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Background and Objective: To test the hypothesis that a multicenter-validated computer deep learning algorithm detects MRI-negative focal cortical dysplasia (FCD)., Methods: We used clinically acquired 3-dimensional (3D) T1-weighted and 3D fluid-attenuated inversion recovery MRI of 148 patients (median age 23 years [range 2-55 years]; 47% female) with histologically verified FCD at 9 centers to train a deep convolutional neural network (CNN) classifier. Images were initially deemed MRI-negative in 51% of patients, in whom intracranial EEG determined the focus. For risk stratification, the CNN incorporated bayesian uncertainty estimation as a measure of confidence. To evaluate performance, detection maps were compared to expert FCD manual labels. Sensitivity was tested in an independent cohort of 23 cases with FCD (13 ± 10 years). Applying the algorithm to 42 healthy controls and 89 controls with temporal lobe epilepsy disease tested specificity., Results: Overall sensitivity was 93% (137 of 148 FCD detected) using a leave-one-site-out cross-validation, with an average of 6 false positives per patient. Sensitivity in MRI-negative FCD was 85%. In 73% of patients, the FCD was among the clusters with the highest confidence; in half, it ranked the highest. Sensitivity in the independent cohort was 83% (19 of 23; average of 5 false positives per patient). Specificity was 89% in healthy and disease controls., Discussion: This first multicenter-validated deep learning detection algorithm yields the highest sensitivity to date in MRI-negative FCD. By pairing predictions with risk stratification, this classifier may assist clinicians in adjusting hypotheses relative to other tests, increasing diagnostic confidence. Moreover, generalizability across age and MRI hardware makes this approach ideal for presurgical evaluation of MRI-negative epilepsy., Classification of Evidence: This study provides Class III evidence that deep learning on multimodal MRI accurately identifies FCD in patients with epilepsy initially diagnosed as MRI negative., (© 2021 American Academy of Neurology.)

Objective: In an attempt to improve postsurgical seizure outcomes for poorly defined cases (PDCs) of pediatric focal epilepsy (i.e., those that are not visible or well defined on 3T MRI), the authors modified their presurgical evaluation strategy. Instead of relying on concordance between video-electroencephalography and 3T MRI and using functional imaging and intracranial recording in select cases, the authors systematically used a multimodal, 3-tiered investigation protocol that also involved new collaborations between their hospital, the Montreal Children's Hospital, and the Montreal Neurological Institute. In this study, the authors examined how their new strategy has impacted postsurgical outcomes. They hypothesized that it would improve postsurgical seizure outcomes, with the added benefit of identifying a subset of tests contributing the most., Methods: Chart review was performed for children with PDCs who underwent resection following the new strategy (i.e., new protocol [NP]), and for the same number who underwent treatment previously (i.e., preprotocol [PP]); ≥ 1-year follow-up was required for inclusion. Well-defined, multifocal, and diffuse hemispheric cases were excluded. Preoperative demographics and clinical characteristics, resection volumes, and pathology, as well as seizure outcomes (Engel class Ia vs > Ia) at 1 year postsurgery and last follow-up were reviewed., Results: Twenty-two consecutive NP patients were compared with 22 PP patients. There was no difference between the two groups for resection volumes, pathology, or preoperative characteristics, except that the NP group underwent more presurgical evaluation tests (p < 0.001). At 1 year postsurgery, 20 of 22 NP patients and 10 of 22 PP patients were seizure free (OR 11.81, 95% CI 2.00-69.68; p = 0.006). Magnetoencephalography and PET/MRI were associated with improved postsurgical seizure outcomes, but both were highly correlated with the protocol group (i.e., independent test effects could not be demonstrated)., Conclusions: A new presurgical evaluation strategy for children with PDCs of focal epilepsy led to improved postsurgical seizure freedom. No individual presurgical evaluation test was independently associated with improved outcome, suggesting that it may be the combined systematic protocol and new interinstitutional collaborations that makes the difference rather than any individual test.

The ILAE Neuroimaging Task Force aims to publish educational case reports highlighting basic aspects related to neuroimaging in epilepsy consistent with the educational mission of the ILAE. Previous quantitative MRI studies have established important imaging markers of epilepsy-related pathology, including features sensitive to hippocampal cell loss and reactive astrogliosis. Here, we review the case of a female with pediatric drug-resistant epilepsy. Throughout her course of treatment, she had seven MRI investigations at several centers; the first three did not follow optimized epilepsy imaging protocols whereas the remaining four adhered to HARNESS-MRI protocols ( har monized n euroimaging of e pilepsy s tructural s equences). Visual inspection of a set of HARNESS-MR images revealed conspicuous left hippocampal hyperintensity which may have been initially overlooked on non-optimized MR images. Quantitative analysis of these multimodal imaging data along hippocampal subfields provided clear evidence of hippocampal sclerosis, with increased atrophy, increased mean diffusivity, increased T2-FLAIR signal, and lower qT1 values observed in the anterior portions of the left, compared to the right hippocampus. The patient underwent a left anterior temporal lobectomy with amygdalohippocampectomy at age 16 years. Histopathology of the resected specimen also confirmed hippocampal sclerosis with widespread gliosis and focal neuronal loss in the hippocampal subfields overlapping with regions of multimodal quantitative alterations. The patient remains seizure-free one year after surgery. Collectively, this case highlights the need for optimized data acquisition protocols early in the treatment of epilepsy and supports quantitative analysis of MRI contrasts to enhance personalized diagnosis and prognosis of drug-resistant patients with epilepsy.

