Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.

PubMed

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

PubMed Central

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems. PMID:29503613

Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks

PubMed Central

Ciuciu, Philippe; Abry, Patrice; He, Biyu J.

2014-01-01

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649

Multiple effects of hydrological connectivity on floodplain processes in human modified river systems

NASA Astrophysics Data System (ADS)

Hein, Thomas; Bondar-Kunze, Elisabeth; Preiner, Stefan; Reckendorfer, Walter; Tritthart, Michael; Weigelhofer, Gabriele; Welti, Nina

2014-05-01

Floodplain and riparian ecosystems provide multiple functions and services of importance for human well-being and are of strategic importance for different sectors at catchment scale. Especially floodplains in the vicinity of urban areas can be areas of conflicting interests ranging from different land use types, flood water retention, drinking water production and recreation to conservation of last remnants of former riverine landscape, as it is the case in floodplains in the Danube Nationalpark downstream Vienna. Many of these ecosystem functions and services are controlled by the exchange conditions between river main channel and floodplain systems, the hydrological connectivity. At the same time these systems have been highly altered and especially the connectivity has been severely impaired. Thus, far ranging effects of changes in hydrological connectivity at various levels can be expected in altered floodplain systems. The aim of this presentation is to explore the complex control of different ecosystem functions and associated services by different parameters of hydrological connectivity, ranging from nutrient, sediment and matter dynamics and biodiversity aspects. Increasing connectivity will be shown to impact microbial dynamics, sediment-water interactions, carbon dynamics and trophic conditions, thus affecting the fundamental functions of particular floodplain systems at various spatial and temporal scales. Based on these changes also the provision of ecosystem services of floodplains is affected. The results clearly show that hydrological connectivity needs to be considered in a sustainable management approach.

Scale invariant rearrangement of resting state networks in the human brain under sustained stimulation.

PubMed

Tommasin, Silvia; Mascali, Daniele; Moraschi, Marta; Gili, Tommaso; Assan, Ibrahim Eid; Fratini, Michela; DiNuzzo, Mauro; Wise, Richard G; Mangia, Silvia; Macaluso, Emiliano; Giove, Federico

2018-06-14

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may be not the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation. Copyright © 2018. Published by Elsevier Inc.

Mapping internal connectivity through human migration in malaria endemic countries.

PubMed

Sorichetta, Alessandro; Bird, Tom J; Ruktanonchai, Nick W; Zu Erbach-Schoenberg, Elisabeth; Pezzulo, Carla; Tejedor, Natalia; Waldock, Ian C; Sadler, Jason D; Garcia, Andres J; Sedda, Luigi; Tatem, Andrew J

2016-08-16

Human mobility continues to increase in terms of volumes and reach, producing growing global connectivity. This connectivity hampers efforts to eliminate infectious diseases such as malaria through reintroductions of pathogens, and thus accounting for it becomes important in designing global, continental, regional, and national strategies. Recent works have shown that census-derived migration data provides a good proxy for internal connectivity, in terms of relative strengths of movement between administrative units, across temporal scales. To support global malaria eradication strategy efforts, here we describe the construction of an open access archive of estimated internal migration flows in endemic countries built through pooling of census microdata. These connectivity datasets, described here along with the approaches and methods used to create and validate them, are available both through the WorldPop website and the WorldPop Dataverse Repository.

Mapping internal connectivity through human migration in malaria endemic countries

PubMed Central

Sorichetta, Alessandro; Bird, Tom J.; Ruktanonchai, Nick W.; zu Erbach-Schoenberg, Elisabeth; Pezzulo, Carla; Tejedor, Natalia; Waldock, Ian C.; Sadler, Jason D.; Garcia, Andres J.; Sedda, Luigi; Tatem, Andrew J.

2016-01-01

Human mobility continues to increase in terms of volumes and reach, producing growing global connectivity. This connectivity hampers efforts to eliminate infectious diseases such as malaria through reintroductions of pathogens, and thus accounting for it becomes important in designing global, continental, regional, and national strategies. Recent works have shown that census-derived migration data provides a good proxy for internal connectivity, in terms of relative strengths of movement between administrative units, across temporal scales. To support global malaria eradication strategy efforts, here we describe the construction of an open access archive of estimated internal migration flows in endemic countries built through pooling of census microdata. These connectivity datasets, described here along with the approaches and methods used to create and validate them, are available both through the WorldPop website and the WorldPop Dataverse Repository. PMID:27529469

Integrating wetland connectivity into models for watershed ...

EPA Pesticide Factsheets

Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal hydrologic connectivity continuum to downstream waters. Via these connections and disconnections, GIWs provide numerous hydrological, biogeochemical, and biological functions linked to human health and watershed-scale ecosystem services. Often, a clear demonstration of these functions and the individual and cumulative effects of GIWs on downstream waters is required for their protection or restoration. Measurements alone are typically too resource intensive to do this. In this presentation, we discuss the use of various modeling approaches to quantify the hydrologic connectivity of GIWs and their associated watershed-scale cumulative effects. Our goal is to improve the science behind understanding the functions and connectivity of GIWs via models that are complemented with various types of novel data. We synthesize what is meant by GIW connectivity and its broad significance to science and decision-making. We further discuss case studies that provide insights to diverse modeling approaches, with varying levels of complexity, for how to estimate GIW connectivity and associated watershed-scale impacts to hydrology. We finally provide insights to the key opportunities and priorities for integrating GIW connectivity into the next generation of models. Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal h

Human connectome module pattern detection using a new multi-graph MinMax cut model.

PubMed

De, Wang; Wang, Yang; Nie, Feiping; Yan, Jingwen; Cai, Weidong; Saykin, Andrew J; Shen, Li; Huang, Heng

2014-01-01

Many recent scientific efforts have been devoted to constructing the human connectome using Diffusion Tensor Imaging (DTI) data for understanding the large-scale brain networks that underlie higher-level cognition in human. However, suitable computational network analysis tools are still lacking in human connectome research. To address this problem, we propose a novel multi-graph min-max cut model to detect the consistent network modules from the brain connectivity networks of all studied subjects. A new multi-graph MinMax cut model is introduced to solve this challenging computational neuroscience problem and the efficient optimization algorithm is derived. In the identified connectome module patterns, each network module shows similar connectivity patterns in all subjects, which potentially associate to specific brain functions shared by all subjects. We validate our method by analyzing the weighted fiber connectivity networks. The promising empirical results demonstrate the effectiveness of our method.

Stepwise Connectivity of the Modal Cortex Reveals the Multimodal Organization of the Human Brain

PubMed Central

Sepulcre, Jorge; Sabuncu, Mert R.; Yeo, Thomas B.; Liu, Hesheng; Johnson, Keith A.

2012-01-01

How human beings integrate information from external sources and internal cognition to produce a coherent experience is still not well understood. During the past decades, anatomical, neurophysiological and neuroimaging research in multimodal integration have stood out in the effort to understand the perceptual binding properties of the brain. Areas in the human lateral occipito-temporal, prefrontal and posterior parietal cortices have been associated with sensory multimodal processing. Even though this, rather patchy, organization of brain regions gives us a glimpse of the perceptual convergence, the articulation of the flow of information from modality-related to the more parallel cognitive processing systems remains elusive. Using a method called Stepwise Functional Connectivity analysis, the present study analyzes the functional connectome and transitions from primary sensory cortices to higher-order brain systems. We identify the large-scale multimodal integration network and essential connectivity axes for perceptual integration in the human brain. PMID:22855814

Cascading events in linked ecological and socioeconomic systems

USGS Publications Warehouse

Peters, Debra P.C.; Sala, O.E.; Allen, Craig D.; Covich, A.; Brunson, M.

2007-01-01

Cascading events that start at small spatial scales and propagate non-linearly through time to influence larger areas often have major impacts on ecosystem goods and services. Events such as wildfires and hurricanes are increasing in frequency and magnitude as systems become more connected through globalization processes. We need to improve our understanding of these events in order to predict their occurrence, minimize potential impacts, and allow for strategic recovery. Here, we synthesize information about cascading events in systems located throughout the Americas. We discuss a variety of examples of cascading events that share a common feature: they are often driven by linked ecological and human processes across scales. In this era of globalization, we recommend studies that explicitly examine connections across scales and examine the role of connectivity among non-contiguous as well as contiguous areas.

Informing conservation management about structural versus functional connectivity: a case-study of Cross River gorillas.

PubMed

Imong, Inaoyom; Robbins, Martha M; Mundry, Roger; Bergl, Richard; Kühl, Hjalmar S

2014-10-01

Connectivity among subpopulations is vital for the persistence of small and fragmented populations. For management interventions to be effective conservation planners have to make the critical distinction between structural connectivity (based on landscape structure) and functional connectivity (which considers both landscape structure and organism-specific behavioral attributes) which can differ considerably within a given context. We assessed spatial and temporal changes in structural and functional connectivity of the Cross River gorilla Gorilla gorilla diehli (CRG) population in a 12,000 km(2) landscape in the Nigeria-Cameroon border region over a 23-year period, comparing two periods: 1987-2000 and 2000-2010. Despite substantial forest connections between occupied areas, genetic evidence shows that only limited dispersal occurs among CRG subpopulations. We used remotely sensed land-cover data and simulated human pressure (using a spatially explicit agent-based model) to assess human impact on connectivity of the CRG population. We calculated cost-weighted distances between areas occupied by gorillas as measures of connectivity (structural based on land-cover only, functional based on both land-cover and simulated human pressure). Whereas structural connectivity decreased by 5% over the 23-year period, functional connectivity decreased by 11%, with both decreasing more during the latter compared to the earlier period. Our results highlight the increasing threat of isolation of CRG subpopulations due to human disturbance, and provide insight into how increasing human influence may lead to functional isolation of wildlife populations despite habitat continuity, a pressing and common issue in tropical Africa often not accounted for when deciding management interventions. In addition to quantifying threats to connectivity, our study provides crucial evidence for management authorities to identify actions that are more likely to be effective for conservation of species in human-dominated landscapes. Our approach can be easily applied to other species, regions, and scales. © 2014 Wiley Periodicals, Inc.

Multivariate Heteroscedasticity Models for Functional Brain Connectivity.

PubMed

Seiler, Christof; Holmes, Susan

2017-01-01

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

How Visual Is the Visual Cortex? Comparing Connectional and Functional Fingerprints between Congenitally Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; Peelen, Marius V; Han, Zaizhu; He, Chenxi; Caramazza, Alfonso; Bi, Yanchao

2015-09-09

Classical animal visual deprivation studies and human neuroimaging studies have shown that visual experience plays a critical role in shaping the functionality and connectivity of the visual cortex. Interestingly, recent studies have additionally reported circumscribed regions in the visual cortex in which functional selectivity was remarkably similar in individuals with and without visual experience. Here, by directly comparing resting-state and task-based fMRI data in congenitally blind and sighted human subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. We found a close agreement between connectional and functional maps, pointing to a strong interdependence of connectivity and function. Visual experience (or the absence thereof) had a pronounced effect on the resting-state connectivity and functional response profile of occipital cortex and the posterior lateral fusiform gyrus. By contrast, connectional and functional fingerprints in the anterior medial and posterior lateral parts of the ventral visual cortex were statistically indistinguishable between blind and sighted individuals. These results provide a large-scale mapping of the influence of visual experience on the development of both functional and connectivity properties of visual cortex, which serves as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions. Significance statement: How is the functionality and connectivity of the visual cortex shaped by visual experience? By directly comparing resting-state and task-based fMRI data in congenitally blind and sighted subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. In addition to revealing regions that are strongly dependent on visual experience (early visual cortex and posterior fusiform gyrus), our results showed regions in which connectional and functional patterns are highly similar in blind and sighted individuals (anterior medial and posterior lateral ventral occipital temporal cortex). These results serve as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions of the visual cortex. Copyright © 2015 the authors 0270-6474/15/3512545-15$15.00/0.

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Human seizures couple across spatial scales through travelling wave dynamics

NASA Astrophysics Data System (ADS)

Martinet, L.-E.; Fiddyment, G.; Madsen, J. R.; Eskandar, E. N.; Truccolo, W.; Eden, U. T.; Cash, S. S.; Kramer, M. A.

2017-04-01

Epilepsy--the propensity toward recurrent, unprovoked seizures--is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms--namely, the effects of an increased extracellular potassium concentration diffusing in space--that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures--and connecting these dynamics to specific biological mechanisms--promises new insights to treat this devastating disease.

Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain

PubMed Central

Krienen, Fenna M.; Yeo, B. T. Thomas; Ge, Tian; Buckner, Randy L.; Sherwood, Chet C.

2016-01-01

The human brain is patterned with disproportionately large, distributed cerebral networks that connect multiple association zones in the frontal, temporal, and parietal lobes. The expansion of the cortical surface, along with the emergence of long-range connectivity networks, may be reflected in changes to the underlying molecular architecture. Using the Allen Institute’s human brain transcriptional atlas, we demonstrate that genes particularly enriched in supragranular layers of the human cerebral cortex relative to mouse distinguish major cortical classes. The topography of transcriptional expression reflects large-scale brain network organization consistent with estimates from functional connectivity MRI and anatomical tracing in nonhuman primates. Microarray expression data for genes preferentially expressed in human upper layers (II/III), but enriched only in lower layers (V/VI) of mouse, were cross-correlated to identify molecular profiles across the cerebral cortex of postmortem human brains (n = 6). Unimodal sensory and motor zones have similar molecular profiles, despite being distributed across the cortical mantle. Sensory/motor profiles were anticorrelated with paralimbic and certain distributed association network profiles. Tests of alternative gene sets did not consistently distinguish sensory and motor regions from paralimbic and association regions: (i) genes enriched in supragranular layers in both humans and mice, (ii) genes cortically enriched in humans relative to nonhuman primates, (iii) genes related to connectivity in rodents, (iv) genes associated with human and mouse connectivity, and (v) 1,454 gene sets curated from known gene ontologies. Molecular innovations of upper cortical layers may be an important component in the evolution of long-range corticocortical projections. PMID:26739559

Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain.

PubMed

Krienen, Fenna M; Yeo, B T Thomas; Ge, Tian; Buckner, Randy L; Sherwood, Chet C

2016-01-26

The human brain is patterned with disproportionately large, distributed cerebral networks that connect multiple association zones in the frontal, temporal, and parietal lobes. The expansion of the cortical surface, along with the emergence of long-range connectivity networks, may be reflected in changes to the underlying molecular architecture. Using the Allen Institute's human brain transcriptional atlas, we demonstrate that genes particularly enriched in supragranular layers of the human cerebral cortex relative to mouse distinguish major cortical classes. The topography of transcriptional expression reflects large-scale brain network organization consistent with estimates from functional connectivity MRI and anatomical tracing in nonhuman primates. Microarray expression data for genes preferentially expressed in human upper layers (II/III), but enriched only in lower layers (V/VI) of mouse, were cross-correlated to identify molecular profiles across the cerebral cortex of postmortem human brains (n = 6). Unimodal sensory and motor zones have similar molecular profiles, despite being distributed across the cortical mantle. Sensory/motor profiles were anticorrelated with paralimbic and certain distributed association network profiles. Tests of alternative gene sets did not consistently distinguish sensory and motor regions from paralimbic and association regions: (i) genes enriched in supragranular layers in both humans and mice, (ii) genes cortically enriched in humans relative to nonhuman primates, (iii) genes related to connectivity in rodents, (iv) genes associated with human and mouse connectivity, and (v) 1,454 gene sets curated from known gene ontologies. Molecular innovations of upper cortical layers may be an important component in the evolution of long-range corticocortical projections.

Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots.

PubMed

Fattebert, Julien; Robinson, Hugh S; Balme, Guy; Slotow, Rob; Hunter, Luke

2015-10-01

Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human-wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large carnivore species where landscape-scale resource selection data already exist.

Identifying Corridors among Large Protected Areas in the United States

PubMed Central

Belote, R. Travis; Dietz, Matthew S.; McRae, Brad H.; Theobald, David M.; McClure, Meredith L.; Irwin, G. Hugh; McKinley, Peter S.; Gage, Josh A.; Aplet, Gregory H.

2016-01-01

Conservation scientists emphasize the importance of maintaining a connected network of protected areas to prevent ecosystems and populations from becoming isolated, reduce the risk of extinction, and ultimately sustain biodiversity. Keeping protected areas connected in a network is increasingly recognized as a conservation priority in the current era of rapid climate change. Models that identify suitable linkages between core areas have been used to prioritize potentially important corridors for maintaining functional connectivity. Here, we identify the most “natural” (i.e., least human-modified) corridors between large protected areas in the contiguous Unites States. We aggregated results from multiple connectivity models to develop a composite map of corridors reflecting agreement of models run under different assumptions about how human modification of land may influence connectivity. To identify which land units are most important for sustaining structural connectivity, we used the composite map of corridors to evaluate connectivity priorities in two ways: (1) among land units outside of our pool of large core protected areas and (2) among units administratively protected as Inventoried Roadless (IRAs) or Wilderness Study Areas (WSAs). Corridor values varied substantially among classes of “unprotected” non-core land units, and land units of high connectivity value and priority represent diverse ownerships and existing levels of protections. We provide a ranking of IRAs and WSAs that should be prioritized for additional protection to maintain minimal human modification. Our results provide a coarse-scale assessment of connectivity priorities for maintaining a connected network of protected areas. PMID:27104683

Identifying Corridors among Large Protected Areas in the United States.

PubMed

Belote, R Travis; Dietz, Matthew S; McRae, Brad H; Theobald, David M; McClure, Meredith L; Irwin, G Hugh; McKinley, Peter S; Gage, Josh A; Aplet, Gregory H

2016-01-01

Conservation scientists emphasize the importance of maintaining a connected network of protected areas to prevent ecosystems and populations from becoming isolated, reduce the risk of extinction, and ultimately sustain biodiversity. Keeping protected areas connected in a network is increasingly recognized as a conservation priority in the current era of rapid climate change. Models that identify suitable linkages between core areas have been used to prioritize potentially important corridors for maintaining functional connectivity. Here, we identify the most "natural" (i.e., least human-modified) corridors between large protected areas in the contiguous Unites States. We aggregated results from multiple connectivity models to develop a composite map of corridors reflecting agreement of models run under different assumptions about how human modification of land may influence connectivity. To identify which land units are most important for sustaining structural connectivity, we used the composite map of corridors to evaluate connectivity priorities in two ways: (1) among land units outside of our pool of large core protected areas and (2) among units administratively protected as Inventoried Roadless (IRAs) or Wilderness Study Areas (WSAs). Corridor values varied substantially among classes of "unprotected" non-core land units, and land units of high connectivity value and priority represent diverse ownerships and existing levels of protections. We provide a ranking of IRAs and WSAs that should be prioritized for additional protection to maintain minimal human modification. Our results provide a coarse-scale assessment of connectivity priorities for maintaining a connected network of protected areas.

Spatial embedding of structural similarity in the cerebral cortex

PubMed Central

Song, H. Francis; Kennedy, Henry; Wang, Xiao-Jing

2014-01-01

Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization. PMID:25368200

Large-scale coupling dynamics of instructed reversal learning.

PubMed

Mohr, Holger; Wolfensteller, Uta; Ruge, Hannes

2018-02-15

The ability to rapidly learn from others by instruction is an important characteristic of human cognition. A recent study found that the rapid transfer from initial instructions to fluid behavior is supported by changes of functional connectivity between and within several large-scale brain networks, and particularly by the coupling of the dorsal attention network (DAN) with the cingulo-opercular network (CON). In the present study, we extended this approach to investigate how these brain networks interact when stimulus-response mappings are altered by novel instructions. We hypothesized that residual stimulus-response associations from initial practice might negatively impact the ability to implement novel instructions. Using functional imaging and large-scale connectivity analysis, we found that functional coupling between the CON and DAN was generally at a higher level during initial than reversal learning. Examining the learning-related connectivity dynamics between the CON and DAN in more detail by means of multivariate patterns analyses, we identified a specific subset of connections which showed a particularly high increase in connectivity during initial learning compared to reversal learning. This finding suggests that the CON-DAN connections can be separated into two functionally dissociable yet spatially intertwined subsystems supporting different aspects of short-term task automatization. Copyright © 2017 Elsevier Inc. All rights reserved.

Understanding large-scale, long-term larval connectivity patterns: The case of the Northern Line Islands in the Central Pacific Ocean

PubMed Central

Mari, Lorenzo; Bonaventura, Luca; Storto, Andrea; Melià, Paco; Gatto, Marino; Masina, Simona

2017-01-01

Protecting key hotspots of marine biodiversity is essential to maintain ecosystem services at large spatial scales. Protected areas serve not only as sources of propagules colonizing other habitats, but also as receptors, thus acting as protected nurseries. To quantify the geographical extent and the temporal persistence of ecological benefits resulting from protection, we investigate larval connectivity within a remote archipelago, characterized by a strong spatial gradient of human impact from pristine to heavily exploited: the Northern Line Islands (NLIs), including part of the Pacific Remote Islands Marine National Monument (PRI-MNM). Larvae are described as passive Lagrangian particles transported by oceanic currents obtained from a oceanographic reanalysis. We compare different simulation schemes and compute connectivity measures (larval exchange probabilities and minimum/average larval dispersal distances from target islands). To explore the role of PRI-MNM in protecting marine organisms with pelagic larval stages, we drive millions of individual-based simulations for various Pelagic Larval Durations (PLDs), in all release seasons, and over a two-decades time horizon (1991–2010). We find that connectivity in the NLIs is spatially asymmetric and displays significant intra- and inter-annual variations. The islands belonging to PRI-MNM act more as sinks than sources of larvae, and connectivity is higher during the winter-spring period. In multi-annual analyses, yearly averaged southward connectivity significantly and negatively correlates with climatological anomalies (El Niño). This points out a possible system fragility and susceptibility to global warming. Quantitative assessments of large-scale, long-term marine connectivity patterns help understand region-specific, ecologically relevant interactions between islands. This is fundamental for devising scientifically-based protection strategies, which must be space- and time-varying to cope with the challenges posed by the concurrent pressures of human exploitation and global climate change. PMID:28809937

Understanding large-scale, long-term larval connectivity patterns: The case of the Northern Line Islands in the Central Pacific Ocean.

PubMed

Mari, Lorenzo; Bonaventura, Luca; Storto, Andrea; Melià, Paco; Gatto, Marino; Masina, Simona; Casagrandi, Renato

2017-01-01

Protecting key hotspots of marine biodiversity is essential to maintain ecosystem services at large spatial scales. Protected areas serve not only as sources of propagules colonizing other habitats, but also as receptors, thus acting as protected nurseries. To quantify the geographical extent and the temporal persistence of ecological benefits resulting from protection, we investigate larval connectivity within a remote archipelago, characterized by a strong spatial gradient of human impact from pristine to heavily exploited: the Northern Line Islands (NLIs), including part of the Pacific Remote Islands Marine National Monument (PRI-MNM). Larvae are described as passive Lagrangian particles transported by oceanic currents obtained from a oceanographic reanalysis. We compare different simulation schemes and compute connectivity measures (larval exchange probabilities and minimum/average larval dispersal distances from target islands). To explore the role of PRI-MNM in protecting marine organisms with pelagic larval stages, we drive millions of individual-based simulations for various Pelagic Larval Durations (PLDs), in all release seasons, and over a two-decades time horizon (1991-2010). We find that connectivity in the NLIs is spatially asymmetric and displays significant intra- and inter-annual variations. The islands belonging to PRI-MNM act more as sinks than sources of larvae, and connectivity is higher during the winter-spring period. In multi-annual analyses, yearly averaged southward connectivity significantly and negatively correlates with climatological anomalies (El Niño). This points out a possible system fragility and susceptibility to global warming. Quantitative assessments of large-scale, long-term marine connectivity patterns help understand region-specific, ecologically relevant interactions between islands. This is fundamental for devising scientifically-based protection strategies, which must be space- and time-varying to cope with the challenges posed by the concurrent pressures of human exploitation and global climate change.

Stochastic analysis of epidemics on adaptive time varying networks

NASA Astrophysics Data System (ADS)

Kotnis, Bhushan; Kuri, Joy

2013-06-01

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

PubMed Central

Liu, Yaou; Duan, Yunyun; Li, Kuncheng

2015-01-01

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain. PMID:26539535

Connectivity-driven white matter scaling and folding in primate cerebral cortex

PubMed Central

Herculano-Houzel, Suzana; Mota, Bruno; Kaas, Jon H.

2010-01-01

Larger brains have an increasingly folded cerebral cortex whose white matter scales up faster than the gray matter. Here we analyze the cellular composition of the subcortical white matter in 11 primate species, including humans, and one Scandentia, and show that the mass of the white matter scales linearly across species with its number of nonneuronal cells, which is expected to be proportional to the total length of myelinated axons in the white matter. This result implies that the average axonal cross-section area in the white matter, a, does not scale significantly with the number of neurons in the gray matter, N. The surface area of the white matter increases with N0.87, not N1.0. Because this surface can be defined as the product of N, a, and the fraction n of cortical neurons connected through the white matter, we deduce that connectivity decreases in larger cerebral cortices as a slowly diminishing fraction of neurons, which varies with N−0.16, sends myelinated axons into the white matter. Decreased connectivity is compatible with previous suggestions that neurons in the cerebral cortex are connected as a small-world network and should slow down the increase in global conduction delay in cortices with larger numbers of neurons. Further, a simple model shows that connectivity and cortical folding are directly related across species. We offer a white matter-based mechanism to account for increased cortical folding across species, which we propose to be driven by connectivity-related tension in the white matter, pulling down on the gray matter. PMID:20956290

Functional connectivity in the resting brain as biological correlate of the Affective Neuroscience Personality Scales.

PubMed

Deris, Nadja; Montag, Christian; Reuter, Martin; Weber, Bernd; Markett, Sebastian

2017-02-15

According to Jaak Panksepp's Affective Neuroscience Theory and the derived self-report measure, the Affective Neuroscience Personality Scales (ANPS), differences in the responsiveness of primary emotional systems form the basis of human personality. In order to investigate neuronal correlates of personality, the underlying neuronal circuits of the primary emotional systems were analyzed in the present fMRI-study by associating the ANPS to functional connectivity in the resting brain. N=120 healthy participants were invited for the present study. The results were reinvestigated in an independent, smaller sample of N=52 participants. A seed-based whole brain approach was conducted with seed-regions bilaterally in the basolateral and superficial amygdalae. The selection of seed-regions was based on meta-analytic data on affective processing and the Juelich histological atlas. Multiple regression analyses on the functional connectivity maps revealed associations with the SADNESS-scale in both samples. Functional resting-state connectivity between the left basolateral amygdala and a cluster in the postcentral gyrus, and between the right basolateral amygdala and clusters in the superior parietal lobe and subgyral in the parietal lobe was associated with SADNESS. No other ANPS-scale revealed replicable results. The present findings give first insights into the neuronal basis of the SADNESS-scale of the ANPS and support the idea of underlying neuronal circuits. In combination with previous research on genetic associations of the ANPS functional resting-state connectivity is discussed as a possible endophenotype of personality. Copyright © 2016 Elsevier Inc. All rights reserved.

Cerebral cartography and connectomics

PubMed Central

Sporns, Olaf

2015-01-01

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. PMID:25823870

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Comparison of Marginal Bone Loss Between Implants with Internal and External Connections: A Systematic Review.

PubMed

Palacios-Garzón, Natalia; Mauri-Obradors, Elisabeth; Roselló-LLabrés, Xavier; Estrugo-Devesa, Albert; Jané-Salas, Enric; López-López, José

The objective of this systematic review was to compare the loss of marginal bone between implants with internal and external connections by analyzing results reported in studies published after 2010. A literature search in MEDLINE with the keywords "dental implant connections, external internal implant connection, bone loss implant designs, internal and external connection implant studies in humans" was conducted. Clinical trials on human beings, comparing both connections and published in English, from 2010 to 2016 were selected. Their methodologic quality was assessed using the Jadad scale. From the initial search, 415 articles were obtained; 32 were chosen as potentially relevant based on their titles and abstracts. Among them, only 10 finally met the inclusion criteria. A total of 1,523 patients with 3,965 implants were analyzed. Six out of 10 studies observed that internal connections showed significantly less bone loss compared with external connections. The remaining four articles did not find statistically significant differences between the two connections. According to this systematic review and considering its limitation due to the degree of heterogeneity between the included studies, both internal and external connections present high survival rates. To assess whether marginal bone loss differs significantly between the two connections, more homogenous clinical studies are needed with identical implant characteristics, larger samples, and longer follow-up periods. Studies included in this review and characterized by long-term follow-ups showed that the external connection is a reliable connection on a long-term basis.

Cerebral cartography and connectomics.

PubMed

Sporns, Olaf

2015-05-19

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Decoding Lifespan Changes of the Human Brain Using Resting-State Functional Connectivity MRI

PubMed Central

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8–79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' “brain ages” from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI. PMID:22952990

Decoding lifespan changes of the human brain using resting-state functional connectivity MRI.

PubMed

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8-79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' "brain ages" from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI.

Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks.

PubMed

How, Javier J; Navlakha, Saket

2018-06-12

Biological networks have long been known to be modular, containing sets of nodes that are highly connected internally. Less emphasis, however, has been placed on understanding how intermodule connections are distributed within a network. Here, we borrow ideas from engineered circuit design and study Rentian scaling, which states that the number of external connections between nodes in different modules is related to the number of nodes inside the modules by a power-law relationship. We tested this property in a broad class of molecular networks, including protein interaction networks for six species and gene regulatory networks for 41 human and 25 mouse cell types. Using evolutionarily defined modules corresponding to known biological processes in the cell, we found that all networks displayed Rentian scaling with a broad range of exponents. We also found evidence for Rentian scaling in functional modules in the Caenorhabditis elegans neural network, but, interestingly, not in three different social networks, suggesting that this property does not inevitably emerge. To understand how such scaling may have arisen evolutionarily, we derived a new graph model that can generate Rentian networks given a target Rent exponent and a module decomposition as inputs. Overall, our work uncovers a new principle shared by engineered circuits and biological networks.

Evoked effective connectivity of the human neocortex.

PubMed

Entz, László; Tóth, Emília; Keller, Corey J; Bickel, Stephan; Groppe, David M; Fabó, Dániel; Kozák, Lajos R; Erőss, Loránd; Ulbert, István; Mehta, Ashesh D

2014-12-01

The role of cortical connectivity in brain function and pathology is increasingly being recognized. While in vivo magnetic resonance imaging studies have provided important insights into anatomical and functional connectivity, these methodologies are limited in their ability to detect electrophysiological activity and the causal relationships that underlie effective connectivity. Here, we describe results of cortico-cortical evoked potential (CCEP) mapping using single pulse electrical stimulation in 25 patients undergoing seizure monitoring with subdural electrode arrays. Mapping was performed by stimulating adjacent electrode pairs and recording CCEPs from the remainder of the electrode array. CCEPs reliably revealed functional networks and showed an inverse relationship to distance between sites. Coregistration to Brodmann areas (BA) permitted group analysis. Connections were frequently directional with 43% of early responses and 50% of late responses of connections reflecting relative dominance of incoming or outgoing connections. The most consistent connections were seen as outgoing from motor cortex, BA6-BA9, somatosensory (SS) cortex, anterior cingulate cortex, and Broca's area. Network topology revealed motor, SS, and premotor cortices along with BA9 and BA10 and language areas to serve as hubs for cortical connections. BA20 and BA39 demonstrated the most consistent dominance of outdegree connections, while BA5, BA7, auditory cortex, and anterior cingulum demonstrated relatively greater indegree. This multicenter, large-scale, directional study of local and long-range cortical connectivity using direct recordings from awake, humans will aid the interpretation of noninvasive functional connectome studies. © 2014 Wiley Periodicals, Inc.

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

Dynamics of Intersubject Brain Networks during Anxious Anticipation

PubMed Central

Najafi, Mahshid; Kinnison, Joshua; Pessoa, Luiz

2017-01-01

How do large-scale brain networks reorganize during the waxing and waning of anxious anticipation? Here, threat was dynamically modulated during human functional MRI as two circles slowly meandered on the screen; if they touched, an unpleasant shock was delivered. We employed intersubject correlation analysis, which allowed the investigation of network-level functional connectivity across brains, and sought to determine how network connectivity changed during periods of approach (circles moving closer) and periods of retreat (circles moving apart). Analysis of positive connection weights revealed that dynamic threat altered connectivity within and between the salience, executive, and task-negative networks. For example, dynamic functional connectivity increased within the salience network during approach and decreased during retreat. The opposite pattern was found for the functional connectivity between the salience and task-negative networks: decreases during approach and increases during approach. Functional connections between subcortical regions and the salience network also changed dynamically during approach and retreat periods. Subcortical regions exhibiting such changes included the putative periaqueductal gray, putative habenula, and putative bed nucleus of the stria terminalis. Additional analysis of negative functional connections revealed dynamic changes, too. For example, negative weights within the salience network decreased during approach and increased during retreat, opposite what was found for positive weights. Together, our findings unraveled dynamic features of functional connectivity of large-scale networks and subcortical regions across participants while threat levels varied continuously, and demonstrate the potential of characterizing emotional processing at the level of dynamic networks. PMID:29209184

Intrahemispheric theta rhythm desynchronization impairs working memory.

PubMed

Alekseichuk, Ivan; Pabel, Stefanie Corinna; Antal, Andrea; Paulus, Walter

2017-01-01

There is a growing interest in large-scale connectivity as one of the crucial factors in working memory. Correlative evidence has revealed the anatomical and electrophysiological players in the working memory network, but understanding of the effective role of their connectivity remains elusive. In this double-blind, placebo-controlled study we aimed to identify the causal role of theta phase connectivity in visual-spatial working memory. The frontoparietal network was over- or de-synchronized in the anterior-posterior direction by multi-electrode, 6 Hz transcranial alternating current stimulation (tACS). A decrease in memory performance and increase in reaction time was caused by frontoparietal intrahemispheric desynchronization. According to the diffusion drift model, this originated in a lower signal-to-noise ratio, known as the drift rate index, in the memory system. The EEG analysis revealed a corresponding decrease in phase connectivity between prefrontal and parietal areas after tACS-driven desynchronization. The over-synchronization did not result in any changes in either the behavioral or electrophysiological levels in healthy participants. Taken together, we demonstrate the feasibility of manipulating multi-site large-scale networks in humans, and the disruptive effect of frontoparietal desynchronization on theta phase connectivity and visual-spatial working memory.

A graph-theory framework for evaluating landscape connectivity and conservation planning.

PubMed

Minor, Emily S; Urban, Dean L

2008-04-01

Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.

Intrinsic Amygdala-Cortical Functional Connectivity Predicts Social Network Size in Humans

PubMed Central

Bickart, Kevin C.; Hollenbeck, Mark C.; Barrett, Lisa Feldman; Dickerson, Bradford C.

2012-01-01

Using resting-state functional MRI data from two independent samples of healthy adults, we parsed the amygdala’s intrinsic connectivity into three partially-distinct large-scale networks that strongly resemble the known anatomical organization of amygdala connectivity in rodents and monkeys. Moreover, in a third independent sample, we discovered that people who fostered and maintained larger and more complex social networks not only had larger amygdala volumes, but also amygdalae with stronger intrinsic connectivity within two of these networks, one putatively subserving perceptual abilities and one subserving affiliative behaviors. Our findings were anatomically specific to amygdalar circuitry in that individual differences in social network size and complexity could not be explained by the strength of intrinsic connectivity between nodes within two networks that do not typically involve the amygdala (i.e., the mentalizing and mirror networks), and were behaviorally specific in that amygdala connectivity did not correlate with other self-report measures of sociality. PMID:23077058

Zipf's law from scale-free geometry.

PubMed

Lin, Henry W; Loeb, Abraham

2016-03-01

The spatial distribution of people exhibits clustering across a wide range of scales, from household (∼10(-2) km) to continental (∼10(4) km) scales. Empirical data indicate simple power-law scalings for the size distribution of cities (known as Zipf's law) and the population density fluctuations as a function of scale. Using techniques from random field theory and statistical physics, we show that these power laws are fundamentally a consequence of the scale-free spatial clustering of human populations and the fact that humans inhabit a two-dimensional surface. In this sense, the symmetries of scale invariance in two spatial dimensions are intimately connected to urban sociology. We test our theory by empirically measuring the power spectrum of population density fluctuations and show that the logarithmic slope α=2.04 ± 0.09, in excellent agreement with our theoretical prediction α=2. The model enables the analytic computation of many new predictions by importing the mathematical formalism of random fields.

Critical dynamics on a large human Open Connectome network

NASA Astrophysics Data System (ADS)

Ódor, Géza

2016-12-01

Extended numerical simulations of threshold models have been performed on a human brain network with N =836 733 connected nodes available from the Open Connectome Project. While in the case of simple threshold models a sharp discontinuous phase transition without any critical dynamics arises, variable threshold models exhibit extended power-law scaling regions. This is attributed to fact that Griffiths effects, stemming from the topological or interaction heterogeneity of the network, can become relevant if the input sensitivity of nodes is equalized. I have studied the effects of link directness, as well as the consequence of inhibitory connections. Nonuniversal power-law avalanche size and time distributions have been found with exponents agreeing with the values obtained in electrode experiments of the human brain. The dynamical critical region occurs in an extended control parameter space without the assumption of self-organized criticality.

Students' Developing Understanding of Water in Environmental Systems

ERIC Educational Resources Information Center

Covitt, Beth A.; Gunckel, Kristin L.; Anderson, Charles W.

2009-01-01

The authors developed a framework of empirically grounded curricular goals for water-science literacy and documented the challenges that students face in achieving these goals. Water-related environmental science literacy requires an understanding of connected natural and human-engineered systems at multiple scales ranging from atomic-molecular…

The social connectivity of urban rivers

NASA Astrophysics Data System (ADS)

Kondolf, G. Mathias; Pinto, Pedro J.

2017-01-01

By social connectivity we refer to the communication and movement of people, goods, ideas, and culture along and across rivers, recognizing longitudinal, lateral, and vertical connectivity, much as has been described for other rivers for hydrology and ecology. We focus on rivers as they pass through cities, and the relationships between these rivers and city dwellers. Historically, the most important longitudinal connectivity function of rivers was their role as major transport routes and the simplification of formerly complex, irregular banks and beds, into straight, uniform shipping channels has resulted in a loss of lateral and vertical connectivity, notably the quotidian uses such as fishing, washing clothes, water supply, swimming and other recreation. The scale of the river itself, and its scale in comparison to the scale of the city, largely determine the river's social function and the degree to which it influences city form. River width affects the perception of 'closeness' of the other bank, ease of bridging the river, influence of the river on the city's street pattern, and type of waterfront uses that occur. Up to 15 m wide, people can converse, whereas across rivers 50 to 200 m wide, people are not recognizable but still clearly visible, instilling the banks with a 'lively' atmosphere. At widths over 200 m, people blur, yet moving vehicles and trees branches shaking in wind may still provide some dynamic elements to an otherwise static landscape composed of building facades. In exceptionally wide rivers, the city on the opposite bank is little more than a skyline, which often becomes a signature and symbol of regional identity. In contemplating how people use rivers, we can define a range of human activities in relation to height above the water (i.e., instream to banktop), a vertical dimension of human connectivity with rivers. Many uses occur on the top of the bank, such as quiet contemplation, walking, or cycling along a riverside trail, while others depend on contact with the water itself, such as wading, diving, and canoeing (which presupposes adequate water quality). Many of these relationships are illustrated by the challenge of reconnecting Cairo with the Nile.

Atomic scale chemical tomography of human bone

NASA Astrophysics Data System (ADS)

Langelier, Brian; Wang, Xiaoyue; Grandfield, Kathryn

2017-01-01

Human bone is a complex hierarchical material. Understanding bone structure and its corresponding composition at the nanometer scale is critical for elucidating mechanisms of biomineralization under healthy and pathological states. However, the three-dimensional structure and chemical nature of bone remains largely unexplored at the nanometer scale due to the challenges associated with characterizing both the structural and chemical integrity of bone simultaneously. Here, we use correlative transmission electron microscopy and atom probe tomography for the first time, to our knowledge, to reveal structures in human bone at the atomic level. This approach provides an overlaying chemical map of the organic and inorganic constituents of bone on its structure. This first use of atom probe tomography on human bone reveals local gradients, trace element detection of Mg, and the co-localization of Na with the inorganic-organic interface of bone mineral and collagen fibrils, suggesting the important role of Na-rich organics in the structural connection between mineral and collagen. Our findings provide the first insights into the hierarchical organization and chemical heterogeneity in human bone in three-dimensions at its smallest length scale - the atomic level. We demonstrate that atom probe tomography shows potential for new insights in biomineralization research on bone.

Cumulative effects of wetland drainage on watershed-scale subsurface hydrologic connectivity

NASA Astrophysics Data System (ADS)

Creed, I. F.; Ameli, A.

2017-12-01

Subsurface hydrologic connectivity influences hydrological, biogeochemical and ecological responses within watersheds. However, information about the location, duration, and frequency of subsurface hydrologic connections within wetlandscapes and between wetlandscapes and streams is often not available. This leads to a lack of understanding of the potential effects of human modifications of the landscape, including wetland degradation and removal, on subsurface hydrologic connectivity and therefore watershed responses. Herein, we develop a computationally efficient, physically-based subsurface hydrologic connectivity model that explicitly characterizes the effects of wetland degradation and removal on the distribution, length, and timing of subsurface hydrologic connectivity within a wetland-dominated watershed in the Prairie Pothole Region of North America. We run the model using a time series of wetland inventories that reflect incremental wetland loss from 1962, to 1993, and to 2009. We also consider a potential future wetland loss scenario based on removal of all wetlands outside of the protected areas of the watershed. Our findings suggest that wetland degradation and removal over this period increased the average length, transit time, and frequency of subsurface hydrologic connections to the regional surface waters, resulting in decreased baseflow in the major river network. This study provides important insights that can be used by wetland managers and policy makers to support watershed-scale wetland protection and restoration plans to improve water resource management.

Hydrologic Connectivity: a Framework to Understand Threshold Behaviour in Semi-Arid Landscapes.

NASA Astrophysics Data System (ADS)

Saco, Patricia; Rodriguez, Jose; Keesstra, Saskia; Moreno-de las Heras, Mariano; Sandi, Steven; Baartman, Jantiene; Cerdà, Artemi

2017-04-01

Anthropogenic activities and climate change are imposing an unprecedented pressure on arid and semi-arid ecosystems, where shortage of water can trigger shifts in landscapes' structures and function leading to degradation and desertification. Hydrological connectivity is a useful framework for understanding water redistribution and scaling issues associated to runoff and sediment production, since human and/or natural disturbances alter the surface water availability and pathways increasing/decreasing connectivity. In this presentation, we illustrate the use of the connectivity framework for several examples of dryland systems that are analysed at a variety of spatial and temporal scales. In doing so, we draw particular attention to the analysis of co-evolution of system structures and function, and how they drive threshold behaviour leading to desertification and degradation. We first analyse the case of semi-arid rangelands, where feedbacks between decline in vegetation density and landscape erosion reinforces degradation processes driven by changes in connectivity until a threshold is crossed above which the return to a functional system is unlikely. We then focus on semi-arid wetlands, where decreases in water volumes promotes dryland vegetation encroachment that changes drainage conditions and connectivity potentially reinforcing redistribution of flow paths to other wetland areas. The examples presented highlight the need to incorporate a co-evolutionary framework for the analysis of changing connectivity patterns and the emergence of thresholds in arid and semi-arid systems.

River Networks and Human Activities: Global Fractal Analysis Using Nightlight Data

NASA Astrophysics Data System (ADS)

McCurley, K. 4553; Fang, Y.; Ceola, S.; Paik, K.; McGrath, G. S.; Montanari, A.; Rao, P. S.; Jawitz, J. W.

2016-12-01

River networks hold an important historical role in affecting human population distribution. In this study, we link the geomorphological structure of river networks to the pattern of human activities at a global scale. We use nightlights as a valuable proxy for the presence of human settlements and economic activity, and we employ HydroSHEDS as the main data source on river networks. We test the hypotheses that, analogous to Horton's laws, human activities (magnitude of nightlights) also show scaling relationship with stream order, and that the intensity of human activities decrease as the distance from the basin outlet increase. Our results demonstrate that the distribution of human activities shows a fractal structure, with power-law scaling between human activities and stream order. This relationship is robust among global river basins. Human activities are more concentrated in larger order basins, but show large variation in equivalent order basins, with higher population density emergent in the basins connected with high-order rivers. For all global river basins longer than 400km, the average intensity of human activities decrease as the distance to the outlets increases, albeit with signatures of large cities at varied distances. The power spectrum of human width (area) function is found to exhibit power law scaling, with a scaling exponent that indicates enrichment of low frequency variation. The universal fractal structure of human activities may reflect an optimum arrangement for humans in river basins to better utilize the water resources, ecological assets, and geographic advantages. The generalized patterns of human activities could be applied to better understand hydrologic and biogeochemical responses in river basins, and to advance catchment management.

Assessing sustainable biophysical human-nature connectedness at regional scales

NASA Astrophysics Data System (ADS)

Dorninger, Christian; Abson, David J.; Fischer, Joern; von Wehrden, Henrik

2017-05-01

Humans are biophysically connected to the biosphere through the flows of materials and energy appropriated from ecosystems. While this connection is fundamental for human well-being, many modern societies have—for better or worse—disconnected themselves from the natural productivity of their immediate regional environment. In this paper, we conceptualize the biophysical human-nature connectedness of land use systems at regional scales. We distinguish two mechanisms by which primordial connectedness of people to regional ecosystems has been circumvented via the use of external inputs. First, ‘biospheric disconnection’ refers to people drawing on non-renewable minerals from outside the biosphere (e.g. fossils, metals and other minerals). Second, ‘spatial disconnection’ arises from the imports and exports of biomass products and imported mineral resources used to extract and process ecological goods. Both mechanisms allow for greater regional resource use than would be possible otherwise, but both pose challenges for sustainability, for example, through waste generation, depletion of non-renewable resources and environmental burden shifting to distant regions. In contrast, biophysically reconnected land use systems may provide renewed opportunities for inhabitants to develop an awareness of their impacts and fundamental reliance on ecosystems. To better understand the causes, consequences, and possible remedies related to biophysical disconnectedness, new quantitative methods to assess the extent of regional biophysical human-nature connectedness are needed. To this end, we propose a new methodological framework that can be applied to assess biophysical human-nature connectedness in any region of the world.

Unravelling connections between river flow and large-scale climate: experiences from Europe

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Kingston, D. G.; Lavers, D.; Stagge, J. H.; Tallaksen, L. M.

2016-12-01

The United Nations has identified better knowledge of large-scale water cycle processes as essential for socio-economic development and global water-food-energy security. In this context, and given the ever-growing concerns about climate change/ variability and human impacts on hydrology, there is an urgent research need: (a) to quantify space-time variability in regional river flow, and (b) to improve hydroclimatological understanding of climate-flow connections as a basis for identifying current and future water-related issues. In this paper, we draw together studies undertaken at the pan-European scale: (1) to evaluate current methods for assessing space-time dynamics for different streamflow metrics (annual regimes, low flows and high flows) and for linking flow variability to atmospheric drivers (circulation indices, air-masses, gridded climate fields and vapour flux); and (2) to propose a plan for future research connecting streamflow and the atmospheric conditions in Europe and elsewhere. We believe this research makes a useful, unique contribution to the literature through a systematic inter-comparison of different streamflow metrics and atmospheric descriptors. In our findings, we highlight the need to consider appropriate atmospheric descriptors (dependent on the target flow metric and region of interest) and to develop analytical techniques that best characterise connections in the ocean-atmosphere-land surface process chain. We call for the need to consider not only atmospheric interactions, but also the role of the river basin-scale terrestrial hydrological processes in modifying the climate signal response of river flows.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed

Klapa, Maria I; Tsafou, Kalliopi; Theodoridis, Evangelos; Tsakalidis, Athanasios; Moschonas, Nicholas K

2013-10-02

Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. First, we defined the UniProtKB manually reviewed human "complete" proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human "complete" proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms.

Fine-scale genetic response to landscape change in a gliding mammal.

PubMed

Goldingay, Ross L; Harrisson, Katherine A; Taylor, Andrea C; Ball, Tina M; Sharpe, David J; Taylor, Brendan D

2013-01-01

Understanding how populations respond to habitat loss is central to conserving biodiversity. Population genetic approaches enable the identification of the symptoms of population disruption in advance of population collapse. However, the spatio-temporal scales at which population disruption occurs are still too poorly known to effectively conserve biodiversity in the face of human-induced landscape change. We employed microsatellite analysis to examine genetic structure and diversity over small spatial (mostly 1-50 km) and temporal scales (20-50 years) in the squirrel glider (Petaurus norfolcensis), a gliding mammal that is commonly subjected to a loss of habitat connectivity. We identified genetically differentiated local populations over distances as little as 3 km and within 30 years of landscape change. Genetically isolated local populations experienced the loss of genetic diversity, and significantly increased mean relatedness, which suggests increased inbreeding. Where tree cover remained, genetic differentiation was less evident. This pattern was repeated in two landscapes located 750 km apart. These results lend support to other recent studies that suggest the loss of habitat connectivity can produce fine-scale population genetic change in a range of taxa. This gives rise to the prediction that many other vertebrates will experience similar genetic changes. Our results suggest the future collapse of local populations of this gliding mammal is likely unless habitat connectivity is maintained or restored. Landscape management must occur on a fine-scale to avert the erosion of biodiversity.

Evolution of the ubiquitin-activating enzyme Uba1 (E1)

NASA Astrophysics Data System (ADS)

Allan, Douglas C.; Phillips, J. C.

2017-10-01

Ubiquitin tags diseased proteins and initiates an enzyme conjugation cascade, which has three stages. The first-stage enzyme Uba1 (E1) has evolved only modestly from slime mold to humans, and is > 14 times larger than Ub. Here we use critical point thermodynamic scaling theory to connect Uba1 (E1) evolution from yeast and slime mold to fruit flies and humans to subtle changes in its amino acid sequences.

Linked Sex Differences in Cognition and Functional Connectivity in Youth.

PubMed

Satterthwaite, Theodore D; Wolf, Daniel H; Roalf, David R; Ruparel, Kosha; Erus, Guray; Vandekar, Simon; Gennatas, Efstathios D; Elliott, Mark A; Smith, Alex; Hakonarson, Hakon; Verma, Ragini; Davatzikos, Christos; Gur, Raquel E; Gur, Ruben C

2015-09-01

Sex differences in human cognition are marked, but little is known regarding their neural origins. Here, in a sample of 674 human participants ages 9-22, we demonstrate that sex differences in cognitive profiles are related to multivariate patterns of resting-state functional connectivity MRI (rsfc-MRI). Males outperformed females on motor and spatial cognitive tasks; females were faster in tasks of emotion identification and nonverbal reasoning. Sex differences were also prominent in the rsfc-MRI data at multiple scales of analysis, with males displaying more between-module connectivity, while females demonstrated more within-module connectivity. Multivariate pattern analysis using support vector machines classified subject sex on the basis of their cognitive profile with 63% accuracy (P < 0.001), but was more accurate using functional connectivity data (71% accuracy; P < 0.001). Moreover, the degree to which a given participant's cognitive profile was "male" or "female" was significantly related to the masculinity or femininity of their pattern of brain connectivity (P = 2.3 × 10(-7)). This relationship was present even when considering males and female separately. Taken together, these results demonstrate for the first time that sex differences in patterns of cognition are in part represented on a neural level through divergent patterns of brain connectivity. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Large-scale topology and the default mode network in the mouse connectome

PubMed Central

Stafford, James M.; Jarrett, Benjamin R.; Miranda-Dominguez, Oscar; Mills, Brian D.; Cain, Nicholas; Mihalas, Stefan; Lahvis, Garet P.; Lattal, K. Matthew; Mitchell, Suzanne H.; David, Stephen V.; Fryer, John D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans. PMID:25512496

EEG functional connectivity is partially predicted by underlying white matter connectivity

PubMed Central

Chu, CJ; Tanaka, N; Diaz, J; Edlow, BL; Wu, O; Hämäläinen, M; Stufflebeam, S; Cash, SS; Kramer, MA.

2015-01-01

Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales. PMID:25534110

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure.

PubMed

Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

2008-11-07

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.

Cortical parcellation based on structural connectivity: A case for generative models.

PubMed

Tittgemeyer, Marc; Rigoux, Lionel; Knösche, Thomas R

2018-06-01

One of the major challenges in systems neuroscience is to identify brain networks and unravel their significance for brain function -this has led to the concept of the 'connectome'. Connectomes are currently extensively studied in large-scale international efforts at multiple scales, and follow different definitions with respect to their connections as well as their elements. Perhaps the most promising avenue for defining the elements of connectomes originates from the notion that individual brain areas maintain distinct (long-range) connection profiles. These connectivity patterns determine the areas' functional properties and also allow for their anatomical delineation and mapping. This rationale has motivated the concept of connectivity-based cortex parcellation. In the past ten years, non-invasive mapping of human brain connectivity has led to immense advances in the development of parcellation techniques and their applications. Unfortunately, many of these approaches primarily aim for confirmation of well-known, existing architectonic maps and, to that end, unsuitably incorporate prior knowledge and frequently build on circular argumentation. Often, current approaches also tend to disregard the specific apertures of connectivity measurements, as well as the anatomical specificities of cortical areas, such as spatial compactness, regional heterogeneity, inter-subject variability, the multi-scaling nature of connectivity information, and potential hierarchical organisation. From a methodological perspective, however, a useful framework that regards all of these aspects in an unbiased way is technically demanding. In this commentary, we first outline the concept of connectivity-based cortex parcellation and discuss its prospects and limitations in particular with respect to structural connectivity. To improve reliability and efficiency, we then strongly advocate for connectivity-based cortex parcellation as a modelling approach; that is, an approximation of the data based on (model) parameter inference. As such, a parcellation algorithm can be formally tested for robustness -the precision of its predictions can be quantified and statistics about potential generalization of the results can be derived. Such a framework also allows the question of model constraints to be reformulated in terms of hypothesis testing through model selection and offers a formative way to integrate anatomical knowledge in terms of prior distributions. Copyright © 2018 Elsevier Inc. All rights reserved.

Human impacts on morphodynamic thresholds in estuarine systems

NASA Astrophysics Data System (ADS)

Wang, Z. B.; Van Maren, D. S.; Ding, P. X.; Yang, S. L.; Van Prooijen, B. C.; De Vet, P. L. M.; Winterwerp, J. C.; De Vriend, H. J.; Stive, M. J. F.; He, Q.

2015-12-01

Many estuaries worldwide are modified, primarily driven by economic gain or safety. These works, combined with global climate changes heavily influence the morphologic development of estuaries. In this paper, we analyze the impact of human activities on the morphodynamic developments of the Scheldt Estuary and the Wadden Sea basins in the Netherlands and the Yangtze Estuary in China at various spatial scales, and identify mechanisms responsible for their change. Human activities in these systems include engineering works and dredging activities for improving and maintaining the navigation channels, engineering works for flood protection, and shoreline management activities such as land reclamations. The Yangtze Estuary is influenced by human activities in the upstream river basin as well, especially through the construction of many dams. The tidal basins in the Netherlands are also influenced by human activities along the adjacent coasts. Furthermore, all these systems are influenced by global changes through (accelerated) sea-level rise and changing weather patterns. We show that the cumulative impacts of these human activities and global changes may lead to exceeding thresholds beyond which the morphology of the tidal basins significantly changes, and loses its natural characteristics. A threshold is called tipping point when the changes are even irreversible. Knowledge on such thresholds or tipping points is important for the sustainable management of these systems. We have identified and quantified various examples of such thresholds and/or tipping points for the morphodynamic developments at various spatial and temporal scales. At the largest scale (mega-scale) we consider the sediment budget of a tidal basin as a whole. A smaller scale (macro-scale) is the development of channel structures in an estuary, especially the development of two competing channels. At the smallest scale (meso-scale) we analyze the developments of tidal flats and the connecting channels.

Beyond Knee-Jerk Environmental Thinking: Teaching Geographic Perspectives on Conservation, Preservation and the Hetch Hetchy Valley Controversy

ERIC Educational Resources Information Center

Moseley, William G.

2009-01-01

Attention to scale, use of space and connections between places and regions are general, yet distinctive, geographical concepts that may be employed in introductory level human-environment geography courses to distinguish them from other environmental studies offerings. This article demonstrates how attention to the aforementioned concepts…

“Skill of Generalized Additive Model to Detect PM2.5 Health Signal in the Presence of Confounding Variables”

EPA Science Inventory

Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and...

Connecting marine ecosystem services to human well-being: insights from participatory well-being assessment in Kenya.

PubMed

Abunge, Caroline; Coulthard, Sarah; Daw, Tim M

2013-12-01

The linkage between ecosystems and human well-being is a focus of the conceptualization of "ecosystem services" as promoted by the Millennium Ecosystem Assessment. However, the actual nature of connections between ecosystems and the well-being of individuals remains complex and poorly understood. We conducted a series of qualitative focus groups with five different stakeholder groups connected to a small-scale Kenyan coastal fishery to understand (1) how well-being is understood within the community, and what is important for well-being, (2) how people's well-being has been affected by changes over the recent past, and (3) people's hopes and aspirations for their future fishery. Our results show that people conceive well-being in a diversity of ways, but that these can clearly map onto the MA framework. In particular, our research unpacks the "freedoms and choices" element of the framework and argues for greater recognition of these aspects of well-being in fisheries management in Kenya through, for example, more participatory governance processes.

Implications of Nubian-Like Core Reduction Systems in Southern Africa for the Identification of Early Modern Human Dispersals

PubMed Central

Phillips, Natasha

2015-01-01

Lithic technologies have been used to trace dispersals of early human populations within and beyond Africa. Convergence in lithic systems has the potential to confound such interpretations, implying connections between unrelated groups. Due to their reductive nature, stone artefacts are unusually prone to this chance appearance of similar forms in unrelated populations. Here we present data from the South African Middle Stone Age sites Uitpanskraal 7 and Mertenhof suggesting that Nubian core reduction systems associated with Late Pleistocene populations in North Africa and potentially with early human migrations out of Africa in MIS 5 also occur in southern Africa during early MIS 3 and with no clear connection to the North African occurrence. The timing and spatial distribution of their appearance in southern and northern Africa implies technological convergence, rather than diffusion or dispersal. While lithic technologies can be a critical guide to human population flux, their utility in tracing early human dispersals at large spatial and temporal scales with stone artefact types remains questionable. PMID:26125972

Ontology-based approach for in vivo human connectomics: the medial Brodmann area 6 case study

PubMed Central

Moreau, Tristan; Gibaud, Bernard

2015-01-01

Different non-invasive neuroimaging modalities and multi-level analysis of human connectomics datasets yield a great amount of heterogeneous data which are hard to integrate into an unified representation. Biomedical ontologies can provide a suitable integrative framework for domain knowledge as well as a tool to facilitate information retrieval, data sharing and data comparisons across scales, modalities and species. Especially, it is urgently needed to fill the gap between neurobiology and in vivo human connectomics in order to better take into account the reality highlighted in Magnetic Resonance Imaging (MRI) and relate it to existing brain knowledge. The aim of this study was to create a neuroanatomical ontology, called “Human Connectomics Ontology” (HCO), in order to represent macroscopic gray matter regions connected with fiber bundles assessed by diffusion tractography and to annotate MRI connectomics datasets acquired in the living human brain. First a neuroanatomical “view” called NEURO-DL-FMA was extracted from the reference ontology Foundational Model of Anatomy (FMA) in order to construct a gross anatomy ontology of the brain. HCO extends NEURO-DL-FMA by introducing entities (such as “MR_Node” and “MR_Route”) and object properties (such as “tracto_connects”) pertaining to MR connectivity. The Web Ontology Language Description Logics (OWL DL) formalism was used in order to enable reasoning with common reasoning engines. Moreover, an experimental work was achieved in order to demonstrate how the HCO could be effectively used to address complex queries concerning in vivo MRI connectomics datasets. Indeed, neuroimaging datasets of five healthy subjects were annotated with terms of the HCO and a multi-level analysis of the connectivity patterns assessed by diffusion tractography of the right medial Brodmann Area 6 was achieved using a set of queries. This approach can facilitate comparison of data across scales, modalities and species. PMID:25914640

Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit/hyperactivity disorder: A rich club organization study

PubMed Central

Ray, Siddharth; Miller, Meghan; Karalunas, Sarah; Robertson, C.J.; Grayson, David; Cary, Paul; Hawkey, Elizabeth; Painter, Julia G.; Kriz, Daniel; Fombonne, Eric; Nigg, Joel T.; Fair, Damien A.

