This work presents a computational tool to support the evaluation of displacement and strain fields by using Digital Image Correlation (DIC) techniques. Two images, referring to different stages of the problem, are analyzed in order to measure these fields. As most often experimental tests are on small scale, the required tools may interfere with the analisys results. Therefore, non-destructive techniques as the DIC can be used as supporting tools for these tests. Besides, DIC is also used in situations when the access doesn’t allow the proper positioning of the tool. The subset DIC algorithm is applied, which consists in splitting the images into subregions, in which the displacements and strains are evaluated. In order to obtain the unknown fields over the whole image, the results from each subregion are interpolated. Then, tests are performed to validate the proposed methodology through four examples, by comparing the results with analytical, numerical or experimental ones, presented in the literature, in which a good level of agreement is observed. Furthermore, two numerical examples are simulated, concerning a triaxial compression test and a diametral compression test. In both cases, the displacement values are obtained with minor errors. / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho apresenta uma ferramenta computacional para auxiliar na análise de campos de deslocamentos e deformações através de técnicas de correlação de imagens digitais (DIC) e consiste na avaliação de duas imagens em estágios diferentes de um determinado problema para a obtenção desses campos. Como na maioria das vezes os ensaios experimentais são realizados em modelos reduzidos, as instrumentações normalmente utilizadas podem afetar os resultados da análise. Então, técnicas não destrutivas como a DIC podem ser utilizadas como ferramentas de apoio a esses ensaios. Além disso, a DIC também é utilizada na análise de elementos com difícil acesso para a colocação da instrumentação convencional. Neste trabalho utiliza-se a técnica Subset DIC Algorithm que divide as imagens em várias sub-regiões e analisa os deslocamentos e as deformações para cada sub-região. Para a obtenção do campo de deslocamentos e deformações da imagem faz-se uma interpolação dos resultados obtidos em cada sub-região. Em seguida, são realizados testes para a validação da metodologia proposta através de quatro exemplos, inclusive fazendo comparações dos resultados com respostas analíticas, numéricas ou experimentais encontradas na literatura, em que, obtiveram-se respostas satisfatórias na obtenção dos campos de deslocamentos e deformações. Também são realizados dois estudos de caso sendo um sobre o ensaio de compressão triaxial e o outro sobre o ensaio de compressão diametral. Em ambos os estudos de caso é possível obter os campos de deslocamentos com erros satisfatórios.

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Numerous macroscale models of arteries have been developed, comprised of populations of discrete coupled Endothelial Cells (EC) and Smooth Muscle Cells (SMC) cells, an example of which is the model of Shaikh et al. (2012), which simulates the complex biochemical processes responsible for the observed propagating waves of Ca2+ observed in experiments. In a 'homogenised' model however, the length scale of each cell is assumed infinitely small while the population of cells are assumed infinitely large, so that the microscopic spatial dynamics of individual cells are unaccounted for. We wish to show in our study, our hypothesis that the homogenised modelling approach for a particular system can be used to replicate observations of the discrete modelling approach for the same system. We may do this by deriving a homogenised model based on Goldbeter et al. (1990), the simplest possible physiological system, and comparing its results with those of the discrete Shaikh et al. (2012), which have already been validated with experimental findings. We will then analyse the mathematical dynamics of our homogenised model to gain a better understanding of how its system parameters influence the behaviour of its solutions. All our homogenised models are essentially formulated as partial differential equations (PDE), specifically they are of type reaction diffusion PDEs. Therefore before we begin developing the homogenised Goldbeter et al. (1990), we will first analyse the Brusselator PDE with the goal that it will help us to understand reaction diffusion systems better. The Brusselator is a suitable preliminary study as it shares two common properties with reaction diffusion equations: oscillatory solutions and a diffusion term.

Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience—or prominence in memory—of narrative events. A pair of Indexter events can share up to five indices with one another: protagonist, time, space, causality, and intentionality. The pairwise event salience hypothesis states that when a past event shares one or more of these indices with the most recently narrated event, that past event is more salient, or easier to recall, than an event which shares none of them. In this study we demonstrate that we can predict user choices based on the salience of past events. Specifically, we investigate the hypothesis that when users are given a choice between two events in an interactive narrative, they are more likely to choose the one which makes the previous events in the story more salient according to this theory.

