Internet of things (IoT) is envisioned as a promising paradigm to interconnect enormous wireless devices. However, the success of IoT is challenged by the difficulty of access management of the massive amount of sporadic and unpredictable user traffics. This thesis focuses on the contention-based random access in massive cellular IoT systems and introduces two novel frameworks to provide enhanced scalability, real-time quality of service management, and resource efficiency. First, a local communication based congestion control framework is introduced to distribute the random access attempts evenly over time under bursty traffic. Second, a multi-agent reinforcement learning based preamble selection framework is designed to increase the access capacity under a fixed number of preambles. Combining the two mechanisms provides superior performance under various 3GPP-specified machine type communication evaluation scenarios in terms of achieving much lower access latency and fewer access failures. / Master of Science / In the age of internet of things (IoT), massive amount of devices are expected to be connected to the wireless networks in a sporadic and unpredictable manner. The wireless connection is usually established by contention-based random access, a four-step handshaking process initiated by a device through sending a randomly selected preamble sequence to the base station. While different preambles are orthogonal, preamble collision happens when two or more devices send the same preamble to a base station simultaneously, and a device experiences access failure if the transmitted preamble cannot be successfully received and decoded. A failed device needs to wait for another random access opportunity to restart the aforementioned process and hence the access delay and resource consumption are increased. The random access control in massive IoT systems is challenged by the increased access intensity, which results in higher collision probability. In this work, we aim to provide better scalability, real-time quality of service management, and resource efficiency in random access control for such systems. Towards this end, we introduce 1) a local communication based congestion control framework by enabling a device to cooperate with neighboring devices and 2) a multi-agent reinforcement learning (MARL) based preamble selection framework by leveraging the ability of MARL in forming the decision-making policy through the collected experience. The introduced frameworks are evaluated under the 3GPP-specified scenarios and shown to outperform the existing standard solutions in terms of achieving lower access delays with fewer access failures.

Autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) have been difficult to differentiate in clinical settings, as these two disorders are phenotypically similar and both exhibit atypical attention and executive functioning. Mischaracterizations between these two disorders can lead to inappropriate medication regimes, significant delays in special services, and personal distress to families and caregivers. There is evidence that ASD and ADHD are biologically different for attentional and executive functioning mechanisms, as only half of individuals with co-occurring ASD and ADHD respond to stimulant medication. Further, neurobehavioral work has supported these biological differences for ASD and ADHD, with both shared and distinct functional connectivity. In specific, two brain networks have been implicated in these disorders: the salience network (SN) and frontoparietal network (FPN). The SN is a network anchored by bilateral anterior insula and the dorsal anterior cingulate cortex and has been implicated in “bottom-up” attentional processes for both internal and external events. The FPN is anchored by lateral prefrontal cortex areas and the parietal lobe and plays a roll in “top-down” executive processes. Functional connectivity subgroups differentiated ASD from ADHD with between SN-FPN connectivity patterns, but not by within-SN or within-FPN connectivity patterns. Further, subgroup differences in ASD+ADHD comorbidity vs. ASD only were found for within-FPN connectivity. / Master of Science / Autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) have been difficult to differentiate in clinical settings, as these two disorders are similar and both exhibit attention and executive functioning difficulties. ASD and ADHD have shared and distinct functional brain network connectivity related to attention and executive functioning. Two brain networks have been implicated in these disorders: the salience network (SN) and frontoparietal network (FPN). The SN is a network that has been implicated in “bottom-up” attentional processes for both internal and external events. The FPN plays a roll in “top-down” executive processes. This study found that functional connectivity patterns between the SN and FPN differentiated ASD from ADHD. Further, connectivity patterns in children with co-occurring ASD and ADHD were characterized by within-FPN connectivity.

