Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

An architecture for adaptive replication-based multimedia streaming in P2P networks

This PhD thesis addresses the issue of scalable media streaming in large-scale networking environments. Multimedia streaming is one of the largest sink of network resources and this trend is still growing as testified by the success of services like Skype, Netflix, Spotify and Popcorn Time (BitTorrent-based). In traditional client-server solutions, when the number of consumers increases, the server becomes the bottleneck. To overcome this problem, the Content-Delivery Network (CDN) model was invented. In CDN model, the server copies the media content to some CDN servers, which are located in different strategic locations on the network. However, they require heavy infrastructure investment around the world, which is too expensive. Peer-to-peer (P2P) solutions are another way to achieve the same result. These solutions are naturally scalable, since each peer can act as both a receiver and a forwarder. Most of the proposed streaming solutions in P2P networks focus on routing scenarios to achieve scalability. However, these solutions cannot work properly in video-on-demand (VoD) streaming, when resources of the media server are not sufficient. Replication is a solution that can be used in these situations. This thesis specifically provides a family of replication-based media streaming protocols, which are scalable, efficient and reliable in P2P networks. First, it provides SCALESTREAM, a replication-based streaming protocol that adaptively replicates media content in different peers to increase the number of consumers that can be served in parallel. The adaptiveness aspect of this solution relies on the fact that it takes into account different constraints like bandwidth capacity of peers to decide when to add or remove replicas. SCALESTREAM routes media blocks to consumers over a tree topology, assuming a reliable network composed of homogenous peers in terms of bandwidth. Second, this thesis proposes RESTREAM, an extended version of SCALESTREAM that addresses the issues raised by unreliable networks composed of heterogeneous peers. Third, this thesis proposes EAGLEMACAW, a multiple-tree replication streaming protocol in which two distinct trees, named EAGLETREE and MACAWTREE, are built in a decentralized manner on top of an underlying mesh network. These two trees collaborate to serve consumers in an efficient and reliable manner. The EAGLETREE is in charge of improving efficiency, while the MACAWTREE guarantees reliability. Finally, this thesis provides TURBOSTREAM, a hybrid replication-based streaming protocol in which a tree overlay is built on top of a mesh overlay network. Both these overlays cover all peers of the system and collaborate to improve efficiency and low-latency in streaming media to consumers. This protocol is implemented and tested in a real networking environment using PlanetLab Europe testbed composed of peers distributed in different places in Europe.

Cognitive anatomy of the temporal lobe: Effect of personality in population with mild cognitive impairment & Functional specialization for memory systems in healthy individuals.

Résumé: L'impact de la maladie d'Alzheimer (MA) est dévastateur pour la vie quotidienne de la personne affectée, avec perte progressive de la mémoire et d'autres facultés cognitives jusqu'à la démence. Il n'existe toujours pas de traitement contre cette maladie et il y a aussi une grande incertitude sur le diagnostic des premiers stades de la MA. La signature anatomique de la MA, en particulier l'atrophie du lobe temporal moyen (LTM) mesurée avec la neuroimagerie, peut être utilisée comme un biomarqueur précoce, in vivo, des premiers stades de la MA. Toutefois, malgré le rôle évident du LMT dans les processus de la mémoire, nous savons que les modèles anatomiques prédictifs de la MA basés seulement sur des mesures d'atrophie du LTM n'expliquent pas tous les cas cliniques. Au cours de ma thèse, j'ai conduit trois projets pour comprendre l'anatomie et le fonctionnement du LMT dans (1) les processus de la maladie et dans (2) les processus de mémoire ainsi que (3) ceux de l'apprentissage. Je me suis intéressée à une population avec déficit cognitif léger (« Mild Cognitive Impairment », MCI), à risque pour la MA. Le but du premier projet était de tester l'hypothèse que des facteurs, autres que ceux cognitifs, tels que les traits de personnalité peuvent expliquer les différences interindividuelles dans le LTM. De plus, la diversité phénotypique des manifestations précliniques de la MA provient aussi d'une connaissance limitée des processus de mémoire et d'apprentissage dans le cerveau sain. L'objectif du deuxième projet porte sur l'investigation des sous-régions du LTM, et plus particulièrement de leur contribution dans différentes composantes de la mémoire de reconnaissance chez le sujet sain. Pour étudier cela, j'ai utilisé une nouvelle