La mobilité devienne un partie intégrante de l’Internet des Object d’aujourd’hui, comme beaucoup d’applications (monitorage des animaux sauvage, suivi des cible dans le champs de bataille) sont impossible de mettre en œuvre juste avec des nœuds statiques. L’objective de cette thèse est de définir une nouvelle architecture de communication articule autour de la mobilité dans les réseaux avec pertes et à bas puissance (Low Power and Lossy Networks - LLNs) (réseaux des capteurs sans fils). Tout d’abord, nous avons analysé théoriquement l’auto configuration des adresses IPv6, fait avec toutes les optimisations disponibles dans Neighbor Discovery Optimization for IPv6 over 6LoWPAN. Cette étape est cruciale pour des protocoles qui donnent de support pour la mobilité dans des réseaux IP, comme MIPv6. Les résultats obtenues – taille des paquets trop grande et consumations énergétique importante pour les routeurs qui tournent Neighbor Discovery – n’ont amener a utiliser le IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). RPL est développe d’el debout pour les LLN. Notre deuxième contribution sont améliorer les opérations du RPL pour mieux supporter les nœuds mobiles. Enfin, nous avons développe une mécanisme inter-couche – Mobility Triggered-RPL – qui profite des actions dans le protocole avec préambule X-Machiavel à la couche accès au medium dans le protocole RPL à la couche routage. / Mobility is becoming an integrating part of todays Internet of Things, as many applications such as wildlife monitoring or target tracking in the battlefield cannot be done only with the help of static nodes. The goal of this thesis is to provide new communication architecture articulated around providing mobility support in Low Power and Lossy Networks (LLNs). First we analyzed from a theoretical point of view the IPv6 address auto-configuration with all optimizations made in Neighbor Discovery Optimization for IPv6 over 6LoWPAN. This step is of crucial importance for protocols that offer mobility support in IP networks, such as MIPv6. Our findings, increased message size that leads to fragmentation and high energy consumption for routers that are involved in Neighbor Discovery message exchange, have lead us to use the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) in order to provide mobility support. RPL is build from ground up with respect to LLN requirements. Our second contribution enhanced RPL operations to support mobility management. Finally, we proposed a cross-layer protocol – Mobility Triggered-RPL – that leverages actions from the X-Machiavel preamble sampling MAC protocol into RPL.

No description available.

Superbursts (SBs) are large, seemingly spontaneous activity fluctuations often encountered in high density neural networks in vitro. Little effort has been put forth to define and analyze SBs which are paroxysmal bursting discharges. Through qualitative and quantitative means, I have described specific occurrences of superbursting activity. A complex of paroxysmal bursting has been termed a "superburst episode," and each individual SB is a "superburst event" which is comprises a fine burst structure. Quantitative calculations (employing overall spike summations and coefficient of variation (CV) calculations), reveal three distinct phases. Phase 1 is a "build up" phase of increasingly strong, coordinated bursting with an average of a 17.6% ± 13.7 increase in activity from reference. Phase 2, the "paroxysmal" phase, is comprised of massive coordinated bursting with high frequency spike content. Individual spike activity increases by 52.9% ± 14.6. Phase 3 is a "recovery phase" of lower coordination and an average of a 50.1% ± 35.6 decrease in spike production from reference. SBs can be induced and terminated by physical manipulation of the medium. Using a peristaltic pump with a flow rate of 0.4ml/min, superbursting activity ceases approximately 28.3 min after the introduction of flow. Alternatively, upon cessation of medium flow superbursting activity reemerges after approximately 8.5 min. Additionally, this study explored other methods capable of inducing superbursting activity using osmotic shocks. The induction and termination of SBs demonstrates that the cell culture environment plays a major role in generating this phenomenon. The observations that high density multi-layer neuronal networks in culture are more likely to enter paroxysmal bursting also supports the hypothesis that enrichment and depletion layers of metabolites and ionic species are involved in such unusual activity. The dynamic similarity of the SB phenomenon with epileptiform discharges make further quantification on the spike pattern level pertinent and important.

