Imaging structural and functional brain networks in temporal lobe epilepsy

Sensitivity to moral and conventional rules in temporal lobe epilepsy

OBJECTIVES

Sensitivity to moral and conventional rules (SMCR) is supported by bilateral brain networks and psychosocial input both of which may be altered in temporal lobe epilepsy (TLE). This study evaluated the components of SMCR in patients with TLE, aiming to clarify their preservation and link to psychopathological and cognitive aspects.

METHODS

Adult patients with unilateral TLE and healthy controls were evaluated using neuropsychological tests for SMCR, memory, language, and executive functions, the Empathy Questionnaire (EQ), and the Symptom Checklist-90-R (SCL-90-R).

RESULTS

The SMCR test items showed good reliability and validity, yielding the Severity and Rules factors distinct from the Executive, Lexical and Memory factors. Patients with right TLE scored worse in moral rules recognition than controls, but this difference was nullified by a significant influence for age and sex. The Severity and Rules factors related to semantic fluency and age and, respectively, TLE side and psychoticism. However, these factors did predict TLE membership.

CONCLUSIONS

In adult patients with TLE, the SMCR test reflects a distinct cognitive domain. Conventional rules are well-retained, while moral reasoning may be only affected in right TLE if unfavorable demographics coexist. Although age, TLE side, semantic abilities, and psychoticism cooperate to determine SMCR, impairment of such domain is not a distinctive feature of TLE.

Topological regularization of networks in temporal lobe epilepsy: a structural MRI study

Objective

Patients with temporal lobe epilepsy (TLE) often exhibit neurocognitive disorders; however, we still know very little about the pathogenesis of cognitive impairment in patients with TLE. Therefore, our aim is to detect changes in the structural connectivity networks (SCN) of patients with TLE.

Methods

Thirty-five patients with TLE were compared with 47 normal controls (NC) matched according to age, gender, handedness, and education level. All subjects underwent thin-slice T1WI scanning of the brain using a 3.0 T MRI. Then, a large-scale structural covariance network was constructed based on the gray matter volume extracted from the structural MRI. Graph theory was then used to determine the topological changes in the structural covariance network of TLE patients.

Results

Although small-world networks were retained, the structural covariance network of TLE patients exhibited topological irregularities in regular architecture as evidenced by an increase in the small world properties (p < 0.001), normalized clustering coefficient (p < 0.001), and a decrease in the transfer coefficient (p < 0.001) compared with the NC group. Locally, TLE patients showed a decrease in nodal betweenness and degree in the left lingual gyrus, right middle occipital gyrus and right thalamus compared with the NC group (p < 0.05, uncorrected). The degree of structural networks in both TLE (Temporal Lobe Epilepsy) and control groups was distributed exponentially in truncated power law. In addition, the stability of random faults in the structural covariance network of TLE patients was stronger (p = 0.01), but its fault tolerance was lower (p = 0.03).

Conclusion

The objective of this study is to investigate the potential neurobiological mechanisms associated with temporal lobe epilepsy through graph theoretical analysis, and to examine the topological characteristics and robustness of gray matter structural networks at the network level.

Edge-wise analysis reveals white matter connectivity associated with focal to bilateral tonic-clonic seizures

OBJECTIVE

Focal to bilateral tonic-clonic seizures (FBTCS) represent a challenging subtype of focal temporal lobe epilepsy (TLE) in terms of both severity and treatment response. Most studies have focused on regional brain analysis that is agnostic to the distribution of white matter (WM) pathways associated with a node. We implemented a more selective, edge-wise approach that allowed for identification of the individual connections unique to FBTCS.

METHODS

T1-weighted and diffusion-weighted images were obtained from 22 patients with solely focal seizures (FS), 43 FBTCS patients, and 65 age/sex-matched healthy participants (HPs), yielding streamline (STR) connectome matrices. We used diffusion tensor-derived STRs in an edge-wise approach to determine specific structural connectivity changes associated with seizure generalization in FBTCS compared to matched FS and HPs. Graph theory metrics were computed on both node- and edge-based connectivity matrices.

RESULTS

Edge-wise analyses demonstrated that all significantly abnormal cross-hemispheric connections belonged to the FBTCS group. Abnormal connections associated with FBTCS were mostly housed in the contralateral hemisphere, with graph metric values generally decreased compared to HPs. In FBTCS, the contralateral amygdala showed selective decreases in the structural connection pathways to the contralateral frontal lobe. Abnormal connections in TLE involved the amygdala, with the ipsilateral side showing increases and the contralateral decreases. All the FS findings indicated higher graph metrics for connections involving the ipsilateral amygdala. Data also showed that some FBTCS connectivity effects are moderated by aging, recent seizure frequency, and longer illness duration.

SIGNIFICANCE

Data showed that not all STR pathways are equally affected by the seizure propagation of FBTCS. We demonstrated two key biases, one indicating a large role for the amygdala in the propagation of seizures, the other pointing to the prominent role of cross-hemispheric and contralateral hemisphere connections in FBTCS. We demonstrated topographic reorganization in FBTCS, pointing to the specific WM tracts involved.

Optimal input reverberation and homeostatic self-organization toward the edge of synchronization

Transient or partial synchronization can be used to do computations, although a fully synchronized network is sometimes related to the onset of epileptic seizures. Here, we propose a homeostatic mechanism that is capable of maintaining a neuronal network at the edge of a synchronization transition, thereby avoiding the harmful consequences of a fully synchronized network. We model neurons by maps since they are dynamically richer than integrate-and-fire models and more computationally efficient than conductance-based approaches. We first describe the synchronization phase transition of a dense network of neurons with different tonic spiking frequencies coupled by gap junctions. We show that at the transition critical point, inputs optimally reverberate through the network activity through transient synchronization. Then, we introduce a local homeostatic dynamic in the synaptic coupling and show that it produces a robust self-organization toward the edge of this phase transition. We discuss the potential biological consequences of this self-organization process, such as its relation to the Brain Criticality hypothesis, its input processing capacity, and how its malfunction could lead to pathological synchronization and the onset of seizure-like activity.

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

The study of brain connectivity has been a cornerstone in understanding the complexities of neurological and psychiatric disorders. It has provided invaluable insights into the functional architecture of the brain and how it is perturbed in disorders. However, a persistent challenge has been achieving the proper spatial resolution, and developing computational algorithms to address biological questions at the multi-cellular level, a scale often referred to as the mesoscale. Historically, neuroimaging studies of brain connectivity have predominantly focused on the macroscale, providing insights into inter-regional brain connections but often falling short of resolving the intricacies of neural circuitry at the cellular or mesoscale level. This limitation has hindered our ability to fully comprehend the underlying mechanisms of neurological and psychiatric disorders and to develop targeted interventions. In light of this issue, our review manuscript seeks to bridge this critical gap by delving into the domain of mesoscale neuroimaging. We aim to provide a comprehensive overview of conditions affected by aberrant neural connections, image acquisition techniques, feature extraction, and data analysis methods that are specifically tailored to the mesoscale. We further delineate the potential of brain connectivity research to elucidate complex biological questions, with a particular focus on schizophrenia and epilepsy. This review encompasses topics such as dendritic spine quantification, single neuron morphology, and brain region connectivity. We aim to showcase the applicability and significance of mesoscale neuroimaging techniques in the field of neuroscience, highlighting their potential for gaining insights into the complexities of neurological and psychiatric disorders.

Connectome-Based Neurosurgery in Primary Intra-Axial Neoplasms: Beyond the Traditional Modular Conception of Brain Architecture for the Preservation of Major Neurological Domains and Higher-Order Cognitive Functions

Despite the therapeutical advancements in the surgical treatment of primary intra-axial neoplasms, which determined both a significative improvement in OS and QoL and a reduction in the incidence of surgery-induced major neurological deficits, nowadays patients continue to manifest subtle post-operative neurocognitive impairments, preventing them from a full reintegration back into social life and into the workforce. The birth of connectomics paved the way for a profound reappraisal of the traditional conception of brain architecture, in favour of a model based on large-scale structural and functional interactions of a complex mosaic of cortical areas organized in a fluid network interconnected by subcortical bundles. Thanks to these advancements, neurosurgery is facing a new era of connectome-based resections, in which the core principle is still represented by the achievement of an ideal onco-functional balance, but with a closer eye on whole-brain circuitry, which constitutes the foundations of both major neurological functions, to be intended as motricity; language and visuospatial function; and higher-order cognitive functions such as cognition, conation, emotion and adaptive behaviour. Indeed, the achievement of an ideal balance between the radicality of tumoral resection and the preservation, as far as possible, of the integrity of local and global brain networks stands as a mandatory goal to be fulfilled to allow patients to resume their previous life and to make neurosurgery tailored and gentler to their individual needs.

