Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding.

PubMed

Pedersen, Mangor; Omidvarnia, Amir H; Walz, Jennifer M; Jackson, Graeme D

2015-01-01

Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications.

Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding

PubMed Central

Pedersen, Mangor; Omidvarnia, Amir H.; Walz, Jennifer M.; Jackson, Graeme D.

2015-01-01

Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications. PMID:26110111

Local and global responses in complex gene regulation networks

NASA Astrophysics Data System (ADS)

Tsuchiya, Masa; Selvarajoo, Kumar; Piras, Vincent; Tomita, Masaru; Giuliani, Alessandro

2009-04-01

An exacerbated sensitivity to apparently minor stimuli and a general resilience of the entire system stay together side-by-side in biological systems. This apparent paradox can be explained by the consideration of biological systems as very strongly interconnected network systems. Some nodes of these networks, thanks to their peculiar location in the network architecture, are responsible for the sensitivity aspects, while the large degree of interconnection is at the basis of the resilience properties of the system. One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. Here we address, on a data analysis perspective, the discrimination between local and global scale regulations, this goal was achieved by means of the examination of two biological systems: innate immune response in macrophages and oscillating growth dynamics in yeast. Our aim was to reconcile the ‘hard-wired’ local view of gene regulation with a global continuous and scalable one borrowed from statistical physics. This reconciliation is based on the network paradigm in which the local ‘hard-wired’ activities correspond to the activation of specific crucial nodes in the regulation network, while the scalable continuous responses can be equated to the collective oscillations of the network after a perturbation.

Integration Processes Compared: Cortical Differences for Consistency Evaluation and Passive Comprehension in Local and Global Coherence.

PubMed

Egidi, Giovanna; Caramazza, Alfonso

2016-10-01

This research studies the neural systems underlying two integration processes that take place during natural discourse comprehension: consistency evaluation and passive comprehension. Evaluation was operationalized with a consistency judgment task and passive comprehension with a passive listening task. Using fMRI, the experiment examined the integration of incoming sentences with more recent, local context and with more distal, global context in these two tasks. The stimuli were stories in which we manipulated the consistency of the endings with the local context and the relevance of the global context for the integration of the endings. A whole-brain analysis revealed several differences between the two tasks. Two networks previously associated with semantic processing and attention orienting showed more activation during the judgment than the passive listening task. A network previously associated with episodic memory retrieval and construction of mental scenes showed greater activity when global context was relevant, but only during the judgment task. This suggests that evaluation, more than passive listening, triggers the reinstantiation of global context and the construction of a rich mental model for the story. Finally, a network previously linked to fluent updating of a knowledge base showed greater activity for locally consistent endings than inconsistent ones, but only during passive listening, suggesting a mode of comprehension that relies on a local scope approach to language processing. Taken together, these results show that consistency evaluation and passive comprehension weigh differently on distal and local information and are implemented, in part, by different brain networks.

A generalized LSTM-like training algorithm for second-order recurrent neural networks

PubMed Central

Monner, Derek; Reggia, James A.

2011-01-01

The Long Short Term Memory (LSTM) is a second-order recurrent neural network architecture that excels at storing sequential short-term memories and retrieving them many time-steps later. LSTM’s original training algorithm provides the important properties of spatial and temporal locality, which are missing from other training approaches, at the cost of limiting it’s applicability to a small set of network architectures. Here we introduce the Generalized Long Short-Term Memory (LSTM-g) training algorithm, which provides LSTM-like locality while being applicable without modification to a much wider range of second-order network architectures. With LSTM-g, all units have an identical set of operating instructions for both activation and learning, subject only to the configuration of their local environment in the network; this is in contrast to the original LSTM training algorithm, where each type of unit has its own activation and training instructions. When applied to LSTM architectures with peephole connections, LSTM-g takes advantage of an additional source of back-propagated error which can enable better performance than the original algorithm. Enabled by the broad architectural applicability of LSTM-g, we demonstrate that training recurrent networks engineered for specific tasks can produce better results than single-layer networks. We conclude that LSTM-g has the potential to both improve the performance and broaden the applicability of spatially and temporally local gradient-based training algorithms for recurrent neural networks. PMID:21803542

Modeling cytoskeletal traffic: an interplay between passive diffusion and active transport.

PubMed

Neri, Izaak; Kern, Norbert; Parmeggiani, Andrea

2013-03-01

We introduce the totally asymmetric simple exclusion process with Langmuir kinetics on a network as a microscopic model for active motor protein transport on the cytoskeleton, immersed in the diffusive cytoplasm. We discuss how the interplay between active transport along a network and infinite diffusion in a bulk reservoir leads to a heterogeneous matter distribution on various scales: we find three regimes for steady state transport, corresponding to the scale of the network, of individual segments, or local to sites. At low exchange rates strong density heterogeneities develop between different segments in the network. In this regime one has to consider the topological complexity of the whole network to describe transport. In contrast, at moderate exchange rates the transport through the network decouples, and the physics is determined by single segments and the local topology. At last, for very high exchange rates the homogeneous Langmuir process dominates the stationary state. We introduce effective rate diagrams for the network to identify these different regimes. Based on this method we develop an intuitive but generic picture of how the stationary state of excluded volume processes on complex networks can be understood in terms of the single-segment phase diagram.

Multistability of neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing

2015-05-01

This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem and other analytical tools are used to develop certain sufficient conditions that ensure that the n-dimensional discontinuous neural networks with time-varying delays can have at least 5(n) equilibrium points, 3(n) of which are locally stable and the others are unstable. The importance of the derived results is that it reveals that the discontinuous neural networks can have greater storage capacity than the continuous ones. Moreover, different from the existing results on multistability of neural networks with discontinuous activation functions, the 3(n) locally stable equilibrium points obtained in this paper are located in not only saturated regions, but also unsaturated regions, due to the non-monotonic structure of discontinuous activation functions. A numerical simulation study is conducted to illustrate and support the derived theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Noise focusing in neuronal tissues: Symmetry breaking and localization in excitable networks with quenched disorder

NASA Astrophysics Data System (ADS)

Orlandi, Javier G.; Casademunt, Jaume

2017-05-01

We introduce a coarse-grained stochastic model for the spontaneous activity of neuronal cultures to explain the phenomenon of noise focusing, which entails localization of the noise activity in excitable networks with metric correlations. The system is modeled as a continuum excitable medium with a state-dependent spatial coupling that accounts for the dynamics of synaptic connections. The most salient feature is the emergence at the mesoscale of a vector field V (r ) , which acts as an advective carrier of the noise. This entails an explicit symmetry breaking of isotropy and homogeneity that stems from the amplification of the quenched fluctuations of the network by the activity avalanches, concomitant with the excitable dynamics. We discuss the microscopic interpretation of V (r ) and propose an explicit construction of it. The coarse-grained model shows excellent agreement with simulations at the network level. The generic nature of the observed phenomena is discussed.

A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

PubMed

Zhou, Caigen; Zeng, Xiaoqin; Luo, Chaomin; Zhang, Huaguang

In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.

Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish

PubMed Central

Teles, Magda C.; Almeida, Olinda; Lopes, João S.; Oliveira, Rui F.

2015-01-01

According to the social decision-making (SDM) network hypothesis, SDM is encoded in a network of forebrain and midbrain structures in a distributed and dynamic fashion, such that the expression of a given social behaviour is better reflected by the overall profile of activation across the different loci rather than by the activity of a single node. This proposal has the implicit assumption that SDM relies on integration across brain regions, rather than on regional specialization. Here we tested the occurrence of functional localization and of functional connectivity in the SDM network. For this purpose we used zebrafish to map different social behaviour states into patterns of neuronal activity, as indicated by the expression of the immediate early genes c-fos and egr-1, across the SDM network. The results did not support functional localization, as some loci had similar patterns of activity associated with different social behaviour states, and showed socially driven changes in functional connectivity. Thus, this study provides functional support to the SDM network hypothesis and suggests that the neural context in which a given node of the network is operating (i.e. the state of its interconnected areas) is central to its functional relevance. PMID:26423839

Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish.

PubMed

Teles, Magda C; Almeida, Olinda; Lopes, João S; Oliveira, Rui F

2015-10-07

According to the social decision-making (SDM) network hypothesis, SDM is encoded in a network of forebrain and midbrain structures in a distributed and dynamic fashion, such that the expression of a given social behaviour is better reflected by the overall profile of activation across the different loci rather than by the activity of a single node. This proposal has the implicit assumption that SDM relies on integration across brain regions, rather than on regional specialization. Here we tested the occurrence of functional localization and of functional connectivity in the SDM network. For this purpose we used zebrafish to map different social behaviour states into patterns of neuronal activity, as indicated by the expression of the immediate early genes c-fos and egr-1, across the SDM network. The results did not support functional localization, as some loci had similar patterns of activity associated with different social behaviour states, and showed socially driven changes in functional connectivity. Thus, this study provides functional support to the SDM network hypothesis and suggests that the neural context in which a given node of the network is operating (i.e. the state of its interconnected areas) is central to its functional relevance. © 2015 The Author(s).

Fiber networks amplify active stress

PubMed Central

Ronceray, Pierre; Broedersz, Chase P.

2016-01-01

Large-scale force generation is essential for biological functions such as cell motility, embryonic development, and muscle contraction. In these processes, forces generated at the molecular level by motor proteins are transmitted by disordered fiber networks, resulting in large-scale active stresses. Although these fiber networks are well characterized macroscopically, this stress generation by microscopic active units is not well understood. Here we theoretically study force transmission in these networks. We find that collective fiber buckling in the vicinity of a local active unit results in a rectification of stress towards strongly amplified isotropic contraction. This stress amplification is reinforced by the networks’ disordered nature, but saturates for high densities of active units. Our predictions are quantitatively consistent with experiments on reconstituted tissues and actomyosin networks and shed light on the role of the network microstructure in shaping active stresses in cells and tissue. PMID:26921325

The Relationship of Policymaking and Networking Characteristics among Leaders of Large Urban Health Departments.

PubMed

Leider, Jonathon P; Castrucci, Brian C; Harris, Jenine K; Hearne, Shelley

2015-08-06

The relationship between policy networks and policy development among local health departments (LHDs) is a growing area of interest to public health practitioners and researchers alike. In this study, we examine policy activity and ties between public health leadership across large urban health departments. This study uses data from a national profile of local health departments as well as responses from a survey sent to three staff members (local health official, chief of policy, chief science officer) in each of 16 urban health departments in the United States. Network questions related to frequency of contact with health department personnel in other cities. Using exponential random graph models, network density and centrality were examined, as were patterns of communication among those working on several policy areas using exponential random graph models. All 16 LHDs were active in communicating about chronic disease as well as about use of alcohol, tobacco, and other drugs (ATOD). Connectedness was highest among local health officials (density = .55), and slightly lower for chief science officers (d = .33) and chiefs of policy (d = .29). After accounting for organizational characteristics, policy homophily (i.e., when two network members match on a single characteristic) and tenure were the most significant predictors of formation of network ties. Networking across health departments has the potential for accelerating the adoption of public health policies. This study suggests similar policy interests and formation of connections among senior leadership can potentially drive greater connectedness among other staff.

The Relationship of Policymaking and Networking Characteristics among Leaders of Large Urban Health Departments

PubMed Central

Leider, Jonathon P.; Castrucci, Brian C.; Harris, Jenine K.; Hearne, Shelley

2015-01-01

Background: The relationship between policy networks and policy development among local health departments (LHDs) is a growing area of interest to public health practitioners and researchers alike. In this study, we examine policy activity and ties between public health leadership across large urban health departments. Methods: This study uses data from a national profile of local health departments as well as responses from a survey sent to three staff members (local health official, chief of policy, chief science officer) in each of 16 urban health departments in the United States. Network questions related to frequency of contact with health department personnel in other cities. Using exponential random graph models, network density and centrality were examined, as were patterns of communication among those working on several policy areas using exponential random graph models. Results: All 16 LHDs were active in communicating about chronic disease as well as about use of alcohol, tobacco, and other drugs (ATOD). Connectedness was highest among local health officials (density = .55), and slightly lower for chief science officers (d = .33) and chiefs of policy (d = .29). After accounting for organizational characteristics, policy homophily (i.e., when two network members match on a single characteristic) and tenure were the most significant predictors of formation of network ties. Conclusion: Networking across health departments has the potential for accelerating the adoption of public health policies. This study suggests similar policy interests and formation of connections among senior leadership can potentially drive greater connectedness among other staff. PMID:26258784

Activity flow over resting-state networks shapes cognitive task activations.

PubMed

Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

2016-12-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

Activity flow over resting-state networks shapes cognitive task activations

PubMed Central

Cole, Michael W.; Ito, Takuya; Bassett, Danielle S.; Schultz, Douglas H.

2016-01-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allows prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations. PMID:27723746

Multistability, local pattern formation, and global collective firing in a small-world network of nonleaky integrate-and-fire neurons.

PubMed

Rothkegel, Alexander; Lehnertz, Klaus

2009-03-01

We investigate numerically the collective dynamical behavior of pulse-coupled nonleaky integrate-and-fire neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Besides a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulentlike patterns, which-depending on network parameters-interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the spatiotemporal dynamics of biological networks.

Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease.

PubMed

Voytek, Bradley; Knight, Robert T

2015-06-15

Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this article, we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low-frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders-including Parkinson's disease, autism, depression, schizophrenia, and anxiety-are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural gray or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states or their treatment are a product of how these physical processes affect dynamic network communication. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Effective professional networking.

PubMed

Goolsby, Mary Jo; Knestrick, Joyce M

2017-08-01

The reasons for nurse practitioners to develop a professional network are boundless and are likely to change over time. Networking opens doors and creates relationships that support new opportunities, personal development, collaborative research, policy activism, evidence-based practice, and more. Successful professional networking involves shared, mutually beneficial interactions between individuals and/or individuals and groups, regardless of whether it occurs face to face or electronically. This article combines nuggets from the literature with guidance based on the authors' combined experience in networking activities at the local, national, and international levels. ©2017 American Association of Nurse Practitioners.

Self-Orientation Modulates the Neural Correlates of Global and Local Processing

PubMed Central

Liddell, Belinda J.; Das, Pritha; Battaglini, Eva; Malhi, Gin S.; Felmingham, Kim L.; Whitford, Thomas J.; Bryant, Richard A.

2015-01-01

Differences in self-orientation (or “self-construal”) may affect how the visual environment is attended, but the neural and cultural mechanisms that drive this remain unclear. Behavioral studies have demonstrated that people from Western backgrounds with predominant individualistic values are perceptually biased towards local-level information; whereas people from non-Western backgrounds that support collectivist values are preferentially focused on contextual and global-level information. In this study, we compared two groups differing in predominant individualistic (N = 15) vs collectivistic (N = 15) self-orientation. Participants completed a global/local perceptual conflict task whilst undergoing functional Magnetic Resonance Imaging (fMRI) scanning. When participants high in individualistic values attended to the global level (ignoring the local level), greater activity was observed in the frontoparietal and cingulo-opercular networks that underpin attentional control, compared to the match (congruent) baseline. Participants high in collectivistic values activated similar attentional control networks o only when directly compared with global processing. This suggests that global interference was stronger than local interference in the conflict task in the collectivistic group. Both groups showed increased activity in dorsolateral prefrontal regions involved in resolving perceptual conflict during heightened distractor interference. The findings suggest that self-orientation may play an important role in driving attention networks to facilitate interaction with the visual environment. PMID:26270820

Self-Orientation Modulates the Neural Correlates of Global and Local Processing.

PubMed

Liddell, Belinda J; Das, Pritha; Battaglini, Eva; Malhi, Gin S; Felmingham, Kim L; Whitford, Thomas J; Bryant, Richard A

2015-01-01

Differences in self-orientation (or "self-construal") may affect how the visual environment is attended, but the neural and cultural mechanisms that drive this remain unclear. Behavioral studies have demonstrated that people from Western backgrounds with predominant individualistic values are perceptually biased towards local-level information; whereas people from non-Western backgrounds that support collectivist values are preferentially focused on contextual and global-level information. In this study, we compared two groups differing in predominant individualistic (N = 15) vs collectivistic (N = 15) self-orientation. Participants completed a global/local perceptual conflict task whilst undergoing functional Magnetic Resonance Imaging (fMRI) scanning. When participants high in individualistic values attended to the global level (ignoring the local level), greater activity was observed in the frontoparietal and cingulo-opercular networks that underpin attentional control, compared to the match (congruent) baseline. Participants high in collectivistic values activated similar attentional control networks o only when directly compared with global processing. This suggests that global interference was stronger than local interference in the conflict task in the collectivistic group. Both groups showed increased activity in dorsolateral prefrontal regions involved in resolving perceptual conflict during heightened distractor interference. The findings suggest that self-orientation may play an important role in driving attention networks to facilitate interaction with the visual environment.

Making an Educational Innovation Stick: Building State Networks to Support Experience-Based Career Education.

ERIC Educational Resources Information Center

Bridgeford, Nancy; Douglas, Marcia

A study assessed the activities of five state networks that were designed to transfer experience-based career education (EBCE) ownership to appropriate state and local institutions and to develop a state-level support system for continued implementation of EBCE in local districts. Focus of the analysis was on factors contributing to EBCE entry,…

Spatial localization of the first and last enzymes effectively connects active metabolic pathways in bacteria.

PubMed

Meyer, Pablo; Cecchi, Guillermo; Stolovitzky, Gustavo

2014-12-14

Although much is understood about the enzymatic cascades that underlie cellular biosynthesis, comparatively little is known about the rules that determine their cellular organization. We performed a detailed analysis of the localization of E.coli GFP-tagged enzymes for cells growing exponentially. We found that out of 857 globular enzymes, at least 219 have a discrete punctuate localization in the cytoplasm and catalyze the first or the last reaction in 60% of biosynthetic pathways. A graph-theoretic analysis of E.coli's metabolic network shows that localized enzymes, in contrast to non-localized ones, form a tree-like hierarchical structure, have a higher within-group connectivity, and are traversed by a higher number of feed-forward and feedback loops than their non-localized counterparts. A Gene Ontology analysis of these enzymes reveals an enrichment of terms related to essential metabolic functions in growing cells. Given that these findings suggest a distinct metabolic role for localization, we studied the dynamics of cellular localization of the cell wall synthesizing enzymes in B. subtilis and found that enzymes localize during exponential growth but not during stationary growth. We conclude that active biochemical pathways inside the cytoplasm are organized spatially following a rule where their first or their last enzymes localize to effectively connect the different active pathways and thus could reflect the activity state of the cell's metabolic network.

Development of coherent neuronal activity patterns in mammalian cortical networks: common principles and local hetereogeneity.

PubMed

Egorov, Alexei V; Draguhn, Andreas

2013-01-01

Many mammals are born in a very immature state and develop their rich repertoire of behavioral and cognitive functions postnatally. This development goes in parallel with changes in the anatomical and functional organization of cortical structures which are involved in most complex activities. The emerging spatiotemporal activity patterns in multi-neuronal cortical networks may indeed form a direct neuronal correlate of systemic functions like perception, sensorimotor integration, decision making or memory formation. During recent years, several studies--mostly in rodents--have shed light on the ontogenesis of such highly organized patterns of network activity. While each local network has its own peculiar properties, some general rules can be derived. We therefore review and compare data from the developing hippocampus, neocortex and--as an intermediate region--entorhinal cortex. All cortices seem to follow a characteristic sequence starting with uncorrelated activity in uncoupled single neurons where transient activity seems to have mostly trophic effects. In rodents, before and shortly after birth, cortical networks develop weakly coordinated multineuronal discharges which have been termed synchronous plateau assemblies (SPAs). While these patterns rely mostly on electrical coupling by gap junctions, the subsequent increase in number and maturation of chemical synapses leads to the generation of large-scale coherent discharges. These patterns have been termed giant depolarizing potentials (GDPs) for predominantly GABA-induced events or early network oscillations (ENOs) for mostly glutamatergic bursts, respectively. During the third to fourth postnatal week, cortical areas reach their final activity patterns with distinct network oscillations and highly specific neuronal discharge sequences which support adult behavior. While some of the mechanisms underlying maturation of network activity have been elucidated much work remains to be done in order to fully understand the rules governing transition from immature to mature patterns of network activity. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Local Network-Level Integration Mediates Effects of Transcranial Alternating Current Stimulation.