2015-01-01

Attention deficit hyperactive disorder (ADHD) and Autism spectrum disorders (ASD) are two of the most common and vexing neurodevelopmental disorders among children. Although the two disorders share many behavioral and neuropsychological characteristics, most MRI studies examine only one of the disorders at a time. Using graph theory combined with structural and functional connectivity, we examined the large-scale network organization among three groups of children: a group with ADHD (8-12 years, n = 20), a group with ASD (7-13 years, n = 16), and typically developing controls (TD) (8-12 years, n = 20). We apply the concept of the rich-club organization, whereby central, highly connected hub regions are also highly connected to themselves. We examine the brain into two different network domains: (1) inside a rich-club network phenomena, and (2) outside a rich-club network phenomena. ASD and ADHD populations had markedly different patterns of rich club and non rich-club connections in both functional and structural data. The ASD group exhibited higher connectivity in structural and functional networks but only inside the rich-club networks. These findings were replicated using the autism brain imaging data exchange (ABIDE) dataset with ASD (n = 85) and TD (n = 101). The ADHD group exhibited a lower generalized fractional anisotropy (GFA) and functional connectivity inside the rich-club networks, but a higher number of axonal fibers and correlation coefficient values outside the rich-club. Despite some shared biological features and frequent comorbity, these data suggest ADHD and ASD exhibit distinct large-scale connectivity patterns in middle childhood. PMID:25116862

The Rich Club of the C. elegans Neuronal Connectome

PubMed Central

Vértes, Petra E.; Ahnert, Sebastian E.; Schafer, William R.; Bullmore, Edward T.

2013-01-01

There is increasing interest in topological analysis of brain networks as complex systems, with researchers often using neuroimaging to represent the large-scale organization of nervous systems without precise cellular resolution. Here we used graph theory to investigate the neuronal connectome of the nematode worm Caenorhabditis elegans, which is defined anatomically at a cellular scale as 2287 synaptic connections between 279 neurons. We identified a small number of highly connected neurons as a rich club (N = 11) interconnected with high efficiency and high connection distance. Rich club neurons comprise almost exclusively the interneurons of the locomotor circuits, with known functional importance for coordinated movement. The rich club neurons are connector hubs, with high betweenness centrality, and many intermodular connections to nodes in different modules. On identifying the shortest topological paths (motifs) between pairs of peripheral neurons, the motifs that are found most frequently traverse the rich club. The rich club neurons are born early in development, before visible movement of the animal and before the main phase of developmental elongation of its body. We conclude that the high wiring cost of the globally integrative rich club of neurons in the C. elegans connectome is justified by the adaptive value of coordinated movement of the animal. The economical trade-off between physical cost and behavioral value of rich club organization in a cellular connectome confirms theoretical expectations and recapitulates comparable results from human neuroimaging on much larger scale networks, suggesting that this may be a general and scale-invariant principle of brain network organization. PMID:23575836

Pollutant Transport and Fate: Relations Between Flow-paths and Downstream Impacts of Human Activities

NASA Astrophysics Data System (ADS)

Thorslund, J.; Jarsjo, J.; Destouni, G.

2017-12-01

The quality of freshwater resources is increasingly impacted by human activities. Humans also extensively change the structure of landscapes, which may alter natural hydrological processes. To manage and maintain freshwater of good water quality, it is critical to understand how pollutants are released into, transported and transformed within the hydrological system. Some key scientific questions include: What are net downstream impacts of pollutants across different hydroclimatic and human disturbance conditions, and on different scales? What are the functions within and between components of the landscape, such as wetlands, on mitigating pollutant load delivery to downstream recipients? We explore these questions by synthesizing results from several relevant case study examples of intensely human-impacted hydrological systems. These case study sites have been specifically evaluated in terms of net impact of human activities on pollutant input to the aquatic system, as well as flow-path distributions trough wetlands as a potential ecosystem service of pollutant mitigation. Results shows that although individual wetlands have high retention capacity, efficient net retention effects were not always achieved at a larger landscape scale. Evidence suggests that the function of wetlands as mitigation solutions to pollutant loads is largely controlled by large-scale parallel and circular flow-paths, through which multiple wetlands are interconnected in the landscape. To achieve net mitigation effects at large scale, a large fraction of the polluted large-scale flows must be transported through multiple connected wetlands. Although such large-scale flow interactions are critical for assessing water pollution spreading and fate through the landscape, our synthesis shows a frequent lack of knowledge at such scales. We suggest ways forward for addressing the mismatch between the large scales at which key pollutant pressures and water quality changes take place and the relatively scale at which most studies and implementations are currently made. These suggestions can help bridge critical knowledge gaps, as needed for improving water quality predictions and mitigation solutions under human and environmental changes.

Resolving anatomical and functional structure in human brain organization: identifying mesoscale organization in weighted network representations.

PubMed

Lohse, Christian; Bassett, Danielle S; Lim, Kelvin O; Carlson, Jean M

2014-10-01

Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

Exploring Visual Evidence of Human Impact on the Environment with Planetary-Scale Zoomable Timelapse Video

NASA Astrophysics Data System (ADS)

Sargent, R.; Egge, M.; Dille, P. S.; O'Donnell, G. D.; Herwig, C.

2016-12-01

Visual evidence ignites curiosity and inspires advocacy. Zoomable imagery and video on a planetary scale provides compelling evidence of human impact on the environment. Earth Timelapse places the observable impact of 30+ years of human activity into the hands of policy makers, scientists, and advocates, with fluidity and speed that supports inquiry and exploration. Zoomability enables compelling narratives and ready apprehension of environmental changes, connecting human-scale evidence to regional and ecosystem-wide trends and changes. Leveraging the power of Google Earth Engine, join us to explore 30+ years of Landset 30m RGB imagery showing glacial retreat, agricultural deforestation, irrigation expansion, and the disappearance of lakes. These narratives are enriched with datasets showing planetary forest gain/loss, annual cycles of agricultural fires, global changes in the health of coral reefs, trends in resource extraction, and of renewable energy development. We demonstrate the intuitive and inquiry-enabling power of these planetary visualizations, and provide instruction on how scientists and advocates can create and share or contribute visualizations of their own research or topics of interest.

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations

PubMed Central

Deco, Gustavo; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-01-01

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure–function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure–function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications. PMID:23825427

Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations.

PubMed

Deco, Gustavo; Ponce-Alvarez, Adrián; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-07-03

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

Limnology in the Upper Paraná River floodplain: large-scale spatial and temporal patterns, and the influence of reservoirs.

PubMed

Roberto, M C; Santana, N N; Thomaz, S M

2009-06-01

Knowledge of abiotic limnological factors is important to monitor changes caused by humans, and to explain the structure and dynamics of populations and communities in a variety of inland water ecosystems. In this study, we used a long term data-set (eight years) collected in 10 habitats with different features (river channels, and connected and isolated lakes) to describe the spatial and temporal patterns of some of the principal limnological factors. In general, the degree of connectivity of the lakes, together with the rivers to which the lakes are connected, were important determinants of their limnological characteristics. These differences are expected, because rivers entering the floodplain come from different geological regions and are subject to different human impacts. At large spatial scales, these differences contribute to the increased habitat diversity of the floodplain and thus to its high biodiversity. With regard to temporal variation, Secchi-disk transparency increased, and total phosphorus decreased in the Paraná River main channel during the last 20 years. Although these changes are directly attributed to the several reservoir cascades located upstream, the closing of the Porto Primavera dam in 1998 enhanced this effect. The increase in water transparency explains biotic changes within the floodplain. The lower-phosphorus Paraná River water probably dilutes concentrations of this element in the floodplain waterbodies during major floods, with future consequences for their productivity.

Fine-Scale Genetic Response to Landscape Change in a Gliding Mammal

PubMed Central

Goldingay, Ross L.; Harrisson, Katherine A.; Taylor, Andrea C.; Ball, Tina M.; Sharpe, David J.; Taylor, Brendan D.

2013-01-01

Understanding how populations respond to habitat loss is central to conserving biodiversity. Population genetic approaches enable the identification of the symptoms of population disruption in advance of population collapse. However, the spatio-temporal scales at which population disruption occurs are still too poorly known to effectively conserve biodiversity in the face of human-induced landscape change. We employed microsatellite analysis to examine genetic structure and diversity over small spatial (mostly 1-50 km) and temporal scales (20-50 years) in the squirrel glider (Petaurus norfolcensis), a gliding mammal that is commonly subjected to a loss of habitat connectivity. We identified genetically differentiated local populations over distances as little as 3 km and within 30 years of landscape change. Genetically isolated local populations experienced the loss of genetic diversity, and significantly increased mean relatedness, which suggests increased inbreeding. Where tree cover remained, genetic differentiation was less evident. This pattern was repeated in two landscapes located 750 km apart. These results lend support to other recent studies that suggest the loss of habitat connectivity can produce fine-scale population genetic change in a range of taxa. This gives rise to the prediction that many other vertebrates will experience similar genetic changes. Our results suggest the future collapse of local populations of this gliding mammal is likely unless habitat connectivity is maintained or restored. Landscape management must occur on a fine-scale to avert the erosion of biodiversity. PMID:24386079

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro

PubMed Central

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P. C.; Livesey, Frederick J.

2015-01-01

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. PMID:26395144

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

PubMed

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

2015-09-15

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

A place meaning scale for tropical marine settings.

PubMed

Wynveen, Christopher J; Kyle, Gerard T

2015-01-01

Over the past 20 years, most of the worldwide hectares set aside for environmental protection have been added to marine protected areas. Moreover, these areas are under tremendous pressure from negative anthropogenic impacts. Given this growth and pressure, there is a need to increase the understanding of the connection between people and marine environments in order to better manage the resource. One construct that researchers have used to understand human-environment connections is place meanings. Place meanings reflect the value and significance of a setting to individuals. Most investigations of place meanings have been confined to terrestrial settings. Moreover, most studies have had small sample sizes or have used place attachment scales as a proxy to gage the meanings individuals ascribe to a setting. Hence, it has become necessary to develop a place meaning scale for use with large samples and for use by those who are concerned about the management of marine environments. Therefore, the purpose of this investigation was to develop a scale to measure the importance people associate with the meanings they ascribe to tropical marine settings and empirically test the scale using two independent samples; that is, Great Barrier Reef Marine Park and the Florida Keys National Marine Sanctuary stakeholders.

A Place Meaning Scale for Tropical Marine Settings

NASA Astrophysics Data System (ADS)

Wynveen, Christopher J.; Kyle, Gerard T.

2015-01-01

Over the past 20 years, most of the worldwide hectares set aside for environmental protection have been added to marine protected areas. Moreover, these areas are under tremendous pressure from negative anthropogenic impacts. Given this growth and pressure, there is a need to increase the understanding of the connection between people and marine environments in order to better manage the resource. One construct that researchers have used to understand human-environment connections is place meanings. Place meanings reflect the value and significance of a setting to individuals. Most investigations of place meanings have been confined to terrestrial settings. Moreover, most studies have had small sample sizes or have used place attachment scales as a proxy to gage the meanings individuals ascribe to a setting. Hence, it has become necessary to develop a place meaning scale for use with large samples and for use by those who are concerned about the management of marine environments. Therefore, the purpose of this investigation was to develop a scale to measure the importance people associate with the meanings they ascribe to tropical marine settings and empirically test the scale using two independent samples; that is, Great Barrier Reef Marine Park and the Florida Keys National Marine Sanctuary stakeholders.

Relationship of resting brain hyperconnectivity and schizophrenia-like symptoms produced by the NMDA receptor antagonist ketamine in humans.

PubMed

Driesen, N R; McCarthy, G; Bhagwagar, Z; Bloch, M; Calhoun, V; D'Souza, D C; Gueorguieva, R; He, G; Ramachandran, R; Suckow, R F; Anticevic, A; Morgan, P T; Krystal, J H

2013-11-01

N-methyl-D-aspartate glutamate receptor (NMDA-R) antagonists produce schizophrenia-like positive and negative symptoms in healthy human subjects. Preclinical research suggests that NMDA-R antagonists interfere with the function of gamma-aminobutyric acid (GABA) neurons and alter the brain oscillations. These changes have been hypothesized to contribute to psychosis. In this investigation, we evaluated the hypothesis that the NMDA-R antagonist ketamine produces alterations in cortical functional connectivity during rest that are related to symptoms. We administered ketamine to a primary sample of 22 subjects and to an additional, partially overlapping, sample of 12 subjects. Symptoms before and after the experimental session were rated with the Positive and Negative Syndrome Scale (PANSS). In the primary sample, functional connectivity was measured via functional magnetic resonance imaging almost immediately after infusion began. In the additional sample, this assessment was repeated after 45 min of continuous ketamine infusion. Global, enhanced functional connectivity was observed at both timepoints, and this hyperconnectivity was related to symptoms in a region-specific manner. This study supports the hypothesis that pathological increases in resting brain functional connectivity contribute to the emergence of positive and negative symptoms associated with schizophrenia.

Relationship of Resting Brain Hyperconnectivity and Schizophrenia-like Symptoms Produced by the NMDA receptor Antagonist Ketamine in Humans

PubMed Central

Driesen, Naomi R.; McCarthy, Gregory; Bhagwagar, Zubin; Bloch, Michael; Calhoun, Vincent; D’Souza, Deepak C.; Gueorguieva, Ralitza; He, George; Ramachandran, Ramani; Suckow, Raymond F.; Anticevic, Alan; Morgan, Peter T.; Krystal, John H.

2012-01-01

N-methyl-D-aspartate glutamate receptor (NMDA-R) antagonists produce schizophrenia-like positive and negative symptoms in healthy human subjects. Preclinical research suggests that NMDA-R antagonists interfere with the function of gamma-aminobutyric acid (GABA) neurons and alter brain oscillations. These changes have been hypothesized to contribute to psychosis. In this investigation, we evaluated the hypothesis that the NMDA-R antagonist ketamine produces alterations in cortical functional connectivity during rest that are related to symptoms. We administered ketamine to a primary sample of twenty-two subjects and to an additional, partially overlapping, sample of twelve subjects. Symptoms before and after the experimental session were rated with the Positive and Negative Symptom Scale (PANSS). In the primary sample, functional connectivity was measured via functional magnetic resonance imaging almost immediately after infusion began. In the additional sample, this assessment was repeated after 45 minutes of continuous ketamine infusion. Global, enhanced functional connectivity was observed at both timepoints and this hyperconnectivity was related to symptoms in a region-specific manner. This study supports the hypothesis that pathological increases in resting brain functional connectivity contribute to the emergence of positive and negative symptoms associated with schizophrenia. PMID:23337947

A Multiscale Parallel Computing Architecture for Automated Segmentation of the Brain Connectome

PubMed Central

Knobe, Kathleen; Newton, Ryan R.; Schlimbach, Frank; Blower, Melanie; Reid, R. Clay

2015-01-01

Several groups in neurobiology have embarked into deciphering the brain circuitry using large-scale imaging of a mouse brain and manual tracing of the connections between neurons. Creating a graph of the brain circuitry, also called a connectome, could have a huge impact on the understanding of neurodegenerative diseases such as Alzheimer’s disease. Although considerably smaller than a human brain, a mouse brain already exhibits one billion connections and manually tracing the connectome of a mouse brain can only be achieved partially. This paper proposes to scale up the tracing by using automated image segmentation and a parallel computing approach designed for domain experts. We explain the design decisions behind our parallel approach and we present our results for the segmentation of the vasculature and the cell nuclei, which have been obtained without any manual intervention. PMID:21926011

Understanding spatial connectivity of individuals with non-uniform population density.

PubMed

Wang, Pu; González, Marta C

2009-08-28

We construct a two-dimensional geometric graph connecting individuals placed in space within a given contact distance. The individuals are distributed using a measured country's density of population. We observe that while large clusters (group of individuals connected) emerge within some regions, they are trapped in detached urban areas owing to the low population density of the regions bordering them. To understand the emergence of a giant cluster that connects the entire population, we compare the empirical geometric graph with the one generated by placing the same number of individuals randomly in space. We find that, for small contact distances, the empirical distribution of population dominates the growth of connected components, but no critical percolation transition is observed in contrast to the graph generated by a random distribution of population. Our results show that contact distances from real-world situations as for WIFI and Bluetooth connections drop in a zone where a fully connected cluster is not observed, hinting that human mobility must play a crucial role in contact-based diseases and wireless viruses' large-scale spreading.

The social brain: scale-invariant layering of Erdős-Rényi networks in small-scale human societies.

PubMed

Harré, Michael S; Prokopenko, Mikhail

2016-05-01

The cognitive ability to form social links that can bind individuals together into large cooperative groups for safety and resource sharing was a key development in human evolutionary and social history. The 'social brain hypothesis' argues that the size of these social groups is based on a neurologically constrained capacity for maintaining long-term stable relationships. No model to date has been able to combine a specific socio-cognitive mechanism with the discrete scale invariance observed in ethnographic studies. We show that these properties result in nested layers of self-organizing Erdős-Rényi networks formed by each individual's ability to maintain only a small number of social links. Each set of links plays a specific role in the formation of different social groups. The scale invariance in our model is distinct from previous 'scale-free networks' studied using much larger social groups; here, the scale invariance is in the relationship between group sizes, rather than in the link degree distribution. We also compare our model with a dominance-based hierarchy and conclude that humans were probably egalitarian in hunter-gatherer-like societies, maintaining an average maximum of four or five social links connecting all members in a largest social network of around 132 people. © 2016 The Author(s).

The Structure of Borders in a Small World

PubMed Central

Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk

2010-01-01

Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity. PMID:21124970

The structure of borders in a small world.

PubMed

Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk

2010-11-18

Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed Central

2013-01-01

Background Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. Results First, we defined the UniProtKB manually reviewed human “complete” proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Conclusions Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human “complete” proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms. PMID:24088582

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams

PubMed Central

Jaeger, Kristin L.; Olden, Julian D.; Pelland, Noel A.

2014-01-01

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6–9% over the course of a year and up to 12–18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna. PMID:25136090

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams.

PubMed

Jaeger, Kristin L; Olden, Julian D; Pelland, Noel A

2014-09-23

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6-9% over the course of a year and up to 12-18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna.

Approximating natural connectivity of scale-free networks based on largest eigenvalue

NASA Astrophysics Data System (ADS)

Tan, S.-Y.; Wu, J.; Li, M.-J.; Lu, X.

2016-06-01

It has been recently proposed that natural connectivity can be used to efficiently characterize the robustness of complex networks. The natural connectivity has an intuitive physical meaning and a simple mathematical formulation, which corresponds to an average eigenvalue calculated from the graph spectrum. However, as a network model close to the real-world system that widely exists, the scale-free network is found difficult to obtain its spectrum analytically. In this article, we investigate the approximation of natural connectivity based on the largest eigenvalue in both random and correlated scale-free networks. It is demonstrated that the natural connectivity of scale-free networks can be dominated by the largest eigenvalue, which can be expressed asymptotically and analytically to approximate natural connectivity with small errors. Then we show that the natural connectivity of random scale-free networks increases linearly with the average degree given the scaling exponent and decreases monotonically with the scaling exponent given the average degree. Moreover, it is found that, given the degree distribution, the more assortative a scale-free network is, the more robust it is. Experiments in real networks validate our methods and results.

Complex Behavior of Contaminant Flux and the Ecology of the Lower Mississippi River

NASA Astrophysics Data System (ADS)

Barton, C. C.; Manheim, F. T.; De Cola, L.; Bollinger, J. E.; Jenkins, J. A.

2001-12-01

This presentation is an overview of a collaborative NSF/USGS/Tulane funded multi-scale study of the Lower Mississippi River system. The study examines the system in three major dimensional realms: space, time, and complexity (systems and their hierarchies). Researchers at Tulane University and the U.S. Geological Survey have initiated a collaborative effort to undertake the study of interacting elements which directly or indirectly affect the water quality, ecology and physical condition of the Mississippi River. These researchers include experts in the fields of water quality chemistry, geochemistry, hydrologic modeling, bioengineering, biology, fish ecology, statistics, complexity analysis, epidemiology, and computer science. Underlying this research are large databases that permit quantitative analysis of the system over the past 40 years. Results to date show that the variation in discharge and the contaminant flux scale independently both exhibit fractal scaling, the signature geometry of nonlinear dynamical and complex systems. Public perception is that the Lower Mississippi River is a health hazard, but for the past decade, traditional water quality measurements show that contaminants are within current regulatory guidelines for human consumption. This difference between public perception and scientific reality represents a complex scientific and social issue. The connections and feedback within the ecological system and the Mississippi River are few because engineering structures isolate the lower Mississippi River from its surroundings. Investigation of the connections and feedback between human health and the ecological health of the River and the surrounding region as well as perceptions of these states of health - holds promise for explaining epidemiological patterns of human disease.

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

How Did Climate and Humans Respond to Past Volcanic Eruptions?

NASA Technical Reports Server (NTRS)

Toohey, Matthew; Ludlow, Francis; Legrande, Allegra N.

2016-01-01

To predict and prepare for future climate change, scientists are striving to understand how global-scale climatic change manifests itself on regional scales and also how societies adapt or don't to sometimes subtle and complex climatic changes. In this regard, the strongest volcanic eruptions of the past are powerful test cases, showcasing how the broad climate system responds to sudden changes in radiative forcing and how societies have responded to the resulting climatic shocks. These issues were at the heart of the inaugural workshop of the Volcanic Impacts on Climate and Society (VICS) Working Group, convened in June 2016 at the Lamont-Doherty Earth Observatory of Columbia University in Palisades, N.Y. The 3-day meeting gathered approximately 50 researchers, who presented work intertwining the history of volcanic eruptions and the physical processes that connect eruptions with human and natural systems on a global scale.

Body Topography Parcellates Human Sensory and Motor Cortex.

PubMed

Kuehn, Esther; Dinse, Juliane; Jakobsen, Estrid; Long, Xiangyu; Schäfer, Andreas; Bazin, Pierre-Louis; Villringer, Arno; Sereno, Martin I; Margulies, Daniel S

2017-07-01

The cytoarchitectonic map as proposed by Brodmann currently dominates models of human sensorimotor cortical structure, function, and plasticity. According to this model, primary motor cortex, area 4, and primary somatosensory cortex, area 3b, are homogenous areas, with the major division lying between the two. Accumulating empirical and theoretical evidence, however, has begun to question the validity of the Brodmann map for various cortical areas. Here, we combined in vivo cortical myelin mapping with functional connectivity analyses and topographic mapping techniques to reassess the validity of the Brodmann map in human primary sensorimotor cortex. We provide empirical evidence that area 4 and area 3b are not homogenous, but are subdivided into distinct cortical fields, each representing a major body part (the hand and the face). Myelin reductions at the hand-face borders are cortical layer-specific, and coincide with intrinsic functional connectivity borders as defined using large-scale resting state analyses. Our data extend the Brodmann model in human sensorimotor cortex and suggest that body parts are an important organizing principle, similar to the distinction between sensory and motor processing. © The Author 2017. Published by Oxford University Press.

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure

PubMed Central

Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

2008-01-01

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges. PMID:19025676

Human gut microbiota and healthy aging: Recent developments and future prospective.

PubMed

Kumar, Manish; Babaei, Parizad; Ji, Boyang; Nielsen, Jens

2016-10-27

The human gut microbiota alters with the aging process. In the first 2-3 years of life, the gut microbiota varies extensively in composition and metabolic functions. After this period, the gut microbiota demonstrates adult-like more stable and diverse microbial species. However, at old age, deterioration of physiological functions of the human body enforces the decrement in count of beneficial species (e.g. Bifidobacteria ) in the gut microbiota, which promotes various gut-related diseases (e.g. inflammatory bowel disease). Use of plant-based diets and probiotics/prebiotics may elevate the abundance of beneficial species and prevent gut-related diseases. Still, the connections between diet, microbes, and host are only partially known. To this end, genome-scale metabolic modeling can help to explore these connections as well as to expand the understanding of the metabolic capability of each species in the gut microbiota. This systems biology approach can also predict metabolic variations in the gut microbiota during ageing, and hereby help to design more effective probiotics/prebiotics.

Human gut microbiota and healthy aging: Recent developments and future prospective

PubMed Central

Kumar, Manish; Babaei, Parizad; Ji, Boyang; Nielsen, Jens

2016-01-01

The human gut microbiota alters with the aging process. In the first 2-3 years of life, the gut microbiota varies extensively in composition and metabolic functions. After this period, the gut microbiota demonstrates adult-like more stable and diverse microbial species. However, at old age, deterioration of physiological functions of the human body enforces the decrement in count of beneficial species (e.g. Bifidobacteria) in the gut microbiota, which promotes various gut-related diseases (e.g. inflammatory bowel disease). Use of plant-based diets and probiotics/prebiotics may elevate the abundance of beneficial species and prevent gut-related diseases. Still, the connections between diet, microbes, and host are only partially known. To this end, genome-scale metabolic modeling can help to explore these connections as well as to expand the understanding of the metabolic capability of each species in the gut microbiota. This systems biology approach can also predict metabolic variations in the gut microbiota during ageing, and hereby help to design more effective probiotics/prebiotics. PMID:28035338

Detection of driver metabolites in the human liver metabolic network using structural controllability analysis

PubMed Central

2014-01-01

Background Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or drug-targets based on network analysis. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis (which is a newly prevailed concept in networks) to biological networks. The exploration on the connections between structural controllability theory and the HLMN could be used to uncover valuable information on the human liver metabolism from a fresh perspective. Results We applied structural controllability analysis to the HLMN and detected driver metabolites. The driver metabolites tend to have strong ability to influence the states of other metabolites and weak susceptibility to be influenced by the states of others. In addition, the metabolites were classified into three classes: critical, high-frequency and low-frequency driver metabolites. Among the identified 36 critical driver metabolites, 27 metabolites were found to be essential; the high-frequency driver metabolites tend to participate in different metabolic pathways, which are important in regulating the whole metabolic systems. Moreover, we explored some other possible connections between the structural controllability theory and the HLMN, and find that transport reactions and the environment play important roles in the human liver metabolism. Conclusion There are interesting connections between the structural controllability theory and the human liver metabolism: driver metabolites have essential biological functions; the crucial role of extracellular metabolites and transport reactions in controlling the HLMN highlights the importance of the environment in the health of human liver metabolism. PMID:24885538

Efficiency of weak brain connections support general cognitive functioning.

PubMed

Santarnecchi, Emiliano; Galli, Giulia; Polizzotto, Nicola Riccardo; Rossi, Alessandro; Rossi, Simone

2014-09-01

Brain network topology provides valuable information on healthy and pathological brain functioning. Novel approaches for brain network analysis have shown an association between topological properties and cognitive functioning. Under the assumption that "stronger is better", the exploration of brain properties has generally focused on the connectivity patterns of the most strongly correlated regions, whereas the role of weaker brain connections has remained obscure for years. Here, we assessed whether the different strength of connections between brain regions may explain individual differences in intelligence. We analyzed-functional connectivity at rest in ninety-eight healthy individuals of different age, and correlated several connectivity measures with full scale, verbal, and performance Intelligent Quotients (IQs). Our results showed that the variance in IQ levels was mostly explained by the distributed communication efficiency of brain networks built using moderately weak, long-distance connections, with only a smaller contribution of stronger connections. The variability in individual IQs was associated with the global efficiency of a pool of regions in the prefrontal lobes, hippocampus, temporal pole, and postcentral gyrus. These findings challenge the traditional view of a prominent role of strong functional brain connections in brain topology, and highlight the importance of both strong and weak connections in determining the functional architecture responsible for human intelligence variability. Copyright © 2014 Wiley Periodicals, Inc.

Differences between child and adult large-scale functional brain networks for reading tasks.

PubMed

Liu, Xin; Gao, Yue; Di, Qiqi; Hu, Jiali; Lu, Chunming; Nan, Yun; Booth, James R; Liu, Li

2018-02-01

Reading is an important high-level cognitive function of the human brain, requiring interaction among multiple brain regions. Revealing differences between children's large-scale functional brain networks for reading tasks and those of adults helps us to understand how the functional network changes over reading development. Here we used functional magnetic resonance imaging data of 17 adults (19-28 years old) and 16 children (11-13 years old), and graph theoretical analyses to investigate age-related changes in large-scale functional networks during rhyming and meaning judgment tasks on pairs of visually presented Chinese characters. We found that: (1) adults had stronger inter-regional connectivity and nodal degree in occipital regions, while children had stronger inter-regional connectivity in temporal regions, suggesting that adults rely more on visual orthographic processing whereas children rely more on auditory phonological processing during reading. (2) Only adults showed between-task differences in inter-regional connectivity and nodal degree, whereas children showed no task differences, suggesting the topological organization of adults' reading network is more specialized. (3) Children showed greater inter-regional connectivity and nodal degree than adults in multiple subcortical regions; the hubs in children were more distributed in subcortical regions while the hubs in adults were more distributed in cortical regions. These findings suggest that reading development is manifested by a shift from reliance on subcortical to cortical regions. Taken together, our study suggests that Chinese reading development is supported by developmental changes in brain connectivity properties, and some of these changes may be domain-general while others may be specific to the reading domain. © 2017 Wiley Periodicals, Inc.

Corticocortical evoked potentials reveal projectors and integrators in human brain networks.

PubMed

Keller, Corey J; Honey, Christopher J; Entz, Laszlo; Bickel, Stephan; Groppe, David M; Toth, Emilia; Ulbert, Istvan; Lado, Fred A; Mehta, Ashesh D

2014-07-02

The cerebral cortex is composed of subregions whose functional specialization is largely determined by their incoming and outgoing connections with each other. In the present study, we asked which cortical regions can exert the greatest influence over other regions and the cortical network as a whole. Previous research on this question has relied on coarse anatomy (mapping large fiber pathways) or functional connectivity (mapping inter-regional statistical dependencies in ongoing activity). Here we combined direct electrical stimulation with recordings from the cortical surface to provide a novel insight into directed, inter-regional influence within the cerebral cortex of awake humans. These networks of directed interaction were reproducible across strength thresholds and across subjects. Directed network properties included (1) a decrease in the reciprocity of connections with distance; (2) major projector nodes (sources of influence) were found in peri-Rolandic cortex and posterior, basal and polar regions of the temporal lobe; and (3) major receiver nodes (receivers of influence) were found in anterolateral frontal, superior parietal, and superior temporal regions. Connectivity maps derived from electrical stimulation and from resting electrocorticography (ECoG) correlations showed similar spatial distributions for the same source node. However, higher-level network topology analysis revealed differences between electrical stimulation and ECoG that were partially related to the reciprocity of connections. Together, these findings inform our understanding of large-scale corticocortical influence as well as the interpretation of functional connectivity networks. Copyright © 2014 the authors 0270-6474/14/349152-12$15.00/0.

Assessing the observed impact of anthropogenic climate change

DOE PAGES

Hansen, Gerrit; Stone, Dáithí

2015-12-21

Impacts of recent regional changes in climate on natural and human systems are documented across the globe, yet studies explicitly linking these observations to anthropogenic forcing of the climate are scarce. Here in this work, we provide a systematic assessment of the role of anthropogenic climate change for the range of impacts of regional climate trends reported in the IPCC’s Fifth Assessment Report. We find that almost two-thirds of the impacts related to atmospheric and ocean temperature can be confidently attributed to anthropogenic forcing. In contrast, evidence connecting changes in precipitation and their respective impacts to human influence is stillmore » weak. Moreover, anthropogenic climate change has been a major influence for approximately three-quarters of the impacts observed on continental scales. Finally, hence the effects of anthropogenic emissions can now be discerned not only globally, but also at more regional and local scales for a variety of natural and human systems.« less

Human-Robot Teaming for Hydrologic Data Gathering at Multiple Scales

NASA Astrophysics Data System (ADS)

Peschel, J.; Young, S. N.

2017-12-01

The use of personal robot-assistive technology by researchers and practitioners for hydrologic data gathering has grown in recent years as barriers to platform capability, cost, and human-robot interaction have been overcome. One consequence to this growth is a broad availability of unmanned platforms that might or might not be suitable for a specific hydrologic investigation. Through multiple field studies, a set of recommendations has been developed to help guide novice through experienced users in choosing the appropriate unmanned platforms for a given application. This talk will present a series of hydrologic data sets gathered using a human-robot teaming approach that has leveraged unmanned aerial, ground, and surface vehicles over multiple scales. The field case studies discussed will be connected to the best practices, also provided in the presentation. This talk will be of interest to geoscience researchers and practitioners, in general, as well as those working in fields related to emerging technologies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansen, Gerrit; Stone, Dáithí

Impacts of recent regional changes in climate on natural and human systems are documented across the globe, yet studies explicitly linking these observations to anthropogenic forcing of the climate are scarce. Here in this work, we provide a systematic assessment of the role of anthropogenic climate change for the range of impacts of regional climate trends reported in the IPCC’s Fifth Assessment Report. We find that almost two-thirds of the impacts related to atmospheric and ocean temperature can be confidently attributed to anthropogenic forcing. In contrast, evidence connecting changes in precipitation and their respective impacts to human influence is stillmore » weak. Moreover, anthropogenic climate change has been a major influence for approximately three-quarters of the impacts observed on continental scales. Finally, hence the effects of anthropogenic emissions can now be discerned not only globally, but also at more regional and local scales for a variety of natural and human systems.« less

Early warning signals of regime shifts from cross-scale connectivity of land-cover patterns

Treesearch

Giovanni Zurlini; Kenneth Bruce Jones; Kurt Hans Riitters; Bai-Lian Li; Irene Petrosillo

2014-01-01

Increasing external pressures from human activities and climate change can lead to desertification, affecting the livelihood of more than 25% of the world’s population. Thus, determining proximity to transition to desertification is particularly central for arid regions before they may convert into deserts, and recent research has focused on devising early warning...

[Construction and evaluation of ecological network in Poyang Lake Eco-economic Zone, China.

PubMed

Chen, Xiao Ping; Chen, Wen Bo

2016-05-01

Large-scale ecological patches play an important role in regional biodiversity conservation. However, with the rapid progress of China's urbanization, human disturbance on the environment is becoming stronger. Large-scale ecological patches will degrade not only in quantity, but also in quality, threatening the connections among them due to isolation and seriously affecting the biodiversity protection. Taking Poyang Lake Eco-economic Zone as a case, this paper established the potential ecological corridors by minimum cost model and GIS technique taking the impacts of landscape types, slope and human disturbance into consideration. Then, based on gravity quantitative model, we analyzed the intensity of ecological interactions between patches, and the potential ecological corridors were divided into two classes for sake of protection. Finally, the important ecological nodes and breaking points were identified, and the structure of the potential ecological network was analyzed. The results showed that forest and cropland were the main landscape types of ecological corridor composition, interaction between ecological patches differed obviously and the structure of the composed regional ecological network was complex with high connectivity and closure. It might provide a scientific basis for the protection of biodiversity and ecological network optimization in Poyang Lake Eco-economic Zone.

Superconducting Optoelectronic Circuits for Neuromorphic Computing

NASA Astrophysics Data System (ADS)

Shainline, Jeffrey M.; Buckley, Sonia M.; Mirin, Richard P.; Nam, Sae Woo

2017-03-01

Neural networks have proven effective for solving many difficult computational problems, yet implementing complex neural networks in software is computationally expensive. To explore the limits of information processing, it is necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density (1 mW /cm2 at 20-MHz firing rate) necessary to scale to systems with enormous entropy. Estimates comparing the proposed hardware platform to a human brain show that with the same number of neurons (1 011) and 700 independent connections per neuron, the hardware presented here may achieve an order of magnitude improvement in synaptic events per second per watt.

New strategy for drug discovery by large-scale association analysis of molecular networks of different species.

PubMed

Zhang, Bo; Fu, Yingxue; Huang, Chao; Zheng, Chunli; Wu, Ziyin; Zhang, Wenjuan; Yang, Xiaoyan; Gong, Fukai; Li, Yuerong; Chen, Xiaoyu; Gao, Shuo; Chen, Xuetong; Li, Yan; Lu, Aiping; Wang, Yonghua

2016-02-25

The development of modern omics technology has not significantly improved the efficiency of drug development. Rather precise and targeted drug discovery remains unsolved. Here a large-scale cross-species molecular network association (CSMNA) approach for targeted drug screening from natural sources is presented. The algorithm integrates molecular network omics data from humans and 267 plants and microbes, establishing the biological relationships between them and extracting evolutionarily convergent chemicals. This technique allows the researcher to assess targeted drugs for specific human diseases based on specific plant or microbe pathways. In a perspective validation, connections between the plant Halliwell-Asada (HA) cycle and the human Nrf2-ARE pathway were verified and the manner by which the HA cycle molecules act on the human Nrf2-ARE pathway as antioxidants was determined. This shows the potential applicability of this approach in drug discovery. The current method integrates disparate evolutionary species into chemico-biologically coherent circuits, suggesting a new cross-species omics analysis strategy for rational drug development.

Structural connectivity at a national scale: Wildlife corridors in Tanzania.

PubMed

Riggio, Jason; Caro, Tim

2017-01-01

Wildlife corridors can help maintain landscape connectivity but novel methods must be developed to assess regional structural connectivity quickly and cheaply so as to determine where expensive and time-consuming surveys of functional connectivity should occur. We use least-cost methods, the most accurate and up-to-date land conversion dataset for East Africa, and interview data on wildlife corridors, to develop a single, consistent methodology to systematically assess wildlife corridors at a national scale using Tanzania as a case study. Our research aimed to answer the following questions; (i) which corridors may still remain open (i.e. structurally connected) at a national scale, (ii) which have been potentially severed by anthropogenic land conversion (e.g., agriculture and settlements), (iii) where are other remaining potential wildlife corridors located, and (iv) which protected areas with lower forms of protection (e.g., Forest Reserves and Wildlife Management Areas) may act as stepping-stones linking more than one National Park and/or Game Reserve. We identify a total of 52 structural connections between protected areas that are potentially open to wildlife movement, and in so doing add 23 to those initially identified by other methods in Tanzanian Government reports. We find that the vast majority of corridors noted in earlier reports as "likely to be severed" have actually not been cut structurally (21 of 24). Nonetheless, nearly a sixth of all the wildlife corridors identified in Tanzania in 2009 have potentially been separated by land conversion, and a third now pass across lands likely to be converted to human use in the near future. Our study uncovers two reserves with lower forms of protection (Uvinza Forest Reserve in the west and Wami-Mbiki Wildlife Management Area in the east) that act as apparently crucial stepping-stones between National Parks and/or Game Reserves and therefore require far more serious conservation support. Methods used in this study are readily applicable to other nations lacking detailed data on wildlife movements and plagued by inaccurate land cover datasets. Our results are the first step in identifying wildlife corridors at a regional scale and provide a springboard for ground-based follow-up conservation.

Structural connectivity at a national scale: Wildlife corridors in Tanzania

PubMed Central

Caro, Tim

2017-01-01

Wildlife corridors can help maintain landscape connectivity but novel methods must be developed to assess regional structural connectivity quickly and cheaply so as to determine where expensive and time-consuming surveys of functional connectivity should occur. We use least-cost methods, the most accurate and up-to-date land conversion dataset for East Africa, and interview data on wildlife corridors, to develop a single, consistent methodology to systematically assess wildlife corridors at a national scale using Tanzania as a case study. Our research aimed to answer the following questions; (i) which corridors may still remain open (i.e. structurally connected) at a national scale, (ii) which have been potentially severed by anthropogenic land conversion (e.g., agriculture and settlements), (iii) where are other remaining potential wildlife corridors located, and (iv) which protected areas with lower forms of protection (e.g., Forest Reserves and Wildlife Management Areas) may act as stepping-stones linking more than one National Park and/or Game Reserve. We identify a total of 52 structural connections between protected areas that are potentially open to wildlife movement, and in so doing add 23 to those initially identified by other methods in Tanzanian Government reports. We find that the vast majority of corridors noted in earlier reports as “likely to be severed” have actually not been cut structurally (21 of 24). Nonetheless, nearly a sixth of all the wildlife corridors identified in Tanzania in 2009 have potentially been separated by land conversion, and a third now pass across lands likely to be converted to human use in the near future. Our study uncovers two reserves with lower forms of protection (Uvinza Forest Reserve in the west and Wami-Mbiki Wildlife Management Area in the east) that act as apparently crucial stepping-stones between National Parks and/or Game Reserves and therefore require far more serious conservation support. Methods used in this study are readily applicable to other nations lacking detailed data on wildlife movements and plagued by inaccurate land cover datasets. Our results are the first step in identifying wildlife corridors at a regional scale and provide a springboard for ground-based follow-up conservation. PMID:29095901

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

PubMed

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity

PubMed Central

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others’ facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition. PMID:29615882

The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales

PubMed Central

Wesolowski, Amy; Buckee, Caroline O.; Pindolia, Deepa K.; Eagle, Nathan; Smith, David L.; Garcia, Andres J.; Tatem, Andrew J.

2013-01-01

Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data. PMID:23326367

Mapping human brain networks with cortico-cortical evoked potentials

PubMed Central

Keller, Corey J.; Honey, Christopher J.; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D.

2014-01-01

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. PMID:25180306

New insights in the homotopic and heterotopic connectivity of the frontal portion of the human corpus callosum revealed by microdissection and diffusion tractography.

PubMed

De Benedictis, Alessandro; Petit, Laurent; Descoteaux, Maxime; Marras, Carlo Efisio; Barbareschi, Mattia; Corsini, Francesco; Dallabona, Monica; Chioffi, Franco; Sarubbo, Silvio

2016-12-01

Extensive studies revealed that the human corpus callosum (CC) plays a crucial role in providing large-scale bi-hemispheric integration of sensory, motor and cognitive processing, especially within the frontal lobe. However, the literature lacks of conclusive data regarding the structural macroscopic connectivity of the frontal CC. In this study, a novel microdissection approach was adopted, to expose the frontal fibers of CC from the dorsum to the lateral cortex in eight hemispheres and in one entire brain. Post-mortem results were then combined with data from advanced constrained spherical deconvolution in 130 healthy subjects. We demonstrated as the frontal CC provides dense inter-hemispheric connections. In particular, we found three types of fronto-callosal fibers, having a dorso-ventral organization. First, the dorso-medial CC fibers subserve homotopic connections between the homologous medial cortices of the superior frontal gyrus. Second, the ventro-lateral CC fibers subserve homotopic connections between lateral frontal cortices, including both the middle frontal gyrus and the inferior frontal gyrus, as well as heterotopic connections between the medial and lateral frontal cortices. Third, the ventro-striatal CC fibers connect the medial and lateral frontal cortices with the contralateral putamen and caudate nucleus. We also highlighted an intricate crossing of CC fibers with the main association pathways terminating in the lateral regions of the frontal lobes. This combined approach of ex vivo microdissection and in vivo diffusion tractography allowed demonstrating a previously unappreciated three-dimensional architecture of the anterior frontal CC, thus clarifying the functional role of the CC in mediating the inter-hemispheric connectivity. Hum Brain Mapp 37:4718-4735, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Musical Structures and Search for Extraterrestrials

NASA Astrophysics Data System (ADS)

Lefebvre, Vladimir A.

Recent findings in cognitive phsychology indicate connections between human feelings and musical scales, on the one hand, and the laws of thermodynamics, on the other. The existence of such a deep correlations allows us to suggest the hypothesis that music is inherent not only to the human beings but to other sapient creatures as well. It is worth, thus, in our search for extraterrestrial civilizations to conduct a "musical" analysis of the spectra of "suspicious" objects. The results of such analysis of the Doppler spectrum of SS 433 will be presented in this paper.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs☆

PubMed Central

Nastase, Samuel A.; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-01-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. PMID:25536493

Multiscale Modeling of Human-Water Interactions: The Role of Time-Scales

NASA Astrophysics Data System (ADS)

Bloeschl, G.; Sivapalan, M.

2015-12-01

Much of the interest in hydrological modeling in the past decades revolved around resolving spatial variability. With the rapid changes brought about by human impacts on the hydrologic cycle, there is now an increasing need to refocus on time dependency. We present a co-evolutionary view of hydrologic systems, in which every part of the system including human systems, co-evolve, albeit at different rates. The resulting coupled human-nature system is framed as a dynamical system, characterized by interactions of fast and slow time scales and feedbacks between environmental and social processes. This gives rise to emergent phenomena such as the levee effect, adaptation to change and system collapse due to resource depletion. Changing human values play a key role in the emergence of these phenomena and should therefore be considered as internal to the system in a dynamic way. The co-evolutionary approach differs from the traditional view of water resource systems analysis as it allows for path dependence, multiple equilibria, lock-in situations and emergent phenomena. The approach may assist strategic water management for long time scales through facilitating stakeholder participation, exploring the possibility space of alternative futures, and helping to synthesise the observed dynamics of different case studies. Future research opportunities include the study of how changes in human values are connected to human-water interactions, historical analyses of trajectories of system co-evolution in individual places and comparative analyses of contrasting human-water systems in different climate and socio-economic settings. Reference Sivapalan, M. and G. Blöschl (2015) Time Scale Interactions and the Co-evolution of Humans and Water. Water Resour. Res., 51, in press.

The T-TEL Method for Assessing Water, Sediment, and Chemical Connectivity

NASA Astrophysics Data System (ADS)

Ali, Genevieve; Oswald, Claire; Spence, Christopher; Wellen, Christopher

2018-02-01

The concept of connectivity has been the subject of a great deal of recent research and provided new insights and breakthroughs on runoff generation processes and watershed biogeochemistry. However, a consensus definition and cohesive mathematical framework that would permit the consistent quantification of hydrologic connectivity, the examination of the interrelationships between water and material (e.g., sediment and chemicals) connectivity, or rigorous study intercomparison, have not been presented by the water resource community. Building on previous conceptualizations and site-specific or process-specific metrics, this paper aimed to review the current state of science on hydrologic connectivity and its role in water-mediated connectivity of material such as solutes and sediment before introducing a conceptual and a mathematical connectivity assessment framework. These frameworks rely on the quantification of Time scales, Thresholds, Excesses and Losses related to water and water-mediated material transport dynamics and are referred to as the T-TEL method. Through a small case study, we show how the T-TEL method allows a wide range of properties to be quantified, namely the occurrence, frequency, duration, magnitude, and spatial extent of water and water-mediated material connectivity. We also propose a research agenda to refine the T-TEL method and ensure its usefulness for facilitating the research and management of connectivity in pristine and human-impacted landscapes.

Human-modified temperatures induce species changes: Joint attribution.

PubMed

Root, Terry L; MacMynowski, Dena P; Mastrandrea, Michael D; Schneider, Stephen H

2005-05-24

Average global surface-air temperature is increasing. Contention exists over relative contributions by natural and anthropogenic forcings. Ecological studies attribute plant and animal changes to observed warming. Until now, temperature-species connections have not been statistically attributed directly to anthropogenic climatic change. Using modeled climatic variables and observed species data, which are independent of thermometer records and paleoclimatic proxies, we demonstrate statistically significant "joint attribution," a two-step linkage: human activities contribute significantly to temperature changes and human-changed temperatures are associated with discernible changes in plant and animal traits. Additionally, our analyses provide independent testing of grid-box-scale temperature projections from a general circulation model (HadCM3).

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

The development of Human Functional Brain Networks

PubMed Central

Power, Jonathan D; Fair, Damien A; Schlaggar, Bradley L

2010-01-01

Recent advances in MRI technology have enabled precise measurements of correlated activity throughout the brain, leading to the first comprehensive descriptions of functional brain networks in humans. This article reviews the growing literature on the development of functional networks, from infancy through adolescence, as measured by resting state functional connectivity MRI. We note several limitations of traditional approaches to describing brain networks, and describe a powerful framework for analyzing networks, called graph theory. We argue that characterization of the development of brain systems (e.g. the default mode network) should be comprehensive, considering not only relationships within a given system, but also how these relationships are situated within wider network contexts. We note that, despite substantial reorganization of functional connectivity, several large-scale network properties appear to be preserved across development, suggesting that functional brain networks, even in children, are organized in manners similar to other complex systems. PMID:20826306

Limited communication capacity unveils strategies for human interaction

NASA Astrophysics Data System (ADS)

Miritello, Giovanna; Lara, Rubén; Cebrian, Manuel; Moro, Esteban

2013-06-01

Connectivity is the key process that characterizes the structural and functional properties of social networks. However, the bursty activity of dyadic interactions may hinder the discrimination of inactive ties from large interevent times in active ones. We develop a principled method to detect tie de-activation and apply it to a large longitudinal, cross-sectional communication dataset (~19 months, ~20 million people). Contrary to the perception of ever-growing connectivity, we observe that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain active in time. On average men display higher capacity than women, and this capacity decreases for both genders over their lifespan. Separating communication capacity from activity reveals a diverse range of tie activation strategies, from stable to exploratory. This allows us to draw novel relationships between individual strategies for human interaction and the evolution of social networks at global scale.

Limited communication capacity unveils strategies for human interaction

PubMed Central

Miritello, Giovanna; Lara, Rubén; Cebrian, Manuel; Moro, Esteban

2013-01-01

Connectivity is the key process that characterizes the structural and functional properties of social networks. However, the bursty activity of dyadic interactions may hinder the discrimination of inactive ties from large interevent times in active ones. We develop a principled method to detect tie de-activation and apply it to a large longitudinal, cross-sectional communication dataset (≈19 months, ≈20 million people). Contrary to the perception of ever-growing connectivity, we observe that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain active in time. On average men display higher capacity than women, and this capacity decreases for both genders over their lifespan. Separating communication capacity from activity reveals a diverse range of tie activation strategies, from stable to exploratory. This allows us to draw novel relationships between individual strategies for human interaction and the evolution of social networks at global scale. PMID:23739519

Lifespan anxiety is reflected in human amygdala cortical connectivity

PubMed Central

He, Ye; Xu, Ting; Zhang, Wei

2016-01-01

Abstract The amygdala plays a pivotal role in processing anxiety and connects to large‐scale brain networks. However, intrinsic functional connectivity (iFC) between amygdala and these networks has rarely been examined in relation to anxiety, especially across the lifespan. We employed resting‐state functional MRI data from 280 healthy adults (18–83.5 yrs) to elucidate the relationship between anxiety and amygdala iFC with common cortical networks including the visual network, somatomotor network, dorsal attention network, ventral attention network, limbic network, frontoparietal network, and default network. Global and network‐specific iFC were separately computed as mean iFC of amygdala with the entire cerebral cortex and each cortical network. We detected negative correlation between global positive amygdala iFC and trait anxiety. Network‐specific associations between amygdala iFC and anxiety were also detectable. Specifically, the higher iFC strength between the left amygdala and the limbic network predicted lower state anxiety. For the trait anxiety, left amygdala anxiety–connectivity correlation was observed in both somatomotor and dorsal attention networks, whereas the right amygdala anxiety–connectivity correlation was primarily distributed in the frontoparietal and ventral attention networks. Ventral attention network exhibited significant anxiety–gender interactions on its iFC with amygdala. Together with findings from additional vertex‐wise analysis, these data clearly indicated that both low‐level sensory networks and high‐level associative networks could contribute to detectable predictions of anxiety behaviors by their iFC profiles with the amygdala. This set of systems neuroscience findings could lead to novel functional network models on neural correlates of human anxiety and provide targets for novel treatment strategies on anxiety disorders. Hum Brain Mapp 37:1178–1193, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:26859312

A Comparison of Physical Education Students’ Motivation Using Polish and Turkish Versions of the Academic Motivation Scale

PubMed Central

Tomik, Rajmund; Berber, Serkan; Düz, Burak; Çivak, Barış; Çalişkan, Uğur; Ogrodnik, Joanna

2016-01-01

Abstract Motivation is an important phenomenon in the realm of education, particularly in the university fields connected with physical education and sport, where it is necessary to accommodate and balance intellectual abilities and physical fitness. The present study tested motivation levels among university students in the fields connected with physical education and sport in Poland and Turkey. It was based on the Self-Determination Theory (Deci and Ryan, 1985), namely intrinsic motivation, extrinsic motivation and amotivation which impact human behaviour. The Academic Motivation Scale was used (Vallerand et al., 1992). The aims of the study were twofold, first, to crossculturally validate Polish and Turkish versions of the Academic Motivation Scale and second, to identify and compare the motivation to study depending on nationality and gender. Both Polish and Turkish versions of the questionnaire were validated and converted to a four-factorial structure. The findings indicated that Polish and Turkish students’ motivation especially differed in amotivation and intrinsic motivation to know and experience stimulation. Moreover, Turkish female students proved to be at the lowest estimate of amotivation. PMID:28031771

A Comparison of Physical Education Students' Motivation Using Polish and Turkish Versions of the Academic Motivation Scale.

PubMed

Ardeńska, Agnieszka; Tomik, Rajmund; Berber, Serkan; Düz, Burak; Çivak, Barış; Çalişkan, Uğur; Ogrodnik, Joanna

2016-12-01

Motivation is an important phenomenon in the realm of education, particularly in the university fields connected with physical education and sport, where it is necessary to accommodate and balance intellectual abilities and physical fitness. The present study tested motivation levels among university students in the fields connected with physical education and sport in Poland and Turkey. It was based on the Self-Determination Theory (Deci and Ryan, 1985), namely intrinsic motivation, extrinsic motivation and amotivation which impact human behaviour. The Academic Motivation Scale was used (Vallerand et al., 1992). The aims of the study were twofold, first, to crossculturally validate Polish and Turkish versions of the Academic Motivation Scale and second, to identify and compare the motivation to study depending on nationality and gender. Both Polish and Turkish versions of the questionnaire were validated and converted to a four-factorial structure. The findings indicated that Polish and Turkish students' motivation especially differed in amotivation and intrinsic motivation to know and experience stimulation. Moreover, Turkish female students proved to be at the lowest estimate of amotivation.

Out of the net: An agent-based model to study human movements influence on local-scale malaria transmission.

PubMed

Pizzitutti, Francesco; Pan, William; Feingold, Beth; Zaitchik, Ben; Álvarez, Carlos A; Mena, Carlos F

2018-01-01

Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

Hydrologic connectivity as a framework for understanding biogeochemical flux through watersheds and along fluvial networks

NASA Astrophysics Data System (ADS)

Covino, Tim

2017-01-01

Hydrologic connections can link hillslopes to channel networks, streams to lakes, subsurface to surface, land to atmosphere, terrestrial to aquatic, and upstream to downstream. These connections can develop across vertical, lateral, and longitudinal dimensions and span spatial and temporal scales. Each of these dimensions and scales are interconnected, creating a mosaic of nested hydrologic connections and associated processes. In turn, these interacting and nested processes influence the transport, cycling, and transformation of organic material and inorganic nutrients through watersheds and along fluvial networks. Although hydrologic connections span dimensions and spatiotemporal scales, relationships between connectivity and carbon and nutrient dynamics are rarely evaluated within this framework. The purpose of this paper is to provide a cross-disciplinary view of hydrologic connectivity - highlighting the various forms of hydrologic connectivity that control fluxes of organic material and nutrients - and to help stimulate integration across scales and dimensions, and collaboration among disciplines.

The connectivity of the brain: multi-level quantitative analysis.

PubMed

Murre, J M; Sturdy, D P

1995-11-01

We develop a mathematical formalism or calculating connectivity volumes generated by specific topologies with various physical packing strategies. We consider four topologies (full, random, nearest-neighbor, and modular connectivity) and three physical models: (i) interior packing, where neurons and connection fibers are intermixed, (ii) sheeted packing where neurons are located on a sheet with fibers running underneath, and (iii) exterior packing where the neurons are located at the surfaces of a cube or sphere with fibers taking up the internal volume. By extensive cross-referencing of available human neuroanatomical data we produce a consistent set of parameters for the whole brain, the cerebral cortex, and the cerebellar cortex. By comparing these inferred values with those predicted by the expressions, we draw the following general conclusions for the human brain, cortex, and cerebellum: (i) Interior packing is less efficient than exterior packing (in a sphere). (ii) Fully and randomly connected topologies are extremely inefficient. More specifically we find evidence that different topologies and physical packing strategies might be used at different scales. (iii) For the human brain at a macro-structural level, modular topologies on an exterior sphere approach the data most closely. (iv) On a mesostructural level, laminarization and columnarization are evidence of the superior efficiency of organizing the wiring as sheets. (v) Within sheets, microstructures emerge in which interior models are shown to be the most efficient. With regard to interspecies similarities and differences we conjecture (vi) that the remarkable constancy of number of neurons per underlying square millimeter of cortex may be the result of evolution minimizing interneuron distance in grey matter, and (vii) that the topologies that best fit the human brain data should not be assumed to apply to other mammals, such as the mouse for which we show that a random topology may be feasible for the cortex.

Conserving tigers in working landscapes.

PubMed

Chanchani, Pranav; Noon, Barry R; Bailey, Larissa L; Warrier, Rekha A

2016-06-01

Tiger (Panthera tigris) conservation efforts in Asia are focused on protected areas embedded in human-dominated landscapes. A system of protected areas is an effective conservation strategy for many endangered species if the network is large enough to support stable metapopulations. The long-term conservation of tigers requires that the species be able to meet some of its life-history needs beyond the boundaries of small protected areas and within the working landscape, including multiple-use forests with logging and high human use. However, understanding of factors that promote or limit the occurrence of tigers in working landscapes is incomplete. We assessed the relative influence of protection status, prey occurrence, extent of grasslands, intensity of human use, and patch connectivity on tiger occurrence in the 5400 km(2) Central Terai Landscape of India, adjacent to Nepal. Two observer teams independently surveyed 1009 km of forest trails and water courses distributed across 60 166-km(2) cells. In each cell, the teams recorded detection of tiger signs along evenly spaced trail segments. We used occupancy models that permitted multiscale analysis of spatially correlated data to estimate cell-scale occupancy and segment-scale habitat use by tigers as a function of management and environmental covariates. Prey availability and habitat quality, rather than protected-area designation, influenced tiger occupancy. Tiger occupancy was low in some protected areas in India that were connected to extensive areas of tiger habitat in Nepal, which brings into question the efficacy of current protection and management strategies in both India and Nepal. At a finer spatial scale, tiger habitat use was high in trail segments associated with abundant prey and large grasslands, but it declined as human and livestock use increased. We speculate that riparian grasslands may provide tigers with critical refugia from human activity in the daytime and thereby promote tiger occurrence in some multiple-use forests. Restrictions on human-use in high-quality tiger habitat in multiple-use forests may complement existing protected areas and collectively promote the persistence of tiger populations in working landscapes. © 2015 Society for Conservation Biology.

Soil erosion and sediment connectivity modelling in Burgundy vineyards: case study of Mercurey, France

NASA Astrophysics Data System (ADS)

Fressard, Mathieu; Cossart, Étienne; Lejot, Jêrome; Michel, Kristell; Perret, Franck; Christol, Aurélien; Mathian, Hélène; Navratil, Oldrich

2017-04-01

This research aims at assessing the impact of agricultural landscape structure on soil erosion and sediment connectivity at the catchment scale. The investigations were conducted the vineyards of Mercurey (Burgundy, France), characterized by important issues related to soil loss, flash floods and associated management infrastructures maintenance. The methodology is based on two main steps that include (1) field investigations and (2) modelling. The field investigations consists in DEM acquisition by LiDAR imaging from a drone, soil mapping and human infrastructures impacting runoff classification and mapping (such as crop rows, storm water-basins, drainage network, roads, etc.). These data aims at supplying the models with field observations. The modelling strategy is based on two main steps: First, the modelling of soil sensitivity to erosion, using the spatial application of the RUSLE equation. Secondly, to assess the sediment connectivity in this area, a model based on graph theory developed by Cossart and Fressard (2017) is tested. The results allow defining the influence of different anthropogenic structures on the sediment connectivity and soil erosion at the basin scale. A set of sub-basins influenced by various anthropogenic infrastructures have been identified and show contrasted sensitivities to erosion. The modelling of sediment connectivity show that the runoff pattern is strongly influenced by the vine rows orientation and the drainage network. I has also permitted to identify non collected (by storm water-basins) areas that strongly contribute to the turbid floods sediment supply and to soil loss during high intensity precipitations events.

Cognitive Flexibility through Metastable Neural Dynamics Is Disrupted by Damage to the Structural Connectome.

PubMed

Hellyer, Peter J; Scott, Gregory; Shanahan, Murray; Sharp, David J; Leech, Robert

2015-06-17

Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome. Copyright © 2015 the authors 0270-6474/15/359050-14$15.00/0.

Dynamic Functional Connectivity States Reflecting Psychotic-like Experiences.

PubMed

Barber, Anita D; Lindquist, Martin A; DeRosse, Pamela; Karlsgodt, Katherine H

2018-05-01

Psychotic-like experiences (PLEs) are associated with lower social and occupational functioning, and lower executive function. Emerging evidence also suggests that PLEs reflect neural dysfunction resembling that of psychotic disorders. The present study examined dynamic connectivity related to a measure of PLEs derived from the Achenbach Adult Self-Report, in an otherwise-healthy sample of adults from the Human Connectome Project. A total of 76 PLE-endorsing and 153 control participants were included in the final sample. To characterize network dysfunction, dynamic connectivity states were examined across large-scale resting-state networks using dynamic conditional correlation and k-means clustering. Three dynamic states were identified. The PLE-endorsing group spent more time than the control group in state 1, a state reflecting hyperconnectivity within visual regions and hypoconnectivity within the default mode network, and less time in state 2, a state characterized by robust within-network connectivity for all networks and strong default mode network anticorrelations. Within the PLE-endorsing group, worse executive function was associated with more time spent in and more transitions into state 1 and less time spent in and fewer transitions into state 3. PLEs are associated with altered large-scale brain dynamics, which tip the system away from spending more time in states reflecting more "typical" connectivity patterns toward more time in states reflecting visual hyperconnectivity and default mode hypoconnectivity. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Comparative ruralism and 'opening new windows' on gentrification.

