/definite AE/LE/ADEM, one had a malignancy and none of them received an alternative diagnosis until the end of follow-up (median 18 months). In total, 80% (8/10) of patients received immunotherapy including corticosteroids, and 6/10 (60%) patients received rituximab, azathioprine, cyclophosphamide, plasma exchange, or IV immunoglobulins. Five (50%) patients improved, one (10%) stabilized, one (10%) worsened, and 3 (30%) died. All deaths were considered to be related to encephalitis. We did not observe differences of immunotherapy-treated patients in likelihood of improvement with or without nonsteroidal immunotherapy (with 2/6, without 1/2). DISCUSSION: Antibody-negative AE should be diagnosed only after comprehensive testing. Diagnostic effort is important because many patients benefit from immunotherapy and some have malignancies.

Computational modeling allows unsupervised classification of epileptic brain states across species.

Current advances in epilepsy treatment aim to personalize and responsively adjust treatment parameters to overcome patient heterogeneity in treatment efficiency. For tailoring treatment to the individual and the current brain state, tools are required that help to identify the patient- and time-point-specific parameters of epilepsy. Computational modeling has long proven its utility in gaining mechanistic insight. Recently, the technique has been introduced as a diagnostic tool to predict individual treatment outcomes. In this article, the Wendling model, an established computational model of epilepsy dynamics, is used to automatically classify epileptic brain states in intracranial EEG from patients (n = 4) and local field potential recordings from in vitro rat data (high-potassium model of epilepsy, n = 3). Five-second signal segments are classified to four types of brain state in epilepsy (interictal, preonset, onset, ictal) by comparing a vector of signal features for each data segment to four prototypical feature vectors obtained by Wendling model simulations. The classification result is validated against expert visual assessment. Model-driven brain state classification achieved a classification performance significantly above chance level (mean sensitivity 0.99 on model data, 0.77 on rat data, 0.56 on human data in a four-way classification task). Model-driven prototypes showed similarity with data-driven prototypes, which we obtained from real data for rats and humans. Our results indicate similar electrophysiological patterns of epileptic states in the human brain and the animal model that are well-reproduced by the computational model, and captured by a key set of signal features, enabling fully automated and unsupervised brain state classification in epilepsy.

Electrical Source Imaging of Somatosensory Evoked Potentials from Intracranial EEG Signals.

Stereoelectroencephalography (SEEG) records electrical brain activity with intracerebral electrodes. However, it has an inherently limited spatial coverage. Electrical source imaging (ESI) infers the position of the neural generators from the recorded electric potentials, and thus, could overcome this spatial undersampling problem. Here, we aimed to quantify the accuracy of SEEG ESI under clinical conditions. We measured the somatosensory evoked potential (SEP) in SEEG and in high-density EEG (HD-EEG) in 20 epilepsy surgery patients. To localize the source of the SEP, we employed standardized low resolution brain electromagnetic tomography (sLORETA) and equivalent current dipole (ECD) algorithms. Both sLORETA and ECD converged to similar solutions. Reflecting the large differences in the SEEG implantations, the localization error also varied in a wide range from 0.4 to 10 cm. The SEEG ESI localization error was linearly correlated with the distance from the putative neural source to the most activated contact. We show that it is possible to obtain reliable source reconstructions from SEEG under realistic clinical conditions, provided that the high signal fidelity recording contacts are sufficiently close to the source of the brain activity.

Timing of Allocentric and Egocentric Spatial Processing in Human Intracranial EEG.

