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149 results for “network connectivity”
Data from: Multi-purpose habitat networks for short-range and long-range connectivity: a new method combining graph and circuit connectivity
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Synaptic connectivity and neuronal network activity changes after extracellular matrix depletion
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Data from: Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks
Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.
Data from: Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish
According to the social decision-making (SDM) network hypothesis, SDM is encoded in a network of forebrain and midbrain structures in a distributed and dynamic fashion, such that the expression of a given social behaviour is better reflected by the overall profile of activation across the different loci rather than by the activity of a single node. This proposal has the implicit assumption that SDM relies on integration across brain regions, rather than on regional specialization. Here we tested the occurrence of functional localization and of functional connectivity in the SDM network. For this purpose we used zebrafish to map different social behaviour states into patterns of neuronal activity, as indicated by the expression of the immediate early genes c-fos and egr-1, across the SDM network. The results did not support functional localization, as some loci had similar patterns of activity associated with different social behaviour states, and showed socially driven changes in functional connectivity. Thus, this study provides functional support to the SDM network hypothesis and suggests that the neural context in which a given node of the network is operating (i.e. the state of its interconnected areas) is central to its functional relevance.
Data from: Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance
Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha–gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions.
Data from: Hydrologic controls on river network connectivity
This study proposes a probabilistic approach for the quantitative assessment of reach- and network-scale hydrological connectivity as dictated by river flow space-time variability. Spatial dynamics of daily streamflows are estimated based on climatic and morphological features of the contributing catchment, integrating a physically based approach that accounts for the stochasticity of rainfall with a water balance framework and a geomorphic recession flow analysis. Ecologically meaningful minimum stage thresholds are used to evaluate the connectivity of individual stream reaches, and other relevant network-scale connectivity metrics. The framework allows a quantitative description of the main hydrological causes and the ecological consequences of water depth dynamics experienced by river networks. The analysis shows that the spatial variability of local-scale hydrological connectivity is strongly affected by the spatial and temporal distribution of climatic variables. Depending on the underlying climatic settings and the critical stage threshold, loss of connectivity can be observed in the headwaters or along the main channel, thereby originating a fragmented river network. The proposed approach provides important clues for understanding the effect of climate on the ecological function of river corridors.
Data from: Fungal community reveals less dispersal limitation and potentially more connected network than that of bacteria in bamboo forest soils
A central aim of current microbial ecology research is to investigate the mechanisms shaping the assembly of soil microbial communities. Despite the importance of bacterial and fungal mediation of carbon cycling in forest ecosystems, knowledge concerning their distribution patterns and underlying mechanisms remains insufficient. Here, soils were sampled from six bamboo forests across the main planting area of Moso bamboo in southern China. The bacterial and fungal diversities were assessed by sequencing 16S rRNA and ITS gene amplicons, respectively, with an Illumina MiSeq. Based on structural equation modeling, dispersal limitation had strongest impact on bacterial beta diversity, while the mean annual precipitation had a smaller impact by directly or indirectly mediating the soil organic carbon density. However, only the mean annual temperature and precipitation played direct roles in fungal beta diversity. Moreover, the co-occurrence network analyses revealed a possibly much higher network connectivity in the fungal network than in the bacteria. With less dispersal limitation, stronger environmental selection, and a potentially more connected network, the fungal community had more important roles in the soil carbon metabolisms in bamboo forests. Fungal beta diversity and the clustering coefficient explained approximately 14.4% and 6.1% of the variation in the carbon metabolic profiles among sites, respectively, but that of bacteria only explained approximately 1.7% and 1.8%, respectively. This study explored soil microbial spatial patterns along with the underlying mechanisms of dispersal limitation, selection, and connectivity of ecological networks, thus providing novel insights into the study of the distinct functional traits of different microbial taxa.