PubMed

Fuscà, Marco; Ruhnau, Philipp; Neuling, Toralf; Weisz, Nathan

2018-05-01

Transcranial alternating current stimulation (tACS) has been proposed as a tool to draw causal inferences on the role of oscillatory activity in cognitive functioning and has the potential to induce long-term changes in cerebral networks. However, effectiveness of tACS underlies high variability and dependencies, which, as previous modeling works have suggested, may be mediated by local and network-level brain states. We used magnetoencephalography to record brain activity from 17 healthy participants at rest as they kept their eyes open (EO) or eyes closed (EC) while being stimulated with sham, weak, or strong alpha-tACS using a montage commonly assumed to target occipital areas. We reconstructed the activity of sources in all stimulation conditions by means of beamforming. The analysis of resting-state brain activity revealed an interaction of the external stimulation with the endogenous alpha power increase from EO to EC. This interaction was localized to the posterior cingulate, a region remote from occipital cortex. This suggests state-dependent (EO vs. EC) long-range effects of tACS. In a follow-up analysis of this online-tACS effect, we find evidence that this state-dependency effect is mediated by functional network changes: connection strength from the precuneus was significantly correlated with the state-dependency effect in the posterior cingulate during tACS. No analogous correlation could be found for alpha power modulations in occipital cortex. Altogether, this is the first strong evidence to illustrate how functional network architectures can shape tACS effects.

Information Transmission and Anderson Localization in two-dimensional networks of firing-rate neurons

NASA Astrophysics Data System (ADS)

Natale, Joseph; Hentschel, George

Firing-rate networks offer a coarse model of signal propagation in the brain. Here we analyze sparse, 2D planar firing-rate networks with no synapses beyond a certain cutoff distance. Additionally, we impose Dale's Principle to ensure that each neuron makes only or inhibitory outgoing connections. Using spectral methods, we find that the number of neurons participating in excitations of the network becomes insignificant whenever the connectivity cutoff is tuned to a value near or below the average interneuron separation. Further, neural activations exceeding a certain threshold stay confined to a small region of space. This behavior is an instance of Anderson localization, a disorder-induced phase transition by which an information channel is rendered unable to transmit signals. We discuss several potential implications of localization for both local and long-range computation in the brain. This work was supported in part by Grants JSMF/ 220020321 and NSF/IOS/1208126.

Networking and Microcomputers. ERIC Digest.

ERIC Educational Resources Information Center

Klausmeier, Jane

Computer networks can fall into three broad categories--local area networks (LAN), microcomputer based messaging systems (this includes computer bulletin board systems), or commercial information systems. Many of the same types of activities take place within the three categories. The major differences are the types of information available and…

An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity

PubMed Central

Whittington, James C. R.; Bogacz, Rafal

2017-01-01

To efficiently learn from feedback, cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error backpropagation algorithm. However, in this algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified, whereas the changes in biological synapses are determined only by the activity of presynaptic and postsynaptic neurons. Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning fully autonomously, employing only simple local Hebbian plasticity. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the backpropagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output. PMID:28333583

An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity.

PubMed

Whittington, James C R; Bogacz, Rafal

2017-05-01

To efficiently learn from feedback, cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error backpropagation algorithm. However, in this algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified, whereas the changes in biological synapses are determined only by the activity of presynaptic and postsynaptic neurons. Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning fully autonomously, employing only simple local Hebbian plasticity. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the backpropagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output.

Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim.

PubMed

Parasuram, Harilal; Nair, Bipin; D'Angelo, Egidio; Hines, Michael; Naldi, Giovanni; Diwakar, Shyam

2016-01-01

Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals.

Voluntary control of intracortical oscillations for reconfiguration of network activity

PubMed Central

Corlier, Juliana; Valderrama, Mario; Navarrete, Miguel; Lehongre, Katia; Hasboun, Dominique; Adam, Claude; Belaid, Hayat; Clémenceau, Stéphane; Baulac, Michel; Charpier, Stéphane; Navarro, Vincent; Le Van Quyen, Michel

2016-01-01

Voluntary control of oscillatory activity represents a key target in the self-regulation of brain function. Using a real-time closed-loop paradigm and simultaneous macro- and micro-electrode recordings, we studied the effects of self-induced intracortical oscillatory activity (4–8 Hz) in seven neurosurgical patients. Subjects learned to robustly and specifically induce oscillations in the target frequency, confirmed by increased oscillatory event density. We have found that the session-to-session variability in performance was explained by the functional long-range decoupling of the target area suggesting a training-induced network reorganization. Downstream effects on more local activities included progressive cross-frequency-coupling with gamma oscillations (30–120 Hz), and the dynamic modulation of neuronal firing rates and spike timing, indicating an improved temporal coordination of local circuits. These findings suggest that effects of voluntary control of intracortical oscillations can be exploited to specifically target plasticity processes to reconfigure network activity, with a particular relevance for memory function or skill acquisition. PMID:27808225

Fiber networks amplify active stress

NASA Astrophysics Data System (ADS)

Lenz, Martin; Ronceray, Pierre; Broedersz, Chase

Large-scale force generation is essential for biological functions such as cell motility, embryonic development, and muscle contraction. In these processes, forces generated at the molecular level by motor proteins are transmitted by disordered fiber networks, resulting in large-scale active stresses. While fiber networks are well characterized macroscopically, this stress generation by microscopic active units is not well understood. I will present a comprehensive theoretical study of force transmission in these networks. I will show that the linear, small-force response of the networks is remarkably simple, as the macroscopic active stress depends only on the geometry of the force-exerting unit. In contrast, as non-linear buckling occurs around these units, local active forces are rectified towards isotropic contraction and strongly amplified. This stress amplification is reinforced by the networks' disordered nature, but saturates for high densities of active units. I will show that our predictions are quantitatively consistent with experiments on reconstituted tissues and actomyosin networks, and that they shed light on the role of the network microstructure in shaping active stresses in cells and tissue.

Games network and application to PAs system.

PubMed

Chettaoui, C; Delaplace, F; Manceny, M; Malo, M

2007-02-01

In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.

Physical limits to biomechanical sensing in disordered fibre networks

NASA Astrophysics Data System (ADS)

Beroz, Farzan; Jawerth, Louise M.; Münster, Stefan; Weitz, David A.; Broedersz, Chase P.; Wingreen, Ned S.

2017-07-01

Cells actively probe and respond to the stiffness of their surroundings. Since mechanosensory cells in connective tissue are surrounded by a disordered network of biopolymers, their in vivo mechanical environment can be extremely heterogeneous. Here we investigate how this heterogeneity impacts mechanosensing by modelling the cell as an idealized local stiffness sensor inside a disordered fibre network. For all types of networks we study, including experimentally-imaged collagen and fibrin architectures, we find that measurements applied at different points yield a strikingly broad range of local stiffnesses, spanning roughly two decades. We verify via simulations and scaling arguments that this broad range of local stiffnesses is a generic property of disordered fibre networks. Finally, we show that to obtain optimal, reliable estimates of global tissue stiffness, a cell must adjust its size, shape, and position to integrate multiple stiffness measurements over extended regions of space.

Leadership of healthcare commissioning networks in England: a mixed-methods study on clinical commissioning groups

PubMed Central

Zachariadis, Markos; Oborn, Eivor; Barrett, Michael; Zollinger-Read, Paul

2013-01-01

Objective To explore the relational challenges for general practitioner (GP) leaders setting up new network-centric commissioning organisations in the recent health policy reform in England, we use innovation network theory to identify key network leadership practices that facilitate healthcare innovation. Design Mixed-method, multisite and case study research. Setting Six clinical commissioning groups and local clusters in the East of England area, covering in total 208 GPs and 1 662 000 population. Methods Semistructured interviews with 56 lead GPs, practice managers and staff from the local health authorities (primary care trusts, PCT) as well as various healthcare professionals; 21 observations of clinical commissioning group (CCG) board and executive meetings; electronic survey of 58 CCG board members (these included GPs, practice managers, PCT employees, nurses and patient representatives) and subsequent social network analysis. Main outcome measures Collaborative relationships between CCG board members and stakeholders from their healthcare network; clarifying the role of GPs as network leaders; strengths and areas for development of CCGs. Results Drawing upon innovation network theory provides unique insights of the CCG leaders’ activities in establishing best practices and introducing new clinical pathways. In this context we identified three network leadership roles: managing knowledge flows, managing network coherence and managing network stability. Knowledge sharing and effective collaboration among GPs enable network stability and the alignment of CCG objectives with those of the wider health system (network coherence). Even though activities varied between commissioning groups, collaborative initiatives were common. However, there was significant variation among CCGs around the level of engagement with providers, patients and local authorities. Locality (sub) groups played an important role because they linked commissioning decisions with patient needs and brought the leaders closer to frontline stakeholders. Conclusions With the new commissioning arrangements, the leaders should seek to move away from dyadic and transactional relationships to a network structure, thereby emphasising on the emerging relational focus of their roles. Managing knowledge mobility, healthcare network coherence and network stability are the three clinical leadership processes that CCG leaders need to consider in coordinating their network and facilitating the development of good clinical commissioning decisions, best practices and innovative services. To successfully manage these processes, CCG leaders need to leverage the relational capabilities of their network as well as their clinical expertise to establish appropriate collaborations that may improve the healthcare services in England. Lack of local GP engagement adds uncertainty to the system and increases the risk of commissioning decisions being irrelevant and inefficient from patient and provider perspectives. PMID:23430596

Automated Information System (AIS) Alarm System

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

Hunteman, W.

1997-05-01

The Automated Information Alarm System is a joint effort between Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratory to demonstrate and implement, on a small-to-medium sized local area network, an automated system that detects and automatically responds to attacks that use readily available tools and methodologies. The Alarm System will sense or detect, assess, and respond to suspicious activities that may be detrimental to information on the network or to continued operation of the network. The responses will allow stopping, isolating, or ejecting the suspicious activities. The number of sensors, the sensitivity of the sensors, themore » assessment criteria, and the desired responses may be set by the using organization to meet their local security policies.« less

Interactions between neurons in the frontal cortex and hippocampus in cats trained to select reinforcements of different value in conditions of cholinergic deficiency.

PubMed

Dolbakyan, E E; Merzhanova, G Kh

2007-09-01

An operant food-related conditioned reflex was developed in six cats by the "active choice" protocol: short-latency pedal presses were followed by presentation of low-quality reinforcement (bread-meat mix), while long-latency pedal presses were followed by presentation of high-quality reinforcement (meat). Animals differed in terms of their food-procuring strategies, displaying "self-control," "ambivalence," or "impulsivity." Multineuron activity was recorded from the frontal cortex and hippocampus (field CA3). Cross-correlation analysis of interneuronal interactions within (local networks) and between (distributed networks) study structures showed that the numbers of interneuronal interactions in both local and distributed networks were maximal in animals with "self-control." On the background of systemic administration of the muscarinic cholinoreceptor blockers scopolamine and trihexyphenidyl, the numbers of interneuronal interactions decreased, while "common source" influences increased. This correlated with impairment of the reproduction of the selected strategy, primarily affecting the animals' self-controlled behavior. These results show that the "self-control" strategy is determined by the organization of local and distributed networks in the frontal cortex and hippocampus.

Real-time method for establishing a detection map for a network of sensors

DOEpatents

Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

2012-09-11

A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

Parametric Loop Division for 3D Localization in Wireless Sensor Networks

PubMed Central

Ahmad, Tanveer

2017-01-01

Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m. PMID:28737714

Graph theoretical analysis of functional network for comprehension of sign language.

PubMed

Liu, Lanfang; Yan, Xin; Liu, Jin; Xia, Mingrui; Lu, Chunming; Emmorey, Karen; Chu, Mingyuan; Ding, Guosheng

2017-09-15

Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t (24) =2.379, p=0.026), small-worldness (t (24) =2.604, p=0.016) and modularity (t (24) =3.513, p=0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action. Copyright © 2017 Elsevier B.V. All rights reserved.

Recruitment of local inhibitory networks by horizontal connections in layer 2/3 of ferret visual cortex.

PubMed

Tucker, Thomas R; Katz, Lawrence C

2003-01-01

To investigate how neurons in cortical layer 2/3 integrate horizontal inputs arising from widely distributed sites, we combined intracellular recording and voltage-sensitive dye imaging to visualize the spatiotemporal dynamics of neuronal activity evoked by electrical stimulation of multiple sites in visual cortex. Individual stimuli evoked characteristic patterns of optical activity, while delivering stimuli at multiple sites generated interacting patterns in the regions of overlap. We observed that neurons in overlapping regions received convergent horizontal activation that generated nonlinear responses due to the emergence of large inhibitory potentials. The results indicate that co-activation of multiple sets of horizontal connections recruit strong inhibition from local inhibitory networks, causing marked deviations from simple linear integration.

Modulation of Olfactory Bulb Network Activity by Serotonin: Synchronous Inhibition of Mitral Cells Mediated by Spatially Localized GABAergic Microcircuits

ERIC Educational Resources Information Center

Schmidt, Loren J.; Strowbridge, Ben W.

2014-01-01

Although inhibition has often been proposed as a central mechanism for coordinating activity in the olfactory system, relatively little is known about how activation of different inhibitory local circuit pathways can generate coincident inhibition of principal cells. We used serotonin (5-HT) as a pharmacological tool to induce spiking in ensembles…

Temporal coding of reward-guided choice in the posterior parietal cortex

PubMed Central

Hawellek, David J.; Wong, Yan T.; Pesaran, Bijan

2016-01-01

Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks. PMID:27821752

Network of Black Students Hopes to Create a New Generation of Civil-Rights Leaders.

ERIC Educational Resources Information Center

Collison, Michelle N-K

1992-01-01

A network of African-American students begun at Howard University (District of Columbia) combines community service with political activism. Students working in a variety of areas urge other young African Americans to become active about local and state policies concerning utilities costs, children, and schools and to empower teenagers for…

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.

Impacts of Social Network on Therapeutic Community Participation: A Follow-up Survey of Data Gathered after Ya'an Earthquake.

PubMed

Li, Zhichao; Chen, Yao; Suo, Liming

2015-01-01

In recent years, natural disasters and the accompanying health risks have become more frequent, and rehabilitation work has become an important part of government performance. On one hand, social networks play an important role in participants' therapeutic community participation and physical & mental recovery. On the other hand, therapeutic communities with widespread participation can also contribute to community recovery after disaster. This paper described a field study in an earthquake-stricken area of Ya'an. A set of 3-stage follow-up data was obtained concerning with the villagers' participation in therapeutic community, social network status, demographic background, and other factors. The Hierarchical linear Model (HLM) method was used to investigate the determinants of social network on therapeutic community participation. First, social networks have significantly impacts on the annual changes of therapeutic community participation. Second, there were obvious differences in education between groups mobilized by the self-organization and local government. However, they all exerted the mobilization force through the acquaintance networks. Third, local cadre networks of villagers could negatively influence the activities of self-organized therapeutic community, while with positively influence in government-organized therapeutic activities. This paper suggests that relevant government departments need to focus more on the reconstruction and cultivation of villagers' social network and social capital in the process of post-disaster recovery. These findings contribute to better understandings of how social networks influence therapeutic community participation, and what role local government can play in post-disaster recovery and public health improvement after natural disasters.

Impacts of Social Network on Therapeutic Community Participation: A Follow-up Survey of Data Gathered after Ya’an Earthquake

PubMed Central

LI, Zhichao; CHEN, Yao; SUO, Liming

2015-01-01

Abstract Background In recent years, natural disasters and the accompanying health risks have become more frequent, and rehabilitation work has become an important part of government performance. On one hand, social networks play an important role in participants’ therapeutic community participation and physical & mental recovery. On the other hand, therapeutic communities with widespread participation can also contribute to community recovery after disaster. Methods This paper described a field study in an earthquake-stricken area of Ya’an. A set of 3-stage follow-up data was obtained concerning with the villagers’ participation in therapeutic community, social network status, demographic background, and other factors. The Hierarchical linear Model (HLM) method was used to investigate the determinants of social network on therapeutic community participation. Results First, social networks have significantly impacts on the annual changes of therapeutic community participation. Second, there were obvious differences in education between groups mobilized by the self-organization and local government. However, they all exerted the mobilization force through the acquaintance networks. Third, local cadre networks of villagers could negatively influence the activities of self-organized therapeutic community, while with positively influence in government-organized therapeutic activities. Conclusion This paper suggests that relevant government departments need to focus more on the reconstruction and cultivation of villagers’ social network and social capital in the process of post-disaster recovery. These findings contribute to better understandings of how social networks influence therapeutic community participation, and what role local government can play in post-disaster recovery and public health improvement after natural disasters. PMID:26060778

Telecommunications Network Plan

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

NONE

1989-05-01

The Office of Civilian Radioactive Waste Management (OCRWM) must, among other things, be equipped to readily produce, file, store, access, retrieve, and transfer a wide variety of technical and institutional data and information. The data and information regularly produced by members of the OCRWM Program supports, and will continue to support, a wide range of program activities. Some of the more important of these information communication-related activities include: supporting the preparation, submittal, and review of a license application to the Nuclear Regulatory Commission (NRC) to authorize the construction of a geologic repository; responding to requests for information from parties affectedmore » by and/or interested in the program; and providing evidence of compliance with all relevant Federal, State, local, and Indian Tribe regulations, statutes, and/or treaties. The OCRWM Telecommunications Network Plan (TNP) is intended to identify, as well as to present the current strategy for satisfying, the telecommunications requirements of the civilian radioactive waste management program. The TNP will set forth the plan for integrating OCRWM`s information resources among major program sites. Specifically, this plan will introduce a telecommunications network designed to establish communication linkages across the program`s Washington, DC; Chicago, Illinois; and Las Vegas, Nevada, sites. The linkages across these and associated sites will comprise Phase I of the proposed OCRWM telecommunications network. The second phase will focus on the modification and expansion of the Phase I network to fully accommodate access to the OCRWM Licensing Support System (LSS). The primary components of the proposed OCRWM telecommunications network include local area networks; extended local area networks; and remote extended (wide) area networks. 10 refs., 6 figs.« less

Network for Astronomy School Education

NASA Astrophysics Data System (ADS)

Deustua, Susana E.; Ros, R. M.; Garcia, B.

2014-01-01

The Network for Astronomy School Education Project (NASE) was developed in response to the IAU's most recent 10 Years Strategic Plan to increase the efforts of the IAU in schools. NASE's mission is to stimulate teaching astronomy in schools, through professional development of primary and secondary school science teachers in developing and emerging countries. NASE's organizational principle is to build capacity by providing courses for three years in cooperation with a Local Organizing Committee (Local NASE Group). The Local NASE Group consists of 6-8 local university professors and education professional who will promote astronomy activities and organize future courses in subsequent years in their region of their country. NASE philosophy is to introduce low-tech astronomy, and has thus developed an a suite of activities that can be carried out with inexpensive, quotidian materials. Supporting these activities is a text for teachers, plus a complete set of instructional materials for each topic. These materials are available in English and Spanish, with future editions available in Chinese and Portuguese. We describe and discuss NASE activities in Central and South America from 2009 to the present.

[Cognitive advantages of the third age: a neural network model of brain aging].

PubMed

Karpenko, M P; Kachalova, L M; Budilova, E V; Terekhin, A T

2009-01-01

We consider a neural network model of age-related cognitive changes in aging brain based on Hopfield network with a sigmoid function of neuron activation. Age is included in the activation function as a parameter in the form of exponential rate denominator, which makes it possible to take into account the weakening of interneuronal links really observed in the aging brain. Analysis of properties of the Lyapunov function associated with the network shows that, with increasing parameter of age, its relief becomes smoother and the number of local minima (network attractors) decreases. As a result, the network gets less frequently stuck in the nearest local minima of the Lyapunov function and reaches a global minimum corresponding to the most effective solution of the cognitive task. It is reasonable to assume that similar changes really occur in the aging brain. Phenomenologically, these changes can be manifested as emergence in aged people of a cognitive quality such as wisdom i.e. ability to find optimal decisions in difficult controversial situations, to distract from secondary aspects and to see the problem as a whole.

Monitoring unrest in a large silicic caldera, the long Valley-inyo craters volcanic complex in east-central California

NASA Astrophysics Data System (ADS)

Hill, D. P.

1984-06-01

Recent patterns of geologic unrest in long Valley caldera in east-central California emphasize that this large, silicic volcanic system and the adjacent, geologically youthful Inyo-Mono Craters volcanic chain are still active and capable of producing locally hazardous volcanic eruptions. A series of four magnitude -6 earthquakes in May 1980 called attention to this current episode of unrest, and subsequent activity has included numerous earthquake swarms in the south moat of the caldera accompanied by inflation of the resurgent dome by more than 50 cm over the last five years. The seismicity associated with this unrest is currently monitored by a network of 31 telemetered seismic stations with an automatic processing system that yelds hypocentral locations and earthquake magnitudes in near-real time. Deformation of the ground is monitored by a) a series of overlapping trilateration networks that provide coverage ranging from annual measurements of regional deformation to daily measurements of deformation local to the active, southern section of the caldera, b) a regional network of level lines surveyed annually, c) a regional network of precise gravity stations occupied annually, d) local, L-shaped level figures surveyed every few months, and e) a network of fourteen borehole tiltmeter clusters (two instruments in each cluster) and a borehole dilatometer, the telemetered signals from which provide continuous data on deformation rates. Additional telemetered data provide continuous information on fluctuations in the local magnetic field, hydrogen gas emission rates at three sites, and water level and temperatures in three wells. Continuous data on disharge rates and temperatures from hot springs and fumaroles are collected by several on-site recorders within the caldera, and samples for liquid and gas chemistry are collected several times per year from selected hot springs and fumaroles.

Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2016-12-01

In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means of the fixed point theorem, nonsmooth analysis theory and rigorous mathematical analysis, it is proven that under some conditions, such n-neuron MNNs can have 5 n equilibrium points located in ℜ n , and 3 n of them are locally μ-stable. As a direct application, some criteria are also obtained on the multiple exponential stability, multiple power stability, multiple log-stability and multiple log-log-stability. All these results reveal that the addressed neural networks with activation functions introduced in this paper can generate greater storage capacity than the ones with Mexican-hat-type activation function. Numerical simulations are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Downstream effects of hippocampal sharp wave ripple oscillations on medial entorhinal cortex layer V neurons in vitro.

PubMed

Roth, Fabian C; Beyer, Katinka M; Both, Martin; Draguhn, Andreas; Egorov, Alexei V

2016-12-01

The entorhinal cortex (EC) is a critical component of the medial temporal lobe (MTL) memory system. Local networks within the MTL express a variety of state-dependent network oscillations that are believed to organize neuronal activity during memory formation. The peculiar pattern of sharp wave-ripple complexes (SPW-R) entrains neurons by a very fast oscillation at ∼200 Hz in the hippocampal areas CA3 and CA1 and then propagates through the "output loop" into the EC. The precise mechanisms of SPW-R propagation and the resulting cellular input patterns in the mEC are, however, largely unknown. We therefore investigated the activity of layer V (LV) principal neurons of the medial EC (mEC) during SPW-R oscillations in horizontal mouse brain slices. Intracellular recordings in the mEC were combined with extracellular monitoring of propagating network activity. SPW-R in CA1 were regularly followed by negative field potential deflections in the mEC. Propagation of SPW-R activity from CA1 to the mEC was mostly monosynaptic and excitatory, such that synaptic input to mEC LV neurons directly reflected unit activity in CA1. Comparison with propagating network activity from CA3 to CA1 revealed a similar role of excitatory long-range connections for both regions. However, SPW-R-induced activity in CA1 involved strong recruitment of rhythmic synaptic inhibition and corresponding fast field oscillations, in contrast to the mEC. These differences between features of propagating SPW-R emphasize the differential processing of network activity by each local network of the hippocampal output loop. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Localizing Pain Matrix and Theory of Mind networks with both verbal and non-verbal stimuli.

PubMed

Jacoby, Nir; Bruneau, Emile; Koster-Hale, Jorie; Saxe, Rebecca

2016-02-01

Functional localizer tasks allow researchers to identify brain regions in each individual's brain, using a combination of anatomical and functional constraints. In this study, we compare three social cognitive localizer tasks, designed to efficiently identify regions in the "Pain Matrix," recruited in response to a person's physical pain, and the "Theory of Mind network," recruited in response to a person's mental states (i.e. beliefs and emotions). Participants performed three tasks: first, the verbal false-belief stories task; second, a verbal task including stories describing physical pain versus emotional suffering; and third, passively viewing a non-verbal animated movie, which included segments depicting physical pain and beliefs and emotions. All three localizers were efficient in identifying replicable, stable networks in individual subjects. The consistency across tasks makes all three tasks viable localizers. Nevertheless, there were small reliable differences in the location of the regions and the pattern of activity within regions, hinting at more specific representations. The new localizers go beyond those currently available: first, they simultaneously identify two functional networks with no additional scan time, and second, the non-verbal task extends the populations in whom functional localizers can be applied. These localizers will be made publicly available. Copyright © 2015 Elsevier Inc. All rights reserved.

Filament turnover tunes both force generation and dissipation to control long-range flows in a model actomyosin cortex

PubMed Central

McCall, Patrick M.; Gardel, Margaret L.; Munro, Edwin M.

2017-01-01

Actomyosin-based cortical flow is a fundamental engine for cellular morphogenesis. Cortical flows are generated by cross-linked networks of actin filaments and myosin motors, in which active stress produced by motor activity is opposed by passive resistance to network deformation. Continuous flow requires local remodeling through crosslink unbinding and and/or filament disassembly. But how local remodeling tunes stress production and dissipation, and how this in turn shapes long range flow, remains poorly understood. Here, we study a computational model for a cross-linked network with active motors based on minimal requirements for production and dissipation of contractile stress: Asymmetric filament compliance, spatial heterogeneity of motor activity, reversible cross-links and filament turnover. We characterize how the production and dissipation of network stress depend, individually, on cross-link dynamics and filament turnover, and how these dependencies combine to determine overall rates of cortical flow. Our analysis predicts that filament turnover is required to maintain active stress against external resistance and steady state flow in response to external stress. Steady state stress increases with filament lifetime up to a characteristic time τm, then decreases with lifetime above τm. Effective viscosity increases with filament lifetime up to a characteristic time τc, and then becomes independent of filament lifetime and sharply dependent on crosslink dynamics. These individual dependencies of active stress and effective viscosity define multiple regimes of steady state flow. In particular our model predicts that when filament lifetimes are shorter than both τc and τm, the dependencies of effective viscosity and steady state stress on filament turnover cancel one another, such that flow speed is insensitive to filament turnover, and shows a simple dependence on motor activity and crosslink dynamics. These results provide a framework for understanding how animal cells tune cortical flow through local control of network remodeling. PMID:29253848

Signal processing in local neuronal circuits based on activity-dependent noise and competition

NASA Astrophysics Data System (ADS)

Volman, Vladislav; Levine, Herbert

2009-09-01

We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For nonperiodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity) and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease in input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit.

Global and local networking for HIV/AIDS prevention: the case of the Saathii E-forum.

PubMed

Desouza, Rebecca; Jyoti Dutta, Mohan

2008-06-01

The global spread of HIV/AIDS has sparked the proliferation of civil society groups working on various aspects of the disease such as prevention, treatment, support, and policy. In this article, we explore the role of the Internet in networking civil society organizations working on HIV/AIDS-related issues across local and global spaces. Specifically, we conducted a thematic analysis of an e-forum established by the nongovernmental organization (NGO) Saathii, working on HIV/AIDS issues in India to (a) identify the specific functions served by the e-forum and (b) explore how global and local actors use the e-forum to network with one another. The thematic analysis documented four key functions of the online forum: (a) to provide HIV/AIDS-related news, (b) to serve as an informational resource, (c) to promote political activism, and (d) to express emotions. The discussion elaborates on the how global and local actors network with one another and build solidarity.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

PubMed

Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

PubMed Central

Gerstner, Wulfram

2017-01-01

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically. PMID:29173280

Neuropeptide Signaling Networks and Brain Circuit Plasticity.

PubMed

McClard, Cynthia K; Arenkiel, Benjamin R

2018-01-01

The brain is a remarkable network of circuits dedicated to sensory integration, perception, and response. The computational power of the brain is estimated to dwarf that of most modern supercomputers, but perhaps its most fascinating capability is to structurally refine itself in response to experience. In the language of computers, the brain is loaded with programs that encode when and how to alter its own hardware. This programmed "plasticity" is a critical mechanism by which the brain shapes behavior to adapt to changing environments. The expansive array of molecular commands that help execute this programming is beginning to emerge. Notably, several neuropeptide transmitters, previously best characterized for their roles in hypothalamic endocrine regulation, have increasingly been recognized for mediating activity-dependent refinement of local brain circuits. Here, we discuss recent discoveries that reveal how local signaling by corticotropin-releasing hormone reshapes mouse olfactory bulb circuits in response to activity and further explore how other local neuropeptide networks may function toward similar ends.

Multistability of second-order competitive neural networks with nondecreasing saturated activation functions.

PubMed

Nie, Xiaobing; Cao, Jinde

2011-11-01

In this paper, second-order interactions are introduced into competitive neural networks (NNs) and the multistability is discussed for second-order competitive NNs (SOCNNs) with nondecreasing saturated activation functions. Firstly, based on decomposition of state space, Cauchy convergence principle, and inequality technique, some sufficient conditions ensuring the local exponential stability of 2N equilibrium points are derived. Secondly, some conditions are obtained for ascertaining equilibrium points to be locally exponentially stable and to be located in any designated region. Thirdly, the theory is extended to more general saturated activation functions with 2r corner points and a sufficient criterion is given under which the SOCNNs can have (r+1)N locally exponentially stable equilibrium points. Even if there is no second-order interactions, the obtained results are less restrictive than those in some recent works. Finally, three examples with their simulations are presented to verify the theoretical analysis.

Analysis of fMRI data using noise-diffusion network models: a new covariance-coding perspective.

PubMed

Gilson, Matthieu

2018-04-01

Since the middle of the 1990s, studies of resting-state fMRI/BOLD data have explored the correlation patterns of activity across the whole brain, which is referred to as functional connectivity (FC). Among the many methods that have been developed to interpret FC, a recently proposed model-based approach describes the propagation of fluctuating BOLD activity within the recurrently connected brain network by inferring the effective connectivity (EC). In this model, EC quantifies the strengths of directional interactions between brain regions, viewed from the proxy of BOLD activity. In addition, the tuning procedure for the model provides estimates for the local variability (input variances) to explain how the observed FC is generated. Generalizing, the network dynamics can be studied in the context of an input-output mapping-determined by EC-for the second-order statistics of fluctuating nodal activities. The present paper focuses on the following detection paradigm: observing output covariances, how discriminative is the (estimated) network model with respect to various input covariance patterns? An application with the model fitted to experimental fMRI data-movie viewing versus resting state-illustrates that changes in local variability and changes in brain coordination go hand in hand.

Thinking Globally, Acting Locally: Using the Local Environment to Explore Global Issues.

ERIC Educational Resources Information Center

Simmons, Deborah

1994-01-01

Asserts that water pollution is a global problem and presents statistics indicating how much of the world's water is threatened. Presents three elementary school classroom activities on water quality and local water resources. Includes a figure describing the work of the Global Rivers Environmental Education Network. (CFR)

Unravelling networks in local public health policymaking in three European countries - a systems analysis.

PubMed

Spitters, Hilde P E M; Lau, Cathrine J; Sandu, Petru; Quanjel, Marcel; Dulf, Diana; Glümer, Charlotte; van Oers, Hans A M; van de Goor, Ien A M

2017-02-03

Facilitating and enhancing interaction between stakeholders involved in the policymaking process to stimulate collaboration and use of evidence, is important to foster the development of effective Health Enhancing Physical Activity (HEPA) policies. Performing an analysis of real-world policymaking processes will help reveal the complexity of a network of stakeholders. Therefore, the main objectives were to unravel the stakeholder network in the policy process by conducting three systems analyses, and to increase insight into the similarities and differences in the policy processes of these European country cases. A systems analysis of the local HEPA policymaking process was performed in three European countries involved in the 'REsearch into POlicy to enhance Physical Activity' (REPOPA) project, resulting in three schematic models showing the main stakeholders and their relationships. The models were used to compare the systems, focusing on implications with respect to collaboration and use of evidence in local HEPA policymaking. Policy documents and relevant webpages were examined and main stakeholders were interviewed. The systems analysis in each country identified the main stakeholders involved and their position and relations in the policymaking process. The Netherlands and Denmark were the most similar and both differed most from Romania, especially at the level of accountability of the local public authorities for local HEPA policymaking. The categories of driving forces underlying the relations between stakeholders were formal relations, informal interaction and knowledge exchange. A systems analysis providing detailed descriptions of positions and relations in the stakeholder network in local level HEPA policymaking is rather unique in this area. The analyses are useful when a need arises for increased interaction, collaboration and use of knowledge between stakeholders in the local HEPA network, as they provide an overview of the stakeholders involved and their mutual relations. This information can be an important starting point to enhance the uptake of evidence and build more effective public health policies.

Estimating network parameters from combined dynamics of firing rate and irregularity of single neurons.

PubMed

Hamaguchi, Kosuke; Riehle, Alexa; Brunel, Nicolas

2011-01-01

High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV(2)) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV(2) is widely distributed from quasi-regular to irregular (CV(2) = 0.3-1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV(2) neurons to move to the excitation-dominated region as well as to an increase of EPSP size.

Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

PubMed

Li, Min; Li, Wenkai; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2018-06-14

Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Localization of Epileptogenic Zone With the Correction of Pathological Networks.

PubMed

Yang, Chuanzuo; Luan, Guoming; Wang, Qian; Liu, Zhao; Zhai, Feng; Wang, Qingyun

2018-01-01

Patients with focal drug-resistant epilepsy are potential candidates for surgery. Stereo-electroencephalograph (SEEG) is often considered as the "gold standard" to identify the epileptogenic zone (EZ) that accounts for the onset and propagation of epileptiform discharges. However, visual analysis of SEEG still prevails in clinical practice. In addition, epilepsy is increasingly understood to be the result of network disorder, but the specific organization of the epileptic network is still unclear. Therefore, it is necessary to quantitatively localize the EZ and investigate the nature of epileptogenic networks. In this study, intracranial recordings from 10 patients were analyzed through adaptive directed transfer function, and the out-degree of effective network was selected as the principal indicator to localize the epileptogenic area. Furthermore, a coupled neuronal population model was used to qualitatively simulate electrical activity in the brain. By removing individual populations, virtual surgery adjusting the network organization could be performed. Results suggested that the accuracy and detection rate of the EZ localization were 82.86 and 85.29%, respectively. In addition, the same stage shared a relatively stable connectivity pattern, while the patterns changed with transition to different processes. Meanwhile, eight cases of simulations indicated that networks in the ictal stage were more likely to generate rhythmic spikes. This indicated the existence of epileptogenic networks, which could enhance local excitability and facilitate synchronization. The removal of the EZ could correct these pathological networks and reduce the amount of spikes by at least 75%. This might be one reason why accurate resection could reduce or even suppress seizures. This study provides novel insights into epilepsy and surgical treatments from the network perspective.

Bidirectional global spontaneous network activity precedes the canonical unidirectional circuit organization in the developing hippocampus.

PubMed

Shi, Yulin; Ikrar, Taruna; Olivas, Nicholas D; Xu, Xiangmin

2014-06-15

Spontaneous network activity is believed to sculpt developing neural circuits. Spontaneous giant depolarizing potentials (GDPs) were first identified with single-cell recordings from rat CA3 pyramidal neurons, but here we identify and characterize a large-scale spontaneous network activity we term global network activation (GNA) in the developing mouse hippocampal slices, which is measured macroscopically by fast voltage-sensitive dye imaging. The initiation and propagation of GNA in the mouse is largely GABA-independent and dominated by glutamatergic transmission via AMPA receptors. Despite the fact that signal propagation in the adult hippocampus is strongly unidirectional through the canonical trisynaptic circuit (dentate gyrus [DG] to CA3 to CA1), spontaneous GNA in the developing hippocampus originates in distal CA3 and propagates both forward to CA1 and backward to DG. Photostimulation-evoked GNA also shows prominent backward propagation in the developing hippocampus from CA3 to DG. Mouse GNA is strongly correlated to electrophysiological recordings of highly localized single-cell and local field potential events. Photostimulation mapping of neural circuitry demonstrates that the enhancement of local circuit connections to excitatory pyramidal neurons occurs over the same time course as GNA and reveals the underlying pathways accounting for GNA backward propagation from CA3 to DG. The disappearance of GNA coincides with a transition to the adult-like unidirectional circuit organization at about 2 weeks of age. Taken together, our findings strongly suggest a critical link between GNA activity and maturation of functional circuit connections in the developing hippocampus. Copyright © 2013 Wiley Periodicals, Inc.

Lab Streaming Layer Enabled Myo Data Collection Software User Manual

DTIC Science & Technology

2017-06-07

time - series data over a local network. LSL handles the networking, time -synchronization, (near-) real- time access as well as, optionally, the... series data collection (e.g., brain activity, heart activity, muscle activity) using the LSL application programming interface (API). Time -synchronized...saved to a single extensible data format (XDF) file. Once the time - series data are collected in a Lab Recorder XDF file, users will be able to query

Real-Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie; Oliver, Brett; Brickner, Christopher

2012-01-01

A document discusses the utilization of embedded clocks inside of operating network data links as an auxiliary clock source to satisfy local oscillator monitoring requirements. Modem network interfaces, typically serial network links, often contain embedded clocking information of very tight precision to recover data from the link. This embedded clocking data can be utilized by the receiving device to monitor the local oscillator for tolerance to required specifications, often important in high-integrity fault-tolerant applications. A device can utilize a received embedded clock to determine if the local or the remote device is out of tolerance by using a single link. The local device can determine if it is failing, assuming a single fault model, with two or more active links. Network fabric components, containing many operational links, can potentially determine faulty remote or local devices in the presence of multiple faults. Two methods of implementation are described. In one method, a recovered clock can be directly used to monitor the local clock as a direct replacement of an external local oscillator. This scheme is consistent with a general clock monitoring function whereby clock sources are clocking two counters and compared over a fixed interval of time. In another method, overflow/underflow conditions can be used to detect clock relationships for monitoring. These network interfaces often provide clock compensation circuitry to allow data to be transferred from the received (network) clock domain to the internal clock domain. This circuit could be modified to detect overflow/underflow conditions of the buffering required and report a fast or slow receive clock, respectively.

The effects of dynamical synapses on firing rate activity: a spiking neural network model.

PubMed

Khalil, Radwa; Moftah, Marie Z; Moustafa, Ahmed A

2017-11-01

Accumulating evidence relates the fine-tuning of synaptic maturation and regulation of neural network activity to several key factors, including GABA A signaling and a lateral spread length between neighboring neurons (i.e., local connectivity). Furthermore, a number of studies consider short-term synaptic plasticity (STP) as an essential element in the instant modification of synaptic efficacy in the neuronal network and in modulating responses to sustained ranges of external Poisson input frequency (IF). Nevertheless, evaluating the firing activity in response to the dynamical interaction between STP (triggered by ranges of IF) and these key parameters in vitro remains elusive. Therefore, we designed a spiking neural network (SNN) model in which we incorporated the following parameters: local density of arbor essences and a lateral spread length between neighboring neurons. We also created several network scenarios based on these key parameters. Then, we implemented two classes of STP: (1) short-term synaptic depression (STD) and (2) short-term synaptic facilitation (STF). Each class has two differential forms based on the parametric value of its synaptic time constant (either for depressing or facilitating synapses). Lastly, we compared the neural firing responses before and after the treatment with STP. We found that dynamical synapses (STP) have a critical differential role on evaluating and modulating the firing rate activity in each network scenario. Moreover, we investigated the impact of changing the balance between excitation (E) and inhibition (I) on stabilizing this firing activity. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

PubMed

Milz, Patricia; Pascual-Marqui, Roberto D; Lehmann, Dietrich; Faber, Pascal L

2016-05-01

Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the distinct electrophysiological cortical frequency-dependent networks within which they operate.

Emergence of localized patterns in globally coupled networks of relaxation oscillators with heterogeneous connectivity

NASA Astrophysics Data System (ADS)

Leiser, Randolph J.; Rotstein, Horacio G.

2017-08-01

Oscillations in far-from-equilibrium systems (e.g., chemical, biochemical, biological) are generated by the nonlinear interplay of positive and negative feedback effects operating at different time scales. Relaxation oscillations emerge when the time scales between the activators and the inhibitors are well separated. In addition to the large-amplitude oscillations (LAOs) or relaxation type, these systems exhibit small-amplitude oscillations (SAOs) as well as abrupt transitions between them (canard phenomenon). Localized cluster patterns in networks of relaxation oscillators consist of one cluster oscillating in the LAO regime or exhibiting mixed-mode oscillations (LAOs interspersed with SAOs), while the other oscillates in the SAO regime. Because the individual oscillators are monostable, localized patterns are a network phenomenon that involves the interplay of the connectivity and the intrinsic dynamic properties of the individual nodes. Motivated by experimental and theoretical results on the Belousov-Zhabotinsky reaction, we investigate the mechanisms underlying the generation of localized patterns in globally coupled networks of piecewise-linear relaxation oscillators where the global feedback term affects the rate of change of the activator (fast variable) and depends on the weighted sum of the inhibitor (slow variable) at any given time. We also investigate whether these patterns are affected by the presence of a diffusive type of coupling whose synchronizing effects compete with the symmetry-breaking global feedback effects.