L'objectif de ma thèse est de participer à la construction d'un nouveau robot humanoïde qui peut réaliser des interactions intuitives avec l'humain à travers l'observation et l'imitation. Pour cela, j'ai conduit une série d'études expérimentales chez le jeune adulte pour caractériser les propriétés cinématiques des mouvements du bras réalisés pendant des interactions motrices et sociales, autant d'éléments qui seront les patterns de référence pour le futur robot. En se concentrant sur le comportement non-verbal, nous avons testé comment les contraintes externes et internes (difficulté, prédictibilité, temporalité) façonne la cinématique des mouvements du bras et de la main dans une simple action séquentielle de prise et de pose d'un objet (étude 1 et 2). Les résultats révèlent des modulations précoces dans la cinématique de la phase d'atteinte et de saisie, en fonction de la taille et de la stabilité du réceptacle terminal sur lequel l'objet devait être placé. Ces modulations observées dans le premier élément de la séquence sont en contradiction avec les modèles d'optimisation de trajectoire utilisés en robotique pour les séquences d'action. Ils suggèrent un couplage fort entre les paramètres moteurs dans une stratégie de planification encapsulée qui rétro-propage les contraintes contextuelles sur les éléments précoces de la séquence. Pour confirmer ces résultats, une seconde série d'étude a été conduite en utilisant des tâches cinématiques et vidéos pour montrer que les intentions motrices humaines pouvaient être lues à travers la détection de ces modulations cinématiques précoces. En utilisant un système de classification artificiel, nous avons testé si les indices de bas niveau pouvaient permettre une catégorisation des essais. Les résultats montrent qu'en absence de capacité cognitive particulière, le réseau de neurone pouvait catégoriser les intentions significativement au-dessus du niveau de la chance en observant les 500 premières millisecondes de l'action (étude 3). La troisième partie de mon travail de thèse s'est tournée vers les mesures en eye-tracking. Nous avons révélé ici que la stratégie proactive de fixations oculaires utilisée pendant l'observation de l'action était similaire à celle utilisée pendant son exécution (étude 4). De plus, les catégorisations correctes d'intentions motrices étaient caractérisées par des saccades plus précises et des fixations plus longues sur l'objet. Les mouvements oculaires sont connus pour jouer un rôle important dans les interactions sociales. Ainsi, dans une dernière expérience (étude 5), nous avons mis en place un jeu compétitif en face à face révélant des effets spécifiques du contexte social qui modifie la cinématique des mouvements d'atteinte selon le type de situations interactives. Dans le manuscrit de thèse je propose une discussion qui replace les résultats dans les modèles neuronaux et cognitifs de l'intégration sensori-mmotrice. Lorsque c'est le cas, des directions futures sont suggérées à la fois pour les modèles cognitifs de contrôle moteur et pour le développement e systèmes artificiels neuro-inspirés intégrant des capacités d'interaction sociale intuitive. / The aim of my PhD thesis was to participate in the construction of a new humanoid robot that can sustain intuitive interactions with humans through observation and imitation. As such, I conducted a series of experimental studies in young adults to better characterize the kinematic properties of those arm movements performed during motor and social interactions, elements that are the reference patterns for the to-come robot. Focusing on non-verbal behavior, we tested how external and internal constraints (difficulty, predictability, timing) shaped the kinematics of both arm and hand movements in a very simple pick and place sequential action (study 1 and 2). The results revealed early modulations in kinematics in the reach-to-grasp phase depending of the size and the stability of the target pad on which the object had to be placed. These modulations observed within the first element of the sequence were in contradiction with the current optimized trajectory models used in robotics for action sequences. They suggest in fact a strong coupling of the motor parameters within an encapsulated planning strategy that back-propagates the contextual constraints on to the early elements of the motor sequence. To confirm these findings, a second serie of studies were conducted using kinematic and video based tasks to show that human motor intentions can be read through the detection of these early kinematic modulations (study 3). Using basic artificial classification, we tested whether low-revel motor indices could afford trial categorization without the need for higher-level process such as motor imagery. results indicated that indeed without cognitive abilities the neural network could categorize the intention of an observed action within the first 500ms, significantly above chance level (study 4). The third place of my PhD work turned to eye tracking. Here, we revealed that the proactive strategy of eye-fixations used during action observation were similar to those made during executed actions. Additionally, good categorization of motor intention was characterized by more accurate saccades and longer object fixations. Eye movements are known to play an important role in social intercations. Hence, in a final experiment (study 5), we setup a face-to-face competitive game to reveal the specific effects thet the social context may play on the kinematic properties of reaching during different types of interactive situations. In the PhD mansucript, I propose a general discussion that sets these results within the current cognitive and neuronal models of sensori-motor integration. When appropriate, future directions are suggested both for cognitive models of motor control and for the development of neuro-inspired articicial systems constitued with intuitive social interaction skills.

