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Focal cortical dysplasias (FCDs) are malformations of cortical development and one of the most common pathologies causing pharmacoresistant focal epilepsy. Resective neurosurgery yields high success rates, especially if the full extent of the lesion is correctly identified and completely removed. The visual assessment of magnetic resonance imaging does not pinpoint the FCD in 30%-50% of cases, and half of all patients with FCD are not amenable to epilepsy surgery, partly because the FCD could not be sufficiently localized. Computational approaches to FCD detection are an active area of research, benefitting from advancements in computer vision. Automatic FCD detection is a significant challenge and one of the first clinical grounds where the application of artificial intelligence may translate into an advance for patients' health. The emergence of new methods from the combination of health and computer sciences creates novel challenges. Imaging data need to be organized into structured, well-annotated datasets and combined with other clinical information, such as histopathological subtypes or neuroimaging characteristics. Algorithmic output, that is, model prediction, requires a technically correct evaluation with adequate metrics that are understandable and usable for clinicians. Publication of code and data is necessary to make research accessible and reproducible. This critical review introduces the field of automatic FCD detection, explaining underlying medical and technical concepts, highlighting its challenges and current limitations, and providing a perspective for a novel research environment.

Objective: Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross‐sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE‐HS) correlate with clinical features. Methods: We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1‐weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA‐Epilepsy consortium, comprising 804 people with MTLE‐HS and 1625 healthy controls from 25 centers. Features with a moderate case–control effect size (Cohen d ≥ .5) were used to train an event‐based model (EBM), which estimates a sequence of disease‐specific biomarker changes from cross‐sectional data and assigns a biomarker‐based fine‐grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance. Results: In MTLE‐HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10−16), age at onset (ρ = −.18, p = 9.82 × 10−7), and ASM resistance (area under the curve = .59, p = .043, Mann–Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE‐HS with mild or nondetectable abnormality on T1W MRI. Significance: From cross‐sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE‐HS subjects in other cohorts and help establish connections between imaging‐based progression staging and clinical features.

Background and Objectives:A new frontier in diagnostic radiology is the inclusion of machine-assisted support tools that facilitate the identification of subtle lesions often not visible to the human eye. Structural neuroimaging plays an essential role in the identification of lesions in patients with epilepsy, which often coincide with the seizure focus. Here we explore the potential for a convolutional neural network (CNN) to determine lateralization of seizure onset in patients with epilepsy using T1-weighted structural MRI scans as input.Methods:Using a dataset of 359 patients with temporal lobe epilepsy (TLE) from 7 surgical centers, we tested whether a CNN based on T1-weighted images could classify seizure laterality concordant with clinical team consensus. This CNN was compared to a randomized model (comparison to chance) and a hippocampal volume logistic regression (comparison to current clinically-available measures). Furthermore, we leveraged a CNN feature visualization technique to identify regions used to classify patients.Results:Across 100 runs, the CNN model was concordant with clinician lateralization on average 78% (SD= 5.1%) of runs with the best performing model achieving 89% concordance. The CNN outperformed the randomized model (average concordance of 51.7%) on 100% of runs with an average improvement of 26.2% and outperformed the hippocampal volume model (average concordance of 71.7%) on 85% of runs with an average improvement of 6.25%. Feature visualization maps revealed that in addition to the medial temporal lobe, regions in the lateral temporal lobe, cingulate, and precentral gyrus aided in classification.Discussion:These extra-temporal lobe features underscore the importance of whole-brain models to highlight areas worthy of clinician scrutiny during temporal lobe epilepsy lateralization. This proof-of-concept study illustrates that a CNN applied to structural MRI data can visually aid clinician-led localization of epileptogenic zone and identify extra-hippocampal regions that may require additional radiological attention.Classification of Evidence:This study provides Class II evidence that in patients with drug-resistant unilateral temporal lobe epilepsy, a convolutional neural network algorithm derived from T1-weighted MR images can correctly classify seizure laterality.

