O estudo dos efeitos de neurotransmissores e neuromoduladores em circuitos nervosos tradicionalmente consiste em observar o comportamento de um sistema, ou parte dele, quando exposto a concentrações constantes da droga, ignorando flutuações ou padrões temporais de liberação. Neste trabalho implementamos um protocolo dinâmico e dependente da atividade do próprio sistema nervoso, que permitiu estudar experimentalmente a influência da dinâmica de liberação nos efeitos que glutamato (Glu, 1 mM) e serotonina (5-HT, 10 mM) produzem no padrão emergente de um centro gerador de padrões (CPG). Os experimentos foram realizados no sistema nervoso estomatogástrico de Callinectes sapidus e Callinectes danae (CPG pilórico) durante sua operação normal in vitro, que pode ser caracterizada por sua frequência de burst, número de spikes/burst dos neurônios, duty cycle dos neurônios, etc. A partir da atividade de um dos neurônios do CPG, medida extracelularmente, um algoritmo baseado no protocolo dynamic clamp (interação em tempo real entre tecido nervoso vivo e simulação computacional) identifica em tempo real um padrão de atividade pré-escolhido e dispara um injetor de picolitros semelhante a um picospritzer®, aspergindo uma pequena quantidade de solução com a droga nas vizinhanças dos neurônios e sinapses que compõe o CPG, de onde é retirada por perfusão contínua de solução fisiológica. Assim, podemos comparar o comportamento emergente do CPG quando este é estimulado de maneira síncrona com sua atividade ou de maneira assíncrona, mas de forma que a mesma quantidade média de droga seja aspergida nos dois casos. Nossos resultados demonstram que um mesmo estímulo apresentado de duas maneiras diferentes, para um mesmo circuito nervoso, pode produzir respostas diferentes na mesma célula. O protocolo se mostrou mais eficiente em mostrar diferenças quando a atividade da droga ocorre em uma escala de tempo menor que aquela do comportamento do CPG. Novos estudos devem ser realizados com outros neutrotransmissores e moduladores tanto de ação ionotrópica quanto metabotrópica, para se adequar o protocolo aos diferentes tipos de substâncias. / Studying the effect of neurotransmitters and neuromodulators usually consists in observing the behavior of a system, or part of it, when exposed to stationary concentrations of the drugs that completely lack any time dependency. Here we describe a protocol that we developed to study the changes of the emerging rhythmic pattern of a Central Pattern Generator (CPG) due to the effects of the aplications dynamics of tiny puffs of glutamate (Glu, 1mM) or serotonin (5-HT, 10 mM) to the neurons and their neuropil. We experimented on the stomatogastric nervous system of Callinectes sapidus and Callinectes danae (pyloric CPG) during normal operation in vitro, that was characterized using bursting frequency, neurons number of spikes/burst, their duty cycle, etc. From the extracelular activity of one of the CPG neurons, a dynamic clamp based protocol (real time interaction between living nervous tissue and computer simulation) detected in real time a given pattern of activity present in a burst and triggered a picospritzer to puff a small amount of solution with the drug in the neighborhood of the neurons and synapses of the CPG, from where it was washed through constant perfusion of normal saline. Such arrangement allowed us to address what are the differences on the emerging CPG behavior when the stimuli was activity synchronous or asynchronous, but with the same mean amount of drug delivered in both cases. In general, our results showed that the same stimulus presented in different ways to the same nervous circuit may generate different responses even in a cell level. Finally, the protocol proved to be more efficient when the drug activity time scale is smaller than the time scale of the CPG bursting behavior. In the future we should work with other neuromodulators and neurotransmiters to improve the protocol.