Os aspectos quantitativos regem as práticas de engenharia visando o gerenciamento de reservatórios. Entretanto, a preocupação em relação aos aspectos qualitativos da água tem aumentado, já que um número cada vez maior de reservatórios estão sendo utilizados para vários tipos de usos. No processo de gerenciamento de reservatórios é necessário que se leve em consideração todos os usos que serão beneficiados pelo sistema em questão. Nesse sentido, o objetivo do trabalho foi o emprego de técnicas computacionais para análise quanti-qualitativa dos usos múltiplos do reservatório de Barra Bonita - SP, realizando simulações computacionais através do modelo MIKE BASIN; propondo e testando um modelo de otimização com programação não-linear baseado no método das restrições e incorporando o uso de geotecnologias para análise espacial (distribuição horizontal) e temporal (sazonalidade) da qualidade da água do reservatório. Selecionou-se o reservatório de Barra Bonita para análise, devido aos usos múltiplos da água (geração de energia, navegação, recreação, turismo e pesca) e a presença de uma eclusa para transposição do desnível entre a jusante da barragem e o reservatório de acumulação da hidrelétrica, o que torna o reservatório uma área de estudo diferenciada. Os resultados das simulações realizadas no modelo MIKE BASIN para avaliar os usos múltiplos do reservatório, demonstraram que o melhor cenário foi o que estabeleceu prioridades iguais para a geração de energia e a navegação. A maximização da geração de energia hidroelétrica, através do modelo de otimização, não prejudicou os outros usos do reservatório (principalmente a navegação) e, mesmo no período seco, a energia média gerada pelo modelo registrou valores acima da energia média real gerada pela Usina Hidrelétrica de Barra Bonita-SP (período de 2001 a 2005). O emprego de geotecnologias (software Surfer) proporcionou boas condições para análise espaço-temporal da qualidade da água, quando aliado ao conhecimento sobre as características e condições do ambiente de estudo. Os dados obtidos em campo, demonstraram que algumas variáveis analisadas, como a condutividade elétrica e a turbidez aumentam significativamente do período seco para o chuvoso, pois estão diretamente relacionados com o aporte de material orgânico e inorgânico. O potencial hidrogeniônico (pH) sofre uma variação muito pequena do período seco para o chuvoso, mas seus valores variam espacialmente, sendo encontrados valores maiores no compartimento da barragem para o período seco, e no final do braço do rio Piracicaba para o período chuvoso. Quanto ao oxigênio dissolvido, este aumenta bastante do período chuvoso para o seco, mas em ambos os períodos as maiores concentrações são encontradas no final do braço do rio Piracicaba - SP. Ressalta-se, que apenas o oxigênio dissolvido (estação seca) não se enquadrou no padrão da Resolução CONAMA nº 357/2005, para águas de classe II. / The quantitative aspects rule the engineering practices aimed at reservoirs management. However, the concern about the qualitative aspects of water has increased, since a growing number of reservoirs are being used for many kinds of applications. In the process of reservoir management it is necessary to take into consideration all the uses that will benefit from the system itself. Hence, the objective of this study was the use of computational techniques for quantitative and qualitative analysis of the multiple applications of the reservoir of Barra Bonita - SP, performing computer simulations using the model MIKE BASIN, proposing and testing an optimization model with non-linear programming based on the constraint method and incorporating the use of geotechnologies for spatial (horizontal distribution) and time (seasonal distribution) analysis of the reservoir water quality. It was selected the reservoir of Barra Bonita for analysis because of the multiple applications of the water (power generation, navigation, recreation, tourism and fishing) and the presence of a lock for transposition of the gap between the dam downstream and the power plant accumulation reservoir, which makes the reservoir a different area of study. The results of the simulations performed in MIKE BASIN model to evaluate the multiple applications of the reservoir showed that the best scenario was the one in which the priorities were the same for power generation and navigation. The maximization of the hydropower generation through the optimization model, did not impair other uses of the reservoir (mainly navigation) and even in the dry season, the average power generated by the model registered values above the average real power generated by the Hydroelectric Power Plant of Barra Bonita-SP (from 2001 to 2005). The use of geotechnologies (Surfer software) provided good conditions for space-time analysis of water quality when coupled with the knowledge about the characteristics and conditions of the studied environment. The data obtained showed that some variables, such as electrical conductivity and turbidity significantly increase from the dry season to the rainy season, since they are directly related to the supply of organic and inorganic materials. The hydrogen potential (pH) undergoes a very small variation from the dry season to the rainy season, but its values vary spatially, with higher values found in the compartment of the dam during the dry season, and at the end of the arm of the Piracicaba river during the wet season. The dissolved oxygen greatly increases from the rainy season to the dry one, but in both periods the highest concentrations are found at the end of the arm of the river Piracicaba - SP. It is emphasized that only the dissolved oxygen (dry season) did not fit the pattern of CONAMA Resolution nº 357/2005, to class II waters.

