Coupling between gamma-band power and cerebral blood volume during recurrent acute neocortical seizures

Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using non-invasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (>30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2-dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25-90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue

Dysfunction of neurovascular/metabolic coupling in chronic focal epilepsy

In this study, we aim to evaluate the mechanisms underlying the neuro-vascular/metabolic coupling in the epileptogenic cortices of rats with chronic focal epilepsy. To that end, we first analyzed intracranial recordings (electrophysiology, laser Doppler flowmetry and optical imaging) obtained from the seizure onset zones during ictal periods and then used these data to fit a metabolically-coupled balloon model. This biophysical model is an extension of the standard balloon model with modulatory effects of changes in tissue oxygenation, capillary dynamics and variable O2 extraction fraction. As previously reported using acute seizure models, we found that there is a significant higher contribution from high local field potential frequency bands to the cerebral blood flow (CBF) responses in the epileptogenic cortices during ictal neuronal activities. The hemodynamic responses associated with ictal activities were distance-dependent with regard to the seizure focus, though varied in profiles from those obtained from acute seizure models. Parameters linking the CBF and relative concentration of deoxy-hemoglobin to neuronal activity in the biophysical model were significantly different between epileptic and normal rats. In particular, we found that the coefficient associated with the strength of the functional hyperemic response was significantly larger in the epileptogenic cortices, although changes in hemoglobin concentration associated with ictal activity reflected the existence of a significantly higher baseline for oxygen metabolism in the epileptogenic cortices

Seizure epicenter depth and translaminar field potential synchrony underlie complex variations in tissue oxygenation during ictal initiation

Whether functional hyperemia during epileptic activity is adequate to meet the heightened metabolic demand of such events is controversial. Whereas some studies have demonstrated hyperoxia during ictal onsets, other work has reported transient hypoxic episodes that are spatially dependent on local surface microvasculature. Crucially, how laminar differences in ictal evolution can affect subsequent cerebrovascular responses has not been thus far investigated, and is likely significant in view of possible laminar-dependent neurovascular mechanisms and angioarchitecture. We addressed this open question using a novel multi-modal methodology enabling concurrent measurement of cortical tissue oxygenation, blood flow and hemoglobin concentration, alongside laminar recordings of neural activity, in a urethane anesthetized rat model of recurrent seizures induced by 4-aminopyridine. We reveal there to be a close relationship between seizure epicenter depth, translaminar LFP synchrony and tissue oxygenation during the early stages of recurrent seizures, whereby deep layer seizures are associated with decreased cross laminar synchrony and prolonged periods of hypoxia, and middle layer seizures are accompanied by increased cross-laminar synchrony and hyperoxia. Through comparison with functional activation by somatosensory stimulation and graded hypercapnia, we show that these seizure-related cerebrovascular responses occur in the presence of conserved neural-hemodynamic and blood flow-volume coupling. Our data provide new insights into the laminar dependency of seizure-related neurovascular responses, which may reconcile inconsistent observations of seizure-related hypoxia in the literature, and highlight a potential layer-dependent vulnerability that may contribute to the harmful effects of clinical recurrent seizures. The relevance of our findings to perfusion-related functional neuroimaging techniques in epilepsy are also discussed