Episodic memory is the ability to remember events from our past accurately. The process of pattern separation is hypothesized to underpin this ability and is defined as the capacity to orthogonalize memory traces, to maximize the features that make them unique. Contemporary cognitive neuroscience suggests that pattern separation entails complex interactions between the hippocampus and neocortex, where specific hippocampal subregions shape neural reinstatement in the neocortex. To test this hypothesis, the current work studied both healthy controls and patients with temporal lobe epilepsy who presented with hippocampal structural anomalies. We measured neural activity in all participants using functional MRI while they retrieved memorized items or lure items, which shared features with the target. Behaviourally, patients with temporal lobe epilepsy were less able to exclude lures than controls and showed a reduction in pattern separation. To assess the hypothesized relationship between neural patterns in the hippocampus and neocortex, we identified the topographic gradients of intrinsic connectivity along neocortical and hippocampal subfield surfaces and determined the topographic profile of the neural activity accompanying pattern separation. In healthy controls, pattern separation followed a graded topography of neural activity, both along the hippocampal long axis (and peaked in anterior segments that are more heavily engaged in transmodal processing) and along the neocortical hierarchy running from unimodal to transmodal regions (peaking in transmodal default mode regions). In patients with temporal lobe epilepsy, however, this concordance between task-based functional activations and topographic gradients was markedly reduced. Furthermore, person-specific measures of concordance between task-related activity and connectivity gradients in patients and controls were related to inter-individual differences in behavioural measures of pattern separation and episodic memory, highlighting the functional relevance of the observed topographic motifs. Our work is consistent with an emerging understanding that successful discrimination between memories with similar features entails a shift in the locus of neural activity away from sensory systems, a pattern that is mirrored along the hippocampal long axis and with respect to neocortical hierarchies. More broadly, our study establishes topographic profiling using intrinsic connectivity gradients, capturing the functional underpinnings of episodic memory processes in a manner that is sensitive to their reorganization in pathology., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Increased (abnormal) ventilation inhomogeneity in individuals with mild Cystic Fibrosis (CF) lung disease may become a treatable trait for small-molecule therapeutics improving Cystic Fibrosis Transmembrane Regulator (CFTR) function. The relationship between CFTR function and ventilation inhomogeneity is unknown. We aimed to identify and quantify increased ventilation inhomogeneity in relation to CFTR function., Methods: This was an international, multi-center, cross-sectional study. We collated data from individuals aged 3-25 years with minimal (CFTR-MF) or residual (CFTR-RF) function of a variety of CFTR genotypes and FEV 1 ≥ 70% predicted. We measured lung function using nitrogen multiple-breath washout and spirometry. We compared lung clearance index (LCI) and FEV 1 between individuals with CFTR-MF vs CFTR-RF using a mixed effects multi-variable linear regression model to account for study differences and a logistic model based on propensity-score matching to adjust for possible confounding., Results: We included 141 with CFTR-MF and 35 with CFTR-RF. LCI (> 1.96 z-score) was elevated in 71.6% individuals with CFTR-MF and in 40.0% with CFTR-RF. FEV 1 (< -1.96 z-score) was reduced in 11.3% individuals with CFTR-MF and in 5.7% with CFTR-RF. The mean difference (95% CI) of LCI and FEV 1 between CFTR-MF and CFTR-RF was 3.71 (1.63 to 5.79) and -0.40 (-0.83 to 0.02) z-score. The LCI differences were similar after adjustment for confounders and in individuals with normal FEV 1 ., Conclusion: Increased ventilation inhomogeneity is associated with less CFTR function. In individuals with mild CF lung disease, LCI can identify and quantify increased ventilation inhomogeneity, a candidate treatable trait., Competing Interests: Declaration of Competing Interest Dr. Bernasconi has no conflicts of interest to disclose. Dr. Kieninger reports grants from the Swiss Society of Cystic Fibrosis (CFCH), outside the submitted work. Mrs. Shaw has no conflicts of interest to disclose. Mrs. Kurz has nothing to disclose. Dr. Moeller has no conflicts of interest to disclose. Dr. Ratjen reports grants and personal fees from Vertex, personal fees from Boehringer/Ingelheim, Calithera, Proteostasis, and Translate Bio, outside the submitted work. Dr Rochat has nothing to disclose. Dr. Stanojevic has nothing to disclose. Dr. Singer reports personal fees from Vertex, personal fees from Novartis, grants from the Swiss Society of Cystic Fibrosis (CFCH), Lungenliga Bern, outside the submitted work., (Copyright © 2020. Published by Elsevier B.V.)

Prior research has shown a role of the medial temporal lobe, particularly the hippocampal-parahippocampal complex, in spatial cognition. Here, we developed a new paradigm, the conformational shift spatial task (CSST), which examines the ability to encode and retrieve spatial relations between unrelated items. This task is short, uses symbolic cues, incorporates two difficulty levels, and can be administered inside the scanner. A cohort of 48 healthy young adults underwent the CSST, together with a set of behavioral measures and multimodal magnetic resonance imaging (MRI). Inter-individual differences in CSST performance correlated with scores on an established spatial memory paradigm, but neither with episodic memory nor mnemonic discrimination, supporting specificity. Analyzing high-resolution structural MRI data, individuals with better spatial memory showed thicker medial and lateral temporal cortices. Functional relevance of these findings was supported by task-based functional MRI analysis in the same participants and ad hoc meta-analysis. Exploratory resting-state functional MRI analyses centered on clusters of morphological effects revealed additional modulation of intrinsic network integration, particularly between lateral and medial temporal structures. Our work presents a novel spatial memory paradigm and supports an integrated structure-function substrate in the human temporal lobe. Task paradigms are programmed in python and made open access., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Objective: Although temporal lobe epilepsy (TLE) is recognized as a system-level disorder, little work has investigated pathoconnectomics from a dynamic perspective. By leveraging computational simulations that quantify patterns of information flow across the connectome, we tested the hypothesis that network communication is abnormal in this condition, studied the interplay between hippocampal- and network-level disease effects, and assessed associations with cognition., Methods: We simulated signal spreading via a linear threshold model that temporally evolves on a structural graph derived from diffusion-weighted magnetic resonance imaging (MRI), comparing a homogeneous group of 31 patients with histologically proven hippocampal sclerosis to 31 age- and sex-matched healthy controls. We evaluated the modulatory effects of structural alterations of the neocortex and hippocampus on network dynamics. Furthermore, multivariate statistics addressed the relationship with cognitive parameters., Results: We observed a slowing of in- and out-spreading times across multiple areas bilaterally, indexing delayed information flow, with the strongest effects in ipsilateral frontotemporal regions, thalamus, and hippocampus. Effects were markedly reduced when controlling for hippocampal volume but not cortical thickness, underscoring the central role of the hippocampus in whole-brain disease expression. Multivariate analysis associated slower spreading time in frontoparietal, limbic, default mode, and subcortical networks with impairment across tasks tapping into sensorimotor, executive, memory, and verbal abilities., Significance: Moving beyond descriptions of static topology toward the formulation of brain dynamics, our work provides novel insight into structurally mediated network dysfunction and demonstrates that altered whole-brain communication dynamics contribute to common cognitive difficulties in TLE., (© 2021 International League Against Epilepsy.)

Neuroimaging techniques, particularly magnetic resonance imaging, yield increasingly sophisticated markers of brain structure and function. Combined with ongoing developments in machine learning, these methods refine our abilities to detect subtle epileptogenic lesions and develop reliable prognostics.

Identifying a structural brain lesion on MRI has important implications in epilepsy and is the most important factor that correlates with seizure freedom after surgery in patients with drug-resistant focal onset epilepsy. However, at conventional magnetic field strengths (1.5 and 3T), only approximately 60%-85% of MRI examinations reveal such lesions. Over the last decade, studies have demonstrated the added value of 7T MRI in patients with and without known epileptogenic lesions from 1.5 and/or 3T. However, translation of 7T MRI to clinical practice is still challenging, particularly in centers new to 7T, and there is a need for practical recommendations on targeted use of 7T MRI in the clinical management of patients with epilepsy. The 7T Epilepsy Task Force-an international group representing 21 7T MRI centers with experience from scanning over 2,000 patients with epilepsy-would hereby like to share its experience with the neurology community regarding the appropriate clinical indications, patient selection and preparation, acquisition protocols and setup, technical challenges, and radiologic guidelines for 7T MRI in patients with epilepsy. This article mainly addresses structural imaging; in addition, it presents multiple nonstructural MRI techniques that benefit from 7T and hold promise as future directions in epilepsy. Answering to the increased availability of 7T MRI as an approved tool for diagnostic purposes, this article aims to provide guidance on clinical 7T MRI epilepsy management by giving recommendations on referral, suitable 7T MRI protocols, and image interpretation., (© 2020 American Academy of Neurology.)

Drug-resistant epilepsy (DRE) considerably affects patient health, cognition, and well-being, and disproportionally contributes to the overall burden of epilepsy. The most common DRE syndromes are temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal epilepsy related to cortical malformations. Both syndromes have been traditionally considered as "focal," and most patients benefit from brain surgery for long-term seizure control. However, increasing evidence indicates that many DRE patients also present with widespread structural and functional network disruptions. These anomalies have been suggested to relate to cognitive impairment and prognosis, highlighting their importance for patient management. The advent of multimodal neuroimaging and formal methods to quantify complex systems has offered unprecedented ability to profile structural and functional brain networks in DRE patients. Here, we performed a systematic review on existing DRE network biomarker candidates and their contribution to three key application areas: (1) modeling of cognitive impairments, (2) localization of the surgical target, and (3) prediction of clinical and cognitive outcomes after surgery. Although network biomarkers hold promise for a range of clinical applications, translation of neuroimaging biomarkers to the patient's bedside has been challenged by a lack of clinical and prospective studies. We therefore close by highlighting conceptual and methodological strategies to improve the evaluation and accessibility of network biomarkers, and ultimately guide clinically actionable decisions., (© 2020 International League Against Epilepsy.)