Investigamos o papel de condutâncias iônicas lentas na transmissão/codificação de informação entre neurônios que disparam em rajadas ou bursts. Para isso, desenvolvemos um protocolo experimental no qual a interação em tempo real entre computador e neurônio biológico permite isolar o efeito da dinâmica de um determinado tipo de canal iônico e estudar sua inuência nos mecanismos de codificação de informação. Os experimentos foram realizados com neurônios do gânglio estomatogástrico do siri azul, Callinectes sapidus, que não possuem condutâncias lentas capazes de fazê-los apresentar rajadas de disparos quando in vitro, condição na qual apresentam comportamento quiescente ou disparam tonicamente. Durante os experimentos, alteramos artificialmente o comportamento de um destes neurônios, conectando-o a um computador que introduz uma corrente capaz de fazê-lo apresentar rajadas. Essa corrente possui uma componente senoidal (vinda de um gerador de funções) e uma componente devido a uma condutância iônica lenta modelada matematicamente. A condutância lenta pode ser escolhida entre duas versões: uma em que a condutância é calculada em tempo real, a partir do valor instantâneo do potencial de membrana do neurônio biológico, e outra em que o valor da condutância é oriundo de uma série temporal previamente gravada. A fonte de informação utilizada nos experimentos é um neurônio artificial pré-sináptico, que possui uma distribuição de potenciais de ação (spikes) escolhida pelo experimentador, e é conectado ao neurônio biológico modificado através de um modelo de sinapse química inibidora. A quantidade de informação do neurônio artificial (variabilidade dos padrões de disparo) codificada pelo neurônio biológico é inferida calculando-se a informação mútua média entre eles para as duas versões da condutância lenta (dinâmica ou previamente gravada). Nossos experimentos reproduziram qualitativamente as observações feitas por nosso grupo no circuito pilórico intacto do siri, que possui neurônios conectados por mutua inibição que naturalmente apresentam bursts. Além disso, observamos que vários picos de informação mútua média, presentes quando a condutância é dinâmica, desaparecem quando esta é substituída pela série temporal previamente gravada da condutância. Assim, pudemos confirmar os resultados previamente obtidos com simulações computacionais em que foram utilizados apenas modelos matemáticos e na ausência de ruído e demonstramos que as condutâncias iônicas lentas constituem um mecanismo biofísico que permite a codificação de estímulos sinápticos em neurônios que apresentam rajadas. / We investigated the role of slow ionic conductances on information processing by bursting neurons. A real time experimental protocol was developed to allow interacting computer models and biological neurons to address the effect of dynamical details of a single type of ion channel in information coding mechanisms. We experimented on Callinectes sapidus (blue crab) stomatogastric ganglion neurons. Such neurons were chosen because they do not present the slow conductances that can led to bursting activity in vitro (in such conditions they can be found either in a quiescent or in a tonic firing state). The experiments consisted in artificially changing the behavior of one of these neurons by injecting a computer generated current to achieve bursting. Such current has a sinusoidal component (from a function generator) and a component due to mathematical model of a slow ionic conductance. The slow conductance was implemented in two versions: in one of them the instantaneous value of the conductance is computed in real time and according to the membrane potential of the biological neuron, in another version the value of the conductance simply comes from a time series previously stored in the computer. A pre-synaptic artificial neuron, with a spike distribution chosen by the experimenter, provided input for the biological neuron through an artificial chemical inhibitory synapse. The amount of information (variability of spike patterns from the artificial neuron) coded by the biological neuron was inferred by calculating the average mutual information along stimulus and response bursts for the two conditions of the slow conductance (dynamically calculated or from file previously stored). Our experiments reproduced the results found in intact pyloric central pattern generator bursting neurons connected by mutual inhibition. Moreover, we show that the average mutual information peaks, found when the conductance is dynamically calculated, disappear when we use the previously recorded time series of the conductance. Such results validate those only found previously in numerical simulations in the absence of noise and point the role of the slow ionic conductances in a biophysical mechanism that allow bursting motor neurons to encode in a nontrivial fashion the information they receive through a single synapse.