Spatial reference frames (RFs) play a key role in spatial cognition, especially in perception, spatial memory, and navigation. There are two main types of RFs: egocentric (self-centered) and allocentric (object-centered). Although many fMRI studies examined the neural correlates of egocentric and allocentric RFs, they could not sample the fast temporal dynamics of the underlying cognitive processes. Therefore, the interaction and timing between these two RFs remain unclear. Taking advantage of the high temporal resolution of intracranial EEG (iEEG), we aimed to determine the timing of egocentric and allocentric information processing and describe the brain areas involved. We recorded iEEG and analyzed broad gamma activity (50-150 Hz) in 37 epilepsy patients performing a spatial judgment task in a three-dimensional circular virtual arena. We found overlapping activation for egocentric and allocentric RFs in many brain regions, with several additional egocentric- and allocentric-selective areas. In contrast to the egocentric responses, the allocentric responses peaked later than the control ones in frontal regions with overlapping selectivity. Also, across several egocentric or allocentric selective areas, the egocentric selectivity appeared earlier than the allocentric one. We identified the maximum number of egocentric-selective channels in the medial occipito-temporal region and allocentric-selective channels around the intraparietal sulcus in the parietal cortex. Our findings favor the hypothesis that egocentric spatial coding is a more primary process, and allocentric representations may be derived from egocentric ones. They also broaden the dominant view of the dorsal and ventral streams supporting egocentric and allocentric space coding, respectively.

Automated Identification of Stereoelectroencephalography Contacts and Measurement of Factors Influencing Accuracy of Frame Stereotaxy.

OBJECTIVE: Stereoelectroencephalography (SEEG) is an established invasive diagnostic technique for use in patients with drug-resistant focal epilepsy evaluated before resective epilepsy surgery. The factors that influence the accuracy of electrode implantation are not fully understood. Adequate accuracy prevents the risk of major surgery complications. Precise knowledge of the anatomical positions of individual electrode contacts is crucial for the interpretation of SEEG recordings and subsequent surgery. METHODS: We developed an image processing pipeline to localize implanted electrodes and detect individual contact positions using computed tomography (CT), as a substitute for time-consuming manual labeling. The algorithm automates measurement of parameters of the electrodes implanted in the skull (bone thickness, implantation angle and depth) for use in modeling of predictive factors that influence implantation accuracy. RESULTS: Fifty-four patients evaluated by SEEG were analyzed. A total of 662 SEEG electrodes with 8,745 contacts were stereotactically inserted. The automated detector localized all contacts with better accuracy than manual labeling (p < 0.001). The retrospective implantation accuracy of the target point was 2.4 ± 1.1 mm. A multifactorial analysis determined that almost 58% of the total error was attributable to measurable factors. The remaining 42% was attributable to random error. CONCLUSION: SEEG contacts can be reliably marked by our proposed method. The trajectory of electrodes can be parametrically analyzed to predict and validate implantation accuracy using a multifactorial model. SIGNIFICANCE: This novel, automated image processing technique is a potentially clinically important, assistive tool for increasing the yield, efficiency, and safety of SEEG.

Structural connectivity-based predictors of cognitive impairment in stroke patients attributable to aging.

Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients' cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.

Distinct patterns of interictal intracranial EEG in focal cortical dysplasia type I and II.

OBJECTIVE: Focal cortical dysplasia (FCD) is the most common malformation causing refractory focal epilepsy. Surgical removal of the entire dysplastic cortex is crucial for achieving a seizure-free outcome. Precise presurgical distinctions between FCD types by neuroimaging are difficult, mainly in patients with normal magnetic resonance imaging findings. However, the FCD type is important for planning the extent of surgical approach and counselling. METHODS: This study included patients with focal drug-resistant epilepsy and definite histopathological FCD type I or II diagnoses who underwent intracranial electroencephalography (iEEG). We detected interictal epileptiform discharges (IEDs) and their recruitment into repetitive discharges (RDs) to compare electrophysiological patterns characterizing FCD types. RESULTS: Patients with FCD type II had a significantly higher IED rate (p < 0.005), a shorter inter-discharge interval within RD episodes (p < 0.003), sleep influence on decreased RD periodicity (p < 0.036), and longer RD episode duration (p < 0.003) than patients with type I. A Bayesian classifier stratified FCD types with 82% accuracy. CONCLUSION: Temporal characteristics of IEDs and RDs reflect the histological findings of FCD subtypes and can differentiate FCD types I and II. SIGNIFICANCE: Presurgical prediction of FCD type can help to plan a more tailored surgical approach in patients with normal magnetic resonance findings.