Doctor of Philosophy / The motivation for the research presented in this thesis stems from the recent availability of high frequency limit order book data, relative scarcity of studies employing such data, economic significance of transaction costs management, and a perceived potential of data mining for uncovering patterns and relationships not identified by the traditional top-down modelling approach. We analyse and build computational models for order submissions on the Australian Stock Exchange, an order-driven market with a public electronic limit order book. The focus of the thesis is on the trade implementation problem faced by a trader who wants to transact a buy or sell order of a certain size. We use two approaches to build our models, top-down and bottom-up. The traditional, top-down approach is applied to develop an optimal order submission plan for an order which is too large to be traded immediately without a prohibitive price impact. We present an optimisation framework and some solutions for non-stationary and non-linear price impact and price impact risk. We find that our proposed transaction costs model produces fairly good forecasts of the variance of the execution shortfall. The second, bottom-up, or data mining, approach is employed for trade sign inference, where trade sign is defined as the side which initiates both a trade and the market order that triggered the trade. We are interested in an endogenous component of the order flow, as evidenced by the predictable relationship between trade sign and the variables used to infer it. We want to discover the rules which govern the trade sign, and establish a connection between them and two empirically observed regularities in market order submissions, competition for order execution and transaction cost minimisation. To achieve the above aims we first use exploratory analysis of trade and limit order book data. In particular, we conduct unsupervised clustering with the self-organising map technique. The visualisation of the transformed data reveals that buyer-initiated and seller-initiated trades form two distinct clusters. We then propose a local non-parametric trade sign inference model based on the k-nearest-neighbour classifier. The best k-nearest-neighbour classifier constructed by us requires only three predictor variables and achieves an average out-of-sample accuracy of 71.40% (SD=4.01%)1, across all of the tested stocks. The best set of predictor variables found for the non-parametric model is subsequently used to develop a piecewise linear trade sign model. That model proves superior to the k-nearest-neighbour classifier, and achieves an average out-of-sample classification accuracy of 74.38% (SD=4.25%). The result is statistically significant, after adjusting for multiple comparisons. The overall classification performance of the piecewise linear model indicates a strong dependence between trade sign and the three predictor variables, and provides evidence for the endogenous component in the order flow. Moreover, the rules for trade sign classification derived from the structure of the piecewise linear model reflect the two regularities observed in market order submissions, competition for order execution and transaction cost minimisation, and offer new insights into the relationship between them. The obtained results confirm the applicability and relevance of data mining for the analysis and modelling of stock market order submissions.

