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Despite clinical symptoms, a large majority of people with mild traumatic brain injury (TBI) have normal computed tomography (CT) and magnetic resonance imaging (MRI) scans. Therefore, present-day neuroimaging tools are insufficient to diagnose or classify low grades of TBI. Advanced neuroimaging techniques, such as diffusion-weighted and functional MRI, may yield novel biomarkers that may aid in the diagnosis of TBI. Therefore, the present study had two aims: first, to characterize the development of MRI-based measures of structural and functional changes in gray and white matter regions from acute to chronic stages after mild and moderate TBI; and second, to identify the imaging markers that can most accurately predict outcome after TBI. To these aims, 52 rats underwent serial functional (resting-state) and structural (T1-, T2-, and diffusion-weighted) MRI before and 1 h, 1 day, 1 week, 1 month and 3-4 months after mild or moderate experimental TBI. All rats underwent behavioral testing. Histology was performed in subgroups of rats at different time points. Early after moderate TBI, axial and radial diffusivities were increased, and fractional anisotropy was reduced in the corpus callosum and bilateral hippocampi, which normalized over time and was paralleled by recovery of sensorimotor function. Correspondingly, histology revealed decreased myelin staining early after TBI, which was not detected at chronic stages. No significant changes in individual outcome measures were detected after mild TBI. However, multivariate analysis showed a significant additive contribution of diffusion parameters in the distinction between control and different grades of TBI-affected brains. Therefore, combining multiple imaging markers may increase the sensitivity for TBI-related pathology.

BackgroundMany 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 including reporting guidelines, but it is unknown whether these efforts have improved RCT quality (i.e. reduced risk of bias). We therefore mapped trends over time in trial publication, trial registration, reporting according to CONSORT, and characteristics of publication and authors.MethodsMeta-information of 176,620 RCTs published between 1966 and 2018 was extracted. Risk of bias probability (four domains: random sequence generation, allocation concealment, blinding of patients/personnel, and blinding of outcome assessment) was assessed using validated risk-of-bias machine learning tools. In addition, trial registration and reporting according to CONSORT were assessed with automated searches. Characteristics were extracted related to publication (number of authors, journal impact factor, medical discipline) and authors (gender and Hirsch-index).FindingsThe annual number of published RCTs substantially increased over four decades, accompanied by increases in the number of authors (5.2 to 7.8), institutions (2.9 to 4.8), female authors (20 to 42%, first authorship; 17 to 29%, last authorship), and Hirsch-indices (10 to 14, first authorship; 16 to 28, last authorship). Risk of bias remained present in most RCTs but decreased over time for the domains 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 CONSORT (1 to 20%) rapidly increased in the latest period. In journals with higher impact factor (>10), risk of bias was consistently lower, higher levels of trial registration more frequent, and mentioning CONSORT.InterpretationThe likelihood of bias in RCTs has generally decreased over the last decades. This may be driven by increased knowledge and improved education, 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.FundingThis study was funded by The Netherlands Organisation for Health Research and Development (445001002).

An improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional and macro-scale diffusion-based structural connectivity, but no significant correlation between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Zooming in on individual connections, we found strong functional connectivity in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Although characteristics of the applied techniques may affect where structural and functional networks (dis)agree, distinct structure-function relationships across the brain could also have a biological basis.

Background Surgery is a widely accepted treatment option for drug-resistant focal epilepsy. A detailed analysis of longitudinal postoperative seizure outcomes and use of antiepileptic drugs for different brain lesions causing epilepsy is not available. We aimed to analyse the association between histopathology and seizure outcome and drug freedom up to 5 years after epilepsy surgery, to improve presurgical decision making and counselling.Methods In this retrospective, multicentre, longitudinal, cohort study, patients who had epilepsy surgery between Jan 1, 2000, and Dec 31, 2012, at 37 collaborating tertiary referral centres across 18 European countries of the European Epilepsy Brain Bank consortium were assessed. We included patients of all ages with histopathology available after epilepsy surgery. Histopathological diagnoses and a minimal dataset of clinical variables were collected from existing local databases and patient records. The primary outcomes were freedom from disabling seizures (Engel class 1) and drug freedom at 1, 2, and 5 years after surgery. Proportions of individuals who were Engel class 1 and drug-free were reported for the 11 main categories of histopathological diagnosis. We analysed the association between histopathology, duration of epilepsy, and age at surgery, and the primary outcomes using random effects multivariable logistic regression to control for confounding.Findings 9147 patients were included, of whom seizure outcomes were available for 8191 (89.5%) participants at 2 years, and for 5577 (61.0%) at 5 years. The diagnoses of low-grade epilepsy associated neuroepithelial tumour (LEAT), vascular malformation, and hippocampal sclerosis had the best seizure outcome at 2 years after surgery, with 77.5% (1027 of 1325) of patients free from disabling seizures for LEAT, 74.0% (328 of 443) for vascular malformation, and 71.5% (2108 of 2948) for hippocampal sderosis. The worst seizure outcomes at 2 years were seen for patients with focal cortical dysplasia type I or mild malformation of cortical development (50.0%, 213 of 426 free from disabling seizures), those with malformation of cortical development-other (52.3%, 212 of 405 free from disabling seizures), and for those with no histopathological lesion (53.5%, 396 of 740 free from disabling seizures). The proportion of patients being both Engel class 1 and drug-free was 0-14% at 1 year and increased to 14-51% at 5 years. Children were more often drug-free; temporal lobe surgeries had the best seizure outcomes; and a longer duration of epilepsy was associated with reduced chance of favourable seizure outcomes and drug freedom. This effect of duration was evident for all lesions, except for hippocampal sclerosis.Interpretation Histopathological diagnosis, age at surgery, and duration of epilepsy are important prognostic factors for outcomes of epilepsy surgery. In every patient with refractory focal epilepsy presumed to be lesional, evaluation for surgery should be considered. Copyright (C) 2020 Elsevier Ltd. All rights reserved.

