Determinants of Functional Outcome after Pediatric Hemispherotomy.

OBJECTIVE: We aimed to evaluate determinants of functional outcome after pediatric hemispherotomy in a large and recent multicenter cohort. METHODS: We retrospectively investigated the functional outcomes of 455 children who underwent hemispherotomy at 5 epilepsy centers in 2000-2016. We identified determinants of unaided walking, voluntary grasping with the hemiplegic hand, and speaking through Bayesian multivariable regression modeling using missing data imputation. RESULTS: Seventy-five percent of children were seizure-free, and 44% stopped antiseizure medication at a 5.1-year mean follow-up (range = 1-17.1). Seventy-seven percent of children could walk unaided, 8% could grasp voluntarily, and 68% could speak at the last follow-up. Children were unlikely to walk when they had contralateral magnetic resonance imaging (MRI) abnormalities (40/73, p = 0.04), recurrent seizures following hemispherotomy (62/109, p = 0.04), and moderately (50/61, p = 0.03) or severely impaired (127/199, p = 0.001) postsurgical intellectual functioning, but were likely to walk when they were older at outcome determination (p = 0.01). Children were unlikely to grasp voluntarily with the hand contralateral to surgery when they had Rasmussen encephalitis (0/61, p = 0.001) or Sturge-Weber syndrome (0/32, p = 0.007). Children were unlikely to speak when they had contralateral MRI abnormalities (30/69, p = 0.002) and longer epilepsy duration (p = 0.01), but likely to speak when they had Sturge-Weber syndrome (29/35, p = 0.01), were older at surgery (p = 0.04), and were older at outcome determination (p < 0.001). INTERPRETATION: Etiology and bilaterality of structural brain abnormalities were key determinants of functional outcome after hemispherotomy. Longer epilepsy duration affected language outcomes. Not surprisingly, walking and talking ability increased with older age at outcome evaluation. ANN NEUROL 2024;95:377-387.

Analysis of 567,758 randomized controlled trials published over 30 years reveals trends in phrases used to discuss results that do not reach statistical significance.

The power of language to modify the reader's perception of interpreting biomedical results cannot be underestimated. Misreporting and misinterpretation are pressing problems in randomized controlled trials (RCT) output. This may be partially related to the statistical significance paradigm used in clinical trials centered around a P value below 0.05 cutoff. Strict use of this P value may lead to strategies of clinical researchers to describe their clinical results with P values approaching but not reaching the threshold to be "almost significant." The question is how phrases expressing nonsignificant results have been reported in RCTs over the past 30 years. To this end, we conducted a quantitative analysis of English full texts containing 567,758 RCTs recorded in PubMed between 1990 and 2020 (81.5% of all published RCTs in PubMed). We determined the exact presence of 505 predefined phrases denoting results that approach but do not cross the line of formal statistical significance (P < 0.05). We modeled temporal trends in phrase data with Bayesian linear regression. Evidence for temporal change was obtained through Bayes factor (BF) analysis. In a randomly sampled subset, the associated P values were manually extracted. We identified 61,741 phrases in 49,134 RCTs indicating almost significant results (8.65%; 95% confidence interval (CI): 8.58% to 8.73%). The overall prevalence of these phrases remained stable over time, with the most prevalent phrases being "marginally significant" (in 7,735 RCTs), "all but significant" (7,015), "a nonsignificant trend" (3,442), "failed to reach statistical significance" (2,578), and "a strong trend" (1,700). The strongest evidence for an increased temporal prevalence was found for "a numerical trend," "a positive trend," "an increasing trend," and "nominally significant." In contrast, the phrases "all but significant," "approaches statistical significance," "did not quite reach statistical significance," "difference was apparent," "failed to reach statistical significance," and "not quite significant" decreased over time. In a random sampled subset of 29,000 phrases, the manually identified and corresponding 11,926 P values, 68,1% ranged between 0.05 and 0.15 (CI: 67. to 69.0; median 0.06). Our results show that RCT reports regularly contain specific phrases describing marginally nonsignificant results to report P values close to but above the dominant 0.05 cutoff. The fact that the prevalence of the phrases remained stable over time indicates that this practice of broadly interpreting P values close to a predefined threshold remains prevalent. To enhance responsible and transparent interpretation of RCT results, researchers, clinicians, reviewers, and editors may reduce the focus on formal statistical significance thresholds and stimulate reporting of P values with corresponding effect sizes and CIs and focus on the clinical relevance of the statistical difference found in RCTs.