Le néocortex possède un état activé dans lequel l'activité corticalemanifeste un comportement complexe. Au niveau cellulaire, l'activitéest caractérisée par de fortes fluctuations sous-liminaires dupotential membranaire et une décharge irrégulière à bassefréquence. Au niveau du réseau, l'activité est marquée par un faibleniveau de synchronie et une dynamique chaotique. Néanmoins, c'est dansce régime que l'information est traitée de manière fiable par lesréseaux neuronaux. Ce régime est donc crucial pour le traitement del'information par le cortex. Dans cette thèse, nous contribuons à sacompréhension en examinant comment les propriétés biophysiques auniveau cellulaire combinées avec les propriétés d'architecture desréseaux façonnent cette dynamique asynchrone.Cette thèse repose sur les modèles de dynamique de réseaux appelésmodèles de champ moyen, un formalisme théorique qui décrit ladynamique de population grâce à une approche auto-consistante. Aucoeur de ce formalisme se trouve la fonction de transfertneuronale : la fonction entrée-sortie d'un neurone. La première partiede cette thèse s'attache à dériver des fonctions de transfertbiologiquement réalistes en incorporant des caractérisationsexpérimentales.Dans un premier temps, nous avons examiné in vitro comment lesneurones néocorticaux pyramidaux de la couche V du cortex visuelrépondent à des fluctuations du potentiel membranaire. Nous avonsobservé que les neurones individuels ne diffèrent pas seulement entermes d'excitabilité, mais qu'ils diffèrent aussi par leurssensibilités aux paramètres des fluctuations. Dans un deuxième temps,nous avons étudié de manière théorique comment l'intégrationdendritique dans des structures arborescentes façonne les fluctuationsau soma. Nous avons observé que, en fonction des propriétés del'activité présynaptique, différentes comodulations des paramètres desfluctuations pouvaient être obtenues. En combinant cette observationavec nos mesures expérimentales, nous avons observé que cela induisaitdes couplages différents entre activité synaptique et déchargeneuronale pour chaque neurone. Nous proposons donc que, puisque cemécanisme offre un moyen d'activer spécifiquement certains neurones enfonction des propriétés de l'entrée, l'hétérogénéité biophysiquepourrait contribuer à l'encodage de propriétés des stimuli dans lestraitements de l'information sensorielle.La deuxième partie de cette thèse examine comment les propriétésd'architecture des réseaux neuronaux se combinent avec les propriétésbiophysiques et affectent les réponses sensorielles via des effets dedynamiques de populations.Nous avons tout d'abord examiné de manière théorique comment un hautniveau d'activité spontanée impactait les réponses post-synaptiquesdans le cortex. Nous avons observé que la compétition entre lerecrutement dans le réseau cortical activé et les effets deconductances associés prédisaient une relation non-triviale entrel'intensité des stimuli et l'amplitude des réponses. Cette prédictionfut observée dans des enregistrements de réponses post-synaptiquesdans le cortex auditif du rat in vivo en réponse à des stimulicorticaux, thalamiques et auditifs.Pour finir, en tirant avantage des approches de champ moyen, nousavons construit un modèle grande échelle du réseau des couches II-IIIincluant le réseau des fibres horizontales. Nous avons examiné lespropriétés intégratives spatio-temporelles du modèle et nous les avonscomparées avec des mesures par imagerie optique de l'activitécérébrale chez le singe éveillé. En particulier, nous avonsreconstruit une expérience typique du traitement sensoriel: lemouvement apparent. Le modèle prédit un fort signal suppressif dont leprofil spatio-temporel correspond quantitativement à celui observé invivo... / The neocortex of awake animals displays an activated state in whichcortical activity manifests highly complex, seemingly noisybehavior. At the level of single neurons the activity is characterizedby strong subthreshold fluctuations and irregular firing at lowrate. At the network level, the activity is weakly synchronized andexhibits a chaotic dynamics. Yet, it is within this regime thatinformation is processed reliably through neural networks. This regimeis thus crucial to neural computation. In this thesis, we contributeto its understanding by investigating how the biophysical propertiesat the cellular level combined with the properties of the networkarchitecture shapes this asynchronous dynamics.This thesis builds up on the so-called mean-field models of networkdynamics, a theoretical formalism that describes population dynamicsvia a self-consistency approach. At the core of this formalism lie theneuronal transfer function: the input-output description of individualneurons. The first part of this thesis focuses on derivingbiologically-realistic neuronal transfer functions. We firstformulate a two step procedure to incorporate biological details (suchas an extended dendritic structure and the effect