Altered functional connectivity after pilocarpine-induced seizures revealed by intrinsic optical signals imaging in awake mice

Significance

Comorbidities such as mood and cognitive disorders are often found in individuals with epilepsy after seizures. Cortex processes sensory, motor, and cognitive information. Brain circuit changes can be studied by observing functional network changes in epileptic mice's cortex.

Aim

The cortex is easily accessible for non-invasive brain imaging and electroencephalogram recording (EEG). However, the impact of seizures on cortical activity and functional connectivity has been rarely studied in vivo.

Approach

Intrinsic optical signal and EEG were used to monitor cortical activity in awake mice within 4 h after pilocarpine induction. It was divided into three periods according to the behavior and EEG of the mice: baseline, onset of seizures (onset, including seizures and resting in between seizure events), and after seizures (post, without seizures). Changes in cortical activity were compared between the baseline and after seizures.

Results

Hemoglobin levels increased significantly, particularly in the parietal association cortex (PT), retrosplenial cortex (RS), primary visual cortex (V1), and secondary visual cortex (V2). The network-wide functional connectivity changed post seizures, e.g., hypoconnectivity between PT and visual-associated cortex (e.g., V1 and V2). In contrast, connectivity between the motor-associated cortex and most other regions increased. In addition, the default mode network (DMN) also changed after seizures, with decreased connectivity between primary somatosensory region (SSp) and visual region (VIS), but increased connectivity involving anterior cingulate cortex (AC) and RS.

Conclusions

Our results provide references for understanding the mechanisms behind changes in brain circuits, which may explain the profound effects of seizures on comorbid health conditions.

Evolution of Stereo-Electroencephalography at Massachusetts General Hospital

The practice of invasive monitoring for presurgical epilepsy workup has evolved at Massachusetts General Hospital (MGH) in parallel to the evolution in the field's understanding of epilepsy as a network disorder. Implantations have shifted from an emphasis on singularly finding single foci for the purpose of resection to a network-hypothesis-driven approach aiming to delineate patients' seizure networks with the goal of developing surgical interventions that disrupt critical nodes of these networks. Here, the authors review all invasive monitoring cases at MGH from April 2016 through June 2023 to describe how this paradigm shift has taken form.

Identification of different MRI atrophy progression trajectories in epilepsy by subtype and stage inference

Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.

Leveraging the resting brain to predict memory decline after temporal lobectomy

OBJECTIVE

Predicting memory morbidity after temporal lobectomy in patients with temporal lobe epilepsy (TLE) relies on indices of preoperative temporal lobe structural and functional integrity. However, epilepsy is increasingly considered a network disorder, and memory a network phenomenon. We assessed the utility of functional network measures to predict postoperative memory changes.

METHODS

Seventy-two adults with TLE (37 left/35 right) underwent preoperative resting-state functional magnetic resonance imaging and pre- and postoperative neuropsychological assessment. We compared functional connectivity throughout the memory network of each patient to a healthy control template (n = 19) to identify differences in global organization. A second metric indicated the degree of integration of the to-be-resected temporal lobe with the rest of the memory network. We included these measures in a linear regression model alongside standard clinical variables as predictors of memory change after surgery.

RESULTS

Left TLE patients with more atypical memory networks, and with greater functional integration of the to-be-resected region with the rest of the memory network preoperatively, experienced the greatest decline in verbal memory after surgery. Together, these two measures explained 44% of variance in verbal memory change, outperforming standard clinical and demographic variables. None of the variables examined was associated with visuospatial memory change in patients with right TLE.

SIGNIFICANCE

Resting-state connectivity provides valuable information concerning both the integrity of to-be-resected tissue and functional reserve across memory-relevant regions outside of the to-be-resected tissue. Intrinsic functional connectivity has the potential to be useful for clinical decision-making regarding memory outcomes in left TLE, and more work is needed to identify the factors responsible for differences seen in right TLE.

Dendritic reorganization in the hippocampus, anterior temporal lobe, and frontal neocortex of lithium-pilocarpine induced Status Epilepticus (SE)

Status Epilepticus (SE) is a distributed network disorder, which involves the hippocampus and extra-hippocampal structures. Epileptogenesis in SE is tightly associated with neurogenesis, plastic changes and neural network reorganization facilitating hyper-excitability. On the other hand, dendritic spines are known to be the excitatory synapse in the brain. Therefore, dendritic spine dynamics could play an intricate role in these network alterations. However, the exact reason behind these structural changes in SE are elusive. In the present study, we have investigated the aforementioned hypothesis in the lithium-pilocarpine treated rat model of SE. We have examined cytoarchitectural and morphological changes using hematoxylin-eosin and Golgi-Cox staining in three different brain regions viz. CA1 pyramidal layer of the dorsal hippocampus, layer V pyramidal neurons of anterior temporal lobe (ATL), and frontal neocortex of the same animals. We observed macrostructural and layer-wise alteration of the pyramidal layer mainly in the hippocampus and ATL of SE rats, which is associated with sclerosis in the hippocampus. Sholl analysis exhibited partial dendritic plasticity in apical and basal dendrites of pyramidal cells as compared to the saline-treated weight-/age-matched control group. These findings indicate that region-specific alterations in dendritogenesis may contribute to the development of independent epileptogenic networks in the hippocampus, ATL, and frontal neocortex of SE rats.

SEEG-based reevaluation of epileptogenic networks and the predictive role for reoperation in MTLE patients with surgical failure

OBJECTIVE

Approximately 20%-30% of mesial temporal lobe epilepsy (MTLE) patients got unfavorable seizure control after surgery, and there was a discrepancy about the reasons for the surgical failure. The functional connectivity (FC) patterns obtained from stereo-electroencephalography (SEEG) reveal information about the dynamics of the epileptic brain and the added value of extracting information that was not identifiable in the SEEG data using FC analysis. This study aims to find out the patterns of the potential epileptogenic network of failure patients and the electrophysiological predictors of reoperation.

METHODS

From January 2012 to December 2019, the MTLE patients with surgical failure were reviewed, and all patients underwent SEEG-guided reoperation. The epileptogenic network was quantified by calculating FC indicators, including phase slope index (PSI), mutual information (MI) strength, imaginary coherence (icoh), and Granger causality.

RESULTS

Ten patients with 13 seizures were included in the analysis, and 7 of them achieved a favorable outcome after the SEEG-guided reoperation. The surgical zone (SZ) with a favorable prognosis showed greater outward information flow than the non-SZ, whereas the SZ with an unfavorable prognosis showed greater inward information flow. The recurrent patients with favorable prognosis had strong connectivity between the posterior hippocampus, temporal neocortex, and insula, whereas the patients with unfavorable prognosis showed strong functional connectivity between the insula and temporal-parietal-occipital junction. The power spectrum of patients with favorable prognosis was significantly lower than that of patients with unfavorable prognosis, especially showing a more oscillation power of low frequency.

SIGNIFICANCE

The SEEG-guided reoperation could achieve favorable seizure control outcomes for recurrent patients. The FCs were a potential indicator to help construct the temporal epileptic network and predictor for the reoperative prognosis in the recurrent patients.

Distinguishing Patients with MRI-Negative Temporal Lobe Epilepsy from Normal Controls Based on Individual Morphological Brain Network

Temporal Lobe Epilepsy (TLE) is the most common subtype of focal epilepsy and the most refractory to drug treatment. Roughly 30% of patients do not have easily identifiable structural abnormalities. In other words, MRI-negative TLE has normal MRI scans on visual inspection. Thus, MRI-negative TLE is a diagnostic and therapeutic challenge. In this study, we investigate the cortical morphological brain network to identify MRI-negative TLE. The 210 cortical ROIs based on the Brainnetome atlas were used to define the network nodes. The least absolute shrinkage and selection operator (LASSO) algorithm and Pearson correlation methods were used to calculate the inter-regional morphometric features vector correlation respectively. As a result, two types of networks were constructed. The topological characteristics of networks were calculated by graph theory. Then after, a two-stage feature selection strategy, including a two-sample t-test and support vector machine-based recursive feature elimination (SVM-RFE), was performed in feature selection. Finally, classification with support vector machine (SVM) and leave-one-out cross-validation (LOOCV) was employed for the training and evaluation of the classifiers. The performance of two constructed brain networks was compared in MRI-negative TLE classification. The results indicated that the LASSO algorithm achieved better performance than the Pearson pairwise correlation method. The LASSO algorithm provides a robust method of individual morphological network construction for distinguishing patients with MRI-negative TLE from normal controls.