Potential merits and flaws of large language models in epilepsy care: A critical review.

The current pace of development and applications of large language models (LLMs) is unprecedented and will impact future medical care significantly. In this critical review, we provide the background to better understand these novel artificial intelligence (AI) models and how LLMs can be of future use in the daily care of people with epilepsy. Considering the importance of clinical history taking in diagnosing and monitoring epilepsy-combined with the established use of electronic health records-a great potential exists to integrate LLMs in epilepsy care. We present the current available LLM studies in epilepsy. Furthermore, we highlight and compare the most commonly used LLMs and elaborate on how these models can be applied in epilepsy. We further discuss important drawbacks and risks of LLMs, and we provide recommendations for overcoming these limitations.

N-of-1 trials in epilepsy: A systematic review and lessons paving the way forward.

OBJECTIVE: Defined as prospective single-patient crossover studies with repeated paired cycles of active and control intervention, N-of-1 trials have gained attention as an option to obtain high-quality evidence of efficacy, particularly for patients with rare epilepsies in whom conduction of well-powered randomized controlled trials can be challenging. The objective of this systematic review is to provide an appraisal of the literature on N-of-1 trials in individuals with epilepsy. METHODS: We searched PubMed and Embase on January 12, 2024, for studies meeting the following criteria: prospectively planned, within-patient, multiple-crossover design in individuals with epilepsy and outcomes related to comorbidities. Information on design, outcome measurements, intervention, and analyses was retrieved. Risk of bias assessment was performed using the Risk of Bias in N-of-1 Trials (RoBiNT) scale. We highlighted methodological aspects of the N-of-1 trials identified and discuss future recommendations. RESULTS: Five studies met our inclusion criteria. An additional multiple-crossover trial that evaluated treatment effects exclusively at group level was also included because of its relevance to N-of-1 study methodology. The studies enrolled individuals with focal seizures, absences or cognitive impairement and electrographic discharges. Treatments included established or investigational antiseizure medications, off-label medications, neurostimulation or lifestyle intervention. Three of the five N-of-1 trials reported on individual cases. The studies' strengths were the use of individualized treatment dosages and symptom-specific patient-reported outcomes. Limitations were related to minimal reporting of baseline characteristics and seizure burden. SIGNIFICANCE: The trials identified by our search exemplify how the N-of-1 design can be applied to assess interventions in individuals with epilepsy-related disorders. Future N-of-1 trials of antiseizure interventions should take into account baseline seizure frequency, should apply statistical models suited to capture seizure frequency changes reliably and make predefined interim assessments. Non-seizure outcome measures evaluable over short periods should be considered. Tailored N-of-1 methodology could pave the way to evidence-based, treatment selection for patients with rare epilepsies.

The methodological quality of 176,620 randomized controlled trials published between 1966 and 2018 reveals a positive trend but also an urgent need for improvement.

