Esta tese aborda o interrelacionamento entre morfologia, topologia e dinâmica de ativação em redes neuronais morfologicamente realistas, construídas com neurônios da base pública Neuromorpho. Foi desenvolvido um arcabouço computacional capaz de simular a dinâmica de ativação neuronal (através do modelo integra-e-dispara) ao longo do desenvolvimento da conexão das redes tridimensionais respectivas. Tal arcabouço permitiu investigar como aspectos da dinâmica de ativação variam ao longo das épocas de desenvolvimento das redes, incluindo antes, durante e depois da percolação. Em particular, calcularam-se correlações de Pearson entre várias medidas dinâmicas e topológicas ao longo das épocas de evolução, de forma a se quantificar de maneira objetiva os possíveis relacionamentos entre a ativação neuronal e a topologia das redes. Foram considerados três tipos de neurônios piramidais: occipitais e pré-frontais de humanos e células piramidais de macado (macaco Rhesus). Os dois primeiros tipos foram verificados (através de histogramas de médias e análise por componentes principais) possuírem características morfológicas semelhantes, enquanto o grupo de células piramidais do macaco apresentaram substancial diferenciação. Vários resultados foram obtidos respectivamente às correlações entre medidas dinâmicas e topológicas. Em particular, verificou- se que os graus médios de entrada e saída das redes estão significativamente correlacionados com as taxas médias de ativação, convergindo rapidamente após a formação do componente fraco. A correlação do grau de entrada mostrou-se mais elevada do que a obtida para o grau de saída. Além disto, a correlação entre o grau de entrada e a taxa média de disparos tendeu a diminuir ao longo das épocas finais das simulações. Verificou-se também como os perfis de evolução de várias correlações entre dinâmica e topologia implicam na diferenciação dos tipos neuronais considerados. / This thesis addresses the interrelationships between morphology, topology and activation dynamics in morphologically realistic neuronal networks, derived from the public data base Neuromorpho. A computational framework has been developed that is capable of simulating the dynamics of neuronal activation (via the integrate-and-fire dynamics) during the development of the network connection in three-dimensional spaces. This framework allowed to investigate how aspects of the activation dynamics vary over the epochs of network development, including before, during and after the critical event of percolation. In particular, we calculated Pearson correlation coefficients between various topological and dynamical measurements throughout the epochs of evolution, in order to quantify in an objective way how the relationships between neuronal activation and network topology changed along the development of the connectivity. We considered three types of neurons: occipital and prefrontal pyramidal cells of human and diverse pyramidal cells of monkey individuals (monkey Rhesus). The first two types were found (via histograms and principal component analysis) to have mostly similar morphological characteristics, while the group of pyramidal cells from apes showed substantial differentiation. Several results were obtained respectively to the correlations between measurements of dynamics and morphology along the epochs of development. In particular, it was found that the input and output average degrees of the network are significantly correlated with the average rates of activation. After a period of large variation that precedes the formation of the weakly connected component, these correlation values converge rapidly to a regime of smooth decrease which suggests saturation of the activation in the network. The correlation implied by the indegree proved to be clearly higher than that obtained for the outdegree. It was also investigated how the profiles of the various correlations along the development epochs implied in the differentiation between the neuronal types considered.

This thesis describes the development of an optimized method for culturing dissociated, monolayer neuronal networks from murine frontal cortex and midbrain. It is presented as a guidebook for use by cell culture specialists and laboratory personnel who require updated and complete procedures for use with microelectrode array (MEA) recording technology. Specific cell culture protocols, contamination prevention and control, as well common problems encountered within the cell culture facility, are discussed. This volume offers value and utility to the rapidly expanding fields of MEA recording and neuronal cell culture. Due to increasing interest in determining the mechanisms underlying Parkinson's disease, the newly developed procedures for mesencephalon isolation and culture on MEAs are an important research contribution.

