Characterizing Frontal Lobe Seizure Semiology in Children.

OBJECTIVE: The objective was to analyze seizure semiology in pediatric frontal lobe epilepsy patients, considering age, to localize the seizure onset zone for surgical resection in focal epilepsy. METHODS: Fifty patients were identified retrospectively, who achieved seizure freedom after frontal lobe resective surgery at Great Ormond Street Hospital. Video-electroencephalography recordings of preoperative ictal seizure semiology were analyzed, stratifying the data based on resection region (mesial or lateral frontal lobe) and age at surgery (≤4 vs >4). RESULTS: Pediatric frontal lobe epilepsy is characterized by frequent, short, complex seizures, similar to adult cohorts. Children with mesial onset had higher occurrence of head deviation (either direction: 55.6% vs 17.4%; p = 0.02) and contralateral head deviation (22.2% vs 0.0%; p = 0.03), ictal body-turning (55.6% vs 13.0%; p = 0.006; ipsilateral: 55.6% vs 4.3%; p = 0.0003), and complex motor signs (88.9% vs 56.5%; p = 0.037). Both age groups (≤4 and >4 years) showed hyperkinetic features (21.1% vs 32.1%), contrary to previous reports. The very young group showed more myoclonic (36.8% vs 3.6%; p = 0.005) and hypomotor features (31.6% vs 0.0%; p = 0.003), and fewer behavioral features (36.8% vs 71.4%; p = 0.03) and reduced responsiveness (31.6% vs 78.6%; p = 0.002). INTERPRETATION: This study presents the most extensive semiological analysis of children with confirmed frontal lobe epilepsy. It identifies semiological features that aid in differentiating between mesial and lateral onset. Despite age-dependent differences, typical frontal lobe features, including hyperkinetic seizures, are observed even in very young children. A better understanding of pediatric seizure semiology may enhance the accuracy of onset identification, and enable earlier presurgical evaluation, improving postsurgical outcomes. ANN NEUROL 2024;95:1138-1148.

Long-term neuropsychological trajectories in children with epilepsy: does surgery halt decline?

Neuropsychological impairments are common in children with drug-resistant epilepsy. It has been proposed that epilepsy surgery might alleviate these impairments by providing seizure freedom; however, findings from prior studies have been inconsistent. We mapped long-term neuropsychological trajectories in children before and after undergoing epilepsy surgery, to measure the impact of disease course and surgery on functioning. We performed a retrospective cohort study of 882 children who had undergone epilepsy surgery at Great Ormond Street Hospital (1990-2018). We extracted patient information and neuropsychological functioning [obtained from IQ tests (domains: full-scale IQ, verbal IQ, performance IQ, working memory and processing speed) and tests of academic attainment (reading, spelling and numeracy)] and investigated changes in functioning using regression analyses. We identified 500 children (248 females) who had undergone epilepsy surgery [median age at surgery = 11.9 years, interquartile range = (7.8, 15.0)] and neuropsychological assessment. These children showed declines in all domains of neuropsychological functioning in the time leading up to surgery (all P-values ≤0.001; e.g. ßFSIQ = -1.9, SEFSIQ = 0.3, PFSIQ < 0.001). Children lost on average one to four points per year, depending on the domain considered; 27%-43% declined by ≥10 points from their first to their last preoperative assessment. At the time of presurgical evaluation, most children (46%-60%) scored one or more standard deviations below the mean (<85) on the different neuropsychological domains; 37% of these met the threshold for intellectual disability (full-scale IQ < 70). On a group level, there was no change in performance from pre- to postoperative assessment on any of the domains (all P-values ≥0.128). However, children who became seizure free through surgery showed higher postoperative neuropsychological performance (e.g. rrb-FSIQ = 0.37, P < 0.001). These children continued to demonstrate improvements in neuropsychological functioning over the course of their long-term follow-up (e.g. ßFSIQ = 0.9, SEFSIQ = 0.3, PFSIQ = 0.004). Children who had discontinued antiseizure medication treatment at 1-year follow-up showed an 8- to 13-point advantage in postoperative working memory, processing speed and numeracy, and greater improvements in verbal IQ, working memory, reading and spelling (all P-values ≤0.034) over the postoperative period compared with children who were seizure free and still receiving antiseizure medication. In conclusion, by providing seizure freedom and the opportunity for antiseizure medication cessation, epilepsy surgery might not only halt but reverse the downward trajectory that children with drug-resistant epilepsy display in neuropsychological functioning. To halt this decline as soon as possible or, potentially, to prevent it from occurring in the first place, children with focal epilepsy should be considered for epilepsy surgery as early as possible after diagnosis.