O estudo dos efeitos de neurotransmissores e neuromoduladores em circuitos nervosos tradicionalmente consiste em observar o comportamento de um sistema, ou parte dele, quando exposto a concentrações constantes da droga, ignorando flutuações ou padrões temporais de liberação. Neste trabalho implementamos um protocolo dinâmico e dependente da atividade do próprio sistema nervoso, que permitiu estudar experimentalmente a influência da dinâmica de liberação nos efeitos que glutamato (Glu, 1 mM) e serotonina (5-HT, 10 mM) produzem no padrão emergente de um centro gerador de padrões (CPG). Os experimentos foram realizados no sistema nervoso estomatogástrico de Callinectes sapidus e Callinectes danae (CPG pilórico) durante sua operação normal in vitro, que pode ser caracterizada por sua frequência de burst, número de spikes/burst dos neurônios, duty cycle dos neurônios, etc. A partir da atividade de um dos neurônios do CPG, medida extracelularmente, um algoritmo baseado no protocolo dynamic clamp (interação em tempo real entre tecido nervoso vivo e simulação computacional) identifica em tempo real um padrão de atividade pré-escolhido e dispara um injetor de picolitros semelhante a um picospritzer®, aspergindo uma pequena quantidade de solução com a droga nas vizinhanças dos neurônios e sinapses que compõe o CPG, de onde é retirada por perfusão contínua de solução fisiológica. Assim, podemos comparar o comportamento emergente do CPG quando este é estimulado de maneira síncrona com sua atividade ou de maneira assíncrona, mas de forma que a mesma quantidade média de droga seja aspergida nos dois casos. Nossos resultados demonstram que um mesmo estímulo apresentado de duas maneiras diferentes, para um mesmo circuito nervoso, pode produzir respostas diferentes na mesma célula. O protocolo se mostrou mais eficiente em mostrar diferenças quando a atividade da droga ocorre em uma escala de tempo menor que aquela do comportamento do CPG. Novos estudos devem ser realizados com outros neutrotransmissores e moduladores tanto de ação ionotrópica quanto metabotrópica, para se adequar o protocolo aos diferentes tipos de substâncias. / Studying the effect of neurotransmitters and neuromodulators usually consists in observing the behavior of a system, or part of it, when exposed to stationary concentrations of the drugs that completely lack any time dependency. Here we describe a protocol that we developed to study the changes of the emerging rhythmic pattern of a Central Pattern Generator (CPG) due to the effects of the aplications dynamics of tiny puffs of glutamate (Glu, 1mM) or serotonin (5-HT, 10 mM) to the neurons and their neuropil. We experimented on the stomatogastric nervous system of Callinectes sapidus and Callinectes danae (pyloric CPG) during normal operation in vitro, that was characterized using bursting frequency, neurons number of spikes/burst, their duty cycle, etc. From the extracelular activity of one of the CPG neurons, a dynamic clamp based protocol (real time interaction between living nervous tissue and computer simulation) detected in real time a given pattern of activity present in a burst and triggered a picospritzer to puff a small amount of solution with the drug in the neighborhood of the neurons and synapses of the CPG, from where it was washed through constant perfusion of normal saline. Such arrangement allowed us to address what are the differences on the emerging CPG behavior when the stimuli was activity synchronous or asynchronous, but with the same mean amount of drug delivered in both cases. In general, our results showed that the same stimulus presented in different ways to the same nervous circuit may generate different responses even in a cell level. Finally, the protocol proved to be more efficient when the drug activity time scale is smaller than the time scale of the CPG bursting behavior. In the future we should work with other neuromodulators and neurotransmiters to improve the protocol.

Investigamos o papel de condutâncias iônicas lentas na transmissão/codificação de informação entre neurônios que disparam em rajadas ou bursts. Para isso, desenvolvemos um protocolo experimental no qual a interação em tempo real entre computador e neurônio biológico permite isolar o efeito da dinâmica de um determinado tipo de canal iônico e estudar sua inuência nos mecanismos de codificação de informação. Os experimentos foram realizados com neurônios do gânglio estomatogástrico do siri azul, Callinectes sapidus, que não possuem condutâncias lentas capazes de fazê-los apresentar rajadas de disparos quando in vitro, condição na qual apresentam comportamento quiescente ou disparam tonicamente. Durante os experimentos, alteramos artificialmente o comportamento de um destes neurônios, conectando-o a um computador que introduz uma corrente capaz de fazê-lo apresentar rajadas. Essa corrente possui uma componente senoidal (vinda de um gerador de funções) e uma componente devido a uma condutância iônica lenta modelada matematicamente. A condutância lenta pode ser escolhida entre duas versões: uma em que a condutância é calculada em tempo real, a partir do valor instantâneo do potencial de membrana do neurônio biológico, e outra em que o valor da condutância é oriundo de uma série temporal previamente