Characterization of the neocortical network excitability with multielectrode arrays: alterations in migraine and epilepsy mouse models.

missin

Characterization of the neocortical network excitability with multielectrode arrays: alterations in migraine and epilepsy mouse models.

missin

IMMUNOHISTOCHEMICAL CHARACTERIZATION OF A NOVEL POPULATION OF RETICULAR THALAMIC NEURONS EXPRESSING CHOLECYSTOKININ AND TYPE 1 CANNABINOID RECEPTORS

The thalamic reticular nucleus (TRN) filters somatosensory stimuli by providing inhibition to the excitatory thalamic relay nuclei, which then communicate with the cortex to appropriately integrate and respond to sensory stimuli. The TRN is also responsible for generating and maintaining sleep spindles, which are important for memory and cognition, and are disrupted in various psychiatric disorders. Previous studies have shown that the TRN is comprised of several neuronal subpopulations that carry out specific functions. These neurons can be distinguished using peptide markers such as parvalbumin (PV), somatostatin (SST), and calbindin (CB). In this thesis, I identified a novel neuronal population in the TRN that expresses the peptide cholecystokinin (CCK) and distal-less homeobox gene 5/6 (Dlx5/6). CCK;Dlx5/6 neurons have been widely studied in the hippocampus and amygdala where they have been shown to highly express the type 1 cannabinoid receptor (CB1R) and produce a long-lasting inhibition of pyramidal neurons. However, basic characterization of CCK;Dlx5/6 neurons has been missing. Through immunohistochemical assays, we found that CCK;Dlx5/6 neurons of the TRN express CB1R and the CCK peptide. Our results show that CCK;Dlx5/6 are highly concentrated in the dorsal areas of the TRN relative to the ventral ones, dorsal areas of the TRN are associated with processing of visual cues. Our preliminary results also show that dorsal and ventromedial areas of the thalamus receive more inputs from CCK;Dlx5/6 neurons than ventral and medial thalamic areas. Furthermore, some of the CCK;Dlx5/6 neurons establish perisomatic synapses with neurons of the lateral dorsal nucleus of the thalamus, this type of connectivity is consistent with previous observations for CCK neurons in amygdala and hippocampus. Taken together our results provide insights into the anatomy of CCK;Dlx5/6 neurons that suggest a potential role of these neurons in visual processing

Inferences of Glia-Mediated Control in Caenorhabditis elegans

Glia cells are key components of the brain that mediate signaling events between pre- and postsynaptic neurons and that play a vital role in regulating behavior. Depressive disorders are characterized as complex, multifunctional mental disorders that lead to unstable and extreme fluctuation in mood and behavior. Previous studies have shown that loss of glial cells results in emotional and behavioral abnormalities. Here, we exploit the Caenorhabditis elegans model, an optimal system in which to study glia-type specific function because the structure and connectivity of the nervous system has been fully described and previous studies have demonstrated that loss of glia is not lethal and does not result in death of the associated neuron. Because of the predetermined cell lineage, C.elegans neurons do not require trophic support from glia. This provides the advantage to separate the supportive role of glia and focus on understanding how glia regulate behavior. My dissertation research aims to identify the influence of a glia-subtype, the Cephalic sheath glia (CEPglia), and a glia specific basic helix-loop-helix (bHLH) transcription factor, HLH-17, in regulating complex and rhythmic behaviors. Complex behaviors integrate multiple sensory modulatory inputs to orchestrate a specific motor output. Similarly, rhythmic behaviors utilize an intrinsic pacemaker to modulate periodic activation of a stereotyped sequence of behaviors. Work from our lab demonstrates that the unique expression of HLH-17 in an astrocyte-like cephalic sheath (CEPglia) is required to modulate dopamine-dependent behaviors such as swimming, egg laying, and paralysis; and that HLH-17 regulates the expression of genes required for mating and defecation. Results from my research suggest that expression of HLH-17 in the CEPglia may be required for regulating the precision and accuracy of independent motor programs and that CEPglia coordinate multiple motor responses. Findings from my work outline a hypothetical model by which astrocyte-like CEPglia modulate the function of motor neurons, in part, by transmitting signals through interneurons to motor neurons that are required for behavior. Additionally, my dissertation research hints at a mechanism in which glia may exert sexually dimorphic regulation of a rhythmic behavior