Leveraging Artificial Intelligence to Improve EEG-fNIRS Data Analysis

La spectroscopie proche infrarouge fonctionnelle (fNIRS) est apparue comme une technique de neuroimagerie qui permet une surveillance non invasive et à long terme de l'hémodynamique corticale. Les technologies de neuroimagerie multimodale en milieu clinique permettent d'étudier les maladies neurologiques aiguës et chroniques. Dans ce travail, nous nous concentrons sur l'épilepsie - un trouble chronique du système nerveux central affectant près de 50 millions de personnes dans le monde entier prédisposant les individus affectés à des crises récurrentes. Les crises sont des aberrations transitoires de l'activité électrique du cerveau qui conduisent à des symptômes physiques perturbateurs tels que des changements aigus ou chroniques des compétences cognitives, des hallucinations sensorielles ou des convulsions de tout le corps. Environ un tiers des patients épileptiques sont récalcitrants au traitement pharmacologique et ces crises intraitables présentent un risque grave de blessure et diminuent la qualité de vie globale. Dans ce travail, nous étudions 1. l'utilité des informations hémodynamiques dérivées des signaux fNIRS dans une tâche de détection des crises et les avantages qu'elles procurent dans un environnement multimodal par rapport aux signaux électroencéphalographiques (EEG) seuls, et 2. la capacité des signaux neuronaux, dérivé de l'EEG, pour prédire l'hémodynamique dans le cerveau afin de mieux comprendre le cerveau épileptique. Sur la base de données rétrospectives EEG-fNIRS recueillies auprès de 40 patients épileptiques et utilisant de nouveaux modèles d'apprentissage en profondeur, la première étude de cette thèse suggère que les signaux fNIRS offrent une sensibilité et une spécificité accrues pour la détection des crises par rapport à l'EEG seul. La validation du modèle a été effectuée à l'aide de l'ensemble de données CHBMIT open source documenté et bien référencé avant d'utiliser notre ensemble de données EEG-fNIRS multimodal interne. Les résultats de cette étude ont démontré que fNIRS améliore la détection des crises par rapport à l'EEG seul et ont motivé les expériences ultérieures qui ont déterminé la capacité prédictive d'un modèle d'apprentissage approfondi développé en interne pour décoder les signaux d'état de repos hémodynamique à partir du spectre complet et d'une bande de fréquences neuronale codée spécifique signaux d'état de repos (signaux sans crise). Ces résultats suggèrent qu'un autoencodeur multimodal peut apprendre des relations multimodales pour prédire les signaux d'état de repos. Les résultats suggèrent en outre que des gammes de fréquences EEG plus élevées prédisent l'hémodynamique avec une erreur de reconstruction plus faible par rapport aux gammes de fréquences EEG plus basses. De plus, les connexions fonctionnelles montrent des modèles spatiaux similaires entre l'état de repos expérimental et les prédictions fNIRS du modèle. Cela démontre pour la première fois que l'auto-encodage intermodal à partir de signaux neuronaux peut prédire l'hémodynamique cérébrale dans une certaine mesure. Les résultats de cette thèse avancent le potentiel de l'utilisation d'EEG-fNIRS pour des tâches cliniques pratiques (détection des crises, prédiction hémodynamique) ainsi que l'examen des relations fondamentales présentes dans le cerveau à l'aide de modèles d'apprentissage profond. S'il y a une augmentation du nombre d'ensembles de données disponibles à l'avenir, ces modèles pourraient être en mesure de généraliser les prédictions qui pourraient éventuellement conduire à la technologie EEG-fNIRS à être utilisée régulièrement comme un outil clinique viable dans une grande variété de troubles neuropathologiques.----------ABSTRACT Functional near-infrared spectroscopy (fNIRS) has emerged as a neuroimaging technique that allows for non-invasive and long-term monitoring of cortical hemodynamics. Multimodal neuroimaging technologies in clinical settings allow for the investigation of acute and chronic neurological diseases. In this work, we focus on epilepsy—a chronic disorder of the central nervous system affecting almost 50 million people world-wide predisposing affected individuals to recurrent seizures. Seizures are transient aberrations in the brain's electrical activity that lead to disruptive physical symptoms such as acute or chronic changes in cognitive skills, sensory hallucinations, or whole-body convulsions. Approximately a third of epileptic patients are recalcitrant to pharmacological treatment and these intractable seizures pose a serious risk for injury and decrease overall quality of life. In this work, we study 1) the utility of hemodynamic information derived from fNIRS signals in a seizure detection task and the benefit they provide in a multimodal setting as compared to electroencephalographic (EEG) signals alone, and 2) the ability of neural signals, derived from EEG, to predict hemodynamics in the brain in an effort to better understand the epileptic brain. Based on retrospective EEG-fNIRS data collected from 40 epileptic patients and utilizing novel deep learning models, the first study in this thesis suggests that fNIRS signals offer increased sensitivity and specificity metrics for seizure detection when compared to EEG alone. Model validation was performed using the documented open source and well referenced CHBMIT dataset before using our in-house multimodal EEG-fNIRS dataset. The results from this study demonstrated that fNIRS improves seizure detection as compared to EEG alone and motivated the subsequent experiments which determined the predictive capacity of an in-house developed deep learning model to decode hemodynamic resting state signals from full spectrum and specific frequency band encoded neural resting state signals (seizure free signals). These results suggest that a multimodal autoencoder can learn multimodal relations to predict resting state signals. Findings further suggested that higher EEG frequency ranges predict hemodynamics with lower reconstruction error in comparison to lower EEG frequency ranges. Furthermore, functional connections show similar spatial patterns between experimental resting state and model fNIRS predictions. This demonstrates for the first time that intermodal autoencoding from neural signals can predict cerebral hemodynamics to a certain extent. The results of this thesis advance the potential of using EEG-fNIRS for practical clinical tasks (seizure detection, hemodynamic prediction) as well as examining fundamental relationships present in the brain using deep learning models. If there is an increase in the number of datasets available in the future, these models may be able to generalize predictions which would possibly lead to EEG-fNIRS technology to be routinely used as a viable clinical tool in a wide variety of neuropathological disorders