Many randomized controlled trials (RCTs) are biased and difficult to reproduce due to methodological flaws and poor reporting. There is increasing attention for responsible research practices and implementation of reporting guidelines, but whether these efforts have improved the methodological quality of RCTs (e.g., lower risk of bias) is unknown. We, therefore, mapped risk-of-bias trends over time in RCT publications in relation to journal and author characteristics. Meta-information of 176,620 RCTs published between 1966 and 2018 was extracted. The risk-of-bias probability (random sequence generation, allocation concealment, blinding of patients/personnel, and blinding of outcome assessment) was assessed using a risk-of-bias machine learning tool. This tool was simultaneously validated using 63,327 human risk-of-bias assessments obtained from 17,394 RCTs evaluated in the Cochrane Database of Systematic Reviews (CDSR). Moreover, RCT registration and CONSORT Statement reporting were assessed using automated searches. Publication characteristics included the number of authors, journal impact factor (JIF), and medical discipline. The annual number of published RCTs substantially increased over 4 decades, accompanied by increases in authors (5.2 to 7.8) and institutions (2.9 to 4.8). The risk of bias remained present in most RCTs but decreased over time for allocation concealment (63% to 51%), random sequence generation (57% to 36%), and blinding of outcome assessment (58% to 52%). Trial registration (37% to 47%) and the use of the CONSORT Statement (1% to 20%) also rapidly increased. In journals with a higher impact factor (>10), the risk of bias was consistently lower with higher levels of RCT registration and the use of the CONSORT Statement. Automated risk-of-bias predictions had accuracies above 70% for allocation concealment (70.7%), random sequence generation (72.1%), and blinding of patients/personnel (79.8%), but not for blinding of outcome assessment (62.7%). In conclusion, the likelihood of bias in RCTs has generally decreased over the last decades. This optimistic trend may be driven by increased knowledge augmented by mandatory trial registration and more stringent reporting guidelines and journal requirements. Nevertheless, relatively high probabilities of bias remain, particularly in journals with lower impact factors. This emphasizes that further improvement of RCT registration, conduct, and reporting is still urgently needed.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Continuous Theta-Burst Stimulation of the Contralesional Primary Motor Cortex for Promotion of Upper Limb Recovery After Stroke: A Randomized Controlled Trial.

BACKGROUND: Despite improvements in acute stroke therapies and rehabilitation strategies, many stroke patients are left with long-term upper limb motor impairment. We assessed whether an inhibitory repetitive transcranial magnetic stimulation treatment paradigm started within 3 weeks after stroke onset promotes upper limb motor recovery. METHODS: We performed a single-center randomized, sham-controlled clinical trial. Patients with ischemic stroke or intracerebral hemorrhage and unilateral upper limb motor impairment were randomized to 10 daily sessions of active or sham continuous theta-burst stimulation (cTBS) of the contralesional primary motor cortex combined with standard upper limb therapy, started within 3 weeks after stroke onset. The primary outcome was the change in the Action Research Arm Test score from baseline (pretreatment) at 3 months after stroke. Secondary outcomes included the score on the modified Rankin Scale at 3 months and the length of stay at the rehabilitation center. Statistical analyses were performed using mixed models for repeated measures. RESULTS: We enrolled 60 patients between April 2017 and February 2021, of whom 29 were randomized to active cTBS and 31 to sham cTBS. One patient randomized to active cTBS withdrew consent before the intervention and was excluded from the analyses. The mean difference in the change in Action Research Arm Test score from baseline at 3 months poststroke was 9.6 points ([95% CI, 1.2-17.9]; P=0.0244) in favor of active cTBS. Active cTBS was associated with better scores on the modified Rankin Scale at 3 months (OR, 0.2 [95% CI, 0.1-0.8]; P=0.0225) and with an 18 days shorter length of stay at the rehabilitation center than sham cTBS ([95% CI, 0.0-36.4]; P=0.0494). There were no serious adverse events. CONCLUSIONS: Ten daily sessions of cTBS of the contralesional primary motor cortex combined with upper limb training, started within 3 weeks after stroke onset, promote recovery of the upper limb, reduce disability and dependence and leads to earlier discharge from the rehabilitation center. REGISTRATION: URL: https://trialsearch.who.int/; Unique identifier: NTR6133.

Transforming epilepsy research: A systematic review on natural language processing applications.

Despite improved ancillary investigations in epilepsy care, patients' narratives remain indispensable for diagnosing and treatment monitoring. This wealth of information is typically stored in electronic health records and accumulated in medical journals in an unstructured manner, thereby restricting complete utilization in clinical decision-making. To this end, clinical researchers increasing apply natural language processing (NLP)-a branch of artificial intelligence-as it removes ambiguity, derives context, and imbues standardized meaning from free-narrative clinical texts. This systematic review presents an overview of the current NLP applications in epilepsy and discusses the opportunities and drawbacks of NLP alongside its future implications. We searched the PubMed and Embase databases with a "natural language processing" and "epilepsy" query (March 4, 2022) and included original research articles describing the application of NLP techniques for textual analysis in epilepsy. Twenty-six studies were included. Fifty-eight percent of these studies used NLP to classify clinical records into predefined categories, improving patient identification and treatment decisions. Other applications of NLP had structured clinical information retrieval from electronic health records, scientific papers, and online posts of patients. Challenges and opportunities of NLP applications for enhancing epilepsy care and research are discussed. The field could further benefit from NLP by replicating successes in other health care domains, such as NLP-aided quality evaluation for clinical decision-making, outcome prediction, and clinical record summarization.