of various ionicchannels) into this transfer function based on experimentalcharacterizations.First, we investigated in vitro how layer V pyramidal neocorticalneurons respond to membrane potential fluctuations on a cell-by-cellbasis. We found that, not only individual neurons strongly differ interms of their excitability, but also, and unexpectedly, in theirsensitivities to fluctuations. In addition, using theoreticalmodeling, we attempted to reproduce these results. The model predictsthat heterogeneous levels of biophysical properties such as sodiuminactivation, sharpness of sodium activation and spike frequencyadaptation account for the observed diversity of firing rateresponses.Then, we studied theoretically how dendritic integration in branchedstructures shape the membrane potential fluctuations at the soma. Wefound that, depending on the type of presynaptic activity, variouscomodulations of the membrane potential fluctuations could beachieved. We showed that, when combining this observation with theheterogeneous firing responses found experimentally, individual neuronsdifferentially responded to the different types of presynapticactivities. We thus propose that, because this mechanism offers a wayto produce specific activation as a function of the input properties,biophysical heterogeneity might contribute to the encoding of the stimulusproperties during sensory processing in neural networks.The second part of this thesis investigates how circuit properties,such as recurrent connectivity and lateral connectivity, combine withbiophysical properties to impact sensory responses through effectsmediated by population dynamics.We first investigated what was the effect of a high level of ongoingdynamics (the Up-state compared to the Down-state) on the scaling ofpost-synaptic responses. We found that the competition between therecruitment within the active recurrent network (in favor of highresponses in the Up-state) and the increased conductance level due tobackground activity (in favor of reduced responses in the Up-state)predicted a non trivial stimulus-response relationship as a functionof the intensity of the stimulation. This prediction was shown toaccurately capture measurements of post-synaptic membrane potentialresponses in response to cortical, thalamic or auditory stimulation inrat auditory cortex in vivo.Finally, by taking advantage of the mean-field approach, weconstructed a tractable large-scale model of the layer II-III networkincluding the horizontal fiber network. We investigate thespatio-temporal properties of this large-scale model and we compareits predictions with voltage sensitive dye imaging in awake fixatingmonkey...

Le cortex cérébral des mammifères est constitué de larges et complexes réseaux de neurones. La tâche de ces assemblées de cellules est d’encoder et de traiter, le plus précisément possible, l'information sensorielle issue de notre environnement extérieur. De façon surprenante, les enregistrements électrophysiologiques effectués sur des animaux en comportement ont montré que l’activité corticale est excessivement irrégulière. Les motifs temporels d’activité ainsi que les taux de décharge moyens des cellules varient considérablement d’une expérience à l’autre, et ce malgré des conditions expérimentales soigneusement maintenues à l’identique. Une hypothèse communément répandue suggère qu'une partie importante de cette variabilité émerge de la connectivité récurrente des réseaux. Cette hypothèse se fonde sur la modélisation des réseaux fortement couplés. Une étude classique [Sompolinsky et al, 1988] a en effet montré qu'un réseau de cellules aux connections aléatoires exhibe une transition de phase : l’activité passe d'un point fixe ou le réseau est inactif, à un régime chaotique, où les taux de décharge des cellules fluctuent au cours du temps et d’une cellule à l’autre. Ces analyses soulèvent néanmoins de nombreuse questions : de telles fluctuations sont-elles encore visibles dans des réseaux corticaux aux architectures plus réalistes? De quelle façon cette variabilité intrinsèque dépend-elle des paramètres biophysiques des cellules et de leurs constantes de temps ? Dans quelle mesure de tels réseaux chaotiques peuvent-ils sous-tendre des computations ? Dans cette thèse, on étudiera la dynamique et les propriétés computationnelles de modèles de circuits de neurones à l’activité hétérogène et variable. Pour ce faire, les outils mathématiques proviendront en grande partie des systèmes dynamiques et des matrices aléatoires. Ces approches seront couplées aux méthodes statistiques des champs moyens développées pour la physique des systèmes désordonnées. Dans la première partie de cette thèse, on étudiera le rôle de nouvelles contraintes biophysiques dans l'apparition d’une activité irrégulière dans des réseaux de neurones aux connections aléatoires. Dans la deuxième et la troisième partie, on analysera les caractéristiques de cette variabilité intrinsèque dans