PubMed

Phillips, Martin; Smith, Darren P

2018-03-01

In response to the five commentaries on our paper 'Comparative approaches to gentrification: lessons from the rural', we open up more 'windows' on rural gentrification and its urban counterpart. First, we highlight the issues of metrocentricity and urbanormativity within gentrification studies, highlighting their employment by our commentators. Second, we consider the issue of displacement and its operation within rural space, as well as gentrification as a coping strategy for neoliberal existence and connections to more-than-human natures. Finally, we consider questions of scale, highlighting the need to avoid naturalistic conceptions of scale and arguing that attention could be paid to the role of material practices, symbolizations and lived experiences in producing scaled geographies of rural and urban gentrification.

The Role of Time-Scales in Socio-hydrology

NASA Astrophysics Data System (ADS)

Blöschl, Günter; Sivapalan, Murugesu

2016-04-01

Much of the interest in hydrological modeling in the past decades revolved around resolving spatial variability. With the rapid changes brought about by human impacts on the hydrologic cycle, there is now an increasing need to refocus on time dependency. We present a co-evolutionary view of hydrologic systems, in which every part of the system including human systems, co-evolve, albeit at different rates. The resulting coupled human-nature system is framed as a dynamical system, characterized by interactions of fast and slow time scales and feedbacks between environmental and social processes. This gives rise to emergent phenomena such as the levee effect, adaptation to change and system collapse due to resource depletion. Changing human values play a key role in the emergence of these phenomena and should therefore be considered as internal to the system in a dynamic way. The co-evolutionary approach differs from the traditional view of water resource systems analysis as it allows for path dependence, multiple equilibria, lock-in situations and emergent phenomena. The approach may assist strategic water management for long time scales through facilitating stakeholder participation, exploring the possibility space of alternative futures, and helping to synthesise the observed dynamics of different case studies. Future research opportunities include the study of how changes in human values are connected to human-water interactions, historical analyses of trajectories of system co-evolution in individual places and comparative analyses of contrasting human-water systems in different climate and socio-economic settings. Reference Sivapalan, M. and G. Blöschl (2015) Time scale interactions and the coevolution of humans and water. Water Resour. Res., 51, 6988-7022, doi:10.1002/2015WR017896.

The storage capacity of Potts models for semantic memory retrieval

NASA Astrophysics Data System (ADS)

Kropff, Emilio; Treves, Alessandro

2005-08-01

We introduce and analyse a minimal network model of semantic memory in the human brain. The model is a global associative memory structured as a collection of N local modules, each coding a feature, which can take S possible values, with a global sparseness a (the average fraction of features describing a concept). We show that, under optimal conditions, the number cM of modules connected on average to a module can range widely between very sparse connectivity (high dilution, c_{M}/N\\to 0 ) and full connectivity (c_{M}\\to N ), maintaining a global network storage capacity (the maximum number pc of stored and retrievable concepts) that scales like pc~cMS2/a, with logarithmic corrections consistent with the constraint that each synapse may store up to a fraction of a bit.

Fetal functional imaging portrays heterogeneous development of emerging human brain networks

PubMed Central

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M.; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26–29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity. PMID:25374531

The convergence of maturational change and structural covariance in human cortical networks.

PubMed

Alexander-Bloch, Aaron; Raznahan, Armin; Bullmore, Ed; Giedd, Jay

2013-02-13

Large-scale covariance of cortical thickness or volume in distributed brain regions has been consistently reported by human neuroimaging studies. The mechanism of this population covariance of regional cortical anatomy has been hypothetically related to synchronized maturational changes in anatomically connected neuronal populations. Brain regions that grow together, i.e., increase or decrease in volume at the same rate over the course of years in the same individual, are thus expected to demonstrate strong structural covariance or anatomical connectivity across individuals. To test this prediction, we used a structural MRI dataset on healthy young people (N = 108; aged 9-22 years at enrollment), comprising 3-6 longitudinal scans on each participant over 6-12 years of follow-up. At each of 360 regional nodes, and for each participant, we estimated the following: (1) the cortical thickness in the median scan and (2) the linear rate of change in cortical thickness over years of serial scanning. We constructed structural and maturational association matrices and networks from these measurements. Both structural and maturational networks shared similar global and nodal topological properties, as well as mesoscopic features including a modular community structure, a relatively small number of highly connected hub regions, and a bias toward short distance connections. Using resting-state functional magnetic resonance imaging data on a subset of the sample (N = 32), we also demonstrated that functional connectivity and network organization was somewhat predictable by structural/maturational networks but demonstrated a stronger bias toward short distance connections and greater topological segregation. Brain structural covariance networks are likely to reflect synchronized developmental change in distributed cortical regions.

Fetal functional imaging portrays heterogeneous development of emerging human brain networks.

PubMed

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach.

PubMed

Xu, Nan; Spreng, R Nathan; Doerschuk, Peter C

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the "common driver" problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.

Classes of real-world 'small-world' networks: From the neural network of C. Elegans to the web of human sexual contacts

NASA Astrophysics Data System (ADS)

Nunes Amaral, Luis A.

2002-03-01

We study the statistical properties of a variety of diverse real-world networks including the neural network of C. Elegans, food webs for seven distinct environments, transportation and technological networks, and a number of distinct social networks [1-5]. We present evidence of the occurrence of three classes of small-world networks [2]: (a) scale-free networks, characterized by a vertex connectivity distribution that decays as a power law; (b) broad-scale networks, characterized by a connectivity distribution that has a power-law regime followed by a sharp cut-off; (c) single-scale networks, characterized by a connectivity distribution with a fast decaying tail. Moreover, we note for the classes of broad-scale and single-scale networks that there are constraints limiting the addition of new links. Our results suggest that the nature of such constraints may be the controlling factor for the emergence of different classes of networks. [See http://polymer.bu.edu/ amaral/Networks.html for details and htpp://polymer.bu.edu/ amaral/Professional.html for access to PDF files of articles.] 1. M. Barthélémy, L. A. N. Amaral, Phys. Rev. Lett. 82, 3180-3183 (1999). 2. L. A. N. Amaral, A. Scala, M. Barthélémy, H. E. Stanley, Proc. Nat. Acad. Sci. USA 97, 11149-11152 (2000). 3. F. Liljeros, C. R. Edling, L. A. N. Amaral, H. E. Stanley, and Y. Åberg, Nature 411, 907-908 (2001). 4. J. Camacho, R. Guimera, L.A.N. Amaral, Phys. Rev. E RC (to appear). 5. S. Mossa, M. Barthelemy, H.E. Stanley, L.A.N. Amaral (submitted).

Dynamics of coupled human-landscape systems

NASA Astrophysics Data System (ADS)

Werner, B. T.; McNamara, D. E.

2007-11-01

A preliminary dynamical analysis of landscapes and humans as hierarchical complex systems suggests that strong coupling between the two that spreads to become regionally or globally pervasive should be focused at multi-year to decadal time scales. At these scales, landscape dynamics is dominated by water, sediment and biological routing mediated by fluvial, oceanic, atmospheric processes and human dynamics is dominated by simplifying, profit-maximizing market forces and political action based on projection of economic effect. Also at these scales, landscapes impact humans through patterns of natural disasters and trends such as sea level rise; humans impact landscapes by the effect of economic activity and changes meant to mitigate natural disasters and longer term trends. Based on this analysis, human-landscape coupled systems can be modeled using heterogeneous agents employing prediction models to determine actions to represent the nonlinear behavior of economic and political systems and rule-based routing algorithms to represent landscape processes. A cellular model for the development of New Orleans illustrates this approach, with routing algorithms for river and hurricane-storm surge determining flood extent, five markets (home, labor, hotel, tourism and port services) connecting seven types of economic agents (home buyers/laborers, home developers, hotel owners/ employers, hotel developers, tourists, port services developer and port services owners/employers), building of levees or a river spillway by political agents and damage to homes, hotels or port services within cells determined by the passage or depth of flood waters. The model reproduces historical aspects of New Orleans economic development and levee construction and the filtering of frequent small-scale floods at the expense of large disasters.

Network-Level Structure-Function Relationships in Human Neocortex

PubMed Central

Mišić, Bratislav; Betzel, Richard F.; de Reus, Marcel A.; van den Heuvel, Martijn P.; Berman, Marc G.; McIntosh, Anthony R.; Sporns, Olaf

2016-01-01

The dynamics of spontaneous fluctuations in neural activity are shaped by underlying patterns of anatomical connectivity. While numerous studies have demonstrated edge-wise correspondence between structural and functional connections, much less is known about how large-scale coherent functional network patterns emerge from the topology of structural networks. In the present study, we deploy a multivariate statistical technique, partial least squares, to investigate the association between spatially extended structural networks and functional networks. We find multiple statistically robust patterns, reflecting reliable combinations of structural and functional subnetworks that are optimally associated with one another. Importantly, these patterns generally do not show a one-to-one correspondence between structural and functional edges, but are instead distributed and heterogeneous, with many functional relationships arising from nonoverlapping sets of anatomical connections. We also find that structural connections between high-degree hubs are disproportionately represented, suggesting that these connections are particularly important in establishing coherent functional networks. Altogether, these results demonstrate that the network organization of the cerebral cortex supports the emergence of diverse functional network configurations that often diverge from the underlying anatomical substrate. PMID:27102654

Humans, water, and the colonization of Australia.

PubMed

Bird, Michael I; O'Grady, Damien; Ulm, Sean

2016-10-11

The Pleistocene global dispersal of modern humans required the transit of arid and semiarid regions where the distribution of potable water provided a primary constraint on dispersal pathways. Here, we provide a spatially explicit continental-scale assessment of the opportunities for Pleistocene human occupation of Australia, the driest inhabited continent on Earth. We establish the location and connectedness of persistent water in the landscape using the Australian Water Observations from Space dataset combined with the distribution of small permanent water bodies (springs, gnammas, native wells, waterholes, and rockholes). Results demonstrate a high degree of directed landscape connectivity during wet periods and a high density of permanent water points widely but unevenly distributed across the continental interior. A connected network representing the least-cost distance between water bodies and graded according to terrain cost shows that 84% of archaeological sites >30,000 y old are within 20 km of modern permanent water. We further show that multiple, well-watered routes into the semiarid and arid continental interior were available throughout the period of early human occupation. Depletion of high-ranked resources over time in these paleohydrological corridors potentially drove a wave of dispersal farther along well-watered routes to patches with higher foraging returns.

Humans, water, and the colonization of Australia

PubMed Central

O’Grady, Damien

2016-01-01

The Pleistocene global dispersal of modern humans required the transit of arid and semiarid regions where the distribution of potable water provided a primary constraint on dispersal pathways. Here, we provide a spatially explicit continental-scale assessment of the opportunities for Pleistocene human occupation of Australia, the driest inhabited continent on Earth. We establish the location and connectedness of persistent water in the landscape using the Australian Water Observations from Space dataset combined with the distribution of small permanent water bodies (springs, gnammas, native wells, waterholes, and rockholes). Results demonstrate a high degree of directed landscape connectivity during wet periods and a high density of permanent water points widely but unevenly distributed across the continental interior. A connected network representing the least-cost distance between water bodies and graded according to terrain cost shows that 84% of archaeological sites >30,000 y old are within 20 km of modern permanent water. We further show that multiple, well-watered routes into the semiarid and arid continental interior were available throughout the period of early human occupation. Depletion of high-ranked resources over time in these paleohydrological corridors potentially drove a wave of dispersal farther along well-watered routes to patches with higher foraging returns. PMID:27671630

Spatial Embedding and Wiring Cost Constrain the Functional Layout of the Cortical Network of Rodents and Primates

PubMed Central

Magrou, Loïc; Gămănuț, Bianca; Van Essen, David C.; Burkhalter, Andreas; Knoblauch, Kenneth; Toroczkai, Zoltán; Kennedy, Henry

2016-01-01

Mammals show a wide range of brain sizes, reflecting adaptation to diverse habitats. Comparing interareal cortical networks across brains of different sizes and mammalian orders provides robust information on evolutionarily preserved features and species-specific processing modalities. However, these networks are spatially embedded, directed, and weighted, making comparisons challenging. Using tract tracing data from macaque and mouse, we show the existence of a general organizational principle based on an exponential distance rule (EDR) and cortical geometry, enabling network comparisons within the same model framework. These comparisons reveal the existence of network invariants between mouse and macaque, exemplified in graph motif profiles and connection similarity indices, but also significant differences, such as fractionally smaller and much weaker long-distance connections in the macaque than in mouse. The latter lends credence to the prediction that long-distance cortico-cortical connections could be very weak in the much-expanded human cortex, implying an increased susceptibility to disconnection syndromes such as Alzheimer disease and schizophrenia. Finally, our data from tracer experiments involving only gray matter connections in the primary visual areas of both species show that an EDR holds at local scales as well (within 1.5 mm), supporting the hypothesis that it is a universally valid property across all scales and, possibly, across the mammalian class. PMID:27441598

Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project

PubMed Central

McDonough, Ian M.; Nashiro, Kaoru

2014-01-01

An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing). While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013) to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy (1) would differ from random noise, (2) would differ between four major resting-state networks previously associated with higher-order cognition, and (3) would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity. PMID:24959130

Mapping human brain networks with cortico-cortical evoked potentials.

PubMed

Keller, Corey J; Honey, Christopher J; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D

2014-10-05

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas.

PubMed

Ecker, Joseph R; Geschwind, Daniel H; Kriegstein, Arnold R; Ngai, John; Osten, Pavel; Polioudakis, Damon; Regev, Aviv; Sestan, Nenad; Wickersham, Ian R; Zeng, Hongkui

2017-11-01

A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

NASA Astrophysics Data System (ADS)

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-12-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks.

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

PubMed Central

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-01-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks. PMID:27917958

DICCCOL: Dense Individualized and Common Connectivity-Based Cortical Landmarks

PubMed Central

Zhu, Dajiang; Guo, Lei; Jiang, Xi; Zhang, Tuo; Zhang, Degang; Chen, Hanbo; Deng, Fan; Faraco, Carlos; Jin, Changfeng; Wee, Chong-Yaw; Yuan, Yixuan; Lv, Peili; Yin, Yan; Hu, Xiaolei; Duan, Lian; Hu, Xintao; Han, Junwei; Wang, Lihong; Shen, Dinggang; Miller, L Stephen

2013-01-01

Is there a common structural and functional cortical architecture that can be quantitatively encoded and precisely reproduced across individuals and populations? This question is still largely unanswered due to the vast complexity, variability, and nonlinearity of the cerebral cortex. Here, we hypothesize that the common cortical architecture can be effectively represented by group-wise consistent structural fiber connections and take a novel data-driven approach to explore the cortical architecture. We report a dense and consistent map of 358 cortical landmarks, named Dense Individualized and Common Connectivity–based Cortical Landmarks (DICCCOLs). Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. Our results have shown that these 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes, as demonstrated in this work. PMID:22490548

Dysbiotic drift and biopsychosocial medicine: how the microbiome links personal, public and planetary health.

PubMed

Prescott, Susan L; Wegienka, Ganesa; Logan, Alan C; Katz, David L

2018-01-01

The emerging concept of planetary health emphasizes that the health of human civilization is intricately connected to the health of natural systems within the Earth's biosphere; here, we focus on the rapidly progressing microbiome science - the microbiota-mental health research in particular - as a way to illustrate the pathways by which exposure to biodiversity supports health. Microbiome science is illuminating the ways in which stress, socioeconomic disadvantage and social polices interact with lifestyle and behaviour to influence the micro and macro-level biodiversity that otherwise mediates health. Although the unfolding microbiome and mental health research is dominated by optimism in biomedical solutions (e.g. probiotics, prebiotics), we focus on the upstream psychosocial and ecological factors implicated in dysbiosis; we connect grand scale biodiversity in the external environment with differences in human-associated microbiota, and, by extension, differences in immune function and mental outlook. We argue that the success of planetary health as a new concept will be strengthened by a more sophisticated understanding of the ways in which individuals develop emotional connections to nature (nature relatedness) and the social policies and practices which facilitate or inhibit the pro-environmental values that otherwise support personal, public and planetary health.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs.

PubMed

Nastase, Samuel A; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-03-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. Copyright © 2014. Published by Elsevier Inc.

Large-scale degradation of Amazonian freshwater ecosystems

NASA Astrophysics Data System (ADS)

Castello, L.; Macedo, M.

2016-12-01

The integrity of freshwater ecosystems depends on their hydrological connectivity with land, water, and climate systems. Hydrological connectivity regulates the structure and function of Amazonian freshwater ecosystems and the provisioning of services that sustain local populations. However, the hydrological connectivity of Amazonian freshwater ecosystems is increasingly disrupted by construction of dams, mining, land-cover changes, and global climate change. This review analyzes these drivers of degradation; evaluates their impacts on hydrological connectivity; and identifies policy deficiencies that hinder freshwater ecosystem protection. There are 155 large hydroelectric dams in operation, 21 dams under construction, and there will be only three free-flowing tributaries if all 277 planned dams for the Basin are built. Land-cover changes driven by mining, dam and road construction, and agriculture and cattle ranching have already affected 20% of the Basin and up to 50% of riparian forests in some regions. Global climate change will likely exacerbate these impacts by creating warmer and dryer conditions, with less predictable rainfall and more extreme events (e.g. droughts and floods). The resulting hydrological alterations are rapidly degrading freshwater ecosystems both independently and via complex feedbacks and synergistic interactions. The ecosystem impacts include biodiversity loss, warmer stream temperatures, stronger and more frequent floodplain fires, and changes to biogeochemical cycles, transport of organic and inorganic materials, and freshwater community structure and function. The impacts also include reductions in water quality, fish yields, and availability of water for navigation, power generation, and human use. This degradation of Amazonian freshwater ecosystems cannot be curbed presently because existing policies are inconsistent across the Basin, ignore cumulative effects, and do not consider the hydrological connectivity of freshwater ecosystems. Maintaining the integrity of these freshwater ecosystems requires a basin-wide research and policy framework to understand and manage hydrological connectivity across multiple spatial scales and jurisdictional boundaries.

Self-organized dynamical complexity in human wakefulness and sleep: different critical brain-activity feedback for conscious and unconscious states.

PubMed

Allegrini, Paolo; Paradisi, Paolo; Menicucci, Danilo; Laurino, Marco; Piarulli, Andrea; Gemignani, Angelo

2015-09-01

Criticality reportedly describes brain dynamics. The main critical feature is the presence of scale-free neural avalanches, whose auto-organization is determined by a critical branching ratio of neural-excitation spreading. Other features, directly associated to second-order phase transitions, are: (i) scale-free-network topology of functional connectivity, stemming from suprathreshold pairwise correlations, superimposable, in waking brain activity, with that of ferromagnets at Curie temperature; (ii) temporal long-range memory associated to renewal intermittency driven by abrupt fluctuations in the order parameters, detectable in human brain via spatially distributed phase or amplitude changes in EEG activity. Herein we study intermittent events, extracted from 29 night EEG recordings, including presleep wakefulness and all phases of sleep, where different levels of mentation and consciousness are present. We show that while critical avalanching is unchanged, at least qualitatively, intermittency and functional connectivity, present during conscious phases (wakefulness and REM sleep), break down during both shallow and deep non-REM sleep. We provide a theory for fragmentation-induced intermittency breakdown and suggest that the main difference between conscious and unconscious states resides in the backwards causation, namely on the constraints that the emerging properties at large scale induce to the lower scales. In particular, while in conscious states this backwards causation induces a critical slowing down, preserving spatiotemporal correlations, in dreamless sleep we see a self-organized maintenance of moduli working in parallel. Critical avalanches are still present, and establish transient auto-organization, whose enhanced fluctuations are able to trigger sleep-protecting mechanisms that reinstate parallel activity. The plausible role of critical avalanches in dreamless sleep is to provide a rapid recovery of consciousness, if stimuli are highly arousing.

Self-organized dynamical complexity in human wakefulness and sleep: Different critical brain-activity feedback for conscious and unconscious states

NASA Astrophysics Data System (ADS)

Allegrini, Paolo; Paradisi, Paolo; Menicucci, Danilo; Laurino, Marco; Piarulli, Andrea; Gemignani, Angelo

2015-09-01

Criticality reportedly describes brain dynamics. The main critical feature is the presence of scale-free neural avalanches, whose auto-organization is determined by a critical branching ratio of neural-excitation spreading. Other features, directly associated to second-order phase transitions, are: (i) scale-free-network topology of functional connectivity, stemming from suprathreshold pairwise correlations, superimposable, in waking brain activity, with that of ferromagnets at Curie temperature; (ii) temporal long-range memory associated to renewal intermittency driven by abrupt fluctuations in the order parameters, detectable in human brain via spatially distributed phase or amplitude changes in EEG activity. Herein we study intermittent events, extracted from 29 night EEG recordings, including presleep wakefulness and all phases of sleep, where different levels of mentation and consciousness are present. We show that while critical avalanching is unchanged, at least qualitatively, intermittency and functional connectivity, present during conscious phases (wakefulness and REM sleep), break down during both shallow and deep non-REM sleep. We provide a theory for fragmentation-induced intermittency breakdown and suggest that the main difference between conscious and unconscious states resides in the backwards causation, namely on the constraints that the emerging properties at large scale induce to the lower scales. In particular, while in conscious states this backwards causation induces a critical slowing down, preserving spatiotemporal correlations, in dreamless sleep we see a self-organized maintenance of moduli working in parallel. Critical avalanches are still present, and establish transient auto-organization, whose enhanced fluctuations are able to trigger sleep-protecting mechanisms that reinstate parallel activity. The plausible role of critical avalanches in dreamless sleep is to provide a rapid recovery of consciousness, if stimuli are highly arousing.

Large-scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy.

PubMed

de Campos, Brunno Machado; Coan, Ana Carolina; Lin Yasuda, Clarissa; Casseb, Raphael Fernandes; Cendes, Fernando

2016-09-01

Mesial temporal lobe epilepsy (MTLE) with hippocampus sclerosis (HS) is associated with functional and structural alterations extending beyond the temporal regions and abnormal pattern of brain resting state networks (RSNs) connectivity. We hypothesized that the interaction of large-scale RSNs is differently affected in patients with right- and left-MTLE with HS compared to controls. We aimed to determine and characterize these alterations through the analysis of 12 RSNs, functionally parceled in 70 regions of interest (ROIs), from resting-state functional-MRIs of 99 subjects (52 controls, 26 right- and 21 left-MTLE patients with HS). Image preprocessing and statistical analysis were performed using UF(2) C-toolbox, which provided ROI-wise results for intranetwork and internetwork connectivity. Intranetwork abnormalities were observed in the dorsal default mode network (DMN) in both groups of patients and in the posterior salience network in right-MTLE. Both groups showed abnormal correlation between the dorsal-DMN and the posterior salience, as well as between the dorsal-DMN and the executive-control network. Patients with left-MTLE also showed reduced correlation between the dorsal-DMN and visuospatial network and increased correlation between bilateral thalamus and the posterior salience network. The ipsilateral hippocampus stood out as a central area of abnormalities. Alterations on left-MTLE expressed a low cluster coefficient, whereas the altered connections on right-MTLE showed low cluster coefficient in the DMN but high in the posterior salience regions. Both right- and left-MTLE patients with HS have widespread abnormal interactions of large-scale brain networks; however, all parameters evaluated indicate that left-MTLE has a more intricate bihemispheric dysfunction compared to right-MTLE. Hum Brain Mapp 37:3137-3152, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The effects of habitat connectivity and regional heterogeneity on artificial pond metacommunities.

PubMed

Pedruski, Michael T; Arnott, Shelley E

2011-05-01

Habitat connectivity and regional heterogeneity represent two factors likely to affect biodiversity across different spatial scales. We performed a 3 × 2 factorial design experiment to investigate the effects of connectivity, heterogeneity, and their interaction on artificial pond communities of freshwater invertebrates at the local (α), among-community (β), and regional (γ) scales. Despite expectations that the effects of connectivity would depend on levels of regional heterogeneity, no significant interactions were found for any diversity index investigated at any spatial scale. While observed responses of biodiversity to connectivity and heterogeneity depended to some extent on the diversity index and spatial partitioning formula used, the general pattern shows that these factors largely act at the β scale, as opposed to the α or γ scales. We conclude that the major role of connectivity in aquatic invertebrate communities is to act as a homogenizing force with relatively little effect on diversity at the α or γ levels. Conversely, heterogeneity acts as a force maintaining differences between communities.

Deconstructing white matter connectivity of human amygdala nuclei with thalamus and cortex subdivisions in vivo.

PubMed

Abivardi, Aslan; Bach, Dominik R

2017-08-01

Structural alterations in long-range amygdala connections are proposed to crucially underlie several neuropsychiatric disorders. While progress has been made in elucidating the function of these connections, our understanding of their structure in humans remains sparse and non-systematic. Harnessing diffusion-weighted imaging and probabilistic tractography in humans, we investigate connections between two main amygdala nucleus groups, thalamic nuclei, and cortex. We first parcellated amygdala into deep (basolateral) and superficial (centrocortical) nucleus groups, and thalamus into six subregions, using previously established protocols based on connectivity. Cortex was parcellated based on T1-weighted images. We found substantial amygdala connections to thalamus, with different patterns for the two amygdala nuclei. Crucially, we describe direct subcortical connections between amygdala and paraventricular thalamus. Different from rodents but similar to non-human primates, these are more pronounced for basolateral than centrocortical amygdala. Substantial white-matter connectivity between amygdala and visual pulvinar is also more pronounced for basolateral amygdala. Furthermore, we establish detailed connectivity profiles for basolateral and centrocortical amygdala to cortical regions. These exhibit cascadic connections with sensory cortices as suggested previously based on tracer methods in non-human animals. We propose that the quantitative connectivity profiles provided here may guide future work on normal and pathological function of human amygdala. Hum Brain Mapp 38:3927-3940, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Comparative ruralism and ‘opening new windows’ on gentrification

PubMed Central

Phillips, Martin; Smith, Darren P

2018-01-01

In response to the five commentaries on our paper ‘Comparative approaches to gentrification: lessons from the rural’, we open up more ‘windows’ on rural gentrification and its urban counterpart. First, we highlight the issues of metrocentricity and urbanormativity within gentrification studies, highlighting their employment by our commentators. Second, we consider the issue of displacement and its operation within rural space, as well as gentrification as a coping strategy for neoliberal existence and connections to more-than-human natures. Finally, we consider questions of scale, highlighting the need to avoid naturalistic conceptions of scale and arguing that attention could be paid to the role of material practices, symbolizations and lived experiences in producing scaled geographies of rural and urban gentrification. PMID:29657709

Wavelet analysis of polarization maps of polycrystalline biological fluids networks

NASA Astrophysics Data System (ADS)

Ushenko, Y. A.

2011-12-01

The optical model of human joints synovial fluid is proposed. The statistic (statistic moments), correlation (autocorrelation function) and self-similar (Log-Log dependencies of power spectrum) structure of polarization two-dimensional distributions (polarization maps) of synovial fluid has been analyzed. It has been shown that differentiation of polarization maps of joint synovial fluid with different physiological state samples is expected of scale-discriminative analysis. To mark out of small-scale domain structure of synovial fluid polarization maps, the wavelet analysis has been used. The set of parameters, which characterize statistic, correlation and self-similar structure of wavelet coefficients' distributions of different scales of polarization domains for diagnostics and differentiation of polycrystalline network transformation connected with the pathological processes, has been determined.

30 Days Wild: Development and Evaluation of a Large-Scale Nature Engagement Campaign to Improve Well-Being

PubMed Central

Richardson, Miles; Cormack, Adam; McRobert, Lucy; Underhill, Ralph

2016-01-01

There is a need to increase people’s engagement with and connection to nature, both for human well-being and the conservation of nature itself. In order to suggest ways for people to engage with nature and create a wider social context to normalise nature engagement, The Wildlife Trusts developed a mass engagement campaign, 30 Days Wild. The campaign asked people to engage with nature every day for a month. 12,400 people signed up for 30 Days Wild via an online sign-up with an estimated 18,500 taking part overall, resulting in an estimated 300,000 engagements with nature by participants. Samples of those taking part were found to have sustained increases in happiness, health, connection to nature and pro-nature behaviours. With the improvement in health being predicted by the improvement in happiness, this relationship was mediated by the change in connection to nature. PMID:26890891

Dual-phase evolution in complex adaptive systems

PubMed Central

Paperin, Greg; Green, David G.; Sadedin, Suzanne

2011-01-01

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle. PMID:21247947

Dual-phase evolution in complex adaptive systems.

PubMed

Paperin, Greg; Green, David G; Sadedin, Suzanne

2011-05-06

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle.

30 Days Wild: Development and Evaluation of a Large-Scale Nature Engagement Campaign to Improve Well-Being.

PubMed

Richardson, Miles; Cormack, Adam; McRobert, Lucy; Underhill, Ralph

2016-01-01

There is a need to increase people's engagement with and connection to nature, both for human well-being and the conservation of nature itself. In order to suggest ways for people to engage with nature and create a wider social context to normalise nature engagement, The Wildlife Trusts developed a mass engagement campaign, 30 Days Wild. The campaign asked people to engage with nature every day for a month. 12,400 people signed up for 30 Days Wild via an online sign-up with an estimated 18,500 taking part overall, resulting in an estimated 300,000 engagements with nature by participants. Samples of those taking part were found to have sustained increases in happiness, health, connection to nature and pro-nature behaviours. With the improvement in health being predicted by the improvement in happiness, this relationship was mediated by the change in connection to nature.

ELUCIDATING BRAIN CONNECTIVITY NETWORKS IN MAJOR DEPRESSIVE DISORDER USING CLASSIFICATION-BASED SCORING.

PubMed

Sacchet, Matthew D; Prasad, Gautam; Foland-Ross, Lara C; Thompson, Paul M; Gotlib, Ian H

2014-04-01

Graph theory is increasingly used in the field of neuroscience to understand the large-scale network structure of the human brain. There is also considerable interest in applying machine learning techniques in clinical settings, for example, to make diagnoses or predict treatment outcomes. Here we used support-vector machines (SVMs), in conjunction with whole-brain tractography, to identify graph metrics that best differentiate individuals with Major Depressive Disorder (MDD) from nondepressed controls. To do this, we applied a novel feature-scoring procedure that incorporates iterative classifier performance to assess feature robustness. We found that small-worldness , a measure of the balance between global integration and local specialization, most reliably differentiated MDD from nondepressed individuals. Post-hoc regional analyses suggested that heightened connectivity of the subcallosal cingulate gyrus (SCG) in MDDs contributes to these differences. The current study provides a novel way to assess the robustness of classification features and reveals anomalies in large-scale neural networks in MDD.

Consciousness, cognition and brain networks: New perspectives.

PubMed

Aldana, E M; Valverde, J L; Fábregas, N

2016-10-01

A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks. Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

The Mental Representation of Social Connections: Generalizability Extended to Beijing Adults

PubMed Central

Hawkley, Louise C.; Gu, Yuanyuan; Luo, Yue-Jia; Cacioppo, John T.

2012-01-01

Social connections are essential for the survival of a social species like humans. People differ in the degree to which they are sensitive to perceived deficits in their social connections, but evidence suggests that they nevertheless construe the nature of their social connections similarly. This construal can be thought of as a mental representation of a multi-faceted social experience. A three-dimensional mental representation has been identified with the UCLA Loneliness Scale and consists of Intimate, Relational, and Collective Connectedness reflecting beliefs about one's individual, dyadic, and collective (group) social value, respectively. Moreover, this mental representation has been replicated with other scales and validated across age, gender, and racial/ethnic lines in U.S. samples. The purpose of this study is to evaluate the extent to which this three-dimensional representation applies to people whose social lives are experienced in a collectivistic rather than individualistic culture. To that end, we used confirmatory factor analyses to assess the fit of the three-dimensional mental structure to data collected from Chinese people living in China. Two hundred sixty-seven young adults (16–25 yrs) and 250 older adults (50–65 yrs) in Beijing completed the revised UCLA Loneliness Scale and demographic and social activity questionnaires. Results revealed adequate fit of the structure to data from young and older Chinese adults. Moreover, the structure exhibited equivalent fit in young and older Chinese adults despite changes in the Chinese culture that exposed these two generations to different cultural experiences. Social activity variables that discriminated among the three dimensions in the Chinese samples corresponded well with variables that discriminated among the three dimensions in the U.S.-based samples, indicating cultural commonalities in the factors predicting dimensions of people's representations of their social connections. Equivalence of the three-dimensional structure is relevant for an understanding of cultural differences in the sources of loneliness and social connectedness. PMID:23028486

The mental representation of social connections: generalizability extended to Beijing adults.

PubMed

Hawkley, Louise C; Gu, Yuanyuan; Luo, Yue-Jia; Cacioppo, John T

2012-01-01

Social connections are essential for the survival of a social species like humans. People differ in the degree to which they are sensitive to perceived deficits in their social connections, but evidence suggests that they nevertheless construe the nature of their social connections similarly. This construal can be thought of as a mental representation of a multi-faceted social experience. A three-dimensional mental representation has been identified with the UCLA Loneliness Scale and consists of Intimate, Relational, and Collective Connectedness reflecting beliefs about one's individual, dyadic, and collective (group) social value, respectively. Moreover, this mental representation has been replicated with other scales and validated across age, gender, and racial/ethnic lines in U.S. samples. The purpose of this study is to evaluate the extent to which this three-dimensional representation applies to people whose social lives are experienced in a collectivistic rather than individualistic culture. To that end, we used confirmatory factor analyses to assess the fit of the three-dimensional mental structure to data collected from Chinese people living in China. Two hundred sixty-seven young adults (16-25 yrs) and 250 older adults (50-65 yrs) in Beijing completed the revised UCLA Loneliness Scale and demographic and social activity questionnaires. Results revealed adequate fit of the structure to data from young and older Chinese adults. Moreover, the structure exhibited equivalent fit in young and older Chinese adults despite changes in the Chinese culture that exposed these two generations to different cultural experiences. Social activity variables that discriminated among the three dimensions in the Chinese samples corresponded well with variables that discriminated among the three dimensions in the U.S.-based samples, indicating cultural commonalities in the factors predicting dimensions of people's representations of their social connections. Equivalence of the three-dimensional structure is relevant for an understanding of cultural differences in the sources of loneliness and social connectedness.

Small Traditional Human Communities Sustain Genomic Diversity over Microgeographic Scales despite Linguistic Isolation

PubMed Central

Cox, Murray P.; Hudjashov, Georgi; Sim, Andre; Savina, Olga; Karafet, Tatiana M.; Sudoyo, Herawati; Lansing, J. Stephen

2016-01-01

At least since the Neolithic, humans have largely lived in networks of small, traditional communities. Often socially isolated, these groups evolved distinct languages and cultures over microgeographic scales of just tens of kilometers. Population genetic theory tells us that genetic drift should act quickly in such isolated groups, thus raising the question: do networks of small human communities maintain levels of genetic diversity over microgeographic scales? This question can no longer be asked in most parts of the world, which have been heavily impacted by historical events that make traditional society structures the exception. However, such studies remain possible in parts of Island Southeast Asia and Oceania, where traditional ways of life are still practiced. We captured genome-wide genetic data, together with linguistic records, for a case–study system—eight villages distributed across Sumba, a small, remote island in eastern Indonesia. More than 4,000 years after these communities were established during the Neolithic period, most speak different languages and can be distinguished genetically. Yet their nuclear diversity is not reduced, instead being comparable to other, even much larger, regional groups. Modeling reveals a separation of time scales: while languages and culture can evolve quickly, creating social barriers, sporadic migration averaged over many generations is sufficient to keep villages linked genetically. This loosely-connected network structure, once the global norm and still extant on Sumba today, provides a living proxy to explore fine-scale genome dynamics in the sort of small traditional communities within which the most recent episodes of human evolution occurred. PMID:27274003

Inferred global connectivity of whale shark Rhincodon typus populations.

PubMed

Sequeira, A M M; Mellin, C; Meekan, M G; Sims, D W; Bradshaw, C J A

2013-02-01

Ten years have passed since the last synopsis of whale shark Rhincodon typus biogeography. While a recent review of the species' biology and ecology summarized the vast data collected since then, it is clear that information on population geographic connectivity, migration and demography of R. typus is still limited and scattered. Understanding R. typus migratory behaviour is central to its conservation management considering the genetic evidence suggesting local aggregations are connected at the generational scale over entire ocean basins. By collating available data on sightings, tracked movements and distribution information, this review provides evidence for the hypothesis of broad-scale connectivity among populations, and generates a model describing how the world's R. typus are part of a single, global meta-population. Rhincodon typus occurrence timings and distribution patterns make possible a connection between several aggregation sites in the Indian Ocean. The present conceptual model and validating data lend support to the hypothesis that R. typus are able to move among the three largest ocean basins with a minimum total travelling time of around 2-4 years. The model provides a worldwide perspective of possible R. typus migration routes, and suggests a modified focus for additional research to test its predictions. The framework can be used to trim the hypotheses for R. typus movements and aggregation timings, thereby isolating possible mating and breeding areas that are currently unknown. This will assist endeavours to predict the longer-term response of the species to ocean warming and changing patterns of human-induced mortality. © 2013 The Authors. Journal of Fish Biology © 2013 The Fisheries Society of the British Isles.

Estimating time-dependent connectivity in marine systems

USGS Publications Warehouse

Defne, Zafer; Ganju, Neil K.; Aretxabaleta, Alfredo

2016-01-01

Hydrodynamic connectivity describes the sources and destinations of water parcels within a domain over a given time. When combined with biological models, it can be a powerful concept to explain the patterns of constituent dispersal within marine ecosystems. However, providing connectivity metrics for a given domain is a three-dimensional problem: two dimensions in space to define the sources and destinations and a time dimension to evaluate connectivity at varying temporal scales. If the time scale of interest is not predefined, then a general approach is required to describe connectivity over different time scales. For this purpose, we have introduced the concept of a “retention clock” that highlights the change in connectivity through time. Using the example of connectivity between protected areas within Barnegat Bay, New Jersey, we show that a retention clock matrix is an informative tool for multitemporal analysis of connectivity.

Historical foundations and future directions in macrosystems ecology.

PubMed

Rose, Kevin C; Graves, Rose A; Hansen, Winslow D; Harvey, Brian J; Qiu, Jiangxiao; Wood, Stephen A; Ziter, Carly; Turner, Monica G

2017-02-01

Macrosystems ecology is an effort to understand ecological processes and interactions at the broadest spatial scales and has potential to help solve globally important social and ecological challenges. It is important to understand the intellectual legacies underpinning macrosystems ecology: How the subdiscipline fits within, builds upon, differs from and extends previous theories. We trace the rise of macrosystems ecology with respect to preceding theories and present a new hypothesis that integrates the multiple components of macrosystems theory. The spatio-temporal anthropogenic rescaling (STAR) hypothesis suggests that human activities are altering the scales of ecological processes, resulting in interactions at novel space-time scale combinations that are diverse and predictable. We articulate four predictions about how human actions are "expanding", "shrinking", "speeding up" and "slowing down" ecological processes and interactions, and thereby generating new scaling relationships for ecological patterns and processes. We provide examples of these rescaling processes and describe ecological consequences across terrestrial, freshwater and marine ecosystems. Rescaling depends in part on characteristics including connectivity, stability and heterogeneity. Our STAR hypothesis challenges traditional assumptions about how the spatial and temporal scales of processes and interactions operate in different types of ecosystems and provides a lens through which to understand macrosystem-scale environmental change. © 2016 John Wiley & Sons Ltd/CNRS.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Evaluation of Encapsulated Liver Cell Spheroids in a Fluidised-Bed Bioartificial Liver for Treatment of Ischaemic Acute Liver Failure in Pigs in a Translational Setting

PubMed Central

Selden, Clare; Spearman, Catherine Wendy; Kahn, Delawir; Miller, Malcolm; Figaji, Anthony; Erro, Eloy; Bundy, James; Massie, Isobel; Chalmers, Sherri-Ann; Arendse, Hiram; Gautier, Aude; Sharratt, Peter; Fuller, Barry; Hodgson, Humphrey

2013-01-01

Liver failure is an increasing problem. Donor-organ shortage results in patients dying before receiving a transplant. Since the liver can regenerate, alternative therapies providing temporary liver-support are sought. A bioartificial-liver would temporarily substitute function in liver failure buying time for liver regeneration/organ-procurement. Our aim: to develop a prototype bioartificial-liver-machine (BAL) comprising a human liver-derived cell-line, cultured to phenotypic competence and deliverable in a clinical setting to sites distant from its preparation. The objective of this study was to determine whether its use would improve functional parameters of liver failure in pigs with acute liver failure, to provide proof-of-principle. HepG2cells encapsulated in alginate-beads, proliferated in a fluidised-bed-bioreactor providing a biomass of 4–6×1010cells, were transported from preparation-laboratory to point-of-use operating theatre (6000miles) under perfluorodecalin at ambient temperature. Irreversible ischaemic liver failure was induced in anaesthetised pigs, after portal-systemic-shunt, by hepatic-artery-ligation. Biochemical parameters, intracranial pressure, and functional-clotting were measured in animals connected in an extracorporeal bioartificial-liver circuit. Efficacy was demonstrated comparing outcomes between animals connected to a circuit containing alginate-encapsulated cells (Cell-bead BAL), and those connected to circuit containing alginate capsules without cells (Empty-bead BAL). Cells of the biomass met regulatory standards for sterility and provenance. All animals developed progressive liver-failure after ischaemia induction. Efficacy of BAL was demonstrated since animals connected to a functional biomass (+ cells) had significantly smaller rises in intracranial pressure, lower ammonia levels, more bilirubin conjugation, improved acidosis and clotting restoration compared to animals connected to the circuit without cells. In the +cell group, human proteins accumulated in pigs' plasma. Delivery of biomass using a short-term cold-chain enabled transport and use without loss of function over 3days. Thus, a fluidised-bed bioreactor containing alginate-encapsulated HepG2cell-spheroids improved important parameters of acute liver failure in pigs. The system can readily be up-scaled and transported to point-of-use justifying development at clinical scale. PMID:24367515

Behavior of wet precast beam column connections under progressive collapse scenario: an experimental study

NASA Astrophysics Data System (ADS)

Nimse, Rohit B.; Joshi, Digesh D.; Patel, Paresh V.

2014-12-01

Progressive collapse denotes a failure of a major portion of a structure that has been initiated by failure of a relatively small part of the structure such as failure of any vertical load carrying element (typically columns). Failure of large part of any structure will results into substantial loss of human lives and natural resources. Therefore, it is important to prevent progressive collapse which is also known as disproportionate collapse. Nowadays, there is an increasing trend toward construction of buildings using precast concrete. In precast concrete construction, all the components of structures are produced in controlled environment and they are being transported to the site. At site such individual components are connected appropriately. Connections are the most critical elements of any precast structure, because in past major collapse of precast structure took place because of connection failure. In this study, behavior of three different 1/3rd scaled wet precast beam column connections under progressive collapse scenario are studied and its performance is compared with monolithic connection. Precast connections are constructed by adopting different connection detailing at the junction by considering reinforced concrete corbel for two specimens and steel billet for one specimen. Performance of specimen is evaluated on the basis of ultimate load carrying capacity, maximum deflection and deflection measured along the span of the beam. From the results, it is observed that load carrying capacity and ductility of precast connections considered in this study are more than that of monolithic connections.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

NASA Astrophysics Data System (ADS)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Human Disease-Drug Network Based on Genomic Expression Profiles

PubMed Central

Hu, Guanghui; Agarwal, Pankaj

2009-01-01

Background Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and drugs can be comprehensively characterized by the changes they induce in gene expression, protein, metabolites and phenotypes. Methodology/Principal Findings We performed a systematic, large-scale analysis of genomic expression profiles of human diseases and drugs to create a disease-drug network. A network of 170,027 significant interactions was extracted from the ∼24.5 million comparisons between ∼7,000 publicly available transcriptomic profiles. The network includes 645 disease-disease, 5,008 disease-drug, and 164,374 drug-drug relationships. At least 60% of the disease-disease pairs were in the same disease area as determined by the Medical Subject Headings (MeSH) disease classification tree. The remaining can drive a molecular level nosology by discovering relationships between seemingly unrelated diseases, such as a connection between bipolar disorder and hereditary spastic paraplegia, and a connection between actinic keratosis and cancer. Among the 5,008 disease-drug links, connections with negative scores suggest new indications for existing drugs, such as the use of some antimalaria drugs for Crohn's disease, and a variety of existing drugs for Huntington's disease; while the positive scoring connections can aid in drug side effect identification, such as tamoxifen's undesired carcinogenic property. From the ∼37K drug-drug relationships, we discover relationships that aid in target and pathway deconvolution, such as 1) KCNMA1 as a potential molecular target of lobeline, and 2) both apoptotic DNA fragmentation and G2/M DNA damage checkpoint regulation as potential pathway targets of daunorubicin. Conclusions/Significance We have automatically generated thousands of disease and drug expression profiles using GEO datasets, and constructed a large scale disease-drug network for effective and efficient drug repositioning as well as drug target/pathway identification. PMID:19657382

The emergence of mind and emotion in the evolution of neocortex.

PubMed

Freeman, Walter J

2011-01-01

The most deeply transformative concept for the growth of 21st Century psychiatry is the constellation of the chaotic dynamics of the brain. Brains are no longer seen as rational systems that are plagued with emotional disorders reflecting primitives inherited from our animal ancestors. Brains are dynamical systems that continually create patterns by acting intentionally into the environment and shaping themselves in accord with the sensory consequences of their intended actions. Emotions are now seen not as reversions to animal behaviors but as the sources of force and energy that brains require for the actions they take to understand the world and themselves. Humans are unique in experiencing consciousness of their own actions, which they experience as conscience: guilt, shame, pride and joy. Chaotic brain dynamics strives always for unity and harmony, but as a necessary condition for adaptation to a changing world, it repeatedly lapses into disorder. The successes are seen in the normal unity of consciousness; the failures are seen in the disorders that we rightly label the schizophrenias and the less severe character disorders. The foundation for healthy unity is revealed by studies in the evolution of brains, in particular the way in which neocortex of mammals emerged from the primitive allocortex of reptiles. The amazing facts of brain dynamics are now falling into several places. The power-law connectivity of cortex supports the scale-free dynamics of the global workspace in brains ranging from mouse to whale. That dynamics in humans holds the secrets of speech and symbol utilization. By recursive interactions in vast areas of human neocortex the scale-free connectivity supports our unified consciousness. Here in this dynamics are to be sought the keys to understanding and treating the disorders that uniquely plague the human mind.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

PubMed Central

Xu, Nan; Spreng, R. Nathan; Doerschuk, Peter C.

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain. PMID:28559793

Do well-connected landscapes promote road-related mortality?

USGS Publications Warehouse

Grilo, C.; Ascensao, F.; Santos-Reis, M.; Bissonette, J.A.

2011-01-01

Cost surface (CS) models have emerged as a useful tool to examine the interactions between landscapes patterns and wildlife at large-scale extents. This approach is particularly relevant to guide conservation planning for species that show vulnerability to road networks in human-dominated landscapes. In this study, we measured the functional connectivity of the landscape in southern Portugal and examined how it may be related to stone marten road mortality risk. We addressed three questions: (1) How different levels of landscape connectivity influence stone marten occurrence in montado patches? (2) Is there any relation between montado patches connectivity and stone marten road mortality risk? (3) If so, which road-related features might be responsible for the species' high road mortality? We developed a series of connectivity models using CS scenarios with different resistance values given to each vegetation cover type to reflect different resistance to species movement. Our models showed that the likelihood of occurrence of stone marten decreased with distance to source areas, meaning continuous montado. Open areas and riparian areas within open area matrices entailed increased costs. We found higher stone marten mortality on roads in well-connected areas. Road sinuosity was an important factor influencing the mortality in those areas. This result challenges the way that connectivity and its relation to mortality has been generally regarded. Clearly, landscape connectivity and road-related mortality are not independent. ?? 2010 Springer-Verlag.

Normative brain size variation and brain shape diversity in humans.

PubMed

Reardon, P K; Seidlitz, Jakob; Vandekar, Simon; Liu, Siyuan; Patel, Raihaan; Park, Min Tae M; Alexander-Bloch, Aaron; Clasen, Liv S; Blumenthal, Jonathan D; Lalonde, Francois M; Giedd, Jay N; Gur, Ruben C; Gur, Raquel E; Lerch, Jason P; Chakravarty, M Mallar; Satterthwaite, Theodore D; Shinohara, Russell T; Raznahan, Armin

2018-06-15

Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Large-scale functional networks connect differently for processing words and symbol strings.

PubMed

Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta

2018-01-01

Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease

PubMed Central

Horn, Andreas; Reich, Martin; Vorwerk, Johannes; Li, Ningfei; Wenzel, Gregor; Fang, Qianqian; Schmitz-Hübsch, Tanja; Nickl, Robert; Kupsch, Andreas; Volkmann, Jens; Kühn, Andrea A.; Fox, Michael D.

2018-01-01

Objective The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p<0.001). This same connectivity profile predicted response in an independent patient cohort (p<0.01). Structural and functional connectivity were independent predictors of clinical improvement (p<0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients. Interpretation Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. PMID:28586141

Temporal scaling behavior of forest and urban fires

NASA Astrophysics Data System (ADS)

Wang, J.; Song, W.; Zheng, H.; Telesca, L.

2009-04-01

It has been found that many natural systems are characterized by scaling behavior. In such systems natural factors dominate the event dynamics. Forest fires in different countries have been found to exhibit frequency-size power law over many orders of magnitude and with similar value of parameters. But in countries with high population density such as China and Japan, more than 95% of the forest fire disasters are caused by human activities. Furthermore, with the development of society, the wildland-urban interface (WUI) area is becoming more and more populated, and the forest fire is much connected with urban fire. Therefore exploring the scaling behavior of fires dominated by human-related factors is very challenging. The present paper explores the temporal scaling behavior of forest fires and urban fires in Japan with mathematical methods. Two factors, Allan factor (AF) and Fano factor (FF) are used to investigate time-scaling of fire systems. It is found that the FF for both forest fires and urban fires increases linearly in log-log scales, and this indicates that it behaves as a power-law for all the investigated timescales. From the AF plot a 7 days cycle is found, which indicates a weekly cycle. This may be caused by human activities which has a weekly periodicity because on weekends people usually have more outdoor activities, which may cause more hidden trouble of fire disasters. Our findings point out that although the human factors are the main cause, both the forest fires and urban fires exhibit time-scaling behavior. At the same time, the scaling exponents for urban fires are larger than forest fires, signifying a more intense clustering. The reason may be that fires are affected not only by weather condition, but also by human activities, which play a more important role for urban fires than forest fires and have a power law distribution and scaling behavior. Then some work is done to the relative humidity. Similar distribution law characterizes the relative humidity. The AF plot and FF plot of relative humidity validate the existence of a strong link between weather and fires, and it is very likely that the daily humidity cycle determines the daily fire periodicity.

Development of the Sources of Spirituality Scale.

PubMed

Davis, Don E; Rice, Kenneth; Hook, Joshua N; Van Tongeren, Daryl R; DeBlaere, Cirleen; Choe, Elise; Worthington, Everett L

2015-07-01

Most measures of spirituality privilege religious spirituality, but people may experience spirituality in a variety of ways, including a sense of closeness, oneness, or connection with a theistic being, the transcendent (i.e., something outside space and time), oneself, humanity, or nature. The overall purpose of the present 4 studies was to develop the Sources of Spirituality (SOS) Scale to measure these different elements of spirituality. In Study 1, we created items, had them reviewed by experts, and used data from a sample of undergraduates (N = 218) to evaluate factor structure and inform initial measurement revisions. The factor structure replicated well in another sample of undergraduates (N = 200; Study 2), and in a sample of community adults (N = 140; Study 3). In a sample of undergraduates (N = 200; Study 4), we then evaluated evidence of construct validity by examining associations between SOS Scale scores and religious commitment, positive attitudes toward the Sacred, and dispositional connection with nature. Moreover, based on latent profile analyses results, we found 5 distinct patterns of spirituality based on SOS subscales. We consider implications for therapy and relevance of the findings for models of spirituality and future research. (c) 2015 APA, all rights reserved).

On the Reliability of Individual Brain Activity Networks.

PubMed

Cassidy, Ben; Bowman, F DuBois; Rae, Caroline; Solo, Victor

2018-02-01

There is intense interest in fMRI research on whole-brain functional connectivity, and however, two fundamental issues are still unresolved: the impact of spatiotemporal data resolution (spatial parcellation and temporal sampling) and the impact of the network construction method on the reliability of functional brain networks. In particular, the impact of spatiotemporal data resolution on the resulting connectivity findings has not been sufficiently investigated. In fact, a number of studies have already observed that functional networks often give different conclusions across different parcellation scales. If the interpretations from functional networks are inconsistent across spatiotemporal scales, then the whole validity of the functional network paradigm is called into question. This paper investigates the consistency of resting state network structure when using different temporal sampling or spatial parcellation, or different methods for constructing the networks. To pursue this, we develop a novel network comparison framework based on persistent homology from a topological data analysis. We use the new network comparison tools to characterize the spatial and temporal scales under which consistent functional networks can be constructed. The methods are illustrated on Human Connectome Project data, showing that the DISCOH 2 network construction method outperforms other approaches at most data spatiotemporal resolutions.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

PubMed Central

Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

2015-01-01

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

Establishing a link between sex-related differences in the structural connectome and behaviour.

PubMed

Tunç, Birkan; Solmaz, Berkan; Parker, Drew; Satterthwaite, Theodore D; Elliott, Mark A; Calkins, Monica E; Ruparel, Kosha; Gur, Raquel E; Gur, Ruben C; Verma, Ragini

2016-02-19

Recent years have witnessed an increased attention to studies of sex differences, partly because such differences offer important considerations for personalized medicine. While the presence of sex differences in human behaviour is well documented, our knowledge of their anatomical foundations in the brain is still relatively limited. As a natural gateway to fathom the human mind and behaviour, studies concentrating on the human brain network constitute an important segment of the research effort to investigate sex differences. Using a large sample of healthy young individuals, each assessed with diffusion MRI and a computerized neurocognitive battery, we conducted a comprehensive set of experiments examining sex-related differences in the meso-scale structures of the human connectome and elucidated how these differences may relate to sex differences at the level of behaviour. Our results suggest that behavioural sex differences, which indicate complementarity of males and females, are accompanied by related differences in brain structure across development. When using subnetworks that are defined over functional and behavioural domains, we observed increased structural connectivity related to the motor, sensory and executive function subnetworks in males. In females, subnetworks associated with social motivation, attention and memory tasks had higher connectivity. Males showed higher modularity compared to females, with females having higher inter-modular connectivity. Applying multivariate analysis, we showed an increasing separation between males and females in the course of development, not only in behavioural patterns but also in brain structure. We also showed that these behavioural and structural patterns correlate with each other, establishing a reliable link between brain and behaviour. © 2016 The Author(s).

The Value of Sharing Information: A Neural Account of Information Transmission.

PubMed

Baek, Elisa C; Scholz, Christin; O'Donnell, Matthew Brook; Falk, Emily B

2017-07-01

Humans routinely share information with one another. What drives this behavior? We used neuroimaging to test an account of information selection and sharing that emphasizes inherent reward in self-reflection and connecting with other people. Participants underwent functional MRI while they considered personally reading and sharing New York Times articles. Activity in neural regions involved in positive valuation, self-related processing, and taking the perspective of others was significantly associated with decisions to select and share articles, and scaled with preferences to do so. Activity in all three sets of regions was greater when participants considered sharing articles with other people rather than selecting articles to read themselves. The findings suggest that people may consider value not only to themselves but also to others even when selecting news articles to consume personally. Further, sharing heightens activity in these pathways, in line with our proposal that humans derive value from self-reflection and connecting to others via sharing.

Enhanced functional connectivity properties of human brains during in-situ nature experience

PubMed Central

2016-01-01

In this study, we investigated the impacts of in-situ nature and urban exposure on human brain activities and their dynamics. We randomly assigned 32 healthy right-handed college students (mean age = 20.6 years, SD = 1.6; 16 males) to a 20 min in-situ sitting exposure in either a nature (n = 16) or urban environment (n = 16) and measured their Electroencephalography (EEG) signals. Analyses revealed that a brief in-situ restorative nature experience may induce more efficient and stronger brain connectivity with enhanced small-world properties compared with a stressful urban experience. The enhanced small-world properties were found to be correlated with “coherent” experience measured by Perceived Restorativeness Scale (PRS). Exposure to nature also induces stronger long-term correlated activity across different brain regions with a right lateralization. These findings may advance our understanding of the functional activities during in-situ environmental exposures and imply that a nature or nature-like environment may potentially benefit cognitive processes and mental well-being. PMID:27547533

Counting on β-Diversity to Safeguard the Resilience of Estuaries

PubMed Central

de Juan, Silvia; Thrush, Simon F.; Hewitt, Judi E.

2013-01-01

Coastal ecosystems are often stressed by non-point source and cumulative effects that can lead to local-scale community homogenisation and a concomitant loss of large-scale ecological connectivity. Here we investigate the use of β-diversity as a measure of both community heterogeneity and ecological connectivity. To understand the consequences of different environmental scenarios on heterogeneity and connectivity, it is necessary to understand the scale at which different environmental factors affect β-diversity. We sampled macrofauna from intertidal sites in nine estuaries from New Zealand’s North Island that represented different degrees of stress derived from land-use. We used multiple regression models to identify relationships between β-diversity and local sediment variables, factors related to the estuarine and catchment hydrodynamics and morphology and land-based stressors. At local scales, we found higher β-diversity at sites with a relatively high total richness. At larger scales, β-diversity was positively related to γ-diversity, suggesting that a large regional species pool was linked with large-scale heterogeneity in these systems. Local environmental heterogeneity influenced β-diversity at both local and regional scales, although variables at the estuarine and catchment scales were both needed to explain large scale connectivity. The estuaries expected a priori to be the most stressed exhibited higher variance in community dissimilarity between sites and connectivity to the estuary species pool. This suggests that connectivity and heterogeneity metrics could be used to generate early warning signals of cumulative stress. PMID:23755252

Scale effect on overland flow connectivity at the plot scale

NASA Astrophysics Data System (ADS)

Peñuela, A.; Javaux, M.; Bielders, C. L.

2012-06-01

A major challenge in present-day hydrological sciences is to enhance the performance of existing distributed hydrological models through a better description of subgrid processes, in particular the subgrid connectivity of flow paths. The relative surface connection function (RSC) was proposed by Antoine et al. (2009) as a functional indicator of runoff flow connectivity. For a given area, it expresses the percentage of the surface connected to the outflow boundary (C) as a function of the degree of filling of the depression storage. This function explicitly integrates the flow network at the soil surface and hence provides essential information regarding the flow paths' connectivity. It has been shown that this function could help improve the modeling of the hydrogram at the square meter scale, yet it is unknown how the scale affects the RSC function, and whether and how it can be extrapolated to other scales. The main objective of this research is to study the scale effect on overland flow connectivity (RSC function). For this purpose, digital elevation data of a real field (9 × 3 m) and three synthetic fields (6 × 6 m) with contrasting hydrological responses were used, and the RSC function was calculated at different scales by changing the length (l) or width (w) of the field. Border effects, at different extents depending on the microtopography, were observed for the smaller scales, when decreasing l or w, which resulted in a strong decrease or increase of the maximum depression storage, respectively. There was no scale effect on the RSC function when changing w. On the contrary, a remarkable scale effect was observed in the RSC function when changing l. In general, for a given degree of filling of the depression storage, C decreased as l increased. This change in C was inversely proportional to the change in l. This observation applied only up to approx. 50-70% (depending on the hydrological response of the field) of filling of depression storage, after which no correlation was found between C and l. The results of this study help identify the minimal scale to study overland flow connectivity. At scales larger than the minimal scale, the RSC function showed a great potential to be extrapolated to other scales.

Scale effect on overland flow connectivity at the plot scale

NASA Astrophysics Data System (ADS)

Peñuela, A.; Javaux, M.; Bielders, C. L.

2013-01-01

A major challenge in present-day hydrological sciences is to enhance the performance of existing distributed hydrological models through a better description of subgrid processes, in particular the subgrid connectivity of flow paths. The Relative Surface Connection (RSC) function was proposed by Antoine et al. (2009) as a functional indicator of runoff flow connectivity. For a given area, it expresses the percentage of the surface connected to the outflow boundary (C) as a function of the degree of filling of the depression storage. This function explicitly integrates the flow network at the soil surface and hence provides essential information regarding the flow paths' connectivity. It has been shown that this function could help improve the modeling of the hydrograph at the square meter scale, yet it is unknown how the scale affects the RSC function, and whether and how it can be extrapolated to other scales. The main objective of this research is to study the scale effect on overland flow connectivity (RSC function). For this purpose, digital elevation data of a real field (9 × 3 m) and three synthetic fields (6 × 6 m) with contrasting hydrological responses were used, and the RSC function was calculated at different scales by changing the length (l) or width (w) of the field. To different extents depending on the microtopography, border effects were observed for the smaller scales when decreasing l or w, which resulted in a strong decrease or increase of the maximum depression storage, respectively. There was no scale effect on the RSC function when changing w, but a remarkable scale effect was observed in the RSC function when changing l. In general, for a given degree of filling of the depression storage, C decreased as l increased, the change in C being inversely proportional to the change in l. However, this observation applied only up to approx. 50-70% (depending on the hydrological response of the field) of filling of depression storage, after which no correlation was found between C and l. The results of this study help identify the minimal scale to study overland flow connectivity. At scales larger than the minimal scale, the RSC function showed a great potential to be extrapolated to other scales.