Background Radiological identification of temporal lobe epilepsy (TLE) is crucial for diagnosis and treatment planning. TLE neuroimaging abnormalities are pervasive at the group level, but they can be subtle and difficult to identify by visual inspection of individual scans, prompting applications of artificial intelligence (AI) assisted technologies. Method We assessed the ability of a convolutional neural network (CNN) algorithm to classify TLE vs. patients with AD vs. healthy controls using T1-weighted magnetic resonance imaging (MRI) scans. We used feature visualization techniques to identify regions the CNN employed to differentiate disease types. Results We show the following classification results: healthy control accuracy = 81.54% (SD = 1.77%), precision = 0.81 (SD = 0.02), recall = 0.85 (SD = 0.03), and F1-score = 0.83 (SD = 0.02); TLE accuracy = 90.45% (SD = 1.59%), precision = 0.86 (SD = 0.03), recall = 0.86 (SD = 0.04), and F1-score = 0.85 (SD = 0.04); and AD accuracy = 88.52% (SD = 1.27%), precision = 0.64 (SD = 0.05), recall = 0.53 (SD = 0.07), and F1 score = 0.58 (0.05). The high accuracy in identification of TLE was remarkable, considering that only 47% of the cohort had deemed to be lesional based on MRI alone. Model predictions were also considerably better than random permutation classifications (p Conclusions AI (CNN deep learning) can classify and distinguish TLE, underscoring its potential utility for future computer-aided radiological assessments of epilepsy, especially for patients who do not exhibit easily identifiable TLE associated MRI features (e.g., hippocampal sclerosis).

BACKGROUND AND PURPOSE: MR imaging studies and neuropathologic findings in individuals with 22q11.2 deletion syndrome show anomalous early brain development. We aimed to retrospectively evaluate cerebral abnormalities, focusing on gray matter heterotopia, and to correlate these with subjects’ neuropsychiatric impairments. MATERIALS AND METHODS: Three raters assessed gray matter heterotopia and other morphologic brain abnormalities on 3D T1WI and T2*WI in 75 individuals with 22q11.2 deletion syndrome (27 females, 15.5 [SD, 7.4] years of age) and 53 controls (24 females, 12.6 [SD, 4.7] years of age). We examined the association among the groups’ most frequent morphologic findings, general cognitive performance, and comorbid neuropsychiatric conditions. RESULTS: Heterotopia in the white matter were the most frequent finding in individuals with 22q11.2 deletion syndrome (n = 29; controls, n = 0; between-group difference, P < .001), followed by cavum septi pellucidi and/or vergae (n = 20; controls, n = 0; P < .001), periventricular cysts (n = 10; controls, n = 0; P = .007), periventricular nodular heterotopia (n = 10; controls, n = 0; P = .007), and polymicrogyria (n = 3; controls, n = 0; P = .3). However, individuals with these morphologic brain abnormalities did not differ significantly from those without them in terms of general cognitive functioning and psychiatric comorbidities. CONCLUSIONS: Taken together, our findings, periventricular nodular heterotopia or heterotopia in the white matter (possibly related to interrupted Arc cells migration), persistent cavum septi pellucidi and/or vergae, and formation of periventricular cysts, give clues to the brain development disorder induced by the 22q11.2 deletion syndrome. There was no evidence that these morphologic findings were associated with differences in psychiatric or cognitive presentation of the 22q11.2 deletion syndrome.

The blood-brain barrier (BBB) is a physiological barrier maintaining a specialized brain micromilieu that is necessary for proper neuronal function. Endothelial tight junctions and specific transcellular/efflux transport systems provide a protective barrier against toxins, pathogens, and immune cells. The barrier function is critically supported by other cell types of the neurovascular unit, including pericytes, astrocytes, microglia, and interneurons. The dysfunctionality of the BBB is a hallmark of neurological diseases, such as ischemia, brain tumors, neurodegenerative diseases, infections, and autoimmune neuroinflammatory disorders. Moreover, BBB dysfunction is critically involved in epilepsy, a brain disorder characterized by spontaneously occurring seizures because of abnormally synchronized neuronal activity. While resistance to antiseizure drugs that aim to reduce neuronal hyperexcitability remains a clinical challenge, drugs targeting the neurovasculature in epilepsy patients have not been explored. The use of novel imaging techniques permits early detection of BBB leakage in epilepsy; however, the detailed mechanistic understanding of causes and consequences of BBB compromise remains unknown. Here, we discuss the current knowledge of BBB involvement in temporal lobe epilepsy with the emphasis on the neurovasculature as a therapeutic target.