Homeostatic structural plasticity can account for topology changes following deafferentation and focal stroke.

PubMed

Butz, Markus; Steenbuck, Ines D; van Ooyen, Arjen

2014-01-01

After brain lesions caused by tumors or stroke, or after lasting loss of input (deafferentation), inter- and intra-regional brain networks respond with complex changes in topology. Not only areas directly affected by the lesion but also regions remote from the lesion may alter their connectivity-a phenomenon known as diaschisis. Changes in network topology after brain lesions can lead to cognitive decline and increasing functional disability. However, the principles governing changes in network topology are poorly understood. Here, we investigated whether homeostatic structural plasticity can account for changes in network topology after deafferentation and brain lesions. Homeostatic structural plasticity postulates that neurons aim to maintain a desired level of electrical activity by deleting synapses when neuronal activity is too high and by providing new synaptic contacts when activity is too low. Using our Model of Structural Plasticity, we explored how local changes in connectivity induced by a focal loss of input affected global network topology. In accordance with experimental and clinical data, we found that after partial deafferentation, the network as a whole became more random, although it maintained its small-world topology, while deafferentated neurons increased their betweenness centrality as they rewired and returned to the homeostatic range of activity. Furthermore, deafferentated neurons increased their global but decreased their local efficiency and got longer tailed degree distributions, indicating the emergence of hub neurons. Together, our results suggest that homeostatic structural plasticity may be an important driving force for lesion-induced network reorganization and that the increase in betweenness centrality of deafferentated areas may hold as a biomarker for brain repair.

Analysis of Time-Dependent Brain Network on Active and MI Tasks for Chronic Stroke Patients

PubMed Central

Chang, Won Hyuk; Kim, Yun-Hee; Lee, Seong-Whan; Kwon, Gyu Hyun

2015-01-01

Several researchers have analyzed brain activities by investigating brain networks. However, there is a lack of the research on the temporal characteristics of the brain network during a stroke by EEG and the comparative studies between motor execution and imagery, which became known to have similar motor functions and pathways. In this study, we proposed the possibility of temporal characteristics on the brain networks of a stroke. We analyzed the temporal properties of the brain networks for nine chronic stroke patients by the active and motor imagery tasks by EEG. High beta band has a specific role in the brain network during motor tasks. In the high beta band, for the active task, there were significant characteristics of centrality and small-worldness on bilateral primary motor cortices at the initial motor execution. The degree centrality significantly increased on the contralateral primary motor cortex, and local efficiency increased on the ipsilateral primary motor cortex. These results indicate that the ipsilateral primary motor cortex constructed a powerful subnetwork by influencing the linked channels as compensatory effect, although the contralateral primary motor cortex organized an inefficient network by using the connected channels due to lesions. For the MI task, degree centrality and local efficiency significantly decreased on the somatosensory area at the initial motor imagery. Then, there were significant correlations between the properties of brain networks and motor function on the contralateral primary motor cortex and somatosensory area for each motor execution/imagery task. Our results represented that the active and MI tasks have different mechanisms of motor acts. Based on these results, we indicated the possibility of customized rehabilitation according to different motor tasks. We expect these results to help in the construction of the customized rehabilitation system depending on motor tasks by understanding temporal functional characteristics on brain network for a stroke. PMID:26656269

Theta-Modulated Gamma-Band Synchronization Among Activated Regions During a Verb Generation Task

PubMed Central

Doesburg, Sam M.; Vinette, Sarah A.; Cheung, Michael J.; Pang, Elizabeth W.

2012-01-01

Expressive language is complex and involves processing within a distributed network of cortical regions. Functional MRI and magnetoencephalography (MEG) have identified brain areas critical for expressive language, but how these regions communicate across the network remains poorly understood. It is thought that synchronization of oscillations between neural populations, particularly at a gamma rate (>30 Hz), underlies functional integration within cortical networks. Modulation of gamma rhythms by theta-band oscillations (4–8 Hz) has been proposed as a mechanism for the integration of local cell coalitions into large-scale networks underlying cognition and perception. The present study tested the hypothesis that these oscillatory mechanisms of functional integration were present within the expressive language network. We recorded MEG while subjects performed a covert verb generation task. We localized activated cortical regions using beamformer analysis, calculated inter-regional phase locking between activated areas, and measured modulation of inter-regional gamma synchronization by theta phase. The results show task-dependent gamma-band synchronization among regions activated during the performance of the verb generation task, and we provide evidence that these transient and periodic instances of high-frequency connectivity were modulated by the phase of cortical theta oscillations. These findings suggest that oscillatory synchronization and cross-frequency interactions are mechanisms for functional integration among distributed brain areas supporting expressive language processing. PMID:22707946

Mapping Epileptic Activity: Sources or Networks for the Clinicians?

PubMed Central

Pittau, Francesca; Mégevand, Pierre; Sheybani, Laurent; Abela, Eugenio; Grouiller, Frédéric; Spinelli, Laurent; Michel, Christoph M.; Seeck, Margitta; Vulliemoz, Serge

2014-01-01

Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity. PMID:25414692

Computational Account of Spontaneous Activity as a Signature of Predictive Coding

PubMed Central

Koren, Veronika

2017-01-01

Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network function. PMID:28114353

Network and neuronal membrane properties in hybrid networks reciprocally regulate selectivity to rapid thalamocortical inputs.

PubMed

Pesavento, Michael J; Pinto, David J

2012-11-01

Rapidly changing environments require rapid processing from sensory inputs. Varying deflection velocities of a rodent's primary facial vibrissa cause varying temporal neuronal activity profiles within the ventral posteromedial thalamic nucleus. Local neuron populations in a single somatosensory layer 4 barrel transform sparsely coded input into a spike count based on the input's temporal profile. We investigate this transformation by creating a barrel-like hybrid network with whole cell recordings of in vitro neurons from a cortical slice preparation, embedding the biological neuron in the simulated network by presenting virtual synaptic conductances via a conductance clamp. Utilizing the hybrid network, we examine the reciprocal network properties (local excitatory and inhibitory synaptic convergence) and neuronal membrane properties (input resistance) by altering the barrel population response to diverse thalamic input. In the presence of local network input, neurons are more selective to thalamic input timing; this arises from strong feedforward inhibition. Strongly inhibitory (damping) network regimes are more selective to timing and less selective to the magnitude of input but require stronger initial input. Input selectivity relies heavily on the different membrane properties of excitatory and inhibitory neurons. When inhibitory and excitatory neurons had identical membrane properties, the sensitivity of in vitro neurons to temporal vs. magnitude features of input was substantially reduced. Increasing the mean leak conductance of the inhibitory cells decreased the network's temporal sensitivity, whereas increasing excitatory leak conductance enhanced magnitude sensitivity. Local network synapses are essential in shaping thalamic input, and differing membrane properties of functional classes reciprocally modulate this effect.

Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme.

PubMed

Li, Dong; Pan, Zhisong; Hu, Guyu; Zhu, Zexuan; He, Shan

2017-03-14

Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response. In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance. The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.

Local communities obstruct global consensus: Naming game on multi-local-world networks

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong; Fan, Zhengping; Xiang, Luna

2018-02-01

Community structure is essential for social communications, where individuals belonging to the same community are much more actively interacting and communicating with each other than those in different communities within the human society. Naming game, on the other hand, is a social communication model that simulates the process of learning a name of an object within a community of humans, where the individuals can generally reach global consensus asymptotically through iterative pair-wise conversations. The underlying network indicates the relationships among the individuals. In this paper, three typical topologies, namely random-graph, small-world and scale-free networks, are employed, which are embedded with the multi-local-world community structure, to study the naming game. Simulations show that (1) the convergence process to global consensus is getting slower as the community structure becomes more prominent, and eventually might fail; (2) if the inter-community connections are sufficiently dense, neither the number nor the size of the communities affects the convergence process; and (3) for different topologies with the same (or similar) average node-degree, local clustering of individuals obstruct or prohibit global consensus to take place. The results reveal the role of local communities in a global naming game in social network studies.

An adaptive neural swarm approach for intrusion defense in ad hoc networks

NASA Astrophysics Data System (ADS)

Cannady, James

2011-06-01

Wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are being increasingly deployed in critical applications due to the flexibility and extensibility of the technology. While these networks possess numerous advantages over traditional wireless systems in dynamic environments they are still vulnerable to many of the same types of host-based and distributed attacks common to those systems. Unfortunately, the limited power and bandwidth available in WSNs and MANETs, combined with the dynamic connectivity that is a defining characteristic of the technology, makes it extremely difficult to utilize traditional intrusion detection techniques. This paper describes an approach to accurately and efficiently detect potentially damaging activity in WSNs and MANETs. It enables the network as a whole to recognize attacks, anomalies, and potential vulnerabilities in a distributive manner that reflects the autonomic processes of biological systems. Each component of the network recognizes activity in its local environment and then contributes to the overall situational awareness of the entire system. The approach utilizes agent-based swarm intelligence to adaptively identify potential data sources on each node and on adjacent nodes throughout the network. The swarm agents then self-organize into modular neural networks that utilize a reinforcement learning algorithm to identify relevant behavior patterns in the data without supervision. Once the modular neural networks have established interconnectivity both locally and with neighboring nodes the analysis of events within the network can be conducted collectively in real-time. The approach has been shown to be extremely effective in identifying distributed network attacks.

Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses.

PubMed

Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile

2015-02-01

Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.

The “Picardie en Forme” Network: Federating Regional Health-enhancing Sports Resources

PubMed

Weissland, Thierry; Passavant, Éric; Allal, Aziz; Amiard, Valérie; Antczak, Boris; Manzo, Julie

2016-06-08

Initiated by the Regional Olympic and Sports Committee and the Regional Directorate of Youth, Sports and Social Cohesion, the “Picardie en Forme” network has been working since 2011 in favour of adults of all ages, with chronic noncommunicable or similar diseases, to encourage a gradual return to reassuring and perennial regular physical activity,. A first step consisted of organizing a care pathway based on two principles: inform general practitioners so that they can encourage their patients to be physically active by referring them to the network, develop a range of local sports by accrediting certain clubs with sports instructors who have been trained in the management of this specific population. In 2013, 121 users entered the network at the request of 61 doctors. 48 sports instructors were trained and 20 associations obtained the Picardie en Forme label. Comparison of the results of tests performed on entry in the network and then eight months later shows a general physical reconditioning of users, increasing their motivation and perceived physical value. However, despite these encouraging results, the network has difficulty retaining users, and maintaining the involvement of general practitioners and certain local partners. This article discusses the relevance of initial approaches and describes the changes made to sustain this regional network, which, for the first time, links sport, health and users.

A Network Perspective on Dropout Prevention in Two Cities

ERIC Educational Resources Information Center

Wells, Rebecca; Gifford, Elizabeth; Bai, Yu; Corra, Ashley

2015-01-01

Purpose: This exploratory case study examines how school systems and other local organizations have been working within two major U.S. cities to improve high school graduation rates. Systematically assessing active interorganizational dropout prevention networks may reveal characteristics affecting communities' capacity to support school…

Understanding the role of contrasting urban contexts in healthy aging: an international cohort study using wearable sensor devices (the CURHA study protocol).

PubMed

Kestens, Yan; Chaix, Basile; Gerber, Philippe; Desprès, Michel; Gauvin, Lise; Klein, Olivier; Klein, Sylvain; Köppen, Bernhard; Lord, Sébastien; Naud, Alexandre; Payette, Hélène; Richard, Lucie; Rondier, Pierre; Shareck, Martine; Sueur, Cédric; Thierry, Benoit; Vallée, Julie; Wasfi, Rania

2016-05-05

Given the challenges of aging populations, calls have been issued for more sustainable urban re-development and implementation of local solutions to address global environmental and healthy aging issues. However, few studies have considered older adults' daily mobility to better understand how local built and social environments may contribute to healthy aging. Meanwhile, wearable sensors and interactive map-based applications offer novel means for gathering information on people's mobility, levels of physical activity, or social network structure. Combining such data with classical questionnaires on well-being, physical activity, perceived environments and qualitative assessment of experience of places opens new opportunities to assess the complex interplay between individuals and environments. In line with current gaps and novel analytical capabilities, this research proposes an international research agenda to collect and analyse detailed data on daily mobility, social networks and health outcomes among older adults using interactive web-based questionnaires and wearable sensors. Our study resorts to a battery of innovative data collection methods including use of a novel multisensor device for collection of location and physical activity, interactive map-based questionnaires on regular destinations and social networks, and qualitative assessment of experience of places. This rich data will allow advanced quantitative and qualitative analyses in the aim to disentangle the complex people-environment interactions linking urban local contexts to healthy aging, with a focus on active living, social networks and participation, and well-being. This project will generate evidence about what characteristics of urban environments relate to active mobility, social participation, and well-being, three important dimensions of healthy aging. It also sets the basis for an international research agenda on built environment and healthy aging based on a shared and comprehensive data collection protocol.

Dendritic Slow Dynamics Enables Localized Cortical Activity to Switch between Mobile and Immobile Modes with Noisy Background Input

PubMed Central

Kurashige, Hiroki; Câteau, Hideyuki

2011-01-01

Mounting lines of evidence suggest the significant computational ability of a single neuron empowered by active dendritic dynamics. This motivates us to study what functionality can be acquired by a network of such neurons. The present paper studies how such rich single-neuron dendritic dynamics affects the network dynamics, a question which has scarcely been specifically studied to date. We simulate neurons with active dendrites networked locally like cortical pyramidal neurons, and find that naturally arising localized activity – called a bump – can be in two distinct modes, mobile or immobile. The mode can be switched back and forth by transient input to the cortical network. Interestingly, this functionality arises only if each neuron is equipped with the observed slow dendritic dynamics and with in vivo-like noisy background input. If the bump activity is considered to indicate a point of attention in the sensory areas or to indicate a representation of memory in the storage areas of the cortex, this would imply that the flexible mode switching would be of great potential use for the brain as an information processing device. We derive these conclusions using a natural extension of the conventional field model, which is defined by combining two distinct fields, one representing the somatic population and the other representing the dendritic population. With this tool, we analyze the spatial distribution of the degree of after-spike adaptation and explain how we can understand the presence of the two distinct modes and switching between the modes. We also discuss the possible functional impact of this mode-switching ability. PMID:21931635

Is the seismicity swarm at long-dormant Jailolo volcano (Indonesia) a signature of a magmatic unrest?

NASA Astrophysics Data System (ADS)

Passarelli, Luigi; Cesca, Simone; Heryandoko, Nova; Lopez Comino, Jose Angel; Strollo, Angelo; Rivalta, Eleonora; Rohadi, Supryianto; Dahm, Torsten; Milkereit, Claus

2017-04-01

Magmatic unrest is challenging to detect when monitoring is sparse and there is little knowledge about the volcano. This is especially true for long-dormant volcanoes. Geophysical observables like seismicity, deformation, temperature and gas emission are reliable indicators of ongoing volcanic unrest caused by magma movements. Jailolo volcano is a Holocene volcano belonging to the Halmahera volcanic arc in the Northern Moluccas Islands, Indonesia. Global databases of volcanic eruptions have no records of its eruptive activity and no geological investigation has been carried out to better assess the past eruptive activity at Jailolo. It probably sits on the northern rim of an older caldera which now forms the Jailolo bay. Hydrothermal activity is intense with several hot-springs and steaming ground spots around the Jailolo volcano. In November 2015 an energetic seismic swarm started and lasted until late February 2016 with four earthquakes with M>5 recorded by global seismic networks. At the time of the swarm no close geophysical monitoring network was available around Jailolo volcano except for a broadband station at 30km distant. We installed last summer a local dense multi-parametric monitoring network with 36 seismic stations, 6 GPS and 2 gas monitoring stations around Jailolo volcano. We revised the focal mechanisms of the larger events and used single station location methods in order to exploit the little information available at the time of the swarm activity. We also combined the old sparse data with our local dense network. Migration of hypocenters and inversion of the local stress field derived by focal mechanisms analysis indicate that the Nov-Feb seismicity swarm may be related to a magmatic intrusion at shallow depth. Data from our dense network confirms ongoing micro-seismic activity underneath Jailolo volcano but there are no indications of new magma intrusion. Our findings indicate that magmatic unrest occurred at Jailolo volcano and call for a revision of the volcanic hazard.

Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

PubMed

Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

2017-04-15

Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (p<0.001) for predicting the task being performed within each scan using artifact-cleaned components. The NMF algorithms, which suppressed negative BOLD signal, had the poorest accuracy compared to the ICA and sparse coding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (p<0.001). Lower classification accuracy occurred when the extracted spatial maps contained more CSF regions (p<0.001). The success of sparse coding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

Neuron hemilineages provide the functional ground plan for the Drosophila ventral nervous system

PubMed Central

Harris, Robin M; Pfeiffer, Barret D; Rubin, Gerald M; Truman, James W

2015-01-01

Drosophila central neurons arise from neuroblasts that generate neurons in a pair-wise fashion, with the two daughters providing the basis for distinct A and B hemilineage groups. 33 postembryonically-born hemilineages contribute over 90% of the neurons in each thoracic hemisegment. We devised genetic approaches to define the anatomy of most of these hemilineages and to assessed their functional roles using the heat-sensitive channel dTRPA1. The simplest hemilineages contained local interneurons and their activation caused tonic or phasic leg movements lacking interlimb coordination. The next level was hemilineages of similar projection cells that drove intersegmentally coordinated behaviors such as walking. The highest level involved hemilineages whose activation elicited complex behaviors such as takeoff. These activation phenotypes indicate that the hemilineages vary in their behavioral roles with some contributing to local networks for sensorimotor processing and others having higher order functions of coordinating these local networks into complex behavior. DOI: http://dx.doi.org/10.7554/eLife.04493.001 PMID:26193122

Wnt6 activates endoderm in the sea urchin gene regulatory network

PubMed Central

Croce, Jenifer; Range, Ryan; Wu, Shu-Yu; Miranda, Esther; Lhomond, Guy; Peng, Jeff Chieh-fu; Lepage, Thierry; McClay, David R.

2011-01-01

In the sea urchin, entry of β-catenin into the nuclei of the vegetal cells at 4th and 5th cleavages is necessary for activation of the endomesoderm gene regulatory network. Beyond that, little is known about how the embryo uses maternal information to initiate specification. Here, experiments establish that of the three maternal Wnts in the egg, Wnt6 is necessary for activation of endodermal genes in the endomesoderm GRN. A small region of the vegetal cortex is shown to be necessary for activation of the endomesoderm GRN. If that cortical region of the egg is removed, addition of Wnt6 rescues endoderm. At a molecular level, the vegetal cortex region contains a localized concentration of Dishevelled (Dsh) protein, a transducer of the canonical Wnt pathway; however, Wnt6 mRNA is not similarly localized. Ectopic activation of the Wnt pathway, through the expression of an activated form of β-catenin, of a dominant-negative variant of GSK-3β or of Dsh itself, rescues endomesoderm specification in eggs depleted of the vegetal cortex. Knockdown experiments in whole embryos show that absence of Wnt6 produces embryos that lack endoderm, but those embryos continue to express a number of mesoderm markers. Thus, maternal Wnt6 plus a localized vegetal cortical molecule, possibly Dsh, is necessary for endoderm specification; this has been verified in two species of sea urchin. The data also show that Wnt6 is only one of what are likely to be multiple components that are necessary for activation of the entire endomesoderm gene regulatory network. PMID:21750039

Effects of Aging on Cortical Neural Dynamics and Local Sleep Homeostasis in Mice

PubMed Central

Fisher, Simon P.; Cui, Nanyi; Peirson, Stuart N.; Foster, Russell G.

2018-01-01

Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture. SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex. PMID:29581380

Effects of Aging on Cortical Neural Dynamics and Local Sleep Homeostasis in Mice.

PubMed

McKillop, Laura E; Fisher, Simon P; Cui, Nanyi; Peirson, Stuart N; Foster, Russell G; Wafford, Keith A; Vyazovskiy, Vladyslav V

2018-04-18

Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture. SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex. Copyright © 2018 McKillop et al.

Evaluation of multi-level social learning for sustainable landscapes: perspective of a development initiative in Bergslagen, Sweden.