Tackling the challenges of group network inference from intracranial EEG data.

Introduction: Intracranial EEG (iEEG) data is a powerful way to map brain function, characterized by high temporal and spatial resolution, allowing the study of interactions among neuronal populations that orchestrate cognitive processing. However, the statistical inference and analysis of brain networks using iEEG data faces many challenges related to its sparse brain coverage, and its inhomogeneity across patients. Methods: We review these challenges and develop a methodological pipeline for estimation of network structure not obtainable from any single patient, illustrated on the inference of the interaction among visual streams using a dataset of 27 human iEEG recordings from a visual experiment employing visual scene stimuli. 100 ms sliding window and multiple band-pass filtered signals are used to provide temporal and spectral resolution. For the connectivity analysis we showcase two connectivity measures reflecting different types of interaction between regions of interest (ROI): Phase Locking Value as a symmetric measure of synchrony, and Directed Transfer Function-asymmetric measure describing causal interaction. For each two channels, initial uncorrected significance testing at p < 0.05 for every time-frequency point is carried out by comparison of the data-derived connectivity to a baseline surrogate-based null distribution, providing a binary time-frequency connectivity map. For each ROI pair, a connectivity density map is obtained by averaging across all pairs of channels spanning them, effectively agglomerating data across relevant channels and subjects. Finally, the difference of the mean map value after and before the stimulation is compared to the same statistic in surrogate data to assess link significance. Results: The analysis confirmed the function of the parieto-medial temporal pathway, mediating visuospatial information between dorsal and ventral visual streams during visual scene analysis. Moreover, we observed the anterior hippocampal connectivity with more posterior areas in the medial temporal lobe, and found the reciprocal information flow between early processing areas and medial place area. Discussion: To summarize, we developed an approach for estimating network connectivity, dealing with the challenge of sparse individual coverage of intracranial EEG electrodes. Its application provided new insights into the interaction between the dorsal and ventral visual streams, one of the iconic dualities in human cognition.

Genetic Testing for Malformations of Cortical Development: A Clinical Diagnostic Study.

Background and Objectives: Malformations of cortical development (MCD), though individually rare, constitute a significant burden of disease. The diagnostic yield of next-generation sequencing (NGS) in these patients varies across studies and methods, and novel genes and variants continue to emerge. Methods: Patients (n = 123) with a definite radiologic or histopathologic diagnosis of MCD, with or without epilepsy were included in this study. They underwent NGS-based targeted gene panel (TGP) testing, whole-exome sequencing (WES), or WES-based virtual panel testing. Selected patients who underwent epilepsy surgery (n = 69) also had somatic gene testing of brain tissue-derived DNA. We analyzed predictors of positive germline genetic finding and diagnostic yield of respective methods. Results: Pathogenic or likely pathogenic germline genetic variants were detected in 21% of patients (26/123). In the surgical subgroup (69/123), we performed somatic sequencing in 40% of cases (28/69) and detected causal variants in 18% (5/28). Diagnostic yield did not differ between TGP, WES-based virtual gene panel, and open WES (p = 0.69). Diagnosis of focal cortical dysplasia type 2A, epilepsy, and intellectual disability were associated with positive results of germline testing. We report previously unpublished variants in 16/26 patients and 4 cases of MCD with likely pathogenic variants in non-MCD genes. Discussion: In this study, we are reporting genetic findings of a large cohort of MCD patients with epilepsy or potentially epileptogenic MCD. We determine predictors of successful ascertainment of a genetic diagnosis in real-life setting and report novel, likely pathogenic variants in MCD and non-MCD genes alike.

Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice.