Insensitivity to chemotherapy is an ongoing issue in cancer treatment, one that appears to be highly dependent on patient-specific variations. It has been shown clinically that while a subset of patients will successfully respond to a particular chemotherapeutic regimen, there exists another subset of patients who when exposed to the same course of therapy will remain resistant to treatment or exhibit signs of relapse after treatment has been administered. This discrepancy raises interesting questions regarding the role that patient-specific variations play in controlling the efficacy of chemotherapy treatment regimens. Doxorubicin (Dox) is a common chemotherapeutic agent used in the treatment of a variety of solid tumors and leukemias and resistance to Dox treatment is a major issue in cancer chemotherapy, oftentimes leading to patient relapse. To gain a deeper understanding of the processes that influence Dox resistance, we must first understand the mechanisms that underlie and contribute to Dox's toxicity. To this end, the metabolic reactions that activate Dox have been implicated as major determinants of Dox cytoxicity and as possible factors that control Dox resistance in cancer cells. There are several lines of evidence that redox-dependent metabolism plays a large role in Dox toxicity. The Dox bioactivation network is comprised of a system of reduction/oxidation (redox) reactions that lead to the formation of toxic Dox metabolites and reactive oxygen species (ROS). Moreover, multi-drug resistant acute lymphoblastic leukemia cells derived from relapsed patients have elevated levels of the antioxidant glutathione and show insensitivity to Dox treatment. The redox dependence of Dox bioactivation, the understanding that Dox treatment generates ROS, and the evidence that Dox resistant cells exhibit increased antioxidant capacity, suggest the possibility that redox pathways modulate the efficacy of Dox treatment in cancer cells. The overall objectives of the proposed dissertation, therefore, were to investigate how the redox properties of the Dox bioactivation network influence Dox toxicity in acute lymphoblastic leukemia cells, and to provide evidence that cell-specific variations in the intracellular levels of these redox components influences the degree to which Dox treatment will induce cancer cell death. The significant findings of this study are that the redox reactions involved in Dox metabolism are dual-natured, containing a toxicity-generating module characterized by nicotinamide adenine dinucleotide phosphate (NADPH)-dependent Dox reductive conversion, as well as an ROS signal-generating module characterized by NADPH- and oxygen-dependent Dox redox cycling. The balance between the coupled redox reactions that comprise the toxicity- and ROS signal-generating modules of Dox bioactivation determines the sensitivity-phenotype of leukemia cells and phenotypic changes in the Dox-sensitivity of leukemia cells can be induced by the successful modulation of the Dox bioactivation network through the pharmacological inhibition of NADPH in a concentration- and cell type-dependent manner. This study highlights the importance of the intracellular redox network in controlling chemotherapy-induced ROS. The unequal distribution in antioxidant burden across the various intracellular antioxidant enzymes suggests a significant role for NADPH supply, as controlled by the enzyme glucose-6-phosphate dehydrogenase (G6PD), to the intracellular ROS buffering capacity of cells during instances of oxidative stress. Changes in G6PD activity were shown to promote protein-S-glutathionylation during oxidative stress conditions, thereby implicating G6PD in the modulation of redox-sensitive signal transduction pathways. The intracellular glutathione redox balance, a measure of the intracellular redox environment, can effectively regulate Dox-induced NF-κB signal transduction in leukemia cells. The systematic modulation of intracellular glutathione redox balance in leukemia cells by N-acetylcysteine (NAC) revealed an important role for protein S-glutathionylation mechanisms in the control of NF-κB signal transduction induced by Dox treatment. These findings identify the glutathione redox network as a potential therapeutic target for the systematic modulation of Dox sensitivity in cancer cells and elucidate the complex role that antioxidants such as NAC can play in modulating the effectiveness of Dox chemotherapy treatment regimens. Lastly, this study highlights the need for and the capacity of computational models to accurately describe the complex redox-reactions that contribute to Dox metabolism in leukemia cells. This study is groundbreaking in its use of computational modeling to analyze reversible electron transfer events between proteins using mass-action kinetics. The models developed in this study can accurately explain cytosolic doxorubicin bioactivation, intracellular hydrogen peroxide clearance, and kinase-specific S-glutathionylation, thereby showing that the use of comprehensive and/or relatively simple computational models can provide semi-quantitative predictions about the behavior of redox systems in mammalian cells as they relate to Dox-induced toxicity and Dox-induced cell signaling.