des réseaux partiellement structurées supportant des calculs simples comme la prise de décision ou la création de motifs temporels. Enfin, inspirés des récents progrès dans le domaine de l’apprentissage statistique, nous analyserons l’interaction entre une architecture aléatoire et une structure de basse dimension dans la dynamique des réseaux non-linéaires. Comme nous le verrons, les modèles ainsi obtenus reproduisent naturellement un phénomène communément observé dans des enregistrements électrophysiologiques : une dynamique de population de basse dimension combinée avec représentations neuronales irrégulières, à haute dimension, et mixtes. / The mammalian cortex consists of large and intricate networks of spiking neurons. The task of these complex recurrent assemblies is to encode and process with high precision the sensory information which flows in from the external environment. Perhaps surprisingly, electrophysiological recordings from behaving animals have pointed out a high degree of irregularity in cortical activity. The patterns of spikes and the average firing rates change dramatically when recorded in different trials, even if the experimental conditions and the encoded sensory stimuli are carefully kept fixed. 
One current hypothesis suggests that a substantial fraction of that variability emerges intrinsically because of the recurrent circuitry, as it has been observed in network models of strongly interconnected units. In particular, a classical study [Sompolinsky et al, 1988] has shown that networks of randomly coupled rate units can exhibit a transition from a fixed point, where the network is silent, to chaotic activity, where firing rates fluctuate in time and across units. Such analysis left a large number of questions unsolved: can fluctuating activity be observed in realistic cortical architectures? How does variability depend on the biophysical parameters and time scales? How can reliable information transmission and manipulation be implemented with such a noisy code? 
In this thesis, we study the spontaneous dynamics and the computational properties of realistic models of large neural circuits which intrinsically produce highly variable and heterogeneous activity. The mathematical tools of our analysis are inherited from dynamical systems and random matrix theory, and they are combined with the mean field statistical approaches developed for the study of physical disordered systems. 
In the first part of the dissertation, we study how strong rate irregularities can emerge in random networks of rate units which obey some among the biophysical constraints that real cortical neurons are subject to. In the second and third part of the dissertation, we investigate how variability is characterized in partially structured models which can support simple computations like pattern generation and decision making. To this aim, inspired by recent advances in networks training techniques, we address how random connectivity and low-dimensional structure interact in the non-linear network dynamics. The network models that we derive naturally capture the ubiquitous experimental observations that the population dynamics is low-dimensional, while neural representations are irregular, high-dimensional and mixed.

A ballistic pendulum impulse generator was used to impact networks in primary culture growing on microelectrode arrays. This approach has the advantage of imparting pure tangential acceleration insults (50 to 300 g) with simultaneous morphological and electrophysiological multichannel monitoring for days before and after the impact. Action potential (AP) production, network activity patterns, and cell electrode coupling of individual units using AP waveshape templates were quantified. Network adhesion was maintained after tangential impacts up to 300g with minimal loss of pre-selected active units. Time lapse phase contrast microscopy revealed stable nuclei pre-impact, but post impact nuclear rotation in 95% of observations (n= 30). All recording experiments (n=31) showed a repeatable two-phase spike production response profile: recovery to near reference in 1-2 hrs, followed by a slow activity decay to a stable, level plateau approximately 30-40% below reference. Phase 1 consisted of a complex two-step recovery: rapid activity increase to an average 23.6% (range: 11-34%) below reference, forming a level plateau lasting from 5 to 20 min, followed by a climb to within 20% of reference where a second plateau was established for 1 to 2 hrs. Cross correlation profiles showed changes in firing hierarchy after impact, and in spontaneous network oscillatory activity. Native oscillations were found in the Delta band (2 to 3 Hz), and decreased by approximately 20% after impact. Under network disinhibition with bicuculline, oscillations were slower (0.8-1Hz) and decreased 40% after impact. These data link network performance deficits with microscopically observable subcellular changes.