Microscale Neuronal Activity Collectively Drives Chaotic and Inflexible Dynamics at the Macroscale in Seizures.

Neuronal activity propagates through the network during seizures, engaging brain dynamics at multiple scales. Such propagating events can be described through the avalanches framework, which can relate spatiotemporal activity at the microscale with global network properties. Interestingly, propagating avalanches in healthy networks are indicative of critical dynamics, where the network is organized to a phase transition, which optimizes certain computational properties. Some have hypothesized that the pathologic brain dynamics of epileptic seizures are an emergent property of microscale neuronal networks collectively driving the brain away from criticality. Demonstrating this would provide a unifying mechanism linking microscale spatiotemporal activity with emergent brain dysfunction during seizures. Here, we investigated the effect of drug-induced seizures on critical avalanche dynamics, using in vivo whole-brain two-photon imaging of GCaMP6s larval zebrafish (males and females) at single neuron resolution. We demonstrate that single neuron activity across the whole brain exhibits a loss of critical statistics during seizures, suggesting that microscale activity collectively drives macroscale dynamics away from criticality. We also construct spiking network models at the scale of the larval zebrafish brain, to demonstrate that only densely connected networks can drive brain-wide seizure dynamics away from criticality. Importantly, such dense networks also disrupt the optimal computational capacities of critical networks, leading to chaotic dynamics, impaired network response properties and sticky states, thus helping to explain functional impairments during seizures. This study bridges the gap between microscale neuronal activity and emergent macroscale dynamics and cognitive dysfunction during seizures.SIGNIFICANCE STATEMENT Epileptic seizures are debilitating and impair normal brain function. It is unclear how the coordinated behavior of neurons collectively impairs brain function during seizures. To investigate this we perform fluorescence microscopy in larval zebrafish, which allows for the recording of whole-brain activity at single-neuron resolution. Using techniques from physics, we show that neuronal activity during seizures drives the brain away from criticality, a regime that enables both high and low activity states, into an inflexible regime that drives high activity states. Importantly, this change is caused by more connections in the network, which we show disrupts the ability of the brain to respond appropriately to its environment. Therefore, we identify key neuronal network mechanisms driving seizures and concurrent cognitive dysfunction.

Integrating standard epilepsy protocol, ASL-perfusion, MP2RAGE/EDGE and the MELD-FCD classifier in the detection of subtle epileptogenic lesions: a 3 Tesla MRI pilot study.

BACKGROUND: Malformations of cortical development (MCDs) in children with focal epilepsy pose significant diagnostic challenges, and a precise radiological diagnosis is crucial for surgical planning. New MRI sequences and the use of artificial intelligence (AI) algorithms are considered very promising in this regard, yet studies evaluating the relative contribution of each diagnostic technique are lacking. METHODS: The study was conducted using a dedicated "EPI-MCD MR protocol" with a 3 Tesla MRI scanner in patients with focal epilepsy and previously negative MRI. MRI sequences evaluated included 3D FLAIR, 3D T1 MPRAGE, T2 Turbo Spin Echo (TSE), 3D T1 MP2RAGE, and Arterial Spin Labelling (ASL). Two paediatric neuroradiologists scored each sequence for localisation and extension of the lesion. The MELD-FCD AI classifier's performance in identifying pathological findings was also assessed. We only included patients where a diagnosis of MCD was subsequently confirmed on histology and/or sEEG. RESULTS: The 3D FLAIR sequence showed the highest yield in detecting epileptogenic lesions, with 3D T1 MPRAGE, T2 TSE, and 3D T1 MP2RAGE sequences showing moderate to low yield. ASL was the least useful. The MELD-FCD classifier achieved a 69.2% true positive rate. In one case, MELD identified a subtle area of cortical dysplasia overlooked by the neuroradiologists, changing the management of the patient. CONCLUSIONS: The 3D FLAIR sequence is the most effective in the MRI-based diagnosis of subtle epileptogenic lesions, outperforming other sequences in localisation and extension. This pilot study emphasizes the importance of careful assessment of the value of additional sequences.