Social cognition is a set of complex processes that mediate much of human behavior. The development of these skills is related to and interdependent on other cognitive processes, particularly inhibitory control, which allows for willful suppression of dominant responses. Many aspects of social behavior rely on inhibitory control to moderate impulsive or socially inappropriate behaviors and process complex perspective-taking. Furthermore, the brain regions associated with inhibitory control and social cognition overlap functionally and structurally. I review neurodevelopmental literature to suggest that social cognition is developmentally dependent on inhibitory control and that the neural foundations of both these skills are measurable in infancy. I tested this model using growth curve and structural equation modeling and show that 10-month, but not 5-month, frontotemporal coherence predicts social cognition in late childhood through preschool inhibitory control. These findings provide insight into the neurodevelopmental trajectory of cognition and suggest that connectivity from frontal regions to other parts of the brain is a foundation for the development of these skills. / Doctor of Philosophy / Social cognition is the ability to understand and interpret another’s thoughts, words, and actions and inhibitory control is the ability to suppress one’s own thoughts, words, and actions. These two types of cognition are similar and use the same brain regions, and I suggest that inhibitory control underlies much of social cognition. In order to test this, I examined children’s inhibitory control and brain connectivity at 5 months, 10 months, 24 months, 48 months, and 9 years and measured social cognition at 9 years. I found that connectivity between the frontal and temporal lobes at 10 months predicted inhibitory control and 48-months, which then predicted social cognition at 9 years. This suggests that infant brain connectivity sets the stage for developing inhibitory control, which is important for later social cognition

Functional connectivity measures have become one of the most common biomarkers when correlating brain activity to task and resting states post treatment. Mindfulness based stress reduction (MBSR) and cognitive behavioral therapy (CBT) are two well established forms of therapies treating clinical populations worldwide today. Although there are several studies that have investigated the neural correlations of these therapy forms individually, no systematic review has compared them side by side, to identify potential similarities and differences in functional connectivity. This systematic review attempts to shed light on how functional connectivity is altered during resting state after completed treatment, by reviewing a total of 4 CBT and 4 MBSR studies containing 337 participants. The results point to possible differences in resting state functional connectivity (rsFC) concerning the insula and similarities involving the cingulate cortex and other parts of the DMN. The insula has been suggested to be involved in the creation of motivation and the integration of bodily sensations and feelings. Furthermore, emotional reactions to personally valued behaviors and the retrieving of episodic memories is associated with the function of the cingulate cortex. These changes in rsFC might relate to the theoretical underpinnings of CBT and MBSR. However, more compelling research needs to be conducted before drawing conclusions on how these therapeutic approaches can alter rsFC and improve psychological health among individuals suffering from clinical conditions.

Rivers and their surrounding riparian and subsurface ecosystems, known as river corridors, are important landscape features that provide a myriad of ecological and societal benefits. While the importance of riverine flooding has been widely acknowledged and extensively studied, very little research has been conducted on the interactions between river channels and their adjacent floodplains. The importance of this hydrologic connectivity between rivers and floodplains has been emphasized in recent decades and now ecological engineering techniques such as stream restoration are often utilized to restore connectivity between streams and their riparian ecosystems. Despite its ubiquity in practice, there are still many basic components of river-floodplain connectivity that are not well understood. Furthermore, a lack of cost-effective monitoring techniques makes sustainable management of river corridors quite challenging. Thus, the overall goals of my dissertation were: 1) develop user-friendly river corridor monitoring techniques utilizing cost-effective approaches such as time-lapse digital imagery and satellite remote sensing and 2) identify the effects of anthropogenic activities on river corridor hydrologic and biogeochemical processes that occur at varying spatial and temporal scales during flood events. These goals were addressed through five independent studies that span spatiotemporal scales. The five studies utilized a combination of novel remote sensing, hydrologic/hydraulic modeling, and high frequency spatial sampling techniques to analyze river corridor dynamics. Results highlight that digital imagery and satellite remote sensing can be effective tools for monitoring river corridors in data scare regions. Additionally, impounding streams and river corridors alters floodplain connectivity and biogeochemical processing of reactive solutes such as nitrogen and phosphorus. Findings from this work highlight the important role that spatial and temporal scale plays in river corridor dynamics. Overall, this research provides new analytical techniques and findings that can be used to effectively monitor and manage river corridors. / PHD / Rivers are important landscape features that provide basic societal needs such as drinking water, water for agricultural irrigation, and hydroelectric energy. Engineers have traditionally sought to manage rivers for these purposes while also minimizing flooding. However, flooding actually provides a number of environmental benefits such as increased aquatic biodiversity and removal of excess sediment and pollutants from rivers. This notion of environmentally friendly flooding is a relatively new concept and much is still unknown about how these processes differ at varying scales. Additionally, there is currently a lack of techniques for monitoring such processes primarily due to the cost required for equipment and labor. Therefore, the goals of this dissertation were twofold: 1) develop cost-effective and user-friendly monitoring techniques that can be used to study river flooding dynamics and 2) examine the impacts of river flooding dynamics at three different spatial scales ranging from a small stream to a large watershed. This was accomplished through five separate case studies that examine rivers and watersheds of varying sizes at varying time scales. The studies utilized several emerging technologies that required a combination of field monitoring, computer simulations of flood dynamics, and satellite imagery to gain a better understanding of river flood hydrology and water quality. A key finding was the important role that scale plays in both spatial and temporal domains. Utilizing varying spatial and temporal scales allowed for identification of different processes that occur across a range of river and watershed sizes. Overall, this work can be used to better inform future river management and restoration decisions.