Not surgical technique, but etiology, contralateral MRI, prior surgery, and side of surgery determine seizure outcome after pediatric hemispherotomy.

OBJECTIVE: We aimed to assess determinants of seizure outcome following pediatric hemispherotomy in a contemporary cohort. METHODS: We retrospectively analyzed the seizure outcomes of 457 children who underwent hemispheric surgery in five European epilepsy centers between 2000 and 2016. We identified variables related to seizure outcome through multivariable regression modeling with missing data imputation and optimal group matching, and we further investigated the role of surgical technique by Bayes factor (BF) analysis. RESULTS: One hundred seventy seven children (39%) underwent vertical and 280 children (61%) underwent lateral hemispherotomy. Three hundred forty-four children (75%) achieved seizure freedom at a mean follow-up of 5.1 years (range 1 to 17.1). We identified acquired etiology other than stroke (odds ratio [OR] 4.4, 95% confidence interval (CI) 1.1-18.0), hemimegalencephaly (OR 2.8, 95% CI 1.1-7.3), contralateral magnetic resonance imaging (MRI) findings (OR 5.5, 95% CI 2.7-11.1), prior resective surgery (OR 5.0, 95% CI 1.8-14.0), and left hemispherotomy (OR 2.3, 95% CI 1.3-3.9) as significant determinants of seizure recurrence. We found no evidence of an impact of the hemispherotomy technique on seizure outcome (the BF for a model including the hemispherotomy technique over the null model was 1.1), with comparable overall major complication rates for different approaches. SIGNIFICANCE: Knowledge about the independent determinants of seizure outcome following pediatric hemispherotomy will improve the counseling of patients and families. In contrast to previous reports, we found no statistically relevant difference in seizure-freedom rates between the vertical and horizontal hemispherotomy techniques when accounting for different clinical features between groups.

Diet as connecting factor: Functional brain connectivity in relation to food intake and sucrose tasting, assessed with resting-state functional MRI in rats.

Eating disorders and obesity form a major health problem in Western Society. To be able to provide adequate treatment and prevention, it is necessary to understand the neural mechanisms underlying the development of eating disorders and obesity. Specific brain networks have been shown to be involved in feeding behavior. We therefore hypothesized that functional connectivity in neural networks involved in feeding behavior is dependent on the status of homeostatic energy balance, thus on being hungry or satiated. To test our hypothesis, we measured functional connectivity and amplitudes of neural signals within neural networks in relation to food intake and sucrose tasting in rats. Therefore, 16 male Wistar rats, of which eight were food-restricted and eight were satiated, underwent resting-state functional magnetic resonance imaging (rs-fMRI) at 9.4 T. Subsequently, half of these animals underwent a sucrose tasting procedure followed by a second rs-fMRI scan. Functional connectivity and amplitude of low-frequency signal fluctuations were statistically analyzed in a linear mixed model. Although we did not detect a significant effect of food intake on functional connectivity before sucrose tasting, there was a trend toward interaction between group (satiated vs. hungry) and treatment (sucrose tasting). Functional connectivity between feeding-related regions tended to decrease stronger upon sucrose tasting in satiated rats as compared to food-restricted rats. Furthermore, rs-fMRI signal amplitudes decreased stronger upon sucrose tasting in satiated rats, as compared to food-restricted rats. These findings indicate that food intake and sucrose tasting can affect functional network organization, which may explain the specific patterns in feeding behavior.

Reappraisal of the Medical Research Council Antiepileptic Drug Withdrawal Study: Contamination-adjusted and dose-response re-analysis.