Lesion detection in epilepsy surgery: Lessons from a prospective evaluation of a machine learning algorithm.

AIM: To evaluate a lesion detection algorithm designed to detect focal cortical dysplasia (FCD) in children undergoing stereoelectroencephalography (SEEG) as part of their presurgical evaluation for drug-resistant epilepsy. METHOD: This was a prospective, single-arm, interventional study (Idea, Development, Exploration, Assessment, and Long-Term Follow-Up phase 1/2a). After routine SEEG planning, structural magnetic resonance imaging sequences were run through an FCD lesion detection algorithm to identify putative clusters. If the top three clusters were not already sampled, up to three additional SEEG electrodes were added. The primary outcome measure was the proportion of patients who had additional electrode contacts in the SEEG-defined seizure-onset zone (SOZ). RESULTS: Twenty patients (median age 12 years, range 4-18 years) were enrolled, one of whom did not undergo SEEG. Additional electrode contacts were part of the SOZ in 1 out of 19 patients while 3 out of 19 patients had clusters that were part of the SOZ but they were already implanted. A total of 16 additional electrodes were implanted in nine patients and there were no adverse events from the additional electrodes. INTERPRETATION: We demonstrate early-stage prospective clinical validation of a machine learning lesion detection algorithm used to aid the identification of the SOZ in children undergoing SEEG. We share key lessons learnt from this evaluation and emphasize the importance of robust prospective evaluation before routine clinical adoption of such algorithms. WHAT THIS PAPER ADDS: The focal cortical dysplasia detection algorithm collocated with the seizure-onset zone (SOZ) in 4 out of 19 patients. The algorithm changed the resection boundaries in 1 of 19 patients undergoing stereoelectroencephalography for drug-resistant epilepsy. The patient with an altered resection due to the algorithm was seizure-free 1 year after resective surgery. Overall, the algorithm did not increase the proportion of patients in whom SOZ was identified.

Predicting seizure outcome after epilepsy surgery: Do we need more complex models, larger samples, or better data?

OBJECTIVE: The accurate prediction of seizure freedom after epilepsy surgery remains challenging. We investigated if (1) training more complex models, (2) recruiting larger sample sizes, or (3) using data-driven selection of clinical predictors would improve our ability to predict postoperative seizure outcome using clinical features. We also conducted the first substantial external validation of a machine learning model trained to predict postoperative seizure outcome. METHODS: We performed a retrospective cohort study of 797 children who had undergone resective or disconnective epilepsy surgery at a tertiary center. We extracted patient information from medical records and trained three models-a logistic regression, a multilayer perceptron, and an XGBoost model-to predict 1-year postoperative seizure outcome on our data set. We evaluated the performance of a recently published XGBoost model on the same patients. We further investigated the impact of sample size on model performance, using learning curve analysis to estimate performance at samples up to N = 2000. Finally, we examined the impact of predictor selection on model performance. RESULTS: Our logistic regression achieved an accuracy of 72% (95% confidence interval [CI] = 68%-75%, area under the curve [AUC] = .72), whereas our multilayer perceptron and XGBoost both achieved accuracies of 71% (95% CIMLP = 67%-74%, AUCMLP = .70; 95% CIXGBoost own = 68%-75%, AUCXGBoost own = .70). There was no significant difference in performance between our three models (all p > .4) and they all performed better than the external XGBoost, which achieved an accuracy of 63% (95% CI = 59%-67%, AUC = .62; pLR = .005, pMLP = .01, pXGBoost own = .01) on our data. All models showed improved performance with increasing sample size, but limited improvements beyond our current sample. The best model performance was achieved with data-driven feature selection. SIGNIFICANCE: We show that neither the deployment of complex machine learning models nor the assembly of thousands of patients alone is likely to generate significant improvements in our ability to predict postoperative seizure freedom. We instead propose that improved feature selection alongside collaboration, data standardization, and model sharing is required to advance the field.

Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States.

BACKGROUND: EEG-fMRI is a useful additional test to localize the epileptogenic zone (EZ) particularly in MRI negative cases. However subject motion presents a particular challenge owing to its large effects on both MRI and EEG signal. Traditionally it is assumed that prospective motion correction (PMC) of fMRI precludes EEG artifact correction. METHODS: Children undergoing presurgical assessment at Great Ormond Street Hospital were included into the study. PMC of fMRI was done using a commercial system with a Moiré Phase Tracking marker and MR-compatible camera. For retrospective EEG correction both a standard and a motion educated EEG artefact correction (REEGMAS) were compared to each other. RESULTS: Ten children underwent simultaneous EEG-fMRI. Overall head movement was high (mean RMS velocity < 1.5 mm/s) and showed high inter- and intra-individual variability. Comparing motion measured by the PMC camera and the (uncorrected residual) motion detected by realignment of fMRI images, there was a five-fold reduction in motion from its prospective correction. Retrospective EEG correction using both standard approaches and REEGMAS allowed the visualization and identification of physiological noise and epileptiform discharges. Seven of 10 children had significant maps, which were concordant with the clinical EZ hypothesis in 6 of these 7. CONCLUSION: To our knowledge this is the first application of camera-based PMC for MRI in a pediatric clinical setting. Despite large amount of movement PMC in combination with retrospective EEG correction recovered data and obtained clinically meaningful results during high levels of subject motion. Practical limitations may currently limit the widespread use of this technology.

Seizure outcome determinants in children after surgery for single unilateral lesions on magnetic resonance imaging: Role of preoperative ictal and interictal electroencephalography.

OBJECTIVE: To determine whether an ictal electroencephalographic (EEG) recording as part of presurgical evaluation of children with a demarcated single unilateral magnetic resonance imaging (MRI) lesion is indispensable for surgical decision-making, we investigated the relationship of interictal/ictal EEG and seizure semiology with seizure-free outcome. METHODS: Data were obtained retrospectively from consecutive patients (≤18 years old) undergoing epilepsy surgery with a single unilateral MRI lesion at our institution over a 6-year period. Video-telemetry EEG (VT-EEG) was classified as concordant or nonconcordant/noninformative in relation to the MRI lesion location. The odds of seizure-free outcome associated with nonconcordant versus concordant for semiology, interictal EEG, and ictal EEG were compared separately. Multivariate logistic regression was conducted to correct for confounding variables. RESULTS: After a median follow-up of 26 months (interquartile range = 17-37.5), 73 (69%) of 117 children enrolled were seizure-free. Histopathological diagnoses included low-grade epilepsy-associated tumors, n = 46 (39%); focal cortical dysplasia (FCD), n = 33 (28%); mesial temporal sclerosis (MTS), n = 23 (20%); polymicrogyria, n = 3 (3%); and nondiagnostic findings/gliosis, n = 12 (10%). The odds of seizure freedom were lower with a nonconcordant interictal EEG (odds ratio [OR] = .227, 95% confidence interval [CI] = .079-.646, p = .006) and nonconcordant ictal EEG (OR = .359, 95% CI = .15-.878, p = .035). In the multivariate logistic regression model, factors predicting lower odds for seizure-free outcome were developmental delay/intellectual disability and higher number of antiseizure medications tried, with a nonsignificant trend for "nonconcordant interictal EEG." In the combined subgroup of patients with FCD and tumors (n = 79), there was no significant relationship of VT-EEG factors and seizure outcomes, whereas in children with MTS and acquired lesions (n = 25), a nonconcordant EEG was associated with poorer seizure outcomes (p = .003). SIGNIFICANCE: An ictal EEG may not be mandatory for presurgical evaluation, particularly when a well-defined single unilateral MRI lesion has been identified and the interictal EEG is concordant.

Extracting the transition network of epileptic seizure onset.