Topological abnormality of structural covariance network in MRI-negative frontal lobe epilepsy

Background

Frontal lobe epilepsy (FLE) is the second most common type of focal epilepsy, however, imaging studies of FLE have been far less than Temporal lobe epilepsy (TLE) and the structural findings were not consistent in previous literature.

Object

Investigate the changes in cortical thickness in patients with FLE and the alteration of the structural covariance networks (SCNs) of cortical thickness with graph-theory.

Method

Thirty patients with FLE (18 males/12 females; 28.33 ± 11.81 years) and 27 demographically matched controls (15 males/12 females; 29.22 ± 9.73 years) were included in this study with high-resolution structural brain MRI scans. The cortical thickness was calculated, and structural covariance network (SCN) of cortical thickness were reconstructed using 68 × 68 matrix and analyzed with graph-theory approach.

Result

Cortical thickness was not significantly different between two groups, but path length and node betweenness were significantly increased in patients with FLE, and the regional network alterations were significantly changed in right precentral gyrus and right temporal pole (FDR corrected, p < 0.05). Comparing to HC group, network hubs were decreased and shifted away from frontal lobe.

Conclusion

The topological properties of cortical thickness covariance network were significantly altered in patients with FLE, even without obvious surface-based morphological damage. Graph-theory based SCN analysis may provide sensitive neuroanatomical biomarkers for FLE.

In vivo characterization of magnetic resonance imaging-based T1w/T2w ratios reveals myelin-related changes in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common type of intractable epilepsy in adults. Although brain myelination alterations have been observed in TLE, it remains unclear how the myelination network changes in TLE. This study developed a novel method in characterization of myelination structural covariance network (mSCN) by T1-weighted and T2-weighted magnetic resonance imaging (MRI). The mSCNs were estimated in 42 left TLE (LTLE), 42 right TLE (RTLE) patients, and 41 healthy controls (HCs). The topology of mSCN was analyzed by graph theory. Voxel-wise comparisons of myelination laterality were also examined among the three groups. Compared to HC, both patient groups showed decreased myelination in frontotemporal regions, amygdala, and thalamus; however, the LTLE showed lower myelination in left medial temporal regions than RTLE. Moreover, the LTLE exhibited decreased global efficiency compared with HC and more increased connections than RTLE. The laterality in putamen was differently altered between the two patient groups: higher laterality at posterior putamen in LTLE and higher laterality at anterior putamen in RTLE. The putamen may play a transfer station role in damage spreading induced by epileptic seizures from the hippocampus. This study provided a novel workflow by combination of T1-weighted and T2-weighted MRI to investigate in vivo the myelin-related microstructural feature in epileptic patients first time. Disconnections of mSCN implicate that TLE is a system disorder with widespread disruptions at regional and network levels.

Neurocysticercosis-related Seizures: Imaging Biomarkers

Neurocysticercosis (NCC)-a parasitic CNS infection endemic to developing nations-has been called the leading global cause of acquired epilepsy yet remains understudied. It is currently unknown why a large proportion of patients develop recurrent seizures, often following the presentation of acute seizures. Furthermore, the presentation of NCC is heterogenous and the features that predispose to the development of an epileptogenic state remain uncertain. Perilesional factors (such as oedema and gliosis) have been implicated in NCC-related ictogenesis, but the effects of cystic factors, including lesion load and location, seem not to play a role in the development of habitual epilepsy. In addition, the cytotoxic consequences of the cyst's degenerative stages are varied and the majority of research, relying on retrospective data, lacks the necessary specificity to distinguish between acute symptomatic and unprovoked seizures. Previous research has established that epileptogenesis can be the consequence of abnormal network connectivity, and some imaging studies have suggested that a causative link may exist between NCC and aberrant network organisation. In wider epilepsy research, network approaches have been widely adopted; studies benefiting predominantly from the rich, multimodal data provided by advanced MRI methods are at the forefront of the field. Quantitative MRI approaches have the potential to elucidate the lesser-understood epileptogenic mechanisms of NCC. This review will summarise the current understanding of the relationship between NCC and epilepsy, with a focus on MRI methodologies. In addition, network neuroscience approaches with putative value will be highlighted, drawing from current imaging trends in epilepsy research.

Study of brain network alternations in non-lesional epilepsy patients by BOLD-fMRI

Objective

To investigate the changes of brain network in epilepsy patients without intracranial lesions under resting conditions.

Methods

Twenty-six non-lesional epileptic patients and 42 normal controls were enrolled for BOLD-fMRI examination. The differences in brain network topological characteristics and functional network connectivity between the epilepsy group and the healthy controls were compared using graph theory analysis and independent component analysis.

Results

The area under the curve for local efficiency was significantly lower in the epilepsy patients compared with healthy controls, while there were no differences in global indicators. Patients with epilepsy had higher functional connectivity in 4 connected components than healthy controls (orbital superior frontal gyrus and medial superior frontal gyrus, medial superior frontal gyrus and angular gyrus, superior parietal gyrus and paracentral lobule, lingual gyrus, and thalamus). In addition, functional connectivity was enhanced in the default mode network, frontoparietal network, dorsal attention network, sensorimotor network, and auditory network in the epilepsy group.

Conclusion

The topological characteristics and functional connectivity of brain networks are changed in in non-lesional epilepsy patients. Abnormal functional connectivity may suggest reduced brain efficiency in epilepsy patients and also may be a compensatory response to brain function early at earlier stages of the disease.

Et tu, CA2: CA2 Is Hyperexcitable and Controls Seizures in a Mouse Model of Temporal Lobe Epilepsy

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[Structural brain changes in patients with temporal lobe epilepsy and comorbid depression]

OBJECTIVE

To assess the morphological features of the brain structures in patients with temporal lobe epilepsy and comorbid depression.

MATERIAL AND METHODS

From 1 January 2017 to 31 December 2020, we studied 80 patients with temporal lobe epilepsy (aged 18-60 years, 38 of whom had comorbid depression) and 48 healthy subjects of comparable age. Magnetic resonance imaging (MRI) of the brain was performed using the epilepsy protocol in a scanner with a magnetic field strength of 1.5 T. Focal temporal lobe epilepsy was diagnosed by neurologists (epileptologists) specialising in epilepsy according to the International League Against Epilepsy (ILAE) classification of epilepsy. Psychiatrists assessed the presence and severity of depressive disorders by clinical interview and by participants' scores on the Beck Depression Inventory (BDI-II). MRI data were processed using FreeSurfer 6.0 software to determine volumes of subcortical structures and thicknesses of cortical structures. At the group level, analysis of covariance with Holm-Bonferroni correction was used as the statistical method.

RESULTS

Morphometric analysis revealed a significant decrease in the volume of the thalamus bilaterally and the brain stem and an increase in the volume of the choroid plexus in the left hemisphere, as well as a significant decrease in the thickness of the entorhinal cortex, temporal pole and isthmus of the cingulate gyrus in the left hemisphere and middle temporal gyrus and inferior temporal gyrus in the right hemisphere in patients with epilepsy compared to healthy controls. No association was found between the presence of depression and significant structural changes on MRI.

CONCLUSION

The data obtained suggest an effect of temporal lobe epilepsy, but not comorbid depression, on the morphology of brain structures.

Interictal Functional Connectivity in Focal Refractory Epilepsies Investigated by Intracranial EEG

Introduction: Focal epilepsies are diseases of neuronal excitability affecting macroscopic networks of cortical and subcortical neural structures. These networks ("epileptogenic networks") can generate pathological electrophysiological activities during seizures, and also between seizures (interictal period). Many works attempt to describe these networks by using quantification methods, particularly based on the estimation of statistical relationships between signals produced by brain regions, namely functional connectivity (FC). Results: FC has been shown to be greatly altered during seizures and in the immediate peri-ictal period. An increasing number of studies have shown that FC is also altered during the interictal period depending on the degree of epileptogenicity of the structures. Furthermore, connectivity values could be correlated with other clinical variables including surgical outcome. Significance: This leads to a conceptual change and to consider epileptic areas as both hyperexcitable and abnormally connected. These data open the door to the use of interictal FC as a marker of epileptogenicity and as a complementary tool for predicting the effect of surgery. Aim: In this article, we review the available data concerning interictal FC estimated from intracranial electroencephalograhy (EEG) in focal epilepsies and discuss it in the light of data obtained from other modalities (EEG imaging) and modeling studies.