Deconstructing white matter connectivity of human amygdala nuclei with thalamus and cortex subdivisions in vivo

PubMed Central

2017-01-01

Abstract Structural alterations in long‐range amygdala connections are proposed to crucially underlie several neuropsychiatric disorders. While progress has been made in elucidating the function of these connections, our understanding of their structure in humans remains sparse and non‐systematic. Harnessing diffusion‐weighted imaging and probabilistic tractography in humans, we investigate connections between two main amygdala nucleus groups, thalamic nuclei, and cortex. We first parcellated amygdala into deep (basolateral) and superficial (centrocortical) nucleus groups, and thalamus into six subregions, using previously established protocols based on connectivity. Cortex was parcellated based on T1‐weighted images. We found substantial amygdala connections to thalamus, with different patterns for the two amygdala nuclei. Crucially, we describe direct subcortical connections between amygdala and paraventricular thalamus. Different from rodents but similar to non‐human primates, these are more pronounced for basolateral than centrocortical amygdala. Substantial white‐matter connectivity between amygdala and visual pulvinar is also more pronounced for basolateral amygdala. Furthermore, we establish detailed connectivity profiles for basolateral and centrocortical amygdala to cortical regions. These exhibit cascadic connections with sensory cortices as suggested previously based on tracer methods in non‐human animals. We propose that the quantitative connectivity profiles provided here may guide future work on normal and pathological function of human amygdala. Hum Brain Mapp 38:3927–3940, 2017. © 2017 Wiley Periodicals, Inc. PMID:28512761

Experimental study on the connection property of full-scale composite member

NASA Astrophysics Data System (ADS)

Panpan, Cao; Qing, Sun

2018-01-01

The excellent properties of composite result in its increasingly application in electric power construction, however there are less experimental studies on full-scale composite member connection property. Full-scale experiments of the connection property between E-glass fiber/epoxy reinforced polymer member and steel casing in practical engineering have been conducted. Based on the axial compression test of the designed specimens, the failure process and failure characteristics were observed, the load-displacement curves and strain distribution of the specimens were obtained. The finite element analysis was used to get the tensile connection strength of the component. The connection property of the components was analyzed to provide basis of the casing connection of GFRP application in practical engineering.

Distant storms as drivers of environmental change at Pacific atolls.

PubMed

Gardner, Jonathan P A; Garton, David W; Collen, John D; Zwartz, Daniel

2014-01-01

The central Pacific Ocean with its many low lying islands and atolls is under threat from sea level rise and increased storm activity. Here, we illustrate how increasing frequency and severity of large scale storm events associated with global climate change may be particularly profound at the local scale for human populations that rely on lagoon systems for provision of a variety of goods and services. In August 2011 a storm originating in the Southern Ocean caused a large amplitude ocean swell to move northward through the Pacific Ocean. Its arrival at Palmyra Atoll coincided with transient elevated sea surface height and triggered turnover of the lagoon water column. This storm-induced change to the lagoon reflects long distance connectivity with propagated wave energy from the Southern Ocean and illustrates the increasing threats generated by climate change that are faced by human populations on most low-lying Pacific islands and atolls.

Distant Storms as Drivers of Environmental Change at Pacific Atolls

PubMed Central

Gardner, Jonathan P. A.; Garton, David W.; Collen, John D.; Zwartz, Daniel

2014-01-01

The central Pacific Ocean with its many low lying islands and atolls is under threat from sea level rise and increased storm activity. Here, we illustrate how increasing frequency and severity of large scale storm events associated with global climate change may be particularly profound at the local scale for human populations that rely on lagoon systems for provision of a variety of goods and services. In August 2011 a storm originating in the Southern Ocean caused a large amplitude ocean swell to move northward through the Pacific Ocean. Its arrival at Palmyra Atoll coincided with transient elevated sea surface height and triggered turnover of the lagoon water column. This storm-induced change to the lagoon reflects long distance connectivity with propagated wave energy from the Southern Ocean and illustrates the increasing threats generated by climate change that are faced by human populations on most low-lying Pacific islands and atolls. PMID:24498232

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

PubMed

Romero-Garcia, Rafael; Whitaker, Kirstie J; Váša, František; Seidlitz, Jakob; Shinn, Maxwell; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T; Vértes, Petra E

2018-05-01

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Scale effect on overland flow connectivity, at the interill scale

NASA Astrophysics Data System (ADS)

Penuela Fernandez, A.; Bielders, C.; Javaux, M.

2012-04-01

The relative surface connection function (RSC) was proposed by Antoine et al. (2009) as a functional indicator of runoff flow connectivity. For a given area, it expresses the percentage of the surface connected to the outlet (C) as a function of the degree of filling of the depression storage. This function explicitly integrates the flow network at the soil surface and hence provides essential information regarding the flow paths' connectivity. It has been shown that this function could help improve the modeling of the hydrogram at the square meter scale, yet it is unknown how the scale affects the RSC function, and whether and how it can be extrapolated to other scales. The main objective of this research is to study the scale effect on overland flow connectivity (RSC function). For this purpose, digital elevation data of a real field (9 x 3 m) and three synthetic fields (6 x 6 m) with contrasting hydrological responses was used, and the RSC function was calculated at different scales by changing the length (L) or width (l) of the field. Border effects were observed for the smaller scales. In most of cases, for L or l smaller than 750mm, increasing L or l, resulted in a strong increase or decrease of the maximum depression storage, respectively. There was no scale effect on the RSC function when changing l. On the contrary, a remarkable scale effect was observed in the RSC function when changing L. In general, for a given degree of filling of the depression storage, C decreased as L increased. This change in C was inversely proportional to the change in L. This observation applied only up to approx. 50-70% (depending on the hydrological response of the field) of filling of depression storage, after which no correlation was found between C and L. The results of this study help identify the critical scale to study overland flow connectivity. At scales larger than the critical scale, the RSC function showed a great potential to be extrapolated to other scales.

Multi-scale connectivity and graph theory highlight critical areas for conservation under climate change

USGS Publications Warehouse

Dilts, Thomas E.; Weisberg, Peter J.; Leitner, Phillip; Matocq, Marjorie D.; Inman, Richard D.; Nussear, Ken E.; Esque, Todd C.

2016-01-01

Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land-use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multi-scale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods including graph theory, circuit theory and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this California threatened species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American Southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously-distributed habitat, and should be applicable across a broad range of taxa.

The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.

PubMed

Djurfeldt, Mikael

2012-07-01

The connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in neuronal network models, from small-scale to large-scale structure. The algebra provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA is expressive enough to describe a wide range of connection patterns, including multiple types of random and/or geometrically dependent connectivity, and can serve as a concise notation for network structure in scientific writing. CSA implementations allow for scalable and efficient representation of connectivity in parallel neuronal network simulators and could even allow for avoiding explicit representation of connections in computer memory. The expressiveness of CSA makes prototyping of network structure easy. A C+ + version of the algebra has been implemented and used in a large-scale neuronal network simulation (Djurfeldt et al., IBM J Res Dev 52(1/2):31-42, 2008b) and an implementation in Python has been publicly released.

Resting-State fMRI Functional Connectivity Is Associated with Sleepiness, Imagery, and Discontinuity of Mind

PubMed Central

Chen, Gang; den Braber, Anouk; van ‘t Ent, Dennis; Boomsma, Dorret I.; Mansvelder, Huibert D.; de Geus, Eco; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

2015-01-01

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies. PMID:26540239

Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views.

PubMed

Sutterer, Matthew J; Tranel, Daniel

2017-11-01

We highlight the past 25 years of cognitive neuroscience and neuropsychology, focusing on the impact to the field of the introduction in 1992 of functional MRI (fMRI). We reviewed the past 25 years of literature in cognitive neuroscience and neuropsychology, focusing on the relation and interplay of fMRI studies and studies utilizing the "lesion method" in human participants with focal brain damage. Our review highlights the state of localist/connectionist research debates in cognitive neuroscience and neuropsychology circa 1992, and details how the introduction of fMRI into the field at that time catalyzed a new wave of efforts to map complex human behavior to specific brain regions. This, in turn, eventually evolved into many studies that focused on networks and connections between brain areas, culminating in recent years with large-scale investigations such as the Human Connectome Project. We argue that throughout the past 25 years, neuropsychology-and more precisely, the "lesion method" in humans-has continued to play a critical role in arbitrating conclusions and theories derived from inferred patterns of local brain activity or wide-spread connectivity from functional imaging approaches. We conclude by highlighting the future for neuropsychology in the context of an increasingly complex methodological armamentarium. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Using multitype branching processes to quantify statistics of disease outbreaks in zoonotic epidemics

NASA Astrophysics Data System (ADS)

Singh, Sarabjeet; Schneider, David J.; Myers, Christopher R.

2014-03-01

Branching processes have served as a model for chemical reactions, biological growth processes, and contagion (of disease, information, or fads). Through this connection, these seemingly different physical processes share some common universalities that can be elucidated by analyzing the underlying branching process. In this work we focus on coupled branching processes as a model of infectious diseases spreading from one population to another. An exceedingly important example of such coupled outbreaks are zoonotic infections that spill over from animal populations to humans. We derive several statistical quantities characterizing the first spillover event from animals to humans, including the probability of spillover, the first passage time distribution for human infection, and disease prevalence in the animal population at spillover. Large stochastic fluctuations in those quantities can make inference of the state of the system at the time of spillover difficult. Focusing on outbreaks in the human population, we then characterize the critical threshold for a large outbreak, the distribution of outbreak sizes, and associated scaling laws. These all show a strong dependence on the basic reproduction number in the animal population and indicate the existence of a novel multicritical point with altered scaling behavior. The coupling of animal and human infection dynamics has crucial implications, most importantly allowing for the possibility of large human outbreaks even when human-to-human transmission is subcritical.

Process connectivity in a naturally prograding river delta

NASA Astrophysics Data System (ADS)

Sendrowski, Alicia; Passalacqua, Paola

2017-03-01

River deltas are lowland systems that can display high hydrological connectivity. This connectivity can be structural (morphological connections), functional (control of fluxes), and process connectivity (information flow from system drivers to sinks). In this work, we quantify hydrological process connectivity in Wax Lake Delta, coastal Louisiana, by analyzing couplings among external drivers (discharge, tides, and wind) and water levels recorded at five islands and one channel over summer 2014. We quantify process connections with information theory, a branch of mathematics concerned with the communication of information. We represent process connections as a network; variables serve as network nodes and couplings as network links describing the strength, direction, and time scale of information flow. Comparing process connections at long (105 days) and short (10 days) time scales, we show that tides exhibit daily synchronization with water level, with decreasing strength from downstream to upstream, and that tides transfer information as tides transition from spring to neap. Discharge synchronizes with water level and the time scale of its information transfer compares well to physical travel times through the system, computed with a hydrodynamic model. Information transfer and physical transport show similar spatial patterns, although information transfer time scales are larger than physical travel times. Wind events associated with water level setup lead to increased process connectivity with highly variable information transfer time scales. We discuss the information theory results in the context of the hydrologic behavior of the delta, the role of vegetation as a connector/disconnector on islands, and the applicability of process networks as tools for delta modeling results.

Understanding metropolitan patterns of daily encounters.

PubMed

Sun, Lijun; Axhausen, Kay W; Lee, Der-Horng; Huang, Xianfeng

2013-08-20

Understanding of the mechanisms driving our daily face-to-face encounters is still limited; the field lacks large-scale datasets describing both individual behaviors and their collective interactions. However, here, with the help of travel smart card data, we uncover such encounter mechanisms and structures by constructing a time-resolved in-vehicle social encounter network on public buses in a city (about 5 million residents). Using a population scale dataset, we find physical encounters display reproducible temporal patterns, indicating that repeated encounters are regular and identical. On an individual scale, we find that collective regularities dominate distinct encounters' bounded nature. An individual's encounter capability is rooted in his/her daily behavioral regularity, explaining the emergence of "familiar strangers" in daily life. Strikingly, we find individuals with repeated encounters are not grouped into small communities, but become strongly connected over time, resulting in a large, but imperceptible, small-world contact network or "structure of co-presence" across the whole metropolitan area. Revealing the encounter pattern and identifying this large-scale contact network are crucial to understanding the dynamics in patterns of social acquaintances, collective human behaviors, and--particularly--disclosing the impact of human behavior on various diffusion/spreading processes.

Understanding metropolitan patterns of daily encounters

PubMed Central

Sun, Lijun; Axhausen, Kay W.; Lee, Der-Horng; Huang, Xianfeng

2013-01-01

Understanding of the mechanisms driving our daily face-to-face encounters is still limited; the field lacks large-scale datasets describing both individual behaviors and their collective interactions. However, here, with the help of travel smart card data, we uncover such encounter mechanisms and structures by constructing a time-resolved in-vehicle social encounter network on public buses in a city (about 5 million residents). Using a population scale dataset, we find physical encounters display reproducible temporal patterns, indicating that repeated encounters are regular and identical. On an individual scale, we find that collective regularities dominate distinct encounters’ bounded nature. An individual’s encounter capability is rooted in his/her daily behavioral regularity, explaining the emergence of “familiar strangers” in daily life. Strikingly, we find individuals with repeated encounters are not grouped into small communities, but become strongly connected over time, resulting in a large, but imperceptible, small-world contact network or “structure of co-presence” across the whole metropolitan area. Revealing the encounter pattern and identifying this large-scale contact network are crucial to understanding the dynamics in patterns of social acquaintances, collective human behaviors, and—particularly—disclosing the impact of human behavior on various diffusion/spreading processes. PMID:23918373

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

Functional organization of intrinsic connectivity networks in Chinese-chess experts.

PubMed

Duan, Xujun; Long, Zhiliang; Chen, Huafu; Liang, Dongmei; Qiu, Lihua; Huang, Xiaoqi; Liu, Timon Cheng-Yi; Gong, Qiyong

2014-04-16

The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

The detailed 3D multi-loop aggregate/rosette chromatin architecture and functional dynamic organization of the human and mouse genomes.

PubMed

Knoch, Tobias A; Wachsmuth, Malte; Kepper, Nick; Lesnussa, Michael; Abuseiris, Anis; Ali Imam, A M; Kolovos, Petros; Zuin, Jessica; Kockx, Christel E M; Brouwer, Rutger W W; van de Werken, Harmen J G; van IJcken, Wilfred F J; Wendt, Kerstin S; Grosveld, Frank G

2016-01-01

The dynamic three-dimensional chromatin architecture of genomes and its co-evolutionary connection to its function-the storage, expression, and replication of genetic information-is still one of the central issues in biology. Here, we describe the much debated 3D architecture of the human and mouse genomes from the nucleosomal to the megabase pair level by a novel approach combining selective high-throughput high-resolution chromosomal interaction capture ( T2C ), polymer simulations, and scaling analysis of the 3D architecture and the DNA sequence. The genome is compacted into a chromatin quasi-fibre with ~5 ± 1 nucleosomes/11 nm, folded into stable ~30-100 kbp loops forming stable loop aggregates/rosettes connected by similar sized linkers. Minor but significant variations in the architecture are seen between cell types and functional states. The architecture and the DNA sequence show very similar fine-structured multi-scaling behaviour confirming their co-evolution and the above. This architecture, its dynamics, and accessibility, balance stability and flexibility ensuring genome integrity and variation enabling gene expression/regulation by self-organization of (in)active units already in proximity. Our results agree with the heuristics of the field and allow "architectural sequencing" at a genome mechanics level to understand the inseparable systems genomic properties.

DIFFUSION-WEIGHTED IMAGING TRACTOGRAPHY-BASED PARCELLATION OF THE HUMAN PARIETAL CORTEX AND COMPARISON WITH HUMAN AND MACAQUE RESTING STATE FUNCTIONAL CONNECTIVITY

PubMed Central

Mars, Rogier B.; Jbabdi, Saad; Sallet, Jérôme; O’Reilly, Jill X.; Croxson, Paula L.; Olivier, Etienne; Noonan, MaryAnn P.; Bergmann, Caroline; Mitchell, Anna S.; Baxter, Mark G.; Behrens, Timothy E.J.; Johansen-Berg, Heidi; Tomassini, Valentina; Miller, Karla L.; Rushworth, Matthew F.S.

2011-01-01

Despite the prominence of parietal activity in human neuromaging investigations of sensorimotor and cognitive processes there remains uncertainty about basic aspects of parietal cortical anatomical organization. Descriptions of human parietal cortex draw heavily on anatomical schemes developed in other primate species but the validity of such comparisons has been questioned by claims that there are fundamental differences between the parietal cortex in humans and other primates. A scheme is presented for parcellation of human lateral parietal cortex into component regions on the basis of anatomical connectivity and the functional interactions of the resulting clusters with other brain regions. Anatomical connectivity was estimated using diffusion-weighted magnetic resonance image (MRI) based tractography and functional interactions were assessed by correlations in activity measured with functional MRI (fMRI) at rest. Resting state functional connectivity was also assessed directly in the rhesus macaque lateral parietal cortex in an additional experiment and the patterns found reflected known neuroanatomical connections. Cross-correlation in the tractography-based connectivity patterns of parietal voxels reliably parcellated human lateral parietal cortex into ten component clusters. The resting state functional connectivity of human superior parietal and intraparietal clusters with frontal and extrastriate cortex suggested correspondences with areas in macaque superior and intraparietal sulcus. Functional connectivity patterns with parahippocampal cortex and premotor cortex again suggested fundamental correspondences between inferior parietal cortex in humans and macaques. In contrast, the human parietal cortex differs in the strength of its interactions between the central inferior parietal lobule region and the anterior prefrontal cortex. PMID:21411650

Psychological impact of the animal-human bond in disaster preparedness and response.

PubMed

Hall, Molly J; Ng, Anthony; Ursano, Robert J; Holloway, Harry; Fullerton, Carol; Casper, Jacob

2004-11-01

The authors present an overview of the impact of the animal-human bond on disaster management and highlight the need to further examine the relationship of animals and humans in disaster response. The human connection to animals influences compliance with individual and community evacuation plans. Search and rescue teams with canine units confront physical and emotional demands that affect both handler and animal. The culling of animal populations on a scale such as occurred during the recent foot-and-mouth epidemic in the United Kingdom affects every member of rural society. Livestock farmers and their families endure enormous emotional losses, and veterinarians and government officials who must implement these programs suffer as well. A familiarity with and understanding of these issues is important for psychiatrists and other mental health professionals who are involved in disaster preparedness and response.

Computational Models for Understanding of Structure, Function and Pharmacology of the Cardiac Potassium Channel Kv11.1 (hERG).

PubMed

Wacker, Soren; Noskov, Sergei Yu; Perissinotti, Laura L

2017-01-01

The rapid delayed rectifier current IKr is one of the major K+ currents involved in repolarization of the human cardiac action potential. Various inherited or drug-induced forms of the long QT syndrome (LQTS) in humans are linked to functional and structural modifications in the IKr conducting channels. IKr is carried by the potassium channel Kv11.1 encoded by the gene KCNH2 (commonly referred to as human ether-a-go-go-related gene or hERG) [1, 2]. The first necessary step for predicting emergent drug effects on the heart is determining and modeling the binding thermodynamics and kinetics of primary and major off-target drug interactions with subcellular targets. The bulk of drugs that target hERG channels are known to have complex interactions at the atomic scale. Accordingly, one of the goals for this review is to provide comprehensive guide in the universe of computational models aiming to refine our understanding of structure-function relations in Kv11.1 and its isoforms. The special emphasis is placed on the mapping of drug binding sites and tentative mechanisms of channel inhibition and activation by drugs. An overview over recent structural models and mapping of binding sites for blockers and activators of IKr current along with the discussion on agreements and discrepancies among different models is presented. There is an apparent reciprocity or feedback loop between drug binding and action potential of the cardiac myocytes. Thus one has to connect drug binding to a particular receptor so that its functional consequences impact on the action potential duration. The natural pathway is to develop multi-scale models that connect between receptor and cellular scales. The potential for such multi-scale model development is discussed through the lens of common gating models. Accordingly, the second part of this review covers an ongoing development of the kinetic models of gating transitions and cardiac ion currents carried by hERG channels with and without drug bound. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

On being the right size: scaling effects in designing a human-on-a-chip

PubMed Central

Moraes, Christopher; Labuz, Joseph M.; Leung, Brendan M.; Inoue, Mayumi; Chun, Tae-Hwa; Takayama, Shuichi

2013-01-01

Developing a human-on-a-chip by connecting multiple model organ systems would provide an intermediate screen for therapeutic efficacy and toxic side effects of drugs prior to conducting expensive clinical trials. However, correctly designing individual organs and scaling them relative to each other to make a functional microscale human analog is challenging, and a generalized approach has yet to be identified. In this work, we demonstrate the importance of rational design of both the individual organ and its relationship with other organs, using a simple two-compartment system simulating insulin-dependent glucose uptake in adipose tissues. We demonstrate that inter-organ scaling laws depend on both the number of cells, and on the spatial arrangement of those cells within the microfabricated construct. We then propose a simple and novel inter-organ ‘metabolically-supported functional scaling’ approach predicated on maintaining in vivo cellular basal metabolic rates, by limiting resources available to cells on the chip. This approach leverages findings from allometric scaling models in mammals that limited resources in vivo prompts cells to behave differently than in resource-rich in vitro cultures. Although applying scaling laws directly to tissues can result in systems that would be quite challenging to implement, engineering workarounds may be used to circumvent these scaling issues. Specific workarounds discussed include the limited oxygen carrying capacity of cell culture media when used as a blood substitute and the ability to engineer non-physiological structures to augment organ function, to create the transport-accessible, yet resource-limited environment necessary for cells to mimic in vivo functionality. Furthermore, designing the structure of individual tissues in each organ compartment may be a useful strategy to bypass scaling concerns at the inter-organ level. PMID:23925524

A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology

PubMed Central

Harte, Richard; Glynn, Liam; Rodríguez-Molinero, Alejandro; Baker, Paul MA; Scharf, Thomas; ÓLaighin, Gearóid

2017-01-01

Background Design processes such as human-centered design, which involve the end user throughout the product development and testing process, can be crucial in ensuring that the product meets the needs and capabilities of the user, particularly in terms of safety and user experience. The structured and iterative nature of human-centered design can often present a challenge when design teams are faced with the necessary, rapid, product development life cycles associated with the competitive connected health industry. Objective We wanted to derive a structured methodology that followed the principles of human-centered design that would allow designers and developers to ensure that the needs of the user are taken into account throughout the design process, while maintaining a rapid pace of development. In this paper, we present the methodology and its rationale before outlining how it was applied to assess and enhance the usability, human factors, and user experience of a connected health system known as the Wireless Insole for Independent and Safe Elderly Living (WIISEL) system, a system designed to continuously assess fall risk by measuring gait and balance parameters associated with fall risk. Methods We derived a three-phase methodology. In Phase 1 we emphasized the construction of a use case document. This document can be used to detail the context of use of the system by utilizing storyboarding, paper prototypes, and mock-ups in conjunction with user interviews to gather insightful user feedback on different proposed concepts. In Phase 2 we emphasized the use of expert usability inspections such as heuristic evaluations and cognitive walkthroughs with small multidisciplinary groups to review the prototypes born out of the Phase 1 feedback. Finally, in Phase 3 we emphasized classical user testing with target end users, using various metrics to measure the user experience and improve the final prototypes. Results We report a successful implementation of the methodology for the design and development of a system for detecting and predicting falls in older adults. We describe in detail what testing and evaluation activities we carried out to effectively test the system and overcome usability and human factors problems. Conclusions We feel this methodology can be applied to a wide variety of connected health devices and systems. We consider this a methodology that can be scaled to different-sized projects accordingly. PMID:28302594

Large-scale degradation of Amazonian freshwater ecosystems.

PubMed

Castello, Leandro; Macedo, Marcia N

2016-03-01

Hydrological connectivity regulates the structure and function of Amazonian freshwater ecosystems and the provisioning of services that sustain local populations. This connectivity is increasingly being disrupted by the construction of dams, mining, land-cover changes, and global climate change. This review analyzes these drivers of degradation, evaluates their impacts on hydrological connectivity, and identifies policy deficiencies that hinder freshwater ecosystem protection. There are 154 large hydroelectric dams in operation today, and 21 dams under construction. The current trajectory of dam construction will leave only three free-flowing tributaries in the next few decades if all 277 planned dams are completed. Land-cover changes driven by mining, dam and road construction, agriculture and cattle ranching have already affected ~20% of the Basin and up to ~50% of riparian forests in some regions. Global climate change will likely exacerbate these impacts by creating warmer and dryer conditions, with less predictable rainfall and more extreme events (e.g., droughts and floods). The resulting hydrological alterations are rapidly degrading freshwater ecosystems, both independently and via complex feedbacks and synergistic interactions. The ecosystem impacts include biodiversity loss, warmer stream temperatures, stronger and more frequent floodplain fires, and changes to biogeochemical cycles, transport of organic and inorganic materials, and freshwater community structure and function. The impacts also include reductions in water quality, fish yields, and availability of water for navigation, power generation, and human use. This degradation of Amazonian freshwater ecosystems cannot be curbed presently because existing policies are inconsistent across the Basin, ignore cumulative effects, and overlook the hydrological connectivity of freshwater ecosystems. Maintaining the integrity of these freshwater ecosystems requires a basinwide research and policy framework to understand and manage hydrological connectivity across multiple spatial scales and jurisdictional boundaries. © 2015 John Wiley & Sons Ltd.

The scaling of human interactions with city size

PubMed Central

Schläpfer, Markus; Bettencourt, Luís M. A.; Grauwin, Sébastian; Raschke, Mathias; Claxton, Rob; Smoreda, Zbigniew; West, Geoffrey B.; Ratti, Carlo

2014-01-01

The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases. PMID:24990287

Don't fight the site: three geomorphic considerations in catchment-scale river rehabilitation planning.

PubMed

Brierley, Gary; Fryirs, Kirstie

2009-06-01

Three geomorphic considerations that underpin the design and implementation of realistic and strategic river conservation and rehabilitation programs that work with the nature are outlined. First, the importance of appreciating the inherent diversity of river forms and processes is discussed. Second, river dynamics are appraised, framing the contemporary behavioral regime of a reach in relation to system evolution to explain changes to river character and behavior over time. Third, the trajectory of a reach is framed in relation to downstream patterns of river types, analyzing landscape connectivity at the catchment scale to interpret geomorphic river recovery potential. The application of these principles is demonstrated using extensive catchment-scale analyses of geomorphic river responses to human disturbance in the Bega and Upper Hunter catchments in southeastern Australia. Differing implications for reach- and catchment-scale rehabilitation planning prompt the imperative that management practices work with nature rather than strive to 'fight the site.'

Structural and functional connectivity as a driver of hillslope erosion following disturbance

USDA-ARS?s Scientific Manuscript database

Hydrologic response to rainfall input on fragmented or burnt hillslopes is strongly influenced by the ensuing connectivity of runoff and erosion processes. Yet, cross-scale process connectivity is seldom evaluated in field studies due scale limitations in experimental design. This study quantified...

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.

Process Versus Product in Social Learning: Comparative Diffusion Tensor Imaging of Neural Systems for Action Execution–Observation Matching in Macaques, Chimpanzees, and Humans

PubMed Central

Hecht, Erin E.; Gutman, David A.; Preuss, Todd M.; Sanchez, Mar M.; Parr, Lisa A.; Rilling, James K.

2013-01-01

Social learning varies among primate species. Macaques only copy the product of observed actions, or emulate, while humans and chimpanzees also copy the process, or imitate. In humans, imitation is linked to the mirror system. Here we compare mirror system connectivity across these species using diffusion tensor imaging. In macaques and chimpanzees, the preponderance of this circuitry consists of frontal–temporal connections via the extreme/external capsules. In contrast, humans have more substantial temporal–parietal and frontal–parietal connections via the middle/inferior longitudinal fasciculi and the third branch of the superior longitudinal fasciculus. In chimpanzees and humans, but not in macaques, this circuitry includes connections with inferior temporal cortex. In humans alone, connections with superior parietal cortex were also detected. We suggest a model linking species differences in mirror system connectivity and responsivity with species differences in behavior, including adaptations for imitation and social learning of tool use. PMID:22539611

Evolutionary history of human disease genes reveals phenotypic connections and comorbidity among genetic diseases

NASA Astrophysics Data System (ADS)

Park, Solip; Yang, Jae-Seong; Kim, Jinho; Shin, Young-Eun; Hwang, Jihye; Park, Juyong; Jang, Sung Key; Kim, Sanguk

2012-10-01

The extent to which evolutionary changes have impacted the phenotypic relationships among human diseases remains unclear. In this work, we report that phenotypically similar diseases are connected by the evolutionary constraints on human disease genes. Human disease groups can be classified into slowly or rapidly evolving classes, where the diseases in the slowly evolving class are enriched with morphological phenotypes and those in the rapidly evolving class are enriched with physiological phenotypes. Our findings establish a clear evolutionary connection between disease classes and disease phenotypes for the first time. Furthermore, the high comorbidity found between diseases connected by similar evolutionary constraints enables us to improve the predictability of the relative risk of human diseases. We find the evolutionary constraints on disease genes are a new layer of molecular connection in the network-based exploration of human diseases.

Evolutionary history of human disease genes reveals phenotypic connections and comorbidity among genetic diseases.

PubMed

Park, Solip; Yang, Jae-Seong; Kim, Jinho; Shin, Young-Eun; Hwang, Jihye; Park, Juyong; Jang, Sung Key; Kim, Sanguk

2012-01-01

The extent to which evolutionary changes have impacted the phenotypic relationships among human diseases remains unclear. In this work, we report that phenotypically similar diseases are connected by the evolutionary constraints on human disease genes. Human disease groups can be classified into slowly or rapidly evolving classes, where the diseases in the slowly evolving class are enriched with morphological phenotypes and those in the rapidly evolving class are enriched with physiological phenotypes. Our findings establish a clear evolutionary connection between disease classes and disease phenotypes for the first time. Furthermore, the high comorbidity found between diseases connected by similar evolutionary constraints enables us to improve the predictability of the relative risk of human diseases. We find the evolutionary constraints on disease genes are a new layer of molecular connection in the network-based exploration of human diseases.

Responses to climate change in hot desert ecosystems: connecting local to global scales

USDA-ARS?s Scientific Manuscript database

The consequences of connectivity in resources, propagules, and information to the interplay between drivers and responses across scales can result in ecological dynamics that are not easily predicted based on local drivers. Three major classes of connectivity events link local ecological dynamics wi...

Anatomical connectivity influences both intra- and inter-brain synchronizations.

PubMed

Dumas, Guillaume; Chavez, Mario; Nadel, Jacqueline; Martinerie, Jacques

2012-01-01

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

Human development XIII: the connection between the structure of the overtone system and the tone language of music. Some implications for our understanding of the human brain.

PubMed

Ventegodt, Søren; Hermansen, Tyge Dahl; Kandel, Isack; Merrick, Joav

2008-07-13

The functioning brain behaves like one highly-structured, coherent, informational field. It can be popularly described as a "coherent ball of energy", making the idea of a local highly-structured quantum field that carries the consciousness very appealing. If that is so, the structure of the experience of music might be a quite unique window into a hidden quantum reality of the brain, and even of life itself. The structure of music is then a mirror of a much more complex, but similar, structure of the energetic field of the working brain. This paper discusses how the perception of music is organized in the human brain with respect to the known tone scales of major and minor. The patterns used by the brain seem to be similar to the overtones of vibrating matter, giving a positive experience of harmonies in major. However, we also like the minor scale, which can explain brain patterns as fractal-like, giving a symmetric "downward reflection" of the major scale into the minor scale. We analyze the implication of beautiful and ugly tones and harmonies for the model. We conclude that when it comes to simple perception of harmonies, the most simple is the most beautiful and the most complex is the most ugly, but in music, even the most disharmonic harmony can be beautiful, if experienced as a part of a dynamic release of musical tension. This can be taken as a general metaphor of painful, yet meaningful, and developing experiences in human life.

Human gastric cancer, Helicobacter pylori and bracken carcinogens: A connecting hypothesis.

PubMed

Oliveros-Bastidas, Alberto; Calcagno-Pissarelli, María Pía; Naya, Marlene; Ávila-Núñez, Jorge Luis; Alonso-Amelot, Miguel E

2016-03-01

Long term infection of Helicobacter pylori (Hp) virulent strains is a key factor in the genesis of human gastric cancer, and so are certain dietary proinflammatory and genotoxic compounds. Carcinogenic bracken fern (Pteridium spp.) is one of these. Toxins from this plant are consumed as bracken culinary preparations, through milk and meat of bracken-exposed livestock, and drain waters from bracken swards. Bracken toxin ptaquiloside (PtQ), a suspected human carcinogen, elicits complex responses in animals leading to death. PtQ and Hp might cooperate in gastric pathologies. This paper presents an hypothesis on PtQ-Hp association leading to the enhancement of carcinogenesis in the human gastric environment that might explain the high gastric cancer incidence and death rates among Hp-infected people living in bracken zones at two levels: (1) The macroscopic scale comprising the flow of PtQ in the human diet. (2) the microscopic scale encompassing (A) gastric luminal medium; (B) gastric mucus structure and mucin degradation elicited by Hp; (C) bacterial pH gradient modification of the gastric mucosa that favors PtQ survival and its penetration into epithelial tissue; (D) combined PtQ/Hp effects on gastric immune and inflammatory responses; (E) PtQ-Hp complementary activity at selected cell signaling cascades and genome disturbance. Copyright © 2015 Elsevier Ltd. All rights reserved.

A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems

NASA Astrophysics Data System (ADS)

Poeppl, Ronald E.; Keesstra, Saskia D.; Maroulis, Jerry

2017-01-01

Human-induced landscape change is difficult to predict due to the complexity inherent in both geomorphic and social systems as well as due to the coupling relationships between them. To better understand system complexity and system response to changing inputs, "connectivity thinking" has become an important recent paradigm within various disciplines including ecology, hydrology and geomorphology. With the presented conceptual connectivity framework on geomorphic change in human-impacted fluvial systems a cautionary note is flagged regarding the need (i) to include and to systematically conceptualise the role of different types of human agency in altering connectivity relationships in geomorphic systems and (ii) to integrate notions of human-environment interactions to connectivity concepts in geomorphology to better explain causes and trajectories of landscape change. Geomorphic response of fluvial systems to human disturbance is shown to be determined by system-specific boundary conditions (incl. system history, related legacy effects and lag times), vegetation dynamics and human-induced functional relationships (i.e. feedback mechanisms) between the different spatial dimensions of connectivity. It is further demonstrated how changes in social systems can trigger a process-response feedback loop between social and geomorphic systems that further governs the trajectory of landscape change in coupled human-geomorphic systems.

Understanding the Spatial Scale of Genetic Connectivity at Sea: Unique Insights from a Land Fish and a Meta-Analysis.

PubMed

Cooke, Georgina M; Schlub, Timothy E; Sherwin, William B; Ord, Terry J

2016-01-01

Quantifying the spatial scale of population connectivity is important for understanding the evolutionary potential of ecologically divergent populations and for designing conservation strategies to preserve those populations. For marine organisms like fish, the spatial scale of connectivity is generally set by a pelagic larval phase. This has complicated past estimates of connectivity because detailed information on larval movements are difficult to obtain. Genetic approaches provide a tractable alternative and have the added benefit of estimating directly the reproductive isolation of populations. In this study, we leveraged empirical estimates of genetic differentiation among populations with simulations and a meta-analysis to provide a general estimate of the spatial scale of genetic connectivity in marine environments. We used neutral genetic markers to first quantify the genetic differentiation of ecologically-isolated adult populations of a land dwelling fish, the Pacific leaping blenny (Alticus arnoldorum), where marine larval dispersal is the only probable means of connectivity among populations. We then compared these estimates to simulations of a range of marine dispersal scenarios and to collated FST and distance data from the literature for marine fish across diverse spatial scales. We found genetic connectivity at sea was extensive among marine populations and in the case of A. arnoldorum, apparently little affected by the presence of ecological barriers. We estimated that ~5000 km (with broad confidence intervals ranging from 810-11,692 km) was the spatial scale at which evolutionarily meaningful barriers to gene flow start to occur at sea, although substantially shorter distances are also possible for some taxa. In general, however, such a large estimate of connectivity has important implications for the evolutionary and conservation potential of many marine fish communities.

Human-centric sensing.

PubMed

Srivastava, Mani; Abdelzaher, Tarek; Szymanski, Boleslaw

2012-01-13

The first decade of the century witnessed a proliferation of devices with sensing and communication capabilities in the possession of the average individual. Examples range from camera phones and wireless global positioning system units to sensor-equipped, networked fitness devices and entertainment platforms (such as Wii). Social networking platforms emerged, such as Twitter, that allow sharing information in real time. The unprecedented deployment scale of such sensors and connectivity options ushers in an era of novel data-driven applications that rely on inputs collected by networks of humans or measured by sensors acting on their behalf. These applications will impact domains as diverse as health, transportation, energy, disaster recovery, intelligence and warfare. This paper surveys the important opportunities in human-centric sensing, identifies challenges brought about by such opportunities and describes emerging solutions to these challenges.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis).

PubMed

Allen, Corrie H; Parrott, Lael; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis)

PubMed Central

Allen, Corrie H.; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning. PMID:27168997

Properties of on-line social systems

NASA Astrophysics Data System (ADS)

Grabowski, A.; Kruszewska, N.; Kosiński, R. A.

2008-11-01

We study properties of five different social systems: (i) internet society of friends consisting of over 106 people, (ii) social network consisting of 3 × 104 individuals, who interact in a large virtual world of Massive Multiplayer Online Role Playing Games (MMORPGs), (iii) over 106 users of music community website, (iv) over 5 × 106 users of gamers community server and (v) over 0.25 × 106 users of books admirer website. Individuals included in large social network form an Internet community and organize themselves in groups of different sizes. The destiny of those systems, as well as the method of creating of new connections, are different, however we found that the properties of these networks are very similar. We have found that the network components size distribution follow the power-law scaling form. In all five systems we have found interesting scaling laws concerning human dynamics. Our research has shown how long people are interested in a single task, how much time they devote to it and how fast they are making friends. It is surprising that the time evolution of an individual connectivity is very similar in each system.

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture.

PubMed

Fan, Lingzhong; Li, Hai; Zhuo, Junjie; Zhang, Yu; Wang, Jiaojian; Chen, Liangfu; Yang, Zhengyi; Chu, Congying; Xie, Sangma; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2016-08-01

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states. © The Author 2016. Published by Oxford University Press.

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation

PubMed Central

Griffis, Joseph C.; Elkhetali, Abdurahman S.; Burge, Wesley K.; Chen, Richard H.; Bowman, Anthony D.; Szaflarski, Jerzy P.; Visscher, Kristina M.

2016-01-01

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation. Importantly, our analyses reveal that eccentricity sectors in V1 have different functional connectivity with non-visual areas associated with large-scale brain networks. Regions associated with the fronto-parietal control network are most strongly connected with central sectors of V1, regions associated with the cingulo-opercular control network are most strongly connected with near-peripheral sectors of V1, and regions associated with the default mode and auditory networks are most strongly connected with far-peripheral sectors of V1. Additional analyses suggest that similar patterns are present during eyes-closed rest. These results suggest that different types of visual information may be prioritized by large-scale brain networks with distinct functional profiles, and provide insights into how the small-scale functional specialization within early visual regions such as V1 relates to the large-scale organization of functionally distinct whole-brain networks. PMID:27554527

The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

NASA Astrophysics Data System (ADS)

Ciddio, Manuela; Mari, Lorenzo; Sokolow, Susanne H.; De Leo, Giulio A.; Casagrandi, Renato; Gatto, Marino

2017-10-01

Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations.

Reconfiguration of parietal circuits with cognitive tutoring in elementary school children

PubMed Central

Jolles, Dietsje; Supekar, Kaustubh; Richardson, Jennifer; Tenison, Caitlin; Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2016-01-01

Cognitive development is shaped by brain plasticity during childhood, yet little is known about changes in large-scale functional circuits associated with learning in academically relevant cognitive domains such as mathematics. Here, we investigate plasticity of intrinsic brain circuits associated with one-on-one math tutoring and its relation to individual differences in children’s learning. We focused on functional circuits associated with the intraparietal sulcus (IPS) and angular gyrus (AG), cytoarchitectonically distinct subdivisions of the human parietal cortex with different roles in numerical cognition. Tutoring improved performance and strengthened IPS connectivity with the lateral prefrontal cortex, ventral temporal-occipital cortex, and hippocampus. Crucially, increased IPS connectivity was associated with individual performance gains, highlighting the behavioral significance of plasticity in IPS circuits. Tutoring-related changes in IPS connectivity were distinct from those of the adjacent AG, which did not predict performance gains. Our findings provide new insights into plasticity of functional brain circuits associated with the development of specialized cognitive skills in children. PMID:27618765

Reconfiguration of parietal circuits with cognitive tutoring in elementary school children.

PubMed

Jolles, Dietsje; Supekar, Kaustubh; Richardson, Jennifer; Tenison, Caitlin; Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2016-10-01

Cognitive development is shaped by brain plasticity during childhood, yet little is known about changes in large-scale functional circuits associated with learning in academically relevant cognitive domains such as mathematics. Here, we investigate plasticity of intrinsic brain circuits associated with one-on-one math tutoring and its relation to individual differences in children's learning. We focused on functional circuits associated with the intraparietal sulcus (IPS) and angular gyrus (AG), cytoarchitectonically distinct subdivisions of the human parietal cortex with different roles in numerical cognition. Tutoring improved performance and strengthened IPS connectivity with the lateral prefrontal cortex, ventral temporal-occipital cortex, and hippocampus. Crucially, increased IPS connectivity was associated with individual performance gains, highlighting the behavioral significance of plasticity in IPS circuits. Tutoring-related changes in IPS connectivity were distinct from those of the adjacent AG, which did not predict performance gains. Our findings provide new insights into plasticity of functional brain circuits associated with the development of specialized cognitive skills in children. Copyright © 2016 Elsevier Ltd. All rights reserved.

Alcohol Affects the Brain's Resting-State Network in Social Drinkers

PubMed Central

Lithari, Chrysa; Klados, Manousos A.; Pappas, Costas; Albani, Maria; Kapoukranidou, Dorothea; Kovatsi, Leda

2012-01-01

Acute alcohol intake is known to enhance inhibition through facilitation of GABAA receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN). To test our hypothesis, electroencephalographic (EEG) measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC) on standardized Low Resolution Electromagnetic Tomography (sLORETA) solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p<0.05, corrected with False Discovery Rate, FDR corrected) in alpha, beta (eyes-open) and theta bands (eyes-closed) following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p<0.05). Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo). Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially- be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as expected, to increased GABA transmission and functional connectivity, while long-term alcohol consumption may be linked to exactly the opposite effect. PMID:23119078

Structural and functional connectivity as a driver of hillslope erosion following disturbance

Treesearch

C. Jason Williams; Frederick B. Pierson; Pete Robichaud; Osama Z. Al-Hamdan; Jan Boll; Eva K. Strand

2016-01-01

Hydrologic response to rainfall on fragmented or burnt hillslopes is strongly influenced by the ensuing connectivity of runoff and erosion processes. Yet cross-scale process connectivity is seldom evaluated in field studies owing to scale limitations in experimental design. This study quantified surface susceptibility and hydrologic response across point to...

Population genetics of the understory fishtail palm Chamaedorea ernesti-augusti in Belize: high genetic connectivity with local differentiation

PubMed Central

Cibrián-Jaramillo, Angélica; Bacon, Christine D; Garwood, Nancy C; Bateman, Richard M; Thomas, Meredith M; Russell, Steve; Bailey, C Donovan; Hahn, William J; Bridgewater, Samuel GM; DeSalle, Rob

2009-01-01

Background Developing a greater understanding of population genetic structure in lowland tropical plant species is highly relevant to our knowledge of increasingly fragmented forests and to the conservation of threatened species. Specific studies are particularly needed for taxa whose population dynamics are further impacted by human harvesting practices. One such case is the fishtail or xaté palm (Chamaedorea ernesti-augusti) of Central America, whose wild-collected leaves are becoming progressively more important to the global ornamental industry. We use microsatellite markers to describe the population genetics of this species in Belize and test the effects of climate change and deforestation on its recent and historical effective population size. Results We found high levels of inbreeding coupled with moderate or high allelic diversity within populations. Overall high gene flow was observed, with a north and south gradient and ongoing differentiation at smaller spatial scales. Immigration rates among populations were more difficult to discern, with minimal evidence for isolation by distance. We infer a tenfold reduction in effective population size ca. 10,000 years ago, but fail to detect changes attributable to Mayan or contemporary deforestation. Conclusion Populations of C. ernesti-augusti are genetically heterogeneous demes at a local spatial scale, but are widely connected at a regional level in Belize. We suggest that the inferred patterns in population genetic structure are the result of the colonization of this species into Belize following expansion of humid forests in combination with demographic and mating patterns. Within populations, we hypothesize that low aggregated population density over large areas, short distance pollen dispersal via thrips, low adult survival, and low fruiting combined with early flowering may contribute towards local inbreeding via genetic drift. Relatively high levels of regional connectivity are likely the result of animal-mediated long-distance seed dispersal. The greatest present threat to the species is the potential onset of inbreeding depression as the result of increased human harvesting activities. Future genetic studies in understory palms should focus on both fine-scale and landscape-level genetic structure. PMID:19818141

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity.

PubMed

Al-Awami, Ali K; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W; Pfister, Hanspeter; Hadwiger, Markus

2014-12-01

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

Leadership solves collective action problems in small-scale societies

PubMed Central

Glowacki, Luke; von Rueden, Chris

2015-01-01

Observation of leadership in small-scale societies offers unique insights into the evolution of human collective action and the origins of sociopolitical complexity. Using behavioural data from the Tsimane forager-horticulturalists of Bolivia and Nyangatom nomadic pastoralists of Ethiopia, we evaluate the traits of leaders and the contexts in which leadership becomes more institutional. We find that leaders tend to have more capital, in the form of age-related knowledge, body size or social connections. These attributes can reduce the costs leaders incur and increase the efficacy of leadership. Leadership becomes more institutional in domains of collective action, such as resolution of intragroup conflict, where collective action failure threatens group integrity. Together these data support the hypothesis that leadership is an important means by which collective action problems are overcome in small-scale societies. PMID:26503683

Leadership solves collective action problems in small-scale societies.

PubMed

Glowacki, Luke; von Rueden, Chris

2015-12-05

Observation of leadership in small-scale societies offers unique insights into the evolution of human collective action and the origins of sociopolitical complexity. Using behavioural data from the Tsimane forager-horticulturalists of Bolivia and Nyangatom nomadic pastoralists of Ethiopia, we evaluate the traits of leaders and the contexts in which leadership becomes more institutional. We find that leaders tend to have more capital, in the form of age-related knowledge, body size or social connections. These attributes can reduce the costs leaders incur and increase the efficacy of leadership. Leadership becomes more institutional in domains of collective action, such as resolution of intragroup conflict, where collective action failure threatens group integrity. Together these data support the hypothesis that leadership is an important means by which collective action problems are overcome in small-scale societies. © 2015 The Author(s).

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

PubMed

Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

Wide-area mapping of resting state hemodynamic correlations at microvascular resolution with multi-contrast optical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Senarathna, Janaka; Hadjiabadi, Darian; Gil, Stacy; Thakor, Nitish V.; Pathak, Arvind P.

2017-02-01

Different brain regions exhibit complex information processing even at rest. Therefore, assessing temporal correlations between regions permits task-free visualization of their `resting state connectivity'. Although functional MRI (fMRI) is widely used for mapping resting state connectivity in the human brain, it is not well suited for `microvascular scale' imaging in rodents because of its limited spatial resolution. Moreover, co-registered cerebral blood flow (CBF) and total hemoglobin (HbT) data are often unavailable in conventional fMRI experiments. Therefore, we built a customized system that combines laser speckle contrast imaging (LSCI), intrinsic optical signal (IOS) imaging and fluorescence imaging (FI) to generate multi-contrast functional connectivity maps at a spatial resolution of 10 μm. This system comprised of three illumination sources: a 632 nm HeNe laser (for LSCI), a 570 nm ± 5 nm filtered white light source (for IOS), and a 473 nm blue laser (for FI), as well as a sensitive CCD camera operating at 10 frames per second for image acquisition. The acquired data enabled visualization of changes in resting state neurophysiology at microvascular spatial scales. Moreover, concurrent mapping of CBF and HbT-based temporal correlations enabled in vivo mapping of how resting brain regions were linked in terms of their hemodynamics. Additionally, we complemented this approach by exploiting the transit times of a fluorescent tracer (Dextran-FITC) to distinguish arterial from venous perfusion. Overall, we demonstrated the feasibility of wide area mapping of resting state connectivity at microvascular resolution and created a new toolbox for interrogating neurovascular function.

Frontoparietal Structural Connectivity in Childhood Predicts Development of Functional Connectivity and Reasoning Ability: A Large-Scale Longitudinal Investigation.

PubMed

Wendelken, Carter; Ferrer, Emilio; Ghetti, Simona; Bailey, Stephen K; Cutting, Laurie; Bunge, Silvia A

2017-08-30

Prior research points to a positive concurrent relationship between reasoning ability and both frontoparietal structural connectivity (SC) as measured by diffusion tensor imaging (Tamnes et al., 2010) and frontoparietal functional connectivity (FC) as measured by fMRI (Cocchi et al., 2014). Further, recent research demonstrates a link between reasoning ability and FC of two brain regions in particular: rostrolateral prefrontal cortex (RLPFC) and the inferior parietal lobe (IPL) (Wendelken et al., 2016). Here, we sought to investigate the concurrent and dynamic, lead-lag relationships among frontoparietal SC, FC, and reasoning ability in humans. To this end, we combined three longitudinal developmental datasets with behavioral and neuroimaging data from 523 male and female participants between 6 and 22 years of age. Cross-sectionally, reasoning ability was most strongly related to FC between RLPFC and IPL in adolescents and adults, but to frontoparietal SC in children. Longitudinal analysis revealed that RLPFC-IPL SC, but not FC, was a positive predictor of future changes in reasoning ability. Moreover, we found that RLPFC-IPL SC at one time point positively predicted future changes in RLPFC-IPL FC, whereas, in contrast, FC did not predict future changes in SC. Our results demonstrate the importance of strong white matter connectivity between RLPFC and IPL during middle childhood for the subsequent development of both robust FC and good reasoning ability. SIGNIFICANCE STATEMENT The human capacity for reasoning develops substantially during childhood and has a profound impact on achievement in school and in cognitively challenging careers. Reasoning ability depends on communication between lateral prefrontal and parietal cortices. Therefore, to understand how this capacity develops, we examined the dynamic relationships over time among white matter tracts connecting frontoparietal cortices (i.e., structural connectivity, SC), coordinated frontoparietal activation (functional connectivity, FC), and reasoning ability in a large longitudinal sample of subjects 6-22 years of age. We found that greater frontoparietal SC in childhood predicts future increases in both FC and reasoning ability, demonstrating the importance of white matter development during childhood for subsequent brain and cognitive functioning. Copyright © 2017 the authors 0270-6474/17/378549-10$15.00/0.

Frontoparietal Structural Connectivity in Childhood Predicts Development of Functional Connectivity and Reasoning Ability: A Large-Scale Longitudinal Investigation

PubMed Central

Ferrer, Emilio; Cutting, Laurie

2017-01-01

Prior research points to a positive concurrent relationship between reasoning ability and both frontoparietal structural connectivity (SC) as measured by diffusion tensor imaging (Tamnes et al., 2010) and frontoparietal functional connectivity (FC) as measured by fMRI (Cocchi et al., 2014). Further, recent research demonstrates a link between reasoning ability and FC of two brain regions in particular: rostrolateral prefrontal cortex (RLPFC) and the inferior parietal lobe (IPL) (Wendelken et al., 2016). Here, we sought to investigate the concurrent and dynamic, lead–lag relationships among frontoparietal SC, FC, and reasoning ability in humans. To this end, we combined three longitudinal developmental datasets with behavioral and neuroimaging data from 523 male and female participants between 6 and 22 years of age. Cross-sectionally, reasoning ability was most strongly related to FC between RLPFC and IPL in adolescents and adults, but to frontoparietal SC in children. Longitudinal analysis revealed that RLPFC–IPL SC, but not FC, was a positive predictor of future changes in reasoning ability. Moreover, we found that RLPFC–IPL SC at one time point positively predicted future changes in RLPFC–IPL FC, whereas, in contrast, FC did not predict future changes in SC. Our results demonstrate the importance of strong white matter connectivity between RLPFC and IPL during middle childhood for the subsequent development of both robust FC and good reasoning ability. SIGNIFICANCE STATEMENT The human capacity for reasoning develops substantially during childhood and has a profound impact on achievement in school and in cognitively challenging careers. Reasoning ability depends on communication between lateral prefrontal and parietal cortices. Therefore, to understand how this capacity develops, we examined the dynamic relationships over time among white matter tracts connecting frontoparietal cortices (i.e., structural connectivity, SC), coordinated frontoparietal activation (functional connectivity, FC), and reasoning ability in a large longitudinal sample of subjects 6–22 years of age. We found that greater frontoparietal SC in childhood predicts future increases in both FC and reasoning ability, demonstrating the importance of white matter development during childhood for subsequent brain and cognitive functioning. PMID:28821657

Field-based study of connectivity in an agricultural catchment

NASA Astrophysics Data System (ADS)

Lexartza-Artza, I.; Wainwright, J.

2009-12-01

Field-based studies of hydrological connectivity can provide context-specific knowledge that might both help understand dynamic complex systems and contribute to other synthetic or modelling approaches. The importance of such an understanding of catchment processes and also of the knowledge of catchment connections with water bodies and the changes of concentration with scale for Integrated Catchment Management has been increasingly emphasized. To provide a holistic understanding, approaches to the study of connectivity need to include both structural and functional aspects of the system and must consider the processes taking place within and across different temporal and spatial scales. A semi-quantitative nested approach has been used to investigate connectivity and study the interactions and feedbacks between the factors influencing transfer processes in the Ingbirchworth Catchment, in the uplands of the River Don, England. A series of reconnaissance techniques have been combined with monitoring of aspects such as rainfall, runoff, sediment transfer and soil-moisture distribution from plot to catchment scale and with consideration of linkages between land and water bodies. The temporal aspect has also been considered, with a special focus on the temporal distribution of events and the influence of longer term catchment changes such as those in land use and management practices. A variability of responses has been observed in relation to the characteristics of events, land use and scale of observation, with elements traditionally considered as limiting or enhancing connectivity responding differently under changing conditions. Sediment redistribution, reshaping of structure and consequent reinforcing loops can be observed across all land uses and landscape units, but the relevance it terms of effective connectivity of highly connected patches varies as the scale is increased. The knowledge acquired can contribute to recognise emerging processes significant for active land-water connection and thus provide useful knowledge for decision making.

Linking biogeomorphic feedbacks from ecosystem engineer to landscape scale: a panarchy approach

NASA Astrophysics Data System (ADS)

Eichel, Jana

2017-04-01

Scale is a fundamental concept in both ecology and geomorphology. Therefore, scale-based approaches are a valuable tool to bridge the disciplines and improve the understanding of feedbacks between geomorphic processes, landforms, material and organisms and ecological processes in biogeomorphology. Yet, linkages between biogeomorphic feedbacks on different scales, e.g. between ecosystem engineering and landscape scale patterns and dynamics, are not well understood. A panarchy approach sensu Holling et al. (2002) can help to close this research gap and explain how structure and function are created in biogeomorphic ecosystems. Based on results from previous biogeomorphic research in Turtmann glacier foreland (Switzerland; Eichel, 2017; Eichel et al. 2013, 2016), a panarchy concept is presented for lateral moraine slope biogeomorphic ecosystems. It depicts biogeomorphic feedbacks on different spatiotemporal scales as a set of nested adaptive cycles and links them by 'remember' and 'revolt' connections. On a small scale (cm2 - m2; seconds to years), the life cycle of the ecosystem engineer Dryas octopetala L. is considered as an adaptive cycle. Biogeomorphic succession within patches created by geomorphic processes represents an intermediate scale adaptive cycle (m2 - ha, years to decades), while geomorphic and ecologic pattern development at a landscape scale (ha - km2, decades to centuries) can be illustrated by an adaptive cycle of ‚biogeomorphic patch dynamics' (Eichel, 2017). In the panarchy, revolt connections link the smaller scale adaptive cycles to larger scale cycles: on lateral moraine slopes, the development of ecosystem engineer biomass and cover controls the engineering threshold of the biogeomorphic feedback window (Eichel et al., 2016) and therefore the onset of the biogeomorphic phase during biogeomorphic succession. In this phase, engineer patches and biogeomorphic structures can be created in the patch mosaic of the landscape. Remember connections link larger scale adaptive cycles to smaller scale cycles: configuration and properties of the lateral moraine slope patch mosaic control patch recolonization during biogeomorphic succession, while the patch-internal disturbance regime determines when the engineer can establish (establishment threshold of the biogeomorphic feedback window). Jointly, biogeomorphic feedback adaptive cycles and their connections in the panarchy create structure and function in the lateral moraine slope biogeomorphic ecosystem. Thus, by linking feedbacks on different spatiotemporal scales in biogeomorphic ecosystems and explaining the creation of ecosystem structure and function, the panarchy concept represents a useful tool for future biogeomorphic research. Eichel, J. 2017. Biogeomorphic dynamics in the Turtmann glacier forefield, Switzerland. PhD thesis, University of Bonn. Eichel J, Corenblit D, Dikau R. 2016. Conditions for feedbacks between geomorphic and vegetation dynamics on lateral moraine slopes: a biogeomorphic feedback window. Earth Surface Processes and Landforms 41: 406-419. DOI: 10.1002/esp.3859 Eichel J, Krautblatter M, Schmidtlein S, Dikau R. 2013. Biogeomorphic interactions in the Turtmann glacier forefield, Switzerland. Geomorphology 201 : 98-110. DOI: 10.1016/j.geomorph.2013.06.012 Holling CS, Gunderson LH, Peterson GD. 2002. Sustainability and Panarchies. In Panarchy: Understanding Transformations in Human and Natural Systems , . Island Press: Washington, D.C.; 63-102.

Enhanced Cortical Connectivity in Absolute Pitch Musicians: A Model for Local Hyperconnectivity

ERIC Educational Resources Information Center

Loui, Psyche; Li, H. Charles; Hohmann, Anja; Schlaug, Gottfried

2011-01-01

Connectivity in the human brain has received increased scientific interest in recent years. Although connection disorders can affect perception, production, learning, and memory, few studies have associated brain connectivity with graded variations in human behavior, especially among normal individuals. One group of normal individuals who possess…

Solidarity with Animals: Assessing a Relevant Dimension of Social Identification with Animals.

PubMed

Amiot, Catherine E; Bastian, Brock

2017-01-01

Interactions with animals are pervasive in human life, a fact that is reflected in the burgeoning field of human-animal relations research. The goal of the current research was to examine the psychology of our social connection with other animals, by specifically developing a measure of solidarity with animals. In 8 studies using correlational, experimental, and longitudinal designs, solidarity with animals predicted more positive attitudes and behaviors toward animals, over and above existing scales of identification, and even when this implied a loss of resources and privileges for humans relative to animals. Solidarity with animals also displayed predicted relationships with relevant variables (anthropomorphism, empathy). Pet owners and vegetarians displayed higher levels of solidarity with animals. Correlational and experimental evidence confirmed that human-animal similarity heightens solidarity with animals. Our findings provide a useful measure that can facilitate important insights into the nature of our relationships with animals.

Solidarity with Animals: Assessing a Relevant Dimension of Social Identification with Animals

PubMed Central

Amiot, Catherine E.; Bastian, Brock

2017-01-01

Interactions with animals are pervasive in human life, a fact that is reflected in the burgeoning field of human-animal relations research. The goal of the current research was to examine the psychology of our social connection with other animals, by specifically developing a measure of solidarity with animals. In 8 studies using correlational, experimental, and longitudinal designs, solidarity with animals predicted more positive attitudes and behaviors toward animals, over and above existing scales of identification, and even when this implied a loss of resources and privileges for humans relative to animals. Solidarity with animals also displayed predicted relationships with relevant variables (anthropomorphism, empathy). Pet owners and vegetarians displayed higher levels of solidarity with animals. Correlational and experimental evidence confirmed that human-animal similarity heightens solidarity with animals. Our findings provide a useful measure that can facilitate important insights into the nature of our relationships with animals. PMID:28045909

Using Satellite Remote Sensing and Household Survey Data to Assess Human Health and Nutrition Response to Environmental Change

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Grace, Kathryn; Shively, Gerald; Johnson, Kiersten B.; Carroll, Mark

2014-01-01

Climate change and degradation of ecosystem services functioning may threaten the ability of current agricultural systems to keep up with demand for adequate and inexpensive food and for clean water, waste disposal and other broader ecosystem services. Human health is likely to be affected by changes occurring across multiple geographic and time scales. Impacts range from increasing transmissibility and the range of vector-borne diseases, such as malaria and yellow fever, to undermining nutrition through deleterious impacts on food production and concomitant increases in food prices. This paper uses case studies to describe methods that make use of satellite remote sensing and Demographic and Health Survey data to better understand individual-level human health and nutrition outcomes. By bringing these diverse datasets together, the connection between environmental change and human health outcomes can be described through new research and analysis.