PubMed

Axelsson, Robert; Angelstam, Per; Myhrman, Lennart; Sädbom, Stefan; Ivarsson, Milis; Elbakidze, Marine; Andersson, Kenneth; Cupa, Petr; Diry, Christian; Doyon, Frederic; Drotz, Marcus K; Hjorth, Arne; Hermansson, Jan Olof; Kullberg, Thomas; Lickers, F Henry; McTaggart, Johanna; Olsson, Anders; Pautov, Yurij; Svensson, Lennart; Törnblom, Johan

2013-03-01

To implement policies about sustainable landscapes and rural development necessitates social learning about states and trends of sustainability indicators, norms that define sustainability, and adaptive multi-level governance. We evaluate the extent to which social learning at multiple governance levels for sustainable landscapes occur in 18 local development initiatives in the network of Sustainable Bergslagen in Sweden. We mapped activities over time, and interviewed key actors in the network about social learning. While activities resulted in exchange of experiences and some local solutions, a major challenge was to secure systematic social learning and make new knowledge explicit at multiple levels. None of the development initiatives used a systematic approach to secure social learning, and sustainability assessments were not made systematically. We discuss how social learning can be improved, and how a learning network of development initiatives could be realized.

Research Activities Within the Professional Development Center Network.

ERIC Educational Resources Information Center

Abram, Marie J.; And Others

A cooperative program to improve education in the public schools involving the combined resources of the state department of education, a state university, and the local school districts is described. This Professional Development Center Network (PDC) conducts research to produce decision-making information to upgrade inservice programs in the…

More than Good Intentions: Building a Network of Collaboratives.

ERIC Educational Resources Information Center

Bailey, Adrienne, Y.

1986-01-01

College Board's national network of school-college collaborative projects to increase the number of high school students prepared to attend college is described: (1) College Board's role; (2) sample conferences on pertinent issues; (3) range of support activities provided by College Board; and (4) lessons learned about both local collaboratives…

Monitoring unrest in a large silicic caldera, the long Valley-inyo craters volcanic complex in east-central California

USGS Publications Warehouse

Hill, D.P.

1984-01-01

Recent patterns of geologic unrest in long Valley caldera in east-central California emphasize that this large, silicic volcanic system and the adjacent, geologically youthful Inyo-Mono Craters volcanic chain are still active and capable of producing locally hazardous volcanic eruptions. A series of four magnitude -6 earthquakes in May 1980 called attention to this current episode of unrest, and subsequent activity has included numerous earthquake swarms in the south moat of the caldera accompanied by inflation of the resurgent dome by more than 50 cm over the last five years. The seismicity associated with this unrest is currently monitored by a network of 31 telemetered seismic stations with an automatic processing system that yelds hypocentral locations and earthquake magnitudes in near-real time. Deformation of the ground is monitored by a) a series of overlapping trilateration networks that provide coverage ranging from annual measurements of regional deformation to daily measurements of deformation local to the active, southern section of the caldera, b) a regional network of level lines surveyed annually, c) a regional network of precise gravity stations occupied annually, d) local, L-shaped level figures surveyed every few months, and e) a network of fourteen borehole tiltmeter clusters (two instruments in each cluster) and a borehole dilatometer, the telemetered signals from which provide continuous data on deformation rates. Additional telemetered data provide continuous information on fluctuations in the local magnetic field, hydrogen gas emission rates at three sites, and water level and temperatures in three wells. Continuous data on disharge rates and temperatures from hot springs and fumaroles are collected by several on-site recorders within the caldera, and samples for liquid and gas chemistry are collected several times per year from selected hot springs and fumaroles. ?? 1984 Intern. Association of Volcanology and Chemistry of the Earth's Interior.

Deep brain stimulation mechanisms: beyond the concept of local functional inhibition.

PubMed

Deniau, Jean-Michel; Degos, Bertrand; Bosch, Clémentine; Maurice, Nicolas

2010-10-01

Deep brain electrical stimulation has become a recognized therapy in the treatment of a variety of motor disorders and has potentially promising applications in a wide range of neurological diseases including neuropsychiatry. Behavioural observation that electrical high-frequency stimulation of a given brain area induces an effect similar to a lesion suggested a mechanism of functional inhibition. In vitro and in vivo experiments as well as per operative recordings in patients have revealed a variety of effects involving local changes of neuronal excitability as well as widespread effects throughout the connected network resulting from activation of axons, including antidromic activation. Here we review current data regarding the local and network activity changes induced by high-frequency stimulation of the subthalamic nucleus and discuss this in the context of motor restoration in Parkinson's disease. Stressing the important functional consequences of axonal activation in deep brain stimulation mechanisms, we highlight the importance of developing anatomical knowledge concerning the fibre connections of the putative therapeutic targets. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Cross-coherent vector sensor processing for spatially distributed glider networks.

PubMed

Nichols, Brendan; Sabra, Karim G

2015-09-01

Autonomous underwater gliders fitted with vector sensors can be used as a spatially distributed sensor array to passively locate underwater sources. However, to date, the positional accuracy required for robust array processing (especially coherent processing) is not achievable using dead-reckoning while the gliders remain submerged. To obtain such accuracy, the gliders can be temporarily surfaced to allow for global positioning system contact, but the acoustically active sea surface introduces locally additional sensor noise. This letter demonstrates that cross-coherent array processing, which inherently mitigates the effects of local noise, outperforms traditional incoherent processing source localization methods for this spatially distributed vector sensor network.

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Nicotine increases brain functional network efficiency.

PubMed

Wylie, Korey P; Rojas, Donald C; Tanabe, Jody; Martin, Laura F; Tregellas, Jason R

2012-10-15

Despite the use of cholinergic therapies in Alzheimer's disease and the development of cholinergic strategies for schizophrenia, relatively little is known about how the system modulates the connectivity and structure of large-scale brain networks. To better understand how nicotinic cholinergic systems alter these networks, this study examined the effects of nicotine on measures of whole-brain network communication efficiency. Resting state fMRI was acquired from fifteen healthy subjects before and after the application of nicotine or placebo transdermal patches in a single blind, crossover design. Data, which were previously examined for default network activity, were analyzed with network topology techniques to measure changes in the communication efficiency of whole-brain networks. Nicotine significantly increased local efficiency, a parameter that estimates the network's tolerance to local errors in communication. Nicotine also significantly enhanced the regional efficiency of limbic and paralimbic areas of the brain, areas which are especially altered in diseases such as Alzheimer's disease and schizophrenia. These changes in network topology may be one mechanism by which cholinergic therapies improve brain function. Published by Elsevier Inc.

Neuronal avalanches and coherence potentials

NASA Astrophysics Data System (ADS)

Plenz, D.

2012-05-01

The mammalian cortex consists of a vast network of weakly interacting excitable cells called neurons. Neurons must synchronize their activities in order to trigger activity in neighboring neurons. Moreover, interactions must be carefully regulated to remain weak (but not too weak) such that cascades of active neuronal groups avoid explosive growth yet allow for activity propagation over long-distances. Such a balance is robustly realized for neuronal avalanches, which are defined as cortical activity cascades that follow precise power laws. In experiments, scale-invariant neuronal avalanche dynamics have been observed during spontaneous cortical activity in isolated preparations in vitro as well as in the ongoing cortical activity of awake animals and in humans. Theory, models, and experiments suggest that neuronal avalanches are the signature of brain function near criticality at which the cortex optimally responds to inputs and maximizes its information capacity. Importantly, avalanche dynamics allow for the emergence of a subset of avalanches, the coherence potentials. They emerge when the synchronization of a local neuronal group exceeds a local threshold, at which the system spawns replicas of the local group activity at distant network sites. The functional importance of coherence potentials will be discussed in the context of propagating structures, such as gliders in balanced cellular automata. Gliders constitute local population dynamics that replicate in space after a finite number of generations and are thought to provide cellular automata with universal computation. Avalanches and coherence potentials are proposed to constitute a modern framework of cortical synchronization dynamics that underlies brain function.

Changes in Brain Structural Networks and Cognitive Functions in Testicular Cancer Patients Receiving Cisplatin-Based Chemotherapy.

PubMed

Amidi, Ali; Hosseini, S M Hadi; Leemans, Alexander; Kesler, Shelli R; Agerbæk, Mads; Wu, Lisa M; Zachariae, Robert

2017-12-01

Cisplatin-based chemotherapy may have neurotoxic effects within the central nervous system. The aims of this study were 1) to longitudinally investigate the impact of cisplatin-based chemotherapy on whole-brain networks in testicular cancer patients undergoing treatment and 2) to explore whether possible changes are related to decline in cognitive functioning. Sixty-four newly orchiectomized TC patients underwent structural magnetic resonance imaging (T1-weighted and diffusion-weighted imaging) and cognitive testing at baseline prior to further treatment and again at a six-month follow-up. At follow-up, 22 participants had received cisplatin-based chemotherapy (CT) while 42 were in active surveillance (S). Brain structural networks were constructed for each participant, and network properties were investigated using graph theory and longitudinally compared across groups. Cognitive functioning was evaluated using standardized neuropsychological tests. All statistical tests were two-sided. Compared with the S group, the CT group demonstrated altered global and local brain network properties from baseline to follow-up as evidenced by decreases in important brain network properties such as small-worldness (P = .04), network clustering (P = .04), and local efficiency (P = .02). In the CT group, poorer overall cognitive performance was associated with decreased small-worldness (r = -0.46, P = .04) and local efficiency (r = -0.51, P = .02), and verbal fluency was associated with decreased local efficiency (r = -0.55, P = .008). Brain structural networks may be disrupted following treatment with cisplatin-based chemotherapy. Impaired brain networks may underlie poorer performance over time on both specific and nonspecific cognitive functions in patients undergoing chemotherapy. To the best of our knowledge, this is the first study to longitudinally investigate changes in structural brain networks in a cancer population, providing novel insights regarding the neurobiological mechanisms of cancer-related cognitive impairment.

Local versus global knowledge in the Barabási-Albert scale-free network model.

PubMed

Gómez-Gardeñes, Jesús; Moreno, Yamir

2004-03-01

The scale-free model of Barabási and Albert (BA) gave rise to a burst of activity in the field of complex networks. In this paper, we revisit one of the main assumptions of the model, the preferential attachment (PA) rule. We study a model in which the PA rule is applied to a neighborhood of newly created nodes and thus no global knowledge of the network is assumed. We numerically show that global properties of the BA model such as the connectivity distribution and the average shortest path length are quite robust when there is some degree of local knowledge. In contrast, other properties such as the clustering coefficient and degree-degree correlations differ and approach the values measured for real-world networks.

The devil is in the detail: brain dynamics in preparation for a global-local task.

PubMed

Leaver, Echo E; Low, Kathy A; DiVacri, Assunta; Merla, Arcangelo; Fabiani, Monica; Gratton, Gabriele

2015-08-01

When analyzing visual scenes, it is sometimes important to determine the relevant "grain" size. Attention control mechanisms may help direct our processing to the intended grain size. Here we used the event-related optical signal, a method possessing high temporal and spatial resolution, to examine the involvement of brain structures within the dorsal attention network (DAN) and the visual processing network (VPN) in preparation for the appropriate level of analysis. Behavioral data indicate that the small features of a hierarchical stimulus (local condition) are more difficult to process than the large features (global condition). Consistent with this finding, cues predicting a local trial were associated with greater DAN activation. This activity was bilateral but more pronounced in the left hemisphere, where it showed a frontal-to-parietal progression over time. Furthermore, the amount of DAN activation, especially in the left hemisphere and in parietal regions, was predictive of subsequent performance. Although local cues elicited left-lateralized DAN activity, no preponderantly right activity was observed for global cues; however, the data indicated an interaction between level of analysis (local vs. global) and hemisphere in VPN. They further showed that local processing involves structures in the ventral VPN, whereas global processing involves structures in the dorsal VPN. These results indicate that in our study preparation for analyzing different size features is an asymmetric process, in which greater preparation is required to focus on small rather than large features, perhaps because of their lesser salience. This preparation involves the same DAN used for other attention control operations.

Collaborative Monitoring and Hazard Mitigation at Fuego Volcano, Guatemala

NASA Astrophysics Data System (ADS)

Lyons, J. J.; Bluth, G. J.; Rose, W. I.; Patrick, M.; Johnson, J. B.; Stix, J.

2007-05-01

A portable, digital sensor network has been installed to closely monitor changing activity at Fuego volcano, which takes advantage of an international collaborative effort among Guatemala, U.S. and Canadian universities, and the Peace Corps. The goal of this effort is to improve the understanding shallow internal processes, and consequently to more effectively mitigate volcanic hazards. Fuego volcano has had more than 60 historical eruptions and nearly-continuous activity make it an ideal laboratory to study volcanic processes. Close monitoring is needed to identify base-line activity, and rapidly identify and disseminate changes in the activity which might threaten nearby communities. The sensor network is comprised of a miniature DOAS ultraviolet spectrometer fitted with a system for automated plume scans, a digital video camera, and two seismo-acoustic stations and portable dataloggers. These sensors are on loan from scientists who visited Fuego during short field seasons and donated use of their sensors to a resident Peace Corps Masters International student from Michigan Technological University for extended data collection. The sensor network is based around the local volcano observatory maintained by Instituto National de Sismologia, Vulcanologia, Metrologia e Hidrologia (INSIVUMEH). INSIVUMEH provides local support and historical knowledge of Fuego activity as well as a secure location for storage of scientific equipment, data processing, and charging of the batteries that power the sensors. The complete sensor network came online in mid-February 2007 and here we present preliminary results from concurrent gas, seismic, and acoustic monitoring of activity from Fuego volcano.

Test-retest reliability of fMRI-based graph theoretical properties during working memory, emotion processing, and resting state.

PubMed

Cao, Hengyi; Plichta, Michael M; Schäfer, Axel; Haddad, Leila; Grimm, Oliver; Schneider, Michael; Esslinger, Christine; Kirsch, Peter; Meyer-Lindenberg, Andreas; Tost, Heike

2014-01-01

The investigation of the brain connectome with functional magnetic resonance imaging (fMRI) and graph theory analyses has recently gained much popularity, but little is known about the robustness of these properties, in particular those derived from active fMRI tasks. Here, we studied the test-retest reliability of brain graphs calculated from 26 healthy participants with three established fMRI experiments (n-back working memory, emotional face-matching, resting state) and two parcellation schemes for node definition (AAL atlas, functional atlas proposed by Power et al.). We compared the intra-class correlation coefficients (ICCs) of five different data processing strategies and demonstrated a superior reliability of task-regression methods with condition-specific regressors. The between-task comparison revealed significantly higher ICCs for resting state relative to the active tasks, and a superiority of the n-back task relative to the face-matching task for global and local network properties. While the mean ICCs were typically lower for the active tasks, overall fair to good reliabilities were detected for global and local connectivity properties, and for the n-back task with both atlases, smallworldness. For all three tasks and atlases, low mean ICCs were seen for the local network properties. However, node-specific good reliabilities were detected for node degree in regions known to be critical for the challenged functions (resting-state: default-mode network nodes, n-back: fronto-parietal nodes, face-matching: limbic nodes). Between-atlas comparison demonstrated significantly higher reliabilities for the functional parcellations for global and local network properties. Our findings can inform the choice of processing strategies, brain atlases and outcome properties for fMRI studies using active tasks, graph theory methods, and within-subject designs, in particular future pharmaco-fMRI studies. © 2013 Elsevier Inc. All rights reserved.

Biomarkers and Stimulation Algorithms for Adaptive Brain Stimulation

PubMed Central

Hoang, Kimberly B.; Cassar, Isaac R.; Grill, Warren M.; Turner, Dennis A.

2017-01-01

The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs), and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI) changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms. PMID:29066947

Network-Cognizant Voltage Droop Control for Distribution Grids

DOE PAGES

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano; ...

2017-08-07

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

Network-Cognizant Voltage Droop Control for Distribution Grids

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

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

U.S. Tank Platoon Training for the 1987 Canadian Army Trophy (CAT) competition Using a Simulation Networking (SIMNET) System

DTIC Science & Technology

1987-10-01

will be addressed as the Testbed is constructed: 0. (1) How can a large cluster of simulators be networked at a singie " site ? [For example, a battalion... network and its subject LAN sites networked with Lt-N technology. *-" m-artter were based umDn technical and military There will be 324 simulators in all...If all sites "Cori consicerations. were active at one time, 1,400 troops would be involved- The technical assessment was that a local area network

Telemedicine as a Tool for Europe-Africa Cooperation: A Practical Experience

NASA Astrophysics Data System (ADS)

Dinis, Manuel; Santiago, Fernando; Silva, Luís; Ferreira, Ricardo; Machado, José; Castela, Eduardo

This paper presents the experience of an Europe-Africa telemedicine network, focused on the pediatric area, and involving hospitals located in Luanda (Angola), Benguela (Angola), Praia (Cape Verde) and Coimbra (Portugal). In the scope of this network, the cooperation between these hospitals goes beyond the teleconsultation sessions. Tele-training, clinical experience exchange, patient transfer agreements and health staff training to local development of new medical capabilities are some of the involved activities. It is therefore agreed that this kind of technical and knowledge network could also be expanded to other African countries with clear benefits to the local citizens, overcoming the digital-divide and improving the cooperation between developed and developing countries.

Dense fibrillar collagen is a potent inducer of invadopodia via a specific signaling network

PubMed Central

Swatkoski, Stephen; Matsumoto, Kazue; Campbell, Catherine B.; Petrie, Ryan J.; Dimitriadis, Emilios K.; Li, Xin; Mueller, Susette C.; Bugge, Thomas H.; Gucek, Marjan

2015-01-01

Cell interactions with the extracellular matrix (ECM) can regulate multiple cellular activities and the matrix itself in dynamic, bidirectional processes. One such process is local proteolytic modification of the ECM. Invadopodia of tumor cells are actin-rich proteolytic protrusions that locally degrade matrix molecules and mediate invasion. We report that a novel high-density fibrillar collagen (HDFC) matrix is a potent inducer of invadopodia, both in carcinoma cell lines and in primary human fibroblasts. In carcinoma cells, HDFC matrix induced formation of invadopodia via a specific integrin signaling pathway that did not require growth factors or even altered gene and protein expression. In contrast, phosphoproteomics identified major changes in a complex phosphosignaling network with kindlin2 serine phosphorylation as a key regulatory element. This kindlin2-dependent signal transduction network was required for efficient induction of invadopodia on dense fibrillar collagen and for local degradation of collagen. This novel phosphosignaling mechanism regulates cell surface invadopodia via kindlin2 for local proteolytic remodeling of the ECM. PMID:25646088

How Can Helpful Policy plus Helpful Professionals Produce System Failure? Exploring Development Interventions with Active Local Professionals and Active Young People with Life-Limiting Conditions

ERIC Educational Resources Information Center

Marsh, Sheila; Rodrigues, Jeff

2015-01-01

The paper reflects on the implications of selecting local multifunctional networks as a principal method of achieving improvement in the transition experience of young people with life-limiting conditions, given the range of blocking factors identified. It summarises a programme of work that aimed to tackle these blocks through developing local…

A study of the status of women in physics in Nagpur

NASA Astrophysics Data System (ADS)

Darisi, Sridevi; Ubale, Seema

2015-12-01

Networking plays an important role in ensuring that women participate equally in science and technology. In Nagpur, India, a growing city in the center of the country, a small and local network called Women in Physics in Nagpur was launched in July 2013 with about 10-15 members. A Google group of the same name was also launched. The main aim of the network was to set collective goals towards a vision for Indian women physicists. This paper reports on one of our early activities, a survey of women in Nagpur who have a physics background, and suggests future activities.

Optimal balance of the striatal medium spiny neuron network.

PubMed

Ponzi, Adam; Wickens, Jeffery R

2013-04-01

Slowly varying activity in the striatum, the main Basal Ganglia input structure, is important for the learning and execution of movement sequences. Striatal medium spiny neurons (MSNs) form cell assemblies whose population firing rates vary coherently on slow behaviourally relevant timescales. It has been shown that such activity emerges in a model of a local MSN network but only at realistic connectivities of 10 ~ 20% and only when MSN generated inhibitory post-synaptic potentials (IPSPs) are realistically sized. Here we suggest a reason for this. We investigate how MSN network generated population activity interacts with temporally varying cortical driving activity, as would occur in a behavioural task. We find that at unrealistically high connectivity a stable winners-take-all type regime is found where network activity separates into fixed stimulus dependent regularly firing and quiescent components. In this regime only a small number of population firing rate components interact with cortical stimulus variations. Around 15% connectivity a transition to a more dynamically active regime occurs where all cells constantly switch between activity and quiescence. In this low connectivity regime, MSN population components wander randomly and here too are independent of variations in cortical driving. Only in the transition regime do weak changes in cortical driving interact with many population components so that sequential cell assemblies are reproducibly activated for many hundreds of milliseconds after stimulus onset and peri-stimulus time histograms display strong stimulus and temporal specificity. We show that, remarkably, this activity is maximized at striatally realistic connectivities and IPSP sizes. Thus, we suggest the local MSN network has optimal characteristics - it is neither too stable to respond in a dynamically complex temporally extended way to cortical variations, nor is it too unstable to respond in a consistent repeatable way. Rather, it is optimized to generate stimulus dependent activity patterns for long periods after variations in cortical excitation.