La problématique de ce doctorat est : comment la structure des réseaux constitue une nouvelle matrice pour la production d’oeuvres artistiques. Pour répondre à cette question, nous commencerons en étudiant l’évolution de la notion de « réseau » de l’antiquité jusqu’à aujourd’hui ; les théories des réseaux concernant leur structure et/ou leur dynamique. Ensuite nous présenterons les applications –de la notion ou des théories de réseaux– tant dans les sciences que dans l’art. Nous listerons et nous analyserons huit types de réseaux et puis nous mentionnerons des oeuvres artistiques qui ont été inspirées par ces types de réseaux et/ou qui utilisent certains (types de) réseaux comme matrice pour leur création. Nous proposerons le projet Lignes Imaginaires, un modèle 3D qui se fonde sur la conception d’un métro de lignes imaginaires, voire de lignes dynamiques et/ou paradoxales qui sont en mouvement, apparaissent/disparaissent, créent de l’infrastructure supplémentaire. L’analyse du métro Lignes Imaginaires dévoile l'importance de la géographie et de la spatialité des réseaux, tandis que leur représentation graphique topologique reste insuffisante pour la représentation précise et pour la compréhension de leur structure (paradoxale). En outre, l’innovation du métro Lignes Imaginaires est que son infrastructure est dynamique et auto-organisée, contrairement aux métros traditionnels où les lignes et leurs itinéraires sont fixes. L’objectif du projet artistique Lignes Imaginaires est de visualiser un concept en créant un métro hors du commun qui pourrait aussi proposer des formes alternatives des réseaux de transports dans le contexte urbain. / This thesis examines and shows ways in which the structure of networks can provide a new matrix for the production of artworks. In order to answer this question we start by studying: the evolution of the term ‘network’ from the ancient times up to nowadays; the theories that refer to network structure or network dynamics. Then we present the applications of these theories into both art and science. We list and analyze eight different types of networks and then we feature artworks which have been inspired by these network types or have used the network structure of a certain type as a matrix for art making. We propose the Imaginary Lines project, a three-dimensional network model which is based on the concept of a metro composed of imaginary lines. More precisely Imaginary Lines metro network encompasses seven paradoxical lines which move, (dis)appear and produce supplementary infrastructure. The Imaginary Lines metro unveils the importance of geography and spatiality, in contrast with topological network graphic representations, which remain insufficient, in terms of utmost accuracy in representation and comprehension of network structure. Additionally, the Imaginary Lines network innovation lays in its infrastructure dynamics as well as in its self-organisation. The objective of the Imaginary Lines artistic project is to visualise a concept by creating an unusual metro, which goes beyond traditional fixed-route transport networks and can support alternative forms of urban transport development.

