abstract: Locomotion in natural environments requires coordinated movements from multiple body parts, and precise adaptations when changes in the environment occur. The contributions of the neurons of the motor cortex underlying these behaviors are poorly understood, and especially little is known about how such contributions may differ based on the anatomical and physiological characteristics of neurons. To elucidate the contributions of motor cortical subpopulations to movements, the activity of motor cortical neurons, muscle activity, and kinematics were studied in the cat during a variety of locomotion tasks requiring accurate foot placement, including some tasks involving both expected and unexpected perturbations of the movement environment. The roles of neurons with two types of neuronal characteristics were studied: the existence of somatosensory receptive fields located at the shoulder, elbow, or wrist of the contralateral forelimb; and the existence projections through the pyramidal tract, including fast- and slow-conducting subtypes. Distinct neuronal adaptations between simple and complex locomotion tasks were observed for neurons with different receptive field properties and fast- and slow-conducting pyramidal tract neurons. Feedforward and feedback-driven kinematic control strategies were observed for adaptations to expected and unexpected perturbations, respectively, during complex locomotion tasks. These kinematic differences were reflected in the response characteristics of motor cortical neurons receptive to somatosensory information from different parts of the forelimb, elucidating roles for the various neuronal populations in accommodating disturbances in the environment during behaviors. The results show that anatomical and physiological characteristics of motor cortical neurons are important for determining if and how neurons are involved in precise control of locomotion during natural behaviors. / Dissertation/Thesis / Doctoral Dissertation Neuroscience 2015

Este trabalho descreve uma simulação computacional biologicamente plausível do sistema olfativo de vertebrados. O modelo construído foi capaz de reproduzir satisfatoriamente características importantes observadas no sistema olfativo de vertebrados, incluindo a recepção de diferentes concentrações e tipos de odores no epitélio olfativo e a propagação dessa informação para o bulbo. Ele também tornou possível a observação de diferentes padrões de resposta odorífera, tanto no epitélio como no bulbo, associados a diferentes odores usados nas simulações. / This work describes a biologically plausible simulation of the olfactory system of vertebrates. The constructed model was capable of reproducing satisfactorily important characterisitics observed in the vertebrate olfactory system, including the reception of different concentrations and odor types at the epithelium and the propagation of this information to the olfactory bulb. Also, it made possible the observation of the different response patterns, both in the epithelium as in the olfactory bulb, associated with different odors used in the simulations.

O entendimento de como a informação é representada e processada no cérebro e quais são os mecanismos necessários para que isto seja possível é um dos grandes desafios da neurociência. A atividade populacional das células corticais possui dinâmica emergente bastante complexa, apresentando padrões auto-sustentados mesmo na ausência de estímulos externos. Esses padrões de atividade podem representar estados internos de auto-organização da rede neural cortical. Porém, quais características da rede cortical seriam essenciais para o entendimento deste tipo de atividade? Podemos elencar duas características fundamentais: a organização topológica da rede e as características dinâmicas das unidades funcionais da rede (os neurônios). Neste trabalho estudamos a influência da topologia e da dinâmica dos neurônios sobre a atividade auto-sustentada de dois modelos corticais diferentes. O primeiro modelo possui arquitetura hierárquica e modular construída segundo uma estratégia top-down. As simulações com este modelo mostram que criação hierárquica de módulos favorece a atividade auto-sustentada em concordância com trabalhos anteriores de outros autores. Também observamos que diferentes classes funcionais de neurônios influenciam de maneiras distintas a atividade auto-sustentada da rede. O segundo modelo possui arquitetura em camadas com regras intra- e inter-laminares específicas baseadas em dados anatômicos do córtex visual primário de gatos. As simulações com este modelo mostram um importante papel das condutâncias sinápticas excitatórias e inibitórias sobre o início da atividade auto-sustentada