Neuronal dysfunction due to iron accumulation in conjunction with reactive oxygen species (ROS) could represent an important, yet underappreciated, component of the epileptogenic process. However, to date, alterations in iron metabolism in the epileptogenic brain have not been addressed in detail. Iron-related neuropathology and antioxidant metabolic processes were investigated in resected brain tissue from patients with temporal lobe epilepsy and hippocampal sclerosis (TLE-HS), post-mortem brain tissue from patients who died after status epilepticus (SE) as well as brain tissue from the electrically induced SE rat model of TLE. Magnetic susceptibility of the presumed seizure-onset zone from three patients with focal epilepsy was compared during and after seizure activity. Finally, the cellular effects of iron overload were studied in vitro using an acute mouse hippocampal slice preparation and cultured human fetal astrocytes. While iron-accumulating neurons had a pyknotic morphology, astrocytes appeared to acquire iron-sequestrating capacity as indicated by prominent ferritin expression and iron retention in the hippocampus of patients with SE or TLE. Interictal to postictal comparison revealed increased magnetic susceptibility in the seizure-onset zone of epilepsy patients. Post-SE rats had consistently higher hippocampal iron levels during the acute and chronic phase (when spontaneous recurrent seizures are evident). In vitro, in acute slices that were exposed to iron, neurons readily took up iron, which was exacerbated by induced epileptiform activity. Human astrocyte cultures challenged with iron and ROS increased their antioxidant and iron-binding capacity, but simultaneously developed a pro-inflammatory phenotype upon chronic exposure. These data suggest that seizure-mediated, chronic neuronal iron uptake might play a role in neuronal dysfunction/loss in TLE-HS. On the other hand, astrocytes sequester iron, specifically in chronic epilepsy. This function might transform astrocytes into a highly resistant, pro-inflammatory phenotype potentially contributing to pro-epileptogenic inflammatory processes. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-021-02348-6.

Patients with anti-leucine-rich glioma-inactivated 1 protein (LGI1) or anti-contactin-associated protein 2 (CASPR2) antibody encephalitis typically present with frequent epileptic seizures. The seizures generally respond well to immunosuppressive therapy, and the long-term seizure outcome seems to be favorable. Consequentially, diagnosing acute symptomatic seizures secondary to autoimmune encephalitis instead of autoimmune epilepsy was proposed. However, published data on long-term seizure outcomes in CASPR2 and LGI1 antibody encephalitis are mostly based on patient reports, and seizure underreporting is a recognized issue. Clinical records from our tertiary epilepsy center were screened retrospectively for patients with LGI1 and CASPR2 antibody encephalitis who reported seizure freedom for at least 3 months and received video-electroencephalography (EEG) for24 h at follow-up visits. Twenty (LGI1, n = 15; CASPR2, n = 5) of 32 patients with LGI1 (n = 24) and CASPR2 (n = 8) antibody encephalitis fulfilled these criteria. We recorded focal aware and impaired awareness seizures in four of these patients (20%) with reported seizure-free intervals ranging from 3 to 27 months. Our results question the favorable seizure outcome in patients with CASPR2 and LGI1 antibody encephalitis and suggest that the proportion of patients who have persistent seizures may be greater. Our findings underline the importance of prolonged video-EEG telemetry in this population.

OBJECTIVE: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric analysis of T1-weighted images, for example, using the Morphometric Analysis Program (v2018; MAP18), which was introduced in 2005, independently validated for its clinical benefits, and successfully integrated in standard presurgical workflows of numerous epilepsy centers worldwide. Here we aimed to develop an artificial neural network (ANN) classifier for robust automated detection of FCDs based on these morphometric maps and probe its generalization performance in a large, independent data set. METHODS: In this retrospective study, we created a feed-forward ANN for FCD detection based on the morphometric output maps of MAP18. The ANN was trained and cross-validated on 113 patients (62 female, mean age ± SD =29.5 ± 13.6 years) with manually segmented FCDs and 362 healthy controls (161 female, mean age ± SD =30.2 ± 9.6 years) acquired on 13 different scanners. In addition, we validated the performance of the trained ANN on an independent, unseen data set of 60 FCD patients (28 female, mean age ± SD =30 ± 15.26 years) and 70 healthy controls (42 females, mean age ± SD = 40.0 ± 12.54 years). RESULTS: In the cross-validation, the ANN achieved a sensitivity of 87.4% at a specificity of 85.4% on the training data set. On the independent validation data set, our method still reached a sensitivity of 81.0% at a comparably high specificity of 84.3%. SIGNIFICANCE: Our method shows a robust automated detection of FCDs and performance generalizability, largely independent of scanning site or MR-sequence parameters. Taken together with the minimal input requirements of a standard T1 image, our approach constitutes a clinically viable and useful tool in the presurgical diagnostic routine for drug-resistant focal epilepsy. ispartof: EPILEPSIA vol:62 issue:4 pages:1005-1021 ispartof: location:United States status: published