Mean-field analysis of basal ganglia and thalamocortical dynamics

When modeling a system as complex as the brain, considerable simplifications are inevitable. The nature of these simplifications depends on the available experimental evidence, and the desired form of model predictions. A focus on the former often inspires models of networks of individual neurons, since properties of single cells are more easily measured than those of entire populations. However, if the goal is to describe the processes responsible for the electroencephalogram (EEG), such models can become unmanageable due to the large numbers of neurons involved. Mean-field models in which assemblies of neurons are represented by their average properties allow activity underlying the EEG to be captured in a tractable manner. The starting point of the results presented here is a recent physiologically-based mean-field model of the corticothalamic system, which includes populations of excitatory and inhibitory cortical neurons, and an excitatory population representing the thalamic relay nuclei, reciprocally connected with the cortex and the inhibitory thalamic reticular nucleus. The average firing rates of these populations depend nonlinearly on their membrane potentials, which are determined by afferent inputs after axonal propagation and dendritic and synaptic delays. It has been found that neuronal activity spreads in an approximately wavelike fashion across the cortex, which is modeled as a two-dimensional surface. On the basis of the literature, the EEG signal is assumed to be roughly proportional to the activity of cortical excitatory neurons, allowing physiological parameters to be extracted by inverse modeling of empirical EEG spectra. One objective of the present work is to characterize the statistical distributions of fitted model parameters in the healthy population. Variability of model parameters within and between individuals is assessed over time scales of minutes to more than a year, and compared with the variability of classical quantitative EEG (qEEG) parameters. These parameters are generally not normally distributed, and transformations toward the normal distribution are often used to facilitate statistical analysis. However, no single optimal transformation exists to render data distributions approximately normal. A uniformly applicable solution that not only yields data following the normal distribution as closely as possible, but also increases test-retest reliability, is described in Chapter 2. Specialized versions of this transformation have been known for some time in the statistical literature, but it has not previously found its way to the empirical sciences. Chapter 3 contains the study of intra-individual and inter-individual variability in model parameters, also providing a comparison of test-retest reliability with that of commonly used EEG spectral measures such as band powers and the frequency of the alpha peak. It is found that the combined model parameters provide a reliable characterization of an individual's EEG spectrum, where some parameters are more informative than others. Classical quantitative EEG measures are found to be somewhat more reproducible than model parameters. However, the latter have the advantage of providing direct connections with the underlying physiology. In addition, model parameters are complementary to classical measures in that they capture more information about spectral structure. Another conclusion from this work was that a few minutes of alert eyes-closed EEG already contain most of the individual variability likely to occur in this state on the scale of years. In Chapter 4, age trends in model parameters are investigated for a large sample of healthy subjects aged 6-86 years. Sex differences in parameter distributions and trends are considered in three age ranges, and related to the relevant literature. We also look at changes in inter-individual variance across age, and find that subjects are in many respects maximally different around adolescence. This study forms the basis for prospective comparisons with age trends in evoked response potentials (ERPs) and alpha peak morphology, besides providing a standard for the assessment of clinical data. It is the first study to report physiologically-based parameters for such a large sample of EEG data. The second main thrust of this work is toward incorporating the thalamocortical system and the basal ganglia in a unified framework. The basal ganglia are a group of gray matter structures reciprocally connected with the thalamus and cortex, both significantly influencing, and influenced by, their activity. Abnormalities in the basal ganglia are associated with various disorders, including schizophrenia, Huntington's disease, and Parkinson's disease. A model of the basal ganglia-thalamocortical system is presented in Chapter 5, and used to investigate changes in average firing rates often measured in parkinsonian patients and animal models of Parkinson's disease. Modeling results support the hypothesis that two pathways through the basal ganglia (the so-called direct and indirect pathways) are differentially affected by the dopamine depletion that is the hallmark of Parkinson's disease. However, alterations in other components of the system are also suggested by matching model predictions to experimental data. The dynamics of the model are explored in detail in Chapter 6. Electrophysiological aspects of Parkinson's disease include frequency reduction of the alpha peak, increased relative power at lower frequencies, and abnormal synchronized fluctuations in firing rates. It is shown that the same parameter variations that reproduce realistic changes in mean firing rates can also account for EEG frequency reduction by increasing the strength of the indirect pathway, which exerts an inhibitory effect on the cortex. Furthermore, even more strongly connected subcircuits in the indirect pathway can sustain limit cycle oscillations around 5 Hz, in accord with oscillations at this frequency often observed in tremulous patients. Additionally, oscillations around 20 Hz that are normally present in corticothalamic circuits can spread to the basal ganglia when both corticothalamic and indirect circuits have large gains. The model also accounts for changes in the responsiveness of the components of the basal ganglia-thalamocortical system, and increased synchronization upon dopamine depletion, which plausibly reflect the loss of specificity of neuronal signaling pathways in the parkinsonian basal ganglia. Thus, a parsimonious explanation is provided for many electrophysiological correlates of Parkinson's disease using a single set of parameter changes with respect to the healthy state. Overall, we conclude that mean-field models of brain electrophysiology possess a versatility that allows them to be usefully applied in a variety of scenarios. Such models allow information about underlying physiology to be extracted from the experimental EEG, complementing traditional measures that may be more statistically robust but do not provide a direct link with physiology. Furthermore, there is ample opportunity for future developments, extending the basic model to encompass different neuronal systems, connections, and mechanisms. The basal ganglia are an important addition, not only leading to unified explanations for many hitherto disparate phenomena, but also contributing to the validation of this form of modeling