Once thriving neighborhoods in mid-sized American cities have been decimated, scarred and disrupted by the serpentine free form highways that have touched them. This product of technological innovation from the 1950s and 60s has had a profound and disturbing affect upon American cities. The collective history, cultural rituals and organic urban fabric of life has been almost completely extinguished in these cities by the false opportunity and instant gratification that comes with so-called 'technological progress.' This, yes this, epitomizes the urban core of a majority of cities across the United States early in the early 21st century. What is to be the future legacy of these American cities upon the life of their residents? It quickly became apparent that to develop a deep understanding of this urban challenge, it was going to be necessary to carefully examine cites that have been acutely affected by urban highways. The neighborhoods at the core of these damaged American cities trudge on'.. Why? Because they have no other option'. The question currently at hand is how can these damaged neighborhoods adjacent to urban highways, and their associated cities, be regenerated? The research phase of this thesis exposed four critical elements of a thriving and organic urban neighborhood; connectivity, realness, livability and performativity. I was encouraged to focus upon and explore this notion of connectivity by my thesis committee, as it represents the element offering the most agency for the design professions. Through interrogating the [dis]connectivity of four specific neighborhoods in Baltimore, Buffalo, Richmond and St Petersburg certain operational systems began to evolve. These systems center around three critical lenses of focus; the economic, social and physical operations that occur within and adjacent to an urban neighborhood. Due to its acute condition, the Gilpin neighborhood of Richmond, Virgina was chosen as a case study to employ the lenses of connectivity through close examination and intervention. / Master of Science / Once thriving neighborhoods in mid-sized American cities have been decimated, scarred and disrupted by the serpentine free form highways that have touched them. This product of technological innovation from the 1950s and 60s has had a profound and disturbing affect upon American cities. The collective history, cultural rituals and organic urban fabric of life has been almost completely extinguished in many of these cities by the false opportunity and instant gratification that comes with so-called ‘technological progress.’ This, yes this, epitomizes the urban core of a majority of cities across the United States early in the early 21st century. <b>What is to be the future legacy of these American cities upon the life of their residents?</b> The neighborhoods at the core of these damaged American cities trudge on… Why? Because they have no other option... <b>The question currently at hand is how can these neighborhoods adjacent to urban highways, and their associated cities, be regenerated?</b> Through interrogating the [dis]connectivity of four specific neighborhoods in Baltimore, Buffalo, Richmond, and St Petersburg certain operational systems began to become apparent. These systems center around three critical lenses of focus; the economic, social, and physical operations that occur within and adjacent to an urban neighborhood. Due to its acute condition, the Gilpin neighborhood of Richmond, Virginia was chosen as a case study to employ the lenses of connectivity through closer examination and intervention.

