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231 results for “functional connectivity”
Data from: Intrinsic functional connectivity delineates transmodal language functions
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Seasonality in functional connectivity: A case study with the American marten in Forillon National Park
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Pairing functional connectivity with population dynamics to prioritize corridors for Southern California spotted owls
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Data from: Brain states govern the spatio-temporal dynamics of resting-state functional connectivity
<p>Previously, using simultaneous resting-state functional magnetic resonance imaging (fMRI) and photometry-based neuronal calcium recordings in the anesthetized rat, we identified blood oxygenation level-dependent (BOLD) responses directly related to slow calcium waves, revealing a cortex-wide and spatially organized correlate of locally recorded neuronal activity (<a href="#_ENREF_68" title="Schwalm, 2017 #1"><span>Schwalm et al., 2017</span></a>). Here, using the same techniques, we investigate two distinct cortical activity states: persistent activity, in which compartmentalized network dynamics were observed; and slow wave activity, dominated by a cortex-wide BOLD component, suggesting a strong functional coupling of inter-cortical activity. During slow wave activity we find a correlation between the occurring slow wave events and the strength of functional connectivity between different cortical areas. These findings suggest that down-up transitions of neuronal excitability can drive cortex-wide functional connectivity. This study provides further evidence that changes in functional connectivity are dependent on the brain's current state, directly linked to the generation of slow waves.</p> <p> </p>
Connectivity-based localization of human hypothalamic nuclei in functional images of standard voxel size
<p>Despite their critical roles in autonomic functions, individual hypothalamic nuclei have not been extensively investigated in humans using functional magnetic resonance imaging, partly due to the difficulty in resolving individual nuclei contained in the small structure of the hypothalamus. Areal parcellation analyses enable discrimination of individual hypothalamic nuclei but require a higher spatial resolution, which necessitates long scanning time or large amounts of data to compensate for the low signal-to-noise ratio in 3T or 1.5T scanners. In this study, we present analytic procedures to estimate likely locations of individual nuclei in the standard 2-mm resolution based on our higher resolution dataset. The spatial profiles of functional connectivity with the cerebral cortex for each nucleus in the medial hypothalamus were calculated using our higher resolution dataset. Voxels in the hypothalamus in standard resolution images from the Human Connectome Project (HCP) database that predominantly shared connectivity profiles with the same nucleus were subsequently identified. Voxels representing individual nuclei, as identified with the analytic procedures, were reproducible across 20 HCP datasets of 20 subjects each. Furthermore, the identified voxels were spatially separate. These results suggest that these analytic procedures are capable of refining voxels that represent individual hypothalamic nuclei in standard resolution. Our results highlight the potential utility of these procedures in various settings such as patient studies, where lengthy scans are infeasible.</p>
Integrating functional connectivity in designing networks of protected areas under climate change: a caribou case-study
<p>Land-use change and climate change are recognized as two main drivers of the current biodiversity decline. Protected areas help safeguard the landscape from additional anthropogenic disturbances and, when properly designed, can help species cope with climate change impacts. When designed to protect the regional biodiversity rather than to conserve focal species or landscape elements, protected areas need to cover a representative sample of the regional biodiversity and be functionally connected, facilitating individual movements among protected areas in a network to maximize their effectiveness. We developed a methodology to define effective protected areas to implement in a regional network using ecological representativeness and functional connectivity as criteria. We illustrated this methodology in the Gaspésie region of Québec, Canada. We simulated movements for the endangered Atlantic-Gaspésie caribou population (<i>Rangifer tarandus caribou</i>), using an individual-based model, to determine functional connectivity based on this large mammal. We created multiple protected areas network scenarios and evaluated their ecological representativeness and functional connectivity for the current and future conditions. We selected a subset of the most effective network scenarios and extracted the protected areas included in them. There was a tradeoff between ecological representativeness and functional connectivity for the created networks. Only a few protected areas among those available were repeatedly chosen in the most effective networks. Protected areas maximizing both ecological representativeness and functional connectivity represented suitable areas to implement in an effective protected areas network. These areas ensured that a representative sample of the regional biodiversity was covered by the network, as well as maximizing the movement over time between and inside the protected areas for the focal population.</p>
Data from: Loss of functional connectivity in migration networks induces population decline in migratory birds
Migratory birds rely on a habitat network along their migration routes by temporarily occupying stopover sites between breeding and non-breeding grounds. Removal or degradation of stopover sites in a network might impede movement, and thereby reduce migration success and survival. The extent to which the breakdown of migration networks, due to changes in land use, impacts the population sizes of migratory birds is poorly understood. We measured the functional connectivity of migration networks of waterfowl species that migrate over the East Asian-Australasian Flyway from 1992-2015. We analysed the relationship between changes in non-breeding population sizes and changes in functional connectivity, while taking into account other commonly-considered species traits, using a Phylogenetic Linear Mixed Model. We found that population sizes significantly declined with a reduction in the functional connectivity of migration networks; no other predictor variables were important. We conclude that the current decrease in functional connectivity, due to habitat loss and degradation in migration networks, can negatively and crucially impact population sizes of migratory birds. Our findings provide new insights into the underlying mechanisms that affect population trends of migratory birds under environmental changes. Establishment of international agreements leading to the creation of systematic conservation networks associated with migratory species' distributions and stopover sites may safeguard migratory bird populations.