La tesi ha l’obiettivo di analizzare il cambiamento organizzativo in una prospettiva di social network analysis, sfruttando dati longitudinali raccolti a seguito della modifica della struttura organizzativa in un Policlinico Universitario italiano. Il manoscritto è organizzativo in tre paper. Il primo paper si focalizza sul tema del rapporto tra network formali e network informali, analizzando come la modifica del primo comporti una corrispondente variazione nel secondo. Il paper dimostra come, in assenza di strutture organizzative ben formalizzate, gli individui tendono ad allacciare nuovi legami con colleghi che appartengono alla stessa specializzazione. Il secondo paper, invece, attingendo prettamente alla letteratura di comportamento organizzativo, analizza il tema della dinamicità del network, fornendo evidenze in relazione alla stabilità del network stesso a seguito del cambiamento. Particolare attenzione, è inoltre, dedicata alle dinamiche intra – team e al ruolo di quest’ultime nell’accettazione o meno del cambiamento. Infine, il terzo paper sviluppa il tema della network density e di come quest’ultima possa essere correlato al cambiamento organizzativo, in termini di reazione al cambiamento. Inoltre, si dimostra come la formalizzazione abbia un impatto positivo sulla densità del network, specie in contesti organizzativi caratterizzati da una bassa gerarchia e coordinamento orizzontale. / This thesis aims to analyze organizational change in a social network analysis perspective, exploiting longitudinal data collected after a modification of the organizational structure in an Italian Teaching Hospital The manuscript is organized into three papers. The first paper focuses on the theme of the relationship between formal networks and informal networks, analyzing how the modification of the first involves a corresponding variation in the second. The paper demonstrates how, in the absence of formalized organizational structures, individuals tend to establish new ties with colleagues who belong to the same specialization. The second paper, drawing purely from the organizational behavior literature, analyzes the issue of the network dynamics , providing evidence and antecedents for network stability in response to organizational change. Particular attention is also given to the intra - team dynamics and the impact of individual perception of collective properties in driving employees in accepting or not the organizational change. Finally, the third paper develops the theme of network density and how the latter can be related to organizational change, in terms of reaction to change. Furthermore, it is shown how formalization has a positive impact on network density, especially in organizational contexts characterized by a low hierarchy and horizontal coordination.

Die Aktivität des Hippocampus im Tiefschlaf ist geprägt durch sharp wave-ripple Komplexe (SPW-R): kurze (50–100 ms) Phasen mit erhöhter neuronaler Aktivität, moduliert durch eine schnelle “Ripple”-Oszillation (140–220 Hz). SPW-R werden mit Gedächtniskonsolidierung in Verbindung gebracht, aber ihr Ursprung ist unklar. Sowohl exzitatorische als auch inhibitorische Neuronpopulationen könnten die Oszillation generieren. Diese Arbeit analysiert Ripple-Oszillationen in inhibitorischen Netzwerkmodellen auf mikro-, meso- und makroskopischer Ebene und zeigt auf, wie die Ripple-Dynamik von exzitatorischem Input, inhibitorischer Kopplungsstärke und dem Rauschmodell abhängt. Zuerst wird ein stark getriebenes Interneuron-Netzwerk mit starker, verzögerter Kopplung analysiert. Es wird eine Theorie entwickelt, die die Drift-bedingte Feuerdynamik im Mean-field Grenzfall beschreibt. Die Ripple-Frequenz und die Dynamik der Membranpotentiale werden analytisch als Funktion des Inputs und der Netzwerkparameter angenähert. Die Theorie erklärt, warum die Ripple-Frequenz im Verlauf eines SPW-R-Ereignisses sinkt (intra-ripple frequency accommodation, IFA). Weiterhin zeigt eine numerische Analyse, dass ein alternatives Modell, basierend auf einem transienten Störungseffekt in einer schwach gekoppelten Interneuron-Population, unter biologisch plausiblen Annahmen keine IFA erzeugen kann. IFA kann somit zur Modellauswahl beitragen und deutet auf starke, verzögerte inhibitorische Kopplung als plausiblen Mechanismus hin. Schließlich wird die Anwendbarkeit eines kürzlich entwickelten mesoskopischen Ansatzes für die effiziente Simulation von Ripples in endlich großen Netzwerken geprüft. Dabei wird das Rauschen nicht im Input der Neurone beschrieben, sondern als stochastisches Feuern entsprechend einer Hazard-Rate. Es wird untersucht, wie die Wahl des Hazards die dynamische Suszeptibilität einzelner Neurone, und damit die Ripple-Dynamik in rekurrenten Interneuron-Netzwerken beeinflusst. / Hippocampal activity during sleep or rest is characterized by sharp wave-ripples (SPW-Rs): transient (50–100 ms) periods of elevated neuronal activity modulated by a fast oscillation — the ripple (140–220 Hz). SPW-Rs have been linked to memory consolidation, but their generation mechanism remains unclear. Multiple potential mechanisms have been proposed, relying on excitation and/or inhibition as the main pacemaker. This thesis analyzes ripple oscillations in inhibitory network models at micro-, meso-, and macroscopic scales and elucidates how the ripple dynamics depends on the excitatory drive, inhibitory coupling strength, and the noise model. First, an interneuron network under strong drive and strong coupling with delay is analyzed. A theory is developed that captures the drift-mediated spiking dynamics in the mean-field limit. The ripple frequency as well as the underlying dynamics of the membrane potential distribution are approximated analytically as a function of the external drive and network parameters. The theory explains why the ripple frequency decreases over the course of an event (intra-ripple frequency accommodation, IFA). Furthermore, numerical analysis shows that an alternative inhibitory ripple model, based on a transient ringing effect in a weakly coupled interneuron population, cannot account for IFA under biologically realistic assumptions. IFA can thus guide model selection and provides new support for strong, delayed inhibitory coupling as a mechanism for ripple generation. Finally, a recently proposed mesoscopic integration scheme is tested as a potential tool for the efficient numerical simulation of ripple dynamics in networks of finite size. This approach requires a switch of the noise model, from noisy input to stochastic output spiking mediated by a hazard function. It is demonstrated how the choice of a hazard function affects the linear response of single neurons and therefore the ripple dynamics in a recurrent interneuron network.

