Rolandic Epilepsy: Self-Limited Epilepsy with Centrotemporal Spikes

Childhood epilepsy with centrotemporal spikes, had been previously considered as benign childhood epilepsy. According to the new classification proposed by Sheffer I. and colleagues the term “benign” has been changed to “self-limited”. Many studies reported that BECTS may cause transient or long lasting cognitive and behavioral disturbances. Rolandic epilepsy is the most frequent among the childhood focal epilepsy and may account for about 15–25% of all epileptic syndromes diagnosed between the ages of 5 to 15 years. The incidence range changes between 7.1–21 per 100000 in population younger than 15 years with male predominance. The age of onset in 90% of cases between 1 and 10 years with peak around 6–7 years. Seizures mainly occur during a night sleep, whereas the probability of awake seizures are less than 10%. The characteristic clinical features are: (1) focal motor seizure with unilateral orofacial tonic or clonic contractions; (2) speech arrest; (3) hypersalivation; (4) sensory symptoms represented by unilateral numbness or paresthesia of tongue, lips, gum and inner part of the check; (5) unilateral clonic jerk in leg and arm with postictal paresis; (6) generalized seizures. The EEG picture is distinctive in Rolandic epilepsy. The background activity is almost always preserved in awake state and during a sleep. The typical interictal EEG pattern is high voltage, diphasic spikes or sharp waves frequently with slow activity on central-midtemporal region. The centrotemporal spikes or rolandic spikes come from the lower rolandic region created a horizontal dipole with maximal electronegativity in the centrotemporal region and electropositivity in the frontal region usually seen unilateral or bilateral. In most cases children with RE have a good prognosis regarding both seizures and neurodevelopment. The remission of seizures usually occurs before the age of 18 years. The cognitive and behavior problem may happen in active period of disease which are reversable in most of patients

BrainmappingNeuronal Networks in Children with Continuous Spikes and Waves during Slow Sleep as revealed by DICS and RPDC

CSWS is an age-related epileptic encephalopathy consisting of the triad of seizures, neuropsychological impairment and a specific EEG-pattern. This EEG-pattern is characterized by spike-and-wave-discharges emphasized during non-REM sleep. Until now, little has been known about the pathophysiologic processes. So far research approaches on the underlying neuronal network have been based on techniques with a good spatial but poor temporal resolution like fMRI and FDG-PET. In this study the search for sources participating in the neuronal network of CSWS is done by processing EEG-data with high temporal resolution. This allows not only interferences on the location of the individual sources but also on the direction of information flow between them. DICS is applied to the data to solve the inverse problem in the frequency domain. Afterwards RPDC, based on Granger causality, is implemented to reveal effective connectivity between the sources. 12 patients suffering from CSWS without any proof for macroscopic cerebral pathologies in a T1-MRI were investigated at two points of time, before and after treatment. All results are compared to other studies on the neuronal network of CSWS, to knowledge about genesis of epileptic activity in general and to knowledge about the pathogenesis of related psychiatric syndromes. During the active phase of CSWS the thalamus represents the central hub of the neuronal network, and also the cerebellum and key nodes of the DMN contribute to it. Therefore the results are concordant to the ones of former studies and to assumptions on the genesis of epileptic activity. In addition, pathogenetic parallels are found to autism, ADHD and memory-impairment. After cessation of CSWS, the network consists of exclusively cortical sources. In addition to the SWI the mean absolute source power, the mean coherence strength and the mean RPDC strength could be revealed as reliable indicators for the severity of the encephalopathy

Imaging functional and structural networks in the human epileptic brain

Epileptic activity in the brain arises from dysfunctional neuronal networks involving cortical and subcortical grey matter as well as their connections via white matter fibres. Physiological brain networks can be affected by the structural abnormalities causing the epileptic activity, or by the epileptic activity itself. A better knowledge of physiological and pathological brain networks in patients with epilepsy is critical for a better understanding the patterns of seizure generation, propagation and termination as well as the alteration of physiological brain networks by a chronic neurological disorder. Moreover, the identification of pathological and physiological networks in an individual subject is critical for the planning of epilepsy surgery aiming at resection or at least interruption of the epileptic network while sparing physiological networks which have potentially been remodelled by the disease. This work describes the combination of neuroimaging methods to study the functional epileptic networks in the brain, structural connectivity changes of the motor networks in patients with localisation-related or generalised epilepsy and finally structural connectivity of the epileptic network. The combination between EEG source imaging and simultaneous EEG-fMRI recordings allowed to distinguish between regions of onset and propagation of interictal epileptic activity and to better map the epileptic network using the continuous activity of the epileptic source. These results are complemented by the first recordings of simultaneous intracranial EEG and fMRI in human. This whole-brain imaging technique revealed regional as well as distant haemodynamic changes related to very focal epileptic activity. The combination of fMRI and DTI tractography showed subtle changes in the structural connectivity of patients with Juvenile Myoclonic Epilepsy, a form of idiopathic generalised epilepsy. Finally, a combination of intracranial EEG and tractography was used to explore the structural connectivity of epileptic networks. Clinical relevance, methodological issues and future perspectives are discussed