na rede, especialmente sobre a largura (intervalo de valores da condutância excitatória) da zona de transição entre as regiões com e sem atividade auto-sustentada no diagrama de condutâncias sinápticas. Conclui-se que a topologia da rede cortical e sua composição em termos de combinações de neurônios de diferentes tipos têm importante papel sobre a existência e as propriedades da atividade auto-sustentada na rede. / To understand how information is represented and processed in the brain and the necessary mechanisms for this is one of the major challenges in neuroscience. The population activity of cortical cells has complex and emergent dynamics, showing self-sustained activity patterns even in the absence of external stimuli. These activity patterns may represent internal self-organizing states of the cortical network. Which characteristics that make up the cortical network would be essential to understand this type of activity? We can list two basic characteristics: the topological organization of the network and the dynamic characteristics of its functional units (the neurons). In this work we studied the influence of topology and neuronal dynamics on self-sustained activity in two different cortical network models. The first model has hierarchical and modular architecture constructed according to a top-down strategy. Simulations with this model show that the hierarchical creation of modules favors self-sustained activity in agreement with results from other authors. We also observed that different functional neuronal classes influence in distict ways the self-sustained activity. The second model has a layered architecture with specific intra- and inter-laminar rules based on anatomical evidence from the primary visual cortex of cats. Simulations with this model show an important role of excitatory and inhibitory synaptic conductances on the beginning of self-sustained network activity, specially on the width of the border (range of excitatory conductance values) between regions with and without self-sustained activity in the excitatory-inhibitory synaptic conductances diagram. We conclude that network topology and its composition in terms of combinations of neurons with different dynamics have an important role on the existence and properties of self-sustained activity in the network.

Desde que surgiu, o computador vem sendo utilizado na modelagem de fenômenos em todas as áreas do conhecimento. Em neurociências, a modelagem computacional é utilizada para descrever, reproduzir e fazer previsões sobre o comportamento dos diferentes componentes do sistema nervoso. Assim como em outras áreas das ciências, este procedimento tem-se mostrado eficiente no estudo e aprimoramento das teorias a respeito da função cerebral. Com o crescente aumento do poder computacional, maiores e mais detalhados modelos podem ser construídos com um grau de realismo biológico cada vez maior. Neste trabalho, apresentamos modelos computacionais biologicamente plausíveis de neurônios corticais do sistema somestésico primário. Os modelos foram construídos com base no formalismo de Hodgkin-Huxley para a implementação de canais iônicos e na técnica de compartimentalização de Rall para modelar sua extensão espacial. Os parâmetros foram ajustados a partir de resultados experimentais 'in vivo' e 'in vitro' com neurônios, retirados da literatura. Os resultados das simulações mostraram que os modelos são biologicamente aceitáveis e de qualidade superior a de outros modelos construídos anteriormente, possibilitando a construção de modelos de redes neuronais em larga escala mais precisos. / Since its appearance, the computer has been used to model phenomena in all areas of knowledge. In neuroscience, computer modeling is used to describe, reproduce and predict behaviors of different components of the nervous system. As well as in other areas of sciences, this procedure has been shown to be efficient in the study and improvement of theories on brain function. With the increasing power of computers, larger and more detailed models can be constructed with an increasing degree of biological realism. In this work, we present biologically plausible computer models of cortical neurons from the primary somatosensory system. The models have been implemented based on the Hodgkin-Huxley formalism for ionic channels and the Rall´s compartmental technique for spatial extent. The parametrs have been adjusted based on in vivo and in vitro experimental results taken from the literature. Simulation results have shown that the models are biologically acceptable and of superior quality in comparison with previous models, allowing the construction of more precise large-scale neuronal network models.

