Thesis
Reference
Large-scale epileptic network in a mouse-model of temporal lobe epilepsy
SHEYBANI, Laurent
Abstract
Dans l'épilepsie du lobe temporal mésial, il est communément admis qu'une région cérébrale appelée "foyer épileptique" (FE) est responsable des crises épileptiques et des symptômes interictaux. Cependant, plusieurs observations soutiennent l'hypothèse que d'autres régions cérébrales participent à l'expression de la maladie, comme la persistance de crises épileptiques après chirurgie ou l'existence de déficits neurologiques inexpliqués par les dysfonctions du FE. L'existence d'altérations fonctionnelles en-dehors du FE n'a toutefois jamais été démontrée. Dans ce travail, nous démontrons l'existence et le développement d'un réseau épileptique à large-échelle s'étendant au-delà du FE. Dans la phase chronique de la maladie, il devient impossible de contrôler le réseau en supprimant pharmacologiquement l'activité du FE. Le fait que ceci soit possible dans la phase précoce indique que le réseau évolue durant la maladie et devient indépendant du FE, à terme. Nos données encouragent une intervention précoce dans la prise en charge des patients épileptiques.
SHEYBANI, Laurent. Large-scale epileptic network in a mouse-model of temporal lobe epilepsy. Thèse de doctorat : Univ. Genève et Lausanne, 2016, no. Neur. 185
URN : urn:nbn:ch:unige-916770
DOI : 10.13097/archive-ouverte/unige:91677
Available at:
http://archive-ouverte.unige.ch/unige:91677
Disclaimer: layout of this document may differ from the published version.
DOCTORAT EN NEUROSCIENCES des Universités de Genève
et de Lausanne
UNIVERSITÉ DE GENÈVE FACULTÉ DE MEDECINE Professeur Christoph M Michel, directeur de thèse
Docteur Charles Quairiaux, co-directeur de thèse
L ARGE -S CALE E PILEPTIC N ETWORK I N A M OUSE -M ODEL O F T EMPORAL L OBE E PILEPSY
THESE Présentée à la Faculté de Médecine de l’Université de Genève
pour obtenir le grade de Docteur en Neurosciences
par
Laurent SHEYBANI
de Genève
Thèse N° 185 Imprimé à Uni-Mail
2016
Large-scale epileptic network in a mouse-model of
temporal lobe epilepsy
FINANCEMENT ... 6
ACKNOWLEDGEMENTS ... 6
RESUME & CONTEXT ... 7
ABSTRACT & BACKGROUND ... 10
ABBREVIATIONS ... 13
INTRODUCTION ... 14
1. General considerations on epilepsy ... 14
a) Definition ... 14
i. Clinical definition ... 14
ii. Neurophysiological definition ... 15
b) Epidemiology ... 16
c) Focal and generalized epilepsies ... 16
d) Common epileptic disorders ... 17
2. Electrophysiology... 17
3. The hippocampus as a major hub of the limbic network ... 18
a) Functions of the hippocampal formation ... 18
b) Structural neuroanatomy of the hippocampal formation ... 19
c) The human hippocampal commissure ... 21
i. Inter-hippocampal structural connectivity in humans ... 21
ii. Inter-hippocampal functional connectivity in humans... 21
d) Theta-rhythm ... 22
i. Theta-rhythm in physiological conditions ... 22
ii. Theta-rhythm in pathological conditions ... 23
4. Temporal lobe epilepsy ... 24
a) Epidemiology and clinical presentation ... 24
b) Treatments of TLE ... 25
c) Significant proportion of relapse after surgery in TLE... 26
d) Recurrence after surgery not consecutive to incomplete focus resection ... 26
e) Mesial temporal lobe epilepsy without hippocampal sclerosis ... 27
5. Cognitive co-morbidities as a consequence of extended epileptic network activity ... 29
a) Neurological co-morbidities in epilepsy ... 29
b) Cognitive co-morbidities and disease duration ... 29
c) Cognitive co-morbidities: the consequence of widespread epileptic activity? ... 30
6. Epilepsy as a progressive disorder ... 30
a) Secondary epileptogenesis... 31
i. Secondary epileptogenesis in animals ... 31
ii. Secondary epileptogenesis in humans ... 32
7. Epileptic networks ... 33
a) The concept of large-scale epileptic networks ... 33
b) Mechanisms of epileptic network generation ... 34
i. Plasticity: definitions ... 35
ii. Plasticity in the primary focus ... 35
iii. Plasticity in the primary focus: epileptogenicity of interictal epileptic discharges ... 36
iv. Epileptic network emergence: large-scale structural abnormalities ... 37
v. Epileptic network emergence: large-scale functional abnormalities ... 38
c) Therapeutic intervention in the epileptic network: insight from animal studies ... 39
d) Therapeutic intervention in the epileptic network: insight from human studies ... 40
8. Network influence in the generation of interictal epileptiform discharges ... 41
a) Prediction of epileptic activity ... 41
b) Prediction in human studies... 41
c) Prediction in animal studies ... 42
d) Epileptic networks in silico ... 42
9. Fast-ripples as a marker of epileptogenic brain areas ... 43
a) Interictal epileptiform discharges ... 44
b) High-frequency oscillations ... 44
i. Definition of high-frequency oscillation ... 44
ii. Mechanisms of generation of fast-ripples ... 44
iii. Fast-ripples generation in the neocortex ... 46
iv. Fast-ripples as biomarkers of the seizure-onset zone... 47
v. Controversy on the validity of fast-ripples as biomarkers of the seizure-onset zone ... 48
10. The mouse-model of hippocampal sclerosis ... 48
a) Properties of kainic acid ... 48
b) First description of the kainate mouse model of hippocampal sclerosis ... 49
c) Remote effects of intrahippocampal kainate injection ... 50
d) Therapeutic perspective using the kainate mouse model of hippocampal sclerosis ... 51
11. Aims of the study ... 51
MATERIALS AND METHODS ... 54
1. Common materials and methods for projects 1 & 2 ... 54
a) Animals and surgeries ... 54
b) Data analysis ... 54
c) Fast-ripples identification and analysis... 56
d) Statistical analysis ... 56
2. Materials and methods specific for project 1 ... 57
a) Surface topographies during generalized spikes ... 57
b) Epileptic focus silencing... 57
c) Video-based analysis of motor symptoms ... 58
3. Materials and methods specific for project 2 ... 58
a) Frequency analyses ... 58
b) Multi-unit activity ... 60
c) Surface maps of spectral power ... 61
RESULTS ... 61
1. Results of Project 1 ... 61
a) Seizures and focal IEDs are strictly generated in the sclerotic hippocampus following kainate injection ... 61
b) Generalized spikes indicate the formation of an epileptic network beyond the EF ... 62
c) Progressive shift in onset of generalized spikes ... 65
d) Propagation of generalized spikes caused myoclonic jerks... 65
e) Focal and remote epileptic fast ripples are biomarkers of large-scale exacerbation of TLE... 66
f) GS and background-associated FRs ... 67
g) Do GS and remote FRs disappear if the hippocampal focus is silenced? ... 73
2. Results of Project 2 ... 73
a) Fast-ripples identification in remote areas using intracortical recordings ... 73
b) Fast-ripples expression is locked to LFP peak suggestive of interictal epileptic discharges ... 74
c) A large-scale 4 Hz-driven network led by the hippocampi initiates FC-FRs expression ... 76
i. 3-5 Hz and 20-30 Hz activities around FC-FRs... 76
ii. Large-scale 3-5 Hz synchronization ... 77
iii. Large-scale 3-5 Hz activity led by both hippocampi precedes FC-FRs ... 78
iv. 4 Hz-resetting locks the 20-30 Hz peak ... 80
d) 4 Hz-wave controls FC-FRs through an induced neuronal down state... 82
i. Down states of MUA before and after FC-FRs ... 82
ii. Down-states of MUA are phase locked to 3-5 Hz oscillaitons ... 82
DISCUSSION ... 85
1. Discussion of Project 1 ... 85
a) Development of a large-scale epileptic network ... 85
b) Emergence of pathological fast-ripples outside of the primary epileptic focus... 86
c) Temporal lobe epilepsy is a progressive disorder ... 87
d) A new challenge in epilepsy research: understanding epileptic network formation and self- sustainability ... 88
e) Limitations and open questions of the study ... 88
i. Behavioral consequences of the epileptic network ... 88
ii. Molecular-circuits mechanisms of generalized spikes generation ... 89
iii. Evaluation of ictal activities ... 89
iv. Comparative analysis of fast-ripples and ripples ... 90
2. Discussion of Project 2 ... 90
a) Overview of the results ... 90
b) The missing link: how the down state leads to increased neuronal firing? ... 91
c) Generalized spikes and the 3-5 Hz-driven network ... 92
d) Physiological and pathological large-scale neuronal network ... 92
e) Limitations and open questions of the study ... 93
i. Spike sorting ... 93
ii. The behavioral relevance of neocortical fast-ripples ... 94
3. General conclusions ... 94
a) Mesial temporal lobe epilepsy is a progressive disorder ... 94
b) Pathological fast-ripples outside of the primary focus and the concept of “epileptic focus” ... 95
4. Ongoing and future studies ... 96
a) Manipulation of the epileptic network ... 96
i. Contralateral hippocampal neuronal bursting before ipsilateral interictal epileptic discharge .... 96
ii. Bursts of action potentials also occur during baseline ... 97
iii. Bursts of action potentials must be theta-locked to be predictive ... 97
iv. Closed-loop in focal epilepsy ... 97
REFERENCES ... 99
F INANCEMENT
Ce projet a reçu le soutien financier du Fond National Suisse pour la recherché scientifique (SNF).