Rôle des astrocytes dans la décharge rythmique neuronale du noyau sensoriel principal du trijumeau

La communication entre les neurones est fondée sur leur capacité à changer leur patron de décharge pour l’encodage de différents messages. Pour plusieurs fonctions vitales, comme la respiration et la mastication, les neurones doivent pouvoir générer des patrons d’activité répétitifs, et les groupes de neurones responsables de ces décharges rythmiques sont des générateurs de patron central (GPC). En dépit de recherches soutenues, les mécanismes précis qui sous-tendent la rythmogénèse dans les GPCs ne sont pas bien définis. Le plus souvent, la potentielle contribution des astrocytes demeure grandement inexplorée, même si ces cellules sont aujourd’hui connues pour leur implication dans la modulation synaptique neuronale. Pour nos travaux, le noyau sensoriel principal du trijumeau (NVsnpr) a été pris comme modèle à cause de son rôle central dans les mouvements rythmiques de la mastication. Dans ce noyau, des travaux antérieurs ont montré que la décharge en bouffées rythmiques est déclenchée dans les neurones lorsque la concentration de calcium extracellulaire ([Ca2+]e) est artificiellement baissée. Nous fondant sur cette observation, notre première hypothèse a postulé que la baisse de la [Ca2+]e pouvait survenir de façon physiologique en lien avec des stimulations sensorielles pertinentes. Deuxièmement, parce que les astrocytes ont été impliqués dans le tamponnage et l’homéostasie d’ions extracellulaires comme le K+, nous avons postulé que ces cellules pouvaient jouer un rôle équivalent dans le contrôle de la [Ca2+]e. Nos résultats montrent que les astrocytes peuvent réguler la [Ca2+]e et ainsi contrôler la capacité des neurones à changer leur patron de décharge. Premièrement, en stimulant les afférences sensorielles au NVsnpr, nous avons montré que des baisses physiologiques de la [Ca2+]e sont observées en parallèle à l’apparition de bouffées rythmiques neuronales. Deuxièmement, nous avons démontré que les astrocytes répondent aux mêmes stimuli qui induisent l’activité rythmique neuronale, et que leur blocage avec un chélateur de Ca2+ empêche les neurones de générer un patron de décharge en bouffées rythmiques. Cette habilité est rétablie en rajoutant la S100β, une protéine astrocytaire liant le Ca2+, dans le milieu extracellulaire, alors que l’anticorps anti-S100β empêche l’activité rythmique. Ces résultats indiquent que les astrocytes régulent une propriété neuronale fondamentale : la capacité à changer de patron de décharge. Ainsi, les GPCs dépendraient des fonctions intégrées des astrocytes et des neurones. Ces découvertes pourraient avoir des implications transposables à plusieurs autres circuits neuronaux dont la fonction dépend de l’induction d’activité rythmique.Communication between neurons rests on their capacity to change their firing pattern to encode different messages. For several vital functions, such as respiration and mastication, neurons need to generate a repetitive firing pattern, and the groups of neurons responsible for these rhythmic discharges are called central pattern generator (CPG). Despite intense research in this field, the exact mechanisms underlying rhythmogenesis in CPGs are not completely defined. In most instances, the potential contribution of astrocytes is largely unexplored, even though these cells are now well known to be involved in neuronal synaptic modulation. In our work, the trigeminal main sensory nucleus (NVsnpr) was used as a model owing to its central role in the rhythmic movement of mastication. Previous work have shown that rhythmic bursting discharge is triggered in NVsnpr neurons when extracellular calcium concentration ([Ca2+]e) is artificially decreased. Based on this observation, our first hypothesis postulated that the reduction of [Ca2+]e could also happen physiologically in relation to relevant sensory stimulation. Secondly, because astrocytes have been involved in the buffering and the homeostasis of extracellular ions like potassium, we have postulated that these cells could also play a role in the control of [Ca2+]e. The results presented in this thesis show that astrocytes can regulate [Ca2+]e and thus control the ability of neurons to change their firing pattern. First, we showed that stimulation of sensory afferent fibers to the NVsnpr induced neuronal rhythmic bursting and in parallel reduction of [Ca2+]e . Secondly, we have demonstrated that astrocytes respond to the same sensory stimuli that induce neuronal rhythmic activity, and their blockade with a Ca2+ chelator prevents generation of neuronal rhythmic bursting. This ability is restored by adding S100β, an astrocytic Ca2+-binding protein, to the extracellular space, while the application of an anti- S100β antibody prevents generation of rhythmic activity. These results indicate that astrocytes regulate a fundamental neuronal property: that is the capacity to change their firing pattern. Thus, CPG functions result from integrated neuronal and glial activities. These findings may have broad implications for many other neural networks whose functions depend on the generation of rhythmic activity