A ocorrência de status epileticus (SE) desencadeia algumas alterações no sistema nervoso central. O giro denteado (GD) do hipocampo sofre com modificações na expressão gênica dos canais iônicos das células granulares (CGs) e essas células sofrem alterações morfológicas. Essas alterações se manifestam com o brotamento de fibras musgosas, redução no número de espinhas dendríticas, encurtamento e estreitamento da arborização dendrítica. As modificações na expressão gênica dos canais iônicos afetam suas densidades máximas de condutância. Este estudo utilizou 40 modelos computacionais realistas para simular alterações nas condutâncias de canais iônicos e seus efeitos sobre dois grupos de CGs do GD. Os modelos foram construídos com base em reconstruções tridimensionais de 20 CGS com morfologia alterada após SE induzido por pilocarpina (CG-PILO) e 20 de morfologia normal (CG-controle). Foram dotados dos canais iônicos de sódio rápido (Na), canal de potássio de retificação tardia rápido (fKdr), canal de potássio de retificação tardia lento (fKdr), canal de potássio de tipo A (KA), canal de potássio dependente de cálcio e de voltagem de alta condutância (BK), canal de potássio dependente de cálcio de baixa condutância (SK) e canais de cálcio dos tipos T, N e L. As simulações foram realizadas no software Neuron. Foram realizados test t para detectar se ocorre diferenças significativas entre os grupos CG-controle e CG-PILO As alterações nas densidades máximas de condutância provocaram mudanças nos parâmetros de excitabilidade dos grupos CG-PILO e CG- controle, alterando valores de frequência de disparos, reobase e cronaxia. Os grupos apresentam respostas significativamente diferentes para as médias de reobase para a maioria dos valores de densidade máxima de condutância,, porém para cronaxia a maioria dos grupo não apresentou diferenças significativas. O grupo CG-controle apresentou médias maiores de frequência de disparos que o CG-PILO e o grupo CG-PILO apresentou valores de reobase maior para as alterações de densidade de condutância da maioria dos canais, sendo essas diferenças significativas. / The occurrence of status epilepticus (SE) triggers some changes in the central nervous system. The dentate gyrus (DG) of the hippocampus suffers from changes in gene expression of ion channels of granule cells (GCs) and these cells undergo morphological changes. These changes manifest themselves with mossy fiber sprouting, reduction in the number of dendritic spines, shortening and narrowing of dendritic branching. Changes in gene expression of ion channels affect their maximum densities of conductance. This study used 40 realistic computer models to simulate changes in conductance of ion channels and its effect on two groups of CGs of the GD. The models were built based on three-dimensional reconstructions of 20 CGS with morphology changed after pilocarpine-induced SE (CG-PILO) and 20 normal morphology (CG-control). The models were equipped with the ion channels of fast sodium (Na), fast delayed rectifying potassium channel (fKDR), slow delayed rectifying potassium channel (fKdr), potassium channel type A (KA), potassium channel dependent calcium and high voltage conductance (BK), potassium channel dependent calcium low conductance (SK) and the calcium channel types T, N and L. The simulations were performed at Neuron software.T tests were performed to p-values <0.05 for detecting significant differences between the GC-control group and GC-PILO. Changes in maximum densities conductance caused changes in excitability parameters CG-PILO and GC- control groups, by changing frequency values of spikes, rheobase and chronaxie. The groups have significantly different responses to the averages for the most rheobase maximum density values of conductance, but these differences were shortly found for chronaxie values. The CG-control group had higher average frequency of spikes than the CG-PILO group. The CG-PILO group had rheobase values higher for conductance density changes the most channels. These differences are significant.