Grant n° 323530_158125.
A CKNOWLEDGEMENTS
Je tiens tout d’abord à remercier Christoph M Michel, qui m’a accueilli dans son laboratoire il y a déjà quatre ans de cela. J’ai toujours été avide de pouvoir discuter des projets, travailler des idées et argumenter sur des questions scientifiques. Christoph s’est toujours montré ouvert et disponible pour ce genre d’exercice, préférant débattre sur des questions plutôt qu’imposer des idées. C’est grâce à cette ouverture, je pense, que nous avons pu entamer un projet sur l’épilepsie chez la souris, alors que nous étions initialement partis pour étudier le système auditif. Reproduire un modèle murin d’épilepsie en laboratoire et améliorer l’EEG de haute densité pour qu’il soit adapté à l’enregistrement de souris éveillées était difficile, parfois décourageant, et Christoph a toujours soutenu mes différentes tentatives, et a pu m’offrir ses conseils précieux notamment pour l’interprétation des premiers signaux électrophysiologiques que nous avons obtenus. J’aurais aimé avoir d’avantage de temps pour recevoir son enseignement sur l’électrophysiologie, notamment chez l’humain, et j’espère en avoir la chance dans un futur proche. Je le remercie également pour la confiance qu’il m’a accordée pour les différents projets « extra-PhD », notamment la création du Young SSN et l’initiative BrainMeOut pour OHBM 2016, pour laquelle j’ai également eu la chance de travailler avec Raphaël Thézé et Aurore Perrault.
J’aimerais également remercier Charles Quairiaux, qui m’a suivi de manière presque journalière (!) durant mon PhD. Je doute d’avoir pu réaliser ce projet sans la patience, les connaissances électrophysiologiques et la confiance que Charles m’a accordée durant ces quatre années. Il s’est montré disponible aussi bien pour les problèmes chirurgicaux que j’ai rencontrés au début de ma thèse (on se souvient des nombreux casques qui se détachaient…), que pour l’interprétation électrophysiologique ou les discusions-débats (parfois animés…) sur des questions scientifiques (mais en fait, c’est quoi l’épilepsie ?). J’aimerais sincèrement le remercier pour sa disponibilité lors de nos nombreuses discussions imprévues sur des analyses en cours, et pour la pertinence de ses remarques (même s’il pouvait m’arriver de prendre du temps à le reconnaitre…).
Merci aussi pour m’avoir motivé à tenter Sierre-Zinal et à reprendre le vélo !
Un grand merci également à Gwenaël Birot, qui a eu la patience de m’enseigner les rudiments de la programmation Matlab, et qui passe encore de nombreuses heures à m’aider. Sa disponilibité et l’aisance qu’il a à trouver des solutions simples à des codes complexes me fascinent et je lui en suis sincèrement reconnaissant.
Je tiens également à remercier tout particulièrement Margitta Seeck, qui m’a soutenu dans mes projets en neurosciences depuis notre travail sur le syndrome de Rasmussen, et qui m’a ensuite apporté régulièrement son aide durant ma thèse, notamment lorsque nous avions besoin d’avis cliniques éclairés. Ce premier projet (Rasmussen) a été déterminant, je crois, pour ma décision d’entamer un projet de recherche, et ensuite me former en neurologie. Merci également à Karl Schaller, qui a régulièrement suivi l’avancée du projet et m’a toujours accueilli avec beaucoup d’intérêt lors de nos entretiens. Je lui suis particulièrement reconnaissant pour la pertinence de nos discussions et sa générosité durant ma thèse, mais également pour m’avoir si bien accueilli en neurochirugie.
J’ai eu la chance durant mes études de médecine de rencontrer et travailler avec Jozsef Kiss, par le biais du Neuroclub et de l’unité « PEC ». Grâce à la dextérité qu’il a à discuter de papiers scientifiques et de recherche en général, il a rapidement éveillé mon intérêt pour la science et m’a énormément apporté durant ma formation prégraduée et post-graduée. Jozsef est assurément une personne déterminante dans mon choix de m’engager dans une formation en science. Je suis encore aujourd’hui avide de ses conseils, et lui serai longtemps reconnaissant de son enseignement et je l’en remercie sincèrement.
Je remercie également Jean-Marc Fritschy, qui m’a gentillement accueilli dans son laboratoire au début de ma thèse pour discuter du modèle murin d’épilepsie que nous avons utilisé, et pour me montrer comment induire l’épilepsie par injection de kainate.
J’aimerais également remercier Julien Bailly, Pierre Mégevand, Oliver Gautschi et Marc Kotowski avec qui j’ai pu m’immerger en neuroscience clinique durant mes études prégraduées.
Enfin, un grand merci à ma famille et à mes proches amis, notamment Xavier, Isaline, Roméo, avec qui j’ai la chance de pouvoir discuter de ma fascination pour les neurosciences, et – bien heureusement – de tant d’autres sujets. Merci à eux et à ma famille pour leur soutien lors des moments de doute !
Enfin, merci au FBMlab pour sa bonne humeur, pour le ski et les after-works d’ABIM ; merci à Gijs Plomp pour son aide en programmation, à Denis Brunet pour son travail si précieux sur Cartool, à toute l’équipe d’épileptologie, à Serge Vulliémoz pour son intérêt pour la science (je prévois d’en abuser prochainement) et pour sa bonne humeur, à Marie-Ange de la Sen pour son aide précieuse.
Merci également à « l’atelier » du CMU, et notamment à Sébastien Pellat pour son aide et sa disponibilité.