Doctor of Philosophy

dissertationPerinatal hypoxic-ischemic (PHI) encephalopathy afflicts roughly 1-2 in every 1000 live births, predisposing affected infants to a higher probability of developing epilepsy, cerebral palsy, and other neurological disorders. In many forms of acquired epilepsy, including PHI, there is a seizure-free period of time between the injury and the onset of the first spontaneous recurrent seizure (SRS) termed the latent period. In animal models of PHI, we aim to better understand the mechanisms that lead to an epileptic network that occur during this latent period. Due to limitations in performing electrophysiological experiments in immature animals, this time period remains under-studied in the pediatric population. We start our study at the cellular level using immunohistochemistry and whole-cell patch clamp methods before moving to the whole brain level with magnetic resonance imaging and the electroencephalogram (EEG) to examine anatomical and physiological changes that precede the development of epilepsy. We find that immediately after injury, early cell loss results in a reduction in the amount of excitatory and inhibitory synaptic input to pyramidal cells within the peri-infarct region. However, this reduction is short term, as there is a rapid recovery in the synaptic inputs 2 weeks later without any identifiable increase in the number of cells. As the brain continues to develop, the cellular loss that occurs early on leads to atrophy, and sometimes complete loss of the cortex, hippocampus, and thalamus. Even with major cell loss, power spectral analysis of the EEG identified no obvious reduction or increase in the power of any of the various cortical rhythms (delta, theta, alpha, beta, and gamma). However, EEG analysis did reveal the earliest known time point at which seizures occur in this animal model, as well as a previously undescribed short-duration convulsive seizure. Our findings suggest that the mechanisms responsible for the development of SRSs begin immediately after injury and result in a variable and progressive latent period

Physiological and pathological brain activation in the anesthetized rat produces hemodynamic-dependent cortical temperature increases that can confound the BOLD fMRI signal

Anesthetized rodent models are ubiquitous in pre-clinical neuroimaging studies. However, because the associated cerebral morphology and experimental methodology results in a profound negative brain-core temperature differential, cerebral temperature changes during functional activation are likely to be principally driven by local inflow of fresh, core-temperature, blood. This presents a confound to the interpretation of blood-oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data acquired from such models, since this signal is also critically temperature-dependent. Nevertheless, previous investigation on the subject is surprisingly sparse. Here, we address this issue through use of a novel multi-modal methodology in the urethane anesthetized rat. We reveal that sensory stimulation, hypercapnia and recurrent acute seizures induce significant increases in cortical temperature that are preferentially correlated to changes in total hemoglobin concentration (Hbt), relative to cerebral blood flow and oxidative metabolism. Furthermore, using a phantom-based evaluation of the effect of such temperature changes on the BOLD fMRI signal, we demonstrate a robust inverse relationship between both variables. These findings suggest that temperature increases, due to functional hyperemia, should be accounted for to ensure accurate interpretation of BOLD fMRI signals in pre-clinical neuroimaging studies

Incessant transitions between active and silent states in cortico-thalamic circuits and altered neuronal excitability lead to epilepsy