Diffusion MRI (dMRI)-based tractography offers unique abilities to map whole-brain structural connections in human and animal brains. However, dMRI-based tractography indirectly measures white matter tracts, with suboptimal accuracy and reliability. Recently, sophisticated methods including constrained spherical deconvolution (CSD) and global tractography have been developed to improve tract reconstructions through modeling of more complex fiber orientations. Our study aimed to determine the accuracy of connectome reconstruction for three dMRI-based tractography approaches: diffusion tensor (DT)-based, CSD-based and global tractography. Therefore, we validated whole brain structural connectome reconstructions based on ten ultrahigh-resolution dMRI rat brain scans and 106 cortical regions, from which varying tractography parameters were compared against standardized neuronal tracer data. All tested tractography methods generated considerable numbers of false positive and false negative connections. There was a parameter range trade-off between sensitivity: 0.06-0.63 interhemispherically and 0.22-0.86 intrahemispherically; and specificity: 0.99-0.60 interhemispherically and 0.99-0.23 intrahemispherically. Furthermore, performance of all tractography methods decreased with increasing spatial distance between connected regions. Similar patterns and trade-offs were found, when we applied spherical deconvolution informed filtering of tractograms, streamline thresholding and group-based average network thresholding. Despite the potential of CSD-based and global tractography to handle complex fiber orientations at voxel level, reconstruction accuracy, especially for long-distance connections, remains a challenge. Hence, connectome reconstruction benefits from varying parameter settings and combination of tractography methods to account for anatomical variation of neuronal pathways. Sinke M.R.T., Otte W.M., Christiaens D., Schmitt O., Leemans A., van der Toorn A., Sarabdjitsingh R.A., Joëls M., Dijkhuizen R.M., ''Diffusion MRI-based cortical connectome reconstruction: dependency on tractography procedures and neuroanatomical characteristics'', Brain structure and function, 2018 (in press). ispartof: Brain Structure and Function vol:223 issue:5 pages:2269-2285 ispartof: location:Germany status: published

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.

Functional outcome after stroke depends on the local site of ischemic injury and on remote effects within connected networks, frequently extending into the contralesional hemisphere. However, the pattern of large-scale contralesional network remodeling remains largely unresolved. In this study, we applied diffusion-based tractography and graph-based network analysis to measure structural connectivity in the contralesional hemisphere chronically after experimental stroke in rats. We used the minimum spanning tree method, which accounts for variations in network density, for unbiased characterization of network backbones that form the strongest connections in a network. Ultrahigh-resolution diffusion MRI scans of eight post-mortem rat brains collected 70 days after right-sided stroke were compared against scans from 10 control brains. Structural network backbones of the left (contralesional) hemisphere, derived from 42 atlas-based anatomical regions, were found to be relatively stable across stroke and control animals. However, several sensorimotor regions showed increased connection strength after stroke. Sensorimotor function correlated with specific contralesional sensorimotor network backbone measures of global integration and efficiency. Our findings point toward post-stroke adaptive reorganization of the contralesional sensorimotor network with recruitment of distinct sensorimotor regions, possibly through strengthening of connections, which may contribute to functional recovery.

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

Herm Lamberink promoveerde cum laude op 15 oktober 2019 bij de Universiteit Utrecht1. Lamberink beschrijft in zijn proefschrift ‘Antiepileptic drug withdrawal’ hoe het risico van staken van de medicamenteuze behandeling beter en meer toegespitst ingeschat kan worden. Hij past deze risico-inschatting ook toe op kinderen die epilepsiechirurgie hebben ondergaan en in aanmerking komen om te stoppen met anti-epileptica.

Van de mensen die baat hebben bij medicatie en aanvalsvrij worden kan een groot deel na enige tijd de therapie staken zonder dat aanvallen terugkeren. Dit roept meteen twee vragen op: (1) wie kan veilig de anti-epileptica staken en (2) hoe lang dient men te wachten voordat de medicatie afgebouwd kan worden? Om elk van deze vragen te beantwoorden werden twee predictiemodellen ontwikkeld. Deze modellen en het resultaat van toepassing hiervan worden hier besproken.

Objectivethe current epilepsy classification is primarily clinical driven and lacks a mechanistic basis. A mechanistic basis of the classification, and within the classification especially the etiology layer, may help to better understand epilepsy and the associated comorbidities. It may also be helpful in guiding epilepsy treatment. With this study we aimed to investigate if there is a modelled mechanistic underpinning for the etiological epilepsy classification by assessing the association between epilepsy etiology and brain network topology.Methodsto that aim we assessed the association between epilepsy etiology and brain network topology. We included children referred to our outpatient first seizure clinic with suspected epilepsy who had a standard interictal EEG recording. From these EEGs, functional networks were constructed based on eyes-closed resting state time-series. Networks were characterized using measures of segregation, integration, centrality, and network strength. Principal component analyses were used to assess whether patients with epilepsy of similar etiology cluster together based on their functional brain network topology.Resultsin total, 228 children with epilepsy were included. Another 402 children served as control subjects. We were not able to detect a correlation between epilepsy etiology and functional brain network topology. We also did not find a difference in brain network topology between the controls and patients with epilepsy.Conclusionsour results do not support the presence of a brain network underpinning for the etiological epilepsy classification. This may support the hypothesis that brain network abnormalities in epilepsy are a result of ongoing seizure activity rather than the epilepsy etiology itself. Further in-depth analyses of network measures and longitudinal studies are needed to confirm this hypothesis.

The effects of skill acquisition on whole-brain structure and functional networks have been extensively investigated in humans but have yet to be explored in rodents. Forelimb reaching training in rodents results in well-established focal functional and structural reorganization within the motor cortex (M1) and cerebellum, indicating distributed alterations in both structure and function. However, it is unclear how local alterations in structure and function relate to distributed learning-related changes across motor networks. Here we trained adult rats in skilled reaching and used multimodal whole-brain in vivo MRI to assess both structural and functional plasticity over time.We detected increases in a myelin-related MRI metric in white matter, cortical areas, and to a lesser extent in the cerebellum, paralleled by strengthened functional connectivity between M1 and cerebellum, possibly reflecting a decrease in cerebellum inhibition over M1. Skill learning therefore leads to myelin increases in pathways that connect sensorimotor regions, and in functional connectivity increases between areas involved in motor learning, all of which correlate with performance. These findings closely mirror previous reports of network-level changes following motor learning in humans and underlines the correspondence between human and rodent brain circuits for motor learning, despite important differences in the anatomy of physiology of movement circuits between species.

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.

People with epilepsy often report seizures precipitated by stress. This is believed to be due to effects of stress hormones, such as cortisol, on neuronal excitability. Cortisol, regardless of stress, is released in hourly pulses, whose effect on epileptic activity is unknown. We tested the relation between cortisol levels and the incidence of epileptiform abnormalities in the electroencephalogram of people with focal epilepsy. Morning cortisol levels were measured in saliva samples obtained every 15 min. Interictal epileptiform discharges were determined in the same time periods. We investigated the relationship between cortisol levels and the epileptiform discharges distinguishing persons with from those without stress-precipitated seizures (linear mixed model), and analysed the contribution of individual, epilepsy and recording characteristics with multivariable analysis. Twenty-nine recordings were performed in 21 individuals. Cortisol was positively related to incidence of epileptiform discharges (β = 0.26, P = 0.002) in people reporting stress-sensitive seizures, but not those who did not report stress sensitivity (β = -0.07, P = 0.64). The relationship between cortisol and epileptiform discharges was positively associated only with stress sensitivity of seizures (β = 0.31, P = 0.005). The relationship between cortisol levels and incidence of interictal epileptiform discharges in people with stress-sensitive seizures suggests that stress hormones influence disease activity in epilepsy, also under basal conditions.