TZO - Working memory performance in glioma patients is associated with functional connectivity between the right dorsolateral prefrontal cortex and default mode network
<p>Data files hosted on Figshare for "Working memory performance in glioma patients is associated with functional connectivity between the right dorsolateral prefrontal cortex and default mode network".</p> <p>Contains functional connectivity matrices, clinical variables, and working memory performance scores of 45 glioma patients.</p>
Network topology and patch connectivity affect dynamics in experimental and model metapopulations
<p>Biological populations are rarely isolated in space and instead interact with others via dispersal in metapopulations. Theory predicts that network connectivity patterns can have critical effects on network robustness, as certain topologies, such as scale-free networks, are more tolerant to disturbances than other patterns. However, at present, experimental evidence of how these topologies affect population dynamics in a metapopulation framework is lacking. We used experimental metapopulations of the aquatic protist <i>Paramecium tetraurelia</i> to determine how network topology influences occupation patterns. We created metapopulations engineered to be comparable in linkage density, but differing in their degree distribution. We compared random networks to scale-free networks by evaluating local population occupancy and abundance throughout 18-30 protist generations. In parallel, we used simulations to explore differences in patch occupation patterns among topologies. Under one scenario, random metapopulations of P. tetraurelia reached higher abundance and higher occupancy (proportion of occupied patches) compared to scale-free systems in both experimental and simulated systems, while in the other both types of metapopulations performed similarly. Increasing patch degree (i.e., number of connections per patch) reduced the probability of extinction of local populations in both types of networks. We suggest the interaction between colonization/extinction rates and network topology alters the likelihood of rescue effects which results in differential patterns of occupancy and abundance in metapopulations.</p>
Couple-Wise Functional Connectivity Similarity Between Auditory And Salience Network Predicts Marital Satisfaction
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Data from: Scalability of asynchronous networks is limited by one-to-one mapping between effective connectivity and correlations
Network models are routinely downscaled compared to nature in terms of numbers of nodes or edges because of a lack of computational resources, often without explicit mention of the limitations this entails. While reliable methods have long existed to adjust parameters such that the first-order statistics of network dynamics are conserved, here we show that limitations already arise if also second-order statistics are to be maintained. The temporal structure of pairwise averaged correlations in the activity of recurrent networks is determined by the effective population-level connectivity. We first show that in general the converse is also true and explicitly mention degenerate cases when this one-to-one relationship does not hold. The one-to-one correspondence between effective connectivity and the temporal structure of pairwise averaged correlations implies that network scalings should preserve the effective connectivity if pairwise averaged correlations are to be held constant. Changes in effective connectivity can even push a network from a linearly stable to an unstable, oscillatory regime and vice versa. On this basis, we derive conditions for the preservation of both mean population-averaged activities and pairwise averaged correlations under a change in numbers of neurons or synapses in the asynchronous regime typical of cortical networks. We find that mean activities and correlation structure can be maintained by an appropriate scaling of the synaptic weights, but only over a range of numbers of synapses that is limited by the variance of external inputs to the network. Our results therefore show that the reducibility of asynchronous networks is fundamentally limited.
Data from: Quantitative analysis of connectivity in populations of a semi-aquatic mammal using kinship categories and network assortativity
Analyzing the impact of anthropogenic and natural river barriers on the dispersal of aquatic and semi-aquatic species may be critical for their conservation, but no adequate genetic methods have been developed for quantifying the effect of specific barriers on current connectivity. Knowledge of kinship relationships between individuals and reconstructions of pedigrees obtained using genomic data can be extremely useful, not only for studying the social organization of animals, but also inferring how the last few generations of offspring have dispersed. In this study, we used kinship data to analyze connectivity patterns in a small semi-aquatic mammal, the Pyrenean desman, in an area comprising two river systems with close headwaters and dams of various sizes. Using a large SNP dataset from 70 specimens, we obtained kinship categories and reconstructed pedigrees. To quantify the barrier effect of specific obstacles, we constructed kinship networks and devised a method based on the assortativity coefficient, which measures the proportion between observed and expected kinship relationships across a barrier. The estimation of this parameter enabled us to infer that the most important barrier in the area was the watershed divide between the rivers, followed by a dam on one of the rivers. Other barriers did not significantly reduce the expected number of kinship relationships across them. This strategy and the information obtained with it may be crucial in determining the most important connectivity problems in an area and help develop conservation plans aimed at improving genetic exchange between populations of threatened species.
Impact of Immune Challenge on Triple Network Connectivity in Humans
ClinicalTrials.gov study NCT02653235. IPD Sharing: NO. Countries: 0. Publications: 1.
Data associated with Balasubramaniam, Beisner et al. (PeerJ, 2016): "Social buffering and contact transmission: Network connections have beneficial and detrimental effects on Shigella infection risk among captive rhesus macaques"
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Data from: Scalability of asynchronous networks is limited by one-to-one mapping between effective connectivity and correlations
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Data from: Fungal community reveals less dispersal limitation and potentially more connected network than that of bacteria in bamboo forest soils
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Data from: Hydrologic controls on river network connectivity
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Data from: Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks
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Data from: Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish
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Data from: Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.