La ligne directrice de nos expériences a été l'hypothèse que l'apparition et/ou la persistance des fluctuations de longue durée entre les états silencieux et actifs dans les réseaux néocorticaux et une excitabilité neuronale modifiée sont les facteurs principaux de l'épileptogenèse, menant aux crises d’épilepsie avec expression comportementale. Nous avons testé cette hypothèse dans deux modèles expérimentaux différents. La déafférentation corticale chronique a essayé de répliquer la déafférentation physiologique du neocortex observée pendant le sommeil à ondes lentes. Dans ces conditions, caractérisées par une diminution de la pression synaptique et par une incidence augmentée de périodes silencieuses dans le système cortico-thalamique, le processus de plasticité homéostatique augmente l’excitabilité neuronale. Par conséquent, le cortex a oscillé entre des périodes actives et silencieuses et, également, a développé des activités hyper-synchrones, s'étendant de l’hyperexcitabilité cellulaire à l'épileptogenèse focale et à des crises épileptiques généralisées. Le modèle de stimulation sous-liminale chronique (« kindling ») du cortex cérébral a été employé afin d'imposer au réseau cortical une charge synaptique supérieure à celle existante pendant les états actifs naturels - état de veille ou sommeil paradoxal (REM). Dans ces conditions un mécanisme différent de plasticité qui s’est exprimé dans le système thalamo-corticale a imposé pour des longues périodes de temps des oscillations continuelles entre les époques actives et silencieuses, que nous avons appelées des activités paroxysmiques persistantes. Indépendamment du mécanisme sous-jacent de l'épileptogenèse les crises d’épilepsie ont montré certaines caractéristiques similaires : une altération dans l’excitabilité neuronale mise en évidence par une incidence accrue des décharges neuronales de type bouffée, une tendance constante vers la généralisation, une propagation de plus en plus rapide, une synchronie augmentée au cours du temps, et une modulation par les états de vigilance (facilitation pendant le sommeil à ondes lentes et barrage pendant le sommeil REM). Les états silencieux, hyper-polarisés, de neurones corticaux favorisent l'apparition des bouffées de potentiels d’action en réponse aux événements synaptiques, et l'influence post-synaptique d'une bouffée de potentiels d’action est beaucoup plus importante par rapport à l’impacte d’un seul potentiel d’action. Nous avons également apporté des évidences que les neurones néocorticaux de type FRB sont capables à répondre avec des bouffées de potentiels d’action pendant les phases hyper-polarisées de l'oscillation lente, propriété qui peut jouer un rôle très important dans l’analyse de l’information dans le cerveau normal et dans l'épileptogenèse. Finalement, nous avons rapporté un troisième mécanisme de plasticité dans les réseaux corticaux après les crises d’épilepsie - une diminution d’amplitude des potentiels post-synaptiques excitatrices évoquées par la stimulation corticale après les crises - qui peut être un des facteurs responsables des déficits comportementaux observés chez les patients épileptiques. Nous concluons que la transition incessante entre des états actifs et silencieux dans les circuits cortico-thalamiques induits par disfacilitation (sommeil à ondes lentes), déafférentation corticale (épisodes ictales à 4-Hz) ou par une stimulation sous-liminale chronique (activités paroxysmiques persistantes) crée des circonstances favorables pour le développement de l'épileptogenèse. En plus, l'augmentation de l’incidence des bouffées de potentiels d’actions induisant une excitation post-synaptique anormalement forte, change l'équilibre entre l'excitation et l'inhibition vers une supra-excitation menant a l’apparition des crises d’épilepsie.The guiding line in our experiments was the hypothesis that the occurrence and / or the persistence of long-lasting fluctuations between silent and active states in the neocortical networks, together with a modified neuronal excitability are the key factors of epileptogenesis, leading to behavioral seizures. We addressed this hypothesis in two different experimental models. The chronic cortical deafferentation replicated the physiological deafferentation of the neocortex observed during slow-wave sleep (SWS). Under these conditions of decreased synaptic input and increased incidence of silent periods in the corticothalamic system the process of homeostatic plasticity up-regulated cortical cellular and network mechanisms and leaded to an increased excitability. Therefore, the deafferented cortex was able to oscillate between active and silent epochs for long periods of time and, furthermore, to develop highly synchronized activities, ranging from cellular hyperexcitability to focal epileptogenesis and generalized seizures. The kindling model was used in order to impose to the cortical network a synaptic drive superior to the one naturally occurring during the active states - wake or rapid eye movements (REM) sleep. Under these conditions a different plasticity mechanism occurring in the thalamo-cortical system imposed long-lasting oscillatory pattern between active and silent epochs, which we called outlasting activities. Independently of the mechanism of epileptogenesis seizures showed some analogous characteristics: alteration of the neuronal firing pattern with increased bursts probability, a constant tendency toward generalization, faster propagation and increased synchrony over the time, and modulation by the state of vigilance (overt during SWS and completely abolished during REM sleep). Silent, hyperpolarized, states of cortical neurons favor the induction of burst firing in response to depolarizing inputs, and the postsynaptic influence of a burst is much stronger as compared to a single spike. Furthermore, we brought evidences that a particular type of neocortical neurons - fast rhythmic bursting (FRB) class - is capable to consistently respond with bursts during the hyperpolarized phase of the slow oscillation, fact that may play a very important role in both normal brain processing and in epileptogenesis. Finally, we reported a third plastic mechanism in the cortical network following seizures - a decreasing amplitude of cortically evoked excitatory post-synaptic potentials (EPSP) following seizures - which may be one of the factors responsible for the behavioral deficits observed in patients with epilepsy. We conclude that incessant transitions between active and silent states in cortico-thalamic circuits induced either by disfacilitation (sleep), cortical deafferentation (4-Hz ictal episodes) and by kindling (outlasting activities) create favorable circumstances for epileptogenesis. The increase in burst-firing, which further induce abnormally strong postsynaptic excitation, shifts the balance of excitation and inhibition toward overexcitation leading to the onset of seizures