Wearable OPM-MEG: A changing landscape for epilepsy

Magnetoencephalography with optically pumped magnometers (OPM-MEG) is an emerging and novel, cost-effective wearable system that can simultaneously record neuronal activity with high temporal resolution ("when" neuronal activity occurs) and spatial resolution ("where" neuronal activity occurs). This paper will first outline recent methodological advances in OPM-MEG compared to conventional superconducting quantum interference device (SQUID)-MEG before discussing how OPM-MEG can become a valuable and noninvasive clinical support tool in epilepsy surgery evaluation. Although OPM-MEG and SQUID-MEG share similar data features, OPM-MEG is a wearable design that fits children and adults, and it is also robust to head motion within a magnetically shielded room. This means that OPM-MEG can potentially extend the application of MEG into the neurobiology of severe childhood epilepsies with intellectual disabilities (e.g., epileptic encephalopathies) without sedation. It is worth noting that most OPM-MEG sensors are heated, which may become an issue with large OPM sensor arrays (OPM-MEG currently has fewer sensors than SQUID-MEG). Future implementation of triaxial sensors may alleviate the need for large OPM sensor arrays. OPM-MEG designs allowing both awake and sleep recording are essential for potential long-term epilepsy monitoring.

Sleep medicine: Practice, challenges and new frontiers

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

Altered topological organization of resting-state functional networks in children with infantile spasms

Covering neuroimaging evidence has demonstrated that epileptic symptoms are associated with the disrupted topological architecture of the brain network. Infantile spasms (IS) as an age-specific epileptic encephalopathy also showed abnormal structural or functional connectivity in specific brain regions or specific networks. However, little is known about the topological alterations of whole-brain functional networks in patients with IS. To fill this gap, we used the graph theoretical analysis to investigate the topological properties (whole-brain small-world property and modular interaction) in 17 patients with IS and 34 age- and gender-matched healthy controls. The functional networks in both groups showed efficient small-world architecture over the sparsity range from 0.05 to 0.4. While patients with IS showed abnormal global properties characterized by significantly decreased normalized clustering coefficient, normalized path length, small-worldness, local efficiency, and significantly increased global efficiency, implying a shift toward a randomized network. Modular analysis revealed decreased intra-modular connectivity within the default mode network (DMN) and fronto-parietal network but increased inter-modular connectivity between the cingulo-opercular network and occipital network. Moreover, the decreased intra-modular connectivity in DMN was significantly negatively correlated with seizure frequency. The inter-modular connectivity between the cingulo-opercular and occipital network also showed a significant correlation with epilepsy frequency. Together, the current study revealed the disrupted topological organization of the whole-brain functional network, which greatly advances our understanding of neuronal architecture in IS and may contribute to predict the prognosis of IS as disease biomarkers.

High-Frequency Oscillations and Epileptogenic Network

Epilepsy is a network disease caused by aberrant neocortical large-scale connectivity spanning regions on the scale of several centimeters. High-frequency oscillations, characterized by the 80-600 Hz signals in electroencephalography, have been proven to be a promising biomarker of epilepsy that can be used in assessing the severity and susceptibility of epilepsy as well as the location of the epileptogenic zone. However, the presence of a high-frequency oscillation network remains a topic of debate as high-frequency oscillations have been previously thought to be incapable of propagation, and the relationship between high-frequency oscillations and the epileptogenic network has rarely been discussed. Some recent studies reported that high-frequency oscillations may behave like networks that are closely relevant to the epileptogenic network. Pathological highfrequency oscillations are network-driven phenomena and elucidate epileptogenic network development; high-frequency oscillations show different characteristics coincident with the epileptogenic network dynamics, and cross-frequency coupling between high-frequency oscillations and other signals may mediate the generation and propagation of abnormal discharges across the network.

De novo epilepsy after microsurgical resection of brain arteriovenous malformations

OBJECTIVE

Seizures are the second most common presenting symptom of brain arteriovenous malformations (bAVMs) after hemorrhage. Risk factors for preoperative seizures and subsequent seizure control outcomes have been well studied. There is a paucity of literature on postoperative, de novo seizures in initially seizure-naïve patients who undergo resection. Whereas this entity has been documented after craniotomy for a wide variety of neurosurgically treated pathologies including tumors, trauma, and aneurysms, de novo seizures after bAVM resection are poorly studied. Given the debilitating nature of epilepsy, the purpose of this study was to elucidate the incidence and risk factors associated with de novo epilepsy after bAVM resection.

METHODS

A retrospective review of patients who underwent resection of a bAVM over a 15-year period was performed. Patients who did not present with seizure were included, and the primary outcome was de novo epilepsy (i.e., a seizure disorder that only manifested after surgery). Demographic, clinical, and radiographic characteristics were compared between patients with and without postoperative epilepsy. Subgroup analysis was conducted on the ruptured bAVMs.

RESULTS

From a cohort of 198 patients who underwent resection of a bAVM during the study period, 111 supratentorial ruptured and unruptured bAVMs that did not present with seizure were included. Twenty-one patients (19%) developed de novo epilepsy. One-year cumulative rates of developing de novo epilepsy were 9% for the overall cohort and 8.5% for the cohort with ruptured bAVMs. There were no significant differences between the epilepsy and no-epilepsy groups overall; however, the de novo epilepsy group was younger in the cohort with ruptured bAVMs (28.7 ± 11.7 vs 35.1 ± 19.9 years; p = 0.04). The mean time between resection and first seizure was 26.0 ± 40.4 months, with the longest time being 14 years. Subgroup analysis of the ruptured and endovascular embolization cohorts did not reveal any significant differences. Of the patients who developed poorly controlled epilepsy (defined as Engel class III–IV), all had a history of hemorrhage and half had bAVMs located in the temporal lobe.

CONCLUSIONS

De novo epilepsy after bAVM resection occurs at an annual cumulative risk of 9%, with potentially long-term onset. Younger age may be a risk factor in patients who present with rupture. The development of poorly controlled epilepsy may be associated with temporal lobe location and a delay between hemorrhage and resection.

The Role of MRI in the Treatment of Drug-Resistant Focal Epilepsy

BACKGROUND

Epilepsy is a prevalent chronic condition affecting about 50 million people worldwide. A third of patients with focal epilepsy suffer from seizures unresponsive to medication. Uncontrolled seizures damage the brain, are associated with cognitive decline, and have negative impact on well-being. For these patients, the surgical resection of the brain region that gives rise to seizures is the most effective treatment.

SUMMARY

Magnetic resonance imaging (MRI) plays a central role in detecting epileptogenic brain lesions. In this review, we critically discuss advances in neuroimaging acquisition, analytical post-acquisition techniques, and machine leaning methods for the detection of epileptogenic lesions, prediction of clinical outcomes, and identification of disease subtypes.

KEY MESSAGE

MRI is a mandatory investigation for diagnosis and treatment of epilepsy, particularly when surgery is being considered. Continuous progress in imaging techniques, combined with machine learning, will continue to push the boundaries of lesion visibility and provide increasingly precise predictors of clinical outcomes. Current efforts aiming at strengthening the competences of epileptologists in neuroimaging will ultimately reduce the need for invasive diagnostics.

Brain structural connectivity sub typing in unilateral temporal lobe epilepsy

To categorize and clinically characterize subtypes of brain structural connectivity patterns in unilateral temporal lobe epilepsy (TLE). Voxel based morphometry (VBM) and surfaced based morphometry (SBM) analysis were used to detect brain structural alterations associated with TLE from MRI data. Principal component analysis (PCA) was performed to identify subtypes of brain structural connectivity patterns. Correlation analysis was used to explore associations between PC scores and clinical characteristics. A total of 59 patients with TLE and 100 healthy adults were included in this study. Widespread cortical atrophy was shown in both left and right TLE (P < 0.05, FWE corrected). Six principal components (PCs) that explained more than 70% of the variance were extracted for left and right TLE, reflecting patterns of brain structural connectivity. PCs representing perisylvian connectivity were positively correlated with verbal IQ (left TLE: r = 0.696, P < 0.001; right TLE: r = 0.484, P = 0.012) and total IQ (left TLE r = 0.608, P < 0.001) and negatively correlated with disease duration (r = -0.448, P = 0.009). In left TLE, the PC in the ipsilateral mesial temporal region was negatively correlated with age at onset (r = -0.382, P = 0.028). In right TLE, the PC representing the default mode network was negatively correlated with number of antiepileptic drugs (r = -0.407, P = 0.039). This study categorized subtypes of unilateral TLE based on brain structural connectivity patterns. Findings may provide insight into seizure pathways, the pathophysiology of epilepsy, including comorbidities such as cognitive impairment, and help predict treatment outcomes.