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

The mesiotemporal lobe (MTL) is implicated in many cognitive processes, is compromised in numerous brain disorders, and exhibits a gradual cytoarchitectural transition from six-layered parahippocampal isocortex to three-layered hippocampal allocortex. Leveraging an ultra-high-resolution histological reconstruction of a human brain, our study showed that the dominant axis of MTL cytoarchitectural differentiation follows the iso-to-allocortical transition and depth-specific variations in neuronal density. Projecting the histology-derived MTL model to in-vivo functional MRI, we furthermore determined how its cytoarchitecture underpins its intrinsic effective connectivity and association to large-scale networks. Here, the cytoarchitectural gradient was found to underpin intrinsic effective connectivity of the MTL, but patterns differed along the anterior-posterior axis. Moreover, while the iso-to-allocortical gradient parametrically represented the multiple-demand relative to task-negative networks, anterior-posterior gradients represented transmodal versus unimodal networks. Our findings establish that the combination of micro- and macrostructural features allow the MTL to represent dominant motifs of whole-brain functional organisation., Competing Interests: CP, OB, JD, SL, SF, JR, ST, SV, AB, NB, AK, AE, AR, JS, BB No competing interests declared, (© 2020, Paquola et al.)

Objective: To test the hypothesis that in periventricular nodular heterotopia (PVNH) structure and function of cortical areas overlying the heterotopic gray matter are preferentially affected., Methods: We studied a group of 40 patients with PVNH and normal-appearing cortex and compared their quantitative MRI markers of brain development, structure, and function to those of 43 age- and sex-matched healthy controls. Inspired by models of neocortical development suggesting that neuronal migration follows a curvilinear path to preserve topologic correspondence between the outer ventricular zone and the cortical surface, we computationally defined the overlying cortex using the Laplace equation and generated synthetic streamlines that link the ventricles, where nodules are located, and the neocortex., Results: We found multilobar cortical thickening encompassing prefrontal, latero-basal temporal, and temporoparietal cortices largely corresponding with the PVNH group-averaged map of the overlying cortex, the latter colocalized with areas of abnormal function, as defined by resting-state fMRI. Patients also presented hippocampal functional hyperconnectivity and malrotation, the latter positively correlating with neocortical maldevelopment indexed by increased folding complexity of the parahippocampus. In clusters of thickness and curvature findings, there were no significant differences between unilateral and bilateral PVNH; contrasting brain-wide metrics between cohorts was also unrevealing. There was no relationship between imaging markers and disease duration except for positive correlation with functional anomalies., Conclusion: Our quantitative image analysis demonstrates widespread structural and functional alterations in PVNH with differential interaction with the overlying cortex and the hippocampus. Right hemispheric predominance may be explained by an early insult, likely genetically determined, on brain morphogenesis., (© 2020 American Academy of Neurology.)

Epilepsy affects about 1% of the world's population, and up to 30% of all patients will ultimately not achieve freedom from seizures with anticonvulsive medication alone. While surgical resection of a magnetic resonance imaging (MRI) -identifiable lesion remains the first-line treatment option for drug-refractory epilepsy, surgery cannot be offered to all. Neuromodulatory therapy targeting "seizures" instead of "epilepsy" has emerged as a valuable treatment option for these patients, including invasive procedures such as deep brain stimulation (DBS), responsive neurostimulation (RNS) and peripheral approaches such as vagus nerve stimulation (VNS). The purpose of this review is to provide in-depth information on current concepts and evidence on network-level aspects of drug-refractory epilepsy. We reviewed the current evidence gained from studies utilizing advanced imaging methodology, with a specific focus on their contributions to neuromodulatory therapy.

Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data., (© 2020 International League Against Epilepsy.)

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Continuing advancements in neuroimaging methodology allow for increasingly detailed in vivo characterization of structural and functional brain networks, leading to the recognition of epilepsy as a disorder of large-scale networks. In surgical candidates, analysis of functional networks has proved invaluable for the identification of eloquent brain areas, such as hemispherical language dominance. More recently, connectome-based biomarkers have demonstrated potential to further inform clinical decision making in drug-refractory epilepsy. This article summarizes current evidence on epilepsy as a network disorder, emphasizing potential benefits of network analysis techniques for preoperative assessments and resection planning., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. Although it is commonly related to hippocampal pathology, increasing evidence suggests structural changes beyond the mesiotemporal lobe. Functional anomalies and their link to underlying structural alterations, however, remain incompletely understood., Methods: We studied 30 drug-resistant TLE patients and 57 healthy controls using multimodal magnetic resonance imaging (MRI) analyses. All patients had histologically verified hippocampal sclerosis and underwent postoperative imaging to outline the extent of their surgical resection. Our analysis leveraged a novel resting-state functional MRI framework that parameterizes functional connectivity distance, consolidating topological and physical properties of macroscale brain networks. Functional findings were integrated with morphological and microstructural metrics, and utility for surgical outcome prediction was assessed using machine learning techniques., Results: Compared to controls, TLE patients showed connectivity distance reductions in temporoinsular and prefrontal networks, indicating topological segregation of functional networks. Testing for morphological and microstructural associations, we observed that functional connectivity contractions occurred independently from TLE-related cortical atrophy but were mediated by microstructural changes in the underlying white matter. Following our imaging study, all patients underwent an anterior temporal lobectomy as a treatment of their seizures, and postsurgical seizure outcome was determined at a follow-up at least 1 year after surgery. Using a regularized supervised machine learning paradigm with fivefold cross-validation, we demonstrated that patient-specific functional anomalies predicted postsurgical seizure outcome with 76 ± 4% accuracy, outperforming classifiers operating on clinical and structural imaging features., Significance: Our findings suggest connectivity distance contractions as a macroscale substrate of TLE. Functional topological isolation may represent a microstructurally mediated network mechanism that tilts the balance toward epileptogenesis in affected networks and that may assist in patient-specific surgical prognostication., (© 2020 International League Against Epilepsy.)

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Thalamo-cortical pathology plays key roles in both generalized and focal epilepsies, but there is little work directly comparing these syndromes at the level of whole-brain mechanisms. Using multimodal imaging, connectomics, and computational simulations, we examined thalamo-cortical and cortico-cortical signatures and underlying microcircuits in 96 genetic generalized (GE) and 107 temporal lobe epilepsy (TLE) patients, along with 65 healthy controls. Structural and functional network profiling highlighted extensive atrophy, microstructural disruptions and decreased thalamo-cortical connectivity in TLE, while GE showed only subtle structural anomalies paralleled by enhanced thalamo-cortical connectivity. Connectome-informed biophysical simulations indicated modest increases in subcortical drive contributing to cortical dynamics in GE, while TLE presented with reduced subcortical drive and imbalanced excitation-inhibition within limbic and somatomotor microcircuits. Multiple sensitivity analyses supported robustness. Our multiscale analyses differentiate human focal and generalized epilepsy at the systems-level, showing paradoxically more severe microcircuit and macroscale imbalances in the former.