OBJECTIVE: The 1991 Medical Research Council (MRC) Study compared seizure relapse for seizure-free patients randomized to withdraw vs continue of antiseizure medications (ASMs). We re-analyzed this trial to account for crossover between arms using contamination-adjusted intention to treat (CA ITT) methods, to explore dose-response curves, and to validate predictions against external data. ITT assesses the effect of being randomized to withdraw, as-treated analysis assesses the confounded effect of withdrawing, but CA ITT assesses the unconfounded effect of actually withdrawing. METHODS: CA ITT involves two stages. First, we used randomized arm to predict whether patients withdrew their ASM (logistic) or total daily ASM dose (linear). Second, we used those values to predict seizure occurrence (logistic). RESULTS: The trial randomized 503 patients to withdraw and 501 patients to continue ASMs. We found that 316 of 376 patients (88%) who were randomized to withdraw decreased their dose at every pre-seizure visit, compared with 35 of 424 (8%) who were randomized to continue (p < .01). Adjusted odds ratios of a 2-year seizure for those who withdrew vs those who did not was 1.3 (95% confidence interval [CI] 0.9-1.9) in the as-treated analysis, 2.5 (95% CI 1.9-3.4) comparing those randomized to withdraw vs continue for ITT, and 3.1 (95% CI 2.1-4.5) for CA ITT. Probabilities (withdrawal vs continue) were 28% vs 24% (as-treated), 40% vs 22% (ITT), and 43% vs 21% (CA ITT). Differences between ITT and CA ITT were greater when varying the predictor (reaching zero ASMs) or outcome (1-year seizures). As-treated dose-response curves demonstrated little to no effects, but larger effects in CA ITT analysis. MRC data overpredicted risk in Lossius data, with moderate discrimination (areas under the curve ~0.70). SIGNIFICANCE: CA ITT results (the effect of actually withdrawing ASMs on seizures) were slightly greater than ITT effects (the effect of recommend withdrawing ASMs on seizures). How these findings affect clinical practice must be individualized.

Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study.

BACKGROUND: For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal. METHODS: This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions. RESULTS: Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44). CONCLUSIONS: Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate.

Activation response and functional connectivity change in rat cortex after bilateral transcranial direct current stimulation-An exploratory study.

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique implicated as a promising adjunct therapy to improve motor function through the neuromodulation of brain networks. Particularly bilateral tDCS, which affects both hemispheres, may yield stronger effects on motor learning than unilateral stimulation. Therefore, the aim of this exploratory study was to develop an experimental model for simultaneous magnetic resonance imaging (MRI) and bilateral tDCS in rats, to measure instant and resultant effects of tDCS on network activity and connectivity. Naïve, male Sprague-Dawley rats were divided into a tDCS (n = 7) and sham stimulation group (n = 6). Functional MRI data were collected during concurrent bilateral tDCS over the sensorimotor cortex, while resting-state functional MRI and perfusion MRI were acquired directly before and after stimulation. Bilateral tDCS induced a hemodynamic activation response, reflected by a bilateral increase in blood oxygenation level-dependent signal in different cortical areas, including the sensorimotor regions. Resting-state functional connectivity within the cortical sensorimotor network decreased after a first stimulation session but increased after a second session, suggesting an interaction between multiple tDCS sessions. Perfusion MRI revealed no significant changes in cerebral blood flow after tDCS. Our exploratory study demonstrates successful application of an MRI-compatible bilateral tDCS setup in an animal model. Our results indicate that bilateral tDCS can locally modulate neuronal activity and connectivity, which may underlie its therapeutic potential.

Bayesian model-averaged meta-analysis in medicine.

We outline a Bayesian model-averaged (BMA) meta-analysis for standardized mean differences in order to quantify evidence for both treatment effectiveness δ and across-study heterogeneity τ . We construct four competing models by orthogonally combining two present-absent assumptions, one for the treatment effect and one for across-study heterogeneity. To inform the choice of prior distributions for the model parameters, we used 50% of the Cochrane Database of Systematic Reviews to specify rival prior distributions for δ and τ . The relative predictive performance of the competing models and rival prior distributions was assessed using the remaining 50% of the Cochrane Database. On average, ℋ1r -the model that assumes the presence of a treatment effect as well as across-study heterogeneity-outpredicted the other models, but not by a large margin. Within ℋ1r , predictive adequacy was relatively constant across the rival prior distributions. We propose specific empirical prior distributions, both for the field in general and for each of 46 specific medical subdisciplines. An example from oral health demonstrates how the proposed prior distributions can be used to conduct a BMA meta-analysis in the open-source software R and JASP. The preregistered analysis plan is available at https://osf.io/zs3df/.