Data from: Fencing solves human‐wildlife conflict locally but shifts problems elsewhere: a case study using functional connectivity modelling of the African elephant
1. Fencing is one of the commonest methods for mitigating human-wildlife conflicts. At the same time, fencing is considered to be of one of the most pressing emerging threats to conservation globally. Although fences act as barriers and eventually can cause population isolation and fragmentation, it is challenging to quantitatively predict the possible consequences fences have for wildlife. 2. Here, we model how fencing designed to mitigate human-elephant conflict (HEC) on the Borderlands between Kenya and Tanzania will affect functional connectivity and movement corridors for African elephants. Specifically, we (1) model functional landscape connectivity integrating natural and anthropogenic factors; (2) predict seasonal movement corridors used by elephants in non-protected areas; and (3) evaluate whether fencing in one area can potentially intensify human-wildlife conflicts elsewhere. 3. We used GPS movement and remote sensing data to develop monthly step-selection functions to model functional connectivity. For future scenarios, we used a currently ongoing fencing project designed for human-elephant conflict mitigation within the study area. We modelled movement corridors using least-cost path and circuit theory methods, evaluated their predictive power and quantified connectivity changes resulting from the planned fencing. 4. Our results suggest that fencing will not cause landscape fragmentation and will not change functional landscape connectivity dramatically. However, fencing will lead to a loss of connectivity locally and will increase the potential for HEC in new areas. We estimated that wetlands important for movement corridors will be more intensively used by the elephants, which may also cause problems of overgrazing. Seasonal analysis highlighted an increasing usage of non-protected lands in the dry season and equal importance of the pinch point wetlands for preserving overall function connectivity. 5. Synthesis and applications. Fencing is a solution to small-scale HEC problems, but will not solve the issue at a broader scale. Moreover, our results highlight that it may intensify the conflicts and overuse of habitat patches in other areas, thereby negating any conservation benefits. If fencing is employed on a broader scale, then it is imperative that corridors are integrated within the protected area network to ensure local connectivity of affected species.
Data from: Ditch network sustains functional connectivity and influences patterns of gene flow in an intensive agricultural landscape
In intensive agricultural landscapes, plant species previously relying on semi-natural habitats may persist as metapopulations within landscape linear elements. Maintenance of populations' connectivity through pollen and seed dispersal is a key factor in species persistence in the face of substantial habitat loss. The goals of this study were to investigate the potential corridor role of ditches and to identify the landscape components that significantly impact patterns of gene flow among remnant populations. Using microsatellite loci, we explored the spatial genetic structure of two hydrochorous wetland plants exhibiting contrasting local abundance and different habitat requirements: the rare and regionally protected Oenanthe aquatica and the more commonly distributed Lycopus europaeus, in an 83 km2 agricultural lowland located in northern France. Both species exhibited a significant spatial genetic structure, along with substantial levels of genetic differentiation, especially for L. europaeus, which also expressed high levels of inbreeding. Isolation-by-distance analysis revealed enhanced gene flow along ditches, indicating their key role in effective seed and pollen dispersal. Our data also suggested that the configuration of the ditch network and the landscape elements significantly affected population genetic structure, with (i) species-specific scale effects on the genetic neighborhood and (ii) detrimental impact of human ditch management on genetic diversity, especially for O. aquatica. Altogether, these findings highlighted the key role of ditches in the maintenance of plant biodiversity in intensive agricultural landscapes with few remnant wetland habitats.
Data from: Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme
Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, i.e. the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic datasets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of inter-individual measures of genotypic dissimilarity may efficiently replace inter-population measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.