Resting-state functional MRI(rs-fMRI) represents a powerful means to assess brain functional connectivity in healthy subjects and in neuropsychiatric patients. Aberrant functional connectivity has been observed in subjects affected by Alcohol Use Disorders (AUD) and other forms of substance dependence, a major health issue worldwide with limited treatment options. Despite intense investigation, the specific neuronal substrates involved and the functional implications of aberrant connectivity in these patients remain unknown. Moreover, it is unclear whether treatment can reverse these alterations, and normalize functional connectivity. Several methodological and conceptual questions in the analysis of functional connectivity are still open, and contribute to this uncertainty. Functional connectivity is defined in terms of correlated MR-signal fluctuations, and in-scanner patient motion and other nuisance signals can introduce spurious correlations, thus representing substantial confounding factors. At a more general level, understanding the effects of complex conditions, like AUD, on brain connectivity and their functional implications requires a deep comprehension of the brain organizational principles at multiple scales, a tremendous challenge that is at the heart of modern neuroscience. In this PhD dissertation I address some of the outstanding questions in the analysis and interpretation of aberrant functional connectivity in AUD. To this end, I have embraced the formalism of graph-theory, a powerful framework to assess the effects of alcohol abuse on the local and global topological organization of resting state connectivity. On the methodological side, I have investigated the effects of subject’s motion on the structure of resting state networks, and compared efficacy of different approaches to remove motion-related confounds. Moreover, I demonstrate the importance of network sparsification to remove spurious connections from the graph while maximizing the structural information that can be extracted from the system. Leveraging these methodological developments, I have evaluated functional alterations in different samples of AUD patients. In two independent studies, I demonstrated specific alterations in the topological organization of the insular cortex and subcortical basal structures in recently detoxified alcoholics. Interestingly, protracted abstinence appears to partially normalize functional connectivity, thus suggesting that alcohol-induced alterations in connectivity may be amenable to treatment. Based on these findings, I have studied the effects on brain functional networks of a putative novel treatment based on deep Transcranial Magnetic Stimulation (TMS). Specifically, I analyzed resting state connectivity in AUD patients subjected to repetitive TMS of the bilateral insula and of the anterior cingulate cortex (ACC), and demonstrated treatment-induced changes that may underlie the efficacy of this potential treatment in surrogate clinical read-outs.

Le cerveau humain est un réseau très complexe. Le fonctionnement cérébral ne résulte donc pas de l'activation de régions cérébrales isolées mais au contraire met en jeu des réseaux distribués dans le cerveau (Bassett and Sporns, 2017; McIntosh, 2000). Par conséquent, l'analyse de la connectivité cérébrale à partir des données de neuroimagerie occupe aujourd'hui une place centrale dans la compréhension des fonctions cognitives (Sporns, 2010). Grâce à son excellente résolution spatiale, l'IRMf est devenue l'une des méthodes non invasives les plus couramment utilisées pour étudier cette connectivité. Cependant, l'IRMf a une faible résolution temporelle ce qui rend très difficile le suivi de la dynamique des réseaux cérébraux. Un défi considérable en neuroscience cognitive est donc l'identification et le suivi des réseaux cérébraux sur des durées courtes (Hutchison et al., 2013), généralement <1s pour une tâche de dénomination d'images, par exemple. Jusqu'à présent, peu d'études ont abordé cette question qui nécessite l'utilisation de techniques ayant une résolution temporelle très élevée (de l'ordre de la ms), ce qui est le cas pour la magnéto- ou l'électro-encéphalographie (MEG ou EEG). Cependant, l'interprétation des mesures de connectivité à partir d'enregistrements effectués au niveau des électrodes (scalp) n'est pas simple, car ces enregistrements ont une faible résolution spatiale et leur précision est altérée par les effets de conduction par le volume (Schoffelen and Gross, 2009). Ainsi, au cours des dernières années, l'analyse de la connectivité fonctionnelle au niveau des sources corticales reconstruites à partir des signaux du scalp a fait l'objet d'un intérêt croissant. L'avantage de cette méthode est d'améliorer la résolution spatiale, tout en conservant l'excellente résolution temporelle de l'EEG ou de la MEG (Hassan et al., 2014; Hassan and Wendling, 2018; Schoffelen and Gross, 2009). Cependant, l'aspect dynamique n'a pas été suffisamment exploité par cette méthode. Le premier objectif de cette thèse est de montrer comment l'approche « EEG connectivité source » permet de suivre la dynamique spatio-temporelle des réseaux cérébraux impliqués soit dans une tache cognitive, soit à l'état de repos. Par ailleurs, les études récentes ont montré que les désordres neurologiques sont le plus souvent associés à des anomalies dans la connectivité cérébrale qui entraînent des altérations dans des réseaux cérébraux «large-échelle» impliquant des régions distantes (Fornito and Bullmore, 2014). C'est particulièrement le cas pour l'épilepsie et les maladies neurodégénératives (Alzheimer, Parkinson) qui constituent, selon l'OMS, un enjeu majeur de santé publique. Dans ce contexte, la demande clinique est très forte pour de nouvelles méthodes capables d'identifier des réseaux pathologiques, méthodes simples à mettre en œuvre et surtout non invasives. Ceci est le deuxième objectif de cette thèse. / The human brain