Aim Most patients with cancers and cancer survivors use the internet to obtain health information and support each other. Our aim was evaluate whether relationships exist between the information prevalences and search volumes of terms related to various cancers and their actual incidence and mortality figures in the USA and the UK. Methods The information prevalences and search volumes of English terms related to various cancers were obtained using the Google search engine and Google Adwords. These data were plotted against actual cancer incidence and mortality data obtained using UK and USA cancer databases. Results Breast cancer and melanoma were outliers, with greater levels of information available than expected from their incidence and mortality alone. Conversely, there were disparities between the information prevalences and actual incidences of colorectal and prostate cancers, both in the USA and the UK, indicative of lower levels of information availability online for these cancers. Conclusion Disparities in health care-related information exist for some tumor types with similar incidence and mortality. Disparities in virtual health care information may also exist in reality. Infodemiological studies might be useful for planning public health measures to increase the knowledge and attitudes of the general population towards treatable or preventable diseases.

Objective Since the introduction of diffusion tensor imaging, white matter abnormalities in epilepsy have been studied extensively. However, the affected areas reported, the extent of abnormalities and the association with relevant clinical parameters are highly variable. We aimed to obtain a more consistent estimate of white matter abnormalities and their association with clinical parameters in different epilepsy types. Methods We systematically searched for differences in white matter fractional anisotropy and mean diffusivity, at regional and voxel level, between people with epilepsy and healthy controls. Meta-analyses were used to quantify the directionality and extent of these differences. Correlations between white matter differences and age of epilepsy onset, duration of epilepsy and sex were assessed with meta-regressions. Results Forty-two studies, with 1027 people with epilepsy and 1122 controls, were included with regional data. Sixteen voxel-based studies were also included. People with temporal or frontal lobe epilepsy had significantly decreased fractional anisotropy (Δ –0.021, 95% confidence interval –0.026 to –0.016) and increased mean diffusivity (Δ0.026 × 10–3 mm2/s, 0.012 to 0.039) in the commissural, association and projection white matter fibers. White matter was much less affected in generalized epilepsy. White matter changes in people with focal epilepsy correlated with age at onset, epilepsy duration and sex. Significance This study provides a better estimation of white matter changes in different epilepsies. Effects are particularly found in people with focal epilepsy. Correlations with the duration of focal epilepsy support the hypothesis that these changes are, at least partly, a consequence of seizures and may warrant early surgery. Future studies need to guarantee adequate group sizes, as white matter differences in epilepsy are small., Highlights • White matter FA and MD are more affected in focal than in generalized epilepsy. • Epilepsy subtypes show distinct patterns of affected white matter regions. • White matter integrity is altered both ipsi- and contralaterally in focal epilepsy. • White matter changes in focal epilepsy seem to be a consequence of seizures.

Knowledge of spatiotemporal patterns of language network changes may help in predicting outcome in aphasic stroke patients. Here we assessed language function and performed functional MRI four times during one year to measure language network activation and cerebrovascular reactivity (with breath-holding) in twelve left-hemispheric stroke patients, of whom two dropped out before the final measurement, and eight age-matched controls. Language outcome was related to increase of activation in left and right posterior inferior temporal gyrus over the first year, while activation increase in right inferior frontal gyrus was inversely correlated to language recovery. Outcome prediction improved by addition of early language-induced activation of the left posterior inferior temporal gyrus to a regression model with baseline language performance as first predictor. Variations in language-induced activation in right inferior frontal gyrus were primarily related to differences in vascular reactivity. Furthermore, several language-activation changes could not be linked to alterations in language proficiency nor vascular reactivity, and were assumed to be caused by unspecified intersession variability. In conclusion, early functional neuroimaging improves outcome prediction of aphasia after stroke. Controlling for cerebrovascular reactivity and unspecified intersession variability may result in more accurate assessment of the relationship between activation pattern shifts and function after stroke.

OBJECTIVES:The clinical profile of children who had possible seizures is heterogeneous, and accuracy of diagnostic testing is limited. We aimed to develop and validate a prediction model that determines the risk of childhood epilepsy by combining available information at first consultation.METHODS:We retrospectively collected data of 451 children who visited our outpatient department for diagnostic workup related to 1 or more paroxysmal event(s). At least 1 year of follow-up was available for all children who were diagnosed with epilepsy or in whom diagnosis remained inconclusive. Clinical characteristics (sex, age of first seizure, event description, medical history) and EEG report were used as predictor variables for building a multivariate logistic regression model. Performance was validated in an external cohort (n = 187).RESULTS:Model discrimination was excellent, with an area under the receiver operating characteristic curve of 0.86 (95% confidence interval [CI]; 0.80–0.92), a positive predictive value of 0.93 (95% CI 0.83–0.97) and a negative predictive value of 0.76 (95% CI 0.70–0.80). Model discrimination in a selective subpopulation of children with uncertain diagnosis after initial clinical workup was good, with an area under the receiver operating characteristic curve of 0.73 (95% CI 0.58–0.87).CONCLUSIONS:This model may prove to be valuable because predictor variables together with a first interictal EEG can be available at first consultation. A Web application is provided (http://epilepsypredictiontools.info/first-consultation) to facilitate the diagnostic process for clinicians who are confronted with children with paroxysmal events, suspected of having an epileptic origin.

The mammalian brain is composed of densely connected and interacting regions, which form structural and functional networks. An improved understanding of the structure–function relation is crucial to understand the structural underpinnings of brain function and brain plasticity after injury. It is currently unclear how functional connectivity strength relates to structural connectivity strength. We obtained an overview of recent papers that report on correspondences between quantitative functional and structural connectivity measures in the mammalian brain. We included network studies in which functional connectivity was measured with resting-state fMRI, and structural connectivity with either diffusion-weighted MRI or neuronal tract tracers. Twenty-seven of the 28 included studies showed a positive structure–function relationship. Large inter-study variations were found comparing functional connectivity strength with either quantitative diffusion-based (correlation coefficient (r) ranges: 0.18–0.82) or neuronal tracer-based structural connectivity measures (r = 0.24–0.74). Two functional datasets demonstrated lower structure–function correlations with neuronal tracer-based (r = 0.22 and r = 0.30) than with diffusion-based measures (r = 0.49 and r = 0.65). The robust positive quantitative structure–function relationship supports the hypothesis that structural connectivity provides the hardware from which functional connectivity emerges. However, methodological differences between the included studies complicate the comparison across studies, which emphasize the need for validation and standardization in brain structure–function studies.