méthode multivariée ainsi que l'IRM à haute résolution pour tester la contribution de ces sous-régions dans les processus de familiarité (« ou Know ») et de remémoration (ou « Recollection »). Finalement, l'objectif du troisième projet était de tester la contribution du LTM en tant que système de mémoire dans l'apprentissage et l'interaction dynamique entre différents systèmes de mémoire durant l'apprentissage. Les résultats du premier projet montrent que, en plus du déficit cognitif observé dans une population avec MCI, les traits de personnalité peuvent expliquer les différences interindividuelles du LTM ; notamment avec une plus grande contribution du neuroticisme liée à une vulnérabilité au stress et à la dépression. Mon étude a permis d'identifier un pattern d'anormalité anatomique dans le LTM associé à la personnalité avec des mesures de volume et de diffusion moyenne du tissu. Ce pattern est caractérisé par une asymétrie droite-gauche du LTM et un gradient antéro-postérieur dans le LTM. J'ai interprété ce résultat par des propriétés tissulaires et neurochimiques différemment sensibles au stress. Les résultats de mon deuxième projet ont contribué au débat actuel sur la contribution des sous-régions du LTM dans les processus de familiarité et de remémoration. Utilisant une nouvelle méthode multivariée, les résultats supportent premièrement une dissociation des sous-régions associées aux différentes composantes de la mémoire. L'hippocampe est le plus associé à la mémoire de type remémoration et le cortex parahippocampique, à la mémoire de type familiarité. Deuxièmement, l'activation correspondant à la trace mnésique pour chaque type de mémoire est caractérisée par une distribution spatiale distincte. La représentation neuronale spécifique, « sparse-distributed», associée à la mémoire de remémoration dans l'hippocampe serait la meilleure manière d'encoder rapidement des souvenirs détaillés sans interférer les souvenirs précédemment stockés. Dans mon troisième projet, j'ai mis en place une tâche d'apprentissage en IRM fonctionnelle pour étudier les processus d'apprentissage d'associations probabilistes basé sur le feedback/récompense. Cette étude m'a permis de mettre en évidence le rôle du LTM dans l'apprentissage et l'interaction entre différents systèmes de mémoire comme la mémoire procédurale, perceptuelle ou d'amorçage et la mémoire de travail. Nous avons trouvé des activations dans le LTM correspondant à un processus de mémoire épisodique; les ganglions de la base (GB), à la mémoire procédurale et la récompense; le cortex occipito-temporal (OT), à la mémoire de représentation perceptive ou l'amorçage et le cortex préfrontal, à la mémoire de travail. Nous avons également observé que ces régions peuvent interagir; le type de relation entre le LTM et les GB a été interprété comme une compétition, ce qui a déjà été reporté dans des études récentes. De plus, avec un modèle dynamique causal, j'ai démontré l'existence d'une connectivité effective entre des régions. Elle se caractérise par une influence causale de type « top-down » venant de régions corticales associées avec des processus de plus haut niveau venant du cortex préfrontal sur des régions corticales plus primaires comme le OT cortex. Cette influence diminue au cours du de l'apprentissage; cela pourrait correspondre à un mécanisme de diminution de l'erreur de prédiction. Mon interprétation est que cela est à l'origine de la connaissance sémantique. J'ai également montré que les choix du sujet et l'activation cérébrale associée sont influencés par les traits de personnalité et des états affectifs négatifs. Les résultats de cette thèse m'ont amenée à proposer (1) un modèle expliquant les mécanismes possibles liés à l'influence de la personnalité sur le LTM dans une population avec MCI, (2) une dissociation des sous-régions du LTM dans différents types de mémoire et une représentation neuronale spécifique à ces régions. Cela pourrait être une piste pour résoudre les débats actuels sur la mémoire de reconnaissance. Finalement, (3) le LTM est aussi un système de mémoire impliqué dans l'apprentissage et qui peut interagir avec les GB par une compétition. Nous avons aussi mis en évidence une interaction dynamique de type « top -down » et « bottom-up » entre le cortex préfrontal et le cortex OT. En conclusion, les résultats peuvent donner des indices afin de mieux comprendre certains dysfonctionnements de la mémoire liés à l'âge et la maladie d'Alzheimer ainsi qu'à améliorer le développement de traitement. Abstract: The impact of Alzheimer's disease is devastating for the daily life of the affected patients, with progressive loss of memory and other cognitive skills until dementia. We still lack disease modifying treatment and there is also a great amount of uncertainty regarding the accuracy of diagnostic classification in the early stages of AD. The anatomical signature of AD, in particular the medial temporal lobe (MTL) atrophy measured with neuroimaging, can