Emergence of network features from multiplexity.
Ontology highlight
ABSTRACT:
SUBMITTER: Cardillo A
PROVIDER: S-EPMC3583169 | biostudies-other | 2013
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Networked systems emerge and subsequently evolve. Although several models describe the process of network evolution, researchers know far less about the initial process of network emergence. Here, we report temporal survey results of a real-world social network starting from its point of inception. We find that individuals' ties undergo an initial cycle of rapid expansion and contraction. This process helps to explain the eventual interactions and working structure in the network (in this case, scientific collaboration). We propose a stylized concept and model of "churn" to describe the process of network emergence and stabilization. Our empirical and simulation results suggest that these network emergence dynamics may be instrumental for explaining network details, as well as behavioral outcomes at later time periods.
| S-EPMC7736284 | biostudies-literature
Project description:The anesthesia awareness with recall (AAWR) phenomenon represents a complication of general anesthesia consisting of memorization of intraoperative events reported by the patient immediately after the end of surgery or at a variable distance from it. Approximately 20% of AAWR cases occur during emergence from anesthesia. Clinically, these unexpected experiences are often associated with distress especially due to a sense of paralysis. Indeed, although AAWR at the emergence has multiple causes, in the majority of cases the complication develops when the anesthesia plan is too early lightened at the end of anesthesia and there is a lack of use, or misuse, of neuromuscular monitoring with improper management of the neuromuscular block. Because the distress caused by the sense of paralysis represents an important predictor for the development of severe psychological complications, the knowledge of the phenomenon, and the possible strategies for its prophylaxis are aspects of considerable importance. Nevertheless, a limited percentage of episodes of AAWR cannot be prevented. This paradox holds also during the emergence phase of anesthesia which represents a very complex neurophysiological process with many aspects yet to be clarified.
| S-EPMC7000929 | biostudies-literature
Project description:Microbial interactions occurring on and around seeds are especially important for plant fitness since seed-borne microorganisms are the initial source of inoculum for the plant microbiota. In this study, we analyze structural and functional changes occurring within the plant microbiota at these early stages of the plant cycle, namely germination and emergence. To this purpose, we performed shotgun DNA sequencing of microbial assemblages associated to seeds, germinating seeds and seedlings of two plant species: bean and radish. We observed an enrichment of Enterobacteriales and Pseudomonadales during emergence and a set of functional traits linked to copiotrophy that could be responsible for this selection as a result of an increase of nutrient availability after germination. Representative bacterial isolates of taxa that are selected in seedlings showed indeed faster bacterial growth rate in comparison to seed-associated bacteria isolates. Finally, binning of metagenomics contigs results in the reconstruction of population genomes of the major bacterial taxa associated to the samples. Together, our results demonstrate that, although seed microbiota varied across plant species, nutrient availability during germination elicits changes of the composition of microbial communities by potentially selecting microbial groups with functional traits linked to copiotrophy. The data presented here represents the first attempts to empirically assess changes in the microbial community during plant emergence and moves us toward a more holistic understanding of the plant microbiome.
| S-EPMC6034153 | biostudies-literature
Project description:The lack of large-scale, continuously evolving empirical data usually limits the study of networks to the analysis of snapshots in time. This approach has been used for verification of network evolution mechanisms, such as preferential attachment. However, these studies are mostly restricted to the analysis of the first links established by a new node in the network and typically ignore connections made after each node's initial introduction. Here, we show that the subsequent actions of individuals, such as their second network link, are not random and can be decoupled from the mechanism behind the first network link. We show that this feature has strong influence on the network topology. Moreover, snapshots in time can now provide information on the mechanism used to establish the second connection. We interpret these empirical results by introducing the "propinquity model," in which we control and vary the distance of the second link established by a new node and find that this can lead to networks with tunable density scaling, as found in real networks. Our work shows that sociologically meaningful mechanisms are influencing network evolution and provides indications of the importance of measuring the distance between successive connections.
| S-EPMC6789902 | biostudies-literature
Project description:The principles governing the functional organization and development of long-range network interactions in the neocortex remain poorly understood. Using in vivo widefield and two-photon calcium imaging of spontaneous activity patterns in mature ferret visual cortex, we find widespread modular correlation patterns that accurately predict the local structure of visually evoked orientation columns several millimeters away. Longitudinal imaging demonstrates that long-range spontaneous correlations are present early in cortical development before the elaboration of horizontal connections and predict mature network structure. Silencing feedforward drive through retinal or thalamic blockade does not eliminate early long-range correlated activity, suggesting a cortical origin. Circuit models containing only local, but heterogeneous, connections are sufficient to generate long-range correlated activity by confining activity patterns to a low-dimensional subspace via multisynaptic short-range interactions. These results suggest that local connections in early cortical circuits can generate structured long-range network correlations that guide the formation of visually evoked distributed functional networks.