This dissertation research explored the capabilities of neuronal networks grown on substrate integrated microelectrode arrays in vitro to be applied to toxicological research and lipid signaling. Chapter 1 details the effects of chlorine on neuronal network spontaneous electrical activity and pharmacological sensitivity. This study demonstrates that neuronal networks can maintain baseline spontaneous activity, and respond normally to pharmacological manipulations in the present of three times the chlorine present in drinking water. The findings suggest that neuronal networks may be used as biological sensors to monitor the quality of water and the presence of novel toxicants that cannot be detected by conventional sensors. Chapter 2 details the neuromodulatory effects of N-acylethanolamides (NAEs) on the spontaneous electrical activity of neuronal networks. NAEs are a group of lipids that can mimic the effects of marijuana and can be derived from a variety of plant sources including soy lecithin. The most prominent NAEs in soy lecithin, palmitoylethanolamide (PEA) and linoleoylethanolamide (LEA), were tested individually and were found to significantly inhibit neuronal spiking and bursting activity. These effects were potentiated by a mixture of NAEs as found in a HPLC enriched fraction from soy lecithin. Cannabinoid receptor-1 (CB1-R) antagonists and other cannabinoid pathway modulators indicated that the CB1-R was not directly involved in the effects of NAEs, but that enzymatic degradation and cellular uptake were more likely targets. The results demonstrate that neuronal networks may also be a viable platform for the elucidation of biochemical pathways and drug mechanisms of action.

Ma thèse comporte deux grandes parties, la première en biophysique et la seconde en science de l’éducation. La première partie présente des travaux à la frontière entre neurobiologie et microfluidique. Le but de ces travaux est de pouvoir reconstruire et étudier des réseaux complexes de neurones in vitro avec une topologie de connections synaptiques bien contrôlées. Une série de micro-structures mécanique et/ou chimique ont été étudiées pour leur capacité à (i) positionner les corps cellulaires des neurones, (ii) orienter la pousse des neurites, et (iii) différencier les axones des dendrites. Un premier réseau comportant trois populations de neurones connectées en série a été reconstruit à l’intérieur d’un circuit microfluidique. Ce réseau qui mime la voie perforante de l’hippocampe pourra être exploité pour des études en physiologie ou en neuro-dégénerescence. Une méthode entièrement optique de stimulation et d’observation de l’activité neuronal a été mise au point. Elle ouvre de nouvelles portes pour étudier des processus cognitifs complexes dans des systèmes simplifiés in vitro. La seconde partie de mon travail a permis le développement et l’étude de jeux pédagogiques pour l’apprentissage de la chimie en licence. Ces jeux, qui peuvent selon les cas remplacer un cours ou une séance d’exercices, donnent des résultats prometteurs pour l’aide à la compréhension et à la mémorisation de concepts tels que la géométrie des molécules ou la réactivité entre molécules organiques. / My PhD is divided in two parts one on biophysic of neuronal networks and one on science of education. The first part present results at the frontier between neurobiology and microfluidic. The overarching goal of this work was to develop tools and methods to build and study complex neuronal networks controlling the topology of synaptic connexions. Micro-patterning techniques with mechanical and/or chemical constraints were explored regarding their capacity to (i) position cell bodies, (ii) orient neurite outgrowth and (iii) polarize neurons. For the first time, a network comprising three different neuronal populations connected in specified directions was reconstructed in a microfluidic device. This network that mimics the perforant pathway of the hippocampus can be used to study physiological rythms or neurodegenerative processes including Alzheimer’s disease. A novel and fully optical method is presented to stimulate and record neuronal activity in vitro. It opens new routes to study complex cognitive processes in simplified in vitro systems. The second part of my work present the development and assessment of educational games in chemistry at the undergraduate level. These games that can either be used to replace courses or exercises, seem promising to improve the understanding and memorization of chemistry concepts og geometries of molecules and organic reactivity.