R ESUME & C ONTEXT
Les références sont incluses dans la version anglaise uniquement
L’épilepsie est l’une des maladies neurologiques la plus fréquente et peut présenter différentes étiologies, telles que vasculaires, traumatiques, infectieuses ou autres. Le dénominateur commun est une activité anormale et incontrôlée d’une population de neurones, menant à des crises d’épilepsie.
L’épilepsie du lobe temporal représente 40% des cas d’épilepsie et est un type d’épilepsie focale. Dans les épilepsies focales, il est actuellement admis qu’une région spécifique du cerveau est responsable de la génération des crises d’épilepsie. La sclérose hippocampique est retrouvée dans 80% de la population souffrant d’épilepsie temporale. L’électroencéphalographie (EEG, l’enregistrement de l’activité électrique du cerveau) est typiquement utilisée pour identifier les signatures de l’activité épileptique, tels que décharges épileptiques interictales ou ralentissement focal. L’EEG est également utilisée pour identifier et localiser le début des activités ictales, qui peut être soit focal soit généralisé.
Dans les épilepsies focales, plusieurs observations – principalement cliniques – ont amené à reconnaitre que des « réseaux épileptiques » (un ensemble de régions cérébrales interconnectées et sous-tendant à une activité pathologique commune) étaient probablement plus important qu’une seule région cérébrale appelée « foyer épileptique » dans la génération d’activités ictales ou interictales.
Trois observations principales soutiennent cette hypothèse : la persistance de crises d’épilepsie après chirurgie de l’épilepsie, l’existence de déficits neurologiques ne pouvant pas être expliqués par les dysfonctions du foyer épileptique et la persistance, voire l'aggravation, de ces déficits après chirurgie.
Ainsi, il a été montré chez des patients souffrant d’épilepsie temporale et ayant été traités chirurgicalement sans succès que le foyer de récurrence n’était pas toujours localisé dans le même lobe cérébral, ni même dans le même hémisphère que le premier foyer épileptique chirurgicalement réséqué. Bien qu’il soit probable que la majorité des cas de récurrence de crises d’épilepsie soit due à une résection chirurgicale incomplète, il existe donc une proportion non négligeable de patients dont la maladie est plus complexe et où l’expression de crises d’épilepsie ne peut pas s’expliquer par l’activité d’une seule région cérébrale. Concernant les déficits neurologiques, il a été montré dans plusieurs études que les patients épileptiques peuvent présenter des déficits inexplicables par les dysfonctions du foyer épileptique, tels que des déficits moteurs dans l’épilepsie temporale. Ces déficits peuvent néanmoins être expliqués sous l’angle du réseau épileptique. Par exemple, il a été montré que des pointes épileptiques interictales dans l’épilepsie temporale droite pouvaient propager dans le lobe temporal contralatéral, alors que les pointes générées dans le lobe temporal gauche ne propageaient pas ou peu, ce qui était cohérent avec l’observation de déficits contralatéraux chez les patients souffrant d’épilepsie temporale droite et l’absence de déficits contralatéraux chez les patients souffrant d’épilepsie temporale gauche. De plus, il a été démontré dans des cas d’épilepsie focale pharmacorésistante que, même si la suppression des crises d’épilepsie peut être obtenue par chirurgie, les performances cognitives peuvent rester en-dessous des valeurs moyennes. Enfin, différentes observations ont souligné que les épilepsies focales sont probablement des maladies progressives qui peuvent s’aggraver avec le temps. En effet, il a été montré que la durée de l’épilepsie corrélait avec la persistance de crises d’épilepsie après chirurgie et avec l’aggravation des performances cognitives
dans des domaines allant au-delà de la mémoire. La corrélation entre la durée de l’épilepsie d’un côté et le statut post-opératoire ainsi que les déficits cognitifs de l’autre indiquent que le facteur « temps » est crucial dans l’évolution d’une maladie épileptique. Un « point de non-retour » après lequel traiter le foyer primaire devient insuffisant pour contrôler la maladie, à cause du développement de nœuds pathologiques à large échelle, explique probablement la corrélation entre durée de la maladie et la diminution du contrôle des crises d’épilepsie après chirurgie ou l’aggravation du statut neurologique.
Ainsi, bien que plusieurs observations cliniques soutiennent l’hypothèse que des activités pathologiques à large échelle pourraient se développer au cours d’une maladie épileptique focale, plusieurs questions restent sans réponse dans le domaine du développement de réseau épileptique à large-échelle. Les études investiguant l’activité épileptique à large-échelle sont généralement transversales, et n’ont donc pas évalué l’évolution du réseau, tandis que les études longitudinales étudiant le développement d’une activité épileptique se concentrent généralement sur le foyer et n’investiguent que rarement les activités à distance. Ainsi, ni l’émergence d’activités pathologiques en-dehors du foyer épileptique, ni leur persistance après suppression pharmacologique du foyer épileptique dans les phases chroniques n’a jamais été expérimentalement démontrée dans une étude longitudinale in vivo. De plus, si leur dépendance au foyer épileptique primaire était démontrée dans une phase plus précoce, ceci soutiendrait l’aspect progressif de la maladie épileptique, encourageant les interventions précoces chez les patients souffrant d’épilepsie.
Dans ce travail, nous voulions tester l’hypothèse selon laquelle l’épilepsie focale peut mener à la formation d’un réseau épileptique autonome à large échelle. Pour investiguer cette hypothèse, qui représente la question principale de notre travail, nous voulions tester la possibilité que :
l’induction d’un foyer épileptique peut mener à l’émergence d’activités pathologiques en- dehors du foyer épileptique, sous la forme de différents biomarqueurs (voir ci-dessous)
les fast-ripples, qui sont actuellement considérés comme des biomarqueurs spécifiques de la région cérébrale responsable de la génération des crises d’épilepsie sont réellement absents en-dehors du foyer primaire, et ce de manière longitudinale au cours de la maladie
les activités pathologiques à large échelle identifiées au cours de la maladie persistent après l’ablation pharmacologique du foyer primaire
la dépendance des activités pathologiques à large échelle à l’intégrité du foyer épileptique puisse évoluer à travers l’évolution de la maladie.
Dans notre travail sur un modèle murin d’épilepsie du lobe temporal mésial, nous présentons la première démonstration qu’après l’induction d’un foyer épileptique, un réseau épileptique à large échelle s’étendant au-delà du foyer épileptique primaire apparait avant l’apparition des crises d’épilepsie, se développe progressivement et ne peut pas être contrôlé par l’ablation pharmacologique du foyer primaire dans la phase chronique, alors que le contrôle des crises a été obtenu. Le fait que la
même procédure ait amené à une diminution significative des activités pathologiques dans le réseau à un stade plus précoce de la maladie soutient la nécessité d’intervenir tôt dans le traitement curatif des patients épileptiques, afin d’éviter le développement de réseau épileptique étendu.
A BSTRACT & B ACKGROUND
Epilepsy is one of the most frequent neurological conditions and can emerge following various etiologies, such as vascular, traumatic, infectious and many others (Clarke, 2009). The common denominator is the abnormal and uncontrollable activity of a population of neurons leading to epileptic seizures. TLE accounts for 40% of the population with epilepsy, and is a kind of focal epilepsy. In focal epilepsy, it is currently held that one particular brain region is responsible for triggering epileptic seizures. Hippocampal sclerosis is found in 80% of the population with TLE. Electroencephalography, i.e., the recording of the electrical activity of the brain, is typically used to identify signatures of epileptic activities, such as IEDs or focal slowing. EEGs are also used to identify and localize the onset of ictal activities, which can be either focal or generalized.