be used as an early in vivo biomarker in early stages of AD. However, despite the evident role of MTL in memory, we know that the derived predictive anatomical model based only on measures of brain atrophy in MTL does not explain all clinical cases. Throughout my thesis, I have conducted three projects to understand the anatomy and the functioning of MTL on (1) disease's progression, (2) memory process and (3) learning process. I was interested in a population with mild cognitive impairment (MCI), at risk for AD. The objective of the first project was to test the hypothesis that factors, other than the cognitive ones, such as the personality traits, can explain inter-individual differences in the MTL. Moreover, the phenotypic diversity in the manifestations of preclinical AD arises also from the limited knowledge of memory and learning processes in healthy brain. The objective of the second project concerns the investigation of sub-regions of the MTL, and more particularly their contributions in the different components of recognition memory in healthy subjects. To study that, I have used a new multivariate method as well as MRI at high resolution to test the contribution of those sub-regions in the processes of familiarity and recollection. Finally, the objective of the third project was to test the contribution of the MTL as a memory system in learning and the dynamic interaction between memory systems during learning. The results of the first project show that, beyond cognitive state of impairment observed in the population with MCI, the personality traits can explain the inter-individual differences in the MTL; notably with a higher contribution of neuroticism linked to proneness to stress and depression. My study has allowed identifying a pattern of anatomical abnormality in the MTL related to personality with measures of volume and mean diffusion of the tissue. That pattern is characterized by right-left asymmetry in MTL and an anterior to posterior gradient within MTL. I have interpreted that result by tissue and neurochemical properties differently sensitive to stress. Results of my second project have contributed to the actual debate on the contribution of MTL sub-regions in the processes of familiarity and recollection. Using a new multivariate method, the results support firstly a dissociation of the subregions associated with different memory components. The hippocampus was mostly associated with recollection and the surrounding parahippocampal cortex, with familiarity type of memory. Secondly, the activation corresponding to the mensic trace for each type of memory is characterized by a distinct spatial distribution. The specific neuronal representation, "sparse-distributed", associated with recollection in the hippocampus would be the best way to rapidly encode detailed memories without overwriting previously stored memories. In the third project, I have created a learning task with functional MRI to sudy the processes of learning of probabilistic associations based on feedback/reward. That study allowed me to highlight the role of the MTL in learning and the interaction between different memory systems such as the procedural memory, the perceptual memory or priming and the working memory. We have found activations in the MTL corresponding to a process of episodic memory; the basal ganglia (BG), to a procedural memory and reward; the occipito-temporal (OT) cortex, to a perceptive memory or priming and the prefrontal cortex, to working memory. We have also observed that those regions can interact; the relation type between the MTL and the BG has been interpreted as a competition. In addition, with a dynamic causal model, I have demonstrated a "top-down" influence from cortical regions associated with high level cortical area such as the prefrontal cortex on lower level cortical regions such as the OT cortex. That influence decreases during learning; that could correspond to a mechanism linked to a diminution of prediction error. My interpretation is that this is at the origin of the semantic knowledge. I have also shown that the subject's choice and the associated brain activation are influenced by personality traits and negative affects. Overall results of this thesis have brought me to propose (1) a model explaining the possible mechanism linked to the influence of personality on the MTL in a population with MCI, (2) a dissociation of MTL sub-regions in different memory types and a neuronal representation specific to each region. This could be a cue to resolve the actual debates on recognition memory. Finally, (3) the MTL is also a system involved in learning and that can interact with the BG by a competition. We have also shown a dynamic interaction of « top -down » and « bottom-up » types between the pre-frontal cortex and the OT cortex. In conclusion, the results could give cues to better understand some memory dysfunctions in aging and Alzheimer's disease and to improve development of treatment.