Sex differences in normal age trajectories of functional brain networks.

PubMed

Scheinost, Dustin; Finn, Emily S; Tokoglu, Fuyuze; Shen, Xilin; Papademetris, Xenophon; Hampson, Michelle; Constable, R Todd

2015-04-01

Resting-state functional magnetic resonance image (rs-fMRI) is increasingly used to study functional brain networks. Nevertheless, variability in these networks due to factors such as sex and aging is not fully understood. This study explored sex differences in normal age trajectories of resting-state networks (RSNs) using a novel voxel-wise measure of functional connectivity, the intrinsic connectivity distribution (ICD). Males and females showed differential patterns of changing connectivity in large-scale RSNs during normal aging from early adulthood to late middle-age. In some networks, such as the default-mode network, males and females both showed decreases in connectivity with age, albeit at different rates. In other networks, such as the fronto-parietal network, males and females showed divergent connectivity trajectories with age. Main effects of sex and age were found in many of the same regions showing sex-related differences in aging. Finally, these sex differences in aging trajectories were robust to choice of preprocessing strategy, such as global signal regression. Our findings resolve some discrepancies in the literature, especially with respect to the trajectory of connectivity in the default mode, which can be explained by our observed interactions between sex and aging. Overall, results indicate that RSNs show different aging trajectories for males and females. Characterizing effects of sex and age on RSNs are critical first steps in understanding the functional organization of the human brain. © 2014 Wiley Periodicals, Inc.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

PubMed

Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large-scale datasets. Software and data sets are available at http://www.sfu.ca/~ester/software/DECOB.zip.

A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology.

PubMed

Harte, Richard; Glynn, Liam; Rodríguez-Molinero, Alejandro; Baker, Paul Ma; Scharf, Thomas; Quinlan, Leo R; ÓLaighin, Gearóid

2017-03-16

Design processes such as human-centered design, which involve the end user throughout the product development and testing process, can be crucial in ensuring that the product meets the needs and capabilities of the user, particularly in terms of safety and user experience. The structured and iterative nature of human-centered design can often present a challenge when design teams are faced with the necessary, rapid, product development life cycles associated with the competitive connected health industry. We wanted to derive a structured methodology that followed the principles of human-centered design that would allow designers and developers to ensure that the needs of the user are taken into account throughout the design process, while maintaining a rapid pace of development. In this paper, we present the methodology and its rationale before outlining how it was applied to assess and enhance the usability, human factors, and user experience of a connected health system known as the Wireless Insole for Independent and Safe Elderly Living (WIISEL) system, a system designed to continuously assess fall risk by measuring gait and balance parameters associated with fall risk. We derived a three-phase methodology. In Phase 1 we emphasized the construction of a use case document. This document can be used to detail the context of use of the system by utilizing storyboarding, paper prototypes, and mock-ups in conjunction with user interviews to gather insightful user feedback on different proposed concepts. In Phase 2 we emphasized the use of expert usability inspections such as heuristic evaluations and cognitive walkthroughs with small multidisciplinary groups to review the prototypes born out of the Phase 1 feedback. Finally, in Phase 3 we emphasized classical user testing with target end users, using various metrics to measure the user experience and improve the final prototypes. We report a successful implementation of the methodology for the design and development of a system for detecting and predicting falls in older adults. We describe in detail what testing and evaluation activities we carried out to effectively test the system and overcome usability and human factors problems. We feel this methodology can be applied to a wide variety of connected health devices and systems. We consider this a methodology that can be scaled to different-sized projects accordingly. ©Richard Harte, Liam Glynn, Alejandro Rodríguez-Molinero, Paul MA Baker, Thomas Scharf, Leo R Quinlan, Gearóid ÓLaighin. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 16.03.2017.

Connecting Mobility to Infectious Diseases: The Promise and Limits of Mobile Phone Data.

PubMed

Wesolowski, Amy; Buckee, Caroline O; Engø-Monsen, Kenth; Metcalf, C J E

2016-12-01

Human travel can shape infectious disease dynamics by introducing pathogens into susceptible populations or by changing the frequency of contacts between infected and susceptible individuals. Quantifying infectious disease-relevant travel patterns on fine spatial and temporal scales has historically been limited by data availability. The recent emergence of mobile phone calling data and associated locational information means that we can now trace fine scale movement across large numbers of individuals. However, these data necessarily reflect a biased sample of individuals across communities and are generally aggregated for both ethical and pragmatic reasons that may further obscure the nuance of individual and spatial heterogeneities. Additionally, as a general rule, the mobile phone data are not linked to demographic or social identifiers, or to information about the disease status of individual subscribers (although these may be made available in smaller-scale specific cases). Combining data on human movement from mobile phone data-derived population fluxes with data on disease incidence requires approaches that can tackle varying spatial and temporal resolutions of each data source and generate inference about dynamics on scales relevant to both pathogen biology and human ecology. Here, we review the opportunities and challenges of these novel data streams, illustrating our examples with analyses of 2 different pathogens in Kenya, and conclude by outlining core directions for future research. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Neuroanatomic connectivity of the human ascending arousal system critical to consciousness and its disorders.

PubMed

Edlow, Brian L; Takahashi, Emi; Wu, Ona; Benner, Thomas; Dai, Guangping; Bu, Lihong; Grant, Patricia Ellen; Greer, David M; Greenberg, Steven M; Kinney, Hannah C; Folkerth, Rebecca D

2012-06-01

The ascending reticular activating system (ARAS) mediates arousal, an essential component of human consciousness. Lesions of the ARAS cause coma, the most severe disorder of consciousness. Because of current methodological limitations, including of postmortem tissue analysis, the neuroanatomic connectivity of the human ARAS is poorly understood. We applied the advanced imaging technique of high angular resolution diffusion imaging (HARDI) to elucidate the structural connectivity of the ARAS in 3 adult human brains, 2 of which were imaged postmortem. High angular resolution diffusion imaging tractography identified the ARAS connectivity previously described in animals and also revealed novel human pathways connecting the brainstem to the thalamus, the hypothalamus, and the basal forebrain. Each pathway contained different distributions of fiber tracts from known neurotransmitter-specific ARAS nuclei in the brainstem. The histologically guided tractography findings reported here provide initial evidence for human-specific pathways of the ARAS. The unique composition of neurotransmitter-specific fiber tracts within each ARAS pathway suggests structural specializations that subserve the different functional characteristics of human arousal. This ARAS connectivity analysis provides proof of principle that HARDI tractography may affect the study of human consciousness and its disorders, including in neuropathologic studies of patients dying in coma and the persistent vegetative state.

A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems

NASA Astrophysics Data System (ADS)

Pöppl, Ronald; Keesstra, Saskia; Maroulis, Jerry

2017-04-01

Human-induced landscape change is difficult to predict due to the complexity inherent in both geomorphic and social systems as well as due to emerging coupling relationships between them. To better understand system complexity and system response to change, connectivity has become an important research paradigm within various disciplines including geomorphology, hydrology and ecology. With the proposed conceptual connectivity framework on geomorphic change in human-impacted fluvial systems a cautionary note is flagged regarding the need (i) to include and to systematically conceptualise the role of different types of human agency in altering connectivity relationships in geomorphic systems and (ii) to integrate notions of human-environment interactions to connectivity concepts in geomorphology to better explain causes and trajectories of landscape change. Underpinned by case study examples, the presented conceptual framework is able to explain how geomorphic response of fluvial systems to human disturbance is determined by system-specific boundary conditions (incl. system history, related legacy effects and lag times), vegetation dynamics and human-induced functional relationships (i.e. feedback mechanisms) between the different spatial dimensions of connectivity. It is further demonstrated how changes in social systems can trigger a process-response feedback loop between social and geomorphic systems that further governs the trajectory of landscape change in coupled human-geomorphic systems.

A multi-scale assessment of population connectivity in African lions (Panthera leo) in response to landscape change

Treesearch

Samuel A. Cushman; Nicholas B. Elliot; David W. Macdonald; Andrew J. Loveridge

2015-01-01

Habitat loss and fragmentation are among the major drivers of population declines and extinction, particularly in large carnivores. Connectivity models provide practical tools for assessing fragmentation effects and developing mitigation or conservation responses. To be useful to conservation practitioners, connectivity models need to incorporate multiple scales and...

Hydrologic connectivity between landscapes and streams: Transferring reach‐ and plot‐scale understanding to the catchment scale

USGS Publications Warehouse

Jencso, Kelsey G.; McGlynn, Brian L.; Gooseff, Michael N.; Wondzell, Steven M.; Bencala, Kenneth E.; Marshall, Lucy A.

2009-01-01

The relationship between catchment structure and runoff characteristics is poorly understood. In steep headwater catchments with shallow soils the accumulation of hillslope area (upslope accumulated area (UAA)) is a hypothesized first‐order control on the distribution of soil water and groundwater. Hillslope‐riparian water table connectivity represents the linkage between the dominant catchment landscape elements (hillslopes and riparian zones) and the channel network. Hydrologic connectivity between hillslope‐riparian‐stream (HRS) landscape elements is heterogeneous in space and often temporally transient. We sought to test the relationship between UAA and the existence and longevity of HRS shallow groundwater connectivity. We quantified water table connectivity based on 84 recording wells distributed across 24 HRS transects within the Tenderfoot Creek Experimental Forest (U.S. Forest Service), northern Rocky Mountains, Montana. Correlations were observed between the longevity of HRS water table connectivity and the size of each transect's UAA (r2 = 0.91). We applied this relationship to the entire stream network to quantify landscape‐scale connectivity through time and ascertain its relationship to catchment‐scale runoff dynamics. We found that the shape of the estimated annual landscape connectivity duration curve was highly related to the catchment flow duration curve (r2 = 0.95). This research suggests internal catchment landscape structure (topography and topology) as a first‐order control on runoff source area and whole catchment response characteristics.

On the connectivity of the cosmic web: theory and implications for cosmology and galaxy formation

NASA Astrophysics Data System (ADS)

Codis, Sandrine; Pogosyan, Dmitri; Pichon, Christophe

2018-06-01

Cosmic connectivity and multiplicity, i.e. the number of filaments globally or locally connected to a given cluster is a natural probe of the growth of structure and in particular of the nature of dark energy. It is also a critical ingredient driving the assembly history of galaxies as it controls mass and angular momentum accretion. The connectivity of the cosmic web is investigated here via the persistent skeleton. This tool identifies topologically the ridges of the cosmic landscape which allows us to investigate how the nodes of the cosmic web are connected together. When applied to Gaussian random fields corresponding to the high redshift universe, it is found that on average the nodes are connected to exactly κ = 4 neighbours in two dimensions and ˜6.1 in three dimensions. Investigating spatial dimensions up to d = 6, typical departures from a cubic lattice κ = 2d are shown to scale like the power 7/4 of the dimension. These numbers strongly depend on the height of the peaks: the higher the peak the larger the connectivity. Predictions from first principles based on peak theory are shown to reproduce well the connectivity and multiplicity of Gaussian random fields and cosmological simulations. As an illustration, connectivity is quantified in galaxy lensing convergence maps and large dark haloes catalogues. As a function of redshift and scale the mean connectivity decreases in a cosmology-dependent way. As a function of halo mass it scales like 10/3 times the log of the mass. Implications on galactic scales are discussed.

Multiscale connectivity and graph theory highlight critical areas for conservation under climate change.

PubMed

Dilt, Thomas E; Weisberg, Peter J; Leitner, Philip; Matocq, Marjorie D; Inman, Richard D; Nussear, Kenneth E; Esque, Todd C

2016-06-01

Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multiscale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods, including graph theory, circuit theory, and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this threatened Californian species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously distributed habitat and should be applicable across a broad range of taxa.

Children and Reading: The Human Connectives. Proceedings of the Reading Conference (Auburn, November 10, 1972).

ERIC Educational Resources Information Center

Noland, Ronald G., Ed.

This publication is a compilation of the talks given at the 1972 Auburn University Department of Elementary Education Reading Conference. The theme of the conference was "Children and Reading: The Human Connectives." The topics and authors include: (1) "Children and Reading: The Human Connectives," by Donald E. Carline; (2) "Solving Problems…

Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions.

PubMed

Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor

2015-01-01

Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization.

Large-scale automated histology in the pursuit of connectomes.

PubMed

Kleinfeld, David; Bharioke, Arjun; Blinder, Pablo; Bock, Davi D; Briggman, Kevin L; Chklovskii, Dmitri B; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P; Lee, Wei-Chung Allen; Meyer, Hanno S; Micheva, Kristina D; Oberlaender, Marcel; Prohaska, Steffen; Reid, R Clay; Smith, Stephen J; Takemura, Shinya; Tsai, Philbert S; Sakmann, Bert

2011-11-09

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Large-Scale Automated Histology in the Pursuit of Connectomes

PubMed Central

Bharioke, Arjun; Blinder, Pablo; Bock, Davi D.; Briggman, Kevin L.; Chklovskii, Dmitri B.; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P.; Lee, Wei-Chung Allen; Meyer, Hanno S.; Micheva, Kristina D.; Oberlaender, Marcel; Prohaska, Steffen; Reid, R. Clay; Smith, Stephen J.; Takemura, Shinya; Tsai, Philbert S.; Sakmann, Bert

2011-01-01

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity. PMID:22072665

Adaptation of pancreatic islet cyto-architecture during development

NASA Astrophysics Data System (ADS)

Striegel, Deborah A.; Hara, Manami; Periwal, Vipul

2016-04-01

Plasma glucose in mammals is regulated by hormones secreted by the islets of Langerhans embedded in the exocrine pancreas. Islets consist of endocrine cells, primarily α, β, and δ cells, which secrete glucagon, insulin, and somatostatin, respectively. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Varying demands and available nutrients during development produce changes in the local connectivity of β cells in an islet. We showed in earlier work that graph theory provides a framework for the quantification of the seemingly stochastic cyto-architecture of β cells in an islet. To quantify the dynamics of endocrine connectivity during development requires a framework for characterizing changes in the probability distribution on the space of possible graphs, essentially a Fokker-Planck formalism on graphs. With large-scale imaging data for hundreds of thousands of islets containing millions of cells from human specimens, we show that this dynamics can be determined quantitatively. Requiring that rearrangement and cell addition processes match the observed dynamic developmental changes in quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that there is a transient shift in preferred connectivity for β cells between 1-35 weeks and 12-24 months.

Strategies Used by Foreign-Born Family Therapists to Connect Across Cultural Differences: A Thematic Analysis.

PubMed

Niño, Alba; Kissil, Karni; Davey, Maureen P

2016-01-01

With the growing diversity in the United States among both clinicians and clients, many therapeutic encounters are cross-cultural, requiring providers to connect across cultural differences. Foreign-born therapists have many areas of differences to work through. Thus, exploring how foreign-born family therapists in the United States connect to their clients can uncover helpful strategies that all therapists can use to establish stronger cross-cultural therapeutic connections. A thematic analysis was conducted to understand strategies 13 foreign-born therapists used during therapeutic encounters. Four themes were identified: making therapy a human-to-human connection, dealing with stereotypes, what really matters, and flexibility. Findings suggest that developing a deep therapeutic connection using emotional attunement and human-to-human engagement is crucial for successful cross-cultural therapy. Clinical and training implications are provided. © 2015 American Association for Marriage and Family Therapy.

Tissue microstructure features derived from anomalous diffusion measurements in magnetic resonance imaging.

PubMed

Yu, Qiang; Reutens, David; O'Brien, Kieran; Vegh, Viktor

2017-02-01

Tissue microstructure features, namely axon radius and volume fraction, provide important information on the function of white matter pathways. These parameters vary on the scale much smaller than imaging voxels (microscale) yet influence the magnetic resonance imaging diffusion signal at the image voxel scale (macroscale) in an anomalous manner. Researchers have already mapped anomalous diffusion parameters from magnetic resonance imaging data, but macroscopic variations have not been related to microscale influences. With the aid of a tissue model, we aimed to connect anomalous diffusion parameters to axon radius and volume fraction using diffusion-weighted magnetic resonance imaging measurements. An ex vivo human brain experiment was performed to directly validate axon radius and volume fraction measurements in the human brain. These findings were validated using electron microscopy. Additionally, we performed an in vivo study on nine healthy participants to map axon radius and volume fraction along different regions of the corpus callosum projecting into various cortical areas identified using tractography. We found a clear relationship between anomalous diffusion parameters and axon radius and volume fraction. We were also able to map accurately the trend in axon radius along the corpus callosum, and in vivo findings resembled the low-high-low-high behaviour in axon radius demonstrated previously. Axon radius and volume fraction measurements can potentially be used in brain connectivity studies and to understand the implications of white matter structure in brain diseases and disorders. Hum Brain Mapp 38:1068-1081, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ba, Qian; Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing; Li, Junyang

2015-03-01

Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong tomore » the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.« less

Large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

2016-03-01

We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

Exploring possible relations between optical variability time scales and broad emission line shapes in AGN

NASA Astrophysics Data System (ADS)

Bon, Edi; Jovanović, Predrag; Marziani, Paola; Bon, Nataša; Otašević, Aleksandar

2018-06-01

Here we investigate the connection of broad emission line shapes and continuum light curve variability time scales of type-1 Active Galactic Nuclei (AGN). We developed a new model to describe optical broad emission lines as an accretion disk model of a line profile with additional ring emission. We connect ring radii with orbital time scales derived from optical light curves, and using Kepler's third law, we calculate mass of central supermassive black hole (SMBH). The obtained results for central black hole masses are in a good agreement with other methods. This indicates that the variability time scales of AGN may not be stochastic, but rather connected to the orbital time scales which depend on the central SMBH mass.

Immunization of complex networks

NASA Astrophysics Data System (ADS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2002-03-01

Complex networks such as the sexual partnership web or the Internet often show a high degree of redundancy and heterogeneity in their connectivity properties. This peculiar connectivity provides an ideal environment for the spreading of infective agents. Here we show that the random uniform immunization of individuals does not lead to the eradication of infections in all complex networks. Namely, networks with scale-free properties do not acquire global immunity from major epidemic outbreaks even in the presence of unrealistically high densities of randomly immunized individuals. The absence of any critical immunization threshold is due to the unbounded connectivity fluctuations of scale-free networks. Successful immunization strategies can be developed only by taking into account the inhomogeneous connectivity properties of scale-free networks. In particular, targeted immunization schemes, based on the nodes' connectivity hierarchy, sharply lower the network's vulnerability to epidemic attacks.

Network modularity reveals critical scales for connectivity in ecology and evolution

USGS Publications Warehouse

Fletcher, Robert J.; Revell, Andre; Reichert, Brian E.; Kitchens, Wiley M.; Dixon, J.; Austin, James D.

2013-01-01

For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.

Comparative human health risk analysis of coastal community water and waste service options.

PubMed

Schoen, Mary E; Xue, Xiaobo; Hawkins, Troy R; Ashbolt, Nicholas J

2014-08-19

As a pilot approach to describe adverse human health effects from alternative decentralized community water systems compared to conventional centralized services (business-as-usual [BAU]), selected chemical and microbial hazards were assessed using disability adjusted life years (DALYs) as the common metric. The alternatives included: (1) composting toilets with septic system, (2) urine-diverting toilets with septic system, (3) low flush toilets with blackwater pressure sewer and on-site greywater collection and treatment for nonpotable reuse, and (4) alternative 3 with on-site rainwater treatment and use. Various pathogens (viral, bacterial, and protozoan) and chemicals (disinfection byproducts [DBPs]) were used as reference hazards. The exposure pathways for BAU included accidental ingestion of contaminated recreational water, ingestion of cross-connected sewage to drinking water, and shower exposures to DBPs. The alternative systems included ingestion of treated greywater from garden irrigation, toilet flushing, and crop consumption; and ingestion of treated rainwater while showering. The pathways with the highest health impact included the ingestion of cross-connected drinking water and ingestion of recreational water contaminated by septic seepage. These were also among the most uncertain when characterizing input parameters, particularly the scale of the cross-connection event, and the removal of pathogens during groundwater transport of septic seepage. A comparison of the health burdens indicated potential health benefits by switching from BAU to decentralized water and wastewater systems.

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Human Development XIII: The Connection Between the Structure of the Overtone System and the Tone Language of Music. Some Implications for Our Understanding of the Human Brain

PubMed Central

Ventegodt, Søren; Hermansen, Tyge Dahl; Kandel, Isack; Merrick, Joav

2008-01-01

The functioning brain behaves like one highly-structured, coherent, informational field. It can be popularly described as a “coherent ball of energy”, making the idea of a local highly-structured quantum field that carries the consciousness very appealing. If that is so, the structure of the experience of music might be a quite unique window into a hidden quantum reality of the brain, and even of life itself. The structure of music is then a mirror of a much more complex, but similar, structure of the energetic field of the working brain. This paper discusses how the perception of music is organized in the human brain with respect to the known tone scales of major and minor. The patterns used by the brain seem to be similar to the overtones of vibrating matter, giving a positive experience of harmonies in major. However, we also like the minor scale, which can explain brain patterns as fractal-like, giving a symmetric “downward reflection” of the major scale into the minor scale. We analyze the implication of beautiful and ugly tones and harmonies for the model. We conclude that when it comes to simple perception of harmonies, the most simple is the most beautiful and the most complex is the most ugly, but in music, even the most disharmonic harmony can be beautiful, if experienced as a part of a dynamic release of musical tension. This can be taken as a general metaphor of painful, yet meaningful, and developing experiences in human life. PMID:18661052

Connecting Humans and Water: The Case for Coordinated Data Collection

NASA Astrophysics Data System (ADS)

Braden, J. B.; Brown, D. G.; Jolejole-Foreman, C.; Maidment, D. R.; Marquart-Pyatt, S. T.; Schneider, D. W.

2012-12-01

"Water problems" are fundamentally human problems -- aligning water quality and quantity with human aspirations. In the U.S., however, the few ongoing efforts to repeatedly observe humans in relation to water at large scale are disjointed both with each other and with observing systems for water quality and quantity. This presentation argues for the systematic, coordinated, and on-going collection of primary data on humans, spanning beliefs, perceptions, behaviors, and institutions, alongside the water environments in which they are embedded. Such an enterprise would advance not only water science and related policy and management decisions, but also generate basic insights into human cognition, decision making, and institutional development as they relate to the science of sustainability. In support of this argument, two types of original analyses are presented. First, two case studies using existing data sets illustrate methodological issues involved in integrating natural system data with social data at large scale: one concerns the influence of water quality conditions on personal efforts to conserve water and contribute financially to environmental protection; the other explores relationships between recreation behavior and water quality. Both case studies show how methodological differences between data programs seriously undercut the potential to draw inference about human responses to water quality while also illustrating the scientific potential that could be realized from linking human and scientific surveys of the water environment. Second, the results of a survey of water scientists concerning important scientific and policy questions around humans and water provide insight into data collection priorities for a coordinated program of observation.

The scaling of human interactions with city size.

PubMed

Schläpfer, Markus; Bettencourt, Luís M A; Grauwin, Sébastian; Raschke, Mathias; Claxton, Rob; Smoreda, Zbigniew; West, Geoffrey B; Ratti, Carlo

2014-09-06

The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Connectivity of the South Florida Coral Reef Ecosystem to Upstream Waters of the Western Caribbean and Gulf of Mexico

NASA Astrophysics Data System (ADS)

Johns, E. M.; Smith, R. H.; Lamkin, J. T.; Birbriezca, L. C.; Vasquez-Yeomans, L.; Cordero, E. S.

2008-05-01

The coastal waters of south Florida, including the coral reefs of NOAA's Florida Keys National Marine Sanctuary (FKNMS), are directly connected by means of strong ocean currents with upstream waters of the western Caribbean Sea and the Gulf of Mexico. The Caribbean Current and the Loop Current provide a rapid conduit for transport from Mexican and Belizean coral reefs, located off the eastern shore of the Yucatan Peninsula, to nearshore regions of northern Cuba, Florida, and the Bahamas. Interdisciplinary cruise data collected in August 2002, March 2006 and January 2007 aboard the NOAA Ship Gordon Gunter, in combination with satellite-tracked surface drifter trajectories and remote sensing imagery, clearly show the highly variable and dynamic nature of the regional current regimes and provide a means of quantifying the potential pathways and transport rates of the coastal waters and their biological and chemical constituents from one region to another. Results from these cruises and ancillary data show that the study areas are connected with rapid transport time scales, and that frontal eddies and gyres play an important role in establishing the time and length scales of this connectivity. Such direct physical connectivity between the coral reef biota of these geographically separated spawning grounds via ocean currents may have an important influence on the degree of biological connectivity between regional larval populations. Initial analyses of ichthyoplankton surveys and inshore collections along the Yucatan mesoamerican reef suggest large scale variability in both local recruitment and large scale spatial distribution. Despite strong northward flowing currents, inshore collections indicate that local recruitment in some areas is strongly influenced by small scale circulation patterns. However, the distribution of spawning aggregations along the Yucatan coast suggests a larger role for the Caribbean Current. Determining the interactions between the larger scale circulation patterns and the smaller scale biological processes is a key research objective for understanding the observed regional population connections.

Current limiter circuit system

DOEpatents

Witcher, Joseph Brandon; Bredemann, Michael V.

2017-09-05

An apparatus comprising a steady state sensing circuit, a switching circuit, and a detection circuit. The steady state sensing circuit is connected to a first, a second and a third node. The first node is connected to a first device, the second node is connected to a second device, and the steady state sensing circuit causes a scaled current to flow at the third node. The scaled current is proportional to a voltage difference between the first and second node. The switching circuit limits an amount of current that flows between the first and second device. The detection circuit is connected to the third node and the switching circuit. The detection circuit monitors the scaled current at the third node and controls the switching circuit to limit the amount of the current that flows between the first and second device when the scaled current is greater than a desired level.

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging

PubMed Central

2016-01-01

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a ‘golden technique’ that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574313

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging.

PubMed

Ugurbil, Kamil

2016-10-05

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a 'golden technique' that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Author(s).

Integration and segregation of large-scale brain networks during short-term task automatization

PubMed Central

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F.; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-01-01

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes. PMID:27808095

Domain Selectivity in the Parahippocampal Gyrus Is Predicted by the Same Structural Connectivity Patterns in Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; He, Chenxi; Peelen, Marius V; Zhong, Suyu; Gong, Gaolang; Caramazza, Alfonso; Bi, Yanchao

2017-05-03

Human ventral occipital temporal cortex contains clusters of neurons that show domain-preferring responses during visual perception. Recent studies have reported that some of these clusters show surprisingly similar domain selectivity in congenitally blind participants performing nonvisual tasks. An important open question is whether these functional similarities are driven by similar innate connections in blind and sighted groups. Here we addressed this question focusing on the parahippocampal gyrus (PHG), a region that is selective for large objects and scenes. Based on the assumption that patterns of long-range connectivity shape local computation, we examined whether domain selectivity in PHG is driven by similar structural connectivity patterns in the two populations. Multiple regression models were built to predict the selectivity of PHG voxels for large human-made objects from white matter (WM) connectivity patterns in both groups. These models were then tested using independent data from participants with similar visual experience (two sighted groups) and using data from participants with different visual experience (blind and sighted groups). Strikingly, the WM-based predictions between blind and sighted groups were as successful as predictions between two independent sighted groups. That is, the functional selectivity for large objects of a PHG voxel in a blind participant could be accurately predicted by its WM pattern using the connection-to-function model built from the sighted group data, and vice versa. Regions that significantly predicted PHG selectivity were located in temporal and frontal cortices in both sighted and blind populations. These results show that the large-scale network driving domain selectivity in PHG is independent of vision. SIGNIFICANCE STATEMENT Recent studies have reported intriguingly similar domain selectivity in sighted and congenitally blind individuals in regions within the ventral visual cortex. To examine whether these similarities originate from similar innate connectional roots, we investigated whether the domain selectivity in one population could be predicted by the structural connectivity pattern of the other. We found that the selectivity for large objects of a PHG voxel in a blind participant could be predicted by its structural connectivity pattern using the connection-to-function model built from the sighted group data, and vice versa. These results reveal that the structural connectivity underlying domain selectivity in the PHG is independent of visual experience, providing evidence for nonvisual representations in this region. Copyright © 2017 the authors 0270-6474/17/374706-12$15.00/0.

Probing multi-scale self-similarity of tissue structures using light scattering spectroscopy: prospects in pre-cancer detection

NASA Astrophysics Data System (ADS)

Chatterjee, Subhasri; Das, Nandan K.; Kumar, Satish; Mohapatra, Sonali; Pradhan, Asima; Panigrahi, Prasanta K.; Ghosh, Nirmalya

2013-02-01

Multi-resolution analysis on the spatial refractive index inhomogeneities in the connective tissue regions of human cervix reveals clear signature of multifractality. We have thus developed an inverse analysis strategy for extraction and quantification of the multifractality of spatial refractive index fluctuations from the recorded light scattering signal. The method is based on Fourier domain pre-processing of light scattering data using Born approximation, and its subsequent analysis through Multifractal Detrended Fluctuation Analysis model. The method has been validated on several mono- and multi-fractal scattering objects whose self-similar properties are user controlled and known a-priori. Following successful validation, this approach has initially been explored for differentiating between different grades of precancerous human cervical tissues.

Responses of Cloud Type Distributions to the Large-Scale Dynamical Circulation: Water Budget-Related Dynamical Phase Space and Dynamical Regimes

NASA Technical Reports Server (NTRS)

Wong, Sun; Del Genio, Anthony; Wang, Tao; Kahn, Brian; Fetzer, Eric J.; L'Ecuyer, Tristan S.

2015-01-01

Goals: Water budget-related dynamical phase space; Connect large-scale dynamical conditions to atmospheric water budget (including precipitation); Connect atmospheric water budget to cloud type distributions.

Nine microsatellite loci developed from the octocoral, Paragorgia arborea

USGS Publications Warehouse

Coykendall, D. Katharine; Morrison, Cheryl L.

2015-01-01

Paragorgia arborea, or bubblegum coral, occurs in continental slope habitats worldwide, which are increasingly threatened by human activities such as energy development and fisheries practices. From 101 putative loci screened, nine microsatellite markers were developed from samples taken from Baltimore canyon in the western North Atlantic Ocean. The number of alleles ranged from two to thirteen per locus and each displayed equilibrium. These nuclear resources will help further research on population connectivity in threatened coral species where mitochondrial markers are known to lack fine-scale genetic diversity.

A large-scale photonic node architecture that utilizes interconnected OXC subsystems.

PubMed

Iwai, Yuto; Hasegawa, Hiroshi; Sato, Ken-ichi

2013-01-14

We propose a novel photonic node architecture that is composed of interconnected small-scale optical cross-connect subsystems. We also developed an efficient dynamic network control algorithm that complies with a restriction on the number of intra-node fibers used for subsystem interconnection. Numerical evaluations verify that the proposed architecture offers almost the same performance as the equivalent single large-scale cross-connect switch, while enabling substantial hardware scale reductions.

From a meso- to micro-scale connectome: array tomography and mGRASP

PubMed Central

Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun

2015-01-01

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781

Connecting the hadron mass scale to the fundamental mass scale of quantum chromodynamics

DOE PAGES

Deur, Alexandre; Brodsky, Stanley J.; de Teramond, Guy F.

2015-10-01

We establish an explicit connection between the long distance physics of confinement and the dynamical interactions of quarks and gluons at short distances and it has been a long-sought goal of quantum chromodynamics. Using holographic QCD, we derive a direct analytic relation between the scale κ which determines the masses of hadrons and the scale Λ s which controls the predictions of perturbative QCD at very short distances. The resulting prediction Λ s=0.341±0.032 GeV in the MS -scheme agrees well with the experimental average 0.339±0.016 GeV. We also derive a relation between Λs and the QCD string tension σ. Furthermore,more » this connection between the fundamental hadronic scale underlying the physics of quark confinement and the perturbative QCD scale controlling hard collisions can be carried out in any renormalization scheme.« less

Mangroves Enhance Reef Fish Abundance at the Caribbean Regional Scale.

PubMed

Serafy, Joseph E; Shideler, Geoffrey S; Araújo, Rafael J; Nagelkerken, Ivan

2015-01-01

Several studies conducted at the scale of islands, or small sections of continental coastlines, have suggested that mangrove habitats serve to enhance fish abundances on coral reefs, mainly by providing nursery grounds for several ontogenetically-migrating species. However, evidence of such enhancement at a regional scale has not been reported, and recently, some researchers have questioned the mangrove-reef subsidy effect. In the present study, using two different regression approaches, we pursued two questions related to mangrove-reef connectivity at the Caribbean regional scale: (1) Are reef fish abundances limited by mangrove forest area?; and (2) Are mean reef fish abundances proportional to mangrove forest area after taking human population density and latitude into account? Specifically, we tested for Caribbean-wide mangrove forest area effects on the abundances of 12 reef fishes that have been previously characterized as "mangrove-dependent". Analyzed were data from an ongoing, long-term (20-year) citizen-scientist fish monitoring program; coastal human population censuses; and several wetland forest information sources. Quantile regression results supported the notion that mangrove forest area limits the abundance of eight of the 12 fishes examined. Linear mixed-effects regression results, which considered potential human (fishing and habitat degradation) and latitudinal influences, suggested that average reef fish densities of at least six of the 12 focal fishes were directly proportional to mangrove forest area. Recent work questioning the mangrove-reef fish subsidy effect likely reflects a failure to: (1) focus analyses on species that use mangroves as nurseries, (2) consider more than the mean fish abundance response to mangrove forest extent; and/or (3) quantitatively account for potentially confounding human impacts, such as fishing pressure and habitat degradation. Our study is the first to demonstrate at a large regional scale (i.e., the Wider Caribbean) that greater mangrove forest size generally functions to increase the densities on neighboring reefs of those fishes that use these shallow, vegetated habitats as nurseries.

Mangroves Enhance Reef Fish Abundance at the Caribbean Regional Scale

PubMed Central

Serafy, Joseph E.; Shideler, Geoffrey S.; Araújo, Rafael J.; Nagelkerken, Ivan

2015-01-01

Several studies conducted at the scale of islands, or small sections of continental coastlines, have suggested that mangrove habitats serve to enhance fish abundances on coral reefs, mainly by providing nursery grounds for several ontogenetically-migrating species. However, evidence of such enhancement at a regional scale has not been reported, and recently, some researchers have questioned the mangrove-reef subsidy effect. In the present study, using two different regression approaches, we pursued two questions related to mangrove-reef connectivity at the Caribbean regional scale: (1) Are reef fish abundances limited by mangrove forest area?; and (2) Are mean reef fish abundances proportional to mangrove forest area after taking human population density and latitude into account? Specifically, we tested for Caribbean-wide mangrove forest area effects on the abundances of 12 reef fishes that have been previously characterized as “mangrove-dependent”. Analyzed were data from an ongoing, long-term (20-year) citizen-scientist fish monitoring program; coastal human population censuses; and several wetland forest information sources. Quantile regression results supported the notion that mangrove forest area limits the abundance of eight of the 12 fishes examined. Linear mixed-effects regression results, which considered potential human (fishing and habitat degradation) and latitudinal influences, suggested that average reef fish densities of at least six of the 12 focal fishes were directly proportional to mangrove forest area. Recent work questioning the mangrove-reef fish subsidy effect likely reflects a failure to: (1) focus analyses on species that use mangroves as nurseries, (2) consider more than the mean fish abundance response to mangrove forest extent; and/or (3) quantitatively account for potentially confounding human impacts, such as fishing pressure and habitat degradation. Our study is the first to demonstrate at a large regional scale (i.e., the Wider Caribbean) that greater mangrove forest size generally functions to increase the densities on neighboring reefs of those fishes that use these shallow, vegetated habitats as nurseries. PMID:26536478

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

PubMed

Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J

2011-06-01

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.

Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization.

PubMed

Beckmann, Matthias; Johansen-Berg, Heidi; Rushworth, Matthew F S

2009-01-28

Whole-brain neuroimaging studies have demonstrated regional variations in function within human cingulate cortex. At the same time, regional variations in cingulate anatomical connections have been found in animal models. It has, however, been difficult to estimate the relationship between connectivity and function throughout the whole cingulate cortex within the human brain. In this study, magnetic resonance diffusion tractography was used to investigate cingulate probabilistic connectivity in the human brain with two approaches. First, an algorithm was used to search for regional variations in the probabilistic connectivity profiles of all cingulate cortex voxels with the whole of the rest of the brain. Nine subregions with distinctive connectivity profiles were identified. It was possible to characterize several distinct areas in the dorsal cingulate sulcal region. Several distinct regions were also found in subgenual and perigenual cortex. Second, the probabilities of connection between cingulate cortex and 11 predefined target regions of interest were calculated. Cingulate voxels with a high probability of connection with the different targets formed separate clusters within cingulate cortex. Distinct connectivity fingerprints characterized the likelihood of connections between the extracingulate target regions and the nine cingulate subregions. Last, a meta-analysis of 171 functional studies reporting cingulate activation was performed. Seven different cognitive conditions were selected and peak activation coordinates were plotted to create maps of functional localization within the cingulate cortex. Regional functional specialization was found to be related to regional differences in probabilistic anatomical connectivity.

Determining fine-scale migratory connectivity and habitat selection for a migratory songbird by using new GPS technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fraser, Kevin C.; Shave, A.; Savage, A.

Migratory aerial insectivores are among the fastest declining avian group, but our understanding of these trends has been limited by poor knowledge of migratory connectivity and the identification of critical habitat across the vast distances they travel annually. Using new, archival GPS loggers, we tracked individual purple martins ( Progne subis) from breeding colonies across North America to determine precise (<10m) locations of migratory and overwintering roost locations in South America and to test hypotheses for fine-scale migratory connectivity and habitat use. We discovered weak migratory connectivity at the roost scale, and extensive, fine-scale mixing of birds in the Amazonmore » from distant (>2000 km) breeding sites, with some individuals sharing the same roosting trees. Despite vast tracts of contiguous forest in this region, birds occupied a much more limited habitat, with most (56%) roosts occurring on small habitat islands that were strongly associated with water. Only 17% of these roosts were in current protected areas. As a result, these data reflect a critical advance in our ability to remotely determine precise migratory connectivity and habitat selection across vast spatial scales, enhancing our understanding of population dynamics and enabling more effective conservation of species at risk.« less

Determining fine-scale migratory connectivity and habitat selection for a migratory songbird by using new GPS technology

DOE PAGES

Fraser, Kevin C.; Shave, A.; Savage, A.; ...

2016-07-27

Migratory aerial insectivores are among the fastest declining avian group, but our understanding of these trends has been limited by poor knowledge of migratory connectivity and the identification of critical habitat across the vast distances they travel annually. Using new, archival GPS loggers, we tracked individual purple martins ( Progne subis) from breeding colonies across North America to determine precise (<10m) locations of migratory and overwintering roost locations in South America and to test hypotheses for fine-scale migratory connectivity and habitat use. We discovered weak migratory connectivity at the roost scale, and extensive, fine-scale mixing of birds in the Amazonmore » from distant (>2000 km) breeding sites, with some individuals sharing the same roosting trees. Despite vast tracts of contiguous forest in this region, birds occupied a much more limited habitat, with most (56%) roosts occurring on small habitat islands that were strongly associated with water. Only 17% of these roosts were in current protected areas. As a result, these data reflect a critical advance in our ability to remotely determine precise migratory connectivity and habitat selection across vast spatial scales, enhancing our understanding of population dynamics and enabling more effective conservation of species at risk.« less

Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes

USGS Publications Warehouse

Allen, Craig D.

2007-01-01

Ecosystem patterns and disturbance processes at one spatial scale often interact with processes at another scale, and the result of such cross-scale interactions can be nonlinear dynamics with thresholds. Examples of cross-scale pattern-process relationships and interactions among forest dieback, fire, and erosion are illustrated from northern New Mexico (USA) landscapes, where long-term studies have recently documented all of these disturbance processes. For example, environmental stress, operating on individual trees, can cause tree death that is amplified by insect mortality agents to propagate to patch and then landscape or even regional-scale forest dieback. Severe drought and unusual warmth in the southwestern USA since the late 1990s apparently exceeded species-specific physiological thresholds for multiple tree species, resulting in substantial vegetation mortality across millions of hectares of woodlands and forests in recent years. Predictions of forest dieback across spatial scales are constrained by uncertainties associated with: limited knowledge of species-specific physiological thresholds; individual and site-specific variation in these mortality thresholds; and positive feedback loops between rapidly-responding insect herbivore populations and their stressed plant hosts, sometimes resulting in nonlinear “pest” outbreak dynamics. Fire behavior also exhibits nonlinearities across spatial scales, illustrated by changes in historic fire regimes where patch-scale grazing disturbance led to regional-scale collapse of surface fire activity and subsequent recent increases in the scale of extreme fire events in New Mexico. Vegetation dieback interacts with fire activity by modifying fuel amounts and configurations at multiple spatial scales. Runoff and erosion processes are also subject to scale-dependent threshold behaviors, exemplified by ecohydrological work in semiarid New Mexico watersheds showing how declines in ground surface cover lead to non-linear increases in bare patch connectivity and thereby accelerated runoff and erosion at hillslope and watershed scales. Vegetation dieback, grazing, and fire can change land surface properties and cross-scale hydrologic connectivities, directly altering ecohydrological patterns of runoff and erosion. The interactions among disturbance processes across spatial scales can be key drivers in ecosystem dynamics, as illustrated by these studies of recent landscape changes in northern New Mexico. To better anticipate and mitigate accelerating human impacts to the planetary ecosystem at all spatial scales, improvements are needed in our conceptual and quantitative understanding of cross-scale interactions among disturbance processes.

A knowledge based approach to matching human neurodegenerative disease and animal models

PubMed Central

Maynard, Sarah M.; Mungall, Christopher J.; Lewis, Suzanna E.; Imam, Fahim T.; Martone, Maryann E.

2013-01-01

Neurodegenerative diseases present a wide and complex range of biological and clinical features. Animal models are key to translational research, yet typically only exhibit a subset of disease features rather than being precise replicas of the disease. Consequently, connecting animal to human conditions using direct data-mining strategies has proven challenging, particularly for diseases of the nervous system, with its complicated anatomy and physiology. To address this challenge we have explored the use of ontologies to create formal descriptions of structural phenotypes across scales that are machine processable and amenable to logical inference. As proof of concept, we built a Neurodegenerative Disease Phenotype Ontology (NDPO) and an associated Phenotype Knowledge Base (PKB) using an entity-quality model that incorporates descriptions for both human disease phenotypes and those of animal models. Entities are drawn from community ontologies made available through the Neuroscience Information Framework (NIF) and qualities are drawn from the Phenotype and Trait Ontology (PATO). We generated ~1200 structured phenotype statements describing structural alterations at the subcellular, cellular and gross anatomical levels observed in 11 human neurodegenerative conditions and associated animal models. PhenoSim, an open source tool for comparing phenotypes, was used to issue a series of competency questions to compare individual phenotypes among organisms and to determine which animal models recapitulate phenotypic aspects of the human disease in aggregate. Overall, the system was able to use relationships within the ontology to bridge phenotypes across scales, returning non-trivial matches based on common subsumers that were meaningful to a neuroscientist with an advanced knowledge of neuroanatomy. The system can be used both to compare individual phenotypes and also phenotypes in aggregate. This proof of concept suggests that expressing complex phenotypes using formal ontologies provides considerable benefit for comparing phenotypes across scales and species. PMID:23717278

Conformity hinders the evolution of cooperation on scale-free networks

NASA Astrophysics Data System (ADS)

Peña, Jorge; Volken, Henri; Pestelacci, Enea; Tomassini, Marco

2009-07-01

We study the effects of conformity, the tendency of humans to imitate locally common behaviors, in the evolution of cooperation when individuals occupy the vertices of a graph and engage in the one-shot prisoner’s dilemma or the snowdrift game with their neighbors. Two different graphs are studied: rings (one-dimensional lattices with cyclic boundary conditions) and scale-free networks of the Barabási-Albert type. The proposed evolutionary-graph model is studied both by means of Monte Carlo simulations and an extended pair-approximation technique. We find improved levels of cooperation when evolution is carried on rings and individuals imitate according to both the traditional payoff bias and a conformist bias. More importantly, we show that scale-free networks are no longer powerful amplifiers of cooperation when fair amounts of conformity are introduced in the imitation rules of the players. Such weakening of the cooperation-promoting abilities of scale-free networks is the result of a less biased flow of information in scale-free topologies, making hubs more susceptible of being influenced by less-connected neighbors.

Connected Vehicle Pilot Deployment Program Phase 1 : Human Use Approval Summary : New York City

DOT National Transportation Integrated Search

2016-08-04

The New York City (NYC) Connected Vehicle (CV) Pilot Deployment will be the largest deployment of connected vehicle technology to date. The purpose of the human use approval activity is to apply the Institutional Review Board (IRB) process to the NYC...

Functional connectivity with the retrosplenial cortex predicts cognitive aging in rats.

PubMed

Ash, Jessica A; Lu, Hanbing; Taxier, Lisa R; Long, Jeffrey M; Yang, Yihong; Stein, Elliot A; Rapp, Peter R

2016-10-25

Changes in the functional connectivity (FC) of large-scale brain networks are a prominent feature of brain aging, but defining their relationship to variability along the continuum of normal and pathological cognitive outcomes has proved challenging. Here we took advantage of a well-characterized rat model that displays substantial individual differences in hippocampal memory during aging, uncontaminated by slowly progressive, spontaneous neurodegenerative disease. By this approach, we aimed to interrogate the underlying neural network substrates that mediate aging as a uniquely permissive condition and the primary risk for neurodegeneration. Using resting state (rs) blood oxygenation level-dependent fMRI and a restrosplenial/posterior cingulate cortex seed, aged rats demonstrated a large-scale network that had a spatial distribution similar to the default mode network (DMN) in humans, consistent with earlier findings in younger animals. Between-group whole brain contrasts revealed that aged subjects with documented deficits in memory (aged impaired) displayed widespread reductions in cortical FC, prominently including many areas outside the DMN, relative to both young adults (Y) and aged rats with preserved memory (aged unimpaired, AU). Whereas functional connectivity was relatively preserved in AU rats, they exhibited a qualitatively distinct network signature, comprising the loss of an anticorrelated network observed in Y adults. Together the findings demonstrate that changes in rs-FC are specifically coupled to variability in the cognitive outcome of aging, and that successful neurocognitive aging is associated with adaptive remodeling, not simply the persistence of youthful network dynamics.

Estimates of segregation and overlap of functional connectivity networks in the human cerebral cortex.

PubMed

Yeo, B T Thomas; Krienen, Fenna M; Chee, Michael W L; Buckner, Randy L

2014-03-01

The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. © 2013.

Estimates of Segregation and Overlap of Functional Connectivity Networks in the Human Cerebral Cortex

PubMed Central

Yeo, BT Thomas; Krienen, Fenna M; Chee, Michael WL; Buckner, Randy L

2014-01-01

The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1,000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. PMID:24185018

Probabilistic diffusion tractography and graph theory analysis reveal abnormal white matter structural connectivity networks in drug-naive boys with attention deficit/hyperactivity disorder.

PubMed

Cao, Qingjiu; Shu, Ni; An, Li; Wang, Peng; Sun, Li; Xia, Ming-Rui; Wang, Jin-Hui; Gong, Gao-Lang; Zang, Yu-Feng; Wang, Yu-Feng; He, Yong

2013-06-26

Attention-deficit/hyperactivity disorder (ADHD), which is characterized by core symptoms of inattention and hyperactivity/impulsivity, is one of the most common neurodevelopmental disorders of childhood. Neuroimaging studies have suggested that these behavioral disturbances are associated with abnormal functional connectivity among brain regions. However, the alterations in the structural connections that underlie these behavioral and functional deficits remain poorly understood. Here, we used diffusion magnetic resonance imaging and probabilistic tractography method to examine whole-brain white matter (WM) structural connectivity in 30 drug-naive boys with ADHD and 30 healthy controls. The WM networks of the human brain were constructed by estimating inter-regional connectivity probability. The topological properties of the resultant networks (e.g., small-world and network efficiency) were then analyzed using graph theoretical approaches. Nonparametric permutation tests were applied for between-group comparisons of these graphic metrics. We found that both the ADHD and control groups showed an efficient small-world organization in the whole-brain WM networks, suggesting a balance between structurally segregated and integrated connectivity patterns. However, relative to controls, patients with ADHD exhibited decreased global efficiency and increased shortest path length, with the most pronounced efficiency decreases in the left parietal, frontal, and occipital cortices. Intriguingly, the ADHD group showed decreased structural connectivity in the prefrontal-dominant circuitry and increased connectivity in the orbitofrontal-striatal circuitry, and these changes significantly correlated with the inattention and hyperactivity/impulsivity symptoms, respectively. The present study shows disrupted topological organization of large-scale WM networks in ADHD, extending our understanding of how structural disruptions of neuronal circuits underlie behavioral disturbances in patients with ADHD.

Connectivity in Agricultural Landscapes; do we Need More than a Dem?

NASA Astrophysics Data System (ADS)

Foster, I.; Boardman, J.; Favis-Mortlock, D.

2017-12-01

DEM's at a scale of metres to kilometres form the basis for many erosion models in part because data have long been available and published by national mapping agencies, such as the UK Ordnance Survey, and also because modelling gradient and flow pathways relative to topography is often simply executed within a GIS. That most landscape connectivity is not driven by topography is a simple issue that modellers appear reluctant to accept, or too challenging to model, yet there is an urgent need to rethink how landscapes function and what drives connectivity laterally and longitudinally at different spatial and temporal scales within agricultural landscapes. Landscape connectivity is driven by a combination of natural and anthropogenic factors that can enhance, reduce or eliminate connectivity at different timescales. In this paper we explore the use of a range of data sources that can be used to build a detailed picture of landscape connectivity at different scales. From a number of case studies we combine the use of maps, lidar data, field mapping, lake and floodplain coring fingerprinting and process monitoring to identify lateral and longitudinal connectivity and the way in which these have changed through time.

Wetland characteristics linked to broad-scale patterns in Culiseta melanura abundance and eastern equine encephalitis virus infection.

PubMed

Skaff, Nicholas K; Armstrong, Philip M; Andreadis, Theodore G; Cheruvelil, Kendra S

2017-10-18

Eastern equine encephalitis virus (EEEV) is an expanding mosquito-borne threat to humans and domestic animal populations in the northeastern United States. Outbreaks of EEEV are challenging to predict due to spatial and temporal uncertainty in the abundance and viral infection of Cs. melanura, the principal enzootic vector. EEEV activity may be closely linked to wetlands because they provide essential habitat for mosquito vectors and avian reservoir hosts. However, wetlands are not homogeneous and can vary by vegetation, connectivity, size, and inundation patterns. Wetlands may also have different effects on EEEV transmission depending on the assessed spatial scale. We investigated associations between wetland characteristics and Cs. melanura abundance and infection with EEEV at multiple spatial scales in Connecticut, USA. Our findings indicate that wetland vegetative characteristics have strong associations with Cs. melanura abundance. Deciduous and evergreen forested wetlands were associated with higher Cs. melanura abundance, likely because these wetlands provide suitable subterranean habitat for Cs. melanura development. In contrast, Cs. melanura abundance was negatively associated with emergent and scrub/shrub wetlands, and wetland connectivity to streams. These relationships were generally strongest at broad spatial scales. Additionally, the relationships between wetland characteristics and EEEV infection in Cs. melanura were generally weak. However, Cs. melanura abundance was strongly associated with EEEV infection, suggesting that wetland-associated changes in abundance may be indirectly linked to EEEV infection in Cs. melanura. Finally, we found that wet hydrological conditions during the transmission season and during the fall/winter preceding the transmission season were associated with higher Cs. melanura abundance and EEEV infection, indicating that wet conditions are favorable for EEEV transmission. These results expand the broad-scale understanding of the effects of wetlands on EEEV transmission and help to reduce the spatial and temporal uncertainty associated with EEEV outbreaks.

The Structural Connectome of the Human Central Homeostatic Network.

PubMed

Edlow, Brian L; McNab, Jennifer A; Witzel, Thomas; Kinney, Hannah C

2016-04-01

Homeostatic adaptations to stress are regulated by interactions between the brainstem and regions of the forebrain, including limbic sites related to respiratory, autonomic, affective, and cognitive processing. Neuroanatomic connections between these homeostatic regions, however, have not been thoroughly identified in the human brain. In this study, we perform diffusion spectrum imaging tractography using the MGH-USC Connectome MRI scanner to visualize structural connections in the human brain linking autonomic and cardiorespiratory nuclei in the midbrain, pons, and medulla oblongata with forebrain sites critical to homeostatic control. Probabilistic tractography analyses in six healthy adults revealed connections between six brainstem nuclei and seven forebrain regions, several over long distances between the caudal medulla and cerebral cortex. The strongest evidence for brainstem-homeostatic forebrain connectivity in this study was between the brainstem midline raphe and the medial temporal lobe. The subiculum and amygdala were the sampled forebrain nodes with the most extensive brainstem connections. Within the human brainstem-homeostatic forebrain connectome, we observed that a lateral forebrain bundle, whose connectivity is distinct from that of rodents and nonhuman primates, is the primary conduit for connections between the brainstem and medial temporal lobe. This study supports the concept that interconnected brainstem and forebrain nodes form an integrated central homeostatic network (CHN) in the human brain. Our findings provide an initial foundation for elucidating the neuroanatomic basis of homeostasis in the normal human brain, as well as for mapping CHN disconnections in patients with disorders of homeostasis, including sudden and unexpected death, and epilepsy.

Herbivorous fishes, ecosystem function and mobile links on coral reefs

NASA Astrophysics Data System (ADS)

Welsh, J. Q.; Bellwood, D. R.

2014-06-01

Understanding large-scale movement of ecologically important taxa is key to both species and ecosystem management. Those species responsible for maintaining functional connectivity between habitats are often called mobile links and are regarded as essential elements of resilience. By providing connectivity, they support resilience across spatial scales. Most marine organisms, including fishes, have long-term, biogeographic-scale connectivity through larval movement. Although most reef species are highly site attached after larval settlement, some taxa may also be able to provide rapid, reef-scale connectivity as adults. On coral reefs, the identity of such taxa and the extent of their mobility are not yet known. We use acoustic telemetry to monitor the movements of Kyphosus vaigiensis, one of the few reef fishes that feeds on adult brown macroalgae. Unlike other benthic herbivorous fish species, it also exhibits large-scale (>2 km) movements. Individual K. vaigiensis cover, on average, a 2.5 km length of reef (11 km maximum) each day. These large-scale movements suggest that this species may act as a mobile link, providing functional connectivity, should the need arise, and helping to support functional processes across habitats and spatial scales. An analysis of published studies of home ranges in reef fishes found a consistent relationship between home range size and body length. K. vaigiensis is the sole herbivore to depart significantly from the expected home range-body size relationship, with home range sizes more comparable to exceptionally mobile large pelagic predators rather than other reef herbivores. While the large-scale movements of K. vaigiensis reveal its potential capacity to enhance resilience over large areas, it also emphasizes the potential limitations of small marine reserves to protect some herbivore populations.

The macroecology of sustainability

USGS Publications Warehouse

Burger, Joseph R.; Allen, Craig D.; Brown, James H.; Burnside, William R.; Davidson, Ana D.; Fristoe, Trevor S.; Hamilton, Marcus J.; Mercado-Silva, Norman; Nekola, Jeffrey C.; Okie, Jordan G.; Zuo, Wenyun

2012-01-01

The discipline of sustainability science has emerged in response to concerns of natural and social scientists, policymakers, and lay people about whether the Earth can continue to support human population growth and economic prosperity. Yet, sustainability science has developed largely independently from and with little reference to key ecological principles that govern life on Earth. A macroecological perspective highlights three principles that should be integral to sustainability science: 1) physical conservation laws govern the flows of energy and materials between human systems and the environment, 2) smaller systems are connected by these flows to larger systems in which they are embedded, and 3) global constraints ultimately limit flows at smaller scales. Over the past few decades, decreasing per capita rates of consumption of petroleum, phosphate, agricultural land, fresh water, fish, and wood indicate that the growing human population has surpassed the capacity of the Earth to supply enough of these essential resources to sustain even the current population and level of socioeconomic development.

Modeling infectious disease dynamics in the complex landscape of global health

PubMed Central

Heesterbeek, Hans; Anderson, Roy; Andreasen, Viggo; Bansal, Shweta; De Angelis, Daniela; Dye, Chris; Eames, Ken; Edmunds, John; Frost, Simon; Funk, Sebastian; Hollingsworth, Deirdre; House, Thomas; Isham, Valerie; Klepac, Petra; Lessler, Justin; Lloyd-Smith, James; Metcalf, Jessica; Mollison, Denis; Pellis, Lorenzo; Pulliam, Juliet; Roberts, Mick; Viboud, Cecile

2015-01-01

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational and spatial scales, which even within a single pathogen often span hours to months, cellular to ecosystem levels, and local to pandemic spread. Some pathogens are directly transmitted between individuals of a single species, while others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity, and dynamic human behavior, raise prevention and control from formerly national to international issues. In the face of this complexity, mathematical models offer essential tools for synthesizing information to understand epidemiological patterns, and for developing the quantitative evidence base for decision-making in global health. PMID:25766240

Modeling infectious disease dynamics in the complex landscape of global health.

PubMed

Heesterbeek, Hans; Anderson, Roy M; Andreasen, Viggo; Bansal, Shweta; De Angelis, Daniela; Dye, Chris; Eames, Ken T D; Edmunds, W John; Frost, Simon D W; Funk, Sebastian; Hollingsworth, T Deirdre; House, Thomas; Isham, Valerie; Klepac, Petra; Lessler, Justin; Lloyd-Smith, James O; Metcalf, C Jessica E; Mollison, Denis; Pellis, Lorenzo; Pulliam, Juliet R C; Roberts, Mick G; Viboud, Cecile

2015-03-13

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health. Copyright © 2015, American Association for the Advancement of Science.

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity.

PubMed

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N

2015-01-01

To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen-Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure-function relationships but requires further validation in other populations of CP.

Importance of human right inferior frontoparietal network connected by inferior branch of superior longitudinal fasciculus tract in corporeal awareness of kinesthetic illusory movement.

PubMed

Amemiya, Kaoru; Naito, Eiichi

2016-05-01

It is generally believed that the human right cerebral hemisphere plays a dominant role in corporeal awareness, which is highly associated with conscious experience of the physical self. Prompted by our previous findings, we examined whether the right frontoparietal activations often observed when people experience kinesthetic illusory limb movement are supported by a large-scale brain network connected by a specific branch of the superior longitudinal fasciculus fiber tracts (SLF I, II, and III). We scanned brain activity with functional magnetic resonance imaging (MRI) while nineteen blindfolded healthy volunteers experienced illusory movement of the right stationary hand elicited by tendon vibration, which was replicated after the scanning. We also scanned brain activity when they executed and imagined right hand movement, and identified the active brain regions during illusion, execution, and imagery in relation to the SLF fiber tracts. We found that illusion predominantly activated the right inferior frontoparietal regions connected by SLF III, which were not substantially recruited during execution and imagery. Among these regions, activities in the right inferior parietal cortices and inferior frontal cortices showed right-side dominance and correlated well with the amount of illusion (kinesthetic illusory awareness) experienced by the participants. The results illustrated the predominant involvement of the right inferior frontoparietal network connected by SLF III when people recognize postural changes of their limb. We assume that the network bears a series of functions, specifically, monitoring the current status of the musculoskeletal system, and building-up and updating our postural model (body schema), which could be a basis for the conscious experience of the physical self. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Intrinsic, stimulus-driven and task-dependent connectivity in human auditory cortex.

PubMed

Häkkinen, Suvi; Rinne, Teemu

2018-06-01

A hierarchical and modular organization is a central hypothesis in the current primate model of auditory cortex (AC) but lacks validation in humans. Here we investigated whether fMRI connectivity at rest and during active tasks is informative of the functional organization of human AC. Identical pitch-varying sounds were presented during a visual discrimination (i.e. no directed auditory attention), pitch discrimination, and two versions of pitch n-back memory tasks. Analysis based on fMRI connectivity at rest revealed a network structure consisting of six modules in supratemporal plane (STP), temporal lobe, and inferior parietal lobule (IPL) in both hemispheres. In line with the primate model, in which higher-order regions have more longer-range connections than primary regions, areas encircling the STP module showed the highest inter-modular connectivity. Multivariate pattern analysis indicated significant connectivity differences between the visual task and rest (driven by the presentation of sounds during the visual task), between auditory and visual tasks, and between pitch discrimination and pitch n-back tasks. Further analyses showed that these differences were particularly due to connectivity modulations between the STP and IPL modules. While the results are generally in line with the primate model, they highlight the important role of human IPL during the processing of both task-irrelevant and task-relevant auditory information. Importantly, the present study shows that fMRI connectivity at rest, during presentation of sounds, and during active listening provides novel information about the functional organization of human AC.