Les comportements motivés tels que les comportements alimentaires ou sexuels sont émis de façon irrégulière sous l’impulsion du système nerveux central. Ils sont régulés par des informations sensorielles et des apprentissages. Dans un apprentissage associatif, le conditionnement opérant appétitif, l’animal apprend les conséquences de son action parl’association d’une action à l’obtention d’une récompense (un stimulus à forte valeur appétitive). Il est établi que cet apprentissage induit la transition d’une motricité initialement peu fréquente et irrégulière en une motricité rythmique, fréquente et régulière. Cependant, les mécanismes cellulaires du système nerveux central qui sont responsables de cettetransition, restent largement méconnus. Notre étude chez le mollusque aplysie nous a permis d’identifier ces mécanismes dans un réseau neuronal identifié et générateur des patterns moteurs du comportement alimentaire. Sur des préparations du système nerveux isolé, nous avons sélectivement contrôlé l’expression fréquente d’une part et régulièred’autre part de la motricité apprise grâce à la manipulation expérimentale de la plasticité fonctionnelle de neurones pacemakers identifiés. Ainsi, nous avons nouvellement établi un lien de causalité entre (1) des modifications membranaires et l’accélération motrice et (2) le renforcement de synapses électriques et la régularité motrice. Nous avons mis en évidence le rôle du transmetteur dopamine dans l’induction de ces plasticités fonctionnelles et l’expression de la motricité fréquente et régulière. Enfin, nous avons analysé les propriétés intrinsèques du neurone responsable de l’impulsion spontanée et irrégulière de la motricité des animaux naïfs. Pour conclure, l’ensemble de ces travaux de thèse offre une vue étendue des mécanismes cellulaires qui déterminent la variabilité d’un comportement motivé et sarégulation par apprentissage. / Motivated behaviors such as feeding or sexual behavior are irregularly expressed by impulsive drives from the central nervous system. However, such goal-directed acts are regulated by sensory inputs and learning. In a form of associative learning, appetitive operant conditioning, an animal learns the consequences of its own actions by making the contingentassociation between an emitted act and delivery of a rewarding (highly appetitive) stimulus. It is now established that this learning procedure induces the transition from an initially infrequent and irregular motor activity to a frequent and regular behavior. However the cellular and central network mechanisms that mediate this behavioral plasticity remain poorlyunderstood. Our study on the marine sea slug Aplysia has allowed us to analyze these mechanisms in an identified neuronal network that is responsible for generating the motor patterns of the animal's feeding behavior. Using in vitro neuronal preparations, we selectively controlled the frequency and regularity of the motor activity induced by operant learning with experimental manipulations of the functional plasticity in identified pacemaker neurons. We found for the first time a causal relationship between the learning-induced plasticity and (1) changes in pacemaker neuron membrane properties and the increased frequency of feeding motor activity, and (2), in the strength of their interconnecting electrical synapses and the regularized phenotype of this motor activity. We then addressed the role of the transmitterdopamine in the induction of this functional plasticity and specifically the expression of a frequent and stereotyped rhythmic feeding motor pattern. Finally, we analyzed the intrinsic membrane properties of the essential pacemaker neuron for generating the irregular motor drive in naïve animals. In conclusion, the data from this thesis work have provided novelinsights into the cellular and synaptic mechanisms underlying the intrinsic variability of a motivated behavior and its regulation by learning.

