39 research outputs found

    An unaware agenda: interictal consciousness impairments in epileptic patients.

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    Consciousness impairments have been described as a cornerstone of epilepsy. Generalized seizures are usually characterized by a complete loss of consciousness, whereas focal seizures have more variable degrees of responsiveness. In addition to these impairments that occur during ictal episodes, alterations of consciousness have also been repeatedly observed between seizures (i.e. during interictal periods). In this opinion article, we review evidence supporting the novel hypothesis that epilepsy produces consciousness impairments which remain present interictally. Then, we discuss therapies aimed to reduce seizure frequency, which may modulate consciousness between epileptic seizures. We conclude with a consideration of relevant pathophysiological mechanisms. In particular, the thalamocortical network seems to be involved in both seizure generation and interictal consciousness impairments, which could inaugurate a promising translational agenda for epilepsy studies

    Reorganization and resilience of brain networks in focal epilepsy

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    Laboratory of Neurobiology and Medical Genetics Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau, the Republic of Moldova, The 75th anniversary of Nicolae Testemitanu State University of Medicine and Pharmacy of the Republic of Moldova (1945-2020)Background: Epilepsy has been considered as a brain network disorder. Advanced computational tools have granted a non-invasive window to explore the brain networks in epilepsy. Studying the reorganization of brain networks can help in modelling the network topology changes related to focal epilepsy. The present study aimed to explore the reorganization and resilience of brain networks in patients with focal epilepsy. Material and methods: The structural 3T T1-weighted MR images of 40 patients with focal epilepsy and 40 healthy subjects, were processed by using FreeSurfer. Cortical thickness values were used for the reconstruction of morphometric networks. The topological organization and resilience of brain networks were assessed by applying the graph theoretical analysis. Results: The topological organization of the brain networks in patients was marked by a higher clustering coefficient, local efficiency and path length (all p<0.05) as compared to healthy individuals. The network hubs (i.e. brain regions responsible for network maintenance) were differently distributed in patients (left superior temporal and right paracentral) and healthy subjects (left anterior cingulate and right superior temporal). The brain networks in patients exhibited lower resilience (p<0.05) to targeted attacks (i.e. the removal of brain regions depending on their importance for network organization) and similar resilience (p>0.05) to random attacks (i.e. random brain area removal). Conclusions: Brain networks in focal epilepsy were characterized by an increased segregability and a decreased integrability. Reduced resilience to targeted attacks in patients, as compared to healthy subjects, suggests an uneven importance of brain regions for network maintenance in the studied groups

    Sleep-related epileptic behaviors and non-REM-related parasomnias: Insights from stereo-EEG

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    During the last decade, many clinical and pathophysiological aspects of sleep-related epileptic and non-epileptic paroxysmal behaviors have been clarified. Advances have been achieved in part through the use of intracerebral recording methods such as stereo-electroencephalography (S-EEG), which has allowed a unique "in vivo" neurophysiological insight into focal epilepsy. Using S-EEG, the local features of physiological and pathological EEG activity in different cortical and subcortical structures have been better defined during the entire sleep-wake spectrum. For example, S-EEG has contributed to clarify the semiology of sleep-related seizures as well as highlight the specific epileptogenic networks involved during ictal activity. Moreover, intracerebral EEG recordings derived from patients with epilepsy have been valuable to study sleep physiology and specific sleep disorders. The occasional co-occurrence of NREM-related parasomnias in epileptic patients undergoing S-EEG investigation has permitted the recordings of such events, highlighting the presence of local electrophysiological dissociated states and clarifying the underlying pathophysiological substrate of such NREM sleep disorders. Based on these recent advances, the authors review and summarize the current and relevant S-EEG literature on sleep-related hypermotor epilepsies and NREM-related parasomnias. Finally, novel data and future research hypothesis will be discussed

    Altered grey matter integrity and network vulnerability relate to epilepsy occurrence in patients with multiple sclerosis