In focal epilepsy, several observations, mainly clinical, have led to the conception that
“epileptic networks”, i.e., interconnected brain regions that subserve a common pathological activity, are probably more important than a single brain area called “epileptic focus” in causing ictal and interictal activities (Engel et al., 2013; Goodfellow et al., 2016; Richardson, 2012; Spencer, 2002;
Terry et al., 2012). Three main observations support this hypothesis: the persistence of seizures after resective surgery (Hennessy et al., 2000; Janszky, 2004; Jehi et al., 2010; McIntosh et al., 2001), the existence of neurological deficits that cannot be explained by the dysfunctional EF (Coito et al., 2015;
Hermann et al., 2008; Hilger et al., 2016; Lin et al., 2012; Oyegbile et al., 2004; Savage, 2014;
Schoenfeld et al., 1999) and the persistence or even worsening of such deficits despite surgery (Battaglia et al., 2006; Matsuzaka et al., 2001; Miranda and Smith, 2001; Roulet-Perez et al., 2010;
Westerveld et al., 2000).
Indeed, it was shown in patients with TLE who underwent resective surgery for refractory epilepsy but who were not seizure-free after surgery, that the focus of recurrence was not always located in the same lobe, or even in the same hemisphere as the first EF previously resected (Hennessy et al., 2000; Jehi et al., 2010). Thus, while in the majority of cases seizure-recurrence is most probably due to incomplete focus resection, there is a substantial proportion of patients for which the disease is more complex and emergence of seizures cannot be explained by the sole activity of one single brain region. Concerning neurological impairments, it was shown in several studies that patients with epilepsy can endure deficits that cannot be explained by the dysfunctional epileptic focus, such as motor dexterity deficits in TLE (Hermann et al., 2008, 2006; Oyegbile et al., 2004; Schoenfeld et al., 1999). However, they can be understood under the scope of the “epileptic network” concept. For
example, it was shown that IEDs in right TLE propagate to the contralateral temporal lobe, whereas IEDs in left TLE do not, and this was congruent with contralateral neuropsychological deficits in right TLE patients, but not in left TLE (Coito et al., 2015). Furthermore, it was shown that after surgery for refractory focal epilepsy, even if seizure-freedom is obtained (Roulet-Perez et al., 2010), cognitive performance can remain under average scores (Battaglia et al., 2006; Matsuzaka et al., 2001; Miranda and Smith, 2001; Westerveld et al., 2000). Last, different observations have highlighted that focal epilepsies are probably progressive diseases that can worsen over time. Corresponding with this hypothesis, duration of epilepsy in TLE has been shown to correlate with seizure-freedom after resective surgery (Janszky, 2004; Yasuda et al., 2010; Yoon et al., 2003) and worsening of cognitive performance in domains that go beyond memory (Alessio et al., 2004; Hermann et al., 2006; Jokeit and Ebner, 1999; Marques et al., 2007; Meyer et al., 1986; Oyegbile et al., 2004; Van Schooneveld and Braun, 2013). The correlation between epilepsy duration on the one hand, and seizure-freedom after surgery or cognitive impairment in the second hand, indicates that timing is crucial in the evolution of an epileptic disorder. A “point of no return” after which treating the EF is no longer sufficient to cure the disease, i.e., because of the emergence of large-scale pathological nodes, explains probably the correlations between duration of epilepsy and decrease of seizure-freedom after surgery or worsening of the neurological status.
Thus, although several clinical evidence support the hypothesis that large-scale pathological activities might emerge along the progression of a focal epileptic disease, several questions remain unanswered in the field of large-scale EN development. Studies investigating large-scale epileptic activity are usually cross-sectional, and thus cannot evaluate the development of the EN, whereas longitudinal studies investigating the emergence of epileptic activity focus generally on the EF and rarely look at remote pathological consequences. Hence, neither the emergence of epileptic activity remote from the EF, nor their persistence after pharmacological silencing of the EF in the chronic stage of the disease has been demonstrated in a longitudinal in vivo study. Furthermore, if their dependence on the EF at an earlier stage of the disease was shown, this would argue for a progressiveness of the epileptic disease, prompting for early intervention in epileptic patients. In our work, we wanted to test the hypothesis that focal epilepsy can lead to the formation of a large-scale, self-sustained epileptic network. To test this working hypothesis, which represents the main question of our research, we wanted to test:
whether the induction of an EF can lead to the emergence of pathological activities outside of the EF, in the form of specific epileptic biomarkers (see below)
whether FRs, which are currently held as specific biomarkers of the seizure-onset zone, are truly absent outside of the primary EF along the evolution of the disease
whether the large-scale pathological activities identified along the evolution of the disease persist after pharmacological removal of the primary EF
whether the dependence of the large-scale pathological activities on the integrity of the EF can evolve through the disease.
In our work on a mouse-model of MTLE (Arabadzisz et al., 2005; Riban et al., 2002), we present the first experimental demonstration that after the induction of a focal epilepsy, a large-scale EN extending beyond the primary EF appears before the emergence of epileptic seizures, develops progressively and cannot be controlled by silencing the primary EF in the chronic stage of the disease, although seizure-control is attained. The fact that the same procedure leads to a significant decrease of pathological activities in the network in the early stage of the disease pleads for early intervention in epileptic patients, in order to avoid the development of extended pathological networks.
A BBREVIATIONS
AP antero-posterior
CA cornu ammonis
CSD current-source density
DBS deep-brain stimulation
DG dentate gyrus
Dxx day (day 7, day 14, day 28)
EEG surface EEG
EEG-iEEG combined surface-intracerebral EEG
EF epileptic focus
EN epileptic network
FC frontal cortex
FRs fast-ripples
GFP global-field power
GrDG granular cell layer of the dentate gyrus
GS generalized spikes
HFO high-frequency oscillations
HS hippocampal sclerosis
IED interictal epileptic discharges
iEEG intracerebral EEG
IP intraperitoneal
IQ interquartile range
Lcglt left cingulate cortex
LFP local-field potential
LH left hippocampus (kainate-injected hippocampus)
LM1 left primary motor cortex
ML medio-lateral
ms milliseconds
MTLE mesial temporal lobe epilepsy
MUA multi-unit activity
PAC phase-amplitude coupling
PYR pyramidal cell layer of the hippocampus
RH right hippocampus
s seconds
SD standard deviation
TAAHC topographic atomize & agglomerate hierarchical clustering
TLE temporal lobe epilepsy
TTX tetrodotoxine
VMI visual motion index
I NTRODUCTION
1. General considerations on epilepsy
a) Definition
i. Clinical definition
Epilepsy is defined by a lasting susceptibility of the brain to produce seizures (Fisher et al., 2014). Seizures are defined by the abnormal and uncontrolled synchronous activation of a population of neurons, which leads to epileptic symptoms (Fisher et al., 2014; Scharfman, 2007). Epileptic symptoms vary widely and depend on the brain region affected by the disease. For example, specific motor symptoms, such as uncontrolled head and eye turning with movement of the arms are usually associated with an EF in the supplementary motor area (Ropper and Brown, 2005). Olfactory symptoms, salivation, mastication and speech arrest are frequently associated with a mesial temporal lobe or opercular localization (Ropper and Brown, 2005). Cognitive deficits, which can include attentional and memory deficiencies, as well as concentration problems and the ability to think (Bell et al., 2011), represent a frequent interictal co-morbidity in certain epileptic disorders, and are now part of the definition of epilepsy (Bell et al., 2011; Fisher et al., 2014; Holmes, 2015; Lin et al., 2012). In children and in adult patients with epilepsy, 30% and 20% of them respectively present learning or neurological deficits (Clarke, 2009).