Evolution and development of brain networks: from Caenorhabditis elegans to Homo sapiens.

PubMed

Kaiser, Marcus; Varier, Sreedevi

2011-01-01

Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. 'Small-world' topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints.

Continent-wide panmixia of an African fruit bat facilitates transmission of potentially zoonotic viruses.

PubMed

Peel, Alison J; Sargan, David R; Baker, Kate S; Hayman, David T S; Barr, Jennifer A; Crameri, Gary; Suu-Ire, Richard; Broder, Christopher C; Lembo, Tiziana; Wang, Lin-Fa; Fooks, Anthony R; Rossiter, Stephen J; Wood, James L N; Cunningham, Andrew A

2013-01-01

The straw-coloured fruit bat, Eidolon helvum, is Africa's most widely distributed and commonly hunted fruit bat, often living in close proximity to human populations. This species has been identified as a reservoir of potentially zoonotic viruses, but uncertainties remain regarding viral transmission dynamics and mechanisms of persistence. Here we combine genetic and serological analyses of populations across Africa, to determine the extent of epidemiological connectivity among E. helvum populations. Multiple markers reveal panmixia across the continental range, at a greater geographical scale than previously recorded for any other mammal, whereas populations on remote islands were genetically distinct. Multiple serological assays reveal antibodies to henipaviruses and Lagos bat virus in all locations, including small isolated island populations, indicating that factors other than population size and connectivity may be responsible for viral persistence. Our findings have potentially important public health implications, and highlight a need to avoid disturbances that may precipitate viral spillover.

Clustering of 770,000 genomes reveals post-colonial population structure of North America

NASA Astrophysics Data System (ADS)

Han, Eunjung; Carbonetto, Peter; Curtis, Ross E.; Wang, Yong; Granka, Julie M.; Byrnes, Jake; Noto, Keith; Kermany, Amir R.; Myres, Natalie M.; Barber, Mathew J.; Rand, Kristin A.; Song, Shiya; Roman, Theodore; Battat, Erin; Elyashiv, Eyal; Guturu, Harendra; Hong, Eurie L.; Chahine, Kenneth G.; Ball, Catherine A.

2017-02-01

Despite strides in characterizing human history from genetic polymorphism data, progress in identifying genetic signatures of recent demography has been limited. Here we identify very recent fine-scale population structure in North America from a network of over 500 million genetic (identity-by-descent, IBD) connections among 770,000 genotyped individuals of US origin. We detect densely connected clusters within the network and annotate these clusters using a database of over 20 million genealogical records. Recent population patterns captured by IBD clustering include immigrants such as Scandinavians and French Canadians; groups with continental admixture such as Puerto Ricans; settlers such as the Amish and Appalachians who experienced geographic or cultural isolation; and broad historical trends, including reduced north-south gene flow. Our results yield a detailed historical portrait of North America after European settlement and support substantial genetic heterogeneity in the United States beyond that uncovered by previous studies.

Clustering of 770,000 genomes reveals post-colonial population structure of North America

PubMed Central

Han, Eunjung; Carbonetto, Peter; Curtis, Ross E.; Wang, Yong; Granka, Julie M.; Byrnes, Jake; Noto, Keith; Kermany, Amir R.; Myres, Natalie M.; Barber, Mathew J.; Rand, Kristin A.; Song, Shiya; Roman, Theodore; Battat, Erin; Elyashiv, Eyal; Guturu, Harendra; Hong, Eurie L.; Chahine, Kenneth G.; Ball, Catherine A.

2017-01-01

Despite strides in characterizing human history from genetic polymorphism data, progress in identifying genetic signatures of recent demography has been limited. Here we identify very recent fine-scale population structure in North America from a network of over 500 million genetic (identity-by-descent, IBD) connections among 770,000 genotyped individuals of US origin. We detect densely connected clusters within the network and annotate these clusters using a database of over 20 million genealogical records. Recent population patterns captured by IBD clustering include immigrants such as Scandinavians and French Canadians; groups with continental admixture such as Puerto Ricans; settlers such as the Amish and Appalachians who experienced geographic or cultural isolation; and broad historical trends, including reduced north-south gene flow. Our results yield a detailed historical portrait of North America after European settlement and support substantial genetic heterogeneity in the United States beyond that uncovered by previous studies. PMID:28169989

Clustering of 770,000 genomes reveals post-colonial population structure of North America.

PubMed

Han, Eunjung; Carbonetto, Peter; Curtis, Ross E; Wang, Yong; Granka, Julie M; Byrnes, Jake; Noto, Keith; Kermany, Amir R; Myres, Natalie M; Barber, Mathew J; Rand, Kristin A; Song, Shiya; Roman, Theodore; Battat, Erin; Elyashiv, Eyal; Guturu, Harendra; Hong, Eurie L; Chahine, Kenneth G; Ball, Catherine A

2017-02-07

Despite strides in characterizing human history from genetic polymorphism data, progress in identifying genetic signatures of recent demography has been limited. Here we identify very recent fine-scale population structure in North America from a network of over 500 million genetic (identity-by-descent, IBD) connections among 770,000 genotyped individuals of US origin. We detect densely connected clusters within the network and annotate these clusters using a database of over 20 million genealogical records. Recent population patterns captured by IBD clustering include immigrants such as Scandinavians and French Canadians; groups with continental admixture such as Puerto Ricans; settlers such as the Amish and Appalachians who experienced geographic or cultural isolation; and broad historical trends, including reduced north-south gene flow. Our results yield a detailed historical portrait of North America after European settlement and support substantial genetic heterogeneity in the United States beyond that uncovered by previous studies.

Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury

PubMed Central

Wu, Xuehai; Zou, Qihong; Hu, Jin; Tang, Weijun; Mao, Ying; Gao, Liang; Zhu, Jianhong; Jin, Yi; Wu, Xin; Lu, Lu; Zhang, Yaojun; Zhang, Yao; Dai, Zhengjia; Gao, Jia-Hong; Weng, Xuchu; Northoff, Georg; Giacino, Joseph T.; He, Yong

2015-01-01

For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI. SIGNIFICANCE STATEMENT Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological mechanisms remain elusive. Using a large sample of patients with varying degrees of consciousness loss, we demonstrate that intrinsic functional connectivity strength in many brain regions, especially in the posterior cingulate cortex and precuneus, significantly correlated with consciousness level and recovery outcome. We further demonstrate that the functional connectivity pattern of these regions can predict patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%. Our study thus provides potentially important biomarkers of acquired brain injury in clinical diagnosis, prediction of recovery outcome, and decision making for treatment strategies for patients with severe loss of consciousness. PMID:26377477

Temporal node centrality in complex networks

NASA Astrophysics Data System (ADS)

Kim, Hyoungshick; Anderson, Ross

2012-02-01

Many networks are dynamic in that their topology changes rapidly—on the same time scale as the communications of interest between network nodes. Examples are the human contact networks involved in the transmission of disease, ad hoc radio networks between moving vehicles, and the transactions between principals in a market. While we have good models of static networks, so far these have been lacking for the dynamic case. In this paper we present a simple but powerful model, the time-ordered graph, which reduces a dynamic network to a static network with directed flows. This enables us to extend network properties such as vertex degree, closeness, and betweenness centrality metrics in a very natural way to the dynamic case. We then demonstrate how our model applies to a number of interesting edge cases, such as where the network connectivity depends on a small number of highly mobile vertices or edges, and show that our centrality definition allows us to track the evolution of connectivity. Finally we apply our model and techniques to two real-world dynamic graphs of human contact networks and then discuss the implication of temporal centrality metrics in the real world.

A Model for Professional Education in the 21st Century: Integrating Humanities and Engineering through Writing.

ERIC Educational Resources Information Center

Olds, Barbara M.; Miller, Ronald L.

The "HumEn" (Humanities/Engineering Integration) program developed at the Colorado School of Mines integrates humanities and engineering through reading and writing. Through integrative reading and writing engineering students are led to make appropriate connections between the humanities and their technical work, connections that will…

Sustaining coupled social-ecological marine systems in Mexico's Gulf of California region

NASA Astrophysics Data System (ADS)

Leslie, H.

2016-02-01

Marine ecosystems provide many benefits to people, including food, protection from coastal storms, and places for recreation and spiritual renewal. These benefits are threatened by human impacts at multiple scales, including fisheries over-exploitation and global climatic change. More solutions-oriented knowledge of the connections between people and nature is urgently needed. I will discuss the approach my collaborators and I have developed to investigate the connections between people and marine ecosystems in the context of the small-scale fisheries of Mexico's Gulf of California. To illustrate the value of this coupled systems approach, I will present findings from two geographic scales. First, using a coupled bio-economic model based on several communities in the Mexican state of Baja California Sur (BCS), I will show how fishers' decisions are influenced by both climatic and institutional variation, and the consequences of these interactions for economic and ecological outcomes associated with fishing. Second, I will place these local-scale results in a broader context. Drawing on both natural and social science theory and data, I will show how environmental and institutional factors related to sustainability vary substantially throughout BCS. Fishing communities that exhibit greater potential for social-ecological sustainability in one dimension do not necessarily exhibit it in others. These results highlight the importance of integrative, coupled system analyses when implementing spatial planning and other ecosystem-based strategies and yield an understanding of the sustainability of coupled social-ecological systems that is quite distinct from that provided by either biophysical or social sciences alone.

Modulatory effects by neodymium-doped yttrium aluminum garnet laser on fibroblast attachment to single rooted tooth surfaces following ultrasonic scaling and root planning: An in vitro study

PubMed Central

Negi, Shanta; Krishnamurthy, Malathi; Ganji, Kiran Kumar; Pendor, Sunil

2015-01-01

Context: One of the most important goals of periodontal therapy is connective tissue reattachment to previously diseased root surfaces. In the recent years, laser therapy has been considered as an important tool in improving the treatment of periodontal disease. Aims: To evaluate the neodymium-doped yttrium aluminum garnet (Nd: YAG) lasers effects on root surfaces affected by periodontal disease and compare this treatment with scaling and root planning (SRP) in terms of fibroblast attachment. Materials and Methods: A sample of 30 single-rooted human teeth extracted because of advanced periodontal disease was used in this study. Sixty specimens obtained by longitudinal sectioning were randomly divided in three groups. Group A control (untreated); Group B SRP; Group C laser (Nd: YAG) and ultrasonic scaling. All specimens were incubated with fibroblast suspension and then fixed and observed under scanning electron microscope. Results: With a median of 8, the control group (Group A) exhibited the least number of total fibroblasts among all the three groups. The laser and scaling - treated group (Group C) showed the highest number of fibroblasts (median = 49, mean ± standard deviation [SD] = 48.28 ± 17.18), followed by SRP only (Group B, median = 22, mean ± SD = 22.24 ± 8.67). Conclusions: Nd: YAG laser irradiation at specific energy densities can be used as a useful tool to condition the root surfaces, enhancing fibroblast attachment. Hence aiding in re-establishment of the connective tissue attachment to the root surfaces of previously diseased teeth. PMID:25810589

Relationship Between Large-Scale Functional and Structural Covariance Networks in Idiopathic Generalized Epilepsy

PubMed Central

Zhang, Zhiqiang; Mantini, Dante; Xu, Qiang; Wang, Zhengge; Chen, Guanghui; Jiao, Qing; Zang, Yu-Feng

2013-01-01

Abstract The human brain can be modeled as a network, whose structure can be revealed by either anatomical or functional connectivity analyses. Little is known, so far, about the topological features of the large-scale interregional functional covariance network (FCN) in the brain. Further, the relationship between the FCN and the structural covariance network (SCN) has not been characterized yet, in the intact as well as in the diseased brain. Here, we studied 59 patients with idiopathic generalized epilepsy characterized by tonic–clonic seizures and 59 healthy controls. We estimated the FCN and the SCN by measuring amplitude of low-frequency fluctuations (ALFF) and gray matter volume (GMV), respectively, and then we conducted graph theoretical analyses. Our ALFF-based FCN and GMV-based results revealed that the normal human brain is characterized by specific topological properties such as small worldness and highly-connected hub regions. The patients had an altered overall topology compared to the controls, suggesting that epilepsy is primarily a disorder of the cerebral network organization. Further, the patients had altered nodal characteristics in the subcortical and medial temporal regions and default-mode regions, for both the FCN and SCN. Importantly, the correspondence between the FCN and SCN was significantly larger in patients than in the controls. These results support the hypothesis that the SCN reflects shared long-term trophic mechanisms within functionally synchronous systems. They can also provide crucial information for understanding the interactions between the whole-brain network organization and pathology in generalized tonic–clonic seizures. PMID:23510272

Individual differences and time-varying features of modular brain architecture.

PubMed

Liao, Xuhong; Cao, Miao; Xia, Mingrui; He, Yong

2017-05-15

Recent studies have suggested that human brain functional networks are topologically organized into functionally specialized but inter-connected modules to facilitate efficient information processing and highly flexible cognitive function. However, these studies have mainly focused on group-level network modularity analyses using "static" functional connectivity approaches. How these extraordinary modular brain structures vary across individuals and spontaneously reconfigure over time remain largely unknown. Here, we employed multiband resting-state functional MRI data (N=105) from the Human Connectome Project and a graph-based modularity analysis to systematically investigate individual variability and dynamic properties in modular brain networks. We showed that the modular structures of brain networks dramatically vary across individuals, with higher modular variability primarily in the association cortex (e.g., fronto-parietal and attention systems) and lower variability in the primary systems. Moreover, brain regions spontaneously changed their module affiliations on a temporal scale of seconds, which cannot be simply attributable to head motion and sampling error. Interestingly, the spatial pattern of intra-subject dynamic modular variability largely overlapped with that of inter-subject modular variability, both of which were highly reproducible across repeated scanning sessions. Finally, the regions with remarkable individual/temporal modular variability were closely associated with network connectors and the number of cognitive components, suggesting a potential contribution to information integration and flexible cognitive function. Collectively, our findings highlight individual modular variability and the notable dynamic characteristics in large-scale brain networks, which enhance our understanding of the neural substrates underlying individual differences in a variety of cognition and behaviors. Copyright © 2017 Elsevier Inc. All rights reserved.

The epidemic spreading model and the direction of information flow in brain networks.

PubMed

Meier, J; Zhou, X; Hillebrand, A; Tewarie, P; Stam, C J; Van Mieghem, P

2017-05-15

The interplay between structural connections and emerging information flow in the human brain remains an open research problem. A recent study observed global patterns of directional information flow in empirical data using the measure of transfer entropy. For higher frequency bands, the overall direction of information flow was from posterior to anterior regions whereas an anterior-to-posterior pattern was observed in lower frequency bands. In this study, we applied a simple Susceptible-Infected-Susceptible (SIS) epidemic spreading model on the human connectome with the aim to reveal the topological properties of the structural network that give rise to these global patterns. We found that direct structural connections induced higher transfer entropy between two brain regions and that transfer entropy decreased with increasing distance between nodes (in terms of hops in the structural network). Applying the SIS model, we were able to confirm the empirically observed opposite information flow patterns and posterior hubs in the structural network seem to play a dominant role in the network dynamics. For small time scales, when these hubs acted as strong receivers of information, the global pattern of information flow was in the posterior-to-anterior direction and in the opposite direction when they were strong senders. Our analysis suggests that these global patterns of directional information flow are the result of an unequal spatial distribution of the structural degree between posterior and anterior regions and their directions seem to be linked to different time scales of the spreading process. Copyright © 2017 Elsevier Inc. All rights reserved.

Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex

PubMed Central

Liu, Hesheng; Agam, Yigal; Madsen, Joseph R.; Kreiman, Gabriel

2010-01-01

Summary The difficulty of visual recognition stems from the need to achieve high selectivity while maintaining robustness to object transformations within hundreds of milliseconds. Theories of visual recognition differ in whether the neuronal circuits invoke recurrent feedback connections or not. The timing of neurophysiological responses in visual cortex plays a key role in distinguishing between bottom-up and top-down theories. Here we quantified at millisecond resolution the amount of visual information conveyed by intracranial field potentials from 912 electrodes in 11 human subjects. We could decode object category information from human visual cortex in single trials as early as 100 ms post-stimulus. Decoding performance was robust to depth rotation and scale changes. The results suggest that physiological activity in the temporal lobe can account for key properties of visual recognition. The fast decoding in single trials is compatible with feed-forward theories and provides strong constraints for computational models of human vision. PMID:19409272

Theta and Alpha Oscillations Are Traveling Waves in the Human Neocortex.

PubMed

Zhang, Honghui; Watrous, Andrew J; Patel, Ansh; Jacobs, Joshua

2018-06-01

Human cognition requires the coordination of neural activity across widespread brain networks. Here, we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found contiguous clusters of cortex in individual patients with oscillations at specific frequencies within 2 to 15 Hz. These oscillatory clusters displayed spatial phase gradients, indicating that they formed traveling waves that propagated at ∼0.25-0.75 m/s. Traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent when subjects performed the task well. Human traveling theta and alpha waves can be modeled by a network of coupled oscillators because the direction of wave propagation correlated with the spatial orientation of local frequency gradients. Our findings suggest that oscillations support brain connectivity by organizing neural processes across space and time. Copyright © 2018 Elsevier Inc. All rights reserved.

The relationship between nature relatedness and anxiety.

PubMed

Martyn, Patricia; Brymer, Eric

2016-07-01

This study investigated the relationship between anxiety and feelings of being connected to nature. Two standardised self-report scales, the Nature Relatedness Scale and the State Trait Inventory for Cognitive and Somatic Anxiety, were used in tandem with a qualitative question. Quantitative results indicated that connection to nature was significantly related to lower levels of overall, state cognitive and trait cognitive anxiety. Qualitative results revealed seven themes: relaxation, time out, enjoyment, connection, expanse, sensory engagement and a healthy perspective. Taken together, these results suggest that opportunities that enhance experiences of being connected to nature may reduce unhelpful anxiety. © The Author(s) 2014.

Altered Insula Connectivity under MDMA.

PubMed

Walpola, Ishan C; Nest, Timothy; Roseman, Leor; Erritzoe, David; Feilding, Amanda; Nutt, David J; Carhart-Harris, Robin L

2017-10-01

Recent work with noninvasive human brain imaging has started to investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA) on large-scale patterns of brain activity. MDMA, a potent monoamine-releaser with particularly pronounced serotonin- releasing properties, has unique subjective effects that include: marked positive mood, pleasant/unusual bodily sensations and pro-social, empathic feelings. However, the neurobiological basis for these effects is not properly understood, and the present analysis sought to address this knowledge gap. To do this, we administered MDMA-HCl (100 mg p.o.) and, separately, placebo (ascorbic acid) in a randomized, double-blind, repeated-measures design with twenty-five healthy volunteers undergoing fMRI scanning. We then employed a measure of global resting-state functional brain connectivity and follow-up seed-to-voxel analysis to the fMRI data we acquired. Results revealed decreased right insula/salience network functional connectivity under MDMA. Furthermore, these decreases in right insula/salience network connectivity correlated with baseline trait anxiety and acute experiences of altered bodily sensations under MDMA. The present findings highlight insular disintegration (ie, compromised salience network membership) as a neurobiological signature of the MDMA experience, and relate this brain effect to trait anxiety and acutely altered bodily sensations-both of which are known to be associated with insular functioning.

Two distinct neural mechanisms underlying indirect reciprocity.

PubMed

Watanabe, Takamitsu; Takezawa, Masanori; Nakawake, Yo; Kunimatsu, Akira; Yamasue, Hidenori; Nakamura, Mitsuhiro; Miyashita, Yasushi; Masuda, Naoki

2014-03-18

Cooperation is a hallmark of human society. Humans often cooperate with strangers even if they will not meet each other again. This so-called indirect reciprocity enables large-scale cooperation among nonkin and can occur based on a reputation mechanism or as a succession of pay-it-forward behavior. Here, we provide the functional and anatomical neural evidence for two distinct mechanisms governing the two types of indirect reciprocity. Cooperation occurring as reputation-based reciprocity specifically recruited the precuneus, a region associated with self-centered cognition. During such cooperative behavior, the precuneus was functionally connected with the caudate, a region linking rewards to behavior. Furthermore, the precuneus of a cooperative subject had a strong resting-state functional connectivity (rsFC) with the caudate and a large gray matter volume. In contrast, pay-it-forward reciprocity recruited the anterior insula (AI), a brain region associated with affective empathy. The AI was functionally connected with the caudate during cooperation occurring as pay-it-forward reciprocity, and its gray matter volume and rsFC with the caudate predicted the tendency of such cooperation. The revealed difference is consistent with the existing results of evolutionary game theory: although reputation-based indirect reciprocity robustly evolves as a self-interested behavior in theory, pay-it-forward indirect reciprocity does not on its own. The present study provides neural mechanisms underlying indirect reciprocity and suggests that pay-it-forward reciprocity may not occur as myopic profit maximization but elicit emotional rewards.

Two distinct neural mechanisms underlying indirect reciprocity

PubMed Central

Watanabe, Takamitsu; Takezawa, Masanori; Nakawake, Yo; Kunimatsu, Akira; Yamasue, Hidenori; Nakamura, Mitsuhiro; Miyashita, Yasushi; Masuda, Naoki

2014-01-01

Cooperation is a hallmark of human society. Humans often cooperate with strangers even if they will not meet each other again. This so-called indirect reciprocity enables large-scale cooperation among nonkin and can occur based on a reputation mechanism or as a succession of pay-it-forward behavior. Here, we provide the functional and anatomical neural evidence for two distinct mechanisms governing the two types of indirect reciprocity. Cooperation occurring as reputation-based reciprocity specifically recruited the precuneus, a region associated with self-centered cognition. During such cooperative behavior, the precuneus was functionally connected with the caudate, a region linking rewards to behavior. Furthermore, the precuneus of a cooperative subject had a strong resting-state functional connectivity (rsFC) with the caudate and a large gray matter volume. In contrast, pay-it-forward reciprocity recruited the anterior insula (AI), a brain region associated with affective empathy. The AI was functionally connected with the caudate during cooperation occurring as pay-it-forward reciprocity, and its gray matter volume and rsFC with the caudate predicted the tendency of such cooperation. The revealed difference is consistent with the existing results of evolutionary game theory: although reputation-based indirect reciprocity robustly evolves as a self-interested behavior in theory, pay-it-forward indirect reciprocity does not on its own. The present study provides neural mechanisms underlying indirect reciprocity and suggests that pay-it-forward reciprocity may not occur as myopic profit maximization but elicit emotional rewards. PMID:24591599

Mapping the Alzheimer’s Brain with Connectomics

PubMed Central

Xie, Teng; He, Yong

2012-01-01

Alzheimer’s disease (AD) is the most common form of dementia. As an incurable, progressive, and neurodegenerative disease, it causes cognitive and memory deficits. However, the biological mechanisms underlying the disease are not thoroughly understood. In recent years, non-invasive neuroimaging and neurophysiological techniques [e.g., structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, and EEG/MEG] and graph theory based network analysis have provided a new perspective on structural and functional connectivity patterns of the human brain (i.e., the human connectome) in health and disease. Using these powerful approaches, several recent studies of patients with AD exhibited abnormal topological organization in both global and regional properties of neuronal networks, indicating that AD not only affects specific brain regions, but also alters the structural and functional associations between distinct brain regions. Specifically, disruptive organization in the whole-brain networks in AD is involved in the loss of small-world characters and the re-organization of hub distributions. These aberrant neuronal connectivity patterns were associated with cognitive deficits in patients with AD, even with genetic factors in healthy aging. These studies provide empirical evidence to support the existence of an aberrant connectome of AD. In this review we will summarize recent advances discovered in large-scale brain network studies of AD, mainly focusing on graph theoretical analysis of brain connectivity abnormalities. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis and monitoring. PMID:22291664

The scale effect on soil erosion. A plot approach to understand connectivity on slopes under cultivation at variable plot sizes and under Mediterranean climatic conditions

NASA Astrophysics Data System (ADS)

Cerdà, Artemi; Bagarello, Vicenzo; Ferro, Vito; Iovino, Massimo; Borja, Manuel Estaban Lucas; Francisco Martínez Murillo, Juan; González Camarena, Rafael

2017-04-01

It is well known that soil erosion changes along time and seasons and attention was paid to this issue in the past (González Hidalgo et al., 2010; 2012). However, although the scientific community knows that soil erosion is also a time spatial scale-scale dependent process (Parsons et al., 1990; Cerdà et al., 2009; González Hidalgo et al., 2013; Sadeghi et al., 2015) very little is done on this topic. This is due to the fact that at different scales, different soil erosion mechanisms (splash, sheetflow, rill development) are active and their rates change with the scale of measurement (Wainwright et al., 2002; López-Vicente et al., 2015). This is making the research on soil erosion complex and difficult, and it is necessary to develop a conceptual framework but also measurements that will inform about the soil erosion behaviour. Connectivity is the key concept to understand how changes in the scale results in different rates of soil and water losses (Parsons et al., 1996; Parsons et al., 2015; Poeppl et al., 2016). Most of the research developed around the connectivity concept was applied in watershed or basin scales (Galdino et al., 2016; Martínez-Casasnovas et al., 2016; López Vicente et al., 2016; Marchamalo et al., 2015; Masselink et al., 2016), but very little is known about the connectivity issue at slope scale (Cerdà and Jurgensen, 2011). El Teularet (Eastern Iberian Peninsula) and Sparacia (Sicily) soil erosion experimental stations are being active for 15 years and data collected on different plots sizes can shed light into the effect of scale on runoff generation and soil losses at different scales and give information to understand how the transport of materials is determined by the connectivity between pedon to slope scale (Cerdà et al., 2014; Bagarello et al., 2015a; 2015b). The comparison of the results of the two research stations will shed light into the rates of soil erosion and mechanisms involved that act under different scales. Our research share information collected during the last 15 years in the Sparacia and El Teularet soil erosion experimental stations under the same management and research how the concept of connectivity can help us to have a better understanding of the soil erosion process, and the effect of scale. All the data will be treated to show the runoff and sediment eroded at different plot sizes to understand how the sediment is transported at event scale. The rainfall characteristics will be also analysed to understand the soil erosion processes at different scales. Acknowledgements The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n 603498 (RECARE project) and the CGL2013- 47862-C2-1-R and CGL2016-75178-C2-2-R national research projects. References Bagarello, V., Ferro, V., Pampalone, V. 2015b. A new version of the USLE-MM for predicting bare plot soil loss at the Sparacia (South Italy) experimental site. Hydrological Processes, 29(19), 4210-4219. Bagarello, V., Ferro, V., Giordano, G., Mannocchi, F., Pampalone, V., Todisco, F. 2015a. A modified applicative criterion of the physical model concept for evaluating plot soil erosion predictions. Catena, 126, 53-58. Cerdà, A. and M. F. Jurgensen. 2011. Ant Mounds as a Source of Sediment on Citrus Orchard Plantations in Eastern Spain. A Three-Scale Rainfall Simulation Approach. Catena 85 (3): 231-236. doi:10.1016/j.catena.2011.01.008. Cerdà, A., Giménez-Morera, A., Jordan, A., Pereira, P., Novara, A., Keesstra, S., Sinoga, J. D. R. 2015. Shrubland as a soil and water conservation agent in Mediterranean-type ecosystems: The Sierra de Enguera study site contribution. Monitoring and Modelling Dynamic Environments, 45. Cerdà, A., R. Brazier, M. Nearing, and J. de Vente. 2013. Scales and Erosion. Catena 102: 1-2. doi:10.1016/j.catena.2011.09.006. Galdino, S., E. E. Sano, R. G. Andrade, C. R. Grego, S. F. Nogueira, C. Bragantini, and A. H. G. Flosi. 2016. Large-Scale Modeling of Soil Erosion with RUSLE for Conservationist Planning of Degraded Cultivated Brazilian Pastures. Land Degradation and Development 27 (3): 773-784. doi:10.1002/ldr.2414. Gonzalez-Hidalgo, J. C., R. J. Batalla, A. Cerdá, and M. de Luis. 2010. Contribution of the Largest Events to Suspended Sediment Transport Across the USA. Land Degradation and Development 21 (2): 83-91. doi:10.1002/ldr.897. Gonzalez-Hidalgo, J. C., R. J. Batalla, A. Cerdà, and M. de Luis. 2012. A Regional Analysis of the Effects of Largest Events on Soil Erosion. Catena 95: 85-90. doi:10.1016/j.catena.2012.03.006. Gonzalez-Hidalgo, J. C., R. J. Batalla, and A. Cerdà. 2013. Catchment Size and Contribution of the Largest Daily Events to Suspended Sediment Load on a Continental Scale. Catena 102: 40-45. doi:10.1016/j.catena.2010.10.011. López-Vicente, M., E. Nadal-Romero, and E. L. H. Cammeraat. 2016. Hydrological Connectivity does Change Over 70 Years of Abandonment and Afforestation in the Spanish Pyrenees. Land Degradation and Development. doi:10.1002/ldr.2531. López-Vicente, M., L. Quijano, L. Palazón, L. Gaspar, and A. Navas. 2015. Assessment of Soil Redistribution at Catchment Scale by Coupling a Soil Erosion Model and a Sediment Connectivity Index (Central Spanish Pre-Pyrenees). Cuadernos De Investigacion Geografica 41 (1): 127-147. doi:10.18172/cig.2649. Marchamalo, M., J. M. Hooke, and P. J. Sandercock. 2016. Flow and Sediment Connectivity in Semi-Arid Landscapes in SE Spain: Patterns and Controls. Land Degradation and Development 27 (4): 1032-1044. doi:10.1002/ldr.2352. Martínez-Casasnovas, J. A., M. C. Ramos, and G. Benites. 2016. Soil and Water Assessment Tool Soil Loss Simulation at the Sub-Basin Scale in the Alt Penedès-Anoia Vineyard Region (Ne Spain) in the 2000s. Land Degradation and Development 27 (2): 160-170. doi:10.1002/ldr.2240. Masselink, R.J.H., S.D. Keesstra, A J.A.M. Temme, M. Seeger, R. Giménez, J. Casalí. 2016. Modelling Discharge and Sediment Yield at Catchment Scale using Connectivity Components. Land Degradation and Development 27 (4): 933-945. doi:10.1002/ldr.2512. Parsons, A.J., Abrahams, A.D., Luk, S.H. 1990. Hydraulics of interrill overland flow on a semi-arid hillslope, southern Arizona. Journal of Hydrology, 117(1), 255-273. Parsons, A.J., Abrahams, A. D., Wainwright, J. 1996. Responses of interrill runoff and erosion rates to vegetation change in southern Arizona. Geomorphology, 14(4), 311-317. Parsons A.J., Bracken L., Peoppl , R., Wainwright J., Keesstra, S.D., 2015. Editorial: Introduction to special issue on connectivity in water and sediment dynamics. In press in Earth Surface Processes and Landforms. DOI: 10.1002/esp.3714 Poeppl, R.,E. Maroulis, J., Keesstra, S.D., 2016. Geomorphology. A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems. http://dx.doi.org/10.1016/j.geomorph.2016.07.033 Sadeghi, S.H.R., Gholami, L., Sharifi, E., Khaledi Darvishan, A., Homaee, M. Scale effect on runoff and soil loss control using rice straw mulch under laboratory conditions. (2015) Solid Earth, 6 (1), pp. 1-8.. DOI: http://dx.doi.org/10.5194/se-6-1-2015 Wainwright, J., Parsons, A.J., Schlesinger, W.H., Abrahams, A.D. 2002. Hydrology-vegetation interactions in areas of discontinuous flow on a semi-arid bajada, southern New Mexico. Journal of Arid Environments, 51(3), 319-338.

Globalization: Ecological consequences of global-scale connectivity in people, resources and information

USDA-ARS?s Scientific Manuscript database

Globalization is a phenomenon affecting all facets of the Earth System. Within the context of ecological systems, it is becoming increasingly apparent that global connectivity among terrestrial systems, the atmosphere, and oceans is driving many ecological dynamics at finer scales and pushing thresh...

Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury

PubMed Central

De Simoni, Sara; Jenkins, Peter O; Bourke, Niall J; Fleminger, Jessica J; Jolly, Amy E; Patel, Maneesh C; Leech, Robert; Sharp, David J

2018-01-01

Abstract Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with measures of executive dysfunction. We show for the first time that altered subcortical connectivity is associated with large-scale network disruption in traumatic brain injury and that this disruption is related to the cognitive impairments seen in these patients. PMID:29186356

A birds-eye view of biological connectivity in mangrove systems

NASA Astrophysics Data System (ADS)

Buelow, Christina; Sheaves, Marcus

2015-01-01

Considerable advances in understanding of biological connectivity have flowed from studies of fish-facilitated connectivity within the coastal ecosystem mosaic. However, there are limits to the information that fish can provide on connectivity. Mangrove-bird communities have the potential to connect coastal habitats in different ways and at different scales than fish, so incorporation of these links into our models of coastal ecosystem mosaics affords the opportunity to greatly increase the breadth of our understanding. We review the habitat and foraging requirements of mangrove-bird functional groups to understand how bird use of mangroves facilitates biological connectivity in coastal ecosystem mosaics, and how that connectivity adds to the diversity and complexity of ecological processes in mangrove ecosystems. Avian biological connectivity is primarily characterized by foraging behavior and habitat/resource requirements. Therefore, the consequence of bird links for coastal ecosystem functioning largely depends on patterns of habitat use and foraging, and potentially influences nutrient cycling, top-down control and genetic information linkage. Habitats that experience concentrated bird guano deposition have high levels of nitrogen and phosphorus, placing particular importance on the consequences of avian nutrient translocation and subsidization for coastal ecosystem functioning. High mobility allows mangrove-bird communities to link mangrove forests to other mangrove, terrestrial and marine-pelagic systems. Therefore, the spatial scale of coastal connectivity facilitated by birds is substantially more extensive than fish-facilitated connectivity. In particular, migratory birds link habitats at regional, continental and inter-continental scales as they travel among seasonally available feeding areas from breeding grounds to non-breeding grounds; scales at which there are few fish equivalents. Knowledge of the nature and patterns of fish connectivity have contributed to shifting the initial, historical perception of mangrove-ecosystem functioning from that of a simple system based on nutrient and energy retention, to a view that includes fish-facilitated energy export. In a similar way, understanding the nature and implications of mangrove connectivity through bird movements and migrations affords new possibilities for revising our view of the extent of functional links between mangroves and other ecosystems.

Damage spreading in spatial and small-world random Boolean networks

NASA Astrophysics Data System (ADS)

Lu, Qiming; Teuscher, Christof

2014-02-01

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Local Patterns to Global Architectures: Influences of Network Topology on Human Learning.

PubMed

Karuza, Elisabeth A; Thompson-Schill, Sharon L; Bassett, Danielle S

2016-08-01

A core question in cognitive science concerns how humans acquire and represent knowledge about their environments. To this end, quantitative theories of learning processes have been formalized in an attempt to explain and predict changes in brain and behavior. We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties. We focus on innovative work that describes how learning is influenced by the topological properties underlying sensory input. The confluence of these theoretical approaches and this recent empirical evidence motivate the importance of scaling-up quantitative approaches to learning at both the behavioral and neural levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Micromechanics of human mitotic chromosomes

NASA Astrophysics Data System (ADS)

Sun, Mingxuan; Kawamura, Ryo; Marko, John F.

2011-02-01

Eukaryote cells dramatically reorganize their long chromosomal DNAs to facilitate their physical segregation during mitosis. The internal organization of folded mitotic chromosomes remains a basic mystery of cell biology; its understanding would likely shed light on how chromosomes are separated from one another as well as into chromosome structure between cell divisions. We report biophysical experiments on single mitotic chromosomes from human cells, where we combine micromanipulation, nano-Newton-scale force measurement and biochemical treatments to study chromosome connectivity and topology. Results are in accord with previous experiments on amphibian chromosomes and support the 'chromatin network' model of mitotic chromosome structure. Prospects for studies of chromosome-organizing proteins using siRNA expression knockdowns, as well as for differential studies of chromosomes with and without mutations associated with genetic diseases, are also discussed.

Distributed and grid computing projects with research focus in human health.

PubMed

Diomidous, Marianna; Zikos, Dimitrios

2012-01-01

Distributed systems and grid computing systems are used to connect several computers to obtain a higher level of performance, in order to solve a problem. During the last decade, projects use the World Wide Web to aggregate individuals' CPU power for research purposes. This paper presents the existing active large scale distributed and grid computing projects with research focus in human health. There have been found and presented 11 active projects with more than 2000 Processing Units (PUs) each. The research focus for most of them is molecular biology and, specifically on understanding or predicting protein structure through simulation, comparing proteins, genomic analysis for disease provoking genes and drug design. Though not in all cases explicitly stated, common target diseases include research to find cure against HIV, dengue, Duchene dystrophy, Parkinson's disease, various types of cancer and influenza. Other diseases include malaria, anthrax, Alzheimer's disease. The need for national initiatives and European Collaboration for larger scale projects is stressed, to raise the awareness of citizens to participate in order to create a culture of internet volunteering altruism.

Spatial Fingerprints of Community Structure in Human Interaction Network for an Extensive Set of Large-Scale Regions

PubMed Central

Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor

2015-01-01

Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization. PMID:25993329

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex.

PubMed

Ulloa, Antonio; Horwitz, Barry

2016-01-01

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were "non-task-specific" (NS) neurons that served as noise generators to "task-specific" neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors.

[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

PubMed

Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

2016-07-01

Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

Probabilistic Tractography Recovers a Rostrocaudal Trajectory of Connectivity Variability in the Human Insular Cortex

PubMed Central

Cerliani, Leonardo; Thomas, Rajat M; Jbabdi, Saad; Siero, Jeroen CW; Nanetti, Luca; Crippa, Alessandro; Gazzola, Valeria; D'Arceuil, Helen; Keysers, Christian

2012-01-01

The insular cortex of macaques has a wide spectrum of anatomical connections whose distribution is related to its heterogeneous cytoarchitecture. Although there is evidence of a similar cytoarchitectural arrangement in humans, the anatomical connectivity of the insula in the human brain has not yet been investigated in vivo. In the present work, we used in vivo probabilistic white-matter tractography and Laplacian eigenmaps (LE) to study the variation of connectivity patterns across insular territories in humans. In each subject and hemisphere, we recovered a rostrocaudal trajectory of connectivity variation ranging from the anterior dorsal and ventral insula to the dorsal caudal part of the long insular gyri. LE suggested that regional transitions among tractography patterns in the insula occur more gradually than in other brain regions. In particular, the change in tractography patterns was more gradual in the insula than in the medial premotor region, where a sharp transition between different tractography patterns was found. The recovered trajectory of connectivity variation in the insula suggests a relation between connectivity and cytoarchitecture in humans resembling that previously found in macaques: tractography seeds from the anterior insula were mainly found in limbic and paralimbic regions and in anterior parts of the inferior frontal gyrus, while seeds from caudal insular territories mostly reached parietal and posterior temporal cortices. Regions in the putative dysgranular insula displayed more heterogeneous connectivity patterns, with regional differences related to the proximity with either putative granular or agranular regions. Hum Brain Mapp 33:2005–2034, 2012. © 2011 Wiley Periodicals, Inc. PMID:21761507

A Composite Network Approach for Assessing Multi-Species Connectivity: An Application to Road Defragmentation Prioritisation

PubMed Central

Saura, Santiago; Rondinini, Carlo

2016-01-01

One of the biggest challenges in large-scale conservation is quantifying connectivity at broad geographic scales and for a large set of species. Because connectivity analyses can be computationally intensive, and the planning process quite complex when multiple taxa are involved, assessing connectivity at large spatial extents for many species turns to be often intractable. Such limitation results in that conducted assessments are often partial by focusing on a few key species only, or are generic by considering a range of dispersal distances and a fixed set of areas to connect that are not directly linked to the actual spatial distribution or mobility of particular species. By using a graph theory framework, here we propose an approach to reduce computational effort and effectively consider large assemblages of species in obtaining multi-species connectivity priorities. We demonstrate the potential of the approach by identifying defragmentation priorities in the Italian road network focusing on medium and large terrestrial mammals. We show that by combining probabilistic species graphs prior to conducting the network analysis (i) it is possible to analyse connectivity once for all species simultaneously, obtaining conservation or restoration priorities that apply for the entire species assemblage; and that (ii) those priorities are well aligned with the ones that would be obtained by aggregating the results of separate connectivity analysis for each of the individual species. This approach offers great opportunities to extend connectivity assessments to large assemblages of species and broad geographic scales. PMID:27768718

Using synchronization in multi-model ensembles to improve prediction

NASA Astrophysics Data System (ADS)

Hiemstra, P.; Selten, F.

2012-04-01

In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of the state variables to obtain synchronization. In addition, when connecting through EOFs, we can reduce this percentage even more to 12%. This reduction is caused by the more efficient description of the model state variables when using EOFs. The connected state variables center around the medium scale structures in the model. Small and large scale structures need not be connected in order to obtain synchronization. This could be related to the baroclinic instabilities in the QG model which are located in the medium scale structures of the model. The baroclinic instabilities are the main source of divergence between the two connected models.

Global frameworks, local strategies: Women's rights, health, and the tobacco control movement in Argentina.

PubMed

Muñoz Martínez, Hepzibah; Pederson, Ann

2018-02-23

The article examines how civil society organisations in Argentina used the United Nations Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW) to frame the country's failure to enact strong national tobacco control legislation as a violation of women's rights in the late 2000s. We analyze this case study through the politics of scale, namely the social processes that produce, reproduce, and contest the boundaries of policies and socio-economic relations. This approach understands how multiple scales overlap and connect to obstruct or enhance the right to health in Latin America. In Argentina, the global organisation of tobacco companies, the reach of international financial institutions and the national dynamics of economic austerity and export-orientation promoted the local production and use of tobacco (leaf and cigarettes) and reproduced health inequalities in the country throughout the 1990s and the early 2000s. Yet, the visible legacy of local and national human rights struggles in the adoption of international human rights treaties into Argentina's national constitution allowed the tobacco control movement to link the scale of women's bodies to the right to health through the use of CEDAW to change national legislation, tackling the social determinants of the tobacco epidemic.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

PubMed

Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

PubMed Central

Grooms, Joshua K.; Thompson, Garth J.; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H.; Epstein, Charles M.

2017-01-01

Abstract A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies. PMID:28462586

Aggrecan nanoscale solid-fluid interactions are a primary determinant of cartilage dynamic mechanical properties.

PubMed

Nia, Hadi Tavakoli; Han, Lin; Bozchalooi, Iman Soltani; Roughley, Peter; Youcef-Toumi, Kamal; Grodzinsky, Alan J; Ortiz, Christine

2015-03-24

Poroelastic interactions between interstitial fluid and the extracellular matrix of connective tissues are critical to biological and pathophysiological functions involving solute transport, energy dissipation, self-stiffening and lubrication. However, the molecular origins of poroelasticity at the nanoscale are largely unknown. Here, the broad-spectrum dynamic nanomechanical behavior of cartilage aggrecan monolayer is revealed for the first time, including the equilibrium and instantaneous moduli and the peak in the phase angle of the complex modulus. By performing a length scale study and comparing the experimental results to theoretical predictions, we confirm that the mechanism underlying the observed dynamic nanomechanics is due to solid-fluid interactions (poroelasticity) at the molecular scale. Utilizing finite element modeling, the molecular-scale hydraulic permeability of the aggrecan assembly was quantified (kaggrecan = (4.8 ± 2.8) × 10(-15) m(4)/N·s) and found to be similar to the nanoscale hydraulic permeability of intact normal cartilage tissue but much lower than that of early diseased tissue. The mechanisms underlying aggrecan poroelasticity were further investigated by altering electrostatic interactions between the molecule's constituent glycosaminoglycan chains: electrostatic interactions dominated steric interactions in governing molecular behavior. While the hydraulic permeability of aggrecan layers does not change across species and age, aggrecan from adult human cartilage is stiffer than the aggrecan from newborn human tissue.

Scale-based fuzzy connectivity: a novel image segmentation methodology and its validation

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Udupa, Jayaram K.

1999-05-01

This paper extends a previously reported theory and algorithms for fuzzy connected object definition. It introduces `object scale' for determining the neighborhood size for defining affinity, the degree of local hanging togetherness between image elements. Object scale allows us to use a varying neighborhood size in different parts of the image. This paper argues that scale-based fuzzy connectivity is natural in object definition and demonstrates that this leads to a more effective object segmentation than without using scale in fuzzy concentrations. Affinity is described as consisting of a homogeneity-based and an object-feature- based component. Families of non scale-based and scale-based affinity relations are constructed. An effective method for giving a rough estimate of scale at different locations in the image is presented. The original theoretical and algorithmic framework remains more-or-less the same but considerably improved segmentations result. A quantitative statistical comparison between the non scale-based and the scale-based methods was made based on phantom images generated from patient MR brain studies by first segmenting the objects, and then by adding noise and blurring, and background component. Both the statistical and the subjective tests clearly indicate the superiority of scale- based method in capturing details and in robustness to noise.

Multilayer modeling and analysis of human brain networks

PubMed Central

2017-01-01

Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916

Anatomical and functional organization of the human substantia nigra and its connections

PubMed Central

Zhang, Yu; Larcher, Kevin Michel-Herve; Misic, Bratislav

2017-01-01

We investigated the anatomical and functional organization of the human substantia nigra (SN) using diffusion and functional MRI data from the Human Connectome Project. We identified a tripartite connectivity-based parcellation of SN with a limbic, cognitive, motor arrangement. The medial SN connects with limbic striatal and cortical regions and encodes value (greater response to monetary wins than losses during fMRI), while the ventral SN connects with associative regions of cortex and striatum and encodes salience (equal response to wins and losses). The lateral SN connects with somatomotor regions of striatum and cortex and also encodes salience. Behavioral measures from delay discounting and flanker tasks supported a role for the value-coding medial SN network in decisional impulsivity, while the salience-coding ventral SN network was associated with motor impulsivity. In sum, there is anatomical and functional heterogeneity of human SN, which underpins value versus salience coding, and impulsive choice versus impulsive action. PMID:28826495

Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis.

PubMed

Song, Jie; Nair, Veena A; Gaggl, Wolfgang; Prabhakaran, Vivek

2015-06-01

The human brain is a complex and dynamic system that can be modeled as a large-scale brain network to better understand the reorganizational changes secondary to epilepsy. In this study, we developed a brain functional network model using graph theory methods applied to resting-state fMRI data acquired from a group of epilepsy patients and age- and gender-matched healthy controls. A brain functional network model was constructed based on resting-state functional connectivity. A minimum spanning tree combined with proportional thresholding approach was used to obtain sparse connectivity matrices for each subject, which formed the basis of brain networks. We examined the brain reorganizational changes in epilepsy thoroughly at the level of the whole brain, the functional network, and individual brain regions. At the whole-brain level, local efficiency was significantly decreased in epilepsy patients compared with the healthy controls. However, global efficiency was significantly increased in epilepsy due to increased number of functional connections between networks (although weakly connected). At the functional network level, there were significant proportions of newly formed connections between the default mode network and other networks and between the subcortical network and other networks. There was a significant proportion of decreasing connections between the cingulo-opercular task control network and other networks. Individual brain regions from different functional networks, however, showed a distinct pattern of reorganizational changes in epilepsy. These findings suggest that epilepsy alters brain efficiency in a consistent pattern at the whole-brain level, yet alters brain functional networks and individual brain regions differently.

Modelling Fine Scale Movement Corridors for the Tricarinate Hill Turtle

NASA Astrophysics Data System (ADS)

Mondal, I.; Kumar, R. S.; Habib, B.; Talukdar, G.

2016-06-01

Habitat loss and the destruction of habitat connectivity can lead to species extinction by isolation of population. Identifying important habitat corridors to enhance habitat connectivity is imperative for species conservation by preserving dispersal pattern to maintain genetic diversity. Circuit theory is a novel tool to model habitat connectivity as it considers habitat as an electronic circuit board and species movement as a certain amount of current moving around through different resistors in the circuit. Most studies involving circuit theory have been carried out at small scales on large ranging animals like wolves or pumas, and more recently on tigers. This calls for a study that tests circuit theory at a large scale to model micro-scale habitat connectivity. The present study on a small South-Asian geoemydid, the Tricarinate Hill-turtle (Melanochelys tricarinata), focuses on habitat connectivity at a very fine scale. The Tricarinate has a small body size (carapace length: 127-175 mm) and home range (8000-15000 m2), with very specific habitat requirements and movement patterns. We used very high resolution Worldview satellite data and extensive field observations to derive a model of landscape permeability at 1 : 2,000 scale to suit the target species. Circuit theory was applied to model potential corridors between core habitat patches for the Tricarinate Hill-turtle. The modelled corridors were validated by extensive ground tracking data collected using thread spool technique and found to be functional. Therefore, circuit theory is a promising tool for accurately identifying corridors, to aid in habitat studies of small species.

Reduced Global Functional Connectivity of the Medial Prefrontal Cortex in Major Depressive Disorder

PubMed Central

Murrough, James W.; Abdallah, Chadi G.; Anticevic, Alan; Collins, Katherine A.; Geha, Paul; Averill, Lynnette A.; Schwartz, Jaclyn; DeWilde, Kaitlin E.; Averill, Christopher; Yang, Genevieve Jia-wei; Wong, Edmund; Tang, Cheuk Y.; Krystal, John H.; Iosifescu, Dan V.; Charney, Dennis S.

2016-01-01

Background Major depressive disorder is a disabling neuropsychiatric condition that is associated with disrupted functional connectivity across brain networks. The precise nature of altered connectivity, however, remains incompletely understood. The current study was designed to examine the coherence of large-scale connectivity in depression using a recently developed technique termed global brain connectivity. Methods A total of 82 subjects, including medication-free patients with major depression (n=57) and healthy volunteers (n=25) underwent functional magnetic resonance imaging with resting data acquisition for functional connectivity analysis. Global brain connectivity was computed as the mean of each voxel’s time series correlation with every other voxel and compared between study groups. Relationships between global connectivity and depressive symptom severity measured using the Montgomery-Åsberg Depression Rating Scale were examined by means of linear correlation. Results Relative to the healthy group, patients with depression evidenced reduced global connectivity bilaterally within multiple regions of medial and lateral prefrontal cortex. The largest between-group difference was observed within the right subgenual anterior cingulate cortex, extending into ventromedial prefrontal cortex bilaterally (Hedges’ g = −1.48, p<0.000001). Within the depressed group, patients with the lowest connectivity evidenced the highest symptom severity within ventromedial prefrontal cortex (r = −0.47, p=0.0005). Conclusions Patients with major depressive evidenced abnormal large-scale functional coherence in the brain that was centered within the subgenual cingulate cortex, and medial prefrontal cortex more broadly. These data extend prior studies of connectivity in depression and demonstrate that functional disconnection of the medial prefrontal cortex is a key pathological feature of the disorder. PMID:27144347

Documentary evidence of historical floods and extreme rainfall events in Sweden 1400-1800

NASA Astrophysics Data System (ADS)

Retsö, D.

2015-03-01

This article explores documentary evidence of floods and extreme rainfall events in Sweden in the pre-instrumental period (1400-1800). The survey shows that two sub-periods can be considered as flood-rich, 1590-1670 and the early 18th century. The result related to a low degree of human impact on hydrology during the period, suggests that climatic factors, such as lower temperatures and increased precipitation connected to the so-called Little Ice Age rather than large-scale atmospheric circulation patterns, should be considered as the main driver behind flood frequency and magnitude.

Food-web structure of seagrass communities across different spatial scales and human impacts.

PubMed

Coll, Marta; Schmidt, Allison; Romanuk, Tamara; Lotze, Heike K

2011-01-01

Seagrass beds provide important habitat for a wide range of marine species but are threatened by multiple human impacts in coastal waters. Although seagrass communities have been well-studied in the field, a quantification of their food-web structure and functioning, and how these change across space and human impacts has been lacking. Motivated by extensive field surveys and literature information, we analyzed the structural features of food webs associated with Zostera marina across 16 study sites in 3 provinces in Atlantic Canada. Our goals were to (i) quantify differences in food-web structure across local and regional scales and human impacts, (ii) assess the robustness of seagrass webs to simulated species loss, and (iii) compare food-web structure in temperate Atlantic seagrass beds with those of other aquatic ecosystems. We constructed individual food webs for each study site and cumulative webs for each province and the entire region based on presence/absence of species, and calculated 16 structural properties for each web. Our results indicate that food-web structure was similar among low impact sites across regions. With increasing human impacts associated with eutrophication, however, food-web structure show evidence of degradation as indicated by fewer trophic groups, lower maximum trophic level of the highest top predator, fewer trophic links connecting top to basal species, higher fractions of herbivores and intermediate consumers, and higher number of prey per species. These structural changes translate into functional changes with impacted sites being less robust to simulated species loss. Temperate Atlantic seagrass webs are similar to a tropical seagrass web, yet differed from other aquatic webs, suggesting consistent food-web characteristics across seagrass ecosystems in different regions. Our study illustrates that food-web structure and functioning of seagrass habitats change with human impacts and that the spatial scale of food-web analysis is critical for determining results.

Food-Web Structure of Seagrass Communities across Different Spatial Scales and Human Impacts

PubMed Central

Coll, Marta; Schmidt, Allison; Romanuk, Tamara; Lotze, Heike K.

2011-01-01

Seagrass beds provide important habitat for a wide range of marine species but are threatened by multiple human impacts in coastal waters. Although seagrass communities have been well-studied in the field, a quantification of their food-web structure and functioning, and how these change across space and human impacts has been lacking. Motivated by extensive field surveys and literature information, we analyzed the structural features of food webs associated with Zostera marina across 16 study sites in 3 provinces in Atlantic Canada. Our goals were to (i) quantify differences in food-web structure across local and regional scales and human impacts, (ii) assess the robustness of seagrass webs to simulated species loss, and (iii) compare food-web structure in temperate Atlantic seagrass beds with those of other aquatic ecosystems. We constructed individual food webs for each study site and cumulative webs for each province and the entire region based on presence/absence of species, and calculated 16 structural properties for each web. Our results indicate that food-web structure was similar among low impact sites across regions. With increasing human impacts associated with eutrophication, however, food-web structure show evidence of degradation as indicated by fewer trophic groups, lower maximum trophic level of the highest top predator, fewer trophic links connecting top to basal species, higher fractions of herbivores and intermediate consumers, and higher number of prey per species. These structural changes translate into functional changes with impacted sites being less robust to simulated species loss. Temperate Atlantic seagrass webs are similar to a tropical seagrass web, yet differed from other aquatic webs, suggesting consistent food-web characteristics across seagrass ecosystems in different regions. Our study illustrates that food-web structure and functioning of seagrass habitats change with human impacts and that the spatial scale of food-web analysis is critical for determining results. PMID:21811637

Function in the Human Connectome: Task-fMRI and Individual Differences in Behavior

PubMed Central

Barch, Deanna M.; Burgess, Gregory C.; Harms, Michael P.; Petersen, Steven E.; Schlaggar, Bradley L.; Corbetta, Maurizio; Glasser, Matthew F.; Curtiss, Sandra; Dixit, Sachin; Feldt, Cindy; Nolan, Dan; Bryant, Edward; Hartley, Tucker; Footer, Owen; Bjork, James M.; Poldrack, Russ; Smith, Steve; Johansen-Berg, Heidi; Snyder, Abraham Z.; Van Essen, David C.

2014-01-01

The primary goal of the Human Connectome Project (HCP) is to delineate the typical patterns of structural and functional connectivity in the healthy adult human brain. However, we know that there are important individual differences in such patterns of connectivity, with evidence that this variability is associated with alterations in important cognitive and behavioral variables that affect real world function. The HCP data will be a critical stepping-off point for future studies that will examine how variation in human structural and functional connectivity play a role in adult and pediatric neurological and psychiatric disorders that account for a huge amount of public health resources. Thus, the HCP is collecting behavioral measures of a range of motor, sensory, cognitive and emotional processes that will delineate a core set of functions relevant to understanding the relationship between brain connectivity and human behavior. In addition, the HCP is using task-fMRI (tfMRI) to help delineate the relationships between individual differences in the neurobiological substrates of mental processing and both functional and structural connectivity, as well as to help characterize and validate the connectivity analyses to be conducted on the structural and functional connectivity data. This paper describes the logic and rationale behind the development of the behavioral, individual difference, and tfMRI batteries and provides preliminary data on the patterns of activation associated with each of the fMRI tasks, at both a group and individual level. PMID:23684877

A Developmental Shift from Positive to Negative Connectivity in Human Amygdala-Prefrontal Circuitry

PubMed Central

Gee, Dylan G.; Humphreys, Kathryn L.; Flannery, Jessica; Goff, Bonnie; Telzer, Eva H.; Shapiro, Mor; Hare, Todd A.; Bookheimer, Susan Y.; Tottenham, Nim

2013-01-01

Recent human imaging and animal studies highlight the importance of frontoamygdala circuitry in the regulation of emotional behavior and its disruption in anxiety-related disorders. While tracing studies have suggested changes in amygdala-cortical connectivity through the adolescent period in rodents, less is known about the reciprocal connections within this circuitry across human development, when these circuits are being fine-tuned and substantial changes in emotional control are observed. The present study examined developmental changes in amygdala-prefrontal circuitry across the ages of 4 to 22 years using task-based functional magnetic resonance imaging (fMRI). Results suggest positive amygdala-prefrontal connectivity in early childhood that switches to negative functional connectivity during the transition to adolescence. Amygdala-mPFC functional connectivity was significantly positive (greater than zero) among participants younger than ten, whereas functional connectivity was significantly negative (less than zero) among participants ten years and older, over and above the effect of amygdala reactivity. The developmental switch in functional connectivity was paralleled by a steady decline in amygdala reactivity. Moreover, the valence switch might explain age-related improvement in task performance and a developmentally normative decline in anxiety. Initial positive connectivity followed by a valence shift to negative connectivity provides a neurobiological basis for regulatory development and may present novel insight into a more general process of developing regulatory connections. PMID:23467374

Nutritional Countermeasures Targeting Reactive Oxygen Species in Cancer: From Mechanisms to Biomarkers and Clinical Evidence

PubMed Central

Samoylenko, Anatoly; Hossain, Jubayer Al; Mennerich, Daniela; Kellokumpu, Sakari; Hiltunen, Jukka Kalervo

2013-01-01

Abstract Reactive oxygen species (ROS) exert various biological effects and contribute to signaling events during physiological and pathological processes. Enhanced levels of ROS are highly associated with different tumors, a Western lifestyle, and a nutritional regime. The supplementation of food with traditional antioxidants was shown to be protective against cancer in a number of studies both in vitro and in vivo. However, recent large-scale human trials in well-nourished populations did not confirm the beneficial role of antioxidants in cancer, whereas there is a well-established connection between longevity of several human populations and increased amount of antioxidants in their diets. Although our knowledge about ROS generators, ROS scavengers, and ROS signaling has improved, the knowledge about the direct link between nutrition, ROS levels, and cancer is limited. These limitations are partly due to lack of standardized reliable ROS measurement methods, easily usable biomarkers, knowledge of ROS action in cellular compartments, and individual genetic predispositions. The current review summarizes ROS formation due to nutrition with respect to macronutrients and antioxidant micronutrients in the context of cancer and discusses signaling mechanisms, used biomarkers, and its limitations along with large-scale human trials. Antioxid. Redox Signal. 19, 2157–2196. PMID:23458328

Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference

PubMed Central

Stone, Eric A.; Ayroles, Julien F.

2009-01-01

In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432

Acid sulfate soils and human health--a Millennium Ecosystem Assessment.

PubMed

Ljung, Karin; Maley, Fiona; Cook, Angus; Weinstein, Philip

2009-11-01

Acid sulfate soils have been described as the "nastiest soils on earth" because of their strong acidity, increased mobility of potentially toxic elements and limited bioavailability of nutrients. They only cover a small area of the world's total problem soils, but often have significant adverse effects on agriculture, aquaculture and the environment on a local scale. Their location often coincides with high population density areas along the coasts of many developing countries. As a result, their negative impacts on ecosystems can have serious implications to those least equipped for coping with the low crop yields and reduced water quality that can result from acid sulfate soil disturbance. The Millennium Ecosystem Assessment called on by the United Nations in 2000 emphasised the importance of ecosystems for human health and well-being. These include the service they provide as sources of food and water, through the control of pollution and disease, as well as for the cultural services ecosystems provide. While the problems related to agriculture, aquaculture and the environment have been the focus of many acid sulfate soil management efforts, the connection to human health has largely been ignored. This paper presents the potential health issues of acid sulfate soils, in relation to the ecosystem services identified in the Millennium Ecosystem Assessment. It is recognised that significant implications on food security and livelihood can result, as well as on community cohesiveness and the spread of vector-borne disease. However, the connection between these outcomes and acid sulfate soils is often not obvious and it is therefore argued that the impact of such soils on human well-being needs to be recognised in order to raise awareness among the public and decision makers, to in turn facilitate proper management and avoid potential human ill-health.