Objective Assess occurrence of the dendritic spine scaffolding protein Drebrin as a pathophysiologically relevant autoantibody target in patients with recurrent seizures and suspected encephalitis as leading symptoms. Methods Sera of 4 patients with adult onset epilepsy and suspected encephalitis of unresolved etiology and equivalent results in autoantibody screening were subjected to epitope identification. We combined a wide array of approaches, ranging from immunoblotting, immunoprecipitation, mass spectrometry, subcellular binding pattern analyses in primary neuronal cultures, and immunohistochemistry in brains of wild-type and Drebrin knockout mice to in vitro analyses of impaired synapse formation, morphology, and aberrant neuronal excitability by antibody exposure. Results In the serum of a patient with adult onset epilepsy and suspected encephalitis, a strong signal at ∼70kDa was detected by immunoblotting, for which mass spectrometry revealed Drebrin as the putative antigen. Three other patients whose sera also showed strong immunoreactivity around 70kDa on Western blotting were also anti-Drebrin-positive. Seizures, memory impairment, and increased protein content in cerebrospinal fluid occurred in anti-Drebrin-seropositive patients. Alterations in cerebral magnetic resonance imaging comprised amygdalohippocampal T2-signal increase and hippocampal sclerosis. Diagnostic biopsy revealed T-lymphocytic encephalitis in an anti-Drebrin-seropositive patient. Exposure of primary hippocampal neurons to anti-Drebrin autoantibodies resulted in aberrant synapse composition and Drebrin distribution as well as increased spike rates and the emergence of burst discharges reflecting network hyperexcitability. Interpretation Anti-Drebrin autoantibodies define a chronic syndrome of recurrent seizures and neuropsychiatric impairment as well as inflammation of limbic and occasionally cortical structures. Immunosuppressant therapies should be considered in this disorder. ANN NEUROL 2020;87:869-884.

Background and ObjectivesLimbic encephalitis (LE) is an autoimmune disease often associated with temporal lobe epilepsy and subacute memory deficits. It is categorized into serologic subgroups, which differ in clinical progress, therapy response, and prognosis. Using longitudinal MRI analysis, we hypothesized that mesiotemporal and cortical atrophy rates would reveal serotype-specific patterns and reflect disease severity.MethodsIn this longitudinal case-control study, all individuals with antibody-positive (glutamic acid decarboxylase 65 [GAD], leucine-rich glioma-inactivated protein 1 [LGI1], contactin-associated protein 2 [CASPR2], andN-methyl-d-aspartate receptor [NMDAR]) nonparaneoplastic LE according to Graus' diagnostic criteria treated between 2005 and 2019 at the University Hospital Bonn were enrolled. A longitudinal healthy cohort was included as the control group. Subcortical segmentation and cortical reconstruction of T1-weighted MRI were performed using the longitudinal framework in FreeSurfer. We applied linear mixed models to examine mesiotemporal volumes and cortical thickness longitudinally.ResultsTwo hundred fifty-seven MRI scans from 59 individuals with LE (34 female, age at disease onset [mean ± SD] 42.5 ± 20.4 years; GAD: n = 30, 135 scans; LGI1: n = 15, 55 scans; CASPR2: n = 9, 37 scans; and NMDAR: n = 5, 30 scans) were included. The healthy control group consisted of 128 scans from 41 individuals (22 female, age at first scan [mean ± SD] 37.7 ± 14.6 years). The amygdalar volume at disease onset was significantly higher in individuals with LE (p≤0.048 for all antibody subgroups) compared with that in healthy controls and decreased over time in all antibody subgroups, except in the GAD subgroup. We observed a significantly higher hippocampal atrophy rate in all antibody subgroups compared with that in healthy controls (allp≤0.002), except in the GAD subgroup. Cortical atrophy rates exceeded normal aging in individuals with impaired verbal memory, while those who were not impaired did not differ significantly from healthy controls.DiscussionOur data depict higher mesiotemporal volumes in the early disease stage, most likely due to edematous swelling, followed by volume regression and atrophy/hippocampal sclerosis in the late disease stage. Our study reveals a continuous and pathophysiologically meaningful trajectory of mesiotemporal volumetry across all serogroups and provides evidence that LE should be considered a network disorder in which extratemporal involvement is an important determinant of disease severity.