Apport de l’IRM structurelle multimodale dans la chirurgie d’épilepsie : le cas de l’épilepsie insulaire

L’épilepsie insulaire (ÉI) est une forme rare d’épilepsie focale qui, en raison des défis liés à son diagnostic, est difficilement cernable. De plus, la prise en charge des patients avec ÉI s’avère complexifiée par le fait que cette pathologie est fréquemment résistante aux médicaments anti-crises. Pour ces cas médico-réfractaires, la chirurgie insulaire est une option viable. Cela dit, les patients subissant une telle intervention développent fréquemment des déficits neurologiques postopératoires; heureusement, la grande majorité de ceux-ci récupèrent complètement et rapidement. Or, le mécanisme sous-tendant ce singulier rétablissement fonctionnel demeure à ce jour mal compris. Deux modalités modernes d’IRM structurelle, soit l’analyse d’épaisseur corticale et la tractographie, ont permis, dans les dernières années, de décrire les altérations architecturales caractéristiques et potentiellement diagnostiques de divers types d’épilepsie ainsi que de caractériser les remodelages plastiques qui suivent la chirurgie de l’épilepsie extra-insulaire. Cependant, à ce jour, aucune étude ne s’est encore penchée sur le cas de l’ÉI. De ce fait, les études qui constituent cette thèse exploitent l’IRM structurelle afin, d’une part, de dépeindre les altérations d’épaisseur du cortex et de connectivité de matière blanche associées à l’ÉI et, d’autre part, de définir les réarrangements de connectivité subséquents à la chirurgie insulaire pour contrôle épileptique. Les deux premières études de cette thèse ont révélé que l’ÉI était associée à un pattern majoritairement ipsilatéral d’atrophie corticale et d’hyperconnectivité impliquant principalement des sous-régions insulaires et des régions connectées à l’insula. De manière intéressante, la topologie de ces changements correspondait, au moins en partie, à celle du réseau épileptique de l’ÉI. Ensuite, la troisième étude visait à décrire, par le biais d’une méta-analyse, l’histoire naturelle postopératoire des patients subissant une chirurgie pour ÉI. Cette analyse a, entre autres, confirmé que cette chirurgie était efficace (66.7% de disparition des crises) et qu’elle était fréquemment accompagnée de complications neurologiques (42.5%) qui, dans la plupart des cas, étaient transitoires (78.7% des complications) et récupéraient entièrement dans les trois mois postopératoires (91.6% des complications transitoires). Finalement, la quatrième étude a révélé que la chirurgie pour ÉI était suivie d’altérations de connectivité diffuses et bilatérales. Notamment, les connexions présentant une augmentation de connectivité concernaient particulièrement des régions localisées soit près de la cavité chirurgicale ou dans l’hémisphère controlatéral à l’intervention. De plus, la majorité de ces renforcements structurels se sont produits dans les six premiers mois suivant la chirurgie, un délai comparable à celui durant lequel la majeure partie de la récupération fonctionnelle postopératoire a été observée dans notre méta-analyse. En somme, nos résultats suggèrent que les altérations morphologiques en lien avec l’ÉI peuvent correspondre à son réseau épileptique sous-jacent. La topologie de ces changements pourrait constituer un biomarqueur structurel diagnostique qui aiderait à la reconnaissance de l’ÉI et, concomitamment, favoriserait possiblement un traitement chirurgical plus adapté et plus efficace. De plus, les augmentations de connectivité postopératoires pourraient correspondre à des réponses neuroplastiques permettant de prendre en charge les fonctions altérées par la chirurgie. Nos constats ont ainsi contribué à la caractérisation des mécanismes étayant la singulière récupération fonctionnelle accompagnant la chirurgie pour ÉI. À plus grande échelle, nos travaux offrent un aperçu du potentiel de l’IRM structurelle à assister au diagnostic de l’épilepsie focale ainsi qu’à participer à la description des changements plastiques subséquents à une résection neurochirurgicale.Insular epilepsy (IE) is a rare type of focal epilepsy that is difficult to diagnose. In addition to the challenging nature of IE detection, management of patients with this condition is complicated by the tendency of insular seizures to be resistant to anti-seizure medications. For such medically refractory cases, insular surgery constitutes a viable and long-lasting therapeutic option. That said, patients who undergo an insular resection for seizure control frequently develop postoperative neurological deficits; fortunately, most of these impairments recover fully and rapidly. While this favorable postoperative course contributes to improving the outcome of IE surgery, the mechanism underlying the functional recovery remains unknown. Two contemporary structural MRI modalities, namely cortical thickness analysis and tractography, have recently been used to describe characteristic structural alterations of focal epilepsies and to elucidate the postoperative plastic remodeling associated with surgery for extra-insular epilepsy. While these analyses added to our understanding of several localization-related epilepsies, none specifically studied IE. In this thesis, we exploit structural MRI techniques to, first, depict the alterations of cortical thickness and white matter connectivity in IE and, second, define the progressive rearrangements that follow insular surgery for epilepsy. The first two studies of the current thesis showed that IE is associated with a primarily ipsilateral pattern of cortical thinning and hyperconnectivity that mainly involves insular subregions and insula-connected regions. Interestingly, the topology of these changes corresponded, at least in part, to the epileptic network of IE. Furthermore, the third study aimed to describe, via a meta-analysis, the postoperative outcome of patients undergoing surgery for IE. Among other findings, the analysis revealed that insular surgery was effective (66.7% seizure freedom rate) but was associated with a significant risk of neurological complications (42.5%) which, in most cases, were transient (78.7% of all complications) and recovered fully within three months (91.6% of transient complications). Finally, the fourth study showed that surgery for IE was followed by a diffuse pattern of bilateral structural connectivity changes. Notably, connections exhibiting an increase in connectivity were specifically located near the surgical cavity and in the contralateral healthy hemisphere. In addition, the majority of the structural strengthening occurred in the first six months following surgery, a time course that is consistent with the short delay during which most of the postoperative functional recovery was observed in our meta-analysis. Our results suggest that the morphological alterations in IE may reflect its underlying epileptic network. The topology of these changes may constitute a structural biomarker that could help diagnose IE more readily and, concomitantly, potentially enable a more targeted and more effective surgical treatment. Moreover, the postoperative increases in connectivity may be compatible with compensatory neuroplastic responses, a process that arose to recoup the functions of the injured insular cortex. Our findings have therefore contributed to the characterization of the driving process that supports the striking functional recovery seen following surgery for IE. On a larger scale, our work provides insights into the potential of structural MRI to assist in the diagnosis of focal epilepsy and to describe plastic changes following neurosurgical resections