Welchen Einfluss die Struktur eines neuronalen Netzwerks auf seine Funktion ausübt, ist ein zentrales Thema der Neurowissenschaften. Obwohl gezeigt wurde, dass die Struktur vieler Gehirnnetzwerke nicht-triviale Gradkorrelationen aufweisen, ist deren Einfluss auf die neuronale Verarbeitung noch nicht vollständig verstanden. Diese Problem stellt einen Schwerpunkt dieser Arbeit dar – wir entwickeln ein „mean field“-Modell zur Untersuchung der Aktivitäten in rekurrenten neuronalen Netzwerken. Diese Untersuchung zeigt unter anderem, dass Gradkorrelationen in neuronalen Netzwerken zu komplexen, multistabilen Aktivitätsregimen führen können. Der zweite Schwerpunkt dieser Arbeit liegt auf Wellen auf der Netzhaut, von denen angenommen wird, dass sie für die Entwicklung des visuellen Systems eine wesentliche Rolle spielen. An Kaninchen durchgeführte Experimente zeigten, dass Wellen auf der Netzhaut im frühesten Stadium mit einer mittleren Rate von 36±18 1/sec auftreten und sich mit einer Geschwindigkeit von 451±91 μm/sec ausbreiten. Es ist bekannt, dass sich die Wellen in der Ganglienzellschicht der Netzhaut ausbreiten und auf Gap Junction-Kopplung zwischen den Neuronen beruhen. Da Gap Junctions (elektrische Synapsen) kurze Integrationszeiten haben, wurde vermutet, dass diese nicht für die niedrige Ausbreitungsgeschwindigkeit der Wellen auf der Netzhaut verantwortlich sein können. Wir entwickeln ein Modell, das aus einem zweidimensionalen Netzwerk von gekoppelten burstenden Neuronen besteht und die beobachtete Ausbreitungsgeschwindigkeit erklärt. Nach unserem Kenntnisstand ist dies das erste Mal, dass gezeigt wurde, dass die experimentell beobachtete Wellengeschwindigkeit und Nukleationsrate der frühen Wellen auf der Netzhaut für eine physiologisch plausible Gap Junction Kopplungsstärke und Rauschintensität zu erwarten sind. / The interplay between the structure and the function of a neuronal network is a fundamental issue in neuroscience. Although many brain networks have been shown to exhibit non-trivial correlations in their connectivity patterns, their role for neuronal computations is yet poorly understood. We set one main focus of this thesis on degree correlations and their influence on the activities in neuronal networks. To this end, we develop a mean field model and investigate the activities in recurrent neuronal networks. We find that depending on the degree-correlations, networks of neurons can exhibit complex, multi-stable activity regimes. The second focus of this thesis concerns retinal waves, which are believed to be essential for the development of the visual system. Experiments performed on rabbits revealed that stage I retinal waves (the earliest stage) are nucleated spontaneously with a mean inter-wave interval of 36±18 1/sec, to propagate without directional bias at a speed of 451±91 μm/sec. It has been known that the waves at this age spread through the ganglion cell layer of the retina and rely on gap junction coupling between the neurons. Because gap junctions (electrical synapses) have short integration times, it has been argued that they cannot set the low speed of stage I retinal waves. We present a theoretical model consisting of a two-dimensional network of the noisy bursting neurons, which are coupled via gap junctions. We demonstrate that this model explains the observed propagation speed, which is discussed analytically. To our knowledge, this is the first time it is demonstrated that the experimentally observed wave speed and nucleation rate of stage I retinal waves is recovered for a gap-junction coupling strength and noise intensity within a physiologically plausible range. Particularly the implication of gap junctions as mediator of these waves was previously unexplained.