Epilepsy in a health district in North-West Cameroon: Clinical characteristics and treatment gap.

INTRODUCTION: Epilepsy is a common yet misunderstood condition in Cameroon, including in the Batibo Health district. METHODS: This cross-sectional study describes epilepsy clinical characteristics, the treatment gap, and associated factors in a rural district in Cameroon. After screening for epilepsy using a door-to-door survey, physicians confirmed suspected cases of epilepsy. Detailed information on the medical, seizure, and treatment history was collected from everyone with epilepsy, followed by a general and neurological examination. RESULTS: We diagnosed 546 people with active epilepsy (at least one seizure in the previous 12 months). The mean age of people with active epilepsy was 25.2 years (SD: 11.1). The mean age at first seizure was 12.5 years (SD: 8.2). Convulsive seizures (uncertain whether generalized or focal) were the most common seizure types (60%), while 41% had focal-onset seizures. About 60% of people had seizures at least monthly. One-quarter of participants had had at least one episode of status epilepticus. Anti-seizure medication (ASM) was taken by 85%, but most were receiving inappropriate treatment or were non-adherent, hence the high treatment gap (80%). Almost a third had had seizure-related injuries. Epilepsy was responsible for low school attendance; 74% of school dropouts were because of epilepsy. CONCLUSION: The high proportion of focal-onset seizures suggests acquired causes (such as neurocysticercosis and onchocerciasis, both endemic in this area). The high epilepsy treatment gap and the high rates of status epilepticus and epilepsy-related injuries underscore the high burden of epilepsy in this rural Cameroonian health district.

Oligodendroglial myelination requires astrocyte-derived lipids.

In the vertebrate nervous system, myelination of axons for rapid impulse propagation requires the synthesis of large amounts of lipids and proteins by oligodendrocytes and Schwann cells. Myelin membranes are thought to be cell-autonomously assembled by these axon-associated glial cells. Here, we report the surprising finding that in normal brain development, a substantial fraction of the lipids incorporated into central nervous system (CNS) myelin are contributed by astrocytes. The oligodendrocyte-specific inactivation of sterol regulatory element-binding protein (SREBP) cleavage-activating protein (SCAP), an essential coactivator of the transcription factor SREBP and thus of lipid biosynthesis, resulted in significantly retarded CNS myelination; however, myelin appeared normal at 3 months of age. Importantly, embryonic deletion of the same gene in astrocytes, or in astrocytes and oligodendrocytes, caused a persistent hypomyelination, as did deletion from astrocytes during postnatal development. Moreover, when astroglial lipid synthesis was inhibited, oligodendrocytes began incorporating circulating lipids into myelin membranes. Indeed, a lipid-enriched diet was sufficient to rescue hypomyelination in these conditional mouse mutants. We conclude that lipid synthesis by oligodendrocytes is heavily supplemented by astrocytes in vivo and that horizontal lipid flux is a major feature of normal brain development and myelination.

Design and Evaluation of a Rodent-Specific Transcranial Magnetic Stimulation Coil: An In Silico and In Vivo Validation Study.

BACKGROUND: Rodent models are fundamental in unraveling cellular and molecular mechanisms of transcranial magnetic stimulation (TMS)-induced effects on the brain. However, proper translation of human TMS protocols to animal models have been restricted by the lack of rodent-specific focal TMS coils. OBJECTIVE: We aimed to improve TMS focalization in rodent brain with a novel small, cooled, and rodent-specific TMS coil. METHODS: A rodent-specific 25-mm figure-of-eight TMS coil was developed. Stimulation focalization was simulated in silico for the rodent coil and a commercial human 50-mm figure-of-eight TMS coil. Both coils were also compared in vivo by electromyography measurements of brachialis motor evoked potential (MEP) responses to TMS at different brain sites in anesthetized rats (n = 6). Focalization was determined from the coils' level of stimulation laterality. Differences in MEPs were statistically analyzed with repeated-measures, within-subjects, ANOVA. RESULTS: In silico simulation results deemed the human coil insufficient for unilateral stimulation of the rat motor cortex, whereas lateralized electrical field induction was projected attainable with the rodent coil. Cortical, in vivo MEP amplitude measurements from multiple points in each hemisphere, revealed unilateral activation of the contralateral brachialis muscle, in absence of ipsilateral brachialis activation, with both coils. CONCLUSION: Computer simulations motivated the design of a smaller rodent-specific TMS coil, but came short in explaining the capability of a larger commercial human coil to induce unilateral MEPs in vivo. Lateralized TMS, as demonstrated for both TMS coils, corroborates their use in translational rodent studies, to elucidate mechanisms of action of therapeutic TMS protocols.