Esse trabalho consiste no estudo de alguns mecanismos responsáveis pela geração das oscilações elétricas observadas no sistema olfativo de vertebrados e das possíveis funções que essas oscilações possam ter no processamento da informação olfativa. Da-se especial atenção ao papel desempenhado pelo ritmo respiratório e pelas sinapses químicas e elétricas nesse processo. Para realizar essa investigação, foram utilizados modelos computacionais que reproduzem aspectos da anatomia e da fisiologia do epitélio olfativo, do bulbo olfativo e do córtex piriforme. Os modelos foram desenvolvidos e simulados no neurossimulador GENESIS, funcionando no sistema operacional LINUX. A análise dos resultados foi feita no programa MATLAB (Mathworks™). Inicialmente, a tese faz uma descrição do substrato neurobiológico que compõe as camadas iniciais do sistema olfativo, incluindo o epitélio, bulbo e córtex olfativo, e de como a informação olfativa é processada por cada camada, discutindo a importância do sentido olfativo e a relevância da neurociência computacional no estudo da origem e do papel das oscilações elétricas existentes nesse sistema (Capítulo 1). O capítulo 2 descreve os materiais e métodos utilizados para a construção dos modelos computacionais e para análise dos resultados. O capítulo 3 faz uma descrição detalhada do modelo computacional utilizado e dos experimentos realizados com o modelo. Finalmente, o capítulo 4 apresenta e discute os resultados das simulações realizadas e o capítulo 5 estende essa discussão, concluindo a tese. O capítulo 6 contém as referências bibliográficas utilizadas no trabalho. Os resultados do trabalho sugerem que as oscilações elétricas no sistema olfativo poderiam ser geradas em várias estruturas e níveis de organização, abrangendo os níveis moleculares, celulares e de sistemas neurais. E que as sinapses químicas e elétricas, assim como os ritmos respiratórios, podem ter um papel fundamental na geração dessas oscilações. Assim, o modelo construído propõe uma explicação plausível para a origem das oscilações elétricas no sistema olfativo de vertebrados e discute as possíveis funções que essas oscilações teriam no contexto do processamento da informação sensorial. / This work is a study of some mechanisms associated with the generation of electric oscillations in the vertebrate olfactory system. Special attention is given for the role of the respiratory rhythm, chemical synapses and electrical synapses in this process. The possible functions of the electric oscillations in olfactory information processing are explored. A computational model that reproduces aspects of the anatomy and physiology of the olfactory epithelium, bulb and piriform cortex was utilized to realize this investigation. The models were developed and simulated in the GENESIS neurosimulator, running under the LINUX operational system. The analysis of the results was made in the software MATLAB (Mathworks™). In the beginning, the thesis describe the neurobiological substracts of the initial layers of the olfactory system, including the olfactory epithelium, bulb and piriform cortex, and explore how the olfactory information is processed by each layer. The chapter 1 presents the importance of the olfactory sense and the use of computational neuroscience to study the role of the electric oscillations in this system. The chapter 2 explains the material and methods utilized to develop the computational model and to analyse the data generated by the model. The chapter 3 describes the used computational model and the experiments realized with the model. Finally, the chapter 4 presents and discusses the results of the simulations. The chapter 5 extends the discussion and concludes the thesis. The chapter 6 contains the bibliographic references. The results of the work suggest that electric oscillations in the olfactory system could be generated in several structures and organizational levels, including the molecular level, the cellular and neural systems level. In particular, the results shown that chemical and electric synapses, as well as the respiratory rhythm, may have a fundamental role in the generation of these oscillations. Indeed, the constructed model proposes a plausible explanation for the origin of the electrical oscillations in the vertebrate olfactory system and discusses the possible function of these oscillations in the context of sensorial information processing.

This thesis aims to understand the learning mechanisms which underpin the process of visual object recognition in the primate ventral visual system. The computational crux of this problem lies in the ability to retain specificity to recognize particular objects or faces, while exhibiting generality across natural variations and distortions in the view (DiCarlo et al., 2012). In particular, the work presented is focussed on gaining insight into the processes through which transformation-invariant visual representations may develop in the primate ventral visual system. The primary motivation for this work is the belief that some of the fundamental mechanisms employed in the primate visual system may only be captured through modelling the individual action potentials of neurons and therefore, existing rate-coded models of this process constitute an inadequate level of description to fully understand the learning processes of visual object recognition. To this end, spiking neural network models are formulated and applied to the problem of learning transformation-invariant visual representations, using a spike-time dependent learning rule to adjust the synaptic efficacies between the neurons. The ways in which the existing rate-coded CT (Stringer et al., 2006) and Trace (Földiák, 1991) learning mechanisms may operate in a simple spiking neural network model are explored, and these findings are then applied to a more accurate model using realistic 3-D stimuli. Three mechanisms are then examined, through which a spiking neural network may solve the problem of learning separate transformation-invariant representations in scenes composed of multiple stimuli by temporally segmenting competing input representations. The spike-time dependent plasticity in the feed-forward connections is then shown to be able to exploit these input layer dynamics to form individual stimulus representations in the output layer. Finally, the work is evaluated and future directions of investigation are proposed.