Mesial-Temporal Epileptic Ripples Correlate With Verbal Memory Impairment

Rationale

High frequency oscillations (HFO; ripples = 80–200, fast ripples 200–500 Hz) are promising epileptic biomarkers in patients with epilepsy. However, especially in temporal epilepsies differentiation of epileptic and physiological HFO activity still remains a challenge. Physiological sleep-spindle-ripple formations are known to play a role in slow-wave-sleep memory consolidation. This study aimed to find out if higher rates of mesial-temporal spindle-ripples correlate with good memory performance in epilepsy patients and if surgical removal of spindle-ripple-generating brain tissue correlates with a decline in memory performance. In contrast, we hypothesized that higher rates of overall ripples or ripples associated with interictal epileptic spikes correlate with poor memory performance.

Methods

Patients with epilepsy implanted with electrodes in mesial-temporal structures, neuropsychological memory testing and subsequent epilepsy surgery were included. Ripples and epileptic spikes were automatically detected in intracranial EEG and sleep-spindles in scalp EEG. The coupling of ripples to spindles was automatically analyzed. Mesial-temporal spindle-ripple rates in the speech-dominant-hemisphere (left in all patients) were correlated with verbal memory test results, whereas ripple rates in the non-speech-dominant hemisphere were correlated with non-verbal memory test performance, using Spearman correlation).

Results

Intracranial EEG and memory test results from 25 patients could be included. All ripple rates were significantly higher in seizure onset zone channels (p < 0.001). Patients with pre-surgical verbal memory impairment had significantly higher overall ripple rates in left mesial-temporal channels than patients with intact verbal memory (Mann–Whitney-U-Test: p = 0.039). Spearman correlations showed highly significant negative correlations of the pre-surgical verbal memory performance with left mesial-temporal spike associated ripples (r_s = −0.458; p = 0.007) and overall ripples (r_s = −0.475; p = 0.006). All three ripple types in right-sided mesial-temporal channels did not correlate with pre-surgical nonverbal memory. No correlation for the difference between post- and pre-surgical memory and pre-surgical spindle-ripple rates was seen in patients with left-sided temporal or mesial-temporal surgery.

Discussion

This study fails to establish a clear link between memory performance and spindle ripples. This highly suggests that spindle-ripples are only a small portion of physiological ripples contributing to memory performance. More importantly, this study indicates that spindle-ripples do not necessarily compromise the predictive value of ripples in patients with temporal epilepsy. The majority of ripples were clearly linked to areas with poor memory function.

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

Differences in Evolution of Epileptic Seizures and Topographical Distribution of Tissue Damage in Selected Limbic Structures Between Male and Female Rats Submitted to the Pilocarpine Model

Epidemiological evidence shows that clinical features and comorbidities in temporal lobe epilepsy (TLE) may have different manifestations depending on the sex of patients. However, little is known about how sex-related mechanisms can interfere with the processes underlying the epileptic phenomenon. The findings of this study show that male rats with epilepsy in the pilocarpine model have longer-lasting and more severe epileptic seizures, while female rats have a higher frequency of epileptic seizures and a greater number of seizure clusters. Significant sex-linked pathological changes were also observed: epileptic brains of male and female rats showed differences in mass reduction of 41.8% in the amygdala and 18.2% in the olfactory bulb, while loss of neuronal cells was present in the hippocampus (12.3%), amygdala (18.1%), and olfactory bulb (7.5%). Another important sex-related finding was the changes in non-neuronal cells with increments for the hippocampus (36.1%), amygdala (14.7%), and olfactory bulb (37%). Taken together, our study suggests that these neuropathological changes may underlie the differences in the clinical features of epileptic seizures observed in male and female rats.

Graph theoretical measures of fast ripples support the epileptic network hypothesis

The epileptic network hypothesis and epileptogenic zone hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The epileptogenic zone hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations, and particularly fast ripples, are thought to be biomarkers of the epileptogenic zone. We sought to test these theories by comparing high-frequency oscillation rates and networks in surgical responders and non-responders, with no appreciable change in seizure frequency or severity, within a retrospective cohort of 48 patients implanted with stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye movement sleep and semi-automatically detected and quantified high-frequency oscillations. Each electrode contact was localized in normalized coordinates. We found that the accuracy of seizure onset zone electrode contact classification using high-frequency oscillation rates was not significantly different in surgical responders and non-responders, suggesting that in non-responders the epileptogenic zone partially encompassed the seizure onset zone(s) (P > 0.05). We also found that in the responders, fast ripple on oscillations exhibited a higher spectral content in the seizure onset zone compared with the non-seizure onset zone (P < 1 × 10⁻⁵). By contrast, in the non-responders, fast ripple had a lower spectral content in the seizure onset zone (P < 1 × 10⁻⁵). We constructed two different networks of fast ripple with a spectral content >350 Hz. The first was a rate–distance network that multiplied the Euclidian distance between fast ripple-generating contacts by the average rate of fast ripple in the two contacts. The radius of the rate–distance network, which excluded seizure onset zone nodes, discriminated non-responders, including patients not offered resection or responsive neurostimulation due to diffuse multifocal onsets, with an accuracy of 0.77 [95% confidence interval (CI) 0.56–0.98]. The second fast ripple network was constructed using the mutual information between the timing of the events to measure functional connectivity. For most non-responders, this network had a longer characteristic path length, lower mean local efficiency in the non-seizure onset zone, and a higher nodal strength among non-seizure onset zone nodes relative to seizure onset zone nodes. The graphical theoretical measures from the rate–distance and mutual information networks of 22 non- responsive neurostimulation treated patients was used to train a support vector machine, which when tested on 13 distinct patients classified non-responders with an accuracy of 0.92 (95% CI 0.75–1). These results indicate patients who do not respond to surgery or those not selected for resection or responsive neurostimulation can be explained by the epileptic network hypothesis that is a decentralized network consisting of widely distributed, hyperexcitable fast ripple-generating nodes.

High b-value diffusion tractography: Abnormal axonal network organization associated with medication-refractory epilepsy

Diffusion magnetic resonance imaging (dMRI) tractography has played a critical role in characterizing patterns of aberrant brain network reorganization among patients with epilepsy. However, the accuracy of dMRI tractography is hampered by the complex biophysical properties of white matter tissue. High b-value diffusion imaging overcomes this limitation by better isolating axonal pathways. In this study, we introduce tractography derived from fiber ball imaging (FBI), a high b-value approach which excludes non-axonal signals, to identify atypical neuronal networks in patients with epilepsy. Specifically, we compared network properties obtained from multiple diffusion tractography approaches (diffusion tensor imaging, diffusion kurtosis imaging, FBI) in order to assess the pathophysiological relevance of network rearrangement in medication-responsive vs. medication-refractory adults with focal epilepsy. We show that drug-resistant epilepsy is associated with increased global network segregation detected by FBI-based tractography. We propose exploring FBI as a clinically feasible alternative to quantify topological changes that could be used to track disease progression and inform on clinical outcomes.

Imaging visuospatial memory in temporal lobe epilepsy—Results of an fMRI study

Purpose

Impairment of cognitive functions is commonly observed in temporal lobe epilepsy (TLE). The aim of this study was to assess visuospatial memory functions and memory-related networks using an adapted version of Roland’s Hometown Walking (RHWT) functional MRI (fMRI) task in patients with TLE.

Methods

We used fMRI to study activation patterns based on a visuospatial memory paradigm in 32 TLE patients (9 right; 23 left) and also within subgroups of lesional and non-lesional TLE. To test for performance, a correlational analysis of fMRI activation patterns and out-of-scanner neuropsychological visuospatial memory testing was performed. Additionally, we assessed memory-related networks using functional connectivity (FC).