Superposed epoch analysis of physiological fluctuations: possible space weather connections

NASA Astrophysics Data System (ADS)

Wanliss, James; Cornélissen, Germaine; Halberg, Franz; Brown, Denzel; Washington, Brien

2018-03-01

There is a strong connection between space weather and fluctuations in technological systems. Some studies also suggest a statistical connection between space weather and subsequent fluctuations in the physiology of living creatures. This connection, however, has remained controversial and difficult to demonstrate. Here we present support for a response of human physiology to forcing from the explosive onset of the largest of space weather events—space storms. We consider a case study with over 16 years of high temporal resolution measurements of human blood pressure (systolic, diastolic) and heart rate variability to search for associations with space weather. We find no statistically significant change in human blood pressure but a statistically significant drop in heart rate during the main phase of space storms. Our empirical findings shed light on how human physiology may respond to exogenous space weather forcing.

Superposed epoch analysis of physiological fluctuations: possible space weather connections.

PubMed

Wanliss, James; Cornélissen, Germaine; Halberg, Franz; Brown, Denzel; Washington, Brien

2018-03-01

There is a strong connection between space weather and fluctuations in technological systems. Some studies also suggest a statistical connection between space weather and subsequent fluctuations in the physiology of living creatures. This connection, however, has remained controversial and difficult to demonstrate. Here we present support for a response of human physiology to forcing from the explosive onset of the largest of space weather events-space storms. We consider a case study with over 16 years of high temporal resolution measurements of human blood pressure (systolic, diastolic) and heart rate variability to search for associations with space weather. We find no statistically significant change in human blood pressure but a statistically significant drop in heart rate during the main phase of space storms. Our empirical findings shed light on how human physiology may respond to exogenous space weather forcing.

The Beta Cell in Its Cluster: Stochastic Graphs of Beta Cell Connectivity in the Islets of Langerhans

PubMed Central

Striegel, Deborah A.; Hara, Manami; Periwal, Vipul

2015-01-01

Pancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets. PMID:26266953

The Beta Cell in Its Cluster: Stochastic Graphs of Beta Cell Connectivity in the Islets of Langerhans.

PubMed

Striegel, Deborah A; Hara, Manami; Periwal, Vipul

2015-08-01

Pancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets.

Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males.

PubMed

Deza Araujo, Yacila I; Nebe, Stephan; Neukam, Philipp T; Pooseh, Shakoor; Sebold, Miriam; Garbusow, Maria; Heinz, Andreas; Smolka, Michael N

2018-06-01

Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.

Effective connectivity of brain regions underlying third-party punishment: Functional MRI and Granger causality evidence.

PubMed

Bellucci, Gabriele; Chernyak, Sergey; Hoffman, Morris; Deshpande, Gopikrishna; Dal Monte, Olga; Knutson, Kristine M; Grafman, Jordan; Krueger, Frank

2017-04-01

Third-party punishment (TPP) for norm violations is an essential deterrent in large-scale human societies, and builds on two essential cognitive functions: evaluating legal responsibility and determining appropriate punishment. Despite converging evidence that TPP is mediated by a specific set of brain regions, little is known about their effective connectivity (direction and strength of connections). Applying parametric event-related functional MRI in conjunction with multivariate Granger causality analysis, we asked healthy participants to estimate how much punishment a hypothetical perpetrator deserves for intentionally committing criminal offenses varying in levels of harm. Our results confirmed that TPP legal decisions are based on two domain-general networks: the mentalizing network for evaluating legal responsibility and the central-executive network for determining appropriate punishment. Further, temporal pole (TP) and dorsomedial prefrontal cortex (PFC) emerged as hubs of the mentalizing network, uniquely generating converging output connections to ventromedial PFC, temporo-parietal junction, and posterior cingulate. In particular, dorsomedial PFC received inputs only from TP and both its activation and its connectivity to dorsolateral PFC correlated with degree of punishment. This supports the hypothesis that dorsomedial PFC acts as the driver of the TPP activation pattern, leading to the decision on the appropriate punishment. In conclusion, these results advance our understanding of the organizational elements of the TPP brain networks and provide better insights into the mental states of judges and jurors tasked with blaming and punishing legal wrongs.

The CB1 Neutral Antagonist Tetrahydrocannabivarin Reduces Default Mode Network and Increases Executive Control Network Resting State Functional Connectivity in Healthy Volunteers.

PubMed

Rzepa, Ewelina; Tudge, Luke; McCabe, Ciara

2015-09-10

The cannabinoid cannabinoid type 1 (CB1) neutral antagonist tetrahydrocannabivarin (THCv) has been suggested as a possible treatment for obesity, but without the depressogenic side-effects of inverse antagonists such as Rimonabant. However, how THCv might affect the resting state functional connectivity of the human brain is as yet unknown. We examined the effects of a single 10mg oral dose of THCv and placebo in 20 healthy volunteers in a randomized, within-subject, double-blind design. Using resting state functional magnetic resonance imaging and seed-based connectivity analyses, we selected the amygdala, insula, orbitofrontal cortex, and dorsal medial prefrontal cortex (dmPFC) as regions of interest. Mood and subjective experience were also measured before and after drug administration using self-report scales. Our results revealed, as expected, no significant differences in the subjective experience with a single dose of THCv. However, we found reduced resting state functional connectivity between the amygdala seed region and the default mode network and increased resting state functional connectivity between the amygdala seed region and the dorsal anterior cingulate cortex and between the dmPFC seed region and the inferior frontal gyrus/medial frontal gyrus. We also found a positive correlation under placebo for the amygdala-precuneus connectivity with the body mass index, although this correlation was not apparent under THCv. Our findings are the first to show that treatment with the CB1 neutral antagonist THCv decreases resting state functional connectivity in the default mode network and increases connectivity in the cognitive control network and dorsal visual stream network. This effect profile suggests possible therapeutic activity of THCv for obesity, where functional connectivity has been found to be altered in these regions. © The Author 2015. Published by Oxford University Press on behalf of CINP.

White-matter functional networks changes in patients with schizophrenia.

PubMed

Jiang, Yuchao; Luo, Cheng; Li, Xuan; Li, Yingjia; Yang, Hang; Li, Jianfu; Chang, Xin; Li, Hechun; Yang, Huanghao; Wang, Jijun; Duan, Mingjun; Yao, Dezhong

2018-04-13

Resting-state functional MRI (rsfMRI) is a useful technique for investigating the functional organization of human gray-matter in neuroscience and neuropsychiatry. Nevertheless, most studies have demonstrated the functional connectivity and/or task-related functional activity in the gray-matter. White-matter functional networks have been investigated in healthy subjects. Schizophrenia has been hypothesized to be a brain disorder involving insufficient or ineffective communication associated with white-matter abnormalities. However, previous studies have mainly examined the structural architecture of white-matter using MRI or diffusion tensor imaging and failed to uncover any dysfunctional connectivity within the white-matter on rsfMRI. The current study used rsfMRI to evaluate white-matter functional connectivity in a large cohort of ninety-seven schizophrenia patients and 126 healthy controls. Ten large-scale white-matter networks were identified by a cluster analysis of voxel-based white-matter functional connectivity and classified into superficial, middle and deep layers of networks. Evaluation of the spontaneous oscillation of white-matter networks and the functional connectivity between them showed that patients with schizophrenia had decreased amplitudes of low-frequency oscillation and increased functional connectivity in the superficial perception-motor networks. Additionally, we examined the interactions between white-matter and gray-matter networks. The superficial perception-motor white-matter network had decreased functional connectivity with the cortical perception-motor gray-matter networks. In contrast, the middle and deep white-matter networks had increased functional connectivity with the superficial perception-motor white-matter network and the cortical perception-motor gray-matter network. Thus, we presumed that the disrupted association between the gray-matter and white-matter networks in the perception-motor system may be compensated for through the middle-deep white-matter networks, which may be the foundation of the extensively disrupted connections in schizophrenia. Copyright © 2018 Elsevier Inc. All rights reserved.

Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

PubMed Central

Samu, David; Seth, Anil K.; Nowotny, Thomas

2014-01-01

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. PMID:24699277

Measuring Perceived Mutuality in Women: Further Validation of the Connection-Disconnection Scale

ERIC Educational Resources Information Center

Sanftner, Jennifer L.; Tantillo, Mary

2010-01-01

Relationships with family and significant friends and partners are important contributors to the quality of life, health, and mental health of women. The Connection-Disconnection Scale (CDS) was developed to assess perceived mutuality (PM) in relationships with mothers, fathers, friends, and romantic partners, and data are presented here that…

Utility photovoltaic group: Status report

NASA Astrophysics Data System (ADS)

Serfass, Jeffrey A.; Hester, Stephen L.; Wills, Bethany N.

1996-01-01

The Utility PhotoVoltaic Group (UPVG) was formed in October of 1992 with a mission to accelerate the use of cost-effective small-scale and emerging grid-connected applications of photovoltaics for the benefit of electric utilities and their customers. The UPVG is now implementing a program to install up to 50 megawatts of photovoltaics in small-scale and grid-connected applications. This program, called TEAM-UP, is a partnership of the U.S. electric utility industry and the U.S. Department of Energy to help develop utility PV markets. TEAM-UP is a utility-directed program to significantly increase utility PV experience by promoting installations of utility PV systems. Two primary program areas are proposed for TEAM-UP: (1) Small-Scale Applications (SSA)—an initiative to aggregate utility purchases of small-scale, grid-independent applications; and (2) Grid-Connected Applications (GCA)—an initiative to identify and competitively award cost-sharing contracts for grid-connected PV systems with high market growth potential, or collective purchase programs involving multiple buyers. This paper describes these programs and outlines the schedule, the procurement status, and the results of the TEAM-UP process.

Continental synchronicity of human influenza virus epidemics despite climatic variation.

PubMed

Geoghegan, Jemma L; Saavedra, Aldo F; Duchêne, Sebastián; Sullivan, Sheena; Barr, Ian; Holmes, Edward C

2018-01-01

The factors that determine the pattern and rate of spread of influenza virus at a continental-scale are uncertain. Although recent work suggests that influenza epidemics in the United States exhibit a strong geographical correlation, the spatiotemporal dynamics of influenza in Australia, a country and continent of approximately similar size and climate complexity but with a far smaller population, are not known. Using a unique combination of large-scale laboratory-confirmed influenza surveillance comprising >450,000 entries and genomic sequence data we determined the local-level spatial diffusion of this important human pathogen nationwide in Australia. We used laboratory-confirmed influenza data to characterize the spread of influenza virus across Australia during 2007-2016. The onset of established epidemics varied across seasons, with highly synchronized epidemics coinciding with the emergence of antigenically distinct viruses, particularly during the 2009 A/H1N1 pandemic. The onset of epidemics was largely synchronized between the most populous cities, even those separated by distances of >3000 km and those that experience vastly diverse climates. In addition, by analyzing global phylogeographic patterns we show that the synchronized dissemination of influenza across Australian cities involved multiple introductions from the global influenza population, coupled with strong domestic connectivity, rather than through the distinct radial patterns of geographic dispersal that are driven by work-flow transmission as observed in the United States. In addition, by comparing the spatial structure of influenza A and B, we found that these viruses tended to occupy different geographic regions, and peak in different seasons, perhaps indicative of moderate cross-protective immunity or viral interference effects. The highly synchronized outbreaks of influenza virus at a continental-scale revealed here highlight the importance of coordinated public health responses in the event of the emergence of a novel, human-to-human transmissible, virus.

From Points to Patterns - Functional Relations between Groundwater Connectivity and Catchment-scale Streamflow Response

NASA Astrophysics Data System (ADS)

Rinderer, M.; McGlynn, B. L.; van Meerveld, I. H. J.

2016-12-01

Groundwater measurements can help us to improve our understanding of runoff generation at the catchment-scale but typically only provide point-scale data. These measurements, therefore, need to be interpolated or upscaled in order to obtain information about catchment scale groundwater dynamics. Our approach used data from 51 spatially distributed groundwater monitoring sites in a Swiss pre-alpine catchment and time series clustering to define six groundwater response clusters. Each of the clusters was characterized by distinctly different site characteristics (i.e., Topographic Wetness Index and curvature), which allowed us to assign all unmonitored locations to one of these clusters. Time series modeling and the definition of response thresholds (i.e., the depth of more transmissive soil layers) allowed us to derive maps of the spatial distribution of active (i.e., responding) locations across the catchment at 15 min time intervals. Connectivity between all active locations and the stream network was determined using a graph theory approach. The extent of the active and connected areas differed during events and suggests that not all active locations directly contributed to streamflow. Gate keeper sites prevented connectivity of upslope locations to the channel network. Streamflow dynamics at the catchment outlet were correlated to catchment average connectivity dynamics. In a sensitivity analysis we tested six different groundwater levels for a site to be considered "active", which showed that the definition of the threshold did not significantly influence the conclusions drawn from our analysis. This study is the first one to derive patterns of groundwater dynamics based on empirical data (rather than interpolation) and provides insight into the spatio-temporal evolution of the active and connected runoff source areas at the catchment-scale that is critical to understanding the dynamics of water quantity and quality in streams.

Capturing the externalities: National and watershed scale damages from release of reactive nitrogen beyond the farm, factory, tailpipe and table

NASA Astrophysics Data System (ADS)

Compton, J.; Sobota, D. J.; McCrackin, M. L.; Harrison, J.

2014-12-01

Human demand for food, fuel, and industrial products results in the release of 61% of the newly fixed anthropogenic N to the environment in the US each year. This 15.8 Tg N yr-1 input to air, land and water has important social, economic and environmental consequences, yet little research clearly links this N release to the full suite of effects. Here we connect the biogeochemical fluxes of N with existing data on N-associated damages in order to quantify the externalities of N release related to human health, ecosystems and climate regulation for the US at national and watershed scales. Release of N to the environment was estimated circa 2000 with models describing N inputs by source, nutrient uptake efficiency, leaching losses, and gaseous emissions at the scale of 8-digit US Geologic Survey Hydrologic Unit Codes (HUC8s). Potential damages or benefits of anthropogenic N leaked to the environment were calculated by scaling specific N fluxes with the costs associated with human health, agriculture, ecosystems, and the climate system. For the US, annual damage costs of anthropogenic N leaked to the environment in 2000 totaled 289 billion USD. Approximately 57% of the total damages were associated with fossil fuel combustion, driven by the human respiratory health impacts of NOx as a precursor of ozone and a component of particulates. Another 37% of the damage costs were associated with agricultural N. Damages associated with agriculture were 85.5 billion, largely through eutrophication and harmful effects on aquatic habitat. Through aggressive but tangible improvements in atmospheric emissions, agricultural N use and wastewater treatment, we could reduce N export to the coast by nearly 25% within 30 years. These improvements would reduce the externalities associated with the leakage of N beyond its intended uses in agriculture, transportation and energy with minimal impact to these sectors dependent on anthropogenic N fixation.

Controlling charge quantization with quantum fluctuations.

PubMed

Jezouin, S; Iftikhar, Z; Anthore, A; Parmentier, F D; Gennser, U; Cavanna, A; Ouerghi, A; Levkivskyi, I P; Idrisov, E; Sukhorukov, E V; Glazman, L I; Pierre, F

2016-08-04

In 1909, Millikan showed that the charge of electrically isolated systems is quantized in units of the elementary electron charge e. Today, the persistence of charge quantization in small, weakly connected conductors allows for circuits in which single electrons are manipulated, with applications in, for example, metrology, detectors and thermometry. However, as the connection strength is increased, the discreteness of charge is progressively reduced by quantum fluctuations. Here we report the full quantum control and characterization of charge quantization. By using semiconductor-based tunable elemental conduction channels to connect a micrometre-scale metallic island to a circuit, we explore the complete evolution of charge quantization while scanning the entire range of connection strengths, from a very weak (tunnel) to a perfect (ballistic) contact. We observe, when approaching the ballistic limit, that charge quantization is destroyed by quantum fluctuations, and scales as the square root of the residual probability for an electron to be reflected across the quantum channel; this scaling also applies beyond the different regimes of connection strength currently accessible to theory. At increased temperatures, the thermal fluctuations result in an exponential suppression of charge quantization and in a universal square-root scaling, valid for all connection strengths, in agreement with expectations. Besides being pertinent for the improvement of single-electron circuits and their applications, and for the metal-semiconductor hybrids relevant to topological quantum computing, knowledge of the quantum laws of electricity will be essential for the quantum engineering of future nanoelectronic devices.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

2016-03-16

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18-88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. Copyright © 2016 Tsvetanov et al.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation

PubMed Central

Henson, Richard N.A.; Tyler, Lorraine K.; Razi, Adeel; Geerligs, Linda; Ham, Timothy E.; Rowe, James B.

2016-01-01

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. SIGNIFICANCE STATEMENT Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18–88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. PMID:26985024

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity

PubMed Central

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S.; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N.

2015-01-01

Aim To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Methods Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen–Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Results Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. Conclusion The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure–function relationships but requires further validation in other populations of CP. PMID:26106533

Development and reliability testing of a self-report instrument to measure the office layout as a correlate of occupational sitting.

PubMed

Duncan, Mitch J; Rashid, Mahbub; Vandelanotte, Corneel; Cutumisu, Nicoleta; Plotnikoff, Ronald C

2013-02-04

Spatial configurations of office environments assessed by Space Syntax methodologies are related to employee movement patterns. These methods require analysis of floors plans which are not readily available in large population-based studies or otherwise unavailable. Therefore a self-report instrument to assess spatial configurations of office environments using four scales was developed. The scales are: local connectivity (16 items), overall connectivity (11 items), visibility of co-workers (10 items), and proximity of co-workers (5 items). A panel cohort (N = 1154) completed an online survey, only data from individuals employed in office-based occupations (n = 307) were used to assess scale measurement properties. To assess test-retest reliability a separate sample of 37 office-based workers completed the survey on two occasions 7.7 (±3.2) days apart. Redundant scale items were eliminated using factor analysis; Chronbach's α was used to evaluate internal consistency and test re-test reliability (retest-ICC). ANOVA was employed to examine differences between office types (Private, Shared, Open) as a measure of construct validity. Generalized Linear Models were used to examine relationships between spatial configuration scales and the duration of and frequency of breaks in occupational sitting. The number of items on all scales were reduced, Chronbach's α and ICCs indicated good scale internal consistency and test re-test reliability: local connectivity (5 items; α = 0.70; retest-ICC = 0.84), overall connectivity (6 items; α = 0.86; retest-ICC = 0.87), visibility of co-workers (4 items; α = 0.78; retest-ICC = 0.86), and proximity of co-workers (3 items; α = 0.85; retest-ICC = 0.70). Significant (p ≤ 0.001) differences, in theoretically expected directions, were observed for all scales between office types, except overall connectivity. Significant associations were observed between all scales and occupational sitting behaviour (p ≤ 0.05). All scales have good measurement properties indicating the instrument may be a useful alternative to Space Syntax to examine environmental correlates of occupational sitting in population surveys.

Development and reliability testing of a self-report instrument to measure the office layout as a correlate of occupational sitting

PubMed Central

2013-01-01

Background Spatial configurations of office environments assessed by Space Syntax methodologies are related to employee movement patterns. These methods require analysis of floors plans which are not readily available in large population-based studies or otherwise unavailable. Therefore a self-report instrument to assess spatial configurations of office environments using four scales was developed. Methods The scales are: local connectivity (16 items), overall connectivity (11 items), visibility of co-workers (10 items), and proximity of co-workers (5 items). A panel cohort (N = 1154) completed an online survey, only data from individuals employed in office-based occupations (n = 307) were used to assess scale measurement properties. To assess test-retest reliability a separate sample of 37 office-based workers completed the survey on two occasions 7.7 (±3.2) days apart. Redundant scale items were eliminated using factor analysis; Chronbach’s α was used to evaluate internal consistency and test re-test reliability (retest-ICC). ANOVA was employed to examine differences between office types (Private, Shared, Open) as a measure of construct validity. Generalized Linear Models were used to examine relationships between spatial configuration scales and the duration of and frequency of breaks in occupational sitting. Results The number of items on all scales were reduced, Chronbach’s α and ICCs indicated good scale internal consistency and test re-test reliability: local connectivity (5 items; α = 0.70; retest-ICC = 0.84), overall connectivity (6 items; α = 0.86; retest-ICC = 0.87), visibility of co-workers (4 items; α = 0.78; retest-ICC = 0.86), and proximity of co-workers (3 items; α = 0.85; retest-ICC = 0.70). Significant (p ≤ 0.001) differences, in theoretically expected directions, were observed for all scales between office types, except overall connectivity. Significant associations were observed between all scales and occupational sitting behaviour (p ≤ 0.05). Conclusion All scales have good measurement properties indicating the instrument may be a useful alternative to Space Syntax to examine environmental correlates of occupational sitting in population surveys. PMID:23379485

Genomic connectivity networks based on the BrainSpan atlas of the developing human brain

NASA Astrophysics Data System (ADS)

Mahfouz, Ahmed; Ziats, Mark N.; Rennert, Owen M.; Lelieveldt, Boudewijn P. F.; Reinders, Marcel J. T.

2014-03-01

The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

Functional subregions of the human entorhinal cortex

PubMed Central

Maass, Anne; Berron, David; Libby, Laura A; Ranganath, Charan; Düzel, Emrah

2015-01-01

The entorhinal cortex (EC) is the primary site of interactions between the neocortex and hippocampus. Studies in rodents and nonhuman primates suggest that EC can be divided into subregions that connect differentially with perirhinal cortex (PRC) vs parahippocampal cortex (PHC) and with hippocampal subfields along the proximo-distal axis. Here, we used high-resolution functional magnetic resonance imaging at 7 Tesla to identify functional subdivisions of the human EC. In two independent datasets, PRC showed preferential intrinsic functional connectivity with anterior-lateral EC and PHC with posterior-medial EC. These EC subregions, in turn, exhibited differential connectivity with proximal and distal subiculum. In contrast, connectivity of PRC and PHC with subiculum followed not only a proximal-distal but also an anterior-posterior gradient. Our data provide the first evidence that the human EC can be divided into functional subdivisions whose functional connectivity closely parallels the known anatomical connectivity patterns of the rodent and nonhuman primate EC. DOI: http://dx.doi.org/10.7554/eLife.06426.001 PMID:26052749

Simulating forest landscape disturbances as coupled human and natural systems

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Liu, Zhihua; Lamsal, Aashis

2015-01-01

Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.

Assessing the role of landscape connectivity on Opisthorchis viverrini transmission dynamics.

PubMed

Wang, Yi-Chen; Yuen, Roy; Feng, Chen-Chieh; Sithithaworn, Paiboon; Kim, Ick-Hoi

2017-08-01

Opisthorchis viverrini (Ov) is one of the most important human parasitic diseases in Southeast Asia. Although the concept of connectivity is widely used to comprehend disease dispersal, knowledge of the influences of landscape connectivity on Ov transmission is still rudimentary. This study aimed to investigate the role of landscape connectivity in Ov transmission between the human and the first intermediate snail hosts. Fieldwork was conducted in three villages respectively in Kamalasai District, Kalasin Province, Phu Wiang District, Khon Kaen Province, and Nong Saeng District, Udon Thani Province. Bithynia snails were collected to examine parasitic infections, water samples were analyzed for fecal contamination, and locations of septic tanks and connections between habitat patches with observable water movement were surveyed. Euclidean distance, topological link and distance, and graph measures were employed to quantify the connectivity between human and snail habitats. The findings showed that snail patches with higher fecal contents were generally located nearer to septic tanks. The statistically significant results for the topological link and distance measures highlighted the importance of water in functionally facilitating Ov transmission. Graph measures revealed differences in landscape connectivity across the sites. The site with the largest landscape component size and the most mutually connected snail patches coincided with the presence of Ov parasite, reinforcing its higher risk for human to snail transmission. The site with the dissected landscape structure potentially limited the transmission. This study underscored the potential effect of landscape connectivity on Ov transmission, contributing to the understanding of the spatial variation of Ov infection risk. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A new conceptual framework for water and sediment connectivity

NASA Astrophysics Data System (ADS)

Keesstra, Saskia; Cerdà, Artemi; Parsons, Tony; Nunes, Joao Pedro; Saco, Patricia

2016-04-01

For many years scientists have tried to understand, describe and quantify sediment transport on multiple scales; from the geomorphological work triggered by a single thunderstorm to the geological time scale land scape evolution, and from particles and soil aggregates up to the continental scale. In the last two decades, a new concept called connectivity (Baartman et al., 2013; Bracken et al., 2013, 2015; Parsons et al., 2015) has been used by the scientific community to describe the connection between the different scales at which the sediment redistribution research along the watershed are being studied: pedon, slope tram, slope, watersheds, and basins. This concept is seen as a means to describe and quantify the results of processes influencing the transport of sediment on all these scales. Therefore the concept of connectivity and the way scales are used in the design of a measurement and monitoring scheme are interconnected (Cerdà et al., 2012), which shows that connectivity is not only a tool for process understanding, but also a tool to measure processes on multiple scales. This research aims to describe catchment system dynamics from a connectivity point of view. This conceptual framework can be helpful to look at catchment systems and synthesize which data are necessary to take into account when measuring or modelling water and sediment transfer in catchment systems, Identifying common patterns and generalities will help discover physical reasons for differences in responses and interaction between these processes. We describe a conceptual framework which is meant to bring a better understanding of the system dynamics of a catchment in terms of water and sediment transfer by breaking apart the system dynamics in stocks (the system state at a given moment) and flows (the system fluxes). Breaking apart the internal system dynamics that determine the behaviour of the catchment system is in our opinion a way to bring a better insight into the concepts of hydrological and sediment connectivity as described in previous research by Bracken et al (2013, 2015). By looking at the individual parts of the system, it becomes more manageable and less conceptual, which is important because we have to indicate where the research on connectivity should focus on. With this approach, processes and feedbacks in the catchment system can be pulled apart to study separately, making the system understandable and measureable, which will enable parameterization of models with actual measured data. The approach we took in describing water and sediment transfer is to first assess how they work in a system in dynamic equilibrium. After describing this, an assessment is made of how such dynamic equilibriums can be taken out of balance by an external push. Baartman, J.E.M., Masselink, R.H., Keesstra, S.D., Temme, A.J.A.M., 2013. Linking landscape morphological complexity and sediment connectivity. Earth Surface Processes and Landforms 38: 1457-1471. Bracken, L.J., Wainwright, J., Ali, G.A., Tetzlaff, D., Smith, M.W., Reaney, S.M., and Roy, A.G. 2013. Concepts of hydrological connectivity: research approaches, pathways and future agendas. Earth Science Reviews, 119, 17-34. Bracken, L.J., Turnbull, L, Wainwright, J. and Boogart, P. Submitted. Sediment Connectivity: A Framework for Understanding Sediment Transfer at Multiple Scales. Earth Surface Processes and Landforms. Cerdà, A., Brazier, R., Nearing, M., and de Vente, J. 2012. scales and erosion. Catena, 102, 1-2. doi:10.1016/j.catena.2011.09.006 Parsons A.J., Bracken L., Peoppl , R., Wainwright J., Keesstra, S.D., 2015. Editorial: Introduction to special issue on connectivity in water and sediment dynamics. In press in Earth Surface Processes and Landforms. DOI: 10.1002/esp.3714

Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain.

PubMed

Kuipers, Jeroen; Kalicharan, Ruby D; Wolters, Anouk H G; van Ham, Tjakko J; Giepmans, Ben N G

2016-05-25

Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae(1-7). Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically ~ 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture(1-5). Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)(8) on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner.

Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain

PubMed Central

Kuipers, Jeroen; Kalicharan, Ruby D.; Wolters, Anouk H. G.

2016-01-01

Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae1-7. Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically ~ 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture1-5. Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)8 on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner. PMID:27285162

Integrating wetland connectivity into models for watershed-scale analyses: Current and future approaches

EPA Science Inventory

Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal hydrologic connectivity continuum to downstream waters. Via these connections and disconnections, GIWs provide numerous hydrological, biogeochemical, and biological functio...

Assessing Ecological Impacts According to Land Use Change

NASA Astrophysics Data System (ADS)

Jeong, S.; Lee, D. K.; Jeong, W.; Jeong, S. G.; Jin, Y.

2015-12-01

Land use patterns have changed by human activities, and it has affected the structure and dynamics of ecosystems. In particular, the conversion of forests into other land use has caused environmental degradation and loss of biodiversity. The evaluation of species and their habitat can be preferentially considered to prevent or minimize the adverse effects of land use change. The objective of study is identifying the impacts of environmental conditions on forest ecosystems by comparing ecological changes with time series spatial data. Species distribution models were developed for diverse species with presence data and time-series environmental variables, which allowed comparison of the habitat suitability and connectivity. Habitat suitability and connectivity were used to estimate impacts of forest ecosystems due to land use change. Our result suggested that the size and degree of ecological impacts are were different depending on the properties of land use change. The elements and species were greatly affected by the land use change according to the results. This study suggested that a methodology for measuring the interference of land use change in species habitat and connectivity. Furthermore, it will help to conserve and manage forest by identifying priority conservation areas with influence factor and scale.

Better models are more effectively connected models

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Bielders, Charles; Darboux, Frederic; Fiener, Peter; Finger, David; Turnbull-Lloyd, Laura; Wainwright, John

2016-04-01

The concept of hydrologic and geomorphologic connectivity describes the processes and pathways which link sources (e.g. rainfall, snow and ice melt, springs, eroded areas and barren lands) to accumulation areas (e.g. foot slopes, streams, aquifers, reservoirs), and the spatial variations thereof. There are many examples of hydrological and sediment connectivity on a watershed scale; in consequence, a process-based understanding of connectivity is crucial to help managers understand their systems and adopt adequate measures for flood prevention, pollution mitigation and soil protection, among others. Modelling is often used as a tool to understand and predict fluxes within a catchment by complementing observations with model results. Catchment models should therefore be able to reproduce the linkages, and thus the connectivity of water and sediment fluxes within the systems under simulation. In modelling, a high level of spatial and temporal detail is desirable to ensure taking into account a maximum number of components, which then enables connectivity to emerge from the simulated structures and functions. However, computational constraints and, in many cases, lack of data prevent the representation of all relevant processes and spatial/temporal variability in most models. In most cases, therefore, the level of detail selected for modelling is too coarse to represent the system in a way in which connectivity can emerge; a problem which can be circumvented by representing fine-scale structures and processes within coarser scale models using a variety of approaches. This poster focuses on the results of ongoing discussions on modelling connectivity held during several workshops within COST Action Connecteur. It assesses the current state of the art of incorporating the concept of connectivity in hydrological and sediment models, as well as the attitudes of modellers towards this issue. The discussion will focus on the different approaches through which connectivity can be represented in models: either by allowing it to emerge from model behaviour or by parameterizing it inside model structures; and on the appropriate scale at which processes should be represented explicitly or implicitly. It will also explore how modellers themselves approach connectivity through the results of a community survey. Finally, it will present the outline of an international modelling exercise aimed at assessing how different modelling concepts can capture connectivity in real catchments.

Beyond the Arcuate Fasciculus: Consensus and Controversy in the Connectional Anatomy of Language

ERIC Educational Resources Information Center

Dick, Anthony Steven; Tremblay, Pascale

2012-01-01

The growing consensus that language is distributed into large-scale cortical and subcortical networks has brought with it an increasing focus on the connectional anatomy of language, or how particular fibre pathways connect regions within the language network. Understanding connectivity of the language network could provide critical insights into…

How restructuring river connectivity changes freshwater fish biodiversity and biogeography

USGS Publications Warehouse

Lynch, Heather L.; Grant, Evan H. Campbell; Muneepeerakul, Rachata; Arunachalam, Muthukumarasamy; Rodriguez-Iturbe, Ignacio; Fagan, William F.

2011-01-01

Interbasin water transfer projects, in which river connectivity is restructured via man-made canals, are an increasingly popular solution to address the spatial mismatch between supply and demand of fresh water. However, the ecological consequences of such restructuring remain largely unexplored, and there are no general theoretical guidelines from which to derive these expectations. River systems provide excellent opportunities to explore how network connectivity shapes habitat occupancy, community dynamics, and biogeographic patterns. We apply a neutral model (which assumes competitive equivalence among species within a stochastic framework) to an empirically derived river network to explore how proposed changes in network connectivity may impact patterns of freshwater fish biodiversity. Without predicting the responses of individual extant species, we find the addition of canals connecting hydrologically isolated river basins facilitates the spread of common species and increases average local species richness without changing the total species richness of the system. These impacts are sensitive to the parameters controlling the spatial scale of fish dispersal, with increased dispersal affording more opportunities for biotic restructuring at the community and landscape scales. Connections between isolated basins have a much larger effect on local species richness than those connecting reaches within a river basin, even when those within-basin reaches are far apart. As a result, interbasin canal projects have the potential for long-term impacts to continental-scale riverine communities.

An investigation into preserving spatially-distinct pore systems in multi-component rocks using a fossiliferous limestone example

NASA Astrophysics Data System (ADS)

Jiang, Zeyun; Couples, Gary D.; Lewis, Helen; Mangione, Alessandro

2018-07-01

Limestones containing abundant disc-shaped fossil Nummulites can form significant hydrocarbon reservoirs but they have a distinctly heterogeneous distribution of pore shapes, sizes and connectivities, which make it particularly difficult to calculate petrophysical properties and consequent flow outcomes. The severity of the problem rests on the wide length-scale range from the millimetre scale of the fossil's pore space to the micron scale of rock matrix pores. This work develops a technique to incorporate multi-scale void systems into a pore network, which is used to calculate the petrophysical properties for subsequent flow simulations at different stages in the limestone's petrophysical evolution. While rock pore size, shape and connectivity can be determined, with varying levels of fidelity, using techniques such as X-ray computed tomography (CT) or scanning electron microscopy (SEM), this work represents a more challenging class where the rock of interest is insufficiently sampled or, as here, has been overprinted by extensive chemical diagenesis. The main challenge is integrating multi-scale void structures derived from both SEM and CT images, into a single model or a pore-scale network while still honouring the nature of the connections across these length scales. Pore network flow simulations are used to illustrate the technique but of equal importance, to demonstrate how supportable earlier-stage petrophysical property distributions can be used to assess the viability of several potential geological event sequences. The results of our flow simulations on generated models highlight the requirement for correct determination of the dominant pore scales (one plus of nm, μm, mm, cm), the spatial correlation and the cross-scale connections.

Non-scaling fixed field alternating gradient permanent magnet cancer therapy accelerator

DOEpatents

Trbojevic, Dejan

2017-05-23

A non-scaling fixed field alternating gradient accelerator includes a racetrack shape including a first straight section connected to a first arc section, the first arc section connected to a second straight section, the second straight section connected to a second arc section, and the second arc section connected to the first straight section; an matching cells configured to match particle orbits between the first straight section, the first arc section, the second straight section, and the second arc section. The accelerator includes the matching cells and an associated matching procedure enabling the particle orbits at varying energies between an arc section and a straight section in the racetrack shape.

A framework for using connectivity to measure and model water and sediment fluxes

NASA Astrophysics Data System (ADS)

Keessta, Saskia; Saco, Patricia; Nunes, Joao; Parsons, Tony; Poeppl, Ronny; Pereira, Paulo; Novara, Agata; Rodrigo Comino, Jesús; Jordán, Antonio; Masselink, Rens; Cerdà, Artemi

2017-04-01

For many years, scientists have tried to understand, describe and quantify water and sediment fluxes at multiple scales (Cerdà et al., 2013; Parsons et al., 2015; Poeppl et al., 2016; Masselink et al., 2016a; Rodrigo Comino et al., 2016). In the past two decades, a new concept called connectivity has been used by Earth Scientists as a means to describe and quantify the influences on the fluxes of water and sediment on different scales: aggregate, pedon, location on the slope, slope, watershed, and basin (Baartman et al., 2013; Parsons et al., 2015; López-Vicente et al., 2015; 2016; Masselink 2016b; Marchamalo et al., 2016; Mekonnen et al., 2016). A better understanding of connectivity can enhance our comprehension of landscape processes and provide a basis for the development of better measurement and modelling approaches, further leading to a better potential for implementing this concept as a management tool. Our research provides a short review of the State-of-the-Art of the connectivity concept, from which we conclude that scientists have been struggling to find a way to quantify connectivity so far. We adapt the knowledge of connectivity to better understand and quantify water and sediment transfers in catchment systems. First, we introduce a new approach to the concept of connectivity to study water and sediment transfers. In this approach water and sediment dynamics are divided in two parts: the system consists of phases and fluxes, each being separately measurable. This approach enables us to: i) better conceptualize our understanding of system dynamics at different timescales, including long timescales; ii) identify the main parameters driving system dynamics, and devise monitoring strategies which capture them; and, iii) build models with a holistic approach to simulate system dynamics without excessive complexity. Secondly, we discuss the role of system boundaries in designing measurement schemes and models. Natural systems have boundaries within which sediment connectivity varies between phases; in (semi-)arid regions these boundaries can be far apart in time due to extreme events. External disturbances (eg. climate change, changed land management) can change these boundaries. It is therefore important to consider the system state as a whole, including its boundaries and internal dynamics, when designing and implementing comprehensive monitoring and modelling approaches. Keywords: Connectivity, catchment systems, measuring and modelling approaches, co-evolution, management, boundary conditions, fire effects. Acknowledgements This research received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n_ 603498 (RECARE project) and the CGL2013- 47862-C2-1-R and CGL2016-75178-C2-2-R national research projects. References Baartman, J.E.M., Masselink, R.H., Keesstra, S.D., Temme, A.J.A.M., 2013. Linking landscape morphological complexity and sediment connectivity. Earth Surface Processes and Landforms 38: 1457-1471. Cerdà A, Brazier R, Nearing M, de Vente J. 2013. Scales and erosion. CATENA 102: 1-2. DOI: 10.1016/j.catena.2011.09.006 López-Vicente, M., E. Nadal-Romero, and E. L. H. Cammeraat. 2016. Hydrological Connectivity does Change Over 70 Years of Abandonment and Afforestation in the Spanish Pyrenees. Land Degradation and Development. doi:10.1002/ldr.2531. López-Vicente, M., L. Quijano, L. Palazón, L. Gaspar, and A. Navas. 2015. Assessment of Soil Redistribution at Catchment Scale by Coupling a Soil Erosion Model and a Sediment Connectivity Index (Central Spanish Pre-Pyrenees). Cuadernos De Investigacion Geografica 41 (1): 127-147. doi:10.18172/cig.2649. Marchamalo, M., J. M. Hooke, and P. J. Sandercock. 2016. Flow and Sediment Connectivity in Semi-Arid Landscapes in SE Spain: Patterns and Controls. Land Degradation and Development 27 (4): 1032-1044. doi:10.1002/ldr.2352. Masselink RJH, Heckmann T, Temme AJAM, Anders NS, Gooren HPA, Keesstra SD. 2016a. A network theory approach for a better understanding of overland flow connectivity. Hydrological Processes. DOI: 10.1002/hyp.10993 Masselink, R. J. H., S. D. Keesstra, A. J. A. M. Temme, M. Seeger, R. Giménez, and J. Casalí. 2016b. Modelling Discharge and Sediment Yield at Catchment Scale using Connectivity Components. Land Degradation and Development 27 (4): 933-945. doi:10.1002/ldr.2512. Mekonnen, M., Keesstra, S.D., Baartman, J.E.M., Stroosnijder, L., Maroulis, J., Reducing sediment connectivity through man-made and natural sediment sinks in the Minizr catchment, north-west Ethiopia. Accepted to Land Degradation and Development. Parsons A.J., Bracken L., Peoppl , R., Wainwright J., Keesstra, S.D., 2015. Editorial: Introduction to special issue on connectivity in water and sediment dynamics. In press in Earth Surface Processes and Landforms. DOI: 10.1002/esp.3714 Parsons A.J., Bracken L., Peoppl , R., Wainwright J., Keesstra, S.D., 2015. Editorial: Introduction to special issue on connectivity in water and sediment dynamics. In press in Earth Surface Processes and Landforms. DOI: 10.1002/esp.3714 Poeppl, R.,E. Maroulis, J., Keesstra, S.D., 2016. Geomorphology. A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems. http://dx.doi.org/10.1016/j.geomorph.2016.07.033 Rodrigo Comino, J., Iserloh, T., Lassu, T., Cerdà, A., Keesstra, S.D., Prosdocimi, M., Brings, C., Marzen, M., Ramos, M.C., Senciales, J.M., Ruiz Sinoga, J.D., Seeger, M., Ries, J.B., 2016. Quantitative comparison of initial soil erosion processes and runoff generation in Spanish and German vineyards. Science of the Total Environment. In press DOI:10.1016/j.scitotenv.2016.05.163

Frozen Fractals all Around: Solar flares, Ampere’s Law, and the Search for Units in Scale-Free Processes.

NASA Astrophysics Data System (ADS)

McAteer, R. T. James

2015-08-01

My soul is spiraling in frozen fractals all around, And one thought crystallizes like an icy blast, I'm never going back, the past is in the past.Elsa, from Disney’s Frozen, characterizes two fundamental aspects of scale-free processes in Nature: fractals are everywhere in space; fractals can be used to probe changes in time. Self-Organized Criticality provides a powerful set of tools to study scale-free processes. It connects spatial fractals (more generically, multifractals) to temporal evolution. The drawback is that this usually results in scale-free, unit-less, indices, which can be difficult to connect to everyday physics. Here, I show a novel method that connects one of the most powerful SOC tools - the wavelet transform modulus maxima approach to calculating multifractality - to one of the most powerful equations in all of physics - Ampere’s law. In doing so I show how the multifractal spectra can be expressed in terms of current density, and how current density can then be used for the prediction of future energy release from such a system.Our physical understanding of the solar magnetic field structure, and hence our ability to predict solar activity, is limited by the type of data currently available. I show that the multifractal spectrum provides a powerful physical connection between the details of photospheric magnetic gradients of current data and the coronal magnetic structure. By decomposing Ampere’s law and comparing it to the wavelet transform modulus maximum method, I show how the scale-free Holder exponent provides a direct measure of current density across all relevant sizes. The prevalence of this current density across various scales is connected to its stability in time, and hence to the ability of the magnetic structure to store and then release energy. Hence (spatial) multifractals inform us of (future) solar activity.Finally I discuss how such an approach can be used in any study of scale-free processes, and highlight the necessary key steps in identifying the nature of the mother wavelet to ensuring the viability of this powerful connection.

Systematic network assessment of the carcinogenic activities of cadmium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Peizhan; Duan, Xiaohua; Li, Mian

Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscapemore » software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.« less

Packaging of electro-microfluidic devices

DOEpatents

Benavides, Gilbert L.; Galambos, Paul C.; Emerson, John A.; Peterson, Kenneth A.; Giunta, Rachel K.; Zamora, David Lee; Watson, Robert D.

2003-04-15

A new architecture for packaging surface micromachined electro-microfluidic devices is presented. This architecture relies on two scales of packaging to bring fluid to the device scale (picoliters) from the macro-scale (microliters). The architecture emulates and utilizes electronics packaging technology. The larger package consists of a circuit board with embedded fluidic channels and standard fluidic connectors (e.g. Fluidic Printed Wiring Board). The embedded channels connect to the smaller package, an Electro-Microfluidic Dual-Inline-Package (EMDIP) that takes fluid to the microfluidic integrated circuit (MIC). The fluidic connection is made to the back of the MIC through Bosch-etched holes that take fluid to surface micromachined channels on the front of the MIC. Electrical connection is made to bond pads on the front of the MIC.

Packaging of electro-microfluidic devices

DOEpatents

Benavides, Gilbert L.; Galambos, Paul C.; Emerson, John A.; Peterson, Kenneth A.; Giunta, Rachel K.; Watson, Robert D.

2002-01-01

A new architecture for packaging surface micromachined electro-microfluidic devices is presented. This architecture relies on two scales of packaging to bring fluid to the device scale (picoliters) from the macro-scale (microliters). The architecture emulates and utilizes electronics packaging technology. The larger package consists of a circuit board with embedded fluidic channels and standard fluidic connectors (e.g. Fluidic Printed Wiring Board). The embedded channels connect to the smaller package, an Electro-Microfluidic Dual-Inline-Package (EMDIP) that takes fluid to the microfluidic integrated circuit (MIC). The fluidic connection is made to the back of the MIC through Bosch-etched holes that take fluid to surface micromachined channels on the front of the MIC. Electrical connection is made to bond pads on the front of the MIC.

Challenges in coupling LTER with environmental assessments: An insight from potential and reality of the Chinese Ecological Research Network in servicing environment assessments.

PubMed

Xia, Shaoxia; Liu, Yu; Yu, Xiubo; Fu, Bojie

2018-08-15

Environmental assessments estimate, evaluate and predict the consequences of natural processes and human activities on the environment. Long-term ecosystem observation and research networks (LTERs) are potentially valuable infrastructure to support environmental assessments. However, very few environmental assessments have successfully incorporated them. In this study, we try to reveal the current status of coupling LTERs with environmental assessments and look at the challenges involved in improving this coupling through exploring the role that Chinese Ecological Research Network (CERN), the LTER of China, currently plays in regional environment assessments. A review of official protocols and standards, regional assessments and CERN researches related to ecosystems and environment shows that there is great potential for coupling CERN with environment assessments. However in practice, CERN does not currently play the expected role. Remote sensing and irregular inventory data are still the main data sources currently used in regional assessments. Several causes led to the present situation: (1) insufficient cross-site research and failure to scale up site-level variables to the regional scale; (2) data barriers resulting from incompatible protocols and low data usability due to lack of data assimilation and scaling; and (3) absence of indicators relevant to human activities in existing monitoring protocols. For these reasons, enhancing cross-site monitoring and research, data assimilation and scaling up are critical steps required to improve coupling of LTER with environmental assessments. Site-focused long-term monitoring should be combined with wide-scale ground surveys and remote sensing to establish an effective connection between different environmental monitoring platforms for regional assessments. It is also necessary to revise the current monitoring protocols to include human activities and their impacts on the ecosystem, or change the LTERs into Long-Term Socio-Ecological Research (LTSER) networks. Copyright © 2018 Elsevier B.V. All rights reserved.

Humanities Thematic Units: Four Example Units for Gifted Students in Grade 6 (the Greeks, the Romans, the Middle Ages and the Renaissance). Programs for Gifted Students.

ERIC Educational Resources Information Center

Woodbury, Virginia Garton

One in a series of units for gifted students, the booklet focuses on humanities instruction in grade 6. Program background information stresses the values of humanities as a way of studying the connections in the student's life, particularly the connections between subject areas and how they relate to humans' feelings and thoughts. Procedures…

Fine-Grained Parcellation of Brain Connectivity Improves Differentiation of States of Consciousness During Graded Propofol Sedation.

PubMed

Liu, Xiaolin; Lauer, Kathryn K; Ward, B Douglas; Roberts, Christopher J; Liu, Suyan; Gollapudy, Suneeta; Rohloff, Robert; Gross, William; Xu, Zhan; Chen, Guangyu; Binder, Jeffrey R; Li, Shi-Jiang; Hudetz, Anthony G

2017-08-01

Conscious perception relies on interactions between spatially and functionally distinct modules of the brain at various spatiotemporal scales. These interactions are altered by anesthesia, an intervention that leads to fading consciousness. Relatively little is known about brain functional connectivity and its anesthetic modulation at a fine spatial scale. Here, we used functional imaging to examine propofol-induced changes in functional connectivity in brain networks defined at a fine-grained parcellation based on a combination of anatomical and functional features. Fifteen healthy volunteers underwent resting-state functional imaging in wakeful baseline, mild sedation, deep sedation, and recovery of consciousness. Compared with wakeful baseline, propofol produced widespread, dose-dependent functional connectivity changes that scaled with the extent to which consciousness was altered. The dominant changes in connectivity were associated with the frontal lobes. By examining node pairs that demonstrated a trend of functional connectivity change between wakefulness and deep sedation, quadratic discriminant analysis differentiated the states of consciousness in individual participants more accurately at a fine-grained parcellation (e.g., 2000 nodes) than at a coarse-grained parcellation (e.g., 116 anatomical nodes). Our study suggests that defining brain networks at a high granularity may provide a superior imaging-based distinction of the graded effect of anesthesia on consciousness.

Complex interaction of dendritic connectivity and hierarchical patch size on biodiversity in river-like landscapes.

PubMed

Carrara, Francesco; Rinaldo, Andrea; Giometto, Andrea; Altermatt, Florian

2014-01-01

Habitat fragmentation and land use changes are causing major biodiversity losses. Connectivity of the landscape or environmental conditions alone can shape biodiversity patterns. In nature, however, local habitat characteristics are often intrinsically linked to a specific connectivity. Such a link is evident in riverine ecosystems, where hierarchical dendritic structures command related scaling on habitat capacity. We experimentally disentangled the effect of local habitat capacity (i.e., the patch size) and dendritic connectivity on biodiversity in aquatic microcosm metacommunities by suitably arranging patch sizes within river-like networks. Overall, more connected communities that occupy a central position in the network exhibited higher species richness, irrespective of patch size arrangement. High regional evenness in community composition was found only in landscapes preserving geomorphological scaling properties of patch sizes. In these landscapes, some of the rarer species sustained regionally more abundant populations better tracking their own niche requirements compared to landscapes with homogeneous patch size or landscapes with spatially uncorrelated patch size. Our analysis suggests that altering the natural link between dendritic connectivity and patch size strongly affects community composition and population persistence at multiple scales. The experimental results are demonstrating a principle that can be tested in theoretical metacommunity models and eventually be projected to real riverine ecosystems.

A Putative Multiple-Demand System in the Macaque Brain.

PubMed

Mitchell, Daniel J; Bell, Andrew H; Buckley, Mark J; Mitchell, Anna S; Sallet, Jerome; Duncan, John

2016-08-17

In humans, cognitively demanding tasks of many types recruit common frontoparietal brain areas. Pervasive activation of this "multiple-demand" (MD) network suggests a core function in supporting goal-oriented behavior. A similar network might therefore be predicted in nonhuman primates that readily perform similar tasks after training. However, an MD network in nonhuman primates has not been described. Single-cell recordings from macaque frontal and parietal cortex show some similar properties to human MD fMRI responses (e.g., adaptive coding of task-relevant information). Invasive recordings, however, come from limited prespecified locations, so they do not delineate a macaque homolog of the MD system and their positioning could benefit from knowledge of where MD foci lie. Challenges of scanning behaving animals mean that few macaque fMRI studies specifically contrast levels of cognitive demand, so we sought to identify a macaque counterpart to the human MD system using fMRI connectivity in 35 rhesus macaques. Putative macaque MD regions, mapped from frontoparietal MD regions defined in humans, were found to be functionally connected under anesthesia. To further refine these regions, an iterative process was used to maximize their connectivity cross-validated across animals. Finally, whole-brain connectivity analyses identified voxels that were robustly connected to MD regions, revealing seven clusters across frontoparietal and insular cortex comparable to human MD regions and one unexpected cluster in the lateral fissure. The proposed macaque MD regions can be used to guide future electrophysiological investigation of MD neural coding and in task-based fMRI to test predictions of similar functional properties to human MD cortex. In humans, a frontoparietal "multiple-demand" (MD) brain network is recruited during a wide range of cognitively demanding tasks. Because this suggests a fundamental function, one might expect a similar network to exist in nonhuman primates, but this remains controversial. Here, we sought to identify a macaque counterpart to the human MD system using fMRI connectivity. Putative macaque MD regions were functionally connected under anesthesia and were further refined by iterative optimization. The result is a network including lateral frontal, dorsomedial frontal, and insular and inferior parietal regions closely similar to the human counterpart. The proposed macaque MD regions can be useful in guiding electrophysiological recordings or in task-based fMRI to test predictions of similar functional properties to human MD cortex. Copyright © 2016 Mitchell et al.

Collective movements of pedestrians: How we can learn from simple experiments with non-human (ant) crowds

PubMed Central

Sarvi, Majid

2017-01-01

Introduction Understanding collective behavior of moving organisms and how interactions between individuals govern their collective motion has triggered a growing number of studies. Similarities have been observed between the scale-free behavioral aspects of various systems (i.e. groups of fish, ants, and mammals). Investigation of such connections between the collective motion of non-human organisms and that of humans however, has been relatively scarce. The problem demands for particular attention in the context of emergency escape motion for which innovative experimentation with panicking ants has been recently employed as a relatively inexpensive and non-invasive approach. However, little empirical evidence has been provided as to the relevance and reliability of this approach as a model of human behaviour. Methods This study explores pioneer experiments of emergency escape to tackle this question and to connect two forms of experimental observations that investigate the collective movement at macroscopic level. A large number of experiments with human and panicking ants are conducted representing the escape behavior of these systems in crowded spaces. The experiments share similar architectural structures in which two streams of crowd flow merge with one another. Measures such as discharge flow rates and the probability distribution of passage headways are extracted and compared between the two systems. Findings Our findings displayed an unexpected degree of similarity between the collective patterns emerged from both observation types, particularly based on aggregate measures. Experiments with ants and humans commonly indicated how significantly the efficiency of motion and the rate of discharge depend on the architectural design of the movement environment. Practical applications Our findings contribute to the accumulation of evidence needed to identify the boarders of applicability of experimentation with crowds of non-human entities as models of human collective motion as well as the level of measurements (i.e. macroscopic or microscopic) and the type of contexts at which reliable inferences can be drawn. This particularly has implications in the context of experimenting evacuation behaviour for which recruiting human subjects may face ethical restrictions. The findings, at minimum, offer promise as to the potential benefit of piloting such experiments with non-human crowds, thereby forming better-informed hypotheses. PMID:28854221

Collective movements of pedestrians: How we can learn from simple experiments with non-human (ant) crowds.

PubMed

Shahhoseini, Zahra; Sarvi, Majid

2017-01-01

Understanding collective behavior of moving organisms and how interactions between individuals govern their collective motion has triggered a growing number of studies. Similarities have been observed between the scale-free behavioral aspects of various systems (i.e. groups of fish, ants, and mammals). Investigation of such connections between the collective motion of non-human organisms and that of humans however, has been relatively scarce. The problem demands for particular attention in the context of emergency escape motion for which innovative experimentation with panicking ants has been recently employed as a relatively inexpensive and non-invasive approach. However, little empirical evidence has been provided as to the relevance and reliability of this approach as a model of human behaviour. This study explores pioneer experiments of emergency escape to tackle this question and to connect two forms of experimental observations that investigate the collective movement at macroscopic level. A large number of experiments with human and panicking ants are conducted representing the escape behavior of these systems in crowded spaces. The experiments share similar architectural structures in which two streams of crowd flow merge with one another. Measures such as discharge flow rates and the probability distribution of passage headways are extracted and compared between the two systems. Our findings displayed an unexpected degree of similarity between the collective patterns emerged from both observation types, particularly based on aggregate measures. Experiments with ants and humans commonly indicated how significantly the efficiency of motion and the rate of discharge depend on the architectural design of the movement environment. Our findings contribute to the accumulation of evidence needed to identify the boarders of applicability of experimentation with crowds of non-human entities as models of human collective motion as well as the level of measurements (i.e. macroscopic or microscopic) and the type of contexts at which reliable inferences can be drawn. This particularly has implications in the context of experimenting evacuation behaviour for which recruiting human subjects may face ethical restrictions. The findings, at minimum, offer promise as to the potential benefit of piloting such experiments with non-human crowds, thereby forming better-informed hypotheses.

Place, Matters of Concern, and Pedagogy: Making Impactful Connections with Our Planet

ERIC Educational Resources Information Center

Iorio, Jeanne Marie; Hamm, Catherine; Parnell, Will; Quintero, Elizabeth

2017-01-01

Neoliberalism, capitalist ideas, and the disastrous human-induced state of the environment are evidence of the lack of connection between humans and the earth, calling for a rethinking of the relationships between humans and the planet. As early childhood educators, we wonder about our role in rethinking these relationships and in particular, the…

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

On nodes and modes in resting state fMRI

PubMed Central

Friston, Karl J.; Kahan, Joshua; Razi, Adeel; Stephan, Klaas Enno; Sporns, Olaf

2014-01-01

This paper examines intrinsic brain networks in light of recent developments in the characterisation of resting state fMRI timeseries — and simulations of neuronal fluctuations based upon the connectome. Its particular focus is on patterns or modes of distributed activity that underlie functional connectivity. We first demonstrate that the eigenmodes of functional connectivity – or covariance among regions or nodes – are the same as the eigenmodes of the underlying effective connectivity, provided we limit ourselves to symmetrical connections. This symmetry constraint is motivated by appealing to proximity graphs based upon multidimensional scaling. Crucially, the principal modes of functional connectivity correspond to the dynamically unstable modes of effective connectivity that decay slowly and show long term memory. Technically, these modes have small negative Lyapunov exponents that approach zero from below. Interestingly, the superposition of modes – whose exponents are sampled from a power law distribution – produces classical 1/f (scale free) spectra. We conjecture that the emergence of dynamical instability – that underlies intrinsic brain networks – is inevitable in any system that is separated from external states by a Markov blanket. This conjecture appeals to a free energy formulation of nonequilibrium steady-state dynamics. The common theme that emerges from these theoretical considerations is that endogenous fluctuations are dominated by a small number of dynamically unstable modes. We use this as the basis of a dynamic causal model (DCM) of resting state fluctuations — as measured in terms of their complex cross spectra. In this model, effective connectivity is parameterised in terms of eigenmodes and their Lyapunov exponents — that can also be interpreted as locations in a multidimensional scaling space. Model inversion provides not only estimates of edges or connectivity but also the topography and dimensionality of the underlying scaling space. Here, we focus on conceptual issues with simulated fMRI data and provide an illustrative application using an empirical multi-region timeseries. PMID:24862075

Multiple successional pathways in human-modified tropical landscapes: new insights from forest succession, forest fragmentation and landscape ecology research.

PubMed

Arroyo-Rodríguez, Víctor; Melo, Felipe P L; Martínez-Ramos, Miguel; Bongers, Frans; Chazdon, Robin L; Meave, Jorge A; Norden, Natalia; Santos, Bráulio A; Leal, Inara R; Tabarelli, Marcelo

2017-02-01

Old-growth tropical forests are being extensively deforested and fragmented worldwide. Yet forest recovery through succession has led to an expansion of secondary forests in human-modified tropical landscapes (HMTLs). Secondary forests thus emerge as a potential repository for tropical biodiversity, and also as a source of essential ecosystem functions and services in HMTLs. Such critical roles are controversial, however, as they depend on successional, landscape and socio-economic dynamics, which can vary widely within and across landscapes and regions. Understanding the main drivers of successional pathways of disturbed tropical forests is critically needed for improving management, conservation, and restoration strategies. Here, we combine emerging knowledge from tropical forest succession, forest fragmentation and landscape ecology research to identify the main driving forces shaping successional pathways at different spatial scales. We also explore causal connections between land-use dynamics and the level of predictability of successional pathways, and examine potential implications of such connections to determine the importance of secondary forests for biodiversity conservation in HMTLs. We show that secondary succession (SS) in tropical landscapes is a multifactorial phenomenon affected by a myriad of forces operating at multiple spatio-temporal scales. SS is relatively fast and more predictable in recently modified landscapes and where well-preserved biodiversity-rich native forests are still present in the landscape. Yet the increasing variation in landscape spatial configuration and matrix heterogeneity in landscapes with intermediate levels of disturbance increases the uncertainty of successional pathways. In landscapes that have suffered extensive and intensive human disturbances, however, succession can be slow or arrested, with impoverished assemblages and reduced potential to deliver ecosystem functions and services. We conclude that: (i) succession must be examined using more comprehensive explanatory models, providing information about the forces affecting not only the presence but also the persistence of species and ecological groups, particularly of those taxa expected to be extirpated from HMTLs; (ii) SS research should integrate new aspects from forest fragmentation and landscape ecology research to address accurately the potential of secondary forests to serve as biodiversity repositories; and (iii) secondary forest stands, as a dynamic component of HMTLs, must be incorporated as key elements of conservation planning; i.e. secondary forest stands must be actively managed (e.g. using assisted forest restoration) according to conservation goals at broad spatial scales. © 2015 Cambridge Philosophical Society.

Abnormal rich club organization and functional brain dynamics in schizophrenia.

PubMed

van den Heuvel, Martijn P; Sporns, Olaf; Collin, Guusje; Scheewe, Thomas; Mandl, René C W; Cahn, Wiepke; Goñi, Joaquín; Hulshoff Pol, Hilleke E; Kahn, René S

2013-08-01

The human brain forms a large-scale structural network of regions and interregional pathways. Recent studies have reported the existence of a selective set of highly central and interconnected hub regions that may play a crucial role in the brain's integrative processes, together forming a central backbone for global brain communication. Abnormal brain connectivity may have a key role in the pathophysiology of schizophrenia. To examine the structure of the rich club in schizophrenia and its role in global functional brain dynamics. Structural diffusion tensor imaging and resting-state functional magnetic resonance imaging were performed in patients with schizophrenia and matched healthy controls. Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands. Forty-eight patients and 45 healthy controls participated in the study. An independent replication data set of 41 patients and 51 healthy controls was included to replicate and validate significant findings. MAIN OUTCOME(S) AND MEASURES: Measures of rich club organization, connectivity density of rich club connections and connections linking peripheral regions to brain hubs, measures of global brain network efficiency, and measures of coupling between brain structure and functional dynamics. Rich club organization between high-degree hub nodes was significantly affected in patients, together with a reduced density of rich club connections predominantly comprising the white matter pathways that link the midline frontal, parietal, and insular hub regions. This reduction in rich club density was found to be associated with lower levels of global communication capacity, a relationship that was absent for other white matter pathways. In addition, patients had an increase in the strength of structural connectivity-functional connectivity coupling. Our findings provide novel biological evidence that schizophrenia is characterized by a selective disruption of brain connectivity among central hub regions of the brain, potentially leading to reduced communication capacity and altered functional brain dynamics.