Here, we report a consanguineous family harboring a novel homozygous frame-shift mutation in ASPM leading to a truncation of the ASPM protein after amino acid position 1830. The phenotype of the patients was associated with microcephaly, epilepsy, and behavioral and cognitive deficits. Despite the obvious genetic similarity, the affected patients show a considerable phenotypic heterogeneity regarding the degree of mental retardation, presence of epilepsy and MRI findings. Interestingly, the degree of mental retardation and the presence of epilepsy correlates well with the severity of abnormalities detected in brain MRI. On the other hand, we detected no evidence for substantial nonsense-mediated ASPM transcript decay in blood samples. This indicates that other factors than ASPM expression levels are relevant for the variability of structural changes in brain morphology seen in patients with primary hereditary microcephaly caused by ASPM mutations.

Here, we report a consanguineous family harboring a novel homozygous frame-shift mutation in

Background and ObjectiveRasmussen encephalitis (RE) is characterized by its unilateral cerebral involvement. However, both ipsi- and contralesional cerebellar atrophy have been anecdotally reported raising questions about the nature and extent of infratentorial findings. Using MRI, we morphometrically investigated the cerebellum and hypothesized abnormalities beyond the effects of secondary atrophy, implicating a primary involvement of the cerebellum by RE.MethodsVoxel-based morphometry of the cerebellum and brainstem was conducted in 57 patients with RE and in 57 matched controls. Furthermore, patient-specific asymmetry indices (AIs) of cerebellar morphometry and fluid-attenuated inversion recovery (FLAIR) intensity were calculated. Using diffusion tensor imaging, the integrity of the cortico-ponto-cerebellar (CPC) tract was assessed. Finally, a spatial independent component analysis (ICA) was used to compare atrophy patterns between groups.ResultsPatients with RE showed bilateral cerebellar and predominantly ipsilesional mesencephalic atrophy (p < 0.01). Morphometric AIs revealed ipsilesional < contralesional asymmetry in 27 and ipsilesional > contralesional asymmetry in 30 patients. In patients with predominant ipsilesional atrophy, morphometric AIs strongly correlated with FLAIR intensity AIs (r = 0.86, p < 0.0001). Fractional anisotropy was lower for ipsilesional-to-contralesional CPC tracts than opposite tracts (T = 2.30, p < 0.05). ICA revealed bilateral and strictly ipsi- and contralesional atrophy components in patients with RE (p < 0.05).DiscussionWe demonstrated atrophy of the ipsilesional-to-contralesional CPC pathway and, consequently, interpret the loss of contralesional gray matter as secondary crossed cerebellar atrophy. The ipsilesional cerebellar atrophy, however, defies this explanation. Based on FLAIR hyperintensities, we interpret ipsilesional atrophy to be due to inflammation in the scope of a primary involvement of the cerebellum by RE.

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem co-expression patterns of epilepsy risk genes. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1,328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-genetic signatures could guide diagnosis, and ultimately, tailor therapeutic approaches to specific epilepsy syndromes.

Brain : a journal of neurology (2022). doi:10.1093/brain/awac119, Published by Oxford Univ. Press, Oxford

BACKGROUND AND PURPOSE Febrile-infection-related epilepsy syndrome (FIRES) is an exceedingly rare and devastating subtype of new-onset refractory status epilepticus, which causes refractory epilepsy and permanent neurocognitive impairment. METHODS This was a long-term follow-up of adult FIRES survivors treated between 2005 and 2018 as part of the EpiCARE initiative, a European Reference Network for rare and complex epilepsies. Clinical, electroencephalography, imaging and functional outcome measures are described using the Scores of Independence for Neurologic and Geriatric Rehabilitation, the modified Rankin Scale and the Global Assessment of Severity of Epilepsy Scale. RESULTS Six patients with refractory epilepsy following FIRES were evaluated. Despite general improvement after intensive care unit discharge, disease severity was still high at follow-up in all patients. The functional outcome, as assessed by the modified Rankin Scale, was moderately impaired in 2/6 patients. In contrast, the Scores of Independence for Neurologic and Geriatric Rehabilitation indicated a loss of independence in 5/6, serious problems in memory and planning/problem-solving in 4/6 and serious attentional problems in 3/6 patients. CONCLUSIONS Febrile-infection-related epilepsy syndrome survivors may regain vital functions and mobility but experience a significant loss of independence and participation due to recurring seizures, structural brain damage and neurocognitive decline. Minimization of disastrous outcomes through the systematic evaluation of rescue therapies within a network of specialized centres is crucial.