| S-EPMC6371984 | biostudies-literature
Project description:Context dependence is a key feature of cortical-basal ganglia circuit activity, and in songbirds the cortical outflow of a basal ganglia circuit specialized for song, LMAN, shows striking increases in trial-by-trial variability and bursting when birds sing alone rather than to females. To reveal where this variability and its social regulation emerge, we recorded stepwise from corticostriatal (HVC) neurons and their target spiny and pallidal neurons in Area X. We find that corticostriatal and spiny neurons both show precise singing-related firing across both social settings. Pallidal neurons, in contrast, exhibit markedly increased trial-by-trial variation when birds sing alone, created by highly variable pauses in firing. This variability persists even when recurrent inputs from LMAN are ablated. These data indicate that variability and its context sensitivity emerge within the basal ganglia network, suggest a network mechanism for this emergence, and highlight variability generation and regulation as basal ganglia functions.
| S-EPMC4132189 | biostudies-literature
Project description:Correlated activity in the entorhinal-hippocampal neuronal networks, supported by oscillatory and intermittent population activity patterns is critical for learning and memory. However, when and how correlated activity emerges in these networks during development remains largely unknown. Here, we found that during the first postnatal week in non-anaesthetized head-restrained rats, activity in the superficial layers of the medial entorhinal cortex (MEC) and hippocampus was highly correlated, with intermittent population bursts in the MEC followed by early sharp waves (eSPWs) in the hippocampus. Neurons in the superficial MEC layers fired before neurons in the dentate gyrus, CA3 and CA1. eSPW current-source density profiles indicated that perforant/temporoammonic entorhinal inputs and intrinsic hippocampal connections are co-activated during entorhinal-hippocampal activity bursts. Finally, a majority of the entorhinal-hippocampal bursts were triggered by spontaneous myoclonic body movements, characteristic of the neonatal period. Thus, during the neonatal period, activity in the entorhinal cortex (EC) and hippocampus is highly synchronous, with the EC leading hippocampal activation. We propose that such correlated activity is embedded into a large-scale bottom-up circuit that processes somatosensory feedback resulting from neonatal movements, and that it is likely to instruct the development of connections between neocortex and hippocampus.
| S-EPMC6319314 | biostudies-literature
Project description:The functional networks of cultured neurons exhibit complex network properties similar to those found in vivo. Starting from random seeding, cultures undergo significant reorganization during the initial period in vitro, yet despite providing an ideal platform for observing developmental changes in neuronal connectivity, little is known about how a complex functional network evolves from isolated neurons. In the present study, evolution of functional connectivity was estimated from correlations of spontaneous activity. Network properties were quantified using complex measures from graph theory and used to compare cultures at different stages of development during the first 5 weeks in vitro. Networks obtained from young cultures (14 days in vitro) exhibited a random topology, which evolved to a small-world topology during maturation. The topology change was accompanied by an increased presence of highly connected areas (hubs) and network efficiency increased with age. The small-world topology balances integration of network areas with segregation of specialized processing units. The emergence of such network structure in cultured neurons, despite a lack of external input, points to complex intrinsic biological mechanisms. Moreover, the functional network of cultures at mature ages is efficient and highly suited to complex processing tasks.
| S-EPMC3355061 | biostudies-literature
Project description:What is the origin of behaviour? Although typically associated with a nervous system, simple organisms also show complex behaviours. Among them, the slime mold Physarum polycephalum, a giant single cell, is ideally suited to study emergence of behaviour. Here, we show how locomotion and morphological adaptation behaviour emerge from self-organized patterns of rhythmic contractions of the actomyosin lining of the tubes making up the network-shaped organism. We quantify the spatio-temporal contraction dynamics by decomposing experimentally recorded contraction patterns into spatial contraction modes. Notably, we find a continuous spectrum of modes, as opposed to a few dominant modes. Our data suggests that the continuous spectrum of modes allows for dynamic transitions between a plethora of specific behaviours with transitions marked by highly irregular contraction states. By mapping specific behaviours to states of active contractions, we provide the basis to understand behaviour's complexity as a function of biomechanical dynamics.
| S-EPMC8782570 | biostudies-literature
Project description:As courts strive to simultaneously remain self-consistent and adapt to new legal challenges, a complex network of of citations between decided cases is established. Using network science methods to analyze the underlying patterns of citations between cases can help us understand the large-scale mechanisms which shape the judicial system. Here, we use the case-to-case citation structure of the Court of Justice of the European Union to examine this question. Using a link-prediction model, we show that over time the complex network of citations evolves in a way which improves our ability to predict new citations. Investigating the factors which enable prediction over time, we find that the content of the case documents plays a decreasing role, whereas both the predictive power and significance of the citation network structure itself show a consistent increase over time. Finally, our analysis enables us to validate existing citations and recommend potential citations for future cases within the court.
| S-EPMC7854739 | biostudies-literature