The clinical definition of epilepsy implies at least one epileptic seizure (Fisher et al., 2005, 2014), but the diagnosis is based on the persistent susceptibility of the brain to elicit seizures, indicating that at least two unprovoked seizures must occur at least 24 hours apart (Fisher et al., 2005).
On a therapeutical perspective, it is more important to define the risk of recurrence, as this will determine the relevance of an immediate treatment after the first unprovoked seizure. In children, it has been shown that seizures occurring during sleep, past history of febrile seizures, Todd’s paresis1 and onset before 3 years were associated with a risk of recurrence after a first unprovoked afebrile seizure (Shinnar et al., 1996). Current studies are investigating biomarkers of recurrence after a single epileptic seizure, and it has been shown that a high risk of recurrence is associated with a seizure
1 Todd’s paresis corresponds to a focal weakness appearing in the post-ictal state
occurring > 1 month after a stroke, a seizure occurring in the context of a structural abnormality, or associated with epileptiform activity in the EEG (Fisher et al., 2014). The identification of biomarkers of recurrence is an active field of research.
Remission is obtained after a seizure-free period of at least 10 years without anti-epileptic drugs needed for the last 5 years, or after a patient suffering from an age-dependent epileptic syndrome is older than the pertinent age, and does not endure seizures any more (Fisher et al., 2014).
ii. Neurophysiological definition
The electrophysiological signature of epileptic activity can vary widely. Epileptic activity can be of interictal or ictal origin. Epileptic seizures define the ictal state, whereas interictal activity represents the period between seizures. Interictal epileptiform discharges are typical epileptic paroxysms, i.e., transient electrophysiological activities seen more frequently in a population with epilepsy than in a control population. They will be called either interictal spikes or interictal epileptiform discharges in the present work. They are believed to correspond to the summated potential field of a population of aligned pyramidal cortical cells (Tao et al., 2007). In the scalp or iEEG, they appear as sharp events of high amplitude, typically > 50 μV in scalp EEG (de Curtis and Avanzini, 2001) and can last up to 250 ms (Staley et al., 2011). High-frequency bursts of action potentials (> 200 Hz) can be seen superimposed over the discharge (de Curtis and Avanzini, 2001).
Using simultaneous scalp and intracranial EEG recordings in epileptic patients undergoing presurgical evaluation of epilepsy, it was shown that the brain area necessary to generate a visible epileptic spike on scalp EEG has to be > 10 cm2 (Tao et al., 2007). IEDs can remain localized to their site of generation, or propagate to remote areas, or virtually to the whole cortex, supposedly through subcortical structures (de Curtis and Avanzini, 2001).
Another interesting paroxysm associated with epileptic activity is focal slowing. In a MEG study of patients with MTLE, it was shown that focal slowing, characterized by high-amplitude activities below 7 Hz, co-localizes with the cerebral source estimated with interictal spike activity (Ishibashi et al., 2002). Different interictal paroxysms and abnormal activities at seizure onset were analysed in a large cohort of 224 patients (Hughes, 1985). Among other paroxysms, hypsarrythmia and spike-and-wave were two frequent EEG patterns in this heterogeneous population of epileptic patients (Hughes, 1985). Hypsarrythmia is a chaotic EEG pattern characterized by high-amplitude, disorganized EEG activity (Shields, 2006) and is specific for infantile spasms, typically seen in West syndrome, an epileptic syndrome with poor prognosis (Clarke, 2009).
Other epileptic biomarkers under intense scrutiny are high-frequency oscillations (Bragin et al., 1999; Jacobs et al., 2010). They will be specifically addressed later in this work (“Fast-ripples as a marker of epileptogenic brain areas”).
Ictal activity does not correspond to an accentuation or increased frequency of IEDs, and different mechanisms are believed to underlie both activities (de Curtis and Avanzini, 2001), although
the large-scale hemodynamic changes related to both activities may be comparable (Tousseyn et al., 2015). In MTLE, the most frequent ictal patterns seen at seizure onset are rhythmic alpha-theta (57%
of cases) and rhythmic delta (43% of cases) (Malter et al., 2016). However, in this cohort of 63 patients with a total of 219 seizures, clinical symptoms were observed before EEG onset in 53% of seizures, indicating that other abnormalities associated with seizure onset are still unidentified in the EEG (Malter et al., 2016).
b) Epidemiology
Epilepsy is one of the most frequent neurological conditions, with a varying prevalence dependent on the medical resources, on which depends the ability to correctly identify and diagnose the affected individuals. Endemic diseases in certain regions of the world may also affect the prevalence of epilepsy (Banerjee et al., 2009). An estimated 50 million people worldwide are affected by epilepsy (Ladino et al., 2014). For a given individual, the cumulative risk to develop epilepsy over a lifetime is 3-5% (Clarke, 2009). In the United States, up to 1% of the population will suffer from epilepsy by the age of 20 (Ropper and Brown, 2005). On the whole, the prevalence is estimated between 2.7 to 3.3 per 1000 (Banerjee et al., 2009). It increases during adolescence and after age 60 (Banerjee et al., 2009; Ropper and Brown, 2005). Epilepsy does not remit in 20% of patients who develop it (Clarke, 2009). The aetiology is not known in the majority of cases (Banerjee et al., 2009).
The mortality is 2-3 times higher in patients with epilepsy than in the control population (Clarke, 2009). Common epileptic disorders are discussed below.
c) Focal and generalized epilepsies
Epilepsies are typically divided in two classes depending on the generalized or the focal origin of seizures. Epilepsies with a focal origin typically have a seizure onset zone limited to one brain region, such as the motor cortex or mesial temporal lobe. On the other hand, generalized epilepsies encompass a diversity of epileptic disorders characterized by a diffuse, i.e., generalized cerebral involvement at seizure onset, which is represented as generalized spike-and-wave in the scalp EEG (Ropper and Brown, 2005). Whether the disease is of focal or generalized origin, patients may lose consciousness during the ictal event: this kind of epileptic seizure is called complex. Whereas focal seizures may or may not induce a loss of consciousness, generalized seizures are usually associated with an altered state of consciousness. In all age groups, complex focal epilepsies are the most frequent type (Ropper and Brown, 2005). The distinctness between focal and generalized seizures may be difficult. Recent results have shown that focal onsets are seen in certain types of generalized epilepsy (Blumenfeld et al., 2003; Meeren et al., 2002). Indeed, Meeren and colleagues (2002) showed in a genetic rat model of absence epilepsy, a typical generalized epileptic syndrome, that a cortical focus located in the somatosensory area preceded the activation of the thalamus, and was thus
considered to lead the epileptic slow-wave discharges generated by this cortico-thalamo-cortical loop.
A time-delay of ~500 milliseconds separated the cortical and thalamic involvement (Meeren et al., 2002). Thus, the rapid propagation and involvement of distant brain regions at the onset of generalized seizures may lead to incorrectly diagnosed generalized epilepsies.
d) Common epileptic disorders
The cause of epilepsy is greatly influenced by the age at presentation. In children, congenital and neonatal origins are the most frequent origins, whereas vascular disease are increasingly more prevalent in the older population (Clarke, 2009). Altogether, idiopathic epilepsies2, which are believed to have a strong genetic basis, account for 10-30% of epilepsies (Clarke, 2009). Vascular disorders are second (10-20%) and HS, which constitutes the main topic of the present work, comes third, accounting for 5-10% of all cases of epilepsy (Clarke, 2009). The fact that idiopathic epilepsies are among the most frequent is very interesting in regard to the primary topic of this work, i.e., EN.