Objective: Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation and a prevalent cause of surgically amenable epilepsy. While cellular and molecular biology data suggest that FCD lesional characteristics lie along a spectrum, this notion remains to be verified in vivo. We tested the hypothesis that machine learning applied to MRI captures FCD lesional variability at a mesoscopic scale., Methods: We studied 46 patients with histologically verified FCD Type II and 35 age- and sex-matched healthy controls. We applied consensus clustering, an unsupervised learning technique that identifies stable clusters based on bootstrap-aggregation, to 3 T multicontrast MRI (T1-weighted MRI and FLAIR) features of FCD normalized with respect to distributions in controls., Results: Lesions were parcellated into four classes with distinct structural profiles variably expressed within and across patients: Class-1 with isolated white matter (WM) damage; Class-2 combining grey matter (GM) and WM alterations; Class-3 with isolated GM damage; Class-4 with GM-WM interface anomalies. Class membership was replicated in two independent datasets. Classes with GM anomalies impacted local function (resting-state fMRI derived ALFF), while those with abnormal WM affected large-scale connectivity (assessed by degree centrality). Overall, MRI classes reflected typical histopathological FCD characteristics: Class-1 was associated with severe WM gliosis and interface blurring, Class-2 with severe GM dyslamination and moderate WM gliosis, Class-3 with moderate GM gliosis, Class-4 with mild interface blurring. A detection algorithm trained on class-informed data outperformed a class-naïve paradigm., Significance: Machine learning applied to widely available MRI contrasts uncovers FCD Type II variability at a mesoscopic scale and identifies tissue classes with distinct structural dimensions, functional and histopathological profiles. Integrating in vivo staging of FCD traits with automated lesion detection is likely to inform the development of novel personalized treatments., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: Previous imaging studies in patients with refractory temporal lobe epilepsy (TLE) have examined the spatial distribution of changes in imaging parameters such as diffusion tensor imaging (DTI) metrics and cortical thickness. Multi-compartment models offer greater specificity with parameters more directly related to known changes in TLE such as altered neuronal density and myelination. We studied the spatial distribution of conventional and novel metrics including neurite density derived from NODDI (Neurite Orientation Dispersion and Density Imaging) and myelin water fraction (MWF) derived from mcDESPOT (Multi-Compartment Driven Equilibrium Single Pulse Observation of T1/T2)] to infer the underlying neurobiology of changes in conventional metrics., Methods: 20 patients with TLE and 20 matched controls underwent magnetic resonance imaging including a volumetric T1-weighted sequence, multi-shell diffusion from which DTI and NODDI metrics were derived and a protocol suitable for mcDESPOT fitting. Models of the grey matter-white matter and grey matter-CSF surfaces were automatically generated from the T1-weighted MRI. Conventional diffusion and novel metrics of neurite density and MWF were sampled from intracortical grey matter and subcortical white matter surfaces and cortical thickness was measured., Results: In intracortical grey matter, diffusivity was increased in the ipsilateral temporal and frontopolar cortices with more restricted areas of reduced neurite density. Diffusivity increases were largely related to reductions in neurite density, and to a lesser extent CSF partial volume effects, but not MWF. In subcortical white matter, widespread bilateral reductions in fractional anisotropy and increases in radial diffusivity were seen. These were primarily related to reduced neurite density, with an additional relationship to reduced MWF in the temporal pole and anterolateral temporal neocortex. Changes were greater with increasing epilepsy duration. Bilaterally reduced cortical thickness in the mesial temporal lobe and centroparietal cortices was unrelated to neurite density and MWF., Conclusions: Diffusivity changes in grey and white matter are primarily related to reduced neurite density with an additional relationship to reduced MWF in the temporal pole. Neurite density may represent a more sensitive and specific biomarker of progressive neuronal damage in refractory TLE that deserves further study., Competing Interests: Declarations of Competing Interest None., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aging is characterized by accumulation of structural and metabolic changes in the brain. Recent studies suggest transmodal brain networks are especially sensitive to aging, which, we hypothesize, may be due to their apical position in the cortical hierarchy. Studying an open-access healthy cohort (n = 102, age range = 30-89 years) with MRI and Aβ PET data, we estimated age-related cortical thinning, hippocampal atrophy and Aβ deposition. In addition to carrying out surface-based morphological and metabolic mapping experiments, we stratified effects along neocortical and hippocampal resting-state functional connectome gradients derived from independent datasets. The cortical gradient depicts an axis of functional differentiation from sensory-motor regions to transmodal regions, whereas the hippocampal gradient recapitulates its long-axis. While age-related thinning and increased Aβ deposition occurred across the entire cortical topography, increased Aβ deposition was especially pronounced toward higher-order transmodal regions. Age-related atrophy was greater toward the posterior end of the hippocampal long-axis. No significant effect of age on Aβ deposition in the hippocampus was observed. Imaging markers correlated with behavioral measures of fluid intelligence and episodic memory in a topography-specific manner, confirmed using both univariate as well as multivariate analyses. Our results strengthen existing evidence of structural and metabolic change in the aging brain and support the use of connectivity gradients as a compact framework to analyze and conceptualize brain-based biomarkers of aging., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Objective: MRI studies of genetic generalized epilepsies have mainly described group-level changes between patients and healthy controls. To determine the endophenotypic potential of structural MRI in juvenile myoclonic epilepsy (JME), we examined MRI-based cortical morphologic markers in patients and their healthy siblings., Methods: In this prospective, cross-sectional study, we obtained 3T MRI in patients with JME, siblings, and controls. We mapped sulco-gyral complexity and surface area, morphologic markers of brain development, and cortical thickness. Furthermore, we calculated mean geodesic distance, a surrogate marker of cortico-cortical connectivity., Results: Compared to controls, patients and siblings showed increased folding complexity and surface area in prefrontal and cingulate cortices. In these regions, they also displayed abnormally increased geodesic distance, suggesting network isolation and decreased efficiency, with strongest effects for limbic, fronto-parietal, and dorsal-attention networks. In areas of findings overlap, we observed strong patient-sibling correlations. Conversely, neocortical thinning was present in patients only and related to disease duration. Patients showed subtle impairment in mental flexibility, a frontal lobe function test, as well as deficits in naming and design learning. Siblings' performance fell between patients and controls., Conclusion: MRI markers of brain development and connectivity are likely heritable and may thus serve as endophenotypes. The topography of morphologic anomalies and their abnormal structural network integration likely explains cognitive impairments in patients with JME and their siblings. By contrast, cortical atrophy likely represents a marker of disease., (Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Objective: To study the intrinsic organization of the thalamocortical circuitry in patients with generalized epilepsy with tonic-clonic seizures (GTCS) via resting-state fMRI (rs-fMRI) connectome analysis and to evaluate its relation to drug response., Methods: In a prospectively followed-up sample of 41 patients and 27 healthy controls, we obtained rs-fMRI and structural MRI. After 1 year of follow-up, 27 patients were classified as seizure-free and 14 as drug-resistant. We examined connectivity within and between resting-state communities in cortical and thalamic subregions. In addition to comparing patients to controls, we examined associations with seizure control. We assessed reproducibility in an independent cohort of 21 patients., Results: Compared to controls, patients showed a more constrained network embedding of the thalamus, while frontocentral neocortical regions expressed increased functional diversity. Findings remained significant after regressing out thalamic volume and cortical thickness, suggesting independence from structural alterations. We observed more marked network imbalances in drug-resistant compared to seizure-free patients. Findings were similar in the reproducibility dataset., Conclusions: Our findings suggest a pathoconnectomic mechanism of generalized epilepsy centered on diverging changes in cortical and thalamic connectivity. More restricted thalamic connectivity could reflect the tendency to engage in recursive thalamocortical loops, which may contribute to hyperexcitability. Conversely, increased connectional diversity of frontocentral networks may relay abnormal activity to an extended bilateral territory. Network imbalances were observed shortly after diagnosis and related to future drug response, suggesting clinical utility., (© 2019 American Academy of Neurology.)