Neuroimaging - Clinical Applications

Modern neuroimaging tools allow unprecedented opportunities for understanding brain neuroanatomy and function in health and disease. Each available technique carries with it a particular balance of strengths and limitations, such that converging evidence based on multiple methods provides the most powerful approach for advancing our knowledge in the fields of clinical and cognitive neuroscience. The scope of this book is not to provide a comprehensive overview of methods and their clinical applications but to provide a "snapshot" of current approaches using well established and newly emerging techniques

Methodological and clinical aspects of ictal and interictal MEG

During the last years magnetoencephalography (MEG), has become an important part of the pre-surgical epilepsy workup. Interictal activity is usually recorded. Nevertheless, the technological advances now enable ictal MEG recordings as well. The records of 26 pharmaco-resistant focal epilepsy patients, who underwent ictal MEG and epilepsy surgery, were reviewed. In 12 patients prediction of ictal onset zone (IOZ) localization by ictal and interictal MEG was compared with ictal intracranial EEG (icEEG). On the lobar surface level the sensitivity of ictal MEG in IOZ location was 0.71 and the specificity 0.73. The sensitivity of the interictal MEG was 0.40 and specificity 0.77. The records of 34 operated epilepsy patients with focal cortical dysplasia (FCD) were retrospectively evaluated. The resected proportion of the source cluster related to interictal MEG was evaluated in respect to postoperative seizure outcome. 17 out of 34 patients with FCD (50%) achieved seizure freedom. The seizure outcome was similar in patients with MR-invisible and MR-visible FCD. With MEG source clusters and favorable seizure outcome (Engel class I and II) the proportion of the cluster volume resection was 49% - significantly higher (p=0.02) than with MEG clusters but unfavorable outcome (5.5% of cluster volume resection). Median nerve somatosensory evoked MEG responses were processed by movement compensation based on signal space separation (MC-SSS) and on spatio-temporal signal space separation (MC-tSSS). MEG was recorded in standard and deviant head positions. With up to 5 cm head displacement, MC-SSS decreased the mean localization error from 3.97 to 2.13 cm, but increased noise of planar gradiometers from 3.4 to 5.3 fT/cm. MC-tSSS reduced noise from 3.4 to 2.8 fT/cm and reduced the mean localization error from 3.91 to 0.89 cm. The MEG data containing speech-related artifacts and data containing alpha rhythm were processed by tSSS with different correlation limits. The speech artifact was progressively suppressed with the decreasing tSSS correlation limit. The optimal artifact suppression was achieved at correlation of 0.8. The randomly distributed source current (RDCS), and auditory and somatosensory evoked fields (AEFs and SEFs) were simulated. The information was calculated employing Shannon's theory of communication for a standard 306-sensor MEG device and for a virtual MEG helmet (VMH), which was constructed based on simulated MEG measurements in different head positions. With the simulation of 360 recorded events using RDCS model the maximum Shannon's number was 989 for single head position in standard MEG array and 1272 in VMH (28.6% additional information). With AEFs the additional contribution of VMH was 12.6% and with SEFs only 1.1%. To conclude, ictal MEG predicts IOZ location with higher sensitivity than interictal MEG. Resection of larger proportion of the MEG source cluster in patients with FCD is associated with a better seizure outcome, however, complete resection of MEG source cluster is often not required for achievement of favorable seizure outcome. The seizure outcome is similar in patients having MR-positive and MR-negative FCD. MC-tSSS decreases the source localization error to less than 1 cm, when the head is displaced up to 5 cm; however, it is reasonable to limit use of movement compensation for no more than 3-cm head displacement to keep the head inside sensor helmet. The optimization of the tSSS correlation limit to about 0.8 can improve the artifact suppression in MEG without substantial change of brain signals. MEG recording of the same brain activity in different head positions with subsequent construction of VMH can improve the information content of the data.Magnetoenkefalografia (MEG) on menetelmä, jolla mitataan aivojen tuottamia heikkoja magneettikenttiä. Yksi menetelmän tärkeimmistä kliinisistä käyttö-tarkoituksista on paikantaa epilepsiapesäkkeitä aivoissa. Tämä on tärkeää epilepsiakirurgian suunnittelussa. Potilaan liikkeet mittauksen aikana ovat aiheuttaneet epätarkkuutta pesäkkeiden paikannukseen ja häiriösignaaleja mittauksiin. Ongelma on ollut erityisen korostunut lasten mittauksissa ja epileptisten kohtausten rekisteröinneissä. Useimmissa potilaissa MEG-paikannus onkin perustunut kohtausten välisten epileptiformisten aivosähköilmiöiden paikannukseen. Pitkät MEG-rekisteröinnit ovat myös olleet haastavia koska yhteistyökykyisten potilaidenkin on vaikea olla liikkumatta pitkiä aikoja. Viime vuosien tekninen kehitys on mahdollistanut MEG-mittaukset myös pään liikkeiden aikana. Myös aivosignaalien ja kehossa olevien magneettisten materiaalien (esim hammaspaikat, sydämen tahdistimet tai aivostimulaattorit) aiheuttamien magneettisten häiriöiden erottaminen on nykyisin toteutettavissa. Tämä kehitys on mahdollistanut MEG-mittaukset potilailla, joilla aiemmin ei ollut mahdollisuutta hyötyä MEG-paikannuksista ja myös MEG-mittaukset epileptisten kohtausten aikana. Tärkeä osa väitöskirjaa on epilepsiakohtausten aikaisten MEG-mittausten kliinisen hyödyn arviointi. Tulokset osoittavat, että kohtauksenaikaiset MEG-mittaukset paikantavat herkemmin epilepsiakohtauksen lähdealueen aivoissa kuin kohtausten välisten epilepsiailmiöiden lähdepaikannus. Lähdealueiden paikannus on yhtä tarkka sekä aivokuoren pinnalla että 4 cm syvyydessä aivouurteissa. Pää ei kuitenkaan saisi liikkua 3 cm enempää MEG-mittauksen aikana, ja menetelmän herkkyys paranee oilennaisesti magneettikenttien matemaattiseen mallinnukseen perustuvalla magneettisten liikehäiriöiden poistolla. Väitöskirja tutkii lisäksi aivokuoren rakennemuutosten (paikallinen aivokuoridysplasia) aiheuttaman epilepsian kohtausten välisiä MEG-mittauksia. Päinvastoin kuin aiemmin on väitetty, ei aina ole tarpeen poistaa koko epileptisia lähdealueita sisältävää aivojen aluetta hyvän leikkaustuloksen saamiseksi. Väitöskirja esittelee myös laskennallisen MEG-anturiston määritysmenetelmän , joka lisää MEG-mittausten informaatiosisältöä huomioimalla pään liikkeet tulosten analyysissä