is a very complex network. Cerebral function therefore does not imply activation of isolated brain regions but instead involves distributed networks in the brain (Bassett and Sporns, 2017, McIntosh, 2000). Therefore, the analysis of the brain connectivity from neuroimaging data has an important role to understand cognitive functions (Sporns, 2010). Thanks to its excellent spatial resolution, fMRI has become one of the most common non-invasive methods used to study this connectivity. However, fMRI has a low temporal resolution which makes it very difficult to monitor the dynamics of brain networks. A considerable challenge in cognitive neuroscience is therefore the identification and monitoring of brain networks over short time durations(Hutchison et al., 2013), usually <1s for a picture naming task, for example. So far, few studies have addressed this issue which requires the use of techniques with a very high temporal resolution (of the order of the ms), which is the case for magneto- or electro-encephalography (MEG or EEG). However, the interpretation of connectivity measurements from recordings made at the level of the electrodes (scalp) is not simple because these recordings have low spatial resolution and their accuracy is impaired by volume conduction effects (Schoffelen and Gross, 2009). Thus, during recent years, the analysis of functional connectivity at the level of cortical sources reconstructed from scalp signals has been of increasing interest. The advantage of this method is to improve the spatial resolution, while maintaining the excellent resolution of EEG or MEG (Hassan et al., 2014; Hassan and Wendling, 2018; Schoffelen and Gross, 2009). However, the dynamic aspect has not been sufficiently exploited by this method. The first objective of this thesis is to show how the EEG connectivity approach source "makes it possible to follow the spatio-temporal dynamics of the cerebral networks involved either in a cognitive task or at rest. Moreover, recent studies have shown that neurological disorders are most often associated with abnormalities in cerebral connectivity that result in alterations in wide-scale brain networks involving remote regions (Fornito and Bullmore, 2014). This is particularly the case for epilepsy and neurodegenerative diseases (Alzheimer's, Parkinson's) which constitute, according to WHO, a major issue of public health.In this context, the need is high for new methods capable of identifying Pathological networks, from easy to use and non-invasive techniques. This is the second objective of this thesis.

This thesis provides a novel dynamic large-scale network perspective on brain activity of human sleep based on the analysis of unique human neuroimaging data. Specifically, I provide new information based on integrating spatial and temporal aspects of brain activity both in the transitions between and during wakefulness and various stages of non-rapid-eye movement (NREM) sleep. This is achieved through investigations of inter-regional interactions, functional connectivity (FC), between activity timecourses throughout the brain. Overall, the presented findings provide new important whole-brain insights for our current understanding of sleep, and potentially also of sleep disorders and consciousness in general. In Chapter 2 I present a robust global increase in similarity between the structural connectivity (SC) and the FC in slow-wave sleep (SWS) in almost all of the participants of two independent fMRI datasets. This could point to a decreased state repertoire and more rigid brain dynamics during SWS. Chapter 2 further identifies the changes in FC strengths between wakefulness and individual stages of NREM sleep across the whole-brain fMRI network. I report connectivity in posterior parts of the brain as particularly strong during wakefulness, while connections between temporal and frontal cortices are increased in strength during N1 and N2 sleep. SWS is characterised by a global drop in FC. In Chapter 3 I take advantage of rare MEG recordings of NREM sleep to show, for the first time, the feasibility of constructing source-space FC networks of sleep using power envelope correlations. The increased temporal information of MEG signals allows me to identify the specific frequencies underlying the FC differences identified in Chapter 2 with fMRI. The beta band (16 – 30 Hz) thus stands out as important for the strong posterior connectivity of wakefulness, while a range of frequency bands from delta (0.25 – 4 Hz) to sigma (13 – 16 Hz) all appear to contribute to N2-specific FC increases. Consistent with the fMRI results, slow-wave sleep shows the lowest level of FC. Interestingly, however, the MEG signals suggest a fronto-temporal network of high connectivity in the alpha band, possibly reflecting memory processes. In Chapter 4 I expand the within-frequency FC analysis of Chapter 3 to explore potential cross-frequency interactions in the MEG FC networks. It is shown that N2 sleep involves an abundance of frequency cross-talk, while SWS includes very little. A multi-layer network approach shows that the gamma band (30 – 48 Hz) is particularly integrated in wakefulness. Chapter 5 addresses the identified MEG FC findings from the perspective of traditional spectral sleep staging. By correlating temporal changes in spectral power at the sensor level to fluctuations in average FC, a specific type of transient events is found to underlie the strong N2-specific coupling in static FC values. Lastly, in Chapter 6 I make the leap out of the constraints of traditional low-resolution sleep staging, and extract dynamic states of FC from fMRI timecourses in a completely unsupervised fashion. This provides a novel representation of whole-brain states of sleep and the dynamics governing them. I argue that data-driven approaches like this are necessary to fully characterise the spatiotemporal principles underlying wakefulness and sleep in the human brain.