Neuroimaging techniques applied to a variety of organisms-from zebrafish, to rodents to humans-can offer valuable insights into neuronal network properties and their dysfunction in epilepsy. A wide range of imaging methods used to monitor neuronal circuits and networks during evoked seizures in animal models and advances in functional magnetic resonance imaging (fMRI) applied to patients with epilepsy were discussed during the XIV Workshop on Neurobiology of Epilepsy (XIV WONOEP) organized in 2017 by the Neurobiology Commission of the International League Against Epilepsy (ILAE). We review the growing number of technological approaches developed, as well as the current state of knowledge gained from studies applying these advanced imaging approaches to epilepsy research., (Wiley Periodicals, Inc. © 2019 International League Against Epilepsy.)

Structural magnetic resonance imaging (MRI) is of fundamental importance to the diagnosis and treatment of epilepsy, particularly when surgery is being considered. Despite previous recommendations and guidelines, practices for the use of MRI are variable worldwide and may not harness the full potential of recent technological advances for the benefit of people with epilepsy. The International League Against Epilepsy Diagnostic Methods Commission has thus charged the 2013-2017 Neuroimaging Task Force to develop a set of recommendations addressing the following questions: (1) Who should have an MRI? (2) What are the minimum requirements for an MRI epilepsy protocol? (3) How should magnetic resonance (MR) images be evaluated? (4) How to optimize lesion detection? These recommendations target clinicians in established epilepsy centers and neurologists in general/district hospitals. They endorse routine structural imaging in new onset generalized and focal epilepsy alike and describe the range of situations when detailed assessment is indicated. The Neuroimaging Task Force identified a set of sequences, with three-dimensional acquisitions at its core, the harmonized neuroimaging of epilepsy structural sequences-HARNESS-MRI protocol. As these sequences are available on most MR scanners, the HARNESS-MRI protocol is generalizable, regardless of the clinical setting and country. The Neuroimaging Task Force also endorses the use of computer-aided image postprocessing methods to provide an objective account of an individual's brain anatomy and pathology. By discussing the breadth and depth of scope of MRI, this report emphasizes the unique role of this noninvasive investigation in the care of people with epilepsy., (Wiley Periodicals, Inc. © 2019 International League Against Epilepsy.)

Objective: To assess whether hippocampal sclerosis (HS) severity is mirrored at the level of large-scale networks., Methods: We studied preoperative high-resolution anatomical and diffusion-weighted MRI of 44 temporal lobe epilepsy (TLE) patients with histopathologic diagnosis of HS (n = 25; TLE-HS) and isolated gliosis (n = 19; TLE-G) and 25 healthy controls. Hippocampal measurements included surface-based subfield mapping of atrophy and T2 hyperintensity indexing cell loss and gliosis, respectively. Whole-brain connectomes were generated via diffusion tractography and examined using graph theory along with a novel network control theory paradigm that simulates functional dynamics from structural network data., Results: Compared to controls, we observed markedly increased path length and decreased clustering in TLE-HS compared to controls, indicating lower global and local network efficiency, while TLE-G showed only subtle alterations. Similarly, network controllability was lower in TLE-HS only, suggesting limited range of functional dynamics. Hippocampal imaging markers were positively associated with macroscale network alterations, particularly in ipsilateral CA1-3. Systematic assessment across several networks revealed maximal changes in the hippocampal circuity. Findings were consistent when correcting for cortical thickness, suggesting independence from gray matter atrophy., Conclusions: Severe HS is associated with marked remodeling of connectome topology and structurally governed functional dynamics in TLE, as opposed to isolated gliosis, which has negligible effects. Cell loss, particularly in CA1-3, may exert a cascading effect on brain-wide connectomes, underlining coupled disease processes across multiple scales., (© 2019 American Academy of Neurology.)

Epilepsy is among the most common chronic neurologic disorders, with 30%-40% of patients having seizures despite antiepileptic drug treatment. The advent of brain imaging and network analyses has greatly improved the understanding of this condition. In particular, developments in magnetic resonance imaging (MRI) have provided measures for the noninvasive characterization and detection of lesions causing epilepsy. MRI techniques can probe structural and functional connectivity, and network analyses have shaped our understanding of whole-brain anomalies associated with focal epilepsies. This review considers the progress made by neuroimaging and connectomics in the study of drug-resistant epilepsies due to focal substrates, particularly temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal lobe epilepsies associated with malformations of cortical development. In these disorders, there is evidence of widespread disturbances of structural and functional connectivity that may contribute to the clinical and cognitive prognosis of individual patients. It is hoped that studying the interplay between macroscale network anomalies and lesional profiles will improve our understanding of focal epilepsies and assist treatment choices., (Wiley Periodicals, Inc. © 2019 International League Against Epilepsy.)

Neuroimaging studies have consistently shown distributed brain anomalies in epilepsy syndromes associated with a focal structural lesion, particularly mesiotemporal sclerosis. Conversely, a system-level approach to focal cortical dysplasia has been rarely considered, likely due to methodological difficulties in addressing variable location and topography. Given the known heterogeneity in focal cortical dysplasia histopathology, we hypothesized that lesional connectivity consists of subtypes with distinct structural signatures. Furthermore, in light of mounting evidence for focal anomalies impacting whole-brain systems, we postulated that patterns of focal cortical dysplasia connectivity may exert differential downstream effects on global network topology. We studied a cohort of patients with histologically verified focal cortical dysplasia type II (n = 27), and age- and sex-matched healthy controls (n = 34). We subdivided each lesion into similarly sized parcels and computed their connectivity to large-scale canonical functional networks (or communities). We then dichotomized connectivity profiles of lesional parcels into those belonging to the same functional community as the focal cortical dysplasia (intra-community) and those adhering to other communities (inter-community). Applying hierarchical clustering to community-reconfigured connectome profiles identified three lesional classes with distinct patterns of functional connectivity: decreased intra- and inter-community connectivity, a selective decrease in intra-community connectivity, and increased intra- as well as inter-community connectivity. Hypo-connectivity classes were mainly composed of focal cortical dysplasia type IIB, while the hyperconnected lesions were type IIA. With respect to whole-brain networks, patients with hypoconnected focal cortical dysplasia and marked structural damage showed only mild imbalances, while those with hyperconnected subtle lesions had more pronounced topological alterations. Correcting for interictal epileptic discharges did not impact connectivity patterns. Multivariate structural equation analysis provided a mechanistic model of such complex, diverging interactions, whereby the focal cortical dysplasia structural makeup shapes its functional connectivity, which in turn modulates whole-brain network topology., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Rapid advances in neuroimaging and network science have produced powerful tools and measures to appreciate human brain organization at multiple spatial and temporal scales. It is now possible to obtain increasingly meaningful representations of whole-brain structural and functional brain networks and to formally assess macroscale principles of network topology. In addition to its utility in characterizing healthy brain organization, individual variability, and life span-related changes, there is high promise of network neuroscience for the conceptualization and, ultimately, management of brain disorders. In the current review, we argue for a science of the human brain that, while strongly embracing macroscale connectomics, also recommends awareness of brain properties derived from meso- and microscale resolutions. Such features include MRI markers of tissue microstructure, local functional properties, as well as information from nonimaging domains, including cellular, genetic, or chemical data. Integrating these measures with connectome models promises to better define the individual elements that constitute large-scale networks, and clarify the notion of connection strength among them. By enriching the description of large-scale networks, this approach may improve our understanding of fundamental principles of healthy brain organization. Notably, it may also better define the substrate of prevalent brain disorders, including stroke, autism, as well as drug-resistant epilepsies that are each characterized by intriguing interactions between local anomalies and network-level perturbations.