gravada. A fonte de informação utilizada nos experimentos é um neurônio artificial pré-sináptico, que possui uma distribuição de potenciais de ação (spikes) escolhida pelo experimentador, e é conectado ao neurônio biológico modificado através de um modelo de sinapse química inibidora. A quantidade de informação do neurônio artificial (variabilidade dos padrões de disparo) codificada pelo neurônio biológico é inferida calculando-se a informação mútua média entre eles para as duas versões da condutância lenta (dinâmica ou previamente gravada). Nossos experimentos reproduziram qualitativamente as observações feitas por nosso grupo no circuito pilórico intacto do siri, que possui neurônios conectados por mutua inibição que naturalmente apresentam bursts. Além disso, observamos que vários picos de informação mútua média, presentes quando a condutância é dinâmica, desaparecem quando esta é substituída pela série temporal previamente gravada da condutância. Assim, pudemos confirmar os resultados previamente obtidos com simulações computacionais em que foram utilizados apenas modelos matemáticos e na ausência de ruído e demonstramos que as condutâncias iônicas lentas constituem um mecanismo biofísico que permite a codificação de estímulos sinápticos em neurônios que apresentam rajadas. / We investigated the role of slow ionic conductances on information processing by bursting neurons. A real time experimental protocol was developed to allow interacting computer models and biological neurons to address the effect of dynamical details of a single type of ion channel in information coding mechanisms. We experimented on Callinectes sapidus (blue crab) stomatogastric ganglion neurons. Such neurons were chosen because they do not present the slow conductances that can led to bursting activity in vitro (in such conditions they can be found either in a quiescent or in a tonic firing state). The experiments consisted in artificially changing the behavior of one of these neurons by injecting a computer generated current to achieve bursting. Such current has a sinusoidal component (from a function generator) and a component due to mathematical model of a slow ionic conductance. The slow conductance was implemented in two versions: in one of them the instantaneous value of the conductance is computed in real time and according to the membrane potential of the biological neuron, in another version the value of the conductance simply comes from a time series previously stored in the computer. A pre-synaptic artificial neuron, with a spike distribution chosen by the experimenter, provided input for the biological neuron through an artificial chemical inhibitory synapse. The amount of information (variability of spike patterns from the artificial neuron) coded by the biological neuron was inferred by calculating the average mutual information along stimulus and response bursts for the two conditions of the slow conductance (dynamically calculated or from file previously stored). Our experiments reproduced the results found in intact pyloric central pattern generator bursting neurons connected by mutual inhibition. Moreover, we show that the average mutual information peaks, found when the conductance is dynamically calculated, disappear when we use the previously recorded time series of the conductance. Such results validate those only found previously in numerical simulations in the absence of noise and point the role of the slow ionic conductances in a biophysical mechanism that allow bursting motor neurons to encode in a nontrivial fashion the information they receive through a single synapse.

There is a significant amount of computational literature on networks of neurons and their resulting behavior. This dissertation combines electrophysiology experiments with computational modeling to validate the assumptions and results found in this literature. First, we investigate the weak coupling assumption, which states that the phase response of a neuron to weak stimuli is separable from the stimulus waveform. For weak stimuli, there is an intrinsic neuronal property described by the infinitesimal phase response curve (IPRC) that will predict the phase response when convolved with the stimulus waveform. Here, we show that there is a linear relationship between the stimulus and phase response of the neuron, and that we are able to obtain IPRCs that successfully predict the neuronal phase response. Next, we use hybrid networks of neurons to study the phase locking behavior of networks as the synaptic time constant is changed. We verify that networks show anti-phase synchrony for fast time constants, and in-phase synchrony for slow time constants. We also show that phase models and phase response curves (PRCs) qualitatively predict phase locking observed in electrophysiology experiments. Finally, we investigate the stability of the dynamic clamp system. We determined that the maximal conductance of the current being simulated, the dynamic clamp sampling rate, the amount of electrode resistance compensation, and the amount of capacitance compensation all affect when the instability is present. There is a dramatic increase in stability when the electrode resistance and system capacitance are well compensated.

No description available.