For almost a century, the electrical properties of the brain and the nervous system have been investigated to gain a better understanding of their mechanisms and to find cures for pathological conditions. Despite the fact that today's advancements in surgical techniques, research, and medical imaging have improved our ability to treat brain disorders, our knowledge of the brain and its functions is still limited. Culturing dissociated cortical neurons on Micro-Electrode Array dishes is a powerful experimental tool for investigating functional and structural characteristics of in-vitro neuronal networks, such as the cellular basis of brain learning, memory and synaptic developmental plasticity. This dissertation focuses on combining MEAs with novel electrophysiology experimental paradigms and statistical data analysis to investigate the mechanisms that regulate brain development at the level of synaptic formation and growth cones. The goal is to use a mathematical approach and specifically designed experiments to investigate whether dissociated neuronal networks can dependably display long and short-term plasticity, which are thought to be the building blocks of memory formation in the brain. Quantifying the functional evolution of dissociated neuronal networks during in- vitro development, using a statistical analysis tool was the first aim of this work. The results of the False Discovery Rate analysis show an evolution in network activity with changes in both the number of statistically significant stimulus/recording pairs as well as the average length of connections and the number of connections per active node. It is therefore proposed that the FDR analysis combined with two metrics, the average connection length and the number of highly connected "supernodes" is a valuable technique for describing neuronal connectivity in MEA dishes. Furthermore, the statistical analysis indicates that cultures dissociated from the same brain tissue display trends in their temporal evolution that are more similar than those obtained with respect to different batches. The second aim of this dissertation was to investigate long and short-term plasticity responsible for memory formation in dissociated neuronal networks. In order to address this issue, a set of experiments was designed and implemented in which the MEA electrode grid was divided into four quadrants, two of which were chronically stimulated, every two days for one hour with a stimulation paradigm that varied over time. Overall network and quadrant responses were then analyzed to quantify what level of plasticity took place in the network and how this was due to the stimulation interruption. The results demonstrate that here were no spatial differences in the stimulus-evoked activity within quadrants. Furthermore, the implemented stimulation protocol induced depression effects in the neuronal networks as demonstrated by the consistently lower network activity following stimulation sessions. Finally, the analysis demonstrated that the inhibitory effects of the stimulation decreased over time, thus suggesting a habituation phenomenon. These findings are sufficient to conclude that electrical stimulation is an important tool to interact with dissociated neuronal cultures, but localized stimuli are not enough to drive spatial synaptic potentiation or depression. On the contrary, the ability to modulate synaptic temporal plasticity was a feasible task to achieve by chronic network stimulation. / Electrical and Computer Engineering

Nos entrées sensorielles, comme nos mouvements, sont entachés d’incertitudes. Pourtant, notre système nerveux central semble être aussi précis que possible compte tenu de ces incertitudes: il les gère de manière optimale, par exemple en pondérant des informations sensorielles redondantes en fonction de leur fiabilité, ou en prenant en compte ses incertitudes motrices lors de la réalisation de mouvements. Si les modalités des combinaisons d’informations redondantes sont bien connues lors de tâches statiques, elles le sont moins en conditions dynamiques, lors de mouvements. La partie expérimentale de cette thèse a permis de confirmer l’existence de mécanismes d’estimation et de contrôle optimaux des mouvements chez l’humain. En effet, nous avons mis en évidence l’intégration optimale d’information visuelle lors de la réalisation de saccades à la lumière: lors de séquences de saccades, le système visuomoteur est capable d’utiliser l’information visuelle pour mettre à jour ses estimations internes de la position de l’œil. Une étude complémentaire des sources de variabilité des saccades suggère un rôle similaire pour la proprioception extra-oculaire. Par une troisième expérience, novatrice, nous avons montré que le toucher est pris en compte en temps réel lors de mouvements de la main en contact avec une surface. Nous avons également inféré une mesure de la variance de l'information tactile. Enfin, à partir des connaissances sur la représentation des variables sensorimotrices dans le système nerveux, nous avons construit plusieurs réseaux de neurones qui implémentent de manière proche de l'optimum statistique la planification et le