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    Background and purpose: The aim of this study was to investigate the relevance of compartmentalized grey matter (GM) pathology and network reorganization in multiple sclerosis (MS) patients with concomitant epilepsy. Methods: From 3-T magnetic resonance imaging scans of 30 MS patients with epilepsy (MSE group; age 41 ± 15 years, 21 females, disease duration 8 ± 6 years, median Expanded Disability Status Scale [EDSS] score 3), 60 MS patients without epilepsy (MS group; age 41 ± 12 years, 35 females, disease duration 6 ± 4 years, EDSS score 2), and 60 healthy subjects (HS group; age 40 ± 13 years, 27 females) the regional volumes of GM lesions and of cortical, subcortical and hippocampal structures were quantified. Network topology and vulnerability were modelled within the graph theoretical framework. Receiver-operating characteristic (ROC) curve analysis was applied to assess the accuracy of GM pathology measures to discriminate between MSE and MS patients. Results: Higher lesion volumes within the hippocampus, mesiotemporal cortex and amygdala were detected in the MSE compared to the MS group (all p < 0.05). The MSE group had lower cortical volumes mainly in temporal and parietal areas compared to the MS and HS groups (all p < 0.05). Lower hippocampal tail and presubiculum volumes were identified in both the MSE and MS groups compared to the HS group (all p < 0.05). Network topology in the MSE group was characterized by higher transitivity and assortativity, and higher vulnerability compared to the MS and HS groups (all p < 0.05). Hippocampal lesion volume yielded the highest accuracy (area under the ROC curve 0.80 [0.67–0.91]) in discriminating between MSE and MS patients. Conclusions: High lesion load, altered integrity of mesiotemporal GM structures, and network reorganization are associated with a greater propensity for epilepsy occurrence in people with MS

    Drug-resistant epilepsy: modern concepts, integrative mechanisms, and therapeutic advances

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    Background: Drug-resistant epilepsy is the cause of severe disability. Multiple questions remain unanswered both in terms of pathogenesis and therapeutic management. For this narrative review, PubMed database and Infomedica library were searched by using “drug-resistance in epilepsy” and “treatment of drug-resistant epilepsy” as key words. The following filters were applied: “Clinical Trial”, “Meta-analysis”, “Multicenter Study”, and “Randomized Controlled Trial”, covering the period of 01.01.2005–06.01.2021.Several hypotheses have been proposed, i.e., pharmacokinetic, intrinsic severity, gene, target, transporter, and neural network hypotheses. Many controlled trials showed different results in terms of seizure control after combined methods of therapies. Immunotherapy, palliative epilepsy surgery alone or associated with neurostimulation procedures including vagus nerve, trigeminal nerve, or deep brain stimulation may be efficient, however, seizure freedom is not always achieved. Genetic epilepsies might benefit from gene and exosome therapy; however, further studies are needed to verify their safety. Conclusions: Neuroscience of drug-resistant epilepsy faces many challenges. Inflammatory mediators, biomarkers, and genes might allow the identification of new treatment targets, contribute to an earlier diagnosis, and assess the clinical outcomes

    Continuous reorganization of cortical information flow in multiple sclerosis : a longitudinal fMRI effective connectivity study

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    Effective connectivity (EC) is able to explore causal effects between brain areas and can depict mechanisms that underlie repair and adaptation in chronic brain diseases. Thus, the application of EC techniques in multiple sclerosis (MS) has the potential to determine directionality of neuronal interactions and may provide an imaging biomarker for disease progression. Here, serial longitudinal structural and resting-state fMRI was performed at 12-week intervals over one year in twelve MS patients. Twelve healthy subjects served as controls (HC). Two approaches for EC quantification were used: Causal Bayesian Network (CBN) and Time-resolved Partial Directed Coherence (TPDC). The EC strength was correlated with the Expanded Disability Status Scale (EDSS) and Fatigue Scale for Motor and Cognitive functions (FSMC). Our findings demonstrated a longitudinal increase in EC between specific brain regions, detected in both the CBN and TPDC analysis in MS patients. In particular, EC from the deep grey matter, frontal, prefrontal and temporal regions showed a continuous increase over the study period. No longitudinal changes in EC were attested in HC during the study. Furthermore, we observed an association between clinical performance and EC strength. In particular, the EC increase in fronto-cerebellar connections showed an inverse correlation with the EDSS and FSMC. Our data depict continuous functional reorganization between specific brain regions indicated by increasing EC over time in MS, which is not detectable in HC. In particular, fronto-cerebellar connections, which were closely related to clinical performance, may provide a marker of brain plasticity and functional reserve in MS

    Mutation analysis of GABAergic neuroinhibitory genes in childhood genetic generalised epilepsies.