Differences in structural and functional networks between young adult and aged rat brains before and after stroke lesion simulations.

Neural network changes during aging may contribute to vulnerability and resilience to brain lesions in age-related neurological disorders, such as stroke. However, the relationship between age-related neural network features and stroke outcome is unknown. Therefore, we assessed structural and functional network status in young adult and aged rat brain, and measured the effects of simulated stroke lesions. Eleven rats underwent diffusion-weighted MRI and resting-state functional MRI at young adult age (post-natal day 88) and old age (between post-natal day 760 and 880). Structural and functional brain network features were calculated from graph-based network analysis. We performed three lesion simulations based on the brain injury pattern in frequently applied rodent stroke models, i.e. a small cortical lesion, a subcortical lesion, or a large cortical plus subcortical lesion, for which we computationally removed the involved network regions. Global network characteristics, i.e. integration and segregation, were not significantly different between the two age groups. However, we detected local differences in structural and functional networks between young adult and old rats, mainly reflected by shifts of hub regions. Stroke lesion simulations induced significant global and local network changes, characterized by lower efficiency and shifts of hub regions in structural and functional networks, which was most evident after a large cortical plus subcortical lesion. Functional and structural hub region shifts after lesion simulations differed between young adult and aged rats. Our lesion simulation study demonstrates that age-dependent brain network status affects structural and functional network reorganization after stroke, particularly involving hub shifts, which may influence functional outcome. Computational lesion studies offer a cheap and simple alternative to empirical studies and can complement or guide more complicated experimental studies in animal models and patients.

Minimum spanning tree analysis of the human connectome.

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models.

Tailoring epilepsy surgery with fast ripples in the intraoperative electrocorticogram.

OBJECTIVE: Intraoperative electrocorticography (ECoG) can be used to delineate the resection area in epilepsy surgery. High-frequency oscillations (HFOs; 80-500 Hz) seem better biomarkers for epileptogenic tissue than spikes. We studied how HFOs and spikes in combined pre- and postresection ECoG predict surgical outcome in different tailoring approaches. METHODS: We, retrospectively, marked HFOs, divided into fast ripples (FRs; 250-500 Hz) and ripples (80-250 Hz), and spikes in pre- and postresection ECoG sampled at 2,048 Hz in people with refractory focal epilepsy. We defined four groups of electroencephalography (EEG) event occurrence: pre+post- (+/-), pre+post+ (+/+), pre-post+ (-/+) and pre-post- (-/-). We subcategorized three tailoring approaches: hippocampectomy with tailoring for neocortical involvement; lesionectomy of temporal lesions with tailoring for mesiotemporal involvement; and lesionectomy with tailoring for surrounding neocortical involvement. We compared the percentage of resected pre-EEG events, time to recurrence, and the different tailoring approaches to outcome (seizure-free vs recurrence). RESULTS: We included 54 patients (median age, 15.5 years; 25 months of follow-up; 30 seizure free). The percentage of resected FRs, ripples, or spikes in pre-ECoG did not predict outcome. The occurrence of FRs in post-ECoG, given FRs in pre-ECoG (+/-, +/+), predicted outcome (hazard ratio, 3.13; confidence interval = 1.22-6.25; p = 0.01). Seven of 8 patients without spikes in pre-ECoG were seizure free. The highest predictive value for seizure recurrence was presence of FRs in post-ECoG for all tailoring approaches. INTERPRETATION: FRs that persist before and after resection predict poor postsurgical outcome. These findings hold for different tailoring approaches. FRs can thus be used for tailoring epilepsy surgery with repeated intraoperative ECoG measurements. Ann Neurol 2017;81:664-676.