In presurgical monitoring, focal seizure onset is visually assessed from intracranial electroencephalogram (EEG), typically based on the selection of channels that show the strongest changes in amplitude and frequency. As epileptic seizure dynamics is increasingly considered to reflect changes in potentially distributed neural networks, it becomes important to also assess the interrelationships between channels. We propose a workflow to quantitatively extract the nodes and edges contributing to the seizure onset using an across-seizure scoring. We propose a quantification of the consistency of EEG channel contributions to seizure onset within a patient. The workflow is exemplified using recordings from patients with different degrees of seizure-onset consistency.

Cortical Thickness Changes Associated with Photoparoxysmal Response.

Photoparoxysmal response (PPR) is an EEG trait of spike and spike-wave discharges in response to photic stimulation that is closely linked to idiopathic generalized epilepsy (IGE). In our previous studies we showed that PPR is associated with functional alterations in the occipital and frontal cortices. The aim of the present study was to determine structural changes associated with PPR. For this purpose we analysed the cortical thickness as derived from T1 MRI images in PPR-positive-subjects (n = 12; 15.5 ± 8.6 years; 4 males), PPR-positive-IGE-patients (n = 12; 14.9 ± 2.7 years; 4 males) and compared these groups with a group of PPR-negative-healthy-controls (HC, n = 17; 15.3 ± 3.6 years; 6 males). Our results revealed an increase of cortical thickness in the occipital, frontal and parietal cortices bilaterally in PPR-positive-subjects in comparison to HC. Moreover PPR-positive-subjects presented a significant decrease of cortical thickness in the temporal cortex in the same group contrast. IGE patients exhibited lower cortical thickness in the temporal lobe bilaterally and in the right paracentral region in comparison to PPR-positive-subjects. Our study demonstrates structural changes in the occipital lobe, frontoparietal regions and temporal lobe, which also show functional changes associated with PPR. Patients with epilepsy present changes in the temporal lobe and supplementary motor area.

Representation and propagation of epileptic activity in absences and generalized photoparoxysmal responses.

Although functional imaging studies described networks associated with generalized epileptic activity, propagation patterns within these networks are not clear. In this study, electroencephalogram (EEG)-based coherent source imaging dynamic imaging of coherent sources (DICS) was applied to different types of generalized epileptiform discharges, namely absence seizures (10 patients) and photoparoxysmal responses (PPR) (eight patients) to describe the representation and propagation of these discharges in the brain. The results of electrical source imaging were compared to EEG-functional magnetic resonance imaging (fMRI) which had been obtained from the same data sets of simultaneous EEG and fMRI recordings. Similar networks were described by DICS and fMRI: (1) absence seizures were associated with thalamic involvement in all patients. Concordant results were also found for brain areas of the default mode network and the occipital cortex. (2) Both DICS and fMRI identified the occipital, parietal, and the frontal cortex in a network associated with PPR. (3) However, only when PPR preceded a generalized tonic-clonic seizure, the thalamus was involved in the generation of PPR as shown by both imaging techniques. Partial directed coherence suggested that during absences, the thalamus acts as a pacemaker while PPR could be explained by a cortical propagation from the occipital cortex via the parietal cortex to the frontal cortex. In conclusion, the electrical source imaging is not only able to describe similar neuronal networks as revealed by fMRI, including deep sources of neuronal activity such as the thalamus, but also demonstrates interactions interactions within these networks and sheds light on pathogenetic mechanisms of absence seizures and PPR.

Simultaneous EEG and fMRI recordings (EEG-fMRI) in children with epilepsy.

By combining electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) it is possible to describe blood oxygenation level-dependent (BOLD) signal changes related to EEG patterns. This way, EEG-pattern-associated networks of hemodynamic changes can be detected anywhere in the brain with good spatial resolution. This review summarizes EEG-fMRI studies that have been performed in children with epilepsy. EEG-fMRI studies in focal epilepsy (structural and nonlesional cases, benign epilepsy with centrotemporal spikes), generalized epilepsy (especially absence epilepsy), and epileptic encephalopathies (West syndrome, Lennox-Gastaut syndrome, continuous spike and waves during slow sleep, and Dravet syndrome) are presented. Although EEG-fMRI was applied mainly to localize the region presumably generating focal interictal discharges in focal epilepsies, EEG-fMRI identified underlying networks in patients with generalized epilepsies and thereby contributed to a better understanding of these epilepsies. In epileptic encephalopathies a specific fingerprint of hemodynamic changes associated with the particular syndrome was detected. The value of the EEG-fMRI technique for diagnosis and investigation of pathogenetic mechanisms of different forms of epilepsy is discussed.