Following the results of the multicentre European retrospective "TimeToStop" cohort study, we initiated a randomised trial to determine cognitive benefits of early postoperative antiepileptic drug withdrawal. Unfortunately, the trial failed to recruit and was terminated, as almost all parents preferred early drug withdrawal. The objectives of the current survey were to obtain insight into current practices regarding drug withdrawal after paediatric epilepsy surgery among epileptologists, and better understand the reasons for difficulties in recruitment. A survey was sent to three international epilepsy surgery networks, questioning drug withdrawal policies. Forty-seven (19%) surveys were returned. For polytherapy, withdrawal was started at a median of three and six months by the TimeToStop collaborators and other paediatric epileptologists, respectively. Withdrawal was completed at a median of 12 and 20 months, respectively. For monotherapy, tapering was initiated at five and 11 months in these two groups, and ended at a median of seven and 12 months, respectively. Most TimeToStop collaborators believed that it was not justified to wait 12 months after surgery before reducing AEDs, regardless of the number of AEDs taken. Current AED policies in Europe have changed as a consequence of the retrospective TimeToStop results, and this accounts for why recruitment in a randomised trial was not feasible.

Clinical trials have a vital role in ensuring the safety and efficacy of new treatments and interventions in medicine. A key characteristic of a clinical trial is its statistical power. Here we investigate whether the statistical power of a trial is related to the gender of first and last authors on the paper reporting the results of the trial. Based on an analysis of 31,873 clinical trials published between 1974 and 2017, we find that adequate statistical power was most often present in clinical trials with a male first author and a female last author (20.6%, 95% confidence interval 19.4-21.8%), and that this figure was significantly higher than the percentage for other gender combinations (12.5-13.5%; P

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.

Prolonged auditory sensory deprivation leads to brain reorganization, indicated by functional enhancement in remaining sensory systems, a phenomenon known as cross-modal plasticity. In this study we investigated differences in functional brain network shifts from eyes-closed to eyes-open conditions between deaf and hearing people. Electroencephalography activity was recorded in deaf (N = 71) and hearing people (N = 122) living in rural Africa, which yielded a unique data-set of congenital, pre-lingual and post-lingual deaf people, with a divergent experience in American Sign Language. Functional networks were determined from the synchronization of electroencephalography signals between fourteen electrodes distributed over the scalp. We studied the synchronization between the auditory and visual cortex and performed whole-brain minimum spanning tree analysis based on the phase lag index of functional connectivity. This tree analysis accounts for variations in global network density and allows unbiased characterization of functional network backbones. We found increased functional connectivity between the auditory and visual cortex in deaf people during the eyes-closed condition in both the alpha and beta bands. Furthermore, we found functional network backbone shifts both in deaf and healthy people as they went from eyes-closed to eyes-open conditions. In both the alpha and beta band the deafs’ brain showed larger functional backbone-shifts in node strength compared to controls. In the alpha band this shift in network strength differed among deaf participants and depended on type of deafness: congenital, pre-lingual or post-lingual deafness. In addition, a correlation was found between functional backbone characteristics and experience of sign language. Our study revealed more insights in functional network reorganization specifically due to prolonged lack of auditory input, but might also be helpful for sensory deprivation and cross-modal plasticity in general. Global cortical network reorganization in deaf people supports the plastic capacities of the young brain. The differences between type of deafness stresses that etiology affects functional reorganization, whereas the association between network organization and acquired sign language experience reflects ongoing brain adaptation in people with hearing disabilities.

Epilepsy is largely under-diagnosed in low-income and middle-income countries, due to lack of medical specialists and expensive electroencephalography (EEG) hardware. In this study we investigate if low-cost consumer-grade EEG in combination with machine learning techniques can offer a reliable screening tool to improve diagnosis rates.We acquired brain signals in people with epilepsy (N=163) and healthy controls (N=138) in two difficult-to-reach areas in rural Guinea-Bissau and Nigeria. Five minutes of fourteen channel resting-state EEG data were acquired with a portable, low-cost consumer-grade EEG recording headset. EEG channel time-series were divided in four-second artifact-free epochs and transformed into delta, theta, alpha, beta and gamma wavelet frequencies. Summary measures such as the mean, standard deviation, minimal value and maximal value of the epoch signal fluctuations were used to train a random forest classifier. Epilepsy diagnosis based on at least three months seizure calendar data was used as the gold standard diagnosis. To prevent too optimistic classification the trained model was evaluated with EEG data from subjects not used in the training. In addition, we tested a classification model trained on Nigeria data against data from people in Guinea-Bissau and vice versa. The most contributing data features in the EEG were found in the beta and theta frequencies in Guinea-Bissau and Nigeria, respectively. Within-country model performance was good with area under the receiver-operating curves of 0.85 and 0.78 (± 0.02 standard errors) in unseen data in Guinea-Bissau and Nigeria, respectively. Across-country performance was moderate (0.62 and 0.64 ± 0.02).Our data suggests that a combination of low cost electroencephalography and machine learning techniques may facilitate diagnostic screening for epilepsy in the most remote areas of the world.

OBJECTIVES: To study the statistical power of randomized clinical trials and examine developments over time.STUDY DESIGN AND SETTING: We analyzed the statistical power in 136,212 clinical trials between 1975 and 2014 extracted from meta-analyses from the Cochrane database of systematic reviews. We determined study power to detect standardized effect sizes, where power was based on the meta-analyzed effect size. Average power, effect size, and temporal patterns were examined for all meta-analyses and a subset of significant meta-analyses.RESULTS: The number of trials with power ≥80% was low (7%) but increased over time: from 5% in 1975-1979 to 9% in 2010-2014. In significant meta-analyses, the proportion of trials with sufficient power increased from 9% to 15% in these years (median power increased from 16% to 23%). This increase was mainly due to increasing sample sizes, while effect sizes remained stable with a median Cohen's h of 0.09 (interquartile range 0.04-0.22) and a median Cohen's d of 0.20 (0.11-0.40).CONCLUSION: This study demonstrates that sufficient power in clinical trials is still problematic, although the situation is slowly improving. Our data encourage further efforts to increase statistical power in clinical trials to guarantee rigorous and reproducible evidence-based medicine.