In the central nervous system, most of the processes ranging from ion channels to neuronal networks occur in a closed loop, where the input to the system depends on its output. In contrast, most experimental preparations and protocols operate autonomously in an open loop and do not depend on the output of the system. Real-time software technology can be an essential tool for understanding the dynamics of many biological processes by providing the ability to precisely control the spatiotemporal aspects of a stimulus and to build activity-dependent stimulus-response closed loops. So far, application of this technology in biological experiments has been limited primarily to the dynamic clamp, an increasingly popular electrophysiology technique for introducing artificial conductances into living cells. Since the dynamic clamp combines mathematical modeling with electrophysiology experiments, it inherits the limitations of both, as well as issues concerning accuracy and stability that are determined by the chosen software and hardware. In addition, most dynamic clamp systems to date are designed for specific experimental paradigms and are not easily extensible to general real-time protocols and analyses. The long-term goal of this research is to develop a suite of real-time tools to evaluate the performance, improve the efficacy, and extend the capabilities of the dynamic clamp technique and real-time neural electrophysiology. We demonstrate a combined dynamic clamp and modeling approach for studying synaptic integration, a software platform for implementing flexible real-time closed-loop protocols, and the potential and limitations of Kalman filter-based techniques for online state and parameter estimation of neuron models.

Neuroprosthetics is at the intersection of neuroscience, biomedical engineering, and physics. A biocompatible neuroprosthesis contains artificial neurons exhibiting biophysically plausible dynamics. Hybrid systems analysis could be used to prototype such artificial neurons. Biohybrid systems are composed of artificial and living neurons coupled via real-time computing and dynamic clamp. Model neurons must be thoroughly tested before coupled with a living cell. We use bifurcation theory to identify hazardous regimes of activity that may compromise biocompatibility and to identify control strategies for regimes of activity desirable for functional behavior. We construct real-time artificial neurons for the analysis of hybrid systems and demonstrate a mechanism through which an artificial neuron could maintain duty cycle independent of variations in period.

Rhythmic neural activity is thought to underlie many high-level functions of the nervous system. Our goals are to understand rhythmic activity starting with small networks, using theoretical and experimental tools. Phase resetting theory describes essential properties that cause and destroy rhythms. We validate and extend one branch of this theory, testing it in bursting neurons coupled by excitation and then extending the theory to account for temporal variability found in our experimental data. We show that the theory makes good predictions of rhythmic activity in heterogeneous networks. We also note differences in mathematical structure between inhibition- and excitation-coupling that cause them to behave differently in noisy contexts and may explain why all central pattern generators (CPGs) found in nature are dominated by inhibition. Our extension of the theory gives a method that is useful to compare experimental and model data and shows that noise may either create or destroy a rhythm. Finally, we described the cellular mechanisms in Aplysia that switch the feeding CPG from arrhythmic to rhythmic behavior in response to reward stimuli. Previous studies showed that a Dopamine reward signal is correlated to changes in electrical coupling and excitability in several important neurons in the CPG. Using the dynamic clamp and an in vitro analog of the full behavioral system, we were able to determine that electrical coupling alone controls rhythmicity, while excitability independently controls the rate of activity. These results beg for further study, including new theory to explain them fully.

Les motoneurones tiennent une place remarquable dans l'organisme : ils constituent l'interface entre le système nerveux central et le système musculaire. Leur excitabilité est une caractéristique primordiale dans le comportement moteur puisqu'elle définit la force musculaire développée en réponse à la commande motrice. Chez la souris, la décharge des motoneurones est marquée par la présence d'oscillations de mode mixte (MMOs) entre les potentiels d'action. Ces MMOs permettent la décharge des motoneurones à basse fréquence et sont responsables d'un régime de décharge particulier nommé zone sous-Primaire, pendant lequel la fréquence de décharge est très variable et le gain de la relation courant-Fréquence élevé. Nous avons étudié les mécanismes responsables de l'apparition de ces MMOs à la fois de manière expérimentale, dans une préparation in vivo de souris anesthésié, incluant l'utilisation du Dynamic Clamp, et théorique, au moyen d'un modèle mono-Compartimental de motoneurone. Nos résultats ont montré que ces MMOs étaient causées par les courants sodiques et potassiques responsables des potentiels d'action et qu'elles émergeaient d'un état de