The majority of MRI studies in temporal lobe epilepsy (TLE) have utilized morphometry to map widespread cortical alterations. Morphological markers, such as cortical thickness or grey matter density, reflect combinations of biological events largely driven by overall cortical geometry rather than intracortical tissue properties. Because of its sensitivity to intracortical myelin, quantitative measurement of longitudinal relaxation time (qT 1 ) provides and an in vivo proxy for cortical microstructure. Here, we mapped the regional distribution of qT 1 in a consecutive cohort of 24 TLE patients and 20 healthy controls. Compared to controls, patients presented with a strictly ipsilateral distribution of qT 1 increases in temporopolar, parahippocampal and orbitofrontal cortices. Supervised statistical learning applied to qT 1 maps could lateralize the seizure focus in 92% of patients. Intracortical profiling of qT 1 along streamlines perpendicular to the cortical mantle revealed marked effects in upper levels that tapered off at the white matter interface. Findings remained robust after correction for cortical thickness and interface blurring, suggesting independence from previously reported morphological anomalies in this disorder. Mapping of qT 1 along hippocampal subfield surfaces revealed marked increases in anterior portions of the ipsilateral CA1-3 and DG that were also robust against correction for atrophy. Notably, in operated patients, qualitative histopathological analysis of myelin stains in resected hippocampal specimens confirmed disrupted internal architecture and fiber organization. Both hippocampal and neocortical qT 1 anomalies were more severe in patients with early disease onset. Finally, analysis of resting-state connectivity from regions of qT 1 increases revealed altered intrinsic functional network embedding in patients, particularly to prefrontal networks. Analysis of qT 1 suggests a preferential susceptibility of ipsilateral limbic cortices to microstructural damage, possibly related to disrupted myeloarchitecture. These alterations may reflect atypical neurodevelopment and affect the integrity of fronto-limbic functional networks., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The hippocampus plays key roles in cognition and affect and serves as a model system for structure/function studies in animals. So far, its complex anatomy has challenged investigations targeting its substructural organization in humans. State-of-the-art MRI offers the resolution and versatility to identify hippocampal subfields, assess its microstructure, and study topographical principles of its connectivity in vivo. We developed an approach to unfold the human hippocampus and examine spatial variations of intrinsic functional connectivity in a large cohort of healthy adults. In addition to mapping common and unique connections across subfields, we identified two main axes of subregional connectivity transitions. An anterior/posterior gradient followed long-axis landmarks and metaanalytical findings from task-based functional MRI, while a medial/lateral gradient followed hippocampal infolding and correlated with proxies of cortical myelin. Findings were consistent in an independent sample and highly stable across resting-state scans. Our results provide robust evidence for long-axis specialization in the resting human hippocampus and suggest an intriguing interplay between connectivity and microstructure., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Objective: In contrast to adult cohorts, neocortical changes in epileptic children with hippocampal damage are not well characterized. Here, we mapped multimodal neocortical markers of epilepsy-related structural compromise in a pediatric cohort of temporal lobe epilepsy and explored how they relate to clinical factors., Methods: We measured cortical thickness, gray-white matter intensity contrast and intracortical FLAIR intensity in 22 patients with hippocampal sclerosis (HS) and 30 controls. Surface-based linear models assessed between-group differences in morphological and MR signal intensity markers. Structural integrity of the hippocampus was measured by quantifying atrophy and FLAIR patterns. Linear models were used to evaluate the relationships between hippocampal and neocortical MRI markers and clinical factors., Results: In the hippocampus, patients demonstrated ipsilateral atrophy and bilateral FLAIR hyperintensity. In the neocortex, patients showed FLAIR signal hyperintensities and gray-white matter boundary blurring in the ipsilesional mesial and lateral temporal neocortex. In contrast, cortical thinning was minimal and restricted to a small area of the ipsilesional temporal pole. Furthermore, patients with a history of febrile convulsions demonstrated more pronounced FLAIR hyperintensity in the ipsilesional temporal neocortex., Interpretation: Pediatric HS patients do not yet demonstrate the widespread cortical thinning present in adult cohorts, which may reflect consequences of a protracted disease process. However, pronounced temporal neocortical FLAIR hyperintensity and blurring of the gray-white matter boundary are already detectable, suggesting that alterations in MR signal intensities may reflect a different underlying pathophysiology that is detectable earlier in the disease and more pervasive in patients with a history of febrile convulsions.

Human cognition is not limited to the available environmental input but can consider realities that are different to the here and now. We describe the cognitive states and neural processes linked to the refinement of descriptions of personal goals. When personal goals became concrete, participants reported greater thoughts about the self and the future during mind-wandering. This pattern was not observed for descriptions of TV programmes. Connectivity analysis of participants who underwent a resting-state functional magnetic resonance imaging scan revealed neural traits associated with this pattern. Strong hippocampal connectivity with ventromedial pre-frontal cortex was common to better-specified descriptions of goals and TV programmes, while connectivity between hippocampus and the pre-supplementary motor area was associated with individuals whose goals were initially abstract but became more concrete over the course of the experiment. We conclude that self-generated cognition that arises during the mind-wandering state can allow goals to be refined, and this depends on neural systems anchored in the hippocampus.

Numerous neurological disorders are associated with atrophy of mesiotemporal lobe structures, including the hippocampus (HP), amygdala (AM), and entorhinal cortex (EC). Accurate segmentation of these structures is, therefore, necessary for understanding the disease process and patient management. Recent multiple-template segmentation algorithms have shown excellent performance in HP segmentation. Purely surface-based methods precisely describe structural boundary but their performance likely depends on a large template library, as segmentation suffers when the boundaries of template and individual MRI are not well aligned while volume-based methods are less dependent. So far only few algorithms attempted segmentation of entire mesiotemporal structures including the parahippocampus. We compared performance of surface- and volume-based approaches in segmenting the three mesiotemporal structures and assess the effects of different environments (i.e., size of templates, under pathology). We also proposed an algorithm that combined surface- with volume-derived similarity measures for optimal template selection. To further improve the method, we introduced two new modules: (1) a non-linear registration that is driven by volume-based intensities and features sampled on deformable template surfaces; (2) a shape averaging based on regional weighting using multi-scale global-to-local icosahedron sampling. Compared to manual segmentations, our approach, namely HybridMulti showed high accuracy in 40 healthy controls (mean Dice index for HP/AM/EC = 89.7/89.3/82.9%) and 135 patients with temporal lobe epilepsy (88.7/89.0/82.6%). This accuracy was comparable across two different datasets of 1.5T and 3T MRI. It resulted in the best performance among tested multi-template methods that were either based on volume or surface data alone in terms of accuracy and sensitivity to detect atrophy related to epilepsy. Moreover, unlike purely surface-based multi-template segmentation, HybridMulti could maintain accurate performance even with a 50% template library size.