Treatment of epilepsy in low-income countries is a challenge considering the lack of resources, availability of antiepileptic drugs, and cultural beliefs. We used a community-based rehabilitation (CBR) service for the detection, monitoring, and treatment of epilepsy. A local network of trained community volunteers provided education, good quality antiepileptic drugs, and clinical follow-up for people with epilepsy (PWE). In a period of 2years, approximately 22,500 people were screened in central Guinea-Bissau, and 112 PWE were identified and registered. Monthly check-ups were offered to monitor treatment effect and increase compliance. Retrospective analysis on 81 records of patients under treatment in June 2016 showed a decrease of seizure frequency in 88.8% after treatment initiation and was maintained throughout the clinical follow-up of 15months. A conservative estimation of the treatment and monitoring of a single person with epilepsy revealed a daily cost of $0.73. Despite acknowledging epilepsy as a neglected condition by the World Health Organization (WHO), most PWE still lack appropriate treatment. Although CBR service has been suggested as efficient strategy to reduce the treatment gap, little information is available on the efficacy of the programs. Our experiences show that CBR service is a cost-effective approach to monitor treatment and increase compliance in PWE. This experience may be of value for other resource-poor settings.

Background This study assessed the epilepsy treatment gap (ETG) and factors associated with access to care and adherence from three sites of Afikpo, Ijebu-Jesa and Gwandu in the Southeast, Southwest and Northwest regions of Nigeria respectively. Methodology People with active epilepsy were recruited from a door-to-door survey undertaken between February and April 2018 using set criteria. The sociodemographic, pattern of care access and treatment-related information were obtained. ETG was defined according to International League Against Epilepsy criteria. Potential factors for ETG were examined using multivariate logistic regression with multiple imputations. Results A total of 252 subjects were recruited from the three sites. The self-reported therapeutic gap was 83.3% (95% CI:78.1–87.7), while the ETG was 94.4% (95% CI: 90.9, 96.9) considering the diagnostic gap with no difference across sites (P=0.230). The potential factors associated with failure to access to care include stigma (OR 0.16, 95% CI: 0.04–0.71; P=0.016), cultural beliefs (OR: 0.31, 95% CI: 0.16–0.62; P=0.001), difficulty reaching a health facility (OR 0.33, 95% CI: 0.14–0.75; P=0.008), and non-acceptance of diagnosis (OR 0.36, 95% 0.15–0.85; P=0.021). Factors associated with non-adherence include cultural beliefs (OR 28.68, 95% CI: 1.70– 483.97; P=0.020), afternoon seizures (OR 0.006, 95% CI: 0.001–0.58; P=0.029), learning difficulty (OR 0.16, 95% CI: 0.03–0.88; P=0.035), and difficulty reaching a health facility (OR 25.44, 95% CI: 0.88–735.88; P=0.059). Conclusion The treatment gap is high in Nigeria. The negative cultural belief can be improved by patient and community education.

Snow avalanches remain a lethal threat to skiers and snowboarders. Information campaigns in areas with ski resorts and with backcountry recreationists may help to increase awareness and consequently reduce risky behavior and casualties. However, useful targets for these campaigns are difficult to identify. Big data surveillance systems might provide promising resources for this target identification. In this study, we evaluated and characterized aggregated country-wide Web searches on snow avalanches in Italy. We aimed to identify which major factors influence online searches for avalanches and might be useful to shape awareness and information campaigns. Using Google Trends, data on search queries for the Italian term “valanga” (avalanche) between the January 1, 2004 and May 19, 2015 were collected and analyzed. Most searches occurred in mountain regions and cities. All peaks in searches volumes were temporally related to news headlines on avalanche accidents, suggesting that emotion might play a great role in using the Internet as a source of information. Public informative campaigns with high emotional content addressed to the general population might hence be considered to effectively promote awareness programs on risk of avalanches and increase public knowledge related to these persisting and serious threats.

BackgroundBiomedical studies with low statistical power are a major concern in the scientific community and are one of the underlying reasons for the reproducibility crisis in science. If randomized clinical trials, which are considered the backbone of evidence-based medicine, also suffer from low power, this could affect medical practice.MethodsWe analysed the statistical power in 137 032 clinical trials between 1975 and 2017 extracted from meta-analyses from the Cochrane database of systematic reviews. We determined study power to detect standardized effect sizes according to Cohen, and in meta-analysis with p-value below 0.05 we based power on the meta-analysed effect size. Average power, effect size and temporal patterns were examined.ResultsThe number of trials with power ≥80% was low but increased over time: from 9% in 1975–1979 to 15% in 2010–2014. This increase was mainly due to increasing sample sizes, whilst effect sizes remained stable with a median Cohen’s h of 0.21 (IQR 0.12-0.36) and a median Cohen’s d of 0.31 (0.19-0.51). The proportion of trials with power of at least 80% to detect a standardized effect size of 0.2 (small), 0.5 (moderate) and 0.8 (large) was 7%, 48% and 81%, respectively.ConclusionsThis study demonstrates that sufficient power in clinical trials is still problematic, although the situation is slowly improving. Our data encourages further efforts to increase statistical power in clinical trials to guarantee rigorous and reproducible evidence-based medicine.

Stroke is a major cause of disability; however, most patients experience spontaneous partial recovery of functions in subacute to chronic phases. Poststroke loss and recovery of functions have been increasingly correlated with brain-wide alterations in the connectivity of neural networks, which is described in this review. Elucidation of the mechanisms of functional brain remodeling could reveal targets and strategies for more effective neurorehabilitation.Data from recent resting-state functional MRI, electroencephalography, magnetoencephalography, and optical imaging studies in patients and animal models have demonstrated that loss of function after stroke is closely associated with disrupted connectivity in large-scale networks beyond the lesion territory. Restoration of functional connectivity in the surviving networks appears to be critical for functional recovery, and this may be promoted with specific therapeutic strategies, such as robot-assisted training and noninvasive brain stimulation. The adaptability of functional networks relies on the structural integrity of neuronal pathways, but the relationship between the two remains incompletely understood. Furthermore, disturbed neurovascular coupling after stroke can confound hemodynamically based measurements of functional connectivity.Identification of key network processes in adaptive brain plasticity can aid in the prediction of functional outcome and the development of therapeutic interventions to support and promote recovery after stroke.