contrôle de mouvements / Our sensory inputs, as well as our movements, are uncertain. Nevertheless, our central nervous systems appears to be as accurate as possible: these uncertainties are handled in an optimal fashion. For example, redundant sensory signals are weighted according to their accuracy, and motor uncertainties are taken in account when movements are made. The characteristics of the combination of redundant sensory signals are well known for static tasks. However, they are less known in dynamic conditions. The experimental part of this thesis allowed to confirm the use of statistically optimal sensorimotor processes during movements. We showed that visual information can be integrated during sequences of saccades, the oculomotor system being able to use visual information to update its internal estimate of eye position. A complementary study on the sources of variability for saccadic eye movements suggests a similar role for extra-ocular proprioception. In a third original experiment, we showed that tactile input is optimally taken in account for the on-line control of arm movements during which fingertips are in contact with a textured surface. Last, we built several neuronal networks models simulating optimal movement planning. These networks were based on current knowledge about probabilistic representations in the nervous system

Die Kartographie ist eine Wissenschaft, die in ihrem Charakter starke interdisziplinäre Züge aufweist. Sie zeigt sich in den verschiedensten Facetten und wird darum in den unterschiedlichsten Wissenschaften angewandt. Markantester Charakter ist, schon per Definition, die Modellierung von geowissenschaftlichen Ereignissen und Sachverhalten. „A unique facility for the creation and manipulation of visual or virtual representations of geospace – maps – to permit the exploration, analysis, understanding and communication of information about that space.“(ICA 2003) Aus dieser Definition wird die Charakteristik einer Kommunikationswissenschaft (Brassel) deutlich. Gerade seit dem Paradigmenwechsel der 1970er Jahre fließen zahlreiche weitere Aspekte wie Informatik, Semiotik und Psychologie in das Verständnis von Kartographie ein. Dadurch wird die Karte nicht mehr als reines graphisches Mittel verstanden, sondern als Träger und Übermittler von Informationen verstanden. Der Kartennutzer und dessen Verständnis von Karten rücken dabei immer weiter in den Vordergrund und werden „Ziel“ der kartographischen Verarbeitung. Aus diesem Verständnis heraus, möchte ich in der folgenden Arbeit einen relativ neuen Einfluss und Aspekt der Kartographie vorstellen. Es handelt sich um das Modell der Self-Organizing Maps (SOM), welches erstmalig Anfang der 1980er Jahre von Teuvo Kohonen vorgestellt wurde und deshalb auch, von einigen Autoren, als Kohonenmaps bezeichnet wird. Dem Typus nach, handelt es sich dabei um künstliche neuronale Netze, welche dem Nervensystem des menschlichen Gehirns nachempfunden sind und damit allgemein als eine Art selbständiger, maschineller Lernvorgang angesehen werden können. Im Speziellen sind Self-Organizing Maps ein unüberwachtes Lernverfahren, das in der Lage ist völlig unbekannte Eingabewerte zu erkennen und zu verarbeiten. Durch diese Eigenschaft eignen sie sich als optimales Werkzeug für Data Mining sowie zur Visualisierung von hochdimensionalen Daten. Eine Vielzahl von Wissenschaftlern hat diesen Vorteil bereits erkannt und das Modell in ihre Arbeit einbezogen oder auf dessen Verwendbarkeit analysiert. Deshalb möchte in dieser Arbeit, einige dieser Verwendungsmöglichkeiten und den daraus resultierenden Vorteil für die Kartographie aufzeigen.

The central nervous system is the most likely target of mobile telephony radiofrequency field (RF) exposure in terms of biological effects. Several EEG (electroencephalography) studies have reported variations in the alpha-band power spectrum during and/or after RF exposure, in resting EEG and during sleep. In this context, the observation of the spontaneous electrical activity of neuronal networks under RF exposure can be an efficient tool to detect the occurrence of low-level RF effects on the nervous system. In this thesis research work we developed a dedicated experimental setup in the GHz range for the simultaneous exposure of neuronal networks and monitoring of electrical activity. A transverse electromagnetic (TEM) cell was used to expose the neuronal networks to GSM-1800 signals at a SAR level of 3.2 W/kg. Recording of the neuronal electrical activity and detection of the extracellular spikes and bursts under exposure were performed using Micro Electrode Arrays (MEAs). This work provides the proof of feasibility and preliminary results of the integrated investigation regarding exposure setup, culture of the neuronal network, recording of the electrical activity and analysis of the signals obtained under RF exposure. In the main experiment (16 cultures), there was a 30% reversible decrease in mean firing rate (MFR) and bursting rate (BR) during the 3 min exposures to RF. Additional experiments are needed to further characterize this effect, especially in terms of temperature elevation at the microscopic level.