Limbic encephalitis (LE) forms a spectrum of autoimmune diseases involving temporal lobe epilepsy and memory impairment. Imaging features of LE are known to depend on the associated antibody and to occur on the brain network level. However, first studies investigating brain networks in LE have either focused on one distinct antibody subgroup or on distinct anatomical regions. In this study, brain graphs of 17 LE patients with autoantibodies against glutamic acid decarboxylase 65 (GAD-LE), four LE patients with autoantibodies against leucine-rich glioma-inactivated 1, five LE patients with autoantibodies against contactin-associated protein-like 2, 26 age- and gender-matched healthy control subjects, and 20 epilepsy control patients with hippocampal sclerosis were constructed based on T1-weighted structural magnetic resonance imaging scans and diffusion tensor imaging. GAD-LE showed significantly altered global network topology in terms of integration and segregation as compared to healthy controls and patients with hippocampal sclerosis (P < .01, analysis of variance with Tukey-Kramer post hoc tests). Linear regression linked global network measures with amygdala volume and verbal memory performance (P < .05). Alterations of local network topology show serotype dependence in hippocampus, amygdala, insula, and various cortical regions. Our findings reveal serotype-dependent patterns of structural connectivity and prove the relevance of in silico network measures on clinical grounds.

Cooperative interactions between the amygdala and hippocampus are widely regarded as critical for overnight emotional processing of waking experiences, but direct support from the human brain for such a dialog is absent. Using overnight intracranial recordings in 4 presurgical epilepsy patients (3 female), we discovered ripples within human amygdala during nonrapid eye movement (NREM) sleep, a brain state known to contribute to affective processing. Like hippocampal ripples, amygdala ripples are associated with sharp waves, linked to sleep spindles, and tend to co-occur with their hippocampal counterparts. Moreover, sharp waves and ripples are temporally linked across the 2 brain structures, with amygdala ripples occurring during hippocampal sharp waves and vice versa. Combined with further evidence of interregional sharp-wave and spindle synchronization, these findings offer a potential physiological substrate for the NREM-sleep-dependent consolidation and regulation of emotional experiences.

Oligonucleotide therapies offer precision treatments for a variety of neurological diseases, including epilepsy, but their deployment is hampered by the blood-brain barrier (BBB). Previous studies showed that intracerebroventricular injection of an antisense oligonucleotide (antagomir) targeting microRNA-134 (Ant-134) reduced evoked and spontaneous seizures in animal models of epilepsy. In this study, we used assays of serum protein and tracer extravasation to determine that BBB disruption occurring after status epilepticus in mice was sufficient to permit passage of systemically injected Ant-134 into the brain parenchyma. Intraperitoneal and intravenous injection of Ant-134 reached the hippocampus and blocked seizure-induced upregulation of miR-134. A single intraperitoneal injection of Ant-134 at 2 h after status epilepticus in mice resulted in potent suppression of spontaneous recurrent seizures, reaching a 99.5% reduction during recordings at 3 months. The duration of spontaneous seizures, when they occurred, was also reduced in Ant-134-treated mice. In vivo knockdown of LIM kinase-1 (Limk-1) increased seizure frequency in Ant-134-treated mice, implicating de-repression of Limk-1 in the antagomir mechanism. These studies indicate that systemic delivery of Ant-134 reaches the brain and produces long-lasting seizure-suppressive effects after systemic injection in mice when timed with BBB disruption and may be a clinically viable approach for this and other disease-modifying microRNA therapies.