Purpose: Recent literature shows that diffusion tensor properties can be estimated more accurately with diffusion kurtosis imaging (DKI) than with diffusion tensor imaging (DTI). Furthermore, the additional non-Gaussian diffusion features from DKI can be sensitive markers for tissue characterization. Despite these benefits, DKI is more susceptible to data artifacts than DTI due to its increased model complexity, higher acquisition demands, and longer scanning times. To increase the reliability of diffusion tensor and kurtosis estimates, we propose a robust estimation procedure for DKI. Methods: We have developed a robust and linear estimation framework, coined REKINDLE (Robust Extraction of Kurtosis INDices with Linear Estimation), consisting of an iteratively reweighted linear least squares approach. Simulations are performed, in which REKINDLE is evaluated and compared with the widely used RESTORE (Robust EStimation of Tensors by Outlier REjection) method. Results: Simulations demonstrate that in the presence of outliers, REKINDLE can estimate diffusion and kurtosis indices reliably and with a 10-fold reduction in computation time compared with RESTORE. Conclusion: We have presented and evaluated REKINDLE, a linear and robust estimation framework for DKI. While REKINDLE has been developed for DKI, it is by design also applicable to DTI and other diffusion models that can be linearized.

Epilepsy is a common neurological disorder in Nigeria. Many individuals are affected in rural areas, although prevalence data is not available. In this study we aimed to establish the prevalence of epilepsy in a rural community in south-east Nigeria, a community suspected for having a high number of people living with epilepsy. We compared this with the prevalence in a nearby semi-urban community in north-central Nigeria. In both communities we identified potential causes of epilepsy and obtained information on the social beliefs regarding epilepsy. We used door-to-door surveys and focus group discussions. The epilepsy prevalence in the rural community was 20.8/1000 [95% confidence interval (CI): 15.7-27.4]. The prevalence in the semi-rural community was lower, namely 4.7/1000 [CI: 3.2-6.9]. The difference in prevalence was highly significant (χ(2)-test, p

The blood-brain barrier (BBB) plays an important role in the homeostasis of the brain. BBB dysfunction has been implicated in the pathophysiology of various neurological disorders, including epilepsy in which it may contribute to disease progression. Precise understanding of BBB dynamics during epileptogenesis may be of importance for the assessment of future therapies, including BBB leakage blocking-agents. Longitudinal changes in BBB integrity can be studied with in vivo magnetic resonance imaging (MRI) in combination with paramagnetic contrast agents. Although this approach has shown to be suitable to detect major BBB leakage during the acute phase in experimental epilepsy models, so far no studies have provided information on dynamics of the extent of BBB leakage towards later phases. Therefore a sensitive and quantitative approach was used in the present study, involving fast T1 mapping (dynamic approach) during a steady-state infusion of gadobutrol, as well as pre- and post-contrast T1-weighted MRI (post- pre approach). This was applied in an experimental epilepsy model in which previous MRI studies failed to detect BBB leakage during epileptogenesis.Adult male Sprague-Dawley rats were injected with kainic acid to induce status epilepticus (SE). MRI experiments were performed before SE (control) and during the acute (1. day) and chronic epileptic phases (6. weeks after SE). BBB leakage was quantified by fast T1 mapping (Look-Locker gradient echo MRI) with a time resolution of 48. s from 5. min before up to 45. min after 20. min step-down infusion of 0.2. M gadobutrol. In addition, T1-weighted MRI was acquired before and 45. min after infusion. MRI data were compared to post-mortem microscopic analysis using the BBB tracer fluorescein.Our MRI data showed BBB leakage, which was evident at 1. day and 6. weeks after SE in the hippocampus, entorhinal cortex, amygdala and piriform cortex. These findings were confirmed by microscopic analysis of fluorescein leakage. Furthermore, our MRI data revealed non-uniform BBB leakage throughout epileptogenesis. This study demonstrates BBB leakage in specific brain regions during epileptogenesis, which can be quantified using MRI. Therefore, MRI may be a valuable tool for experimental or clinical studies to elucidate the role of the BBB in epileptogenesis.

Our aim was to evaluate Wikipedia page visits in relation to the most common neurological disorders by determining which factors are related to peaks in Wikipedia searches for these conditions. Millions of people worldwide use the internet daily as a source of health information. Wikipedia is a popular free online encyclopedia used by patients and physicians to search for health-related information. The following Wikipedia articles were considered: Alzheimer's disease; Amyotrophic lateral sclerosis; Dementia; Epilepsy; Epileptic seizure; Migraine; Multiple sclerosis; Parkinson's disease; Stroke; Traumatic brain injury. We analyzed information regarding the total article views for 90 days and the rank of these articles among all those available in Wikipedia. We determined the highest search volume peaks to identify possible relation with online news headlines. No relation between incidence or prevalence of neurological disorders and the search volume for the related articles was found. Seven out of 10 neurological conditions showed relations in search volume peaks and news headlines. Six out of these seven peaks were related to news about famous people suffering from neurological disorders, especially those from showbusiness. Identification of discrepancies between disease burden and health seeking behavior on Wikipedia is useful in the planning of public health campaigns. Celebrities who publicly announce their neurological diagnosis might effectively promote awareness programs, increase public knowledge and reduce stigma related to diagnoses of neurological disorders.

Neurophysiological studies have reported functional network alterations in epilepsy, most consistently in the theta frequency band. Highly interconnected brain regions (so-called 'hubs') seem to be important in these epileptic networks. High frequency oscillations (HFOs) in intracranial EEG recordings are recently discovered biomarkers that can identify the epileptogenic area and are thought to result from altered neuronal interactions. We studied whether the epileptogenic zone (identified by HFOs and seizure onset zone) is associated with pathological hubs. Bilateral depth electrode recordings from the hippocampus and amygdala were available from twelve patients suspected of temporal lobe epilepsy. HFOs, classified as ripples (80-250 Hz) and fast ripples (250-500 Hz), and epileptiform spikes were marked for all patients in a five-minute epoch of slow-wave sleep. For each channel, we computed hub-measures from a period without epileptiform spikes and found that the epileptogenic zone was associated with a decreased hub-value in the theta frequency band. The amount of HFOs, especially fast ripples, was negatively correlated with the hub-value per channel. Results from post-hoc analyses of other frequency bands, particularly the broad- and gamma frequency band, pointed in the same direction as the results for the theta frequency band. These findings suggest a pathological functional 'isolation' of the epileptogenic zone in the interictal state.

Focal epilepsy has recently been associated with remote white matter damage, including reduced white matter volume. Longitudinal assessment of these white matter changes, in relation to functional mechanisms and consequences, may be ideally done by in vivo neuroimaging in well-controlled experimental animal models. We assessed whether advanced machine learning algorithm models could accurately detect volumetric changes in white matter from multiparametric MR images, longitudinally collected in a neocortical focal epilepsy rat model. We measured classification accuracy in two supervised segmentation models: i.e. the generalized linear model and the nonlinear random forest model-by comparing computed white matter probabilities with actual neuroanatomically identified white matter. We found excellent overall discriminatory power for both models. However, the random forest model demonstrated a superior goodness-of-fit calibration plot that was close to the ideal calibration line. Based on this model, we measured that total white matter volume increased in young adult control and epileptic rats over a period of 10 weeks, but the average white matter volume was significantly lower in the focal epilepsy group. Changes in gray matter volume were not significantly different between control and epileptic rats. Our results (1) indicate that recurrent spontaneous seizures have an adverse effect on global white matter growth and (2) show that individual whole brain white matter volume can be accurately determined using a combination of multiparametric MRI and supervised segmentation models, offering a powerful tool to assess white matter volume changes in preclinical studies of neurological disease.