La localisation des sources en azimuth repose sur le traitement des différences de temps d'arrivée des sons à chacune des oreilles: les différences interaurales de temps (``Interaural Time Differences'' (ITD)). Pour certaines espèces, il a été montré que cet indice dépendait du spectre du signal émis par la source. Pourtant, cette variation est souvent ignorée, les humains et les animaux étant supposés ne pas y être sensibles. Le but de cette thèse est d'étudier cette dépendance en utilisant des méthodes acoustiques, puis d'en explorer les conséquences tant au niveau électrophysiologique qu'au niveau de la psychophysique humaine. A la proximité de sphères rigides, le champ sonore est diffracté, ce qui donne lieu à des régimes de propagation de l'onde sonore différents selon la fréquence. En conséquence, quand la tête d'un animal est modélisée par une sphère rigide, l'ITD pour une position donnée dépend de la fréquence. Je montre que cet effet est reflété dans les indices humains en analysant des enregistrements acoustiques pour de nombreux sujets. De plus, j'explique cet effet à deux échelles: localement en fréquence, la variation de l'ITD donne lieu à différents délais interauraux dans l'enveloppe et la structure fine des signaux qui atteignent les oreilles. Deuxièmement, l'ITD de sons basses-fréquences est généralement plus grand que celui pour des sons hautes-fréquences venant de la même position. Dans une seconde partie, je discute l'état de l'art sur le système binaural sensible à l'ITD chez les mammifères. J'expose que l'hétérogénéité des réponses de ces neurones est prédite lorsque l'on fait l'hypothèse que les cellules encodent des ITDs variables avec la fréquence. De plus, je discute comment ces cellules peuvent être sensibles à une position dans l'espace, quel que soit le spectre du signal émis par la source. De manière générale, j'argumente que les données disponibles chez les mammifères sont en adéquation avec l'hypothèse de cellules sélectives à une position dans l'espace. Enfin, j'explore l'impact de la dépendance en fréquence de l'ITD sur le comportement humain, en utilisant des techniques psychoacoustiques. Les sujets doivent faire correspondre la position latérale de deux sons qui n'ont pas le même spectre. Les résultats suggèrent que les humains perçoivent des sons avec différents spectres à la même position lorsqu'ils ont des ITDs différents, comme prédit part des enregistrements acoustiques. De plus, cet effet est prédit par un modèle sphérique de la tête du sujet. En combinant des approches de différents domaines, je montre que le système binaural est remarquablement adapté aux indices disponibles dans son environnement. Cette stratégie de localisation des sources utilisée par les animaux peut être d'une grande inspiration dans le développement de systèmes robotiques. / Azimuth sound localization in many animals relies on the processing of differences in time-of-arrival of the low-frequency sounds at both ears: the interaural time differences (ITD). It was observed in some species that this cue depends on the spectrum of the signal emitted by the source. Yet, this variation is often discarded, as humans and animals are assumed to be insensitive to it. The purpose of this thesis is to assess this dependency using acoustical techniques, and explore the consequences of this additional complexity on the neurophysiology and psychophysics of sound localization. In the vicinity of rigid spheres, a sound field is diffracted, leading to frequency-dependent wave propagation regimes. Therefore, when the head is modeled as a rigid sphere, the ITD for a given position is a frequency-dependent quantity. I show that this is indeed reflected on human ITDs by studying acoustical recordings for a large number of human and animal subjects. Furthermore, I explain the effect of this variation at two scales. Locally in frequency the ITD introduces different envelope and fine structure delays in the signals reaching the ears. Second the ITD for low-frequency sounds is generally bigger than for high frequency sounds coming from the same position. In a second part, I introduce and discuss the current views on the binaural ITD-sensitive system in mammals. I expose that the heterogenous responses of such cells are well predicted when it is assumed that they are tuned to frequency-dependent ITDs. Furthermore, I discuss how those cells can be made to be tuned to a particular position in space irregardless of the frequency content of the stimulus. Overall, I argue that current data in mammals is consistent with the hypothesis that cells are tuned to a single position in space. Finally, I explore the impact of the frequency-dependence of ITD on human behavior, using psychoacoustical techniques. Subjects are asked to match the lateral position of sounds presented with different frequency content. Those results suggest that humans perceive sounds with different frequency contents at the same position provided that they have different ITDs, as predicted from acoustical data. The extent to which this occurs is well predicted by a spherical model of the head. Combining approaches from different fields, I show that the binaural system is remarkably adapted to the cues available in its environment. This processing strategy used by animals can be of great inspiration to the design of robotic systems.