This document represents a doctoral thesis held under the Brazilian School of Public and Business Administration of Getulio Vargas Foundation (EBAPE/FGV), developed through the elaboration of three articles. The research that resulted in the articles is within the scope of the project entitled 'Windows of opportunities and knowledge networks: implications for catch-up in developing countries', funded by Support Programme for Research and Academic Production of Faculty (ProPesquisa) of Brazilian School of Public and Business Administration (EBAPE) of Getulio Vargas Foundation. / Submitted by Marne Santos de Melo (marne.melo@gmail.com) on 2016-05-03T22:11:34Z No. of bitstreams: 1 PhD Dissertation_MarneMelo_Final_Version.pdf: 2457125 bytes, checksum: 159e5ecfb2ba7a58c8f0bf57741590b7 (MD5) / Rejected by Marcia Bacha (marcia.bacha@fgv.br), reason: Aluna irá submeter novamente com o arquivo certo. 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No. of bitstreams: 1 PhD Dissertation_MarneMelo_Final_Version_05052016.pdf: 2534725 bytes, checksum: f6d42a161060acc546b6d30458d2a77e (MD5) Previous issue date: 2016-04-15 / This study aims to investigate the theory of catch-up cycles in the setting of developing countries. We chose the Brazilian seeds sector as the locus of investigation. In order to explain catching up and industrial leadership, as suggested by the authors, we confront changes at the global level and windows of opportunities that emerged with responses from the main company of the sector - Embrapa. In our empirical study, we made use of in-depth interviews with historical and longitudinal analysis. We found evidence that changes in key dimensions alter in importance over time, but that institutions/public policy seem to be the forces that most contribute to strong dominance of transnational companies nowadays. Moreover, differently than suggested by some authors (although they are mainly focused in the Argentinean seeds sector), we find evidence that transnational companies – particularly the Gene Giants – do are driven the process of seeds innovation in the industry. In addition, the highest amount of launching of new varieties each year is not synonymous of more (or bigger) innovation; dominant positions in the market is not directly associated with higher levels of technological innovation. In fact, market innovation – e. g., commercial approach of transnational companies, which includes financing of producers and sales distribution - seems to be, at least, as relevant as technological innovation in the setting of seeds industry. / Esse estudo busca investigar a teoria de ciclos de 'catch-up' no contexto de países em desenvolvimento. O setor de sementes agrícolas brasileiro foi escolhido como locus de investigação. A fim de explicar catching up e lideranças na indústria, foram confrontadas mudanças e janelas de oportunidades ocorridas no nível global com as respostas da principal empresa do setor – Embrapa. No estudo empírico, fizemos uso de entrevistas em profundidade e análise histórica e longitudinal. Foram encontradas evidências de que mudanças em dimensões-chave alteram em importância ao longo do tempo, mas que instituições/políticas públicas parecem ser as forças que mais tem contribuído para a forte dominância das empresas transnacionais atualmente. Além disso, diferentemente do que tem sido sugerido por alguns autores (embora eles estivessem focados principalmente no setor de sementes da Argentina), encontramos evidências de que as empresas transnacionais - em particular as 'Gene Giants' - realmente tem direcionado o processo de inovação na indústria de sementes. Além disso, a maior quantidade de lançamento de novas variedades a cada ano não é sinónimo de mais (ou de