Objective: In drug-resistant temporal lobe epilepsy (TLE), relative to the large number of whole-brain morphological studies, neocortical T2 changes have not been systematically investigated. The aim of this study was to assess the anatomical principles that govern the distribution of neocortical T2-weighted fluid-attenuated inversion recovery (FLAIR) signal intensity and uncover its topographic principles., Methods: Using a surface-based sampling scheme, we mapped neocortical FLAIR intensity of 61 TLE patients relative to 38 healthy controls imaged at 3 T. To address topographic principles of the susceptibility to FLAIR signal changes in TLE, we assessed associations with normative data on tissue composition using 2 complementary approaches. First, we evaluated whether the degree of TLE-related FLAIR intensity changes differed across cytoarchitectonic classes as defined by Von Economo-Koskinas taxonomy. Second, as a proxy to map regions with similar intracortical composition, we carried out a FLAIR intensity covariance paradigm in controls by seeding systematically from all cortical regions, and identified those networks that were the best spatial predictors of the between-group FLAIR changes., Results: Increased intensities were observed in bilateral limbic and paralimbic cortices (hippocampus, parahippocampus, cingulate, temporopolar, insular, orbitofrontal). Effect sizes were highest in periallocortical limbic and insular classes as defined by the Von Economo-Koskinas cytoarchitectonic taxonomy. Furthermore, systematic FLAIR intensity covariance analysis in healthy controls revealed that similarity patterns characteristic of limbic cortices, most notably the hippocampus, served as sensitive predictors for the topography of FLAIR hypersignal in patients. FLAIR intensity findings were robust against correction for morphological confounds. Patients with a history of febrile convulsions showed more marked signal changes in parahippocampal and retrosplenial cortices, known to be strongly connected to the hippocampus., Significance: FLAIR intensity mapping and covariance analysis provide a model of TLE gray matter pathology based on shared vulnerability of periallocortical and limbic cortices., (Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.)

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = -0.24 to -0.73; P < 1.49 × 10-4), and lower thickness in the precentral gyri bilaterally (d = -0.34 to -0.52; P < 4.31 × 10-6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = -1.73 to -1.91, P < 1.4 × 10-19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = -0.36 to -0.52; P < 1.49 × 10-4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = -0.29 to -0.54; P < 1.49 × 10-4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = -0.27 to -0.51; P < 1.49 × 10-4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < -0.0018; P < 1.49 × 10-4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed., (© The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Growing evidence highlights the importance of white matter in the pathogenesis of focal epilepsy. Ex vivo and post-mortem studies show pathological changes in epileptic patients in white matter myelination, axonal integrity, and cellular composition. Diffusion-weighted MRI and its analytical extensions, particularly diffusion tensor imaging (DTI), have been the most widely used technique to image the white matter in vivo for the last two decades, and have shown microstructural alterations in multiple tracts both in the vicinity and at distance from the epileptogenic focus. These techniques have also shown promising ability to predict cognitive status and response to pharmacological or surgical treatments. More recently, the hypothesis that focal epilepsy may be more adequately described as a system-level disorder has motivated a shift towards the study of macroscale brain connectivity. This review will cover emerging findings contributing to our understanding of white matter alterations in focal epilepsy, studied by means of histological and ultrastructural analyses, diffusion MRI, and large-scale network analysis. Focus is put on temporal lobe epilepsy and focal cortical dysplasia. This topic was addressed in a special interest group on neuroimaging at the 70th annual meeting of the American Epilepsy Society, held in Houston December 2-6, 2016., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Neuroimaging studies of malformations of cortical development have mainly focused on the characterization of the primary lesional substrate, while whole-brain investigations remain scarce. Our purpose was to assess large-scale brain organization in prevalent cortical malformations. Based on experimental evidence suggesting that distributed effects of focal insults are modulated by stages of brain development, we postulated differential patterns of network anomalies across subtypes of malformations. We studied a cohort of patients with focal cortical dysplasia type II (n = 63), subcortical nodular heterotopia (n = 44), and polymicrogyria (n = 34), and compared them to 82 age- and sex-matched controls. Graph theoretical analysis of structural covariance networks indicated a consistent rearrangement towards a regularized architecture characterized by increased path length and clustering, as well as disrupted rich-club topology, overall suggestive of inefficient global and excessive local connectivity. Notably, we observed a gradual shift in network reconfigurations across subgroups, with only subtle changes in focal cortical dysplasia type II, moderate effects in heterotopia and maximal effects in polymicrogyria. Analysis of resting state functional connectivity also revealed gradual network changes, with most marked rearrangement in polymicrogyria; contrary to findings in the structural domain, however, functional architecture was characterized by decreases in both local and global parameters. Diverging results in the structural and functional domain were supported by formal structure-function coupling analysis. Our findings support the concept that time of insult during corticogenesis impacts the severity of topological network reconfiguration. Specifically, late-stage malformations, typified by polymicrogyria, may selectively disrupt the formation of large-scale cortico-cortical networks and thus lead to a more profound impact on whole-brain organization than early stage disturbances of predominantly radial migration patterns observed in cortical dysplasia type II, which likely affect a relatively confined cortical territory., (© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objective: It remains unclear whether drug-resistant temporal lobe epilepsy (TLE) is associated with cumulative brain damage, with no expert consensus and no quantitative syntheses of the available evidence., Methods: We conducted a systematic review and meta-analysis of MRI studies on progressive atrophy, searching PubMed and Ovid MEDLINE databases for cross-sectional and longitudinal quantitative MRI studies on drug-resistant TLE., Results: We screened 2,976 records and assessed eligibility of 248 full-text articles. Forty-two articles met the inclusion criteria for quantitative evaluation. We observed a predominance of cross-sectional studies, use of different clinical indices of progression, and high heterogeneity in age-control procedures. Meta-analysis of 18/1 cross-sectional/longitudinal studies on hippocampal atrophy (n = 979 patients) yielded a pooled effect size of r = -0.42 for ipsilateral atrophy related to epilepsy duration (95% confidence interval [CI] -0.51 to -0.32; p < 0.0001; I 2 = 65.22%) and r = -0.35 related to seizure frequency (95% CI -0.47 to -0.22; p = 61.97%). Sensitivity analyses did not change the results. Narrative synthesis of 25/3 cross-sectional/longitudinal studies on whole brain atrophy (n = 1,504 patients) indicated that >80% of articles reported duration-related progression in extratemporal cortical and subcortical regions. Detailed analysis of study design features yielded low to moderate levels of evidence for progressive atrophy across studies, mainly due to dominance of cross-sectional over longitudinal investigations, use of diverse measures of seizure estimates, and absence of consistent age control procedures.I 2 = 61.97%). Sensitivity analyses did not change the results. Narrative synthesis of 25/3 cross-sectional/longitudinal studies on whole brain atrophy (n = 1,504 patients) indicated that >80% of articles reported duration-related progression in extratemporal cortical and subcortical regions. Detailed analysis of study design features yielded low to moderate levels of evidence for progressive atrophy across studies, mainly due to dominance of cross-sectional over longitudinal investigations, use of diverse measures of seizure estimates, and absence of consistent age control procedures., Conclusions: While the neuroimaging literature is overall suggestive of progressive atrophy in drug-resistant TLE, published studies have employed rather weak designs to directly demonstrate it. Longitudinal multicohort studies are needed to unequivocally differentiate aging from disease progression., (© 2017 American Academy of Neurology.)

The hippocampus contributes to episodic, spatial and semantic aspects of memory, yet individual differences within and between these functions are not well-understood. In 136 healthy individuals, we investigated whether these differences reflect variation in the strength of connections between functionally-specialised segments of the hippocampus and diverse cortical regions that participate in different aspects of memory. Better topographical memory was associated with stronger connectivity between lingual gyrus and left anterior, rather than posterior, hippocampus. Better semantic memory was associated with increased connectivity between the intracalcarine/cuneus and left, rather than right, posterior hippocampus. Notably, we observed a double dissociation between semantic and topographical memory: better semantic memory was associated with stronger connectivity between left temporoparietal cortex and left anterior hippocampus, while better topographic memory was linked to stronger connectivity with right anterior hippocampus. Together these data support a division-of-labour account of hippocampal functioning: at the population level, differences in connectivity across the hippocampus reflect functional specialisation for different facets of memory, while variation in these connectivity patterns across individuals is associated with differences in the capacity to retrieve different types of information. In particular, within-hemisphere connectivity between hippocampus and left temporoparietal cortex supports conceptual processing at the expense of spatial ability., (Copyright © 2017. Published by Elsevier Inc.)