Biogrid--a microfluidic device for large-scale enzyme-free dissociation of stem cell aggregates.

PubMed

Wallman, Lars; Åkesson, Elisabet; Ceric, Dario; Andersson, Per Henrik; Day, Kelly; Hovatta, Outi; Falci, Scott; Laurell, Thomas; Sundström, Erik

2011-10-07

Culturing stem cells as free-floating aggregates in suspension facilitates large-scale production of cells in closed systems, for clinical use. To comply with GMP standards, the use of substances such as proteolytic enzymes should be avoided. Instead of enzymatic dissociation, the growing cell aggregates may be mechanically cut at passage, but available methods are not compatible with large-scale cell production and hence translation into the clinic becomes a severe bottle-neck. We have developed the Biogrid device, which consists of an array of micrometerscale knife edges, micro-fabricated in silicon, and a manifold in which the microgrid is placed across the central fluid channel. By connecting one side of the Biogrid to a syringe or a pump and the other side to the cell culture, the culture medium with suspended cell aggregates can be aspirated, forcing the aggregates through the microgrid, and ejected back to the cell culture container. Large aggregates are thereby dissociated into smaller fragments while small aggregates pass through the microgrid unaffected. As proof-of-concept, we demonstrate that the Biogrid device can be successfully used for repeated passage of human neural stem/progenitor cells cultured as so-called neurospheres, as well as for passage of suspension cultures of human embryonic stem cells. We also show that human neural stem/progenitor cells tolerate transient pressure changes far exceeding those that will occur in a fluidic system incorporating the Biogrid microgrids. Thus, by using the Biogrid device it is possible to mechanically passage large quantities of cells in suspension cultures in closed fluidic systems, without the use of proteolytic enzymes.

Pathogenic landscapes: Interactions between land, people, disease vectors, and their animal hosts

PubMed Central

2010-01-01

Background Landscape attributes influence spatial variations in disease risk or incidence. We present a review of the key findings from eight case studies that we conducted in Europe and West Africa on the impact of land changes on emerging or re-emerging vector-borne diseases and/or zoonoses. The case studies concern West Nile virus transmission in Senegal, tick-borne encephalitis incidence in Latvia, sandfly abundance in the French Pyrenees, Rift Valley Fever in the Ferlo (Senegal), West Nile Fever and the risk of malaria re-emergence in the Camargue, and rodent-borne Puumala hantavirus and Lyme borreliosis in Belgium. Results We identified general principles governing landscape epidemiology in these diverse disease systems and geographic regions. We formulated ten propositions that are related to landscape attributes, spatial patterns and habitat connectivity, pathways of pathogen transmission between vectors and hosts, scale issues, land use and ownership, and human behaviour associated with transmission cycles. Conclusions A static view of the "pathogenecity" of landscapes overlays maps of the spatial distribution of vectors and their habitats, animal hosts carrying specific pathogens and their habitat, and susceptible human hosts and their land use. A more dynamic view emphasizing the spatial and temporal interactions between these agents at multiple scales is more appropriate. We also highlight the complementarity of the modelling approaches used in our case studies. Integrated analyses at the landscape scale allows a better understanding of interactions between changes in ecosystems and climate, land use and human behaviour, and the ecology of vectors and animal hosts of infectious agents. PMID:20979609

Spike-timing-dependent plasticity in the human dorso-lateral prefrontal cortex.

PubMed

Casula, Elias Paolo; Pellicciari, Maria Concetta; Picazio, Silvia; Caltagirone, Carlo; Koch, Giacomo

2016-12-01

Changes in the synaptic strength of neural connections are induced by repeated coupling of activity of interconnected neurons with precise timing, a phenomenon known as spike-timing-dependent plasticity (STDP). It is debated if this mechanism exists in large-scale cortical networks in humans. We combined transcranial magnetic stimulation (TMS) with concurrent electroencephalography (EEG) to directly investigate the effects of two paired associative stimulation (PAS) protocols (fronto-parietal and parieto-frontal) of pre and post-synaptic inputs within the human fronto-parietal network. We found evidence that the dorsolateral prefrontal cortex (DLPFC) has the potential to form robust STDP. Long-term potentiation/depression of TMS-evoked cortical activity is prompted after that DLPFC stimulation is followed/preceded by posterior parietal stimulation. Such bidirectional changes are paralleled by sustained increase/decrease of high-frequency oscillatory activity, likely reflecting STDP responsivity. The current findings could be important to drive plasticity of damaged cortical circuits in patients with cognitive or psychiatric disorders. Copyright © 2016 Elsevier Inc. All rights reserved.

Canonical Genetic Signatures of the Adult Human Brain

PubMed Central

Hawrylycz, Michael; Miller, Jeremy A.; Menon, Vilas; Feng, David; Dolbeare, Tim; Guillozet-Bongaarts, Angela L.; Jegga, Anil G.; Aronow, Bruce J.; Lee, Chang-Kyu; Bernard, Amy; Glasser, Matthew F.; Dierker, Donna L.; Menche, Jörge; Szafer, Aaron; Collman, Forrest; Grange, Pascal; Berman, Kenneth A.; Mihalas, Stefan; Yao, Zizhen; Stewart, Lance; Barabási, Albert-László; Schulkin, Jay; Phillips, John; Ng, Lydia; Dang, Chinh; Haynor, David R.; Jones, Allan; Van Essen, David C.; Koch, Christof; Lein, Ed

2015-01-01

The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure, and function. We applied a correlation-based metric of “differential stability” (DS) to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing meso-scale genetic organization. The highest DS genes are highly biologically relevant, with enrichment for brain-related biological annotations, disease associations, drug targets, and literature citations. Using high DS genes we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components, and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely-patterned genes displayed dramatic shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry. PMID:26571460

The Macroecology of Sustainability

PubMed Central

Burger, Joseph R.; Allen, Craig D.; Brown, James H.; Burnside, William R.; Davidson, Ana D.; Fristoe, Trevor S.; Hamilton, Marcus J.; Mercado-Silva, Norman; Nekola, Jeffrey C.; Okie, Jordan G.; Zuo, Wenyun

2012-01-01

The discipline of sustainability science has emerged in response to concerns of natural and social scientists, policymakers, and lay people about whether the Earth can continue to support human population growth and economic prosperity. Yet, sustainability science has developed largely independently from and with little reference to key ecological principles that govern life on Earth. A macroecological perspective highlights three principles that should be integral to sustainability science: 1) physical conservation laws govern the flows of energy and materials between human systems and the environment, 2) smaller systems are connected by these flows to larger systems in which they are embedded, and 3) global constraints ultimately limit flows at smaller scales. Over the past few decades, decreasing per capita rates of consumption of petroleum, phosphate, agricultural land, fresh water, fish, and wood indicate that the growing human population has surpassed the capacity of the Earth to supply enough of these essential resources to sustain even the current population and level of socioeconomic development. PMID:22723741

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

The application of heterogeneous cluster grouping to reflective writing for medical humanities literature study to enhance students' empathy, critical thinking, and reflective writing.

PubMed

Liao, Hung-Chang; Wang, Ya-Huei

2016-09-02

To facilitate interdisciplinary collaboration and to make connections between patients' diseases and their social/cultural contexts, the study examined whether the use of heterogeneous cluster grouping in reflective writing for medical humanities literature acquisition could have positive effects on medical university students in terms of empathy, critical thinking, and reflective writing. A 15-week quasi-experimental design was conducted to investigate the learning outcomes. After conducting cluster algorithms, heterogeneous learning clusters (experimental group; n = 43) and non-heterogeneous learning clusters (control group; n = 43) were derived for a medical humanities literature study. Before and after the intervention, an Empathy Scale in Patient Care (ES-PC), a critical thinking disposition assessment (CTDA-R), and a reflective writing test were administered to both groups. The findings showed that on the empathy scale, significant differences in the "behavioral empathy," "affective empathy," and overall sections existed between the post-test mean scores of the experimental group and those of the control group, but such differences did not exist in "intelligent empathy." Regarding critical thinking, there were significant differences in "systematicity and analyticity," "skepticism and well-informed," "maturity and skepticism," and overall sections. As for reflective writing, significant differences existed in "ideas," "voice and point of view," "critical thinking and representation," "depth of reflection on personal growth," and overall sections, but not in "focus and context structure" and "language and conventions." This study outlined an alternative for using heterogeneous cluster grouping in reflective writing about medical humanities literature to facilitate interdisciplinary cooperation to provide more humanizing medical care.

Synaptic Scaling in Combination with Many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity

PubMed Central

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Wörgötter, Florentin

2011-01-01

Synaptic scaling is a slow process that modifies synapses, keeping the firing rate of neural circuits in specific regimes. Together with other processes, such as conventional synaptic plasticity in the form of long term depression and potentiation, synaptic scaling changes the synaptic patterns in a network, ensuring diverse, functionally relevant, stable, and input-dependent connectivity. How synaptic patterns are generated and stabilized, however, is largely unknown. Here we formally describe and analyze synaptic scaling based on results from experimental studies and demonstrate that the combination of different conventional plasticity mechanisms and synaptic scaling provides a powerful general framework for regulating network connectivity. In addition, we design several simple models that reproduce experimentally observed synaptic distributions as well as the observed synaptic modifications during sustained activity changes. These models predict that the combination of plasticity with scaling generates globally stable, input-controlled synaptic patterns, also in recurrent networks. Thus, in combination with other forms of plasticity, synaptic scaling can robustly yield neuronal circuits with high synaptic diversity, which potentially enables robust dynamic storage of complex activation patterns. This mechanism is even more pronounced when considering networks with a realistic degree of inhibition. Synaptic scaling combined with plasticity could thus be the basis for learning structured behavior even in initially random networks. PMID:22203799

Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology.

PubMed

Karbasi, Amin; Salavati, Amir Hesam; Vetterli, Martin

2018-04-01

The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network's topology has received a lot of attentions in neuroscience and has been the center of many research initiatives such as Human Connectome Project. Nevertheless, direct and invasive approaches that slice and observe the neural tissue have proven to be time consuming, complex and costly. As a result, the inverse methods that utilize firing activity of neurons in order to identify the (functional) connections have gained momentum recently, especially in light of rapid advances in recording technologies; It will soon be possible to simultaneously monitor the activities of tens of thousands of neurons in real time. While there are a number of excellent approaches that aim to identify the functional connections from firing activities, the scalability of the proposed techniques plays a major challenge in applying them on large-scale datasets of recorded firing activities. In exceptional cases where scalability has not been an issue, the theoretical performance guarantees are usually limited to a specific family of neurons or the type of firing activities. In this paper, we formulate the neural network reconstruction as an instance of a graph learning problem, where we observe the behavior of nodes/neurons (i.e., firing activities) and aim to find the links/connections. We develop a scalable learning mechanism and derive the conditions under which the estimated graph for a network of Leaky Integrate and Fire (LIf) neurons matches the true underlying synaptic connections. We then validate the performance of the algorithm using artificially generated data (for benchmarking) and real data recorded from multiple hippocampal areas in rats.

Multiplex Networks of Cortical and Hippocampal Neurons Revealed at Different Timescales

PubMed Central

Timme, Nicholas; Ito, Shinya; Myroshnychenko, Maxym; Yeh, Fang-Chin; Hiolski, Emma; Hottowy, Pawel; Beggs, John M.

2014-01-01

Recent studies have emphasized the importance of multiplex networks – interdependent networks with shared nodes and different types of connections – in systems primarily outside of neuroscience. Though the multiplex properties of networks are frequently not considered, most networks are actually multiplex networks and the multiplex specific features of networks can greatly affect network behavior (e.g. fault tolerance). Thus, the study of networks of neurons could potentially be greatly enhanced using a multiplex perspective. Given the wide range of temporally dependent rhythms and phenomena present in neural systems, we chose to examine multiplex networks of individual neurons with time scale dependent connections. To study these networks, we used transfer entropy – an information theoretic quantity that can be used to measure linear and nonlinear interactions – to systematically measure the connectivity between individual neurons at different time scales in cortical and hippocampal slice cultures. We recorded the spiking activity of almost 12,000 neurons across 60 tissue samples using a 512-electrode array with 60 micrometer inter-electrode spacing and 50 microsecond temporal resolution. To the best of our knowledge, this preparation and recording method represents a superior combination of number of recorded neurons and temporal and spatial recording resolutions to any currently available in vivo system. We found that highly connected neurons (“hubs”) were localized to certain time scales, which, we hypothesize, increases the fault tolerance of the network. Conversely, a large proportion of non-hub neurons were not localized to certain time scales. In addition, we found that long and short time scale connectivity was uncorrelated. Finally, we found that long time scale networks were significantly less modular and more disassortative than short time scale networks in both tissue types. As far as we are aware, this analysis represents the first systematic study of temporally dependent multiplex networks among individual neurons. PMID:25536059

From Pole to Pole: Educating Tomorrow's Leaders

NASA Astrophysics Data System (ADS)

Albert, M. R.; Virginia, R. A.

2003-12-01

The high northern and southern latitudes of the earth share an extreme climate, but are vastly different in their histories, ecological systems and human cultures. Polar regions are increasingly under threat from climate change, resource extraction, and the collapse of large-scale marine ecosystems. These systems are important indicators of human influence on global scale processes (ozone depletion, global warming) and are valued for their biodiversity and uniquely adapted cultures. Unfortunately, the polar regions are often poorly understood by our citizens. Dartmouth College offers a liberal arts undergraduate education that trains tomorrow's leaders in politics, humanities, science and medicine. Through the Dickey Institute of Arctic Studies at Dartmouth College, we designed and taught an undergraduate interdisciplinary course to introduce the major physical, ecological and human systems of high latitudes, including the circumpolar northern Arctic regions and the continent of Antarctic and its southern oceans. Using an interdisciplinary approach we examined the science, societies, politics and policies that shape our viewpoint of cold regions. The connections of the polar regions to global processes and international issues were emphasized. In this paper we will describe our use of differing viewpoints to examine varying topics of importance in the polar regions. Starting the course as a tourist, we proceeded as traveler, explorer, scientist, resident, and politician to reach our final goal as informed voter at the end of the semester. A variety of invited speakers enhanced the course. Hoping before the course to attract twenty students, the fifty students enrolled in the course gave us high ratings. .

Dynamic social networks promote cooperation in experiments with humans

PubMed Central

Rand, David G.; Arbesman, Samuel; Christakis, Nicholas A.

2011-01-01

Human populations are both highly cooperative and highly organized. Human interactions are not random but rather are structured in social networks. Importantly, ties in these networks often are dynamic, changing in response to the behavior of one's social partners. This dynamic structure permits an important form of conditional action that has been explored theoretically but has received little empirical attention: People can respond to the cooperation and defection of those around them by making or breaking network links. Here, we present experimental evidence of the power of using strategic link formation and dissolution, and the network modification it entails, to stabilize cooperation in sizable groups. Our experiments explore large-scale cooperation, where subjects’ cooperative actions are equally beneficial to all those with whom they interact. Consistent with previous research, we find that cooperation decays over time when social networks are shuffled randomly every round or are fixed across all rounds. We also find that, when networks are dynamic but are updated only infrequently, cooperation again fails. However, when subjects can update their network connections frequently, we see a qualitatively different outcome: Cooperation is maintained at a high level through network rewiring. Subjects preferentially break links with defectors and form new links with cooperators, creating an incentive to cooperate and leading to substantial changes in network structure. Our experiments confirm the predictions of a set of evolutionary game theoretic models and demonstrate the important role that dynamic social networks can play in supporting large-scale human cooperation. PMID:22084103

Disruption of posteromedial large-scale neural communication predicts recovery from coma.

PubMed

Silva, Stein; de Pasquale, Francesco; Vuillaume, Corine; Riu, Beatrice; Loubinoux, Isabelle; Geeraerts, Thomas; Seguin, Thierry; Bounes, Vincent; Fourcade, Olivier; Demonet, Jean-Francois; Péran, Patrice

2015-12-08

We hypothesize that the major consciousness deficit observed in coma is due to the breakdown of long-range neuronal communication supported by precuneus and posterior cingulate cortex (PCC), and that prognosis depends on a specific connectivity pattern in these networks. We compared 27 prospectively recruited comatose patients who had severe brain injury (Glasgow Coma Scale score <8; 14 traumatic and 13 anoxic cases) with 14 age-matched healthy participants. Standardized clinical assessment and fMRI were performed on average 4 ± 2 days after withdrawal of sedation. Analysis of resting-state fMRI connectivity involved a hypothesis-driven, region of interest-based strategy. We assessed patient outcome after 3 months using the Coma Recovery Scale-Revised (CRS-R). Patients who were comatose showed a significant disruption of functional connectivity of brain areas spontaneously synchronized with PCC, globally notwithstanding etiology. The functional connectivity strength between PCC and medial prefrontal cortex (mPFC) was significantly different between comatose patients who went on to recover and those who eventually scored an unfavorable outcome 3 months after brain injury (Kruskal-Wallis test, p < 0.001; linear regression between CRS-R and PCC-mPFC activity coupling at rest, Spearman ρ = 0.93, p < 0.003). In both etiology groups (traumatic and anoxic), changes in the connectivity of PCC-centered, spontaneously synchronized, large-scale networks account for the loss of external and internal self-centered awareness observed during coma. Sparing of functional connectivity between PCC and mPFC may predict patient outcome, and further studies are needed to substantiate this potential prognosis biomarker. © 2015 American Academy of Neurology.

Sex-Specific Selection and Sex-Biased Gene Expression in Humans and Flies.

PubMed

Cheng, Changde; Kirkpatrick, Mark

2016-09-01

Sexual dimorphism results from sex-biased gene expression, which evolves when selection acts differently on males and females. While there is an intimate connection between sex-biased gene expression and sex-specific selection, few empirical studies have studied this relationship directly. Here we compare the two on a genome-wide scale in humans and flies. We find a distinctive "Twin Peaks" pattern in humans that relates the strength of sex-specific selection, quantified by genetic divergence between male and female adults at autosomal loci, to the degree of sex-biased expression. Genes with intermediate degrees of sex-biased expression show evidence of ongoing sex-specific selection, while genes with either little or completely sex-biased expression do not. This pattern apparently results from differential viability selection in males and females acting in the current generation. The Twin Peaks pattern is also found in Drosophila using a different measure of sex-specific selection acting on fertility. We develop a simple model that successfully recapitulates the Twin Peaks. Our results suggest that many genes with intermediate sex-biased expression experience ongoing sex-specific selection in humans and flies.

Opioids and social bonding: naltrexone reduces feelings of social connection

PubMed Central

Ray, Lara A.; Irwin, Michael R.; Way, Baldwin M.; Eisenberger, Naomi I.

2016-01-01

Close social bonds are critical to a happy and fulfilled life and yet little is known, in humans, about the neurochemical mechanisms that keep individuals feeling close and connected to one another. According to the brain opioid theory of social attachment, opioids may underlie the contented feelings associated with social connection and may be critical to continued bonding. However, the role of opioids in feelings of connection toward close others has only begun to be examined in humans. In a double-blind, placebo-controlled, crossover study of naltrexone (an opioid antagonist), 31 volunteers took naltrexone for 4 days and placebo for 4 days (separated by a 10-day washout period). Participants came to the laboratory once on the last day of taking each drug to complete a task designed to elicit feelings of social connection. Participants also completed daily reports of feelings of social connection while on naltrexone and placebo. In line with hypotheses, and for the first time in humans, results demonstrated that naltrexone (vs placebo) reduced feelings of connection both in the laboratory and in daily reports. These results highlight the importance of opioids for social bonding with close others, lending support to the brain opioid theory of social attachment. PMID:26796966

Minimum spanning tree analysis of the human connectome.

PubMed

van Dellen, Edwin; Sommer, Iris E; Bohlken, Marc M; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A; Douw, Linda; Otte, Willem M; Mandl, René C W; Stam, Cornelis J

2018-06-01

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Spatio-Temporal Evolution and Scaling Properties of Human Settlements (Invited)

NASA Astrophysics Data System (ADS)

Small, C.; Milesi, C.; Elvidge, C.; Baugh, K.; Henebry, G. M.; Nghiem, S. V.

2013-12-01

Growth and evolution of cities and smaller settlements is usually studied in the context of population and other socioeconomic variables. While this is logical in the sense that settlements are groups of humans engaged in socioeconomic processes, our means of collecting information about spatio-temporal distributions of population and socioeconomic variables often lack the spatial and temporal resolution to represent the processes at scales which they are known to occur. Furthermore, metrics and definitions often vary with country and through time. However, remote sensing provides globally consistent, synoptic observations of several proxies for human settlement at spatial and temporal resolutions sufficient to represent the evolution of settlements over the past 40 years. We use several independent but complementary proxies for anthropogenic land cover to quantify spatio-temporal (ST) evolution and scaling properties of human settlements globally. In this study we begin by comparing land cover and night lights in 8 diverse settings - each spanning gradients of population density and degree of land surface modification. Stable anthropogenic night light is derived from multi-temporal composites of emitted luminance measured by the VIIRS and DMSP-OLS sensors. Land cover is represented as mixtures of sub-pixel fractions of rock, soil and impervious Substrates, Vegetation and Dark surfaces (shadow, water and absorptive materials) estimated from Landsat imagery with > 94% accuracy. Multi-season stability and variability of land cover fractions effectively distinguishes between spectrally similar land covers that corrupt thematic classifications based on single images. We find that temporal stability of impervious substrates combined with persistent shadow cast between buildings results in temporally stable aggregate reflectance across seasons at the 30 m scale of a Landsat pixel. Comparison of night light brightness with land cover composition, stability and variability yields several consistent relationships that persist across a variety of settlement types and physical environments. We use the multiple threshold method of Small et al (2011) to represent a continuum of settlement density by segmenting both night light brightness and multi-season land cover characteristics. Rank-size distributions of spatially contiguous segments quantify scaling and connectivity of land cover. Spatial and temporal evolution of rank-size distributions is consistent with power laws as suggested by Zipf's Law for city size based on population. However, unlike Zipf's Law, the observed distributions persist to global scales in which the larger agglomerations are much larger than individual cities. The scaling relations observed extend from the scale of cities and smaller settlements up to vast spatial networks of interconnected settlements.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder.

PubMed

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura Km; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido Kw; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-11-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder

PubMed Central

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura KM; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido KW; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-01-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period. PMID:27238621

Health effects of fine particulate air pollution: lines that connect

DOE Office of Scientific and Technical Information (OSTI.GOV)

Judith C. Chow; John G. Watson; Joe L. Mauderly

2006-10-15

In the 2006 A&WMA Critical Review on 'Health Effects of fine particulate air pollution: lines that connect' Drs. C. Arden Pope III and Douglas Dockery addressed the epidemiological evidence for the effects of particulate matter (PM) on human health indicators. The review documents substantial progress since the 1997 Critical Review in the areas of: (1) short-term exposure and mortality; (2) long-term exposure and mortality; (3) time scales of exposure; (4) the shape of the concentration-response function; (5) cardiovascular disease; and (6) biological plausibility. This critical review discussion was compiled from written submissions and presentation transcripts, which were revised for concisenessmore » and to minimize redundancy. The invited discussants were as follows were: Dr. Joe L. Mauderly, Dr. Daniel L. Costa, Dr. Ronald E. Wyzga, and Dr. Sverre Vedal. The contributing discussants were: Dr. George M. Hidy, Sam L. Altshuler, Dr. David Marrack, Jon M. Heuss, and Dr. George T. Wolff. See Coal Abstracts entry Sep 2006 00390 for the Critical Review. 80 refs.« less

Music and words in the visual cortex: The impact of musical expertise.

PubMed

Mongelli, Valeria; Dehaene, Stanislas; Vinckier, Fabien; Peretz, Isabelle; Bartolomeo, Paolo; Cohen, Laurent

2017-01-01

How does the human visual system accommodate expertise for two simultaneously acquired symbolic systems? We used fMRI to compare activations induced in the visual cortex by musical notation, written words and other classes of objects, in professional musicians and in musically naïve controls. First, irrespective of expertise, selective activations for music were posterior and lateral to activations for words in the left occipitotemporal cortex. This indicates that symbols characterized by different visual features engage distinct cortical areas. Second, musical expertise increased the volume of activations for music and led to an anterolateral displacement of word-related activations. In musicians, there was also a dramatic increase of the brain-scale networks connected to the music-selective visual areas. Those findings reveal that acquiring a double visual expertise involves an expansion of category-selective areas, the development of novel long-distance functional connectivity, and possibly some competition between categories for the colonization of cortical space. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cognitive control related network analysis: A novel way to measure neuron fiber connection of Alzheimer's disease.

PubMed

Changle Zhang; Tao Chai; Na Gao; Ma, Heather T

2017-07-01

Effective measurement of cognitive impairment caused by Alzheimer's disease (AD) will provide a chance for early medical intervention and delay the disease onset. Diffusion tensor imaging (DTI) provides a non-intrusive examination of cranial nerve diseases which can help us observe the microstructure of neuron fibers. Cognitive control network (CCN) consists of the brain regions that highly related to human self-control. In this study, hub-and-spoke model which was widely used in transportation and sociology area had been employed to analyze the relationship of CCN and other regions under its control, cognitive control related network (CCRN) was built by applying this model. Local and global graph theoretical parameters were calculated and went through statistical analysis. Significant difference had been found in the scale of local as well as global which may represent the impairment of cognitive control ability. This result may provide a potential bio-marker for the loss of connection caused by Alzheimer's disease.

Ising-based model of opinion formation in a complex network of interpersonal interactions

NASA Astrophysics Data System (ADS)

Grabowski, A.; Kosiński, R. A.

2006-03-01

In our work the process of opinion formation in the human population, treated as a scale-free network, is modeled and investigated numerically. The individuals (nodes of the network) are characterized by their authorities, which influence the interpersonal interactions in the population. Hierarchical, two-level structures of interpersonal interactions and spatial localization of individuals are taken into account. The effect of the mass media, modeled as an external stimulation acting on the social network, on the process of opinion formation is investigated. It was found that in the time evolution of opinions of individuals critical phenomena occur. The first one is observed in the critical temperature of the system TC and is connected with the situation in the community, which may be described by such quantifiers as the economic status of people, unemployment or crime wave. Another critical phenomenon is connected with the influence of mass media on the population. As results from our computations, under certain circumstances the mass media can provoke critical rebuilding of opinions in the population.

Children's use of geometry for reorientation.

PubMed

Lee, Sang Ah; Spelke, Elizabeth S

2008-09-01

Research on navigation has shown that humans and laboratory animals recover their sense of orientation primarily by detecting geometric properties of large-scale surface layouts (e.g. room shape), but the reasons for the primacy of layout geometry have not been clarified. In four experiments, we tested whether 4-year-old children reorient by the geometry of extended wall-like surfaces because such surfaces are large and perceived as stable, because they serve as barriers to vision or to locomotion, or because they form a single, connected geometric figure. Disoriented children successfully reoriented by the shape of an arena formed by surfaces that were short enough to see and step over. In contrast, children failed to reorient by the shape of an arena defined by large and stable columns or by connected lines on the floor. We conclude that preschool children's reorientation is not guided by the functional relevance of the immediate environmental properties, but rather by a specific sensitivity to the geometric properties of the extended three-dimensional surface layout.

Sex differences in the structural connectome of the human brain.

PubMed

Ingalhalikar, Madhura; Smith, Alex; Parker, Drew; Satterthwaite, Theodore D; Elliott, Mark A; Ruparel, Kosha; Hakonarson, Hakon; Gur, Raquel E; Gur, Ruben C; Verma, Ragini

2014-01-14

Sex differences in human behavior show adaptive complementarity: Males have better motor and spatial abilities, whereas females have superior memory and social cognition skills. Studies also show sex differences in human brains but do not explain this complementarity. In this work, we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged 8-22 y, 428 males and 521 females) and discovered unique sex differences in brain connectivity during the course of development. Connection-wise statistical analysis, as well as analysis of regional and global network measures, presented a comprehensive description of network characteristics. In all supratentorial regions, males had greater within-hemispheric connectivity, as well as enhanced modularity and transitivity, whereas between-hemispheric connectivity and cross-module participation predominated in females. However, this effect was reversed in the cerebellar connections. Analysis of these changes developmentally demonstrated differences in trajectory between males and females mainly in adolescence and in adulthood. Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.

Method Of Packaging And Assembling Electro-Microfluidic Devices

DOEpatents

Benavides, Gilbert L.; Galambos, Paul C.; Emerson, John A.; Peterson, Kenneth A.; Giunta, Rachel K.; Zamora, David Lee; Watson, Robert D.

2004-11-23

A new architecture for packaging surface micromachined electro-microfluidic devices is presented. This architecture relies on two scales of packaging to bring fluid to the device scale (picoliters) from the macro-scale (microliters). The architecture emulates and utilizes electronics packaging technology. The larger package consists of a circuit board with embedded fluidic channels and standard fluidic connectors (e.g. Fluidic Printed Wiring Board). The embedded channels connect to the smaller package, an Electro-Microfluidic Dual-Inline-Package (EMDIP) that takes fluid to the microfluidic integrated circuit (MIC). The fluidic connection is made to the back of the MIC through Bosch-etched holes that take fluid to surface micromachined channels on the front of the MIC. Electrical connection is made to bond pads on the front of the MIC.

Bridging the Gap between the Human and Macaque Connectome: A Quantitative Comparison of Global Interspecies Structure-Function Relationships and Network Topology

PubMed Central

Miranda-Dominguez, Oscar; Mills, Brian D.; Grayson, David; Woodall, Andrew; Grant, Kathleen A.; Kroenke, Christopher D.

2014-01-01

Resting state functional connectivity MRI (rs-fcMRI) may provide a powerful and noninvasive “bridge” for comparing brain function between patients and experimental animal models; however, the relationship between human and macaque rs-fcMRI remains poorly understood. Here, using a novel surface deformation process for species comparisons in the same anatomical space (Van Essen, 2004, 2005), we found high correspondence, but also unique hub topology, between human and macaque functional connectomes. The global functional connectivity match between species was moderate to strong (r = 0.41) and increased when considering the top 15% strongest connections (r = 0.54). Analysis of the match between functional connectivity and the underlying anatomical connectivity, derived from a previous retrograde tracer study done in macaques (Markov et al., 2012), showed impressive structure–function correspondence in both the macaque and human. When examining the strongest structural connections, we found a 70–80% match between structural and functional connectivity matrices in both species. Finally, we compare species on two widely used metrics for studying hub topology: degree and betweenness centrality. The data showed topological agreement across the species, with nodes of the posterior cingulate showing high degree and betweenness centrality. In contrast, nodes in medial frontal and parietal cortices were identified as having high degree and betweenness in the human as opposed to the macaque. Our results provide: (1) a thorough examination and validation for a surface-based interspecies deformation process, (2) a strong theoretical foundation for making interspecies comparisons of rs-fcMRI, and (3) a unique look at topological distinctions between the species. PMID:24741045

Restoring habitat permeability to roaded landscapes with isometrically-scaled wildlife crossings

USGS Publications Warehouse

Bissonette, J.A.; Adair, W.

2008-01-01

Globally, human activities impact from one-third to one-half of the earth's land surface; a major component of development involves the construction of roads. In the US and Europe, road networks fragment normal animal movement patterns, reduce landscape permeability, and increase wildlife-vehicle collisions, often with serious wildlife population and human health consequences. Critically, the placement of wildlife crossing structures to restore landscape connectivity and reduce the number of wildlife-vehicle collisions has been a hit-or-miss proposition with little ecological underpinning, however recent important developments in allometric scaling laws can be used to guide their placement. In this paper, we used cluster analysis to develop domains of scale for mammalian species groups having similar vagility and developed metrics that reflect realistic species movement dynamics. We identified six home range area domains; three quarters of 102 species clustered in the three smallest domains. We used HR0.5 to represent a daily movement metric; when individual species movements were plotted against road mile markers, 71.2% of 72 species found in North America were included at distances of ???1 mi. The placement of wildlife crossings based on the HR0.5 metric, along with appropriate auxiliary mitigation, will re-establish landscape permeability by facilitating wildlife movement across the roaded landscape and significantly improve road safety by reducing wildlife vehicle collisions.

EEG functional connectivity, axon delays and white matter disease.

PubMed

Nunez, Paul L; Srinivasan, Ramesh; Fields, R Douglas

2015-01-01

Both structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists. Treatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG's oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework. Myelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning. Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks. Combined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence. White matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments. Copyright © 2014 International Federation of Clinical Neurophysiology. All rights reserved.

The Conundrum of Functional Brain Networks: Small-World Efficiency or Fractal Modularity

PubMed Central

Gallos, Lazaros K.; Sigman, Mariano; Makse, Hernán A.

2012-01-01

The human brain has been studied at multiple scales, from neurons, circuits, areas with well-defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs. PMID:22586406

Measuring Large-Scale Social Networks with High Resolution

PubMed Central

Stopczynski, Arkadiusz; Sekara, Vedran; Sapiezynski, Piotr; Cuttone, Andrea; Madsen, Mette My; Larsen, Jakob Eg; Lehmann, Sune

2014-01-01

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection. PMID:24770359

Connectivity from source to sink in a lowland area: the Loire river basin (France)

NASA Astrophysics Data System (ADS)

Gay, Aurore; Cerdan, Olivier; Degan, Francesca; Salvador, Sebastien

2014-05-01

Sediment connectivity relates to the transfer of sediments from sources to sinks via runoff and in channel transport. It is highly dependent on spatial variability of landscape properties such as differences in morphology, land use and infiltration/runoff characteristics but may also vary in time due to differences in rainfall amount/intensity and changes in vegetation cover throughout the year. In the Loire river basin, we found that sediment fluxes displayed strong variations in space but also at the interannual and seasonnal time scales (Gay et al. 2013). In this context, our goal is to better understand and quantify hillslope sediment redistributions within this lowland area thanks to the use of semi distributed connectivity approach. To this aim, Borselli's index of connectivity (IC, Borselli et al., 2008) is selected to assess hillslope connectivity at annual and seasonal time scales. Several improvements are proposed to take into account the coupling of the structural landscape connectivity and its hydrosedimentary response. Parameters such as rainfall intensity and differences in seasonal land cover are integrated into the model to account for landscape variations through time. Infiltration and runoff indices were also tested. Preliminary results confirm the variability of landscape connectivity throughout the year. The integration of the index of infiltration and runoff properties of landscape (IDPR) as defined by Mardhel et al. 2004 seems to improve the IC model outputs. From this first step, in-stream sediment connectivity index should be developed for a better understanding and assessment of sediment redistributions at the entire catchment scale. L. Borselli L., Cassi P., Torri D. Prolegomena to sediment and flow connectivity in the landscape: a GIS and field numerical assessment. Catena, 75 (2008), pp. 268-277 Gay A., Cerdan O., Delmas M., Desmet M., Variability of sediment yields in the Loire river basin (France): the role of small scale catchments (under review). Mardhel V., Frantar P., Uhan J., Mio A. Index of development and persistence of the river networks as a component of regional groundwater vulnerability assessment in Slovenia.Int. Conf. groundwater vulnerability assessment and mapping. Ustron, Poland, 15-18 June 2004.

Convergent innovation for affordable nutrition, health, and health care: the global pulse roadmap.

PubMed

Jha, Srivardhini K; McDermott, John; Bacon, Gordon; Lannon, Chris; Joshi, P K; Dubé, Laurette

2014-12-01

The paper outlines how the principles of convergent innovation (CI) can be applied to bring about a transformation in the pulse value chain. The paper presents three pioneering CI initiatives--two in conception and one in operation--by various actors in the pulse ecosystem, which are delivering economic and human development impact in particular segments of the pulse value chain. It goes on to propose the way forward to scale up these efforts and connect them into a roadmap so as to achieve transformation throughout society, calling into action a number of actors in the ecosystem. © 2014 New York Academy of Sciences.

Connecting the study of wild influenza with the potential for pandemic disease

PubMed Central

Runstadler, Jonathan; Hill, Nichola; Hussein, Islam T.M.; Puryear, Wendy; Keogh, Mandy

2013-01-01

Continuing outbreaks of pathogenic (H5N1) and pandemic (SOIVH1N1) influenza have underscored the need to understand the origin, characteristics, and evolution of novel influenza A virus (IAV) variants that pose a threat to human health. In the last 4–5 years, focus has been placed on the organization of large-scale surveillance programs to examine the phylogenetics of avian influenza virus (AIV) and host-virus relationships in domestic and wild animals. Here we review the current gaps in wild animal and environmental surveillance and the current understanding of genetic signatures in potentially pandemic strains. PMID:23541413

On identifying relationships between the flood scaling exponent and basin attributes.

PubMed

Medhi, Hemanta; Tripathi, Shivam

2015-07-01

Floods are known to exhibit self-similarity and follow scaling laws that form the basis of regional flood frequency analysis. However, the relationship between basin attributes and the scaling behavior of floods is still not fully understood. Identifying these relationships is essential for drawing connections between hydrological processes in a basin and the flood response of the basin. The existing studies mostly rely on simulation models to draw these connections. This paper proposes a new methodology that draws connections between basin attributes and the flood scaling exponents by using observed data. In the proposed methodology, region-of-influence approach is used to delineate homogeneous regions for each gaging station. Ordinary least squares regression is then applied to estimate flood scaling exponents for each homogeneous region, and finally stepwise regression is used to identify basin attributes that affect flood scaling exponents. The effectiveness of the proposed methodology is tested by applying it to data from river basins in the United States. The results suggest that flood scaling exponent is small for regions having (i) large abstractions from precipitation in the form of large soil moisture storages and high evapotranspiration losses, and (ii) large fractions of overland flow compared to base flow, i.e., regions having fast-responding basins. Analysis of simple scaling and multiscaling of floods showed evidence of simple scaling for regions in which the snowfall dominates the total precipitation.

A Multi-Scale Integrated Approach to Representing Watershed Systems: Significance and Challenges

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Katopodes, N.

2013-12-01

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a key to representing watershed systems lies in an integrated, interdisciplinary approach, whereby a physically-based model is used for assessments/evaluations associated with future changes in landuse, climate, and ecosystems.

Using connectome-based predictive modeling to predict individual behavior from brain connectivity

PubMed Central

Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd

2017-01-01

Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017

Dexmedetomidine Disrupts the Local and Global Efficiencies of Large-scale Brain Networks.

PubMed

Hashmi, Javeria A; Loggia, Marco L; Khan, Sheraz; Gao, Lei; Kim, Jieun; Napadow, Vitaly; Brown, Emery N; Akeju, Oluwaseun

2017-03-01

A clear understanding of the neural basis of consciousness is fundamental to research in clinical and basic neuroscience disciplines and anesthesia. Recently, decreased efficiency of information integration was suggested as a core network feature of propofol-induced unconsciousness. However, it is unclear whether this finding can be generalized to dexmedetomidine, which has a different molecular target. Dexmedetomidine was administered as a 1-μg/kg bolus over 10 min, followed by a 0.7-μg · kg · h infusion to healthy human volunteers (age range, 18 to 36 yr; n = 15). Resting-state functional magnetic resonance imaging data were acquired during baseline, dexmedetomidine-induced altered arousal, and recovery states. Zero-lag correlations between resting-state functional magnetic resonance imaging signals extracted from 131 brain parcellations were used to construct weighted brain networks. Network efficiency, degree distribution, and node strength were computed using graph analysis. Parcellated brain regions were also mapped to known resting-state networks to study functional connectivity changes. Dexmedetomidine significantly reduced the local and global efficiencies of graph theory-derived networks. Dexmedetomidine also reduced the average brain connectivity strength without impairing the degree distribution. Functional connectivity within and between all resting-state networks was modulated by dexmedetomidine. Dexmedetomidine is associated with a significant drop in the capacity for efficient information transmission at both the local and global levels. These changes result from reductions in the strength of connectivity and also manifest as reduced within and between resting-state network connectivity. These findings strengthen the hypothesis that conscious processing relies on an efficient system of information transfer in the brain.

Avian and simian malaria: do they have a cancer connection?

PubMed

Ward, Martin; Benelli, Giovanni

2017-03-01

It has been claimed that infectious agents transmitted by mosquitoes (Diptera: Culicidae) may have a greater connection to cancer then hitherto supposed and that the immune system struggles to recognize and fight some of these infectious agents. One of the claims made is that there is a connection between human malaria and brain cancers in the USA. However, the USA declared itself free of human malaria in the last century, yet cancer incidences remain high, suggesting any overall cancer connection is slight. Two fundamental questions arise from the possible mosquito-cancer connection. Firstly, if mosquitoes are able to vector some pathogens and parasites linked with cancer pathogenesis, why has the fact not been discovered decades ago? Secondly, if there is a connection (other than in relation to Burkett's lymphoma), what is its extent? The answers may well lie with the various types of malarias known to exist. The discovery in humans of the simian malaria, caused by Plasmodium knowlesi, suggests that other forms of simian or even avian malaria may be capable of survival in humans, albeit at low levels of parasitemia, and humans may be a dead-end host. Other carcinogenic infectious agents transmitted by mosquitoes may also go undetected because either no one is looking for them, or they are looking in wrong anatomical locations and/or with inadequate tools. Research on false negative test results with respect to many infectious agents is sadly lacking, so its extent is unknown. However, electronic and other media provide numerous instances of patients failing to be diagnosed for both human malaria and Lyme's disease, to take just two examples. This review suggests that to shed light on a potential mosquito-cancer connection, more research is required to establish whether other simian and avian forms of malaria play a part. If so, then they potentially provide unique markers for early cancer detection.

Topological Filtering of Dynamic Functional Brain Networks Unfolds Informative Chronnectomics: A Novel Data-Driven Thresholding Scheme Based on Orthogonal Minimal Spanning Trees (OMSTs)

PubMed Central

Dimitriadis, Stavros I.; Salis, Christos; Tarnanas, Ioannis; Linden, David E.

2017-01-01

The human brain is a large-scale system of functionally connected brain regions. This system can be modeled as a network, or graph, by dividing the brain into a set of regions, or “nodes,” and quantifying the strength of the connections between nodes, or “edges,” as the temporal correlation in their patterns of activity. Network analysis, a part of graph theory, provides a set of summary statistics that can be used to describe complex brain networks in a meaningful way. The large-scale organization of the brain has features of complex networks that can be quantified using network measures from graph theory. The adaptation of both bivariate (mutual information) and multivariate (Granger causality) connectivity estimators to quantify the synchronization between multichannel recordings yields a fully connected, weighted, (a)symmetric functional connectivity graph (FCG), representing the associations among all brain areas. The aforementioned procedure leads to an extremely dense network of tens up to a few hundreds of weights. Therefore, this FCG must be filtered out so that the “true” connectivity pattern can emerge. Here, we compared a large number of well-known topological thresholding techniques with the novel proposed data-driven scheme based on orthogonal minimal spanning trees (OMSTs). OMSTs filter brain connectivity networks based on the optimization between the global efficiency of the network and the cost preserving its wiring. We demonstrated the proposed method in a large EEG database (N = 101 subjects) with eyes-open (EO) and eyes-closed (EC) tasks by adopting a time-varying approach with the main goal to extract features that can totally distinguish each subject from the rest of the set. Additionally, the reliability of the proposed scheme was estimated in a second case study of fMRI resting-state activity with multiple scans. Our results demonstrated clearly that the proposed thresholding scheme outperformed a large list of thresholding schemes based on the recognition accuracy of each subject compared to the rest of the cohort (EEG). Additionally, the reliability of the network metrics based on the fMRI static networks was improved based on the proposed topological filtering scheme. Overall, the proposed algorithm could be used across neuroimaging and multimodal studies as a common computationally efficient standardized tool for a great number of neuroscientists and physicists working on numerous of projects. PMID:28491032

Landscape genetic analyses reveal fine-scale effects of forest fragmentation in an insular tropical bird.

PubMed

Khimoun, Aurélie; Peterman, William; Eraud, Cyril; Faivre, Bruno; Navarro, Nicolas; Garnier, Stéphane

2017-10-01

Within the framework of landscape genetics, resistance surface modelling is particularly relevant to explicitly test competing hypotheses about landscape effects on gene flow. To investigate how fragmentation of tropical forest affects population connectivity in a forest specialist bird species, we optimized resistance surfaces without a priori specification, using least-cost (LCP) or resistance (IBR) distances. We implemented a two-step procedure in order (i) to objectively define the landscape thematic resolution (level of detail in classification scheme to describe landscape variables) and spatial extent (area within the landscape boundaries) and then (ii) to test the relative role of several landscape features (elevation, roads, land cover) in genetic differentiation in the Plumbeous Warbler (Setophaga plumbea). We detected a small-scale reduction of gene flow mainly driven by land cover, with a negative impact of the nonforest matrix on landscape functional connectivity. However, matrix components did not equally constrain gene flow, as their conductivity increased with increasing structural similarity with forest habitat: urban areas and meadows had the highest resistance values whereas agricultural areas had intermediate resistance values. Our results revealed a higher performance of IBR compared to LCP in explaining gene flow, reflecting suboptimal movements across this human-modified landscape, challenging the common use of LCP to design habitat corridors and advocating for a broader use of circuit theory modelling. Finally, our results emphasize the need for an objective definition of landscape scales (landscape extent and thematic resolution) and highlight potential pitfalls associated with parameterization of resistance surfaces. © 2017 John Wiley & Sons Ltd.

The visual system of male scale insects

NASA Astrophysics Data System (ADS)

Buschbeck, Elke K.; Hauser, Martin

2009-03-01

Animal eyes generally fall into two categories: (1) their photoreceptive array is convex, as is typical for camera eyes, including the human eye, or (2) their photoreceptive array is concave, as is typical for the compound eye of insects. There are a few rare examples of the latter eye type having secondarily evolved into the former one. When viewed in a phylogenetic framework, the head morphology of a variety of male scale insects suggests that this group could be one such example. In the Margarodidae (Hemiptera, Coccoidea), males have been described as having compound eyes, while males of some more derived groups only have two single-chamber eyes on each side of the head. Those eyes are situated in the place occupied by the compound eye of other insects. Since male scale insects tend to be rare, little is known about how their visual systems are organized, and what anatomical traits are associated with this evolutionary transition. In adult male Margarodidae, one single-chamber eye (stemmateran ocellus) is present in addition to a compound eye-like region. Our histological investigation reveals that the stemmateran ocellus has an extended retina which is formed by concrete clusters of receptor cells that connect to its own first-order neuropil. In addition, we find that the ommatidia of the compound eyes also share several anatomical characteristics with simple camera eyes. These include shallow units with extended retinas, each of which is connected by its own small nerve to the lamina. These anatomical changes suggest that the margarodid compound eye represents a transitional form to the giant unicornal eyes that have been described in more derived species.

A conceptual model for quantifying connectivity using graph theory and cellular (per-pixel) approach

NASA Astrophysics Data System (ADS)

Singh, Manudeo; Sinha, Rajiv; Tandon, Sampat K.

2016-04-01

The concept of connectivity is being increasingly used for understanding hydro-geomorphic processes at all spatio-temporal scales. Connectivity is defined as the potential for energy and material flux (water, sediments, nutrients, heat, etc.) to navigate within or between the landscape systems and has two components, structural connectivity and dynamic connectivity. Structural connectivity is defined by the spatially connected features (physical linkages) through which energy and materials flow. Dynamic connectivity is a process defined connectivity component. These two connectivity components also interact with each other by forming a feedback system. This study attempts to explore a method to quantify structural and dynamic connectivity. In fluvial transport systems, sediment and water can flow in either a diffused manner or in a channelized way. At all the scales, hydrological and sediment fluxes can be tracked using a cellular (per-pixel) approach and can be quantified using graphical approach. The material flux, slope and LULC (Land Use Land Cover) weightage factors of a pixel together determine if it will contribute towards connectivity of the landscape/system. In a graphical approach, all the contributing pixels will form a node at their centroid and this node will be connected to the next 'down-node' via a directed edge with 'least cost path'. The length of the edge will depend on the desired spatial scale and its path direction will depend on the traversed pixel's slope and the LULC (weightage) factors. The weightage factors will lie in-between 0 to 1. This value approaches 1 for the LULC factors which promote connectivity. For example, in terms of sediment connectivity, the weightage could be RUSLE (Revised Universal Soil Loss Equation) C-factors with bare unconsolidated surfaces having values close to 1. This method is best suited for areas with low slopes, where LULC can be a deciding as well as dominating factor. The degree of connectivity and its pathways will show changes under different LULC conditions even if the slope remains the same. The graphical approach provides the statistics of connected and disconnected graph elements (edges, nodes) and graph components, thereby allowing the quantification of structural connectivity. This approach also quantifies the dynamic connectivity by allowing the measurement of the fluxes (e.g. via hydrographs or sedimentographs) at any node as well as at any system outlet. The contribution of any sub-system can be understood by removing the remaining sub-systems which can be conveniently achieved by masking associated graph elements.

Asymmetric projections of the arcuate fasciculus to the temporal cortex underlie lateralized language function in the human brain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Takaya, Shigetoshi; Kuperberg, Gina R.; Tufts Univ., Medford, MA

The arcuate fasciculus (AF) in the human brain has asymmetric structural properties. However, the topographic organization of the asymmetric AF projections to the cortex and its relevance to cortical function remain unclear. Here we mapped the posterior projections of the human AF in the inferior parietal and lateral temporal cortices using surface-based structural connectivity analysis based on diffusion MRI and investigated their hemispheric differences. We then performed the cross-modal comparison with functional connectivity based on resting-state functional MRI (fMRI) and task-related cortical activation based on fMRI using a semantic classification task of single words. Structural connectivity analysis showed that themore » left AF connecting to Broca's area predominantly projected in the lateral temporal cortex extending from the posterior superior temporal gyrus to the mid part of the superior temporal sulcus and the middle temporal gyrus, whereas the right AF connecting to the right homolog of Broca's area predominantly projected to the inferior parietal cortex extending from the mid part of the supramarginal gyrus to the anterior part of the angular gyrus. The left-lateralized projection regions of the AF in the left temporal cortex had asymmetric functional connectivity with Broca's area, indicating structure-function concordance through the AF. During the language task, left-lateralized cortical activation was observed. Among them, the brain responses in the temporal cortex and Broca's area that were connected through the left-lateralized AF pathway were specifically correlated across subjects. These results suggest that the human left AF, which structurally and functionally connects the mid temporal cortex and Broca's area in asymmetrical fashion, coordinates the cortical activity in these remote cortices during a semantic decision task. As a result, the unique feature of the left AF is discussed in the context of the human capacity for language.« less

Asymmetric projections of the arcuate fasciculus to the temporal cortex underlie lateralized language function in the human brain

DOE PAGES

Takaya, Shigetoshi; Kuperberg, Gina R.; Tufts Univ., Medford, MA; ...

2015-09-15

The arcuate fasciculus (AF) in the human brain has asymmetric structural properties. However, the topographic organization of the asymmetric AF projections to the cortex and its relevance to cortical function remain unclear. Here we mapped the posterior projections of the human AF in the inferior parietal and lateral temporal cortices using surface-based structural connectivity analysis based on diffusion MRI and investigated their hemispheric differences. We then performed the cross-modal comparison with functional connectivity based on resting-state functional MRI (fMRI) and task-related cortical activation based on fMRI using a semantic classification task of single words. Structural connectivity analysis showed that themore » left AF connecting to Broca's area predominantly projected in the lateral temporal cortex extending from the posterior superior temporal gyrus to the mid part of the superior temporal sulcus and the middle temporal gyrus, whereas the right AF connecting to the right homolog of Broca's area predominantly projected to the inferior parietal cortex extending from the mid part of the supramarginal gyrus to the anterior part of the angular gyrus. The left-lateralized projection regions of the AF in the left temporal cortex had asymmetric functional connectivity with Broca's area, indicating structure-function concordance through the AF. During the language task, left-lateralized cortical activation was observed. Among them, the brain responses in the temporal cortex and Broca's area that were connected through the left-lateralized AF pathway were specifically correlated across subjects. These results suggest that the human left AF, which structurally and functionally connects the mid temporal cortex and Broca's area in asymmetrical fashion, coordinates the cortical activity in these remote cortices during a semantic decision task. As a result, the unique feature of the left AF is discussed in the context of the human capacity for language.« less

Tinnitus alters resting state functional connectivity (RSFC) in human auditory and non-auditory brain regions as measured by functional near-infrared spectroscopy (fNIRS)

PubMed Central

Hu, Xiao-Su; Issa, Mohamad; Bisconti, Silvia; Kovelman, Ioulia; Kileny, Paul; Basura, Gregory

2017-01-01

Tinnitus, or phantom sound perception, leads to increased spontaneous neural firing rates and enhanced synchrony in central auditory circuits in animal models. These putative physiologic correlates of tinnitus to date have not been well translated in the brain of the human tinnitus sufferer. Using functional near-infrared spectroscopy (fNIRS) we recently showed that tinnitus in humans leads to maintained hemodynamic activity in auditory and adjacent, non-auditory cortices. Here we used fNIRS technology to investigate changes in resting state functional connectivity between human auditory and non-auditory brain regions in normal-hearing, bilateral subjective tinnitus and controls before and after auditory stimulation. Hemodynamic activity was monitored over the region of interest (primary auditory cortex) and non-region of interest (adjacent non-auditory cortices) and functional brain connectivity was measured during a 60-second baseline/period of silence before and after a passive auditory challenge consisting of alternating pure tones (750 and 8000Hz), broadband noise and silence. Functional connectivity was measured between all channel-pairs. Prior to stimulation, connectivity of the region of interest to the temporal and fronto-temporal region was decreased in tinnitus participants compared to controls. Overall, connectivity in tinnitus was differentially altered as compared to controls following sound stimulation. Enhanced connectivity was seen in both auditory and non-auditory regions in the tinnitus brain, while controls showed a decrease in connectivity following sound stimulation. In tinnitus, the strength of connectivity was increased between auditory cortex and fronto-temporal, fronto-parietal, temporal, occipito-temporal and occipital cortices. Together these data suggest that central auditory and non-auditory brain regions are modified in tinnitus and that resting functional connectivity measured by fNIRS technology may contribute to conscious phantom sound perception and potentially serve as an objective measure of central neural pathology. PMID:28604786

The Human Connection

ERIC Educational Resources Information Center

Holliday, Christina O.

2005-01-01

Without effective classroom management, teaching and learning cannot take place. The responsibility for a teacher's success in the classroom lies as much in the human connection between administrator and teacher as between teacher and student. In fact, it lies with all who work with schools: universities, school boards, administrators, and…

A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Malassezia yeasts produce a collection of exceptionally potent activators of the Ah (dioxin) receptor detected in diseased human skin

PubMed Central

Magiatis, Prokopios; Pappas, Periklis; Gaitanis, George; Mexia, Nikitia; Melliou, Eleni; Galanou, Maria; Vlachos, Christophoros; Stathopoulou, Konstantina; Skaltsounis, Alexios Leandros; Marselos, Marios; Velegraki, Aristea; Denison, Michael S.; Bassukas, Ioannis D.

2013-01-01

Malassezia yeasts are commensal microorganisms which under insufficiently understood conditions can become pathogenic. We have previously shown that specific strains isolated from diseased human skin can preferentially produce agonists of the aryl hydrocarbon receptor (AhR), whose activation has been linked to certain skin diseases. Investigation of skin scale extracts from patients with Malassezia associated diseases demonstrated 10–1000 fold higher AhR activating capacity than control skin extracts. LC/MS/MS analysis of the patients’ extracts revealed the presence of indirubin, 6-formylindolo[3,2-b]carbazole (FICZ), indolo[3,2-b]carbazole (ICZ), malassezin, and pityriacitrin. The same compounds were also identified in 9/12 Malassezia species culture extracts tested, connecting their presence in skin scales with this yeast. Studying the activity of the Malassezia culture-extracts and pure metabolites in HaCaT cells by Reverse Transcriptase Real-Time PCR revealed significant alterations in mRNA levels of the endogenous AhR-responsive genes Cyp1A1, Cyp1B1 and AhRR. Indirubin and FICZ activated AhR in HaCaT and human HepG2 cells with significantly higher, yet transient, potency as compared to the prototypical AhR ligand, dioxin. In loco synthesis of these highly potent AhR inducers by Malassezia yeasts could have a significant impact on skin homeostatic mechanisms and disease development. PMID:23448877

Early development of synchrony in cortical activations in the human.

PubMed

Koolen, N; Dereymaeker, A; Räsänen, O; Jansen, K; Vervisch, J; Matic, V; Naulaers, G; De Vos, M; Van Huffel, S; Vanhatalo, S

2016-05-13

Early intermittent cortical activity is thought to play a crucial role in the growth of neuronal network development, and large scale brain networks are known to provide the basis for higher brain functions. Yet, the early development of the large scale synchrony in cortical activations is unknown. Here, we tested the hypothesis that the early intermittent cortical activations seen in the human scalp EEG show a clear developmental course during the last trimester of pregnancy, the period of intensive growth of cortico-cortical connections. We recorded scalp EEG from altogether 22 premature infants at post-menstrual age between 30 and 44 weeks, and the early cortical synchrony was quantified using recently introduced activation synchrony index (ASI). The developmental correlations of ASI were computed for individual EEG signals as well as anatomically and mathematically defined spatial subgroups. We report two main findings. First, we observed a robust and statistically significant increase in ASI in all cortical areas. Second, there were significant spatial gradients in the synchrony in fronto-occipital and left-to-right directions. These findings provide evidence that early cortical activity is increasingly synchronized across the neocortex. The ASI-based metrics introduced in our work allow direct translational comparison to in vivo animal models, as well as hold promise for implementation as a functional developmental biomarker in future research on human neonates. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Directional connectivity of resting state human fMRI data using cascaded ICA-PDC analysis.

PubMed

Silfverhuth, Minna J; Remes, Jukka; Starck, Tuomo; Nikkinen, Juha; Veijola, Juha; Tervonen, Osmo; Kiviniemi, Vesa

2011-11-01

Directional connectivity measures, such as partial directed coherence (PDC), give us means to explore effective connectivity in the human brain. By utilizing independent component analysis (ICA), the original data-set reduction was performed for further PDC analysis. To test this cascaded ICA-PDC approach in causality studies of human functional magnetic resonance imaging (fMRI) data. Resting state group data was imaged from 55 subjects using a 1.5 T scanner (TR 1800 ms, 250 volumes). Temporal concatenation group ICA in a probabilistic ICA and further repeatability runs (n = 200) were overtaken. The reduced data-set included the time series presentation of the following nine ICA components: secondary somatosensory cortex, inferior temporal gyrus, intracalcarine cortex, primary auditory cortex, amygdala, putamen and the frontal medial cortex, posterior cingulate cortex and precuneus, comprising the default mode network components. Re-normalized PDC (rPDC) values were computed to determine directional connectivity at the group level at each frequency. The integrative role was suggested for precuneus while the role of major divergence region may be proposed to primary auditory cortex and amygdala. This study demonstrates the potential of the cascaded ICA-PDC approach in directional connectivity studies of human fMRI.

Issues in Estimating Program Effects and Studying Implementation in Large-Scale Educational Experiments: The Case of a Connected Classroom Technology Program

ERIC Educational Resources Information Center

Shin, Hye Sook

2009-01-01

Using data from a nationwide, large-scale experimental study of the effects of a connected classroom technology on student learning in algebra (Owens et al., 2004), this dissertation focuses on challenges that can arise in estimating treatment effects in educational field experiments when samples are highly heterogeneous in terms of various…

The Influence of Salmon Recolonization on Riparian Communities in the Cedar River, Washington, USA

NASA Astrophysics Data System (ADS)

Moravek, J.; Clipp, H.; Kiffney, P.

2016-02-01

Salmon are a valuable resource throughout the Pacific Northwest, but increasing human activity is degrading coastal ecosystems and threatening local salmon populations. Salmon conservation efforts often focus on habitat restoration, including the re-colonization of salmon into historically obstructed areas such as the Cedar River in Washington, USA. However, to assess the long term implications of salmon re-colonization on a landscape scale, it is critical to consider not only the river ecosystem but also the surrounding riparian habitat. Although prior studies suggest that salmon alter riparian food web dynamics, the riparian community on the Cedar River has not yet been characterized. To investigate possible connections between salmon and the riparian habitat after 12 years of re-colonization, we surveyed riparian spider communities along a gradient of salmon inputs (g/m2). In 10-m transects along the banks of the river, we identified spiders and spider webs, collected prey from webs, and characterized nearby aquatic macroinvertebrate communities. We found that the density of aquatic macroinvertebrates, as well as the density of spider prey, both had significant positive relationships with salmon inputs, supporting the hypothesis that salmon provide energy and nutrients for both aquatic and riparian food webs. We also found that spider diversity significantly decreased with salmon inputs, potentially due to confounding factors such as stream gradient or vegetation structure. Although additional information is needed to fully understand this relationship, the significant connection between salmon inputs and spider diversity is compelling motivation for further studies regarding the link between aquatic and riparian systems on the Cedar River. Understanding the connections between salmon and the riparian community is critical to characterizing the long term, landscape-scale implications of sustainable salmon management in the Pacific Northwest.