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    Epilepsy affects over 450,000 people in the UK and there are over 50 epilepsy phenotypes; genetic generalised epilepsy (GGE) account for up to 30% of seizure types. It is established that GGE and other neurological disorders are, in some cases, caused by channelopathies within post-synaptic inhibitory neurotransmitter systems such as GAB A (epilepsy) and Glycine (hyperekplexia). GAB A is the primary inhibitory neurotransmitter in the brain and is synthesised from glutamate by GAD65 and 67, and is released from the pre-synaptic nerve terminal into the synaptic cleft, where it binds to post-synaptic GABA receptors and initiate neuroinhibition. This inhibition is removed by post-synaptic GABA transporters (GAT1 and GAT3) that uptake GABA back into the cell for re-packaging in presynaptic vesicles or breakdown by transamination. Abnormalities in this system have been linked to diseases including anxiety, psychosis, Parkinsons’s Disease and epilepsy. GABAergic animal models have demonstrated a tendency to seizure, including GABA transporter and enzyme models in relation to epilepsy.Given the above, the aim of this study was to identify GGE causing variants in four GABAergic genes. GGE patient samples (n=101) were recruited from 3 global centres and screened for variations in GAT1, GAT3, GAD65, GAD67 using high-throughput LightScanner analysis and bi-directional Sanger sequencing. Control population studies («=480) were carried out and analysis of online databases to determine the frequency of variants. Twenty novel or very rare variants were identified in 48 patient samples representing a detection rate of 6.8%, where a clustering of phenotypes included a predisposition towards absence seizures. The biological consequences of these variants were predicted using three online predictive programmes, multiple phylogenetic alignments and 3D structural modelling. Mutation expression constructs were prepared and expression levels were validated by immunocytochemistry. Functional characterisation of these variants will hopefully improve genetic diagnosis in GGE and determine causality of GABAergic absence seizures

    Tonic GABAa current in absence epilepsy

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    Typical absence seizures are characteristic of many idiopathic generalised epilepsies and the only seizure-type in childhood absence epilepsy. We know that absence seizures arise in thalamocortical networks and that GABAergic agents exacerbate or induce absences. Furthermore, raised levels of GABA have been identified in the ventrobasal thalamus in an established genetic animal model (genetic absence epilepsy rats from Strasbourg GAERS), which was later suggested as a result of aberrant GABA uptake. I have shown that enhanced tonic GABAa current in TC neurons of the VB is a common phenomenon across genetic and pharmacological models of absence seizures. Furthermore, my data show that increased extrasynaptic GABAaR (cGABAaR) function in the VB is both sufficient and necessary to induce SWDs. This is supported by the fact that focal intrathalamic application of a selective agonist for eGABAARs, THIP, was sufficient to elicit SWDs in normal animals and that mice lacking cGABAaRs were resistant to absence seizure induction by y-butyrolactone. Moreover, I have presented data that directly implicate aberrant type-1 GABA transporters (GAT-1) in SWD generation in vivo, with GAT-1 knockout mice exhibiting spontaneous SWDs and focal thalamic administration of the GAT-1 blocker, N0711, inducing SWDs in normal rats a potential new model of absence epilepsy. In addition, my data indicate that activation of postsynaptic GABAbRs enhances tonic GABAA current, presumably via the Gl o protein coupled adenyl cyclase pathway, which was present under control conditions and occurred in several brain areas. This postsynaptic GABAb-cGABAaR link is further supported by the fact that GBL failed to induce SWDs in 5-subunit knockout mice. Thus, one of the cellular thalamic pathologies that characterises absence seizures is an astrocyte-specific aberrant GAT-1 with the resulting elevated extracellular GABA level enhancing tonic GABAa current through two mechanisms: direct activation of high affinity eGABAARs and indirect increase in eGABAAR function due to activation of postsynaptic GABAbRs.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Whole Brain Network Dynamics of Epileptic Seizures at Single Cell Resolution

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    Epileptic seizures are characterised by abnormal brain dynamics at multiple scales, engaging single neurons, neuronal ensembles and coarse brain regions. Key to understanding the cause of such emergent population dynamics, is capturing the collective behaviour of neuronal activity at multiple brain scales. In this thesis I make use of the larval zebrafish to capture single cell neuronal activity across the whole brain during epileptic seizures. Firstly, I make use of statistical physics methods to quantify the collective behaviour of single neuron dynamics during epileptic seizures. Here, I demonstrate a population mechanism through which single neuron dynamics organise into seizures: brain dynamics deviate from a phase transition. Secondly, I make use of single neuron network models to identify the synaptic mechanisms that actually cause this shift to occur. Here, I show that the density of neuronal connections in the network is key for driving generalised seizure dynamics. Interestingly, such changes also disrupt network response properties and flexible dynamics in brain networks, thus linking microscale neuronal changes with emergent brain dysfunction during seizures. Thirdly, I make use of non-linear causal inference methods to study the nature of the underlying neuronal interactions that enable seizures to occur. Here I show that seizures are driven by high synchrony but also by highly non-linear interactions between neurons. Interestingly, these non-linear signatures are filtered out at the macroscale, and therefore may represent a neuronal signature that could be used for microscale interventional strategies. This thesis demonstrates the utility of studying multi-scale dynamics in the larval zebrafish, to link neuronal activity at the microscale with emergent properties during seizures
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