Aujourd'hui, la campagne n'est plus seulement un lieu de production agricole puisque de nouveaux usages, notamment récréatifs, apparaissent (Urbain 2002, Perrier-Cornet, Hervieu, 2002). Ainsi, cette thèse porte sur les associations et leur rôle dans la recomposition de la structure sociale et sportive de la société rurale en Franche-Comté, en matière d'intégration et/ou d'exclusion. Notre travail empirique, entrecroisant des phases quantitatives et qualitatives, s'apparente à une plongée analytique dans la vie sociale des clubs ruraux. Nous y observons les mécanismes d'engagement et de désengagement des sportifs en suivant leur itinéraire au sein des structures associatives. Dans une approche mêlant l'influence des situations et des dispositions, notre étude se donne pour objectif d'analyser les différentes modalités de construction ou de déconstruction des « connectivités » dans et/ou à partir des clubs sportifs des villages ruraux. Nous définissons les connectivités selon trois dimensions : la « communalité », soit le partage ou la possession d'un attribut commun, la « connexité », comme les attaches relationnelles qui lient les individus entre eux et la « groupalité », comme le sentiment d'appartenir à un groupe particulier, limité, solidaire (Brubaker, 2001). Sans pour autant écarter les contraintes macro-sociales, la construction plurielle des connectivités sportives associatives résulte de l'inscription des individus au sein d'une « configuration » particulière (Elias, 1991), au centre de laquelle l' « esprit club » joue un rôle prépondérant. En ce sens, les associations sportives rurales, à travers leurs temporalités, sportives et extra-sportives, exercent une influence déterminante sur la structuration des connectivités/dé-connectivités. L'articulation de logiques individuelles et collectives entraîne alors leur différenciation et parfois même leur décomposition. Notre recherche sur ces connectivités/dé-connectivités différenciées permet, alors, de démontrer leur rapport réciproque avec le processus d'intégration et/ou d'exclusion et d'évaluer la portée structurante et/ou reléguante de la réalité du sport à la campagne. / Today, the countryside is no longer exclusively a place for agricultural production. Indeed, new uses are appearing, amongst which, recreational activities (Urbain 2002, Perrier-Cornet, Hervieu, 2002). This thesis deals with associations and their role into the reorganization of the social and sports structure in rural society in Franche-Comté, with a focus on integration and/or exclusion. Our empirical work counts both quantitative and qualitative phases and can be compared to an analytical dive into the social life of the rural athletic clubs. There, we observe the mechanisms of sportsmen's involvement and uninvolvment by following their ‘career' within the associative structures. In an approach combining the influence of situational and individual characteristics, our study aims at analyzing the various modalities for the construction or the deconstruction of the "connectivities" in and/or from the sports clubs in the rural villages. We define connectivities according to three dimensions: the "commonality" is the sharing or the ownership of a common attribute; the "connectedness" is defined as the relational ties which bind the individuals together; and the "groupness", as the feeling of belonging to a particular, limited, united group (Brubaker, 2001). Without pushing aside the macro-social constraints, the plural construction of the associative sports connectivities is the result of the inscription of the individuals within a particular "configuration" (Elias, 1991), at the center of which the "club spirit" plays a major role. The rural sports associations, through their sports-related and non-sports-related temporalities, exercise a determining influence on the structuring of the connectivities/dis-connectivities. The articulation of individual and collective logics then causes their differentiation and sometimes even their decomposition. So, our research on these differentiated connectivities/dis-connectivities allows to demonstrate their mutual relationship with the integration and/or exclusion process and to estimate the structuring and/or relegating impact of the reality of sports activities in the countryside.