During sleep, new memories undergo a gradual transfer from hippocampal (HPC) to neocortical (NC) sites. Precisely timed neural oscillations are thought to mediate this sleep-dependent memory consolidation, but exactly how sleep oscillations instantiate the HPC-NC dialog remains elusive. Employing overnight invasive electroencephalography in ten neurosurgical patients, we identified three broad classes of phase-based communication between HPC and lateral temporal NC. First, we observed interregional phase synchrony for non-rapid eye movement (NREM) spindles, and N2 and rapid eye movement (REM) theta activity. Second, we found asymmetrical N3 cross-frequency phase-amplitude coupling between HPC slow oscillations (SOs) and NC activity spanning the delta to high-gamma/ripple bands, but not in the opposite direction. Lastly, N2 theta and NREM spindle synchrony were themselves modulated by HPC SOs. These forms of interregional communication emphasize the role of HPC SOs in the HPC-NC dialog, and may offer a physiological basis for the sleep-dependent reorganization of mnemonic content., Cox et al. investigate communication between the hippocampus and neocortex during sleep using invasive electroencephalography from human patients. They characterize the oscillations exhibiting interregional coordination and identify an important orchestrating role for hippocampal slow oscillations.

Shape-based markers have entered the field of morphometric neuroimaging analysis as a second mainstay alongside conventional volumetric approaches. We aimed to assess the added value of shape description for the analysis of lesional and autoimmune temporal lobe epilepsy (TLE) focusing on hippocampus and amygdala. We retrospectively investigated MRI and clinical data from 65 patients with lesional TLE (hippocampal sclerosis (HS) and astrogliosis) and from 62 patients with limbic encephalitis (LE) with serologically proven autoantibodies. Surface reconstruction and volumetric segmentation were performed with FreeSurfer. For the shape analysis, we used BrainPrint, a tool that utilizes eigenvalues of the Laplace-Beltrami operator on triangular meshes to calculate intra-subject asymmetry. Psychometric tests of memory performance were ascertained, to evaluate clinical relevance of the shape descriptor. The potential benefit of shape in addition to volumetric information for classification was assessed by five-fold repeated cross validation and logistic regression. For the LE group, the best performing classification model consisted of a combination of volume and shape asymmetry (mean AUC = 0.728), the logistic regression model was significantly improved considering both modalities instead of just volume asymmetry. For lesional TLE, the best model only considered volumetric information (mean AUC = 0.867). Shape asymmetry of the hippocampus was largely associated with verbal memory performance only in LE patients (OR = 1.07, p = 0.02). For lesional TLE, shape description is robust, but redundant when compared to volumetric approaches. For LE, in contrast, shape asymmetry as a complementary modality significantly improves the detection of subtle morphometric changes and is further associated with memory performance, which underscores the clinical relevance of shape asymmetry as a novel imaging biomarker.

Limbic encephalitis (LE) is an immune-related disease with limbic symptoms, variable and asymmetric magnetic resonance imaging (MRI) aspects and antibody profiles. This study investigated the diagnostic value of quantitative relaxation times T2 (qT2) and MRI signal intensities (SI) in LE. The prospective 3T-MRI study included 39 epilepsy patients with initially suspected LE and 20 healthy controls. Values and asymmetry indices of qT2, T2-weighted (T2-w) and proton density (PD)-w SI of manually delineated and automatically segmented amygdala and hippocampus were measured. Additionally, two raters made a blinded visual analysis on FLAIR (fluid attenuation inversion recovery) and T2-w images. According to diagnostic guidelines, 22 patients had probable LE and 17 patients had possible LE. The qT2 was higher (p

MRI has a crucial position in the diagnostic routine of epilepsy patients. It relevantly contributes to etiological diagnostics and is indispensable in presurgical evaluation. As modern MRI research has been a boon to clinical neuroscience in general, it also holds the promise of enhancing diagnostics of epilepsy patients; i.e. increasing the diagnostic yield while decreasing the number of MRI-negative patients. Its rapid progress, however, has caused uncertainty about which of its latest developments already are of clinical interest and which still are of academic interest. It is the purpose of this review to clarify what, to the authors' mind, good practice of MRI in epilepsy patient care is today and what it might be tomorrow.Progress of diagnostic MRI in epilepsy patients is driven by development of scanner hardware, scanner sequence and data postprocessing. Ultra high-field MRI and elaborate sequences provide datasets of novel quality which can be fed into postprocessing programs extracting pathognomonic features of structural or functional anatomy. The integration of these features by means of computerized classifiers yield previously unsurpassed diagnostic validity. Enthusiasm about Diffusion Tensor Imaging and functional MRI in the evaluation before epilepsy surgery is quelled.The application of an epilepsy tailored MRI protocol at 3 Tesla followed by meticulous expert evaluation early after the onset of epilepsy is most crucial. It is hoped that future research will result in MRI workups more standardized than today and widely used postprocessing routines analyzing co-registered three-dimensional volumes from different modalities.