Objective: To characterize in vivo MRI signatures of focal cortical dysplasia (FCD) type IIA and type IIB through combined analysis of morphology, intensity, microstructure, and function., Methods: We carried out a multimodal 3T MRI profiling of 33 histologically proven FCD type IIA (9) and IIB (24) lesions. A multisurface approach operating on manual consensus labels systematically sampled intracortical and subcortical lesional features. Geodesic distance mapping quantified the same features in the lesion perimeter. Logistic regression assessed the relationship between MRI and histology, while supervised pattern learning was used for individualized subtype prediction., Results: FCD type IIB was characterized by abnormal morphology, intensity, diffusivity, and function across all surfaces, while type IIA lesions presented only with increased fluid-attenuated inversion recovery signal and reduced diffusion anisotropy close to the gray-white matter interface. Similar to lesional patterns, perilesional anomalies were more marked in type IIB extending up to 16 mm. Structural MRI markers correlated with categorical histologic characteristics. A profile-based classifier predicted FCD subtypes with equal sensitivity of 85%, while maintaining a high specificity of 94% against healthy and disease controls., Conclusions: Image processing applied to widely available MRI contrasts has the ability to dissociate FCD subtypes at a mesoscopic level. Integrating in vivo staging of pathologic traits with automated lesion detection is likely to provide an objective definition of lesional boundary and assist emerging approaches, such as minimally invasive thermal ablation, which do not supply tissue specimen., (© 2017 American Academy of Neurology.)

Drug-resistant temporal lobe epilepsy is increasingly recognized as a system-level disorder affecting the structure and function of large-scale grey matter networks. While diffusion magnetic resonance imaging studies have demonstrated deep fibre tract alterations, the superficial white matter immediately below the cortex has so far been neglected despite its proximity to neocortical regions and key role in maintaining cortico-cortical connectivity. Using multi-modal 3 T magnetic resonance imaging, we mapped the topography of superficial white matter diffusion alterations in 61 consecutive temporal lobe epilepsy patients relative to 38 healthy controls and studied the relationship to large-scale structural as well as functional networks. Our approach continuously sampled mean diffusivity and fractional anisotropy along surfaces running 2 mm below the cortex. Multivariate statistics mapped superficial white matter diffusion anomalies in patients relative to controls, while correlation and mediation analyses evaluated their relationship to structural (cortical thickness, mesiotemporal volumetry) and functional parameters (resting state functional magnetic resonance imaging amplitude) and clinical variables. Patients presented with overlapping anomalies in mean diffusivity and anisotropy, particularly in ipsilateral temporo-limbic regions. Diffusion anomalies did not relate to cortical thinning; conversely, they mediated large-scale functional amplitude decreases in patients relative to controls in default mode hub regions (i.e. anterior and posterior midline regions, lateral temporo-parietal cortices), and were themselves mediated by hippocampal atrophy. With respect to clinical variables, we observed more marked diffusion anomalies in patients with a history of febrile convulsions and those with longer disease duration. Similarly, more marked diffusion alterations were associated with seizure-free outcome. Bootstrap analyses indicated high reproducibility of our findings, suggesting generalizability. The temporo-limbic distribution of superficial white matter anomalies, together with the mediation-level findings, suggests that this so far neglected region serves a key link between the hippocampal atrophy and large-scale default mode network alterations in temporal lobe epilepsy., (© The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objective: Although most temporal lobe epilepsy (TLE) patients show marked hippocampal sclerosis (HS) upon pathological examination, 40% present with no significant cell loss but gliotic changes only. To evaluate effects of hippocampal pathology on brain structure and functional networks, we aimed at dissociating multimodal magnetic resonance imaging (MRI) characteristics in patients with HS (TLE-HS) and those with gliosis only (TLE-G)., Methods: In 20 TLE-HS, 19 TLE-G, and 25 healthy controls, we carried out a novel MRI-based hippocampal subfield surface analysis that integrated volume, T2 signal intensity, and diffusion markers with seed-based hippocampal functional connectivity., Results: Compared to controls, TLE-HS presented with marked ipsilateral atrophy, T2 hyperintensity, and mean diffusivity increases across all subfields, whereas TLE-G presented with dentate gyrus hypertrophy, focal increases in T2 intensity and mean diffusivity. Multivariate assessment confirmed a more marked ipsilateral load of anomalies across all subfields in TLE-HS, whereas anomalies in TLE-G were restricted to the subiculum. A between-cohort dissociation was independently suggested by resting-state functional connectivity analysis, revealing marked hippocampal decoupling from anterior and posterior default mode hubs in TLE-HS, whereas TLE-G did not differ from controls. Back-projection connectivity analysis from cortical targets revealed consistently decreased network embedding across all subfields in TLE-HS, while changes in TLE-G were limited to the subiculum. Hippocampal disconnectivity strongly correlated to T2 hyperintensity and marginally to atrophy., Interpretation: Multimodal MRI reveals diverging structural and functional connectivity profiles across the TLE spectrum. Pathology-specific modulations of large-scale functional brain networks lend novel evidence for a close interplay of structural and functional disruptions in focal epilepsy. Ann Neurol 2016;80:142-153., (© 2016 American Neurological Association.)

Temporal lobe epilepsy (TLE) is the most frequent drug-resistant epilepsy in adults and commonly associated with variable degrees of mesiotemporal atrophy on magnetic resonance imaging (MRI). Analyses of inter-regional connectivity have unveiled disruptions in large-scale cortico-cortical networks; little is known about the topological organization of the mesiotemporal lobe, the limbic subnetwork central to the disorder. We generated covariance networks based on high-resolution MRI surface-shape descriptors of the hippocampus, entorhinal cortex, and amygdala in 134 TLE patients and 45 age- and sex-matched controls. Graph-theoretical analysis revealed increased path length and clustering in patients, suggesting a shift toward a more regularized arrangement; findings were reproducible after split-half assessment and across 2 parcellation schemes. Analysis of inter-regional correlations and module participation showed increased within-structure covariance, but decreases between structures, particularly with regards to the hippocampus and amygdala. While higher clustering possibly reflects topological consequences of axonal sprouting, decreases in interstructure covariance may be a consequence of disconnection within limbic circuitry. Preoperative network parameters, specifically the segregation of the ipsilateral hippocampus, predicted long-term seizure freedom after surgery., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Objectives: Our aim is to assess the subfield-specific histopathological correlates of hippocampal volume and intensity changes (T1, T2) as well as diff!usion MRI markers in TLE, and investigate the efficacy of quantitative MRI measures in predicting histopathology in vivo., Experimental Design: We correlated in vivo volumetry, T2 signal, quantitative T1 mapping, as well as diffusion MRI parameters with histological features of hippocampal sclerosis in a subfield-specific manner. We made use of on an advanced co-registration pipeline that provided a seamless integration of preoperative 3 T MRI with postoperative histopathological data, on which metrics of cell loss and gliosis were quantitatively assessed in CA1, CA2/3, and CA4/DG., Principal Observations: MRI volumes across all subfields were positively correlated with neuronal density and size. Higher T2 intensity related to increased GFAP fraction in CA1, while quantitative T1 and diffusion MRI parameters showed negative correlations with neuronal density in CA4 and DG. Multiple linear regression analysis revealed that in vivo multiparametric MRI can predict neuronal loss in all the analyzed subfields with up to 90% accuracy., Conclusion: Our results, based on an accurate co-registration pipeline and a subfield-specific analysis of MRI and histology, demonstrate the potential of MRI volumetry, diffusion, and quantitative T1 as accurate in vivo biomarkers of hippocampal pathology., (© 2015 Wiley Periodicals, Inc.)