Variability of EEG-fMRI findings in patients with SCN1A-positive Dravet syndrome.

PURPOSE: Dravet syndrome (DS) or severe myoclonic epilepsy of infancy is an intractable epileptic encephalopathy of early childhood that is caused by a mutation in the SCN1A gene in most patients. The aim of this study was to identify a syndrome-specific epileptic network underlying interictal epileptiform discharges (IEDs) in patients with DS. METHODS: Ten patients with the diagnosis of DS associated with mutations in the SCN1A gene were investigated using simultaneous recording of electroencephalography and functional magnetic resonance imaging ((EEG-fMRI). Time series of IEDs were used as regressors for the statistical fMRI analysis. KEY FINDINGS: In nine patients with DS, individual blood oxygenation level-dependent (BOLD) signal changes were seen. In three patients the thalamus was involved. Furthermore, regions of the default mode network were activated in seven patients. However, a common activation pattern associated with IEDs could not be detected. SIGNIFICANCE: The study demonstrates that, despite a common genetic etiology in DS, different neuronal networks underlie the individual IEDs.

EEG-fMRI in atypical benign partial epilepsy.

Atypical benign partial epilepsy (ABPE) is a subgroup among the idiopathic focal epilepsies of childhood. Aim of this study was to investigate neuronal networks underlying ABPE and compare the results with previous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) studies of related epilepsy syndromes. Ten patients with ABPE underwent simultaneous EEG-fMRI recording. In all 10 patients several types of interictal epileptiform discharges (IEDs) were recorded. Individual IED-associated blood oxygen level-dependent (BOLD) signal changes were analyzed in a single subject analysis for each IED type (33 studies). A group analysis was also performed to determine common BOLD signal changes across the patients. IED-associated BOLD signal changes were found in 31 studies. Focal BOLD signal changes concordant with the spike field (21 studies) and distant cortical and subcortical BOLD signal changes (31 studies) were detected. The group analysis revealed a thalamic activation. This study demonstrated that ABPE is characterized by patterns similar to studies in rolandic epilepsy (focal BOLD signal changes in the spike field) as well as patterns observed in continuous spikes and waves during slow sleep (CSWS) (distant BOLD signal changes in cortical and subcortical structures), thereby underscoring that idiopathic focal epilepsies of childhood form a spectrum of overlapping syndromes.

Neuronal networks in west syndrome as revealed by source analysis and renormalized partial directed coherence.

West syndrome is a severe epileptic encephalopathy of infancy with a poor developmental outcome. This syndrome is associated with the pathognomonic EEG feature of hypsarrhythmia. The aim of the study was to describe neuronal networks underlying hypsarrhythmia using the source analysis method (dynamic imaging of coherent sources or DICS) which represents an inverse solution algorithm in the frequency domain. In order to investigate the interaction within the detected network, a renormalized partial directed coherence (RPDC) method was also applied as a measure of the directionality of information flow between the source signals. Both DICS and RPDC were performed for EEG delta activity (1-4 Hz) in eight patients with West syndrome and in eight patients with partial epilepsies (control group). The brain area with the strongest power in the given frequency range was defined as the reference region. The coherence between this reference region and the entire brain was computed using DICS. After that, the RPDC was applied to the source signals estimated by DICS. The results of electrical source imaging were compared to results of a previous EEG-fMRI study which had been carried out using the same cohort of patients. As revealed by DICS, delta activity in hypsarrhythmia was associated with coherent sources in the occipital cortex (main source) as well as the parietal cortex, putamen, caudate nucleus and brainstem. In patients with partial epilepsies, delta activity could be attributed to sources in the occipital, parietal and sensory-motor cortex. In West syndrome, RPDC showed the strongest and most significant direction of ascending information flow from the brainstem towards the putamen and cerebral cortex. The neuronal network underlying hypsarrhythmia in this study resembles the network which was described in previous EEG-fMRI and PET studies with involvement of the brainstem, putamen and cortical regions in the generation of hypsarrhythmia. The RPDC suggests that brainstem could have a key role in the pathogenesis of West syndrome. This study supports the theory that hypsarrhythmia results from ascending brainstem pathways that project widely to basal ganglia and cerebral cortex.