Optimal Balance of the Striatal Medium Spiny Neuron Network

PubMed Central

Ponzi, Adam; Wickens, Jeffery R.

2013-01-01

Slowly varying activity in the striatum, the main Basal Ganglia input structure, is important for the learning and execution of movement sequences. Striatal medium spiny neurons (MSNs) form cell assemblies whose population firing rates vary coherently on slow behaviourally relevant timescales. It has been shown that such activity emerges in a model of a local MSN network but only at realistic connectivities of and only when MSN generated inhibitory post-synaptic potentials (IPSPs) are realistically sized. Here we suggest a reason for this. We investigate how MSN network generated population activity interacts with temporally varying cortical driving activity, as would occur in a behavioural task. We find that at unrealistically high connectivity a stable winners-take-all type regime is found where network activity separates into fixed stimulus dependent regularly firing and quiescent components. In this regime only a small number of population firing rate components interact with cortical stimulus variations. Around connectivity a transition to a more dynamically active regime occurs where all cells constantly switch between activity and quiescence. In this low connectivity regime, MSN population components wander randomly and here too are independent of variations in cortical driving. Only in the transition regime do weak changes in cortical driving interact with many population components so that sequential cell assemblies are reproducibly activated for many hundreds of milliseconds after stimulus onset and peri-stimulus time histograms display strong stimulus and temporal specificity. We show that, remarkably, this activity is maximized at striatally realistic connectivities and IPSP sizes. Thus, we suggest the local MSN network has optimal characteristics – it is neither too stable to respond in a dynamically complex temporally extended way to cortical variations, nor is it too unstable to respond in a consistent repeatable way. Rather, it is optimized to generate stimulus dependent activity patterns for long periods after variations in cortical excitation. PMID:23592954

Changes in Brain Network Efficiency and Working Memory Performance in Aging

PubMed Central

Stanley, Matthew L.; Simpson, Sean L.; Dagenbach, Dale; Lyday, Robert G.; Burdette, Jonathan H.; Laurienti, Paul J.

2015-01-01

Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory. PMID:25875001

Changes in brain network efficiency and working memory performance in aging.

PubMed

Stanley, Matthew L; Simpson, Sean L; Dagenbach, Dale; Lyday, Robert G; Burdette, Jonathan H; Laurienti, Paul J

2015-01-01

Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory.

Risk management in air protection in the Republic of Croatia.

PubMed

Peternel, Renata; Toth, Ivan; Hercog, Predrag

2014-03-01

In the Republic of Croatia, according to the Air Protection Act, air pollution assessment is obligatory on the whole State territory. For individual regions and populated areas in the State a network has been established for permanent air quality monitoring. The State network consists of stations for measuring background pollution, regional and cross-border remote transfer and measurements as part of international government liabilities, then stations for measuring air quality in areas of cultural and natural heritage, and stations for measuring air pollution in towns and industrial zones. The exceeding of alert and information threshold levels of air pollutants are related to emissions from industrial plants, and accidents. Each excess represents a threat to human health in case of short-time exposure. Monitoring of alert and information threshold levels is carried out at stations from the state and local networks for permanent air quality monitoring according to the Air Quality Measurement Program in the State network for permanent monitoring of air quality and air quality measurement programs in local networks for permanent air quality monitoring. The State network for permanent air quality monitoring has a developed automatic system for reporting on alert and information threshold levels, whereas many local networks under the competence of regional and local self-governments still lack any fully installed systems of this type. In case of accidents, prompt action at all responsibility levels is necessary in order to prevent crisis and this requires developed and coordinated competent units of State Administration as well as self-government units. It is also necessary to be continuously active in improving the implementation of legislative regulations in the field of crises related to critical and alert levels of air pollutants, especially at local levels.

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

PubMed Central

McDonnell, Mark D.; Ward, Lawrence M.

2014-01-01

Abstract Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity. PMID:24743633

Building AN International Polar Data Coordination Network

NASA Astrophysics Data System (ADS)

Pulsifer, P. L.; Yarmey, L.; Manley, W. F.; Gaylord, A. G.; Tweedie, C. E.

2013-12-01

In the spirit of the World Data Center system developed to manage data resulting from the International Geophysical Year of 1957-58, the International Polar Year 2007-2009 (IPY) resulted in significant progress towards establishing an international polar data management network. However, a sustained international network is still evolving. In this paper we argue that the fundamental building blocks for such a network exist and that the time is right to move forward. We focus on the Arctic component of such a network with linkages to Antarctic network building activities. A review of an important set of Network building blocks is presented: i) the legacy of the IPY data and information service; ii) global data management services with a polar component (e.g. World Data System); iii) regional systems (e.g. Arctic Observing Viewer; iv) nationally focused programs (e.g. Arctic Observing Viewer, Advanced Cooperative Arctic Data and Information Service, Polar Data Catalogue, Inuit Knowledge Centre); v) programs focused on the local (e.g. Exchange for Local Observations and Knowledge of the Arctic, Geomatics and Cartographic Research Centre). We discuss current activities and results with respect to three priority areas needed to establish a strong and effective Network. First, a summary of network building activities reports on a series of productive meetings, including the Arctic Observing Summit and the Polar Data Forum, that have resulted in a core set of Network nodes and participants and a refined vision for the Network. Second, we recognize that interoperability for information sharing fundamentally relies on the creation and adoption of community-based data description standards and data delivery mechanisms. There is a broad range of interoperability frameworks and specifications available; however, these need to be adapted for polar community needs. Progress towards Network interoperability is reviewed, and a prototype distributed data systems is demonstrated. We discuss remaining challenges. Lastly, to establish a sustainable Arctic Data Coordination Network (ADCN) as part of a broader polar Network will require adequate continued resources. We conclude by outlining proposed business models for the emerging Arctic Data Coordination Network and a broader polar Network.

Autapse-Induced Spiral Wave in Network of Neurons under Noise

PubMed Central

Qin, Huixin; Ma, Jun; Wang, Chunni; Wu, Ying

2014-01-01

Autapse plays an important role in regulating the electric activity of neuron by feedbacking time-delayed current on the membrane of neuron. Autapses are considered in a local area of regular network of neurons to investigate the development of spatiotemporal pattern, and emergence of spiral wave is observed while it fails to grow up and occupy the network completely. It is found that spiral wave can be induced to occupy more area in the network under optimized noise on the network with periodical or no-flux boundary condition being used. The developed spiral wave with self-sustained property can regulate the collective behaviors of neurons as a pacemaker. To detect the collective behaviors, a statistical factor of synchronization is calculated to investigate the emergence of ordered state in the network. The network keeps ordered state when self-sustained spiral wave is formed under noise and autapse in local area of network, and it independent of the selection of periodical or no-flux boundary condition. The developed stable spiral wave could be helpful for memory due to the distinct self-sustained property. PMID:24967577

Nicotine Increases Brain Functional Network Efficiency

PubMed Central

Wylie, Korey P.; Rojas, Donald C.; Tanabe, Jody; Martin, Laura F.; Tregellas, Jason R.

2012-01-01

Despite the use of cholinergic therapies in Alzheimer’s disease and the development of cholinergic strategies for schizophrenia, relatively little is known about how the system modulates the connectivity and structure of large-scale brain networks. To better understand how nicotinic cholinergic systems alter these networks, this study examined the effects of nicotine on measures of whole-brain network communication efficiency. Resting-state fMRI was acquired from fifteen healthy subjects before and after the application of nicotine or placebo transdermal patches in a single blind, crossover design. Data, which were previously examined for default network activity, were analyzed with network topology techniques to measure changes in the communication efficiency of whole-brain networks. Nicotine significantly increased local efficiency, a parameter that estimates the network’s tolerance to local errors in communication. Nicotine also significantly enhanced the regional efficiency of limbic and paralimbic areas of the brain, areas which are especially altered in diseases such as Alzheimer’s disease and schizophrenia. These changes in network topology may be one mechanism by which cholinergic therapies improve brain function. PMID:22796985

Reducing a cortical network to a Potts model yields storage capacity estimates

NASA Astrophysics Data System (ADS)

Naim, Michelangelo; Boboeva, Vezha; Kang, Chol Jun; Treves, Alessandro

2018-04-01

An autoassociative network of Potts units, coupled via tensor connections, has been proposed and analysed as an effective model of an extensive cortical network with distinct short- and long-range synaptic connections, but it has not been clarified in what sense it can be regarded as an effective model. We draw here the correspondence between the two, which indicates the need to introduce a local feedback term in the reduced model, i.e. in the Potts network. An effective model allows the study of phase transitions. As an example, we study the storage capacity of the Potts network with this additional term, the local feedback w, which contributes to drive the activity of the network towards one of the stored patterns. The storage capacity calculation, performed using replica tools, is limited to fully connected networks, for which a Hamiltonian can be defined. To extend the results to the case of intermediate partial connectivity, we also derive the self-consistent signal-to-noise analysis for the Potts network; and finally we discuss the implications for semantic memory in humans.

Autapse-induced spiral wave in network of neurons under noise.

PubMed

Qin, Huixin; Ma, Jun; Wang, Chunni; Wu, Ying

2014-01-01

Autapse plays an important role in regulating the electric activity of neuron by feedbacking time-delayed current on the membrane of neuron. Autapses are considered in a local area of regular network of neurons to investigate the development of spatiotemporal pattern, and emergence of spiral wave is observed while it fails to grow up and occupy the network completely. It is found that spiral wave can be induced to occupy more area in the network under optimized noise on the network with periodical or no-flux boundary condition being used. The developed spiral wave with self-sustained property can regulate the collective behaviors of neurons as a pacemaker. To detect the collective behaviors, a statistical factor of synchronization is calculated to investigate the emergence of ordered state in the network. The network keeps ordered state when self-sustained spiral wave is formed under noise and autapse in local area of network, and it independent of the selection of periodical or no-flux boundary condition. The developed stable spiral wave could be helpful for memory due to the distinct self-sustained property.

Learning from and Reacting to School Inspection--Two Swedish Case Narratives

ERIC Educational Resources Information Center

Segerholm, Christina; Hult, Agneta

2018-01-01

Throughout Europe, school inspection has become a visible means of governing education. This education and inspection policy is mediated, brokered, interpreted, and learned through networked activities where the global/European meet the national/local, giving national and local "uptake" a variety of characteristics. We explore the local…

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity.

PubMed

Tsai, Kuo-Ting; Hu, Chin-Kun; Li, Kuan-Wei; Hwang, Wen-Liang; Chou, Ya-Hui

2018-05-23

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.

Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking

PubMed Central

Bulea, Thomas C.; Kim, Jonghyun; Damiano, Diane L.; Stanley, Christopher J.; Park, Hyung-Soon

2015-01-01

Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training. PMID:26029077

Implementing a social network intervention designed to enhance and diversify support for people with long-term conditions. A qualitative study.

PubMed

Kennedy, Anne; Vassilev, Ivaylo; James, Elizabeth; Rogers, Anne

2016-02-29

For people with long-term conditions, social networks provide a potentially central means of mobilising, mediating and accessing support for health and well-being. Few interventions address the implementation of improving engagement with and through social networks. This paper describes the development and implementation of a web-based tool which comprises: network mapping, user-centred preference elicitation and need assessment and facilitated engagement with resources. The study aimed to determine whether the intervention was acceptable, implementable and acted to enhance support and to add to theory concerning social networks and engagement with resources and activities. A longitudinal design with 15 case studies used ethnographic methods comprising video, non-participant observation of intervention delivery and qualitative interviews (baseline, 6 and 12 months). Participants were people with type 2 diabetes living in a marginalised island community. Facilitators were local health trainers and care navigators. Analysis applied concepts concerning implementation of technology for self-management support to explain how new practices of work were operationalised and how the technology impacted on relationships fit with everyday life and allowed for visual feedback. Most participants reported identifying and taking up new activities as a result of using the tool. Thematic analysis suggested that workability of the tool was predicated on disruption and reconstruction of networks, challenging/supportive facilitation and change and reflection over time concerning network support. Visualisation of the network enabled people to mobilise support and engage in new activities. The tool aligned synergistically with the facilitators' role of linking people to local resources. The social network tool works through a process of initiating positive disruption of established self-management practice through mapping and reflection on personal network membership and support. This opens up possibilities for reconstructing self-management differently from current practice. Key facets of successful implementation were: the visual maps of networks and support options; facilitation characterised by a perceived lack of status difference which assisted engagement and constructive discussion of support and preferences for activities; and background work (a reliable database, tailored preferences, option reduction) for facilitator and user ease of use.

Understanding spatial and temporal patterning of astrocyte calcium transients via interactions between network transport and extracellular diffusion

NASA Astrophysics Data System (ADS)

Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.

2017-02-01

Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.

43 CFR 2806.43 - How does BLM calculate rent for passive reflectors and local exchange networks?

Code of Federal Regulations, 2013 CFR

2013-10-01

... MANAGEMENT (2000) RIGHTS-OF-WAY UNDER THE FEDERAL LAND POLICY MANAGEMENT ACT Rents Communication Site Rights... used to bend or ricochet electronic signals between active relay stations or between an active relay...

43 CFR 2806.43 - How does BLM calculate rent for passive reflectors and local exchange networks?

Code of Federal Regulations, 2012 CFR

2012-10-01

... MANAGEMENT (2000) RIGHTS-OF-WAY UNDER THE FEDERAL LAND POLICY MANAGEMENT ACT Rents Communication Site Rights... used to bend or ricochet electronic signals between active relay stations or between an active relay...

43 CFR 2806.43 - How does BLM calculate rent for passive reflectors and local exchange networks?

Code of Federal Regulations, 2014 CFR

2014-10-01

... MANAGEMENT (2000) RIGHTS-OF-WAY UNDER THE FEDERAL LAND POLICY MANAGEMENT ACT Rents Communication Site Rights... used to bend or ricochet electronic signals between active relay stations or between an active relay...

Synergistic effects in threshold models on networks.

PubMed

Juul, Jonas S; Porter, Mason A

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can-depending on a parameter-either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Synergistic effects in threshold models on networks

NASA Astrophysics Data System (ADS)

Juul, Jonas S.; Porter, Mason A.

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Localizing Tortoise Nests by Neural Networks.

PubMed

Barbuti, Roberto; Chessa, Stefano; Micheli, Alessio; Pucci, Rita

2016-01-01

The goal of this research is to recognize the nest digging activity of tortoises using a device mounted atop the tortoise carapace. The device classifies tortoise movements in order to discriminate between nest digging, and non-digging activity (specifically walking and eating). Accelerometer data was collected from devices attached to the carapace of a number of tortoises during their two-month nesting period. Our system uses an accelerometer and an activity recognition system (ARS) which is modularly structured using an artificial neural network and an output filter. For the purpose of experiment and comparison, and with the aim of minimizing the computational cost, the artificial neural network has been modelled according to three different architectures based on the input delay neural network (IDNN). We show that the ARS can achieve very high accuracy on segments of data sequences, with an extremely small neural network that can be embedded in programmable low power devices. Given that digging is typically a long activity (up to two hours), the application of ARS on data segments can be repeated over time to set up a reliable and efficient system, called Tortoise@, for digging activity recognition.

Stimulus-dependent spiking relationships with the EEG

PubMed Central

Snyder, Adam C.

2015-01-01

The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954

Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

PubMed Central

Bettinardi, Ruggero G.; Tort-Colet, Núria; Ruiz-Mejias, Marcel; Sanchez-Vives, Maria V.; Deco, Gustavo

2015-01-01

Intrinsic brain activity is characterized by the presence of highly structured networks of correlated fluctuations between different regions of the brain. Such networks encompass different functions, whose properties are known to be modulated by the ongoing global brain state and are altered in several neurobiological disorders. In the present study, we induced a deep state of anesthesia in rats by means of a ketamine/medetomidine peritoneal injection, and analyzed the time course of the correlation between the brain activity in different areas while anesthesia spontaneously decreased over time. We compared results separately obtained from fMRI and local field potentials (LFPs) under the same anesthesia protocol, finding that while most profound phases of anesthesia can be described by overall sparse connectivity, stereotypical activity and poor functional integration, during lighter states different frequency-specific functional networks emerge, endowing the gradual restoration of structured large-scale activity seen during rest. Noteworthy, our in vivo results show that those areas belonging to the same functional network (the default-mode) exhibited sustained correlated oscillations around 10 Hz throughout the protocol, suggesting the presence of a specific functional backbone that is preserved even during deeper phases of anesthesia. Finally, the overall pattern of results obtained from both imaging and in vivo-recordings suggests that the progressive emergence from deep anesthesia is reflected by a corresponding gradual increase of organized correlated oscillations across the cortex. PMID:25804643

The Use of Meta-Level Control for Coordination in a Distributed Problem Solving Network,

DTIC Science & Technology

1983-01-01

crucial aspect of the design organizational structuring in coordinating the local activity of achs decentralized network control policies. It is...TEMTED EXflD.MENTS WITn and ratings of the subgoals." Threshold values indicating ORGANIZATIONAL STRUCIURING IkeA usaw lani of a subal are specif’ied in...the monitoring are. This environmental vehicle, approximate position, time frame, and belief. The scenario was designed to test the networks ability

The Canadian Immunization Monitoring Program, ACTive (IMPACT): Active surveillance for vaccine adverse events and vaccine-preventable diseases

PubMed Central

Bettinger, JA; Halperin, SA; Vaudry, W; Law, BJ; Scheifele, DW

2014-01-01

For almost 25 years the Canadian Immunization Monitoring Program, ACTive (IMPACT) has been conducting active surveillance for severe adverse events following immunization (AEFIs) and vaccine-preventable diseases in children. The network, which consists of volunteer paediatric infectious diseases investigators at 12 tertiary care paediatric hospitals, is an important component of Canada’s AEFI monitoring. The network employs nurses at each of the sites to search for and report possible AEFIs to local, provincial and national public health authorities. The active nature of the surveillance ensures a high level of vigilance for severe AEFIs in children. PMID:29769912

Dissecting local circuits in vivo: integrated optogenetic and electrophysiology approaches for exploring inhibitory regulation of cortical activity.

PubMed

Cardin, Jessica A

2012-01-01

Local cortical circuit activity in vivo comprises a complex and flexible series of interactions between excitatory and inhibitory neurons. Our understanding of the functional interactions between these different neural populations has been limited by the difficulty of identifying and selectively manipulating the diverse and sparsely represented inhibitory interneuron classes in the intact brain. The integration of recently developed optical tools with traditional electrophysiological techniques provides a powerful window into the role of inhibition in regulating the activity of excitatory neurons. In particular, optogenetic targeting of specific cell classes reveals the distinct impacts of local inhibitory populations on other neurons in the surrounding local network. In addition to providing the ability to activate or suppress spiking in target cells, optogenetic activation identifies extracellularly recorded neurons by class, even when naturally occurring spike rates are extremely low. However, there are several important limitations on the use of these tools and the interpretation of resulting data. The purpose of this article is to outline the uses and limitations of optogenetic tools, along with current methods for achieving cell type-specific expression, and to highlight the advantages of an experimental approach combining optogenetics and electrophysiology to explore the role of inhibition in active networks. To illustrate the efficacy of these combined approaches, I present data comparing targeted manipulations of cortical fast-spiking, parvalbumin-expressing and low threshold-spiking, somatostatin-expressing interneurons in vivo. Copyright © 2011 Elsevier Ltd. All rights reserved.

Network analysis reveals strongly localized impacts of El Niño

NASA Astrophysics Data System (ADS)

Fan, Jingfang; Meng, Jun; Ashkenazy, Yosef; Havlin, Shlomo; Schellnhuber, Hans Joachim

2017-07-01

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, we construct directed and weighted climate networks based on near-surface air temperature to investigate the global impacts of El Niño and La Niña. We find that regions that are characterized by higher positive/negative network “in”-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger in-weighted activities are found to be concentrated in very localized areas, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Niño (La Niña) event to another; still, some El Niño (La Niña) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Niño/La Niña events and also may be applied in the investigation of other climate variables.

Network analysis reveals strongly localized impacts of El Niño.

PubMed

Fan, Jingfang; Meng, Jun; Ashkenazy, Yosef; Havlin, Shlomo; Schellnhuber, Hans Joachim

2017-07-18

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, we construct directed and weighted climate networks based on near-surface air temperature to investigate the global impacts of El Niño and La Niña. We find that regions that are characterized by higher positive/negative network "in"-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger in-weighted activities are found to be concentrated in very localized areas, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Niño (La Niña) event to another; still, some El Niño (La Niña) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Niño/La Niña events and also may be applied in the investigation of other climate variables.

Using the virtual brain to reveal the role of oscillations and plasticity in shaping brain's dynamical landscape.