faible excitabilité de la membrane, dû à l'inactivation lente des courants sodiques. Nous avons également montré que le courant de post-Hyperpolarisation pouvait paradoxalement augmenter l’excitabilité des motoneurones et réduire les MMOs en dé-Inactivant le courant sodique. La Sclérose Latérale Amyotrophique (SLA) conduit à la dégénérescence spécifique de ces motoneurones qui s'accompagne d'une vacuolisation de leur arborisation dendritique. L'augmentation précoce de l'excitabilité des motoneurones dans la maladie a largement été évoquée pour rendre compte de leur atteinte. Une hyperexcitabilité, aussi bien d'origine intrinsèque qu'extrinsèque pourrait en effet produire une excitotoxicité délétère pour la cellule. Si une telle modification de l'excitabilité est en cause dans la maladie, elle devrait persister jusqu'aux âges auxquels se produisent les premières dénervations des jonctions neuromusculaires. Nous avons enregistré les propriétés électrophysiologiques des motoneurones dans une préparation in vivo de souris adultes SOD1-G93A, modèle de la SLA. Nos résultats ont montré que leur conductance d'entrée était augmentée dans les jours qui précèdent les premières dénervations de leurs jonctions neuromusculaires. Malgré cela, leur excitabilité n'était pas modifiée. Loin d'être intrinsèquement hyperexcitables, une fraction d'entre eux perdaient même leur capacité à décharger de manière répétée. Nous avons finalement étudié la vacuolisation qui prend place dans les dendrites des motoneurones au cours de la maladie et son lien avec la couverture synaptique. Nous avons montré que la vacuolisation dendritique prenait place avant les dénervations et que la taille des vacuoles augmentait avec l'âge des souris SOD1-G93A. De manière intéressante, cette progression semblait plus rapide dans les motoneurones les plus sensibles à la maladie. Bien que la couverture synaptique n'était pas modifiée au cours de la maladie, nous avons mis en évidence une densité de synapses excitatrices et inhibitrices plus importante sur les régions dendritiques qui se vacuolisent. Ces résultats suggèrent un lien entre l'activité synaptique et la formation de vacuoles dans les motoneurones au cours de la SLA. Les motoneurones ne présentant pas d'hyperexcitabilité intrinsèque, une excitotoxicité d'origine synaptique pourrait alors être responsable de leur dégénérescence. / Motoneurones hold a remarkable position in the organism: they are the interface between the central nervous system and the muscular system. Their excitability is a crucial characteristic in motor behavior since it determines the muscular force produced in response to motor command. In mice, motoneurone discharge is marked by the presence of sub-Threshold oscillations between action potentials which create a behavior of mixed mode oscillations (MMOs). These MMOs allow the motoneurones to fire at low frequency and are responsible for a sub-Primary range of discharge during which the firing frequency is irregular and the slope of current-Frequency relation is steep. We investigated the mechanisms responsible for these MMOs by in vivo recordings in anesthetized mice, using Dynamic Clamp, and by theoretical modelization in a monocompartimental model of motoneurone. Our results showed that MMOs were caused by sodium and potasium currents responsible for action potentials and that they emerged from a state of low membrane excitability caused by a slow inactivation of the sodium current. Paradoxically, we also showed that the after-Hyperpolarization current was able to increase the membrane excitability and to reduce MMOs by de-Inactivating the sodium current. Amyotrophic Lateral Sclerosis (ALS) leads to the specific degeneration of these motoneurones and is accompanied by a vacuolation of their dendritic trees. An early increase in motoneurons excitability during the disease has been widely proposed to account for their degeneration. Indeed, a motoneuron hyperexcitability of intrinsic or extrinsic origin could produce a deleterious excitotoxicity. If such a change of excitability is involved in the disease, it should last until the ages where the first denervation of neuromuscular junctions occurs. We recorded the electrophysiological properties of motoneurones in an in vivo preparation of adult SOD1-G93A mice, model of ALS. Our results showed that their input conductance was increased before the first denervation of their neuromuscular junctions. Nevertheless, their excitability was not modified. Far from being intrinsically hyperexcitable, a fraction of them even lost their ability to discharge repeatedly. We finally studied the vacuolation that takes place in dendrites of motoneurones during the disease and its relation with synaptic coverage. We have shown that the dendritic vacuolation takes place before the denervation and that the size of these vacuoles increases with age in SOD1-G93A mice. Interestingly, this increase was faster in the most vulnerable motoneurones. Although synaptic coverage was not altered in the disease, we ¬revealed higher densities of excitatory and inhibitory synapses on dendritic regions that vacuolate. These results suggest a link between synaptic activity and vacuoles formation in motoneurones during ALS. Motoneurones were not intrinsically hyperexcitable, instead, an excitotoxicity from a synaptic origin may be responsible for their degeneration.