Results

Greater contralateral than ipsilateral mesiotemporal (parahippocampal gyrus/hippocampus) activation was observed in left (n = 23)/right (n = 9) TLE. In lesional left TLE (n = 17), significant activations were seen in right more than left mesiotemporal areas (parahippocampal gyrus), while non-lesional left TLE patients (n = 6) showed significant bilateral (left>right) activations in mesiotemporal structures (parahippocampal gyrus). In left TLE, visuospatial cognitive testing correlated with fMRI activations in left (parahippocampal gyrus) and right mesiotemporal structures (hippocampus), characterized by greater fMRI activation being associated with better memory scores. In right TLE, higher scores in visuospatial memory testing were associated with greater fMRI activations in left and right insular regions. FC patterns of memory-related networks differ in right and left TLE.

Conclusion

While TLE in general leads to asymmetrical mesiotemporal activation, lesion-induced and non-lesional TLE patients reveal different memory fMRI activation patterns. In right TLE, insular regions try to compensate for impaired right mesiotemporal structures during the performance of visuospatial tasks. Underlying functional visuospatial memory networks differ in right and left TLE.

Multimodal connectome biomarkers of cognitive and affective dysfunction in the common epilepsies

Epilepsy is one of the most common chronic neurological conditions, traditionally defined as a disorder of recurrent seizures. Cognitive and affective dysfunction are increasingly recognized as core disease dimensions and can affect patient well-being, sometimes more than the seizures themselves. Connectome-based approaches hold immense promise for revealing mechanisms that contribute to dysfunction and to identify biomarkers. Our review discusses emerging multimodal neuroimaging and connectomics studies that highlight network substrates of cognitive/affective dysfunction in the common epilepsies. We first discuss work in drug-resistant epilepsy syndromes, that is, temporal lobe epilepsy, related to mesiotemporal sclerosis (TLE), and extratemporal epilepsy (ETE), related to malformations of cortical development. While these are traditionally conceptualized as ‘focal’ epilepsies, many patients present with broad structural and functional anomalies. Moreover, the extent of distributed changes contributes to difficulties in multiple cognitive domains as well as affective-behavioral challenges. We also review work in idiopathic generalized epilepsy (IGE), a subset of generalized epilepsy syndromes that involve subcortico-cortical circuits. Overall, neuroimaging and network neuroscience studies point to both shared and syndrome-specific connectome signatures of dysfunction across TLE, ETE, and IGE. Lastly, we point to current gaps in the literature and formulate recommendations for future research.

Epilepsy is increasingly recognized as a network disorder characterized by recurrent seizures as well as broad-ranging cognitive difficulties and affective dysfunction. Our manuscript reviews recent literature highlighting brain network substrates of cognitive and affective dysfunction in common epilepsy syndromes, namely temporal lobe epilepsy secondary to mesiotemporal sclerosis, extratemporal epilepsy secondary to malformations of cortical development, and idiopathic generalized epilepsy syndromes arising from subcortico-cortical pathophysiology. We discuss prior work that has indicated both shared and distinct brain network signatures of cognitive and affective dysfunction across the epilepsy spectrum, improves our knowledge of structure-function links and interindividual heterogeneity, and ultimately aids screening and monitoring of therapeutic strategies.

Abnormal Static and Dynamic Functional Connectivity in Left and Right Temporal Lobe Epilepsy

Objective

Temporal lobe epilepsy (TLE) can be conceptualized as a network disease. However, the network characteristics in lateralization remain controversial.

Methods

In this study, resting-state functional MRI scans were acquired from 53 TLE patients [22 with left-side TLE (LTLE) and 31 with right-side TLE (RTLE)] and 37 matched healthy controls. We focused on the characteristics of static and dynamic functional connectivity, including static connectivity patterns and topological properties, as well as temporal properties of the dynamic connectivity state and the variability of the dynamic connectivity and network topological organization. Correlation analyses were conducted between abnormal static and dynamic properties and cognitive performances.

Results

The static functional connectivity analysis presented a significantly decreased cortical-cortical connectivity pattern and increased subcortical-cortical connectivity pattern in RTLE. The global-level network in RTLE showed a significant decrease in global efficiency. The dynamic functional connectivity analysis revealed that RTLE patients exhibited aberrant connectivity states, as well as increased variability in the subcortical-cortical connectivity. The global-level network in RTLE revealed increased variance in global efficiency and local efficiency. The static or dynamic functional connectivity in LTLE did not show any significant abnormalities. The altered dynamic properties were associated with worsening cognitive performance in language and conceptual thinking by the TLE patients.

Conclusion

Our findings demonstrated the presence of abnormalities in the static and dynamic functional connectivity of TLE patients. RTLE patients exhibited more pronounced aberrant connectivity patterns and topological properties, which might represent a mechanism for reconfiguration of brain networks in RTLE patients. These observations extended our understanding of the pathophysiological network mechanisms of TLE.

Hippocampal injury in patients with status epilepticus: Quantitative analysis of hippocampal volume and structural co-variance network

OBJECTIVE

This study aimed to evaluate the differences in hippocampal structural volumes and intra-hippocampal networks between patients with status epilepticus (SE) and healthy controls.

METHODS

We enrolled 45 patients with SE and 35 age- and sex-matched healthy controls. We excluded patients with active structural lesions, which could be a direct cause of SE, but included patients with co-existing lesions. Co-existing lesions were defined as any lesions possibly related to the occurrence of SE, including encephalomalacia, cavernous malformation, dural arteriovenous fistula, and normal pressure hydrocephalus, etc. We divided 45 patients into those with co-existing lesions (n = 21) and those without co-existing lesions (n = 24). We conducted a volumetric analysis using FreeSurfer (version 7), and the intra-hippocampal structural co-variance network was analyzed with a graph theoretical analysis based on the structural volumes of the hippocampal subfields.

RESULTS

The structural volumes and intra-hippocampal structural co-variance networks were not different between patients with and without co-existing lesions. However, both structural volumes and intra-hippocampal structural co-variance networks were significantly different in patients with SE compared to healthy controls, and the ratio of the volume difference: [(volume of controls-volume of patients)/volume of controls] was highest in the left hippocampus (0.195), left amygdala (0.143), left thalamus (0.126), and right cortex (0.084). In addition, the global connectivity measurements including radius, diameter, eccentricity, and assortativity were significantly increased, and the small-worldness index was significantly decreased in patients with SE. Notably, structural volumes were negatively related to age but not to the duration of SE.

SIGNIFICANCE

Our study revealed significant alterations in structural volumes and intra-hippocampal structural co-variance networks in patients with SE compared to healthy controls, even though hippocampal atrophy was not evident on visual analysis; this is likely due to the direct effect of SE itself.

Neurobehavioural comorbidities of epilepsy: towards a network-based precision taxonomy

Cognitive and behavioural comorbidities are prevalent in childhood and adult epilepsies and impose a substantial human and economic burden. Over the past century, the classic approach to understanding the aetiology and course of these comorbidities has been through the prism of the medical taxonomy of epilepsy, including its causes, course, characteristics and syndromes. Although this 'lesion model' has long served as the organizing paradigm for the field, substantial challenges to this model have accumulated from diverse sources, including neuroimaging, neuropathology, neuropsychology and network science. Advances in patient stratification and phenotyping point towards a new taxonomy for the cognitive and behavioural comorbidities of epilepsy, which reflects the heterogeneity of their clinical presentation and raises the possibility of a precision medicine approach. As we discuss in this Review, these advances are informing the development of a revised aetiological paradigm that incorporates sophisticated neurobiological measures, genomics, comorbid disease, diversity and adversity, and resilience factors. We describe modifiable risk factors that could guide early identification, treatment and, ultimately, prevention of cognitive and broader neurobehavioural comorbidities in epilepsy and propose a road map to guide future research.