Indeed, genetic abnormalities are more likely to affect more than one single brain region (as seen for example in tuberous sclerosis), and thus may be a typical case where several pathological hubs interact to form an EN.
In our work, we decided to focus on one of the most frequent epileptic syndrome, the MTLE, for which HS is the most frequent cause. To investigate the existence, development and extent of large-scale EN, we used large-scale recordings (high-density, surface EEG recordings) as well as intracerebral, multi-sites EEG recordings. In the following section, we begin with a description of the properties of EEG recording. Following on this, we present the functional neuroanatomy of the hippocampus and its major inputs and outputs in physiological conditions. After this presentation, we will address the core of the study, i.e., EN in TLE.
2. Electrophysiology
Electrophysiology is the method used to record the electrical activity of the brain.
Communication and interaction between neurons is mainly based on chemical signals at the level of synapses (although electrical communication through GAP junctions3 also exists). However, the release of neurotransmitters at the level of synapses depends on the depolarization of the synaptic bouton. The propagation of electrical activity along the neuron, which eventually leads to the depolarization of the synaptic bouton, induces a dipole that can be recorded either intracellularly or extracellularly. Two main types of neuronal electrical activities can be recorded, namely the post- synaptic activity (i.e., dendritic) which gives rise to LFP and the pre-synaptic activity (i.e., axonic),
2 Idiopathic epilepsies, in contrast with “symptomatic” epilepsies, are diseases with no identified cause.
3 GAP junctions are ionic transmembrane channels through which ions can travel from one neuron to another
which gives rise to MUA (Christoph M. et al., 2009). Low-frequency activity between 1-100 Hz is believed to be composed of dendritic activity, whereas very high frequency activity above 600 Hz is believed to represent action potentials, although recent evidence has suggested that dendritic activity might also be present in very high frequencies > 100 Hz (Scheffer-Teixeira et al., 2013). Hence, the frequency bands between 100-600 Hz are made of mixed activities (dendritic and synaptic), composed of ripples (80-200 Hz) and FRs (200-600 Hz), which are believed to represent synchronized population spikes (see below). The ability of an electrode to record a dipole depends on the amplitude of this dipole, and on the position of the electrode in regard to that dipole (the “solid angle”) (Gloor, 1985). It is assumed that action potentials cannot be recorded with surface EEG, given the low amplitude of these events, but a recent paper has reported the ability of scalp EEG to record FRs, which are believed to represent synchronized action potentials (see below) (Pizzo et al., 2016). In theory, this is possible and depends greatly on the number of cells that express an action potential within a common temporal window (Gloor, 1985).
LFP (1-100 Hz) is classically divided into 5 main frequency bands: (δ) 0.1-4 Hz, (θ) 4-7 Hz, (α) 7-12 Hz, (β) 12-20 Hz and (γ) 20-100 Hz. Specific functions are attributed to these different rhythms, although the boundaries can vary, notably across species. For example, theta activity has been shown to be important in memory formation (see below and (Buzsáki and Moser, 2013)) and alpha activity is implicated in cognitive functions such as gating of sensory information (Sadaghiani et al., 2012) or the temporal resolution of visual processing (Samaha and Postle, 2015).
In clinic, scalp EEG, electro-corticogram (i.e., electrodes positioned directly over the brain surface) and intracerebral recordings are used. EEG offers a high sampling frequency, which can be high enough to record action potentials generated by single neurons. However, given the low amplitude of these events, the recording electrode must be located close to the neuronal generator4. Scalp EEG has the disadvantage to be far away from these generators, and hence to be unable to record action potentials. However, it offers the possibility to obtain a wide coverage of surface brain (i.e., scalp) activity. To combine scalp EEG and intracerebral microelectrodes allows obtaining a large surface coverage together with a high temporal sampling of specific brain regions. Whereas intracerebral recording is limited in humans, this combination is possible in animal research.
3. The hippocampus as a major hub of the limbic network
a) Functions of the hippocampal formation
In normal conditions, the hippocampus, and more generally the hippocampal formation, is mainly implicated in memory formation and spatial navigation (Bird and Burgess, 2008; Buzsáki and
4 Or, the neuronal generators must express action potentials in a synchronized temporal window (Gloor, 1985)
Moser, 2013; Hasselmo, 2005). These complex cognitive functions rely on intact structural and functional connections between the hippocampus and distant brain regions. As examples, it has been shown that memory formation involves connections with, notably, prefrontal regions (Preston and Eichenbaum, 2013) and spatial navigation involves connections with the entorhinal cortex (Brun et al., 2002).
b) Structural neuroanatomy of the hippocampal formation
In humans and mice, the hippocampal formation is located in the mesial parts of the temporal lobes. It is made of an “archi-cortex” composed of 3 distinct layers at least for the dentate gyrus (Fig 1).
Figure 1: Trisynaptic circuit of the hippocampus
The entorhinal cortex projects to the granule cells of the DG through the performant path. The granule cells then project to the CA3 cell layer (mossy fibers). The Schaffer collaterals come from the CA3 neurons that project to the CA1 pyramidal cell layer, which then send back axons to the
entorhinal cortex through the subiculum.
The dentate gyrus includes a molecular layer, a granular cell layer and a polymorphic layer (Amaral et al., 2007). The cornu ammonis is made of three subfields (CA1, CA2 and CA3) which are divided into 4 layers (oriens, pyramidal cells, radiatum and lacunosum-moleculare layer, the last being the closest to the dentate gyrus) (Amaral et al., 2007). The CA3 also includes a lacunosum layer between the pyramidal cells and the radiatum layers (Amaral et al., 2007). In rodents, the hippocampal formation is C-shaped and runs from the “septal” part (i.e., dorsal) to the “temporal” regions (i.e., ventral). The hippocampus is part of the limbic system, which comprises medial cortical and subcortical regions of the brain. Among them, the main structures of the limbic system include (Andersen et al., 2007; Martin, 2003):
the limbic association cortex o cingulate gyrus
o parahippocampal gyrus
the amygdala
the ventral striatum
specific nuclei of the thalamus and the hypothalamus
the epithalamus
the septal nuclei
the midbrain periacqueductal gray matter
the hippocampal formation o subiculum
o entorhinal cortex o hippocampus
The entorhinal cortex is the main output and the main input structure of the hippocampal formation. The hippocampal formation receives afferent connections from various brain regions, which converge to the entorhinal cortex (van Groen et al., 2003; Martin, 2003). Axons of the entorhinal cortex then form the performant path that projects in the hippocampus (van Groen et al., 2003). The hippocampal formation has two main efferent pathways:
through the entorhinal cortex, the hippocampal formation is connected to (Bird and Burgess, 2008):
o the parahippocampal gyrus o the perirhinal cortex
which themselves are connected to neocortical structures of the temporal lobe (Parent et al., 2009).
through the fornix, the hippocampus is connected to (Bird and Burgess, 2008):
o the mammillary bodies, that project to the anterior nucleus of the thalamus which then projects to the cingulate cortex
o the medial prefrontal cortex (Parent et al., 2009) o the septal nuclei
o the contralateral hippocampus
The intrinsic connectivity of the hippocampus has been extensively described (Scharfman, 2002). As shown in Fig 1, the entorhinal cortex sends axons through the performant path to granule cells of the dentate gyrus. The output of the granule cells, the mossy fibers, then contacts the pyramidal cells of the CA3 of the hippocampus. Finally, axons of the pyramidal cells, called the Schaffer collaterals, contact the pyramidal cells of the CA1 of the hippocampus. Output fibers then reach the subiculum, which contact brain areas located outside of the hippocampal formation (Martin, 2003). A more exhaustive description of parahippocampal and hippocampal connectivity can be found here (Moser et al., 2014). CA3 pyramidal neurons also receive projections from the medial septal nucleus and the nucleus of the diagonal band of Broca (Andersen et al., 2007).
c) The human hippocampal commissure
i. Inter-hippocampal structural connectivity in humans
Studies on the structural and functional connectivity between both hippocampi provided contrasting results. The hippocampal commissure can be divided into two subcategories, forming either the ventral commissure, whose fibers connect homotopic regions of the hippocampi (e.g., the cornu ammonis) and heterotopic regions (cornu ammonis and entorhinal cortex), or the dorsal commissure, whose fibers originate from the entorhinal cortex, presubiculum and parahippocampal gyrus and end mainly in the contralateral entorhinal cortex (Andersen et al., 2007; Gloor et al., 1993;
van Groen et al., 2003). Hippocampal connections are rare in the non-human primate (Wilson et al., 1990) and are suspected to be absent in humans according to certain authors (Andersen et al., 2007).