Background Community-based epilepsy care programs improve access to epilepsy treatment in resource-poor settings. Community volunteers are important to these services. Most studies on familiarity with, understanding of, and attitudes towards people with epilepsy (PWE), however, ignore these volunteers. Methods We explored these issues among 15 community volunteers involved in a community-based rehabilitation child epilepsy service recently initiated in Guinea-Bissau using face-to-face interviews. Results We found that the volunteers had a reasonable understanding of epilepsy, moderate attitudes towards PWE, and a good understanding of difficulties PWE encounter in society. Conclusion Evaluation of understanding and attitudes of community volunteers may be useful to improve low-cost community-based epilepsy programs. A correct understanding of epilepsy among community volunteers may increase effective treatment of and support to children with epilepsy through community-based epilepsy programs.

Background: Auditory verbal hallucinations (AVH) are a cardinal feature of schizophrenia and can severely disrupt behavior and decrease quality of life. Identification of areas with high functional connectivity (so-called hub regions) that are associated with the predisposition to hallucinate may provide potential targets for neuromodulation in the treatment of AVH. Methods: Resting-state fMRI scans during which no hallucinations had occurred were acquired from 29 nonpsychotic individuals with AVH and 29 matched controls. These nonpsychotic individuals with AVH provide the opportunity to study AVH without several confounds associated with schizophrenia, such as antipsychotic medication use and other symptoms related to the illness. Hub regions were identified by assessing weighted connectivity strength and betweenness centrality across groups using a permutation analysis. Results: Nonpsychotic individuals with AVH exhibited increased functioning as hub regions in the temporal cortices and the posterior cingulate/precuneus, which is an important area in the default mode network (DMN), compared to the nonhallucinating controls. In addition, the right inferior temporal gyrus, left paracentral lobule and right amygdala were less important as a hub region in the AVH group. Conclusions: These results suggest that the predisposition to hallucinate may be related to aberrant functioning of the DMN and the auditory cortices. Hum Brain Mapp 35:1436–1445, 2014. © 2013 Wiley Periodicals, Inc.

OBJECTIVE: To assess whether there is a difference in the background activity in the ripple band (80-200Hz) between epileptic and non-epileptic channels, and to assess whether this difference is sufficient for their reliable separation. METHODS: We calculated mean and standard deviation of wavelet entropy in 303 non-epileptic and 334 epileptic channels from 50 patients with intracerebral depth electrodes and used these measures as predictors in a multivariable logistic regression model. We assessed sensitivity, positive predictive value (PPV) and negative predictive value (NPV) based on a probability threshold corresponding to 90% specificity. RESULTS: The probability of a channel being epileptic increased with higher mean (p=0.004) and particularly with higher standard deviation (p

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.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).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.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.

ObjectiveBlood–brain barrier (BBB) leakage may play a pro‐epileptogenic role after status epilepticus. In the accompanying contrast‐enhanced magnetic resonance imaging (CE‐MRI) study we showed that the mammalian target of rapamycin (mTOR) inhibitor rapamycin reduced BBB leakage and seizure activity during the chronic epileptic phase. Given rapamycin's role in growth and immune response, the potential therapeutic effects of rapamycin after status epilepticus with emphasis on brain inflammation and brain vasculature were investigated.MethodsSeven weeks after kainic acid–induced status epilepticus, rats were perfusion fixed and (immuno)histochemistry was performed using several glial and vascular markers. In addition, an in vitro model for the human BBB was used to determine the effects of rapamycin on transendothelial electrical resistance as a measure for BBB integrity.Results(Immuno)histochemistry showed that local blood vessel density, activated microglia, and astrogliosis were reduced in rapamycin‐treated rats compared to vehicle‐treated rats. In vitro studies showed that rapamycin could attenuate TNFα‐induced endothelial barrier breakdown.SignificanceThese data suggest that rapamycin improves BBB function during the chronic epileptic phase by a reduction of local brain inflammation and blood vessel density that can contribute to a milder form of epilepsy.

ObjectiveThe mammalian target of rapamycin (mTOR) pathway has received increasing attention as a potential antiepileptogenic target. Treatment with the mTOR inhibitor rapamycin after status epilepticus reduces the development of epilepsy in a rat model. To study whether rapamycin mediates this effect via restoration of blood–brain barrier (BBB) dysfunction, contrast‐enhanced magnetic resonance imaging (CE‐MRI) was used to determine BBB permeability throughout epileptogenesis.MethodsImaging was repeatedly performed until 6 weeks after kainic acid–induced status epilepticus in rapamycin (6 mg/kg for 6 weeks starting 4 h after SE) and vehicle‐treated rats, using gadobutrol as contrast agent. Seizures were detected using video monitoring in the week following the last imaging session.ResultsGadobutrol leakage was widespread and extensive in both rapamycin and vehicle‐treated epileptic rats during the acute phase, with the piriform cortex and amygdala as the most affected regions. Gadobutrol leakage was higher in rapamycin‐treated rats 4 and 8 days after status epilepticus compared to vehicle‐treated rats. However, during the chronic epileptic phase, gadobutrol leakage was lower in rapamycin‐treated epileptic rats along with a decreased seizure frequency. This was confirmed by local fluorescein staining in the brains of the same rats. Total brain volume was reduced by this rapamycin treatment regimen.SignificanceThe initial slow recovery of BBB function in rapamycin‐treated epileptic rats indicates that rapamycin does not reduce seizure activity by a gradual recovery of BBB integrity. The reduced BBB leakage during the chronic phase, however, could contribute to the decreased seizure frequency in post–status epilepticus rats treated with rapamycin. Furthermore, the data show that CE‐MRI (using step‐down infusion with gadobutrol) can be used as biomarker for monitoring the effect of drug therapy in rats.