Data from: Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum)
Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multi-scale analysis to determine how landscape composition, configuration, and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side-by-side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation-by-distance and isolation-by-resistance models for this land snail, with an equal fit to least-cost paths and circuit-theory-based models. Each of the 12 landscapes analyzed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavorable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results, and shows how multi-scale analyses provide insight to scale-dependent processes.
[Dataset] enhanced functional connectivity properties of human brains during in-situ nature experience
<p>Raw data</p> <p>Artifact-free EEG raw data recorded by Emotiv Epoc (sample rate 128/s, 14 channels).</p>
Functional and structural computed connectivity profiles for pre-defined whole-brain and cortical hull maps
<p>This Repository holds Lead-DBS Lead-Mapper v.2.5.2 computed functional and structural estimated connectivity. The structural dMRI connectivity is computed based on the "HCP1000 6K" connecome and the fMRI connectivity "GSP 1000 Yeo 2011" connectome.</p> <p>Both connectivity metrices were computed using two pre-defined grids:</p> <ol> <li> Cortical hull (1025 points). The grid was estimated based on the <a href="https:/github.com/neuromodulation/py_neuromodulation/blob/main/py_neuromodulation/ConnectivityDecoding/_get_grid_hull.m">SPM cortex_20484 grid</a> and subsampled by every 20th point. The grid is saved as a <a href="(https:/github.com/neuromodulation/py_neuromodulation/blob/main/py_neuromodulation/ConnectivityDecoding/mni_coords_cortical_surface.mat)">.mat file</a> and can be acessed through the main repository .</li> <li>Whole-brain (1236 points). Given the Lead-DBS provided <a href="https://github.com/neuromodulation/py_neuromodulation/blob/main/py_neuromodulation/ConnectivityDecoding/Automated%20Anatomical%20Labeling%203%20(Rolls%202020).nii">AAL3 atlas</a> the whole-brain .nii grid is subsampled by a factor of 150. See here the <a href="https://github.com/neuromodulation/py_neuromodulation/blob/main/py_neuromodulation/ConnectivityDecoding/_get_grid_whole_brain.py">grid computation</a>.</li> </ol> <p>Both grids can be accessed trough the <a href="https://github.com/neuromodulation/py_neuromodulation/tree/main">py_neuromodulation</a> API using the <a href="https://github.com/neuromodulation/py_neuromodulation/blob/main/py_neuromodulation/nm_RMAP.py">nm_RMAP.py</a> module.</p>
Functional Connectivity Development along the Sensorimotor-Association Axis Enhances the Cortical Hierarchy
<p><span>Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total <em>n </em>= 3,355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (<em>n </em>= 1,207), Nathan Kline Institute-Rockland Sample (<em>n</em> = 397), Human Connectome Project: Development (<em>n</em> = 625), and Healthy Brain Network (<em>n</em> = 1,126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development. <strong><span> </span></strong><span> </span></span></p>
Functional connectivity and graph theory of self networks in toodlers with ASD
<p>The study collected fMRI data from children with autism and typical developmental disorders at 18-24 months and 25-48 months, and analyzed the brain's self network using functional connectivity and graph theory methods</p>
Predictive utility of task-related functional connectivity vs. voxel activation - Data and code archive
<p>Functional connectivity, both in resting state and task performance, has steadily increased its share of neuroimaging research effort in the last 1.5 decades. In the current study, we investigated the predictive utility regarding behavioral performance and task information for 240 participants, aged 20-77, for both voxel activation and functional connectivity in 12 cognitive tasks, belonging to 4 cognitive reference domains (Episodic Memory, Fluid Reasoning, Perceptual Speed, and Vocabulary). We also added a model only comprising brain-structure information not specifically acquired during performance of a cognitive task. We used a simple brain-behavioral prediction technique based on Principal Component Analysis (PCA) and regression and studied the utility of both modalities in quasi out-of-sample predictions, using split-sample simulations (=5-fold Monte Carlo cross validation) with 1,000 iterations for which a regression model predicting a cognitive outcome was estimated in a training sample, with a subsequent assessment of prediction success in a non-overlapping test sample. The sample assignments were identical for functional connectivity, voxel activation, and brain structure, enabling apples-to-apples comparisons of predictive utility. All 3 models that were investigated included the demographic covariates age, gender, and years of education. A minimal reference model using simple linear regression with just these 3 covariates was included for comparison as well and was evaluated with the same resampling scheme as described above. Results of the comparison between voxel activation and functional connectivity were mixed and showed some dependency on cognitive outcome; however, mean differences in predictive utility between voxel activation and functional connectivity were rather small in terms of within-modality variability or predictive success. More notably, only in the case of Fluid Reasoning did concurrent functional neuroimaging provided compelling about cognitive performance beyond structural brain imaging or the minimal reference model.</p>