Abnormal changes of synaptic excitability in migraine with aura.

Migraine patients are characterized by altered cortical excitability and information processing between attacks. The relationship between these abnormalities is still poorly understood. In this study, visual evoked potentials (VEP) and proton magnetic resonance spectroscopy were recorded simultaneously in migraineurs and healthy subjects. In order to investigate the homeostatic-like plasticity in the visual cortex, cortical excitability was modified using transcranial direct current stimulation (tDCS). Before any stimulation, migraineurs showed significantly higher glutamate/creatine ratios (Glx/Cr) than healthy subjects. In healthy subjects, excitatory (anodal) tDCS caused an increase and inhibitory (cathodal) tDCS a decrease in the Glx/Cr ratio. Subsequent photic stimulation (PS) reversed the changes in Glx/Cr ratios, which returned back to baseline, demonstrating homeostatic-like metaplasticity in the control group. In migraine patients, both anodal and cathodal tDCS decreased the Glx/Cr ratio, which did not return to baseline after PS. While healthy subjects showed an increase in VEP amplitude under anodal and a reduction under cathodal tDCS, the modifiability of VEP under tDCS was reduced in migraineurs. The results demonstrate a reduced responsiveness of the occipital cortex to interventions that change cortical excitability in migraine. Moreover, altered glutamatergic neurotransmission seems to mediate the relation between abnormal cortical information processing and excitability in migraineurs.

Patterns of altered functional connectivity in mesial temporal lobe epilepsy.

PURPOSE: In mesial temporal lobe epilepsy (MTLE) the epileptogenic area is confined to the mesial temporal lobe, but other cortical and subcortical areas are also affected and cognitive and psychiatric impairments are usually documented. Functional connectivity methods are based on the correlation of the blood oxygen level dependent (BOLD) signal between brain regions, which exhibit consistent and reproducible functional networks from resting state data. The aim of this study is to compare functional connectivity of patients with MTLE during the interictal period with healthy subjects. We hypothesize that patients show reduced functional connectivity compared to controls, the interest being to determine which regions show this reduction. METHODS: We selected electroencephalography-functional magnetic resonance imaging (EEG-fMRI) resting state data without EEG spikes from 16 patients with right and 7 patients with left MTLE. EEG-fMRI resting state data of 23 healthy subjects matched for age, sex, and manual preference were selected as controls. Four volumes of interest in the left and right amygdalae and hippocampi (LA, RA, LH, and RH) were manually segmented in the anatomic MRI of each subject. The averaged BOLD time course within each volume of interest was used to detect brain regions with BOLD signal correlated with it. Group differences between patients and controls were estimated. KEY FINDINGS: In patients with right MTLE, group difference functional connectivity maps (RMTLE - controls) showed for RA and RH decreased connectivity with the brain areas of the default mode network (DMN), the ventromesial limbic prefrontal regions, and contralateral mesial temporal structures; and for LA and LH, decreased connectivity with DMN and contralateral hippocampus. Additional decreased connectivity was found between LA and pons and between LH and ventromesial limbic prefrontal structures. In patients with left MTLE, functional connectivity maps (LMTLE - controls) showed for LA and LH decreased connectivity with DMN, contralateral hippocampus, and bilateral ventromesial limbic prefrontal regions; no change in connectivity was detected for RA; and for RH, there was decreased connectivity with DMN, bilateral ventromesial limbic prefrontal regions, and contralateral amygdala and hippocampus. SIGNIFICANCE: In unilateral MTLE, amygdala and hippocampus on the affected and to a lesser extent on the healthy side are less connected, and are also less connected with the dopaminergic mesolimbic and the DMNs. Changes in functional connectivity between mesial temporal lobe structures and these structures may explain cognitive and psychiatric impairments often found in patients with MTLE.

White matter microstructural changes of thalamocortical networks in photosensitivity and idiopathic generalized epilepsy.