Blood-brain barrier (BBB) permeability assessment remains of ongoing interest in clinical practice and research. Transitions between intravascular (IV) and extravascular (EV) gray matter (GM) compartments may provide information regarding the microstructural status of the BBB. Due to different transverse relaxation times (T

Cooperative interactions between the amygdala and hippocampus are widely regarded as critical for overnight emotional processing of waking experiences, but direct support from the human brain for such a dialog is absent. Using intracranial recordings in four pre-surgical epilepsy patients (two male, two female), we discovered ripples within human amygdala during non-rapid eye movement (NREM) sleep. Like hippocampal ripples, amygdala ripples are strongly associated with sharp waves, are linked to sleep spindles, and tend to co-occur with their hippocampal counterparts. Moreover, sharp waves and ripples are temporally linked across the two brain structures, with amygdala ripples occurring during hippocampal sharp waves and vice versa. Combined with further evidence of interregional sharp wave and spindle synchronization, these findings offer a potential physiological substrate for the NREM-sleep-dependent consolidation and regulation of emotional experiences.

Motor function after hemispheric lesions has been associated with the structural integrity of either the pyramidal tract (PT) or alternate motor fibers (aMF). In this study, we aimed to differentially characterize the roles of PT and aMF in motor compensation by relating diffusion-tensor-imaging-derived parameters of white matter microstructure to measures of proximal and distal motor function in patients after hemispherotomy. Twenty-five patients (13 women; mean age: 21.1 years) after hemispherotomy (at mean age: 12.4 years) underwent Diffusion Tensor Imaging and evaluation of motor function using the Fugl-Meyer Assessment and the index finger tapping test. Regression analyses revealed that fractional anisotropy of the PT explained (p = 0.050) distal motor function including finger tapping rate (p = 0.027), whereas fractional anisotropy of aMF originating in the contralesional cortex and crossing to the ipsilesional hemisphere in the pons explained proximal motor function (p = 0.001). Age at surgery was found to be the only clinical variable to explain motor function (p

Highlights • Fixel-based analysis allows for novel view on limbic encephalitis. • Bilateral alterations in superior longitudinal fascicle of GAD-limbic-encephalitis. • Fiber tract alterations observed relate to verbal memory performance., Limbic encephalitis (LE) is an autoimmune syndrome often associated with temporal lobe epilepsy. Recent research suggests that particular structural changes in LE depend on the type of the associated antibody and occur in both mesiotemporal gray matter and white matter regions. However, it remains questionable to what degree conventional diffusion tensor imaging (DTI)-methods reflect alterations in white matter microstructure, since these methods do not account for crossing fibers. To address this methodological shortcoming, we applied fixel-based analysis as a novel technique modeling distinct fiber populations. For our study, 19 patients with LE associated with autoantibodies against glutamic acid decarboxylase 65 (GAD-LE, mean age = 35.9 years, 11 females), 4 patients with LE associated with autoantibodies against leucine-rich glioma-inactivated 1 (LGI1-LE, mean age = 63.3 years, 2 females), 5 patients with LE associated with contactin-associated protein-like 2 (CASPR2, mean age = 57.4, 0 females), 20 age- and gender-matched control patients with hippocampal sclerosis (19 GAD-LE control patients: mean age = 35.1 years, 11 females; 4 LGI1-LE control patients: mean age = 52.6 years, 2 females; 5 CASPR2-LE control patients: mean age = 42.7 years, 0 females; 10 patients are included in more than one group) and 33 age- and gender-matched healthy control subjects (19 GAD-LE healthy controls: mean age = 34.6 years, 11 females; 8 LGI1-LE healthy controls: mean age = 57.0 years, 4 females, 10 CASPR2-LE healthy controls: mean age = 57.2 years, 0 females; 4 subjects are included in more than one group) underwent structural imaging and DTI at 3 T and neuropsychological testing. Patient images were oriented according to lateralization in EEG resulting in an affected and unaffected hemisphere. Fixel-based metrics fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC = FD · FC) were calculated to retrieve information about white matter integrity both on the micro- and the macroscale. As compared to healthy controls, patients with GAD-LE showed significantly (family-wise error-corrected, p