PubMed

Roy, Dipanjan; Sigala, Rodrigo; Breakspear, Michael; McIntosh, Anthony Randal; Jirsa, Viktor K; Deco, Gustavo; Ritter, Petra

2014-12-01

Spontaneous brain activity, that is, activity in the absence of controlled stimulus input or an explicit active task, is topologically organized in multiple functional networks (FNs) maintaining a high degree of coherence. These "resting state networks" are constrained by the underlying anatomical connectivity between brain areas. They are also influenced by the history of task-related activation. The precise rules that link plastic changes and ongoing dynamics of resting-state functional connectivity (rs-FC) remain unclear. Using the framework of the open source neuroinformatics platform "The Virtual Brain," we identify potential computational mechanisms that alter the dynamical landscape, leading to reconfigurations of FNs. Using a spiking neuron model, we first demonstrate that network activity in the absence of plasticity is characterized by irregular oscillations between low-amplitude asynchronous states and high-amplitude synchronous states. We then demonstrate the capability of spike-timing-dependent plasticity (STDP) combined with intrinsic alpha (8-12 Hz) oscillations to efficiently influence learning. Further, we show how alpha-state-dependent STDP alters the local area dynamics from an irregular to a highly periodic alpha-like state. This is an important finding, as the cortical input from the thalamus is at the rate of alpha. We demonstrate how resulting rhythmic cortical output in this frequency range acts as a neuronal tuner and, hence, leads to synchronization or de-synchronization between brain areas. Finally, we demonstrate that locally restricted structural connectivity changes influence local as well as global dynamics and lead to altered rs-FC.

Networking activities and perceptions of HIV risk among male migrant market vendors in China.

PubMed

Wang, Wenqing; Muessig, Kathryn E; Li, Mingqiang; Zhang, Ying-Xia; Zhang, Yingxia

2014-02-01

HIV research among internal migrants in China has not fully explored the contexts and perceptions of "risk". In 2011, urban markets in Liuzhou, China were mapped, and sixty male vendors, age 22-56, were selected for in-depth interviews on migration, social and family life, and perceptions and practices of sexual risk behavior. Participants were evenly divided among higher income shop and small stall vendors. All men were sexually active. Only the shop vendors reported non-marital sexual partners, including concurrent partners (n = 15), commercial partners (n = 10), and other sexual relationships (n = 11). Shop vendors engaged in networking activities that facilitated commercial and non-commercial high-risk sex. Perceptions of HIV risk from commercial sex led some men to doubt the protective ability of condoms and rely on local (unproven) self-protection techniques. Networking activities played a role in high-risk sex and shaping migrants' risk perceptions and health practices. The networks created through these processes could also be used to facilitate health promotion activities.

Expanding Local Cancer Clinical Trial Options: Analysis of the Economic Impact of the Midwest Cancer Alliance in Kansas.

PubMed

Gafford, J Atlee; Gurley-Calvez, Tami; Krebill, Hope; Lai, Sue Min; Christiadi; Doolittle, Gary C

2017-09-01

Patients benefit from receiving cancer treatment closer to home when possible and at high-volume regional centers when specialized care is required. The purpose of this analysis was to estimate the economic impact of retaining more patients in-state for cancer clinical trials and care, which might offset some of the costs of establishing broader cancer trial and treatment networks. Kansas Cancer Registry data were used to estimate the number of patients retained in-state for cancer care following the expansion of local cancer clinical trial options through the Midwest Cancer Alliance based at the University of Kansas Medical Center. The 2014 economic impact of this enhanced local clinical trial network was estimated in four parts: Medical spending was estimated on the basis of National Cancer Institute cost-of-care estimates. Household travel cost savings were estimated as the difference between in-state and out-of-state travel costs. Trial-related grant income was calculated from administrative records. Indirect and induced economic benefits to the state were estimated using an economic impact model. The authors estimated that the enhanced local cancer clinical trial network resulted in approximately $6.9 million in additional economic activity in the state in 2014, or $362,000 per patient retained in-state. This estimate includes $3.6 million in direct spending and $3.3 million in indirect economic activity. The enhanced trial network also resulted in 45 additional jobs. Retaining patients in-state for cancer care and clinical trial participation allows patients to remain closer to home for care and enhances the state economy.

An Investigation of the Differences and Similarities between Generated Small-World Networks for Right- and Left-Hand Motor Imageries.

PubMed

Zhang, Jiang; Li, Yuyao; Chen, Huafu; Ding, Jurong; Yuan, Zhen

2016-11-04

In this study, small-world network analysis was performed to identify the similarities and differences between functional brain networks for right- and left-hand motor imageries (MIs). First, Pearson correlation coefficients among the nodes within the functional brain networks from healthy subjects were calculated. Then, small-world network indicators, including the clustering coefficient, the average path length, the global efficiency, the local efficiency, the average node degree, and the small-world index, were generated for the functional brain networks during both right- and left-hand MIs. We identified large differences in the small-world network indicators between the functional networks during MI and in the random networks. More importantly, the functional brain networks underlying the right- and left-hand MIs exhibited similar small-world properties in terms of the clustering coefficient, the average path length, the global efficiency, and the local efficiency. By contrast, the right- and left-hand MI brain networks showed differences in small-world characteristics, including indicators such as the average node degree and the small-world index. Interestingly, our findings also suggested that the differences in the activity intensity and range, the average node degree, and the small-world index of brain networks between the right- and left-hand MIs were associated with the asymmetry of brain functions.

Dynamics of alpha control: Preparatory suppression of posterior alpha oscillations by frontal modulators revealed with combined EEG and event-related optical signal (EROS)

PubMed Central

Mathewson, Kyle E.; Beck, Diane M.; Ro, Tony; Maclin, Edward L.; Low, Kathy A.; Fabiani, Monica; Gratton, Gabriele

2015-01-01

We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously we proposed that alpha (8-12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top-down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently-recorded electroencephalogram (EEG), while subjects performed a visual target-detection task. The pre-target alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha's inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across subjects. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network, and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks prior to posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top-down control from attention networks modulates both posterior alpha and awareness of visual stimuli. PMID:24702458

Active matter logic for autonomous microfluidics

NASA Astrophysics Data System (ADS)

Woodhouse, Francis G.; Dunkel, Jörn

2017-04-01

Chemically or optically powered active matter plays an increasingly important role in materials design, but its computational potential has yet to be explored systematically. The competition between energy consumption and dissipation imposes stringent physical constraints on the information transport in active flow networks, facilitating global optimization strategies that are not well understood. Here, we combine insights from recent microbial experiments with concepts from lattice-field theory and non-equilibrium statistical mechanics to introduce a generic theoretical framework for active matter logic. Highlighting conceptual differences with classical and quantum computation, we demonstrate how the inherent non-locality of incompressible active flow networks can be utilized to construct universal logical operations, Fredkin gates and memory storage in set-reset latches through the synchronized self-organization of many individual network components. Our work lays the conceptual foundation for developing autonomous microfluidic transport devices driven by bacterial fluids, active liquid crystals or chemically engineered motile colloids.

Networks and landscapes: a framework for setting goals and evaluating performance at the large landscape scale

Treesearch

R Patrick Bixler; Shawn Johnson; Kirk Emerson; Tina Nabatchi; Melly Reuling; Charles Curtin; Michele Romolini; Morgan Grove

2016-01-01

The objective of large landscape conser vation is to mitigate complex ecological problems through interventions at multiple and overlapping scales. Implementation requires coordination among a diverse network of individuals and organizations to integrate local-scale conservation activities with broad-scale goals. This requires an understanding of the governance options...

System data communication structures for active-control transport aircraft, volume 1

NASA Technical Reports Server (NTRS)

Hopkins, A. L.; Martin, J. H.; Brock, L. D.; Jansson, D. G.; Serben, S.; Smith, T. B.; Hanley, L. D.

1981-01-01

Candidate data communication techniques are identified, including dedicated links, local buses, broadcast buses, multiplex buses, and mesh networks. The design methodology for mesh networks is then discussed, including network topology and node architecture. Several concepts of power distribution are reviewed, including current limiting and mesh networks for power. The technology issues of packaging, transmission media, and lightning are addressed, and, finally, the analysis tools developed to aid in the communication design process are described. There are special tools to analyze the reliability and connectivity of networks and more general reliability analysis tools for all types of systems.

Attentional performance is correlated with the local regional efficiency of intrinsic brain networks.

PubMed

Xu, Junhai; Yin, Xuntao; Ge, Haitao; Han, Yan; Pang, Zengchang; Tang, Yuchun; Liu, Baolin; Liu, Shuwei

2015-01-01

Attention is a crucial brain function for human beings. Using neuropsychological paradigms and task-based functional brain imaging, previous studies have indicated that widely distributed brain regions are engaged in three distinct attention subsystems: alerting, orienting and executive control (EC). Here, we explored the potential contribution of spontaneous brain activity to attention by examining whether resting-state activity could account for individual differences of the attentional performance in normal individuals. The resting-state functional images and behavioral data from attention network test (ANT) task were collected in 59 healthy subjects. Graph analysis was conducted to obtain the characteristics of functional brain networks and linear regression analyses were used to explore their relationships with behavioral performances of the three attentional components. We found that there was no significant relationship between the attentional performance and the global measures, while the attentional performance was associated with specific local regional efficiency. These regions related to the scores of alerting, orienting and EC largely overlapped with the regions activated in previous task-related functional imaging studies, and were consistent with the intrinsic dorsal and ventral attention networks (DAN/VAN). In addition, the strong associations between the attentional performance and specific regional efficiency suggested that there was a possible relationship between the DAN/VAN and task performances in the ANT. We concluded that the intrinsic activity of the human brain could reflect the processing efficiency of the attention system. Our findings revealed a robust evidence for the functional significance of the efficiently organized intrinsic brain network for highly productive cognitions and the hypothesized role of the DAN/VAN at rest.

IAU Public Astronomical Organisations Network

NASA Astrophysics Data System (ADS)

Canas, Lina; Cheung, Sze Leung

2015-08-01

The Office for Astronomy Outreach has devoted intensive means to create and support a global network of public astronomical organisations around the world. Focused on bringing established and newly formed amateur astronomy organizations together, providing communications channels and platforms for disseminating news to the global community and the sharing of best practices and resources among these associations around the world. In establishing the importance that these organizations have for the dissemination of activities globally and acting as key participants in IAU various campaigns social media has played a key role in keeping this network engaged and connected. Here we discuss the implementation process of maintaining this extensive network, the processing and gathering of information and the interactions between local active members at a national and international level.

Iconic memory and parietofrontal network: fMRI study using temporal integration.

PubMed

Saneyoshi, Ayako; Niimi, Ryosuke; Suetsugu, Tomoko; Kaminaga, Tatsuro; Yokosawa, Kazuhiko

2011-08-03

We investigated the neural basis of iconic memory using functional magnetic resonance imaging. The parietofrontal network of selective attention is reportedly relevant to readout from iconic memory. We adopted a temporal integration task that requires iconic memory but not selective attention. The results showed that the task activated the parietofrontal network, confirming that the network is involved in readout from iconic memory. We further tested a condition in which temporal integration was performed by visual short-term memory but not by iconic memory. However, no brain region revealed higher activation for temporal integration by iconic memory than for temporal integration by visual short-term memory. This result suggested that there is no localized brain region specialized for iconic memory per se.

Complete stability of delayed recurrent neural networks with Gaussian activation functions.

PubMed

Liu, Peng; Zeng, Zhigang; Wang, Jun

2017-01-01

This paper addresses the complete stability of delayed recurrent neural networks with Gaussian activation functions. By means of the geometrical properties of Gaussian function and algebraic properties of nonsingular M-matrix, some sufficient conditions are obtained to ensure that for an n-neuron neural network, there are exactly 3 k equilibrium points with 0≤k≤n, among which 2 k and 3 k -2 k equilibrium points are locally exponentially stable and unstable, respectively. Moreover, it concludes that all the states converge to one of the equilibrium points; i.e., the neural networks are completely stable. The derived conditions herein can be easily tested. Finally, a numerical example is given to illustrate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Oscillatory network with self-organized dynamical connections for synchronization-based image segmentation.

PubMed

Kuzmina, Margarita; Manykin, Eduard; Surina, Irina

2004-01-01

An oscillatory network of columnar architecture located in 3D spatial lattice was recently designed by the authors as oscillatory model of the brain visual cortex. Single network oscillator is a relaxational neural oscillator with internal dynamics tunable by visual image characteristics - local brightness and elementary bar orientation. It is able to demonstrate either activity state (stable undamped oscillations) or "silence" (quickly damped oscillations). Self-organized nonlocal dynamical connections of oscillators depend on oscillator activity levels and orientations of cortical receptive fields. Network performance consists in transfer into a state of clusterized synchronization. At current stage grey-level image segmentation tasks are carried out by 2D oscillatory network, obtained as a limit version of the source model. Due to supplemented network coupling strength control the 2D reduced network provides synchronization-based image segmentation. New results on segmentation of brightness and texture images presented in the paper demonstrate accurate network performance and informative visualization of segmentation results, inherent in the model.

Active influence in dynamical models of structural balance in social networks

NASA Astrophysics Data System (ADS)

Summers, Tyler H.; Shames, Iman

2013-07-01

We consider a nonlinear dynamical system on a signed graph, which can be interpreted as a mathematical model of social networks in which the links can have both positive and negative connotations. In accordance with a concept from social psychology called structural balance, the negative links play a key role in both the structure and dynamics of the network. Recent research has shown that in a nonlinear dynamical system modeling the time evolution of “friendliness levels” in the network, two opposing factions emerge from almost any initial condition. Here we study active external influence in this dynamical model and show that any agent in the network can achieve any desired structurally balanced state from any initial condition by perturbing its own local friendliness levels. Based on this result, we also introduce a new network centrality measure for signed networks. The results are illustrated in an international-relations network using United Nations voting record data from 1946 to 2008 to estimate friendliness levels amongst various countries.

Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

NASA Astrophysics Data System (ADS)

Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

2017-03-01

Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological function.

Integration of Optical Manipulation and Electrophysiological Tools to Modulate and Record Activity in Neural Networks

NASA Astrophysics Data System (ADS)

Difato, F.; Schibalsky, L.; Benfenati, F.; Blau, A.

2011-07-01

We present an optical system that combines IR (1064 nm) holographic optical tweezers with a sub-nanosecond-pulsed UV (355 nm) laser microdissector for the optical manipulation of single neurons and entire networks both on transparent and non-transparent substrates in vitro. The phase-modulated laser beam can illuminate the sample concurrently or independently from above or below assuring compatibility with different types of microelectrode array and patch-clamp electrophysiology. By combining electrophysiological and optical tools, neural activity in response to localized stimuli or injury can be studied and quantified at sub-cellular, cellular, and network level.

Global competition and local cooperation in a network of neural oscillators

NASA Astrophysics Data System (ADS)

Terman, David; Wang, DeLiang

An architecture of locally excitatory, globally inhibitory oscillator networks is proposed and investigated both analytically and by computer simulation. The model for each oscillator corresponds to a standard relaxation oscillator with two time scales. Oscillators are locally coupled by a scheme that resembles excitatory synaptic coupling, and each oscillator also inhibits other oscillators through a common inhibitor. Oscillators are driven to be oscillatory by external stimulation. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing the other oscillators from jumping up. We show analytically that with the selective gating mechanism, the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate the model's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding and may provide an effective computational framework for scene segmentation and figure/ ground segregation.

Analysing human mobility patterns of hiking activities through complex network theory.

PubMed

Lera, Isaac; Pérez, Toni; Guerrero, Carlos; Eguíluz, Víctor M; Juiz, Carlos

2017-01-01

The exploitation of high volume of geolocalized data from social sport tracking applications of outdoor activities can be useful for natural resource planning and to understand the human mobility patterns during leisure activities. This geolocalized data represents the selection of hike activities according to subjective and objective factors such as personal goals, personal abilities, trail conditions or weather conditions. In our approach, human mobility patterns are analysed from trajectories which are generated by hikers. We propose the generation of the trail network identifying special points in the overlap of trajectories. Trail crossings and trailheads define our network and shape topological features. We analyse the trail network of Balearic Islands, as a case of study, using complex weighted network theory. The analysis is divided into the four seasons of the year to observe the impact of weather conditions on the network topology. The number of visited places does not decrease despite the large difference in the number of samples of the two seasons with larger and lower activity. It is in summer season where it is produced the most significant variation in the frequency and localization of activities from inland regions to coastal areas. Finally, we compare our model with other related studies where the network possesses a different purpose. One finding of our approach is the detection of regions with relevant importance where landscape interventions can be applied in function of the communities.

Analysing human mobility patterns of hiking activities through complex network theory

PubMed Central

Pérez, Toni; Guerrero, Carlos; Eguíluz, Víctor M.; Juiz, Carlos

2017-01-01

The exploitation of high volume of geolocalized data from social sport tracking applications of outdoor activities can be useful for natural resource planning and to understand the human mobility patterns during leisure activities. This geolocalized data represents the selection of hike activities according to subjective and objective factors such as personal goals, personal abilities, trail conditions or weather conditions. In our approach, human mobility patterns are analysed from trajectories which are generated by hikers. We propose the generation of the trail network identifying special points in the overlap of trajectories. Trail crossings and trailheads define our network and shape topological features. We analyse the trail network of Balearic Islands, as a case of study, using complex weighted network theory. The analysis is divided into the four seasons of the year to observe the impact of weather conditions on the network topology. The number of visited places does not decrease despite the large difference in the number of samples of the two seasons with larger and lower activity. It is in summer season where it is produced the most significant variation in the frequency and localization of activities from inland regions to coastal areas. Finally, we compare our model with other related studies where the network possesses a different purpose. One finding of our approach is the detection of regions with relevant importance where landscape interventions can be applied in function of the communities. PMID:28542280

Magnetic anomalies possibly linked to local low seismicity

NASA Astrophysics Data System (ADS)

Masci, F.; Palangio, P.; di Persio, M.

2009-09-01

During the last twenty years a time-synchronized network of magnetometers has operated in Central Italy along the Apennine chain to monitor the magnetic field anomalies eventually related to the tectonic activity. At present time the network consists of five stations. In the past only few anomalies in the local geomagnetic field, possibly associated to earthquakes, has been observed, not least because the network area has shown a low-moderate seismic activity with the epicentres of the few events with Ml≥5 located away from the network station. During 2007 two Ml≍4 earthquakes occurred in proximity of two stations of the network. Here we report the magnetic anomalies in the geomagnetic field that could be related with these tectonic events. To better investigate these two events a study of ULF (ultra-low-frequency) emissions has been carried out on the geomagnetic field components H, D, and Z measured in L'Aquila Observatory during the period from January 2006 to December 2008. We want to stress that this paper refers to the period before the 2009 L'Aquila seismic sequence which main shock (Ml=5.8) of 6 April heavily damaged the medieval centre of the city and surroundings. At present time the analysis of the 2009 data is in progress.

MRCK-1 drives apical constriction in C. elegans by linking developmental patterning to force generation

PubMed Central

Marston, Daniel J.; Higgins, Christopher D.; Peters, Kimberly A.; Cupp, Timothy D.; Dickinson, Daniel J.; Pani, Ariel M.; Moore, Regan P.; Cox, Amanda H.; Kiehart, Daniel P.; Goldstein, Bob

2016-01-01

Summary Apical constriction is a change in cell shape that drives key morphogenetic events including gastrulation and neural tube formation. Apical force-producing actomyosin networks drive apical constriction by contracting while connected to cell-cell junctions. The mechanisms by which developmental patterning regulates these actomyosin networks and associated junctions with spatial precision are not fully understood. Here, we identify a myosin light chain kinase MRCK-1 as a key regulator of C. elegans gastrulation that integrates spatial and developmental patterning information. We show that MRCK-1 is required for activation of contractile actomyosin dynamics and elevated cortical tension in the apical cell cortex of endodermal precursor cells. MRCK-1 is apically localized by active Cdc42 at the external, cell-cell contact-free surfaces of apically constricting cells, downstream of cell fate determination mechanisms. We establish that the junctional components α-catenin, β-catenin, and cadherin become highly enriched at the apical junctions of apically-constricting cells, and that MRCK-1 and myosin activity are required in vivo for this enrichment. Taken together, our results define mechanisms that position a myosin activator to a specific cell surface where it both locally increases cortical tension and locally enriches junctional components to facilitate apical constriction. These results reveal crucial links that can tie spatial information to local force generation to drive morphogenesis. PMID:27451898

A mutual support mechanism through intercellular movement of CAPRICE and GLABRA3 can pattern the Arabidopsis root epidermis.