The ventral commissure in particular has significantly decreased in size in humans (Gloor et al., 1993;
Suárez et al., 2014). A systematic anatomo-functional study of the dorsal and ventral commissures in human epileptic patients could not clearly identify the ventral commissure, and concluded that it may be nonexistent (Gloor et al., 1993). However, the dorsal commissure was clearly identified and followed the same path as described in monkeys, which led the authors to conclude that it also originates from the entorhinal cortex, presubiculum and parts of the parahippocampal gyrus, and terminates in the contralateral entorhinal cortex.
ii. Inter-hippocampal functional connectivity in humans
Single pulse stimulation of temporal lobe areas failed to reveal a functional connectivity between mesial temporal regions in one human study (Wilson et al., 1990). In a more recent publication, up to 7% of stimulated sites in the mesial temporal lobe showed a contralateral response (Jiménez-Jiménez et al., 2015), which remains very low. The difference between these two studies
might be, at least partially, due to weaker stimulation parameters in (Wilson et al., 1990) (amplitude:
4-8 mA vs 0.25-5 mA and duration 1 ms vs 0.1 ms). However, it was demonstrated in epileptic patients that almost 10% (20/220) of mesial temporal lobe seizures spread first to the contralateral mesial temporal lobe and only after to ipsilateral neocortical temporal regions (Gloor et al., 1993). The inverse, i.e., first spread to the ipsilateral neocortical temporal areas then contralateral mesial temporal lobe, represented only 3% (6/220) of seizures (Gloor et al., 1993). In a more recent study on MTLE, it was shown that 42% of seizures propagate to the contralateral side with a median time-delay of 10 seconds (Malter et al., 2016). Hence, single pulse stimulation may not be strong enough to elicit a contralateral propagation, although epileptic seizures are. The authors concluded that the dorsal hippocampal commissure allows these propagations: a propagation through the corpus callosum is excluded by the fact that it does not contain inter-hippocampal fibers, and only a minority of parahippocampal and amygdala fibers crosses the midline through the anterior commissure (Gloor et al., 1993). The posterior commissure is not discussed in this article, but is known to carry mainly axons from pretectal neurons implicated in the pupillary reflex, which makes it a poor candidate for inter-hippocampal communication. On the whole, evidence exists that propagation of epileptic activity from one hippocampus to the contralateral occurs in patients. Less ecological testing, such as single pulse stimulation, may underestimate the degree of interhippocampal connectivity.
Coherence, i.e., correlation of frequency power between bilateral regions of the CA1 of both hippocampi, in the frequency range of theta (6-9 Hz) and gamma (40-100 Hz), was demonstrated in mice (Buzsáki et al., 2003). In humans, interhippocampal coherence was shown for lower frequencies (0.5-2 Hz) (Moroni et al., 2012).
d) Theta-rhythm
i. Theta-rhythm in physiological conditions
Very interestingly, one of the main functions of the hippocampus, i.e., memory formation, relies on a particular rhythm called θ-rhythm (Bird and Burgess, 2008; Buzsáki and Moser, 2013).
Theta-rhythm is believed to be necessary for the temporal organization of neuronal assemblies coding for the “successive information bits of a specific memory”5 (Buzsáki and Moser, 2013). This rhythm (Fig. 2) corresponds to an oscillation recorded in the hippocampus, with phase values of ~80-250 ms (4-12 Hz) (Montgomery et al., 2008; Sheremet et al., 2016), or 80-140 ms (4-7 Hz) (Hasselmo, 2005;
5 This is a “crude” summary of how memory is stored. The review by Buzsáki and Moser (2013) presents in a very interesting way the relation between storage of navigation maps and specific items of episodic memory. Navigation maps are stored in a complex network involving the entorhinal cortex and
hippocampus and rely on the integrated activity of different cells coding for different locations within a defined area. Along a straight path, a sequential firing of different neurons is observed, each neuron firing for a given location along the linear path. The same procedure is believed to happen for the storage of memory: each “information bit” is stored successively by different “neuronal assemblies”, whose organization is believed to depend upon theta-activity.
Kahana et al., 1999; Kamondi et al., 1998) depending on the definition. The highest amplitude is recorded in the stratum lacunosum-moleculare of the hippocampal CA1 region (Buzsáki, 2002) as well as in the hippocampal fissure and hilus, which are close to the dentate gyrus (Buzsáki et al., 2003). The minimal amplitude is seen right below the pyramidal layer of the CA1 (Buzsáki et al., 2003). Theta-rhythm can be recorded elsewhere, notably in the entorhinal cortex (Buzsáki, 2002).
Theta-rhythm is believed to originate from pacemakers cells located outside of the hippocampal formation in the medial septum-diagonal band of Broca (Buzsáki, 2002; Colgin, 2016). These GABAergic neurons project to interneurons of CA1, CA3 and dentate gyrus, hence disinhibiting the hippocampal pyramidal cells (Buzsáki, 2002; Colgin, 2016).
Figure 2: Theta rhythm in the normal hippocampus
Theta rhythm in the normal hippocampus presents maximal amplitude close to the hilus and
hippocampal fissure. Here, we used a linear probe to record from the most superficial to the deepest regions of the mouse hippocampus. The 2-3 first electrodes are located in the over-lying neocortex.
Theta-rhythm is implicated in memory processing, navigation, locomotor activity (Bird and Burgess, 2008) and rapid-eye movement sleep (Montgomery et al., 2008). A recent report has shown that theta- rhythm can also be locally generated by pyramidal cells of the CA1 of the hippocampus in vitro (Goutagny et al., 2009).
ii. Theta-rhythm in pathological conditions
Given that theta activity is inherent to hippocampal functioning, it is crucial to ask whether theta might be modified or influenced by epileptic activity and whether it might influence the epileptic threshold. In the kainate mouse-model of HS (see chapter 10), theta activity in the injected
hippocampus has been shown to be significantly lower than in the contralateral, non-injected side (Haussler et al., 2012; Riban et al., 2002). The contralateral hippocampus also shows a significant decrease of theta activity (in comparison to non-injected or saline-injected animals), yet still significantly higher than theta in the ipsilateral hippocampus (Arabadzisz et al., 2005). In control animals, theta activity between the dentate gyrus and the entorhinal cortex of the same hippocampus presents a phase-lag close to zero, whereas this synchrony is significantly different in epileptic hippocampi (Froriep et al., 2012). Hence theta activity is not only decreased, but also altered, at least in the injected hippocampus6.