Identifying factors whose fluctuations are associated with choice inconsistency is a major issue for rational decision theory. Here, we investigated the neuro-computational mechanisms through which mood fluctuations may bias human choice behavior. Intracerebral EEG data were collected in a large group of subjects (n=30) while they were performing interleaved quiz and choice tasks that were designed to examine how a series of unrelated feedbacks affect decisions between safe and risky options. Neural baseline activity preceding choice onset was confronted first to mood level, estimated by a computational model integrating the feedbacks received in the quiz task, and then to the weighting of option attributes, in a computational model predicting risk attitude in the choice task. Results showed that (1) elevated broadband gamma activity (BGA) in the ventromedial prefrontal cortex (vmPFC) and dorsal anterior insula (daIns) was respectively signaling periods of high and low mood, (2) increased vmPFC and daIns BGA respectively promoted and tempered risk taking by overweighting gain vs. loss prospects. Thus, incidental feedbacks induce brain states that correspond to different moods and bias the evaluation of risky options. More generally, these findings might explain why people experiencing positive (or negative) outcome in some part of their life tend to expect success (or failure) in any other.

IL-2, IL-6 and chitinase 3-like 2 might predict early relapse activity in multiple sclerosis.

BACKGROUND: The possibility to better predict the severity of the disease in a patient newly diagnosed with multiple sclerosis would allow the treatment strategy to be personalized and lead to better clinical outcomes. Prognostic biomarkers are highly needed. OBJECTIVE: To assess the prognostic value of intrathecal IgM synthesis, cerebrospinal fluid and serum IL-2, IL-6, IL-10, chitinase 3-like 2 and neurofilament heavy chains obtained early after the onset of the disease. METHODS: 58 patients after the first manifestation of multiple sclerosis were included. After the initial diagnostic assessment including serum and cerebrospinal fluid biomarkers, all patients initiated therapy with either glatiramer acetate, teriflunomide, or interferon beta. To assess the evolution of the disease, we followed the patients clinically and with MRI for two years. RESULTS: The IL-2:IL-6 ratio (both in cerebrospinal fluid) <0.48 (p = 0.0028), IL-2 in cerebrospinal fluid ≥1.23pg/ml (p = 0.026), and chitinase 3-like 2 in cerebrospinal fluid ≥7900pg/ml (p = 0.033), as well as baseline EDSS ≥1.5 (p = 0.0481) and age <22 (p = 0.0312), proved to be independent markers associated with shorter relapse free intervals. CONCLUSION: The IL-2:IL-6 ratio, IL-2, and chitinase 3-like 2 (all in cerebrospinal fluid) might be of value as prognostic biomarkers in early phases of multiple sclerosis.

Detection of interictal epileptiform discharges in an extended scalp EEG array and high-density EEG-A prospective multicenter study.

OBJECTIVES: High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time-efficient, but they need to identify the correct IED types. Thus we compared semiautomated and automated detection of IED types in long-term video-EEG (electroencephalography) monitoring (LTM) using an extended scalp EEG array and short-term high-density EEG (hdEEG) with visual detection of IED types and the seizure-onset zone (SOZ). METHODS: We prospectively recruited consecutive patients from four epilepsy centers who underwent both LTM with 40-electrode scalp EEG and short-term hdEEG with 256 electrodes. Only patients with a single circumscribed SOZ in LTM were included. In LTM and hdEEG, IED types were identified visually, semiautomatically and automatically. Concordances of semiautomated and automated detections in LTM and hdEEG, as well as visual detections in hdEEG, were compared against visually detected IED types and the SOZ in LTM. RESULTS: Fifty-two of 62 patients with LTM and hdEEG were included. The most frequent IED types per patient, detected semiautomatically and automatically in LTM and visually in hdEEG, were significantly concordant with the most frequently visually identified IED type in LTM and the SOZ. Semiautomated and automated detections of IED types in hdEEG were significantly concordant with visually identified IED types in LTM, only when IED types with more than 50 detected single IEDs were selected. The threshold of 50 detected IED in hdEEG was reached in half of the patients. For all IED types per patient, agreement between visual and semiautomated detections in LTM was high. SIGNIFICANCE: Semiautomated and automated detections of IED types in LTM show significant agreement with visually detected IED types and the SOZ. In short-term hdEEG, semiautomated detections of IED types are concordant with visually detected IED types and the SOZ in LTM if high IED counts were detected.