PubMed

Savage, Natasha Saint; Walker, Tom; Wieckowski, Yana; Schiefelbein, John; Dolan, Liam; Monk, Nicholas A M

2008-09-23

The patterning of the Arabidopsis root epidermis depends on a genetic regulatory network that operates both within and between cells. Genetic studies have identified a number of key components of this network, but a clear picture of the functional logic of the network is lacking. Here, we integrate existing genetic and biochemical data in a mathematical model that allows us to explore both the sufficiency of known network interactions and the extent to which additional assumptions about the model can account for wild-type and mutant data. Our model shows that an existing hypothesis concerning the autoregulation of WEREWOLF does not account fully for the expression patterns of components of the network. We confirm the lack of WEREWOLF autoregulation experimentally in transgenic plants. Rather, our modelling suggests that patterning depends on the movement of the CAPRICE and GLABRA3 transcriptional regulators between epidermal cells. Our combined modelling and experimental studies show that WEREWOLF autoregulation does not contribute to the initial patterning of epidermal cell fates in the Arabidopsis seedling root. In contrast to a patterning mechanism relying on local activation, we propose a mechanism based on lateral inhibition with feedback. The active intercellular movements of proteins that are central to our model underlie a mechanism for pattern formation in planar groups of cells that is centred on the mutual support of two cell fates rather than on local activation and lateral inhibition.

A Mutual Support Mechanism through Intercellular Movement of CAPRICE and GLABRA3 Can Pattern the Arabidopsis Root Epidermis

PubMed Central

Savage, Natasha Saint; Walker, Tom; Wieckowski, Yana; Schiefelbein, John; Dolan, Liam; Monk, Nicholas A. M

2008-01-01

The patterning of the Arabidopsis root epidermis depends on a genetic regulatory network that operates both within and between cells. Genetic studies have identified a number of key components of this network, but a clear picture of the functional logic of the network is lacking. Here, we integrate existing genetic and biochemical data in a mathematical model that allows us to explore both the sufficiency of known network interactions and the extent to which additional assumptions about the model can account for wild-type and mutant data. Our model shows that an existing hypothesis concerning the autoregulation of WEREWOLF does not account fully for the expression patterns of components of the network. We confirm the lack of WEREWOLF autoregulation experimentally in transgenic plants. Rather, our modelling suggests that patterning depends on the movement of the CAPRICE and GLABRA3 transcriptional regulators between epidermal cells. Our combined modelling and experimental studies show that WEREWOLF autoregulation does not contribute to the initial patterning of epidermal cell fates in the Arabidopsis seedling root. In contrast to a patterning mechanism relying on local activation, we propose a mechanism based on lateral inhibition with feedback. The active intercellular movements of proteins that are central to our model underlie a mechanism for pattern formation in planar groups of cells that is centred on the mutual support of two cell fates rather than on local activation and lateral inhibition. PMID:18816165

Localization of multilayer networks by optimized single-layer rewiring.

PubMed

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Localization of multilayer networks by optimized single-layer rewiring

NASA Astrophysics Data System (ADS)

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Autoassociative memory retrieval and spontaneous activity bumps in small-world networks of integrate-and-fire neurons.

PubMed

Anishchenko, Anastasia; Treves, Alessandro

2006-10-01

The metric structure of synaptic connections is obviously an important factor in shaping the properties of neural networks, in particular the capacity to retrieve memories, with which are endowed autoassociative nets operating via attractor dynamics. Qualitatively, some real networks in the brain could be characterized as 'small worlds', in the sense that the structure of their connections is intermediate between the extremes of an orderly geometric arrangement and of a geometry-independent random mesh. Small worlds can be defined more precisely in terms of their mean path length and clustering coefficient; but is such a precise description useful for a better understanding of how the type of connectivity affects memory retrieval? We have simulated an autoassociative memory network of integrate-and-fire units, positioned on a ring, with the network connectivity varied parametrically between ordered and random. We find that the network retrieves previously stored memory patterns when the connectivity is close to random, and displays the characteristic behavior of ordered nets (localized 'bumps' of activity) when the connectivity is close to ordered. Recent analytical work shows that these two behaviors can coexist in a network of simple threshold-linear units, leading to localized retrieval states. We find that they tend to be mutually exclusive behaviors, however, with our integrate-and-fire units. Moreover, the transition between the two occurs for values of the connectivity parameter which are not simply related to the notion of small worlds.

[Improving Structures for Healthy and Self-Determined Ageing in an Urban District].

PubMed

Heusinger, J; Kammerer, K; Wolter, B; Schuster, M

2015-09-01

Between 2007 and 2010 the Institut für Gerontologische Forschung e.V. investigated the "Primary Prevention Effects of the Märkisches Viertel Network" in the Berlin district "Märkisches Viertel". The study integrates, amongst others, various participatory methods to investigate the health promotion effects of the volunteer Märkisches Viertel Network, an organisation that brings together different local actors working to assist and encourage older people to live independent lives. Sustained active collaboration by a heterogeneous mixture of actors in a spatially defined quarter, engagement by the local housing association, and increasing acknowledgement of and participation by older residents were identified as success factors for a change in local structures. © Georg Thieme Verlag KG Stuttgart · New York.

Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation

NASA Astrophysics Data System (ADS)

Wang, DeLiang; Terman, David

1995-01-01

A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.

The UNESCO Global Network of National Geoparks

NASA Astrophysics Data System (ADS)

Mc Keever1, P.; Zouros, N.; Patzak, M.; Missotten, R.

2009-12-01

The UNESCO Global Network of National Geoparks was founded in 2004, following the model successfully established by the European Geoparks Network in 2000. It now comprises 63 members in 19 nations across the world. A Global Geopark is an area with geological heritage of international value but where that heritage is being used for the sustainable economic benefit if the local inhabitants, primarily through education and tourism. Supported by IUGS and IUCN, the aim of the Global Geoparks Network is to facilitate exchange and sharing between members to assist in the protection and conservation of the geological heritage of our planet but to do so in way where local communities can take ownership of these special places and where they can get some sustainable economic benefit from them. While allowing for the sustainable economic development of geoparks, the network explicitly forbids the destruction or sale of the geological value of a geopark. This paper outlines the ethos of the Global Geoparks Network and describes the typical activities of geoparks and how the network functions. Using two examples it also illustrates how members of the Global Geoparks Network provide good examples as tools not only for holistic nature conservation but also for economic development.

Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.

Maintaining network activity in submerged hippocampal slices: importance of oxygen supply.

PubMed

Hájos, Norbert; Ellender, Tommas J; Zemankovics, Rita; Mann, Edward O; Exley, Richard; Cragg, Stephanie J; Freund, Tamás F; Paulsen, Ole

2009-01-01

Studies in brain slices have provided a wealth of data on the basic features of neurons and synapses. In the intact brain, these properties may be strongly influenced by ongoing network activity. Although physiologically realistic patterns of network activity have been successfully induced in brain slices maintained in interface-type recording chambers, they have been harder to obtain in submerged-type chambers, which offer significant experimental advantages, including fast exchange of pharmacological agents, visually guided patch-clamp recordings, and imaging techniques. Here, we investigated conditions for the emergence of network oscillations in submerged slices prepared from the hippocampus of rats and mice. We found that the local oxygen level is critical for generation and propagation of both spontaneously occurring sharp wave-ripple oscillations and cholinergically induced fast oscillations. We suggest three ways to improve the oxygen supply to slices under submerged conditions: (i) optimizing chamber design for laminar flow of superfusion fluid; (ii) increasing the flow rate of superfusion fluid; and (iii) superfusing both surfaces of the slice. These improvements to the recording conditions enable detailed studies of neurons under more realistic conditions of network activity, which are essential for a better understanding of neuronal network operation.

Enhancing innovation between scientific and indigenous knowledge: pioneer NGOs in India.

PubMed

Torri, Maria-Costanza; Laplante, Julie

2009-10-22

Until recently, little attention has been paid to local innovation capacity as well as management practices and institutions developed by communities and other local actors based on their traditional knowledge. This paper doesn't focus on the results of scientific research into innovation systems, but rather on how local communities, in a network of supportive partnerships, draw knowledge for others, combine it with their own knowledge and then innovate in their local practices. Innovation, as discussed in this article, is the capacity of local stakeholders to play an active role in innovative knowledge creation in order to enhance local health practices and further environmental conservation. In this article, the innovative processes through which this capacity is created and reinforced will be defined as a process of "ethnomedicine capacity". The field study undertaken by the first author took place in India, in the State of Tamil Nadu, over a period of four months in 2007. The data was collected through individual interviews and focus groups and was complemented by participant observations. The research highlights the innovation capacity related to ethnomedical knowledge. As seen, the integration of local and scientific knowledge is crucial to ensure the practices anchor themselves in daily practices. The networks created are clearly instrumental to enhancing the innovation capacity that allows the creation, dissemination and utilization of 'traditional' knowledge. However, these networks have evolved in very different forms and have become entities that can fit into global networks. The ways in which the social capital is enhanced at the village and network levels are thus important to understand how traditional knowledge can be used as an instrument for development and innovation. The case study analyzed highlights examples of innovation systems in a developmental context. They demonstrate that networks comprised of several actors from different levels can synergistically forge linkages between local knowledge and formal sciences and generate positive and negative impacts. The positive impact is the revitalization of perceived traditions while the negative impacts pertain to the transformation of these traditions into health commodities controlled by new elites, due to unequal power relations.

Enhancing innovation between scientific and indigenous knowledge: pioneer NGOs in India

PubMed Central

Torri, Maria-Costanza; Laplante, Julie

2009-01-01

Background Until recently, little attention has been paid to local innovation capacity as well as management practices and institutions developed by communities and other local actors based on their traditional knowledge. This paper doesn't focus on the results of scientific research into innovation systems, but rather on how local communities, in a network of supportive partnerships, draw knowledge for others, combine it with their own knowledge and then innovate in their local practices. Innovation, as discussed in this article, is the capacity of local stakeholders to play an active role in innovative knowledge creation in order to enhance local health practices and further environmental conservation. In this article, the innovative processes through which this capacity is created and reinforced will be defined as a process of "ethnomedicine capacity". Methods The field study undertaken by the first author took place in India, in the State of Tamil Nadu, over a period of four months in 2007. The data was collected through individual interviews and focus groups and was complemented by participant observations. Results The research highlights the innovation capacity related to ethnomedical knowledge. As seen, the integration of local and scientific knowledge is crucial to ensure the practices anchor themselves in daily practices. The networks created are clearly instrumental to enhancing the innovation capacity that allows the creation, dissemination and utilization of 'traditional' knowledge. However, these networks have evolved in very different forms and have become entities that can fit into global networks. The ways in which the social capital is enhanced at the village and network levels are thus important to understand how traditional knowledge can be used as an instrument for development and innovation. Conclusion The case study analyzed highlights examples of innovation systems in a developmental context. They demonstrate that networks comprised of several actors from different levels can synergistically forge linkages between local knowledge and formal sciences and generate positive and negative impacts. The positive impact is the revitalization of perceived traditions while the negative impacts pertain to the transformation of these traditions into health commodities controlled by new elites, due to unequal power relations. PMID:19849851

High Resolution Vp and Vp/Vs Local Earthquake Tomography of the Val d'Agri Region (Southern Apennines, Italy).

NASA Astrophysics Data System (ADS)

Improta, L.; Bagh, S.; De Gori, P.; Pastori, M.; Piccinini, D.; Valoroso, L.; Anselmi, M.; Buttinelli, M.; Chiarabba, C.

2015-12-01

The Val d'Agri (VA) Quaternary basin in the southern Apennines extensional belt hosts the largest oilfield in onshore Europe and normal-fault systems with high (up to M7) seismogenic potential. Frequent small-magnitude swarms related to both active crustal extension and anthropogenic activity have occurred in the region. Causal factors for induced seismicity are a water impoundment with severe seasonal oscillations and a high-rate wastewater injection well. We analyzed around 1200 earthquakes (ML<3.3) occurred in the VA and surrounding regions between 2001-2014. We integrated waveforms recorded at 46 seismic stations belonging to 3 different networks: a dense temporary network installed by INGV in 2005-2006, the permanent national network of INGV, and the trigger-mode monitoring network managed by the local operator ENI petroleum company. We used local earthquake tomography to investigate static and transient features of the crustal velocity structure and to accurately locate earthquakes. Vp and Vp/Vs models are parameterized by a 3x3x2 km spacing and well resolved down to about 12 km depth. The complex Vp model illuminates broad antiformal structures corresponding to wide ramp-anticlines involving Mesozoic carbonates of the Apulia hydrocarbon reservoir, and NW-SE trending low Vp regions related to thrust-sheet-top clastic basins. The VA basin corresponds to shallow low-Vp region. Focal mechanisms show normal faulting kinematics with minor strike slip solutions in agreement with the local extensional regime. Earthquake locations and focal solutions depict shallow (< 5 km depth) E-dipping extensional structures beneath the artificial lake located in the southern sector of the basin, and along the western margin of the VA. A few swarms define relatively deep transfer structures accommodating the differential extension between main normal faults. The spatio-temporal distribution of around 220 events correlates with wastewater disposal activity, illuminating a NE-dipping fault between 2-5 km depth in the carbonate reservoir. The fault measures 5 km along dip and corresponds to a pre-existing thrust fault favorably oriented with respect to the local extensional field.

The development and achievement of a healthy cities network in Taiwan: sharing leadership and partnership building.

PubMed

Hu, Susan C; Kuo, Hsien-Wen

2016-03-01

The World Health Organization (WHO) Healthy Cities (HC) projects are the best known of the settings-based approaches to health promotion. They engage local governments in health development through a process of political commitment, institutional change, capacity-building, partnership-based planning and innovative projects. Many cities have promoted HC projects in Taiwan since 2002. In 2008, the Taiwan Alliance for Healthy Cities (TAHC) was launched to assist local governments in effectively establishing, operating and promoting HC projects. In this article, we share our experiences of establishing a platform and network to promote the HC program in Taiwan. Based on individual city profiles and governance in Taiwan, the TAHC developed a well-organized framework and model to encourage strong leadership in local governments and to promote participation and engagement in their communities. In the last 6 years, leaders from Taiwan's local governments in HC networks have integrated the HC concepts into their governance models, actively engaging and combining various resources with practical expertise and private sectors. The network of health in Taiwan allows each city to develop its unique perspective on the HC projects. Using this method, not only local government meets its needs, but also increases governance efficiency and effectiveness, resulting in the promotion of its citizens' overall sustainable urban health development. This HC network in Taiwan has partnerships with government and non-governmental organizations (NGOs), with academic support and citizen involvement, a dynamic data collection system and demonstrated leadership in the sharing of information in the Asian region. © The Author(s) 2016.

Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection.

PubMed

Sarikaya, Duygu; Corso, Jason J; Guru, Khurshid A

2017-07-01

Video understanding of robot-assisted surgery (RAS) videos is an active research area. Modeling the gestures and skill level of surgeons presents an interesting problem. The insights drawn may be applied in effective skill acquisition, objective skill assessment, real-time feedback, and human-robot collaborative surgeries. We propose a solution to the tool detection and localization open problem in RAS video understanding, using a strictly computer vision approach and the recent advances of deep learning. We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos. To the best of our knowledge, this approach will be the first to incorporate deep neural networks for tool detection and localization in RAS videos. Our architecture applies a region proposal network (RPN) and a multimodal two stream convolutional network for object detection to jointly predict objectness and localization on a fusion of image and temporal motion cues. Our results with an average precision of 91% and a mean computation time of 0.1 s per test frame detection indicate that our study is superior to conventionally used methods for medical imaging while also emphasizing the benefits of using RPN for precision and efficiency. We also introduce a new data set, ATLAS Dione, for RAS video understanding. Our data set provides video data of ten surgeons from Roswell Park Cancer Institute, Buffalo, NY, USA, performing six different surgical tasks on the daVinci Surgical System (dVSS) with annotations of robotic tools per frame.

Abnormally Malicious Autonomous Systems and their Internet Connectivity

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

Shue, Craig A; Kalafut, Prof. Andrew; Gupta, Prof. Minaxi

While many attacks are distributed across botnets, investigators and network operators have recently targeted malicious networks through high profile autonomous system (AS) de-peerings and network shut-downs. In this paper, we explore whether some ASes indeed are safe havens for malicious activity. We look for ISPs and ASes that exhibit disproportionately high malicious behavior using ten popular blacklists, plus local spam data, and extensive DNS resolutions based on the contents of the blacklists. We find that some ASes have over 80% of their routable IP address space blacklisted. Yet others account for large fractions of blacklisted IP addresses. Several ASes regularlymore » peer with ASes associated with significant malicious activity. We also find that malicious ASes as a whole differ from benign ones in other properties not obviously related to their malicious activities, such as more frequent connectivity changes with their BGP peers. Overall, we conclude that examining malicious activity at AS granularity can unearth networks with lax security or those that harbor cybercrime.« less

Spontaneous Ad Hoc Mobile Cloud Computing Network

PubMed Central

Lacuesta, Raquel; Sendra, Sandra; Peñalver, Lourdes

2014-01-01

Cloud computing helps users and companies to share computing resources instead of having local servers or personal devices to handle the applications. Smart devices are becoming one of the main information processing devices. Their computing features are reaching levels that let them create a mobile cloud computing network. But sometimes they are not able to create it and collaborate actively in the cloud because it is difficult for them to build easily a spontaneous network and configure its parameters. For this reason, in this paper, we are going to present the design and deployment of a spontaneous ad hoc mobile cloud computing network. In order to perform it, we have developed a trusted algorithm that is able to manage the activity of the nodes when they join and leave the network. The paper shows the network procedures and classes that have been designed. Our simulation results using Castalia show that our proposal presents a good efficiency and network performance even by using high number of nodes. PMID:25202715

Spontaneous ad hoc mobile cloud computing network.

PubMed

Lacuesta, Raquel; Lloret, Jaime; Sendra, Sandra; Peñalver, Lourdes

2014-01-01

Cloud computing helps users and companies to share computing resources instead of having local servers or personal devices to handle the applications. Smart devices are becoming one of the main information processing devices. Their computing features are reaching levels that let them create a mobile cloud computing network. But sometimes they are not able to create it and collaborate actively in the cloud because it is difficult for them to build easily a spontaneous network and configure its parameters. For this reason, in this paper, we are going to present the design and deployment of a spontaneous ad hoc mobile cloud computing network. In order to perform it, we have developed a trusted algorithm that is able to manage the activity of the nodes when they join and leave the network. The paper shows the network procedures and classes that have been designed. Our simulation results using Castalia show that our proposal presents a good efficiency and network performance even by using high number of nodes.

Public/Private Partnerships: Building Support for Employer-Sponsored Eldercare: A Guide for the Aging Network.

ERIC Educational Resources Information Center

Sheehy, Edward

This guidebook provides practical information to assist state and local aging agencies in developing strategic relationships with businesses in their communities. It focuses on the experiences of those state agencies and Area Agencies on Aging that are actively working with local employers and it presents a framework for other agencies. The book…

Designed Curriculum and Local Culture: Acknowledging the Primacy of Classroom Culture.

ERIC Educational Resources Information Center

Squire, Kurt D.; MaKinster, James G.; Barnett, Michael; Luehmann, April Lynn; Barab, Sasha L.

2003-01-01

Examines four teachers implementing a project-based curriculum (Air Quality module) on a web-based platform (ActiveInk Network) in four very different settings. Discusses each case across two themes by examining how the project-level question was contextualized to meet local needs and the cultural context that surrounded the implementation of the…

Multiscale Aspects of Generation of High-Gamma Activity during Seizures in Human Neocortex123

PubMed Central

Marcuccilli, Charles J.; Ben-Mabrouk, Faiza; Lew, Sean M.; Goodman, Robert R.; McKhann, Guy M.; Frim, David M.; Kohrman, Michael H.; Schevon, Catherine A.; van Drongelen, Wim

2016-01-01

High-gamma (HG; 80-150 Hz) activity in macroscopic clinical records is considered a marker for critical brain regions involved in seizure initiation; it is correlated with pathological multiunit firing during neocortical seizures in the seizure core, an area identified by correlated multiunit spiking and low frequency seizure activity. However, the effects of the spatiotemporal dynamics of seizure on HG power generation are not well understood. Here, we studied HG generation and propagation, using a three-step, multiscale signal analysis and modeling approach. First, we analyzed concurrent neuronal and microscopic network HG activity in neocortical slices from seven intractable epilepsy patients. We found HG activity in these networks, especially when neurons displayed paroxysmal depolarization shifts and network activity was highly synchronized. Second, we examined HG activity acquired with microelectrode arrays recorded during human seizures (n = 8). We confirmed the presence of synchronized HG power across microelectrode records and the macroscale, both specifically associated with the core region of the seizure. Third, we used volume conduction-based modeling to relate HG activity and network synchrony at different network scales. We