Objective High frequency oscillations (HFOs; > 80 Hz), especially fast ripples (FRs, 250–500 Hz), are novel biomarkers for epileptogenic tissue. The pathophysiology suggests enhanced functional connectivity within FR generating tissue. Our aim was to determine the relation between brain areas showing FRs and ‘baseline’ functional connectivity within EEG networks, especially in the high frequency bands. Methods We marked FRs, ripples (80–250 Hz) and spikes in the electrocorticogram of 14 patients with refractory temporal lobe epilepsy. We assessed ‘baseline’ functional connectivity in epochs free of epileptiform events within these recordings, using the phase lag index. We computed the Eigenvector Centrality (EC) per channel in the FR and gamma band network. We compared EC between channels that did or did not show events at other moments in time. Results FR-band EC was higher in channels with than without spikes. Gamma-band EC was lower in channels with ripples and FRs. Conclusions We confirmed previous findings of functional isolation in the gamma-band and found a first proof of functional integration in the FR-band network of channels covering presumed epileptogenic tissue. Significance ‘Baseline’ high-frequency network parameters might help intra-operative recognition of epileptogenic tissue without the need for waiting for events. These findings can increase our understanding of the ‘architecture’ of epileptogenic networks and help unravel the pathophysiology of HFOs., Highlights • The epileptogenic area is functionally isolated in the gamma-band network. • The epileptogenic area seems functionally integrated in the high frequency network. • The ‘baseline’ signal contains clinically useful high frequency surrogate biomarker information.

Objective: The effectiveness of anthelminthic and corticosteroid drug therapy in parenchymal neurocysticercosis is well established. The treatment of parenchymal solitary cysticercus granuloma (SCG), however, remains controversial. We attempted to obtain a consistent estimate of the efficacy of anthelminthic and corticosteroid drug treatment in SCG. Methods: Randomized-controlled trials (RCTs) comparing rates of seizure freedom, granuloma resolution, and residual calcification in individuals with SCG treated with anthelminthic or corticosteroid drugs with those treated with antiepileptic drugs (AEDs) alone were systematically reviewed and quantified using fixed- or random-effects meta-analysis. Results: Fifteen RCTs were identified for inclusion. Ten RCTs assigned 765 people with SCG to AED treatment with or without anthelminthic drug (albendazole) treatment. A further 5 RCTs assigned 457 people with SCG to AED treatment with or without corticosteroid drugs. Anthelminthic treatment was associated with significantly increased rates of seizure freedom (nonevent odds ratio: 2.45; 95% confidence interval: 1.49–4.03; p = 0.0004) and significantly higher rates of granuloma resolution (odds ratio: 2.09; 95% confidence interval: 1.41–3.00; p = 0.0003), but did not alter the risk of residual calcification. Corticosteroid treatment was not significantly associated with any outcome. Conclusions: Anthelminthic treatment with albendazole provides improved rates of seizure freedom and hastens resolution of the granuloma. The role of corticosteroid treatment remains uncertain. The benefits (or lack thereof in the case of corticosteroids) are consistent when measured across different time points after treatment.

Summary Purpose: Extratemporal epilepsy often coincides with cognitive decline, which may be associated with hippocampal dysfunction. Severe hippocampal sclerosis can be detected with conventional neuroimaging in some patients with chronic extrahippocampal epilepsy (so-called dual pathology). However, subtle structural hippocampal changes may already develop at a much earlier phase, and in a larger number of patients. Our goal was to longitudinally characterize the development of bilateral hippocampal pathology in an experimental neocortical focal epilepsy model. Methods: Focal unilateral neocortical epilepsy was induced by microinjection of tetanus toxin in the primary motor cortex in adult male Sprague-Dawley rats. Another group of age-matched rats served as controls. In both groups, structural magnetic resonance imaging (MRI) was performed at 1, 3, 7, and 10 weeks of follow-up. Bilateral hippocampi were outlined and macroscopically analyzed using a state-of-the-art point-based morphometry model. Hippocampal microstructural changes at the end of follow-up, 10 weeks after epilepsy induction, were assessed with postmortem standard cresyl-violet, Fluoro-Jade, proteolipid protein 1, vimentin, glial fibrillary acidic protein, and ionized calcium binding adaptor molecule 1 stainings. Key Findings: All rats in the injected group developed seizures. The ipsilateral hippocampal volume was on average 8.76 (mean) ± 3.32% (standard deviation) smaller in the epileptic animals as compared to controls (p = 0.01) during the 10 weeks of follow-up. The contralateral hippocampus showed a similar reduction of 8.49 (mean) ± 3.27% (standard deviation) in total volume (p = 0.02). Clear hippocampal shape differences were found between the two groups. The most affected areas after epilepsy induction were the bilateral dorso-mediorostral, dorsolateral, and ventrolateral areas of the hippocampi. Normal developmental shape changes of the hippocampus, as detected in control rats, were largely absent in the ipsilateral hippocampus of epileptic rats. Quantitative histologic analysis revealed significant neuronal loss in the hippocampus, most pronounced in the hilar subregion, globally impaired myelination, reactive astrocytosis, and activated microglia. We found a weak but significant correlation between the number of neurons and hippocampal volume (r = 0.25, p = 0.0025). Significance: We found evidence of hippocampal pathology in both hemispheres following experimental focal neocortical epilepsy. The observed development of bilateral hippocampal pathology, with onset in the early stages of focal neocortical epilepsy, may be a significant factor in comorbidities, such as cognitive dysfunction, found in patients with extratemporal localization-related epilepsy.

Summary Purpose: Diffusion tensor imaging (DTI) is used increasingly to study white matter integrity in people with temporal lobe epilepsy (TLE). Most studies report fractional anisotropy (FA) decrease and mean diffusivity (MD) increase in multiple white matter regions. The disturbance of white matter integrity varies across studies and between regions. We aimed to obtain a more consistent estimate of white matter diffusion characteristics and relate these to the distance from the seizure focus. Methods: Studies comparing diffusion characteristics of people with epilepsy with those of healthy controls were systematically reviewed and quantified using random and mixed effects meta analysis. In addition to the overall meta-analysis, pooled FA and MD differences were determined per hemisphere and white matter category separately. Key Findings: We included 13 cross-sectional studies. The pooled FA difference for all white matter was −0.026 (95% confidence interval [CI] −0.033 to −0.019) and MD difference was 0.028 × 10−3 mm2/s (95% CI 0.015–0.04). FA was reduced significantly in people with TLE compared with healthy controls in both ipsilateral (mean difference −0.03) and contralateral white matter (−0.02). MD was significantly increased ipsilaterally and contralaterally. MD differed significantly between white matter connected to the affected temporal lobe and remote white matter. Significance: The meta-analysis provides a better estimation of the true diffusion characteristics. White matter structural integrity in TLE is disturbed more severely in the ipsilateral than in the contralateral hemisphere, and tracts closely connected with the affected temporal lobe are most disturbed. The exact underlying mechanisms remain to be elucidated.