Functional connectivity in the face of congenital structural changes – a case of homozygous LAMC3 Mutation
<p>Results of diffusion tensor imaging analysis for each participant. These results were summarized in a manuscript titled as " <strong>Functional connectivity in the face of congenital structural changes – a case of homozygous <em>LAMC3</em> Mutation</strong> "</p>
Source data related to the manuscript by Zhou et al (2024), entitled "Impaired Functional Connectivity of Cortico-Amygdala Pathway Can Drive Social Behavior Deficits in Synucleinopathies"
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Data from: Replicated landscape genetic and network analyses reveal wide variation in functional connectivity for American pikas
Landscape connectivity is essential for maintaining viable populations, particularly for species restricted to fragmented habitats or naturally arrayed in metapopulations and facing rapid climate change. The importance of assessing both structural connectivity (the physical distribution of favorable habitat patches) and functional connectivity (how species move among habitat patches) for managing such species is well understood. However, the degree to which functional connectivity for a species varies among landscapes, and the resulting implications for conservation, have rarely been assessed. We used a landscape genetics approach to evaluate resistance to gene flow and, thus, to determine how landscape and climate-related variables influence gene flow for American pikas (Ochotona princeps) in eight federally managed sites in the western United States. We used those empirically-derived, individual-based landscape resistance models in conjunction with predictive occupancy models to generate patch-based network models describing functional landscape connectivity. Metareplication across landscapes enabled identification of limiting factors for dispersal that would not otherwise have been apparent. Despite the cool microclimates characteristic of pika habitat, south-facing aspects consistently represented higher resistance to movement, supporting the previous hypothesis that exposure to relatively high temperatures may limit dispersal in American pikas. We found that other barriers to dispersal included areas with a high degree of topographic relief, such as cliffs and ravines, as well as streams and distances greater than one to four kilometers depending on the site. Using the empirically-derived network models of habitat patch connectivity, we identified habitat patches that were likely disproportionately important for maintaining functional connectivity, areas in which habitat appeared fragmented, and locations that could be targeted for management actions to improve functional connectivity. We concluded that climate change, besides influencing patch occupancy as predicted by other studies, may alter landscape resistance for pikas, thereby influencing functional connectivity through multiple pathways simultaneously. Spatial autocorrelation among genotypes varied across study sites and was largest where habitat was most dispersed, suggesting that dispersal distances increased with habitat fragmentation, up to a point. This study demonstrates how landscape features linked to climate can affect functional connectivity for species with naturally fragmented distributions, and reinforces the importance of replicating studies across landscapes.
Data from: The structural and functional connectivity of the grassland plant Lychnis flos-cuculi
Understanding the relationship between structural and functional connectivity is essential for successful restoration and conservation management, particularly in intensely managed agricultural landscapes. We evaluated the relationship between structural and functional connectivity of the wetland plant Lychnis flos-cuculi in a fragmented agricultural landscape using landscape genetic and network approaches. First, we studied the effect of structural connectivity, such as geographic distance and various landscape elements (forest, agricultural land, settlements and ditch verges), on gene flow among populations as a measurement of functional connectivity. Second, we examined the effect of structural graph-theoretic connectivity measures on gene flow among populations and on genetic diversity within populations of L. flos-cuculi. Among landscape elements, forests hindered gene flow in L. flos-cuculi, whereas gene flow was independent of geographic distance. Among the structural graph-theoretic connectivity variables, only intrapopulation connectivity, which was based on population size, had a significant positive effect on gene flow, that is, more gene flow took place among larger populations. Unexpectedly, interpopulation connectivity of populations, which takes into account the spatial location and distance among populations, did not influence gene flow in L. flos-cuculi. However, higher observed heterozygosity and lower inbreeding was observed in populations characterised by higher structural interpopulation connectivity. This finding shows that a spatially coherent network of populations is significant for maintaining the genetic diversity of populations. Nevertheless, lack of significant relationships between gene flow and most of the structural connectivity measures suggests that structural connectivity does not necessarily correspond to functional connectivity.
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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.