Functional network correlates of language and semiology in epilepsy

Epilepsy surgery is appropriate for 2-3% of all epilepsy diagnoses. The goal of the presurgical workup is to delineate the seizure network and to identify the risks associated with surgery. While interpretation of functional MRI and results in EEG-fMRI studies have largely focused on anatomical parameters, the focus of this thesis was to investigate canonical intrinsic connectivity networks in language function and seizure semiology. Epilepsy surgery aims to remove brain areas that generate seizures. Language dysfunction is frequently observed after anterior temporal lobe resection (ATLR), and the presurgical workup seeks to identify the risks associated with surgical outcome. The principal aim of experimental studies was to elaborate understanding of language function as expressed in the recruitment of relevant connectivity networks and to evaluate whether it has value in the prediction of language decline after anterior temporal lobe resection. Using cognitive fMRI, we assessed brain areas defined by parameters of anatomy and canonical intrinsic connectivity networks (ICN) that are involved in language function, specifically word retrieval as expressed in naming and fluency. fMRI data was quantified by lateralisation indices and by ICN_atlas metrics in a priori defined ICN and anatomical regions of interest. Reliability of language ICN recruitment was studied in 59 patients and 30 healthy controls who were included in our language experiments. New and established language fMRI paradigms were employed on a three Tesla scanner, while intellectual ability, language performance and emotional status were established for all subjects with standard psychometric assessment. Patients who had surgery were reinvestigated at an early postoperative stage of four months after anterior temporal lobe resection. A major part of the work sought to elucidate the association between fMRI patterns and disease characteristics including features of anxiety and depression, and prediction of postoperative language outcome. We studied the efficiency of reorganisation of language function associated with disease features prior to and following surgery. A further aim of experimental work was to use EEG-fMRI data to investigate the relationship between canonical intrinsic connectivity networks and seizure semiology, potentially providing an avenue for characterising the seizure network in the presurgical workup. The association of clinical signs with the EEG-fMRI informed activation patterns were studied using the data from eighteen patients’ whose seizures and simultaneous EEG-fMRI activations were reported in a previous study. The accuracy of ICN_atlas was validated and the ICN construct upheld in the language maps of TLE patients. The ICN construct was not evident in ictal fMRI maps and simulated ICN_atlas data. Intrinsic connectivity network recruitment was stable between sessions in controls. Amodal linguistic processing and the relevance of temporal intrinsic connectivity networks for naming and that of frontal intrinsic connectivity networks for word retrieval in the context of fluency was evident in intrinsic connectivity networks regions. The relevance of intrinsic connectivity networks in the study of language was further reiterated by significant association between some disease features and language performance, and disease features and activation in intrinsic connectivity networks. However, the anterior temporal lobe (ATL) showed significantly greater activation compared to intrinsic connectivity networks – a result which indicated that ATL functional language networks are better studied in the context of the anatomically demarked ATL, rather than its functionally connected intrinsic connectivity networks. Activation in temporal lobe networks served as a predictor for naming and fluency impairment after ATLR and an increasing likelihood of significant decline with greater magnitude of left lateralisation. Impairment of awareness served as a significant classifying feature of clinical expression and was significantly associated with the inhibition of normal brain functions. Canonical intrinsic connectivity networks including the default mode network were recruited along an anterior-posterior anatomical axis and were not significantly associated with clinical signs