PURPOSE: Photosensitivity or photoparoxysmal response (PPR) is an electroencephalography trait that is highly associated with idiopathic generalized epilepsies (IGEs) and characterized by changes in cortical excitability in response to photic stimulation. Studying functional and structural changes of PPR might provide important insights into the pathogenesis of IGE. Recent studies revealed a functional network consisting of occipital, parietal, and precentral areas that might be implicated in PPR. Herein, we investigate the microstructural changes associated with PPR. METHODS: Twelve healthy subjects with PPR, nine patients with IGE and PPR (IGE-PPR group), and 18 healthy controls were studied with diffusion magnetic resonance imaging. Tract-based spatial statistics were used to test for regional differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, and radial diffusivity between groups. KEY FINDINGS: Subjects with PPR exhibited higher FA in the right precentral juxtacortical white matter and higher MD in lateral occipital areas relative to controls. Patients with IGE-patients showed additional increases in regional FA in the thalamus and juxtacortical precentral and parietal areas. Both subjects with PPR and patients with IGE-PPR presented axial and radial diffusivity changes in the occipital regions. SIGNIFICANCE: Our results show that PPR is associated with subcortical microstructural changes in precentral, parietal, and occipital regions. The coexistence of PPR and IGE is associated with white matter abnormalities in the thalamus and precuneus. PPR and epilepsy share similar functional and structural networks in widespread cortical and subcortical areas.

Proportion of resected seizure onset zone contacts in pediatric stereo-EEG-guided resective surgery does not correlate with outcome.

OBJECTIVE: We aimed to determine whether the proportion of putative seizure onset zone (SOZ) contacts resected associates with seizure outcome in a cohort of children undergoing stereoelectroencephalography (SEEG)-guided resective epilepsy surgery. METHODS: Patients who underwent SEEG-guided resective surgery over a six-year period were included. The proportion of SOZ contacts resected was determined by co-registration of pre- and post-operative imaging. Outcome was classified as seizure free (SF, Engel class I) or not seizure-free (NSF, Engel class II-IV) at last clinical follow-up. RESULTS: Twenty-nine patients underwent resection of whom 22 had sufficient imaging data for analysis (median age at surgery of 10 years, range 5-18). Fifteen (68.2%) were SF at median follow-up of 19.5 months (range 12-46). On univariate analysis, histopathology, was the only significant factor associated with SF (p < 0.05). The percentage of defined SOZ contacts resected ranged from 25-100% and was not associated with SF (p = 0.89). In a binary logistic regression model, it was highly likely that histology was the only independent predictor of outcome. CONCLUSIONS: The percentage of SOZ contacts resected was not associated with SF in children undergoing SEEG-guided resective epilepsy surgery. SIGNIFICANCE: Factors such as spatial organisation of the epileptogenic zone, neurophysiological biomarkers and the prospective identification of pathological tissue may therefore play an important role.

Independent component analysis (ICA) of generalized spike wave discharges in fMRI: comparison with general linear model-based EEG-fMRI.

Most EEG-fMRI studies in epileptic patients are analyzed using the general linear model (GLM), which assumes a known hemodynamic response function (HRF) to epileptic spikes. In contrast, independent component analysis (ICA) can extract blood-oxygenation level dependent (BOLD) responses without imposing constraints on the HRF. ICA might therefore detect responses that vary in time and shape, and that are not detected in the GLM analysis. In this study, we compared the findings of ICA and GLM analyses in 12 patients with idiopathic generalized epilepsy. Spatial ICA was used to extract independent components from the functional magnetic resonance imaging (fMRI) data. A deconvolution method identified component time courses significantly related to the generalized EEG discharges, without constraining the shape of the HRF. The results from the ICA analysis were compared to those from the GLM analysis. GLM maps and ICA maps showed significant correlation and revealed BOLD responses in the thalamus, caudate nucleus, and default mode areas. In patients with a low rate of discharges per minute, the GLM analysis detected BOLD signal changes within the thalamus and the caudate nucleus that were not revealed by the ICA. In conclusion, ICA is a viable alternative technique to GLM analyses in EEG-fMRI studies related to generalized discharges. This study demonstrated that the BOLD response largely resembles the standard HRF and that GLM analysis is adequate. However, ICA is more dependent on a sufficient number of events than GLM analysis.