Optogenetic investigation of cortical network dynamics in epilepsy

Ph. D. ThesisUnderstanding the cortical network properties which determine the susceptibility of cortex to the onset of seizures remains a major goal of epilepsy research. The determinants of seizure risk in cortical networks are dynamic, showing dependency on intrinsic cortical activity and environmental influences. The failure to identify reliable electrographic indicators of imminent seizure onset suggests that the contributory factors may not be electrographically obvious. A strong candidate for such a property is the activity dependent disinhibition of the excitatory network which results from increases in intracellular chloride concentration. Chloride loading has been shown previously to occur during periods of intense neuronal activity, resulting from concomitant excitatory and inhibitory synaptic transmission. To explore how network dynamics evolve from a stable healthy state to one permissive for the onset and propagation of seizures, I used an optogenetic approach to selectively interrogate dynamic changes to excitatory transmission between the principal cells of the cortical circuit following an acute ictogenic challenge, both in vitro and in vivo. Using ultra-low frequency optogenetic stimulation genetically targeted to the pyramidal cells of neocortex, I demonstrate that epileptiform activity, which develops spontaneously following an acute chemoconvulsant challenge, can both be reduced and monitored, using an active probing strategy. Delivering continuous and focal optogenetic stimulations to superficial neocortex and regions of the hippocampal formation evokes glutamatergic responses in the LFP which can be used to assay dendritic excitability in the network. At ultralow frequencies, between 0.1-0.033 Hz, optogenetic stimulation markedly reduced the rate of evolution of epileptiform activity, when delivered to neocortex or hippocampal structures, in acutely prepared adult mouse brain slices bathed in 0Mg2+ perfusate. The response evoked by these test pulses undergoes an all-or-nothing transformation observable in the LFP which reliably telegraphed the onset of ictal activity in two models of epilepsy. Using electrophysiological tools and 2-photon calcium imaging of individual dendrites, I demonstrate that this phenomenon likely reflects a reduction in the threshold for dendritic spikes. Using an anatomically realistic computational model pyramidal cell I show that this effect is reproduced by modest positive shifts in the GABAergic reversal potential in distal pyramidal cell dendrites. Finally, I report preliminary data demonstrating a potential mechanism for the diurnal modulation of seizure risk. Diurnal periodicity in seizure susceptibility have been observed longitudinal recordings from both patients and chronically epileptic experimental animals. Using the optical chloride sensor ClopHensor I examine steady-state pyramidal cell chloride concentration over the diurnal period and show that periodicity in chloride homeostasis is consistent with the phase of diurnally modulated seizure risk. In this thesis I use a range of optical and electrophysiological tools to explore the contribution of dynamic chloride concentration in pyramidal cells in determining cortical susceptibility to seizures onset. Using two acute epilepsy models I demonstrate that an assayable increase in dendritic excitability precedes ictogenesis, and demonstrate a potential mechanism by which variation in [Cl-]i can give rise to this effect. I go on to show diurnal variation in [Cl-]i in cortical pyramidal cells, and link this to circadian modulation of susceptibility to chemoconvulsants, suggesting a functional mechanism for the dynamic seizure risk observed in epileptic patients

Making Waves in the Brain: What Are Oscillations, and Why Modulating Them Makes Sense for Brain Injury.

Traumatic brain injury (TBI) can result in persistent cognitive, behavioral and emotional deficits. However, the vast majority of patients are not chronically hospitalized; rather they have to manage their disabilities once they are discharged to home. Promoting recovery to pre-injury level is important from a patient care as well as a societal perspective. Electrical neuromodulation is one approach that has shown promise in alleviating symptoms associated with neurological disorders such as in Parkinson's disease (PD) and epilepsy. Consistent with this perspective, both animal and clinical studies have revealed that TBI alters physiological oscillatory rhythms. More recently several studies demonstrated that low frequency stimulation improves cognitive outcome in models of TBI. Specifically, stimulation of the septohippocampal circuit in the theta frequency entrained oscillations and improved spatial learning following TBI. In order to evaluate the potential of electrical deep brain stimulation for clinical translation we review the basic neurophysiology of oscillations, their role in cognition and how they are changed post-TBI. Furthermore, we highlight several factors for future pre-clinical and clinical studies to consider, with the hope that it will promote a hypothesis driven approach to subsequent experimental designs and ultimately successful translation to improve outcome in patients with TBI