Computer agents are required to make appropriate decisions quickly and efficiently. As the environments in which they act become increasingly complex, efficient decision-making becomes significantly more challenging. This thesis examines the positive ways in which human emotions influence people’s ability to make good decisions in complex, uncertain contexts, and develops computational analogues of these beneficial functions, demonstrating their usefulness in agent decision-making and communication. For decision-making by a single agent in large-scale environments with stochasticity and high uncertainty, the thesis presents GRUE (Goal Re-prioritization Using Emotion), a decision-making technique that deploys emotion-inspired computational operators to dynamically re-prioritize the agent’s goals. In two complex domains, GRUE is shown to result in improved agent performance over many existing techniques. Agents working in groups benefit from communicating and sharing information that would otherwise be unobservable. The thesis defines an affective signaling mechanism, inspired by the beneficial communicative functions of human emotion, that increases coordination. In two studies, agents using the mechanism are shown to make faster and more accurate inferences than agents that do not signal, resulting in improved performance. Moreover, affective signals confer performance increases equivalent to those achieved by broadcasting agents’ entire private state information. Emotions are also useful signals in agents’ interactions with people, influencing people’s perceptions of them. A computer-human negotiation study is presented, in which virtual agents expressed emotion. Agents whose emotion expressions matched their negotiation strategy were perceived as more trustworthy, and they were more likely to be selected for future interactions. In addition, to address similar limitations in strategic environments, this thesis uses the theory of reasoning patters in complex game-theoretic settings. An algorithm is presented that speeds up equilibrium computation in certain classes of games. For Bayesian games, with and without a common prior, the thesis also discusses a novel graphical formalism that allows agents’ possibly inconsistent beliefs to be succinctly represented, and for reasoning patterns to be defined in such games. Finally, the thesis presents a technique for generating advice from a game’s reasoning patterns for human decision-makers, and demonstrates empirically that such advice helps people make better decisions in a complex game. / Engineering and Applied Sciences

The motor nervous system is one of the main systems of the body and is our principle means ofbehavior. Some of the most debilitating and wide spread disorders are motor systempathologies. In particular the basal ganglia are complex networks of the brain that control someaspects of movement in all vertebrates. Although these networks have been extensively studied,lack of proper methods to study them on a system level has hindered the process ofunderstanding what they do and how they do it. In order to facilitate this process I have usedcomputational models as an approach that can faithfully take into account many aspects of ahigh dimensional multi faceted system.In order to minimize the complexity of the system, I first took agnathan fish and amphibians asmodeling animals. These animals have rather simple neuronal networks and have been wellstudied so that developing their biologically plausible models is more feasible. I developedmodels of sensory motor transformation centers that are capable of generating basic behaviorsof approach, avoidance and escape. The networks in these models used a similar layeredstructure having a sensory map in one layer and a motor map on other layers. The visualinformation was received as place coded information, but was converted into population codedand ultimately into rate coded signals usable for muscle contractions.In parallel to developing models of visuomotor centers, I developed a novel model of the basalganglia. The model suggests that a subsystem of the basal ganglia is in charge of resolvingconflicts between motor programs suggested by different motor centers in the nervous system.This subsystem that is composed of the subthalamic nucleus and pallidum is called thearbitration system. Another subsystem of the basal ganglia called the extension system which iscomposed of the striatum and pallidum can bias decisions made by an animal towards theactions leading to lower cost and higher outcome by learning to associate proper actions todifferent states. Such states are generally complex states and the novel hypothesis I developedsuggests that the extension system is capable of learning such complex states and linking themto appropriate actions. In this framework, striatal neurons play the role of conjunction (BooleanAND) neurons while pallidal neurons can be envisioned as disjunction (Boolean OR) neurons.In the next set of experiments I tried to take the idea of basal ganglia subsystems to a new levelby dividing the rodent arbitration system into two functional subunits. A rostral group of ratpallidal neurons form dense local inhibition among themselves and even send inhibitoryprojections to the caudal segment. The caudal segment does not project back to its rostralcounterpart, but both segments send inhibitory projections to the output nuclei of the rat basalganglia i.e. the entopeduncular nucleus and substantia nigra. The rostral subsystems is capableof precisely detecting one (or several) components of a rudimentary action and suppress othercomponents. The components that are reinforced are those which lead to rewarding stateswhereas those that are suppressed are those which do not. The hypothesis explains neuronalmechanisms involved in this process and suggests that this subsystem is a means of generatingsimple but precise movements (such as using a single digit) from innate crude actions that theanimal can perform even at birth (such as general movement of the whole limb). In this way, therostral subsystem may play important role in exploration based learning.In an attempt to more precisely describe the relation between the arbitration and extensionsystems, we investigated the effect of dynamic synapses between subthalamic, pallidal andstriatal neurons and output neurons of the basal ganglia. The results imply that output neuronsare sensitive to striatal bursts and pallidal irregular firing. They also suggest that few striatalneurons are enough to fully suppress output neurons. Finally the results show that the globuspallidus exerts its effect on output neurons by direct inhibition rather than indirect influence viathe subthalamic nucleus. / <p>QC 20131209</p>