An interesting study showed that induction of hippocampal theta activity, either by septal injection of carbachol, a cholinergic agonist, or electrical low frequency (4-8 Hz) stimulation of septal nuclei could stop an ongoing epileptic seizure in a rat model of epilepsy (pentylenetetrazol ip) (Miller et al., 1994), suggesting that theta activity could have anticonvulsant effects. However, such a finding contrasts with the observed increase seizure susceptibility during rapid-eye movement sleep, a sleep state typically associated with high theta (Miller et al., 1994), in a rat model of TLE (Sedigh- Sarvestani et al., 2014). Another study demonstrated in rats that theta power increases in the pre-ictal state (Broggini et al., 2016). Hence, contrasting results exist concerning the potential role of theta activity in susceptibility or protection against seizures. Whether theta-rhythm decreases or increases the risk of epileptic activity probably depends on many different factors. However, it is interesting to note that this rhythm may affect the epileptic threshold.
4. Temporal lobe epilepsy
a) Epidemiology and clinical presentation
The present work focuses on MTLE, one of the most frequent type of focal epilepsy. Up to 40% of adult epileptic patients suffer from TLE, and the disease represents a prevalence of about 1.7 per 1000 people (Ladino et al., 2014). TLE can be of neocortical origin or from mesial parts of the temporal lobe. MTLE associated with HS is the most frequent type of TLE (Clarke, 2009), and corresponds to the pathology studied here. Patients with MTLE typically experience an aura followed by complex partial seizures. The aura corresponds to the initial symptoms preceding the actual seizure, which may be an epigastric discomfort, hallucination, illusion or others (Ropper and Brown, 2005). There may not be a true loss of consciousness, and rather an abnormal state of consciousness, for which the patients are later found amnesic (Ropper and Brown, 2005). During the seizure, patients can typically present oro-alimentary automatisms, such as chewing or swallowing, gestural automatisms or verbal automatisms (Clarke, 2009). At seizure onset, the EEG presents a typical
6 Note however that a phase-lag close to zero should be interpreted carefully, given the use of a common reference in this study; a lack of phase-lag should be considered as a mere electromagnetic contamination.
rhythmic 5-7 Hz discharges pattern in medial temporal lobe derivates (Clarke, 2009). Patients can present secondary generalized seizures. Neurological co-morbidities, which occur in the interictal state, are frequent in HS. Very interestingly, their nature goes beyond the primary functions of the hippocampus, suggesting that other brain regions are affected in this disease. They are discussed in the following chapter (“Cognitive co-morbidities as a consequence of extended epileptic network activity”).
The most common cause of TLE is HS, a pathology characterized by atrophy and gliosis of different structures of the mesial temporal lobe, including the hippocampus, parahippocampal gyrus and the entorhinal cortex (Tatum IV, 2012). HS accounts for at least 80% of all cases of TLE (Tatum IV, 2012) and for up to 10% of adults with newly diagnosed focal epilepsy (Walker, 2015). This prevalence, in comparison to the higher prevalence of TLE in epileptic adults (40%, see above) indicates that other epileptic disorders are probably more likely to remit than TLE.
A particular feature of TLE is that HS is highly suspected to be triggered by an initial acute event. Traumatic brain injury (Lowenstein et al., 1992), status epilepticus (Clarke, 2009; Milligan et al., 2009; Pohlmann-Eden, 2004), and more specifically febrile status epilepticus are highly suspected to favour the subsequent development of HS (Ladino et al., 2014; Lewis et al., 2014; Tatum IV, 2012), although a common pathology to both febrile status epilepticus and HS could also explain the association (Kasperaviciute et al., 2013). In this study (Kasperaviciute et al., 2013) the authors performed a genome-wide association study comparing patients suffering from TLE with HS and history of febrile seizures versus controls, and could highlight a significant association between patients with HS + febrile seizures and a specific variant in SCN1A, which codes for a sodium- channel. The variant seems to be specific for patients with HS + febrile seizures, as it was absent in patients with HS without febrile seizures or febrile seizures alone (Kasperaviciute et al., 2013).
b) Treatments of TLE
A particularly problematic characteristic of TLE is the fact that it has a low rate of medical control, as only 11%-42% of patients will become seizure-free with antiepileptic drugs (Tatum IV, 2012). In a review on resective epilepsy surgery for focal epilepsy, the authors reported even more troubling results, with a rate of seizure-control in TLE ranging from 0-8% with medical treatment, which was significantly lower than surgery (58-73%), after a follow-up of 1 to 2 years depending on the study (Jobst and Cascino, 2015). Pharmacoresistant epilepsy is defined by the incapacity to achieve seizure control despite the correct use of two different antiepileptic drugs (Potschka and Brodie, 2012). Based on the time to treatment failure, lamotrigine is considered the first-line medical treatment before carbamazepine, gabapentin, oxcarbazepine or topiramate in patients with focal epilepsies (Marson et al., 2007).
Given the low rate of control using antiepileptic drugs, the curative treatment of HS is the surgical resection of the epileptogenic brain region (Adada, 2008; Jobst and Cascino, 2015; Spencer
and Burchiel, 2012). It is estimated that 60-70% of patients will be seizure-free after resection (Janszky, 2004; Jobst and Cascino, 2015; McIntosh et al., 2001; Wiebe et al., 2001). This remains stable at least 2 years after surgery, but then drops to 40-50% at 10 years (Chang et al., 2015;
McIntosh, 2004).
c) Significant proportion of relapse after surgery in TLE
The reason why patients relapse several months to years after surgery is poorly understood and probably multifactorial (Janszky, 2004; Ramos et al., 2009). The first explanation is incomplete focus removal, especially when it is close to eloquent cortices. In a large cohort including 497 patients who underwent anterior temporal resections for refractory epilepsy, the outcome showed a seizure-free rate of only 55% at 5 years (de Tisi et al., 2011). In a smaller series of 282 patients who underwent surgery for pharmacoresistant TLE, 20% continued to endure seizures at least monthly, with an interval between surgery and reassessment ranging from 3 to 17 years (Hennessy et al., 2000). However, in this series incomplete focus resection cannot account for all relapses, as 30% of patients had recurring seizures from the contralateral hemisphere (Hennessy et al., 2000). Among those with ipsilateral recurrent seizures, 80% had a remaining focal activity in the temporal lobe, indicating that ~20% of patients with ipsilateral recurrence presented seizures starting outside of the initial EF (Hennessy et al., 2000). Even more interesting is the fact that among patients with recurrent ipsilateral epileptic activity, many presented EEG abnormalities, such as generalized seizures, and experienced symptoms, notably cognitive impairment, that suggested an “epileptic encephalopathy” (Hennessy et al., 2000), which could be defined as a global disorder of the brain consecutive to the epileptic condition. In a similar study evaluating failed surgery in TLE, the focus of recurrence could not be identified in 35% of cases; of them, 44% had presented no seizure during the evaluation, indicating that up to 20% of recurrence are due to non-localizable EEG or discordant EEG and imaging evaluation (Jehi et al., 2010). Even among those with an identified focus of recurrence (n=44), 7 presented a contralateral focus (Jehi et al., 2010). Altogether, these two large series indicate that relapse after surgery in TLE could not be always attributed to incomplete focus removal. The following section addresses the other possible mechanisms promoting the reappearance of seizures after surgery.
d) Recurrence after surgery not consecutive to incomplete focus resection
Thus, while the EF explains the majority of seizure onsets, a considerable proportion of seizure recurrence and persisting behavioural deficits (see below) after resective surgery cannot be explained by the dysfunctional EF. What are the mechanisms leading to persisting ictal activity (and neurological deficits, see below) after presumably complete focus removal? Can we expect these mechanisms to be progressive, i.e., to induce the emergence of persisting epileptic symptoms after