maior) inovação; posições dominantes no mercado também não estão diretamente associadas a níveis mais elevados de inovação tecnológica. Na verdade, a inovação no mercado - e. g, abordagem comercial das empresas transnacionais, o que inclui o financiamento de produtores e de distribuição de vendas - parecem ser, pelo menos, tão relevantes quanto a inovação tecnológica no cenário da indústria de sementes. RESUMO 2 - UNDERSTANDING THE DYNAMICS OF NETWORK STRUCTURES: ALLYING THE GROUNDED-THEORY TO SOCIAL NETWORK APPROACH APPLIED TO THE BRAZILIAN SEEDS SECTOR O objetivo deste trabalho é lançar luz sobre uma lacuna previamente identificada em Powell et al. (2005) e posteriormente explorada em Ahuja, Soda e Zaheer (2012): a compreensão das origens e evolução das estruturas de rede intensivas em conhecimento; em outras palavras, seu dinamismo. Especificamente, essa pesquisa examinou como e por que redes centradas em uma empresa pública de P&D de um país em desenvolvimento têm evoluído para assumir as formas que elas possuem. No processo de examinar a questão de pesquisa, especial atenção foi dada para as várias razões pelas quais os setores público e privado buscam estabelecer parcerias. O contexto empírico escolhido foi o setor de sementes agrícolas do Brasil, mas nos focamos especificamente no programa de melhoramento de soja da Embrapa, a principal empresa representativa do setor. A lógica subjacente utilizada para desenvolver nosso arcabouço teórico foi a 'grounded theory'. O desenho de pesquisa é um estudo de caso único longitudinal, estudo indutivo, mas também foi feito uso da abordagem de rede social. Com base nos achados de pesquisa, nós desenvolvemos um arcabouço teórico para compreender o dinamismo das redes. Nós constatamos diferentes interesses entre as empresas, que mudaram ao longo do tempo, e diferentes efeitos para cada tipo de rede. Além disso, foi confirmada a crescente relevância da interação entre atores organizacionais e importantes 'trade-offs' entre organizações públicas e privadas. RESUMO 3 - TECHNOLOGICAL TRAJECTORY OF EMBRAPA AND THE CONQUEST OF CERRADO Apesar da existência de inúmeros estudos dedicados a investigar a trajetória tecnológica das empresas, pouca atenção tem sido dada a algumas características dessa trajetória. Como exemplo, podem ser citados o tempo que as empresas levam para avançar tecnologicamente e a influência de fatores, tais como as redes de conhecimento e mecanismos de aprendizagem na capacidade tecnológica das firmas. Na verdade, a relação redes-capacidades é considerada por muitos autores uma das mais importantes interações, que tem sido negligenciada. Esse artigo busca minimizar esses 'gaps' na literatura. Especificamente, nós examinamos a trajetória tecnológica da principal empresa brasileira do setor de sementes agrícolas – Embrapa – incluindo o tempo para avançar tecnologicamente e a relação redes de conhecimento-capacidades tecnológicas. No processo de examinar a trajetória tecnológica da Embrapa, nós examinamos como a Embrapa conquistou o Cerrado e mensuramos alguns importantes resultados de inovações tecnológicas – produção e exportação. Por meio de um estudo de caso longitudinal, nós concluímos que a Embrapa adotou diferentes trajetórias ao longo do tempo. Inicialmente a empresa adotou a trajetória 'path-following', em seguida a trajetória 'path-skipping' e, posteriormente, a trajetória 'path-creating'. A Embrapa também mudou seus parceiros ao longo do tempo (ou eles tiveram seus papeis adaptados às condições da época). Com a ajuda de parceiros, a Embrapa foi capaz de rapidamente alcançar o nível de liderança mundial. Ademais, indicadores de produção e exportação provaram ser relevantes para mensurar resultados de esforços de inovação.