Clinical phenotype modulates brain's myelin and iron content in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is associated with brain pathology extending beyond temporal lobe structures. We sought to look for informative patterns of brain tissue properties in TLE that go beyond the established morphometry differences. We hypothesised that volume differences, particularly in hippocampus, will be paralleled by changes in brain microstructure. The cross-sectional study included TLE patients (n = 25) from a primary care center and sex-/age-matched healthy controls (n = 55). We acquired quantitative relaxometry-based magnetic resonance imaging (MRI) data yielding whole-brain maps of grey matter volume, magnetization transfer (MT) saturation, and effective transverse relaxation rate R2* indicative for brain tissue myelin and iron content. For statistical analysis, we used the computational anatomy framework of voxel-based morphometry and voxel-based quantification. There was a positive correlation between seizure activity and MT saturation measures in the ipsilateral hippocampus, paralleled by volume differences bilaterally. Disease duration correlated positively with iron content in the mesial temporal lobe, while seizure freedom was associated with a decrease of iron in the very same region. Our findings demonstrate the link between TLE clinical phenotype and brain anatomy beyond morphometry differences to show the impact of disease burden on specific tissue properties. We provide direct evidence for the differential effect of clinical phenotype characteristics on processes involving tissue myelin and iron in mesial temporal lobe structures. This study offers a proof-of-concept for the investigation of novel imaging biomarkers in focal epilepsy.

Resting-State MEG Source Space Network Metrics Associated with the Duration of Temporal Lobe Epilepsy

To evaluate the relationship between the network metrics of 68 brain regions and duration of temporal lobe epilepsy (TLE). Magnetoencephalography (MEG) data from 53 patients with TLE (28 left TLE, 25 right TLE) were recorded between seizures at resting state and analyzed in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and lower gamma (30-48 Hz). Three local network metrics, betweenness centrality, nodal degree, and nodal efficiency, were chosen to analyze the functional brain network. In Left, Right, and All (Left + Right) TLE groups, different metrics provide significant positive or negative correlations with the duration of TLE, in different frequency bands, and in different brain regions. In the Left TLE group, significant correlation between TLE duration and metric exists in the delta, beta, or lower gamma band, with network betweenness centrality, nodal degree, or nodal efficiency, in left caudal middle frontal, left middle temporal, or left supramarginal. In the Right TLE group, significant correlation exists in lower gamma or delta band, with nodal degree, or nodal efficiency, in left precuneus or right temporal pole. In the All TLE group, the significant correlation exists in delta, theta, beta, or lower gamma band, with nodal degree, or betweenness centrality, in either left or right hemisphere. Network metrics for some specific brain regions changed in patients with TLE as the duration of their TLE increased. Further researching these changes may be important for studying the pathogenesis, presurgical evaluation, and clinical treatment of long-term TLE.

Emotion recognition and theory of mind after temporal lobe epilepsy surgery: A systematic review

In order to navigate in our complex social world successfully, it is crucial to maintain and practice cognitive skills that are dedicated to adaptive social functioning. Emerging evidence suggests that besides deficits in declarative memory, executive functions, and language, impairments in social cognition (SC, e.g., emotion recognition, theory of mind) are also present in temporal lobe epilepsy (TLE). The organic and psycho-social consequences of epilepsy surgery might have additional implications regarding this deficit. Here we qualitatively synthesize longitudinal and cross-sectional findings on SC after TLE surgery. A literature search using PubMed and Scopus identified 275 potential articles. Studies were eligible if they (1) included patients with a diagnosis of TLE, (2) included a healthy comparison group, (3) reported original research, (4) were published in peer-reviewed journals and in English language, (5) reported the intervention of epilepsy surgery. Articles that (1) were case studies, (2) did not focus on SC abilities, (3) used interviews or self-report questionnaires to examine SC functions were excluded. A total of 16 original studies assessing emotion recognition (ER) and/or theory of mind (ToM) matched our criteria. The literature suggests that neither ER nor ToM abilities change after surgery: post-surgery patients show similar impairment patterns to pre-surgery patients. Nevertheless, individual improvement or decline could be masked by group comparisons and results should be considered in light of methodological heterogeneity among studies.

Patient-Specific Network Connectivity Combined With a Next Generation Neural Mass Model to Test Clinical Hypothesis of Seizure Propagation

Dynamics underlying epileptic seizures span multiple scales in space and time, therefore, understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. In this view, mathematical models have been developed, ranging from single neuron to neural population. In this study, we consider a neural mass model able to exactly reproduce the dynamics of heterogeneous spiking neural networks. We combine mathematical modeling with structural information from non invasive brain imaging, thus building large-scale brain network models to explore emergent dynamics and test the clinical hypothesis. We provide a comprehensive study on the effect of external drives on neuronal networks exhibiting multistability, in order to investigate the role played by the neuroanatomical connectivity matrices in shaping the emergent dynamics. In particular, we systematically investigate the conditions under which the network displays a transition from a low activity regime to a high activity state, which we identify with a seizure-like event. This approach allows us to study the biophysical parameters and variables leading to multiple recruitment events at the network level. We further exploit topological network measures in order to explain the differences and the analogies among the subjects and their brain regions, in showing recruitment events at different parameter values. We demonstrate, along with the example of diffusion-weighted magnetic resonance imaging (dMRI) connectomes of 20 healthy subjects and 15 epileptic patients, that individual variations in structural connectivity, when linked with mathematical dynamic models, have the capacity to explain changes in spatiotemporal organization of brain dynamics, as observed in network-based brain disorders. In particular, for epileptic patients, by means of the integration of the clinical hypotheses on the epileptogenic zone (EZ), i.e., the local network where highly synchronous seizures originate, we have identified the sequence of recruitment events and discussed their links with the topological properties of the specific connectomes. The predictions made on the basis of the implemented set of exact mean-field equations turn out to be in line with the clinical pre-surgical evaluation on recruited secondary networks.

Incorporation of quantitative MRI in a model to predict temporal lobe epilepsy surgery outcome

Quantitative volumetric brain MRI measurement is important in research applications, but translating it into patient care is challenging. We explore the incorporation of clinical automated quantitative MRI measurements in statistical models predicting outcomes of surgery for temporal lobe epilepsy. Four hundred and thirty-five patients with drug-resistant epilepsy who underwent temporal lobe surgery at Cleveland Clinic, Mayo Clinic and University of Campinas were studied. We obtained volumetric measurements from the pre-operative T1-weighted MRI using NeuroQuant, a Food and Drug Administration approved software package. We created sets of statistical models to predict the probability of complete seizure-freedom or an Engel score of I at the last follow-up. The cohort was randomly split into training and testing sets, with a ratio of 7:3. Model discrimination was assessed using the concordance statistic (C-statistic). We compared four sets of models and selected the one with the highest concordance index. Volumetric differences in pre-surgical MRI located predominantly in the frontocentral and temporal regions were associated with poorer outcomes. The addition of volumetric measurements to the model with clinical variables alone increased the model’s C-statistic from 0.58 to 0.70 (right-sided surgery) and from 0.61 to 0.66 (left-sided surgery) for complete seizure freedom and from 0.62 to 0.67 (right-sided surgery) and from 0.68 to 0.73 (left-sided surgery) for an Engel I outcome score. 57% of patients with extra-temporal abnormalities were seizure-free at last follow-up, compared to 68% of those with no such abnormalities (P-value = 0.02). Adding quantitative MRI data increases the performance of a model developed to predict post-operative seizure outcomes. The distribution of the regions of interest included in the final model supports the notion that focal epilepsies are network disorders and that subtle cortical volume loss outside the surgical site influences seizure outcome.

Atypical age-related changes in the structure of the mentalizing network in children with refractory focal epilepsy

Refractory focal epilepsy (rFE) is commonly comorbid with impaired social functioning, which significantly reduces quality of life. Previous research has identified a mentalizing network in the brain-composed of the anterior temporal cortex, medial prefrontal cortex (mPFC), posterior temporal sulcus (pSTS), and temporoparietal junction-that is thought to play a critical role in social cognition. In typically-developing (TD) youth, this network undergoes a protracted developmental process with cortical thinning and white matter expansion occurring across adolescence. Because epilepsy is associated with both social dysfunction and irregular neural development, we investigated whether gray and white matter in the mentalizing network differed between youth with rFE (n = 22) and TD youth (n = 41) aged 8-21 years. Older age was associated with reduced cortical thickness in the bilateral mPFC in TD youth, but not in rFE youth. Compared to TD youth, rFE youth had greater white matter density in the right pSTS. Our findings suggest that rFE youth show atypical patterns of cortical thickness and white matter density in regions of the brain that are typically associated with social information processing, potentially as a result of ongoing seizures, comorbid conditions, or other illness-related factors. These results encourage future research to examine whether such variations in neural structure are predictive of specific social deficits in rFE youth.