Absence epilepsy is a neurological disorder that commonly occurs in children. Some studies have shown that absence seizures predominantly originate either in the thalamus or the cerebral cortex. Some cerebellar nuclei (CN) neurons project to these brain areas, as explained further in Fig. 2.6 in Chapter 2. Also, some CN neurons have been observed to show modulation during the absence seizures. This indicates that they somehow participate in the seizure and hence are referred to as "participating neurons" in this thesis. In this research, I demonstrate how machine learning techniques and computer simulations can be applied to investigate the properties and the input conditions present in these participating neurons. My investigation found a sub-group of CN neurons, with similar interictal spiking activity, spiking activity between the seizures, that are most likely to participate in seizures. To investigate the input conditions present in the CN neurons that produce this type of interictal activity, I used a morphologically realistic conductance based model of an excitatory CN projection neuron [66] and optimised the input parameters to this model using an Evolutionary Algorithm (EA). The results of the EA revealed that these participating CN neurons receive a synchronous and bursting input from Purkinje cells and bursting input with long intervals(approx. 500ms) from mossy fibre. The same interictal activity can also be produced when the Purkinje cell input to the CN neuron is asynchronous. The excitatory input in this case also had long interburst intervals but there is a decrease in excitatory and inhibitory synaptic weight. Surprisingly, a slight change in these input parameters can change the interictal spiking pattern to an ictal spiking pattern, the spiking pattern observed during absence seizures. I also discovered that it is possible to prevent a participating CN neuron from taking part in the seizures by blocking the Purkinje cell input.

abstract: The increasing availability of experimental data and computational power have resulted in increasingly detailed and sophisticated models of brain structures. Biophysically realistic models allow detailed investigations of the mechanisms that operate within those structures. In this work, published mouse experimental data were synthesized to develop an extensible, open-source platform for modeling the mouse main olfactory bulb and other brain regions. A “virtual slice” model of a main olfactory bulb glomerular column that includes detailed models of tufted, mitral, and granule cells was created to investigate the underlying mechanisms of a gamma frequency oscillation pattern (“gamma fingerprint”) often observed in rodent bulbar local field potential recordings. The gamma fingerprint was reproduced by the model and a mechanistic hypothesis to explain aspects of the fingerprint was developed. A series of computational experiments tested the hypothesis. The results demonstrate the importance of interactions between electrical synapses, principal cell synaptic input strength differences, and granule cell inhibition in the formation of the gamma fingerprint. The model, data, results, and reproduction materials are accessible at https://github.com/justasb/olfactorybulb. The discussion includes a detailed description of mechanisms underlying the gamma fingerprint and how the model predictions can be tested experimentally. In summary, the modeling platform can be extended to include other types of cells, mechanisms and brain regions and can be used to investigate a wide range of experimentally testable hypotheses. / Dissertation/Thesis / Doctoral Dissertation Neuroscience 2019