Temporal lobe epilepsy alters neural responses to human and avatar facial expressions in the face perception network

BACKGROUND AND OBJECTIVE

Although avatars are now widely used in advertisement, entertainment, and business today, no study has investigated whether brain lesions in neurological patients interfere with brain activation in response to dynamic avatar facial expressions. The aim of our event-related fMRI study was to compare brain activation differences in people with epilepsy and controls during the processing of fearful and neutral dynamic expressions displayed by human or avatar faces.

METHODS

Using functional magnetic resonance imaging (fMRI), we examined brain responses to dynamic facial expressions of trained actors and their avatar look-alikes in 16 people with temporal lobe epilepsy (TLE) and 26 controls. The actors' fearful and neutral expressions were recorded on video and conveyed onto their avatar look-alikes by face tracking.

RESULTS

Our fMRI results show that people with TLE exhibited reduced response differences between fearful and neutral expressions displayed by humans in the right amygdala and the left superior temporal sulcus (STS). Further, TLE was associated with reduced response differences between human and avatar fearful expressions in the dorsal pathway of the face perception network (STS and inferior frontal gyrus) as well as in the medial prefrontal cortex.

CONCLUSIONS

Taken together, these findings suggest that brain responses to dynamic facial expressions are altered in people with TLE compared to neurologically healthy individuals-regardless of whether the face is human or computer-generated. In TLE, areas sensitive to dynamic facial features and associated with processes relating to the self and others are particularly affected when processing dynamic human and avatar expressions. Our findings highlight that the impact of TLE on facial emotion processing must be extended to artificial faces and should be considered when applying dynamic avatars in the context of neurological conditions.

Alterations of the structural covariance network in the hypothalamus of patients with cluster headache

OBJECTIVE

The hypothalamus is one of the key structures involved in the pathophysiology of cluster headaches. This study aimed to analyze the volume of hypothalamic subunits and structural covariance networks in the hypothalamus of patients with cluster headache.

METHODS

We retrospectively enrolled 18 patients with episodic cluster headache and 18 age- and sex-matched healthy controls. We calculated individual structural volumes in ten hypothalamic subunits using three-dimensional T1-weighted imaging and the FreeSurfer program, which conducted an automated segmentation based on deep convolutional neural networks. We also performed an analysis of the structural covariance network in the hypothalamus using graph theory and the BRAPH program. We compared the volumes of hypothalamic subunits and structural covariance networks in the hypothalamus of patients with cluster headache versus those of healthy controls.

RESULTS

There were no significant differences in the structural volumes of the whole hypothalamus and hypothalamic subunits between patients with cluster headache and healthy controls. However, patients with cluster headache had significant alterations of the structural covariance network in the hypothalamus compared to that of healthy controls. The network measure of small-worldness index in patients with cluster headache was lower than that in healthy controls (0.844 vs. 0.955, p = 0.004).

CONCLUSION

We demonstrated a significant difference in the structural covariance network in the hypothalamus of patients with cluster headache versus those of healthy controls. These findings could be related to the pathogenesis of cluster headache.

Creatine attenuates seizure severity, anxiety and depressive-like behaviors in pentylenetetrazole kindled mice

Epilepsy has been associated with several behavioral changes such as depression and anxiety while some antiepileptic drugs can precipitate psychiatric conditions in patients. This study evaluated the ameliorative effect of creatine on seizure severity and behavioral changes in pentylenetetrazole (PTZ) kindled mice. Mice were kindled by administering sub-convulsive doses of PTZ (35 mg/kg i.p.) at interval of 48 h. The naïve group (n = 7) constituted group 1, while successfully kindled mice were randomly assigned to five groups (n = 7). Group II served as vehicle treated group; groups III-V were treated with creatine 75, 150, and 300 mg/kg/day, p.o; Group V was given 25 mg/kg/day of phenytoin p.o. The treatment was for 15 consecutive days. The intensity of convulsion was scored according to a seven-point scale ranging from stage 0-7. Tail suspension test (TST) and Elevated plus maze (EPM) were utilized to assess depression and anxiety-like behavior respectively. After behavioral evaluation on day 15th, their brain was isolated and assayed for catalase, superoxide dismutase, reduced glutathione, and malondialdehyde. There was a significant (p < 0.05) reduction in the seizure scores, anxiety and depression-like behaviors in mice from the 5th day of treatment. The antioxidant assays revealed significant (p < 0.05) increase in catalase and reduced glutathione, and significant (p < 0.05) reduction in lipid peroxidation in treated mice. This study provides evidence for the seizure reducing property of creatine and its ameliorating potential on anxiety and depressive-like behaviors that follows seizure episodes.

Effective connectivity among the hippocampus, amygdala, and temporal neocortex in epilepsy patients: A cortico-cortical evoked potential study

OBJECTIVE

Mesial temporal lobe epilepsy (MTLE) is one of the most common types of intractable epilepsy. The hippocampus and amygdala are two crucial structures of the mesial temporal lobe and play important roles in the epileptogenic network of MTLE. This study aimed to explore the effective connectivity among the hippocampus, amygdala, and temporal neocortex and to determine whether differences in effective connectivity exist between MTLE patients and non-MTLE patients.

METHODS

This study recruited 20 patients from a large cohort of drug-resistant epilepsy patients, of whom 14 were MTLE patients. Single-pulse electrical stimulation (SPES) was performed to acquire cortico-cortical evoked potentials (CCEPs). The root mean square (RMS) was used as the metric of the magnitude of CCEP to represent the effective connectivity. We then conducted paired and independent sample t-tests to assess the directionality of the effective connectivity.

RESULTS

In both MTLE patients and non-MTLE patients, the directional connectivity from the amygdala to the hippocampus was stronger than that from the hippocampus to the amygdala (P < 0.01); the outward connectivity from the amygdala to the cortex was stronger than the inward connectivity from the cortex to the amygdala (P < 0.01); the amygdala had stronger connectivity to the neocortex than the hippocampus (P < 0.01). In MTLE patients, the neocortex had stronger connectivity to the hippocampus than to the amygdala (P < 0.01). No significant differences in directional connectivity were noted between the two groups.

CONCLUSIONS

A unique effective connectivity pattern among the hippocampus, amygdala, and temporal neocortex was identified through CCEPs analysis. This study may aid in our understanding of physiological and pathological networks in the brain and inspire neurostimulation protocols for neurological and psychiatric disorders.

Effective connectivity alteration according to recurrence in transient global amnesia

PURPOSE

This study aimed to evaluate alterations in structural covariance network and effective connectivity of the intrahippocampal circuit in patients with transient global amnesia (TGA). We also investigated whether there were differences of them according to recurrence.

METHODS

We enrolled 88 patients with TGA and 50 healthy controls. We classified patients with TGA into two groups: the single event group (N = 77) and recurrent events group (N = 11). We performed volumetric analysis using the FreeSurfer program and structural covariance network analysis based on the structural volumes using a graph theoretical analysis in patients with TGA and healthy controls. The effective connectivity of the intrahippocampal circuit was also evaluated using structural equation modeling.

RESULTS

There were no significant differences between patients with all TGA events/a single TGA event and healthy controls with regard to global structural covariance network. However, patients with recurrent events had significant alterations in global structural covariance network with a decrease in the small-worldness index (0.907 vs. 0.970, p = 0.032). In patients with all events/a single, there were alterations in effective connectivity from the entorhinal cortex to CA4, only. However, in patients with recurrent events, there were alterations in effective connectivity from the subiculum to the fimbria as well as from the entorhinal cortex to CA4 in bilateral hemispheres.

CONCLUSION

Our study revealed significant alterations in structural covariance network and disruption of the intrahippocampal circuit in patients with TGA compared to healthy controls, which is more prominent when amnestic events recurred. It could be related to the pathogenesis of TGA.

5-HT/GABA interaction in epilepsy

Epilepsy is a neurological condition characterized by synchronous neuronal oscillations (seizures) in the electroencephalogram. Seizures are classified in focal or generalized (depending on the brain territory interested during seizures), and in convulsive and/or not convulsive (depending on the presence or not of involuntary movements). The current pharmacological treatments are mainly based on GABA modulation although different neurotransmitters are also involved in epilepsy, including serotonin. However despite much extensive progress in the understanding of epilepsy mechanisms, still, a percentage of people with epilepsy are pharmaco-resistant calling for the need for new therapeutic targets. Here we review preclinical and human evidence showing that serotonin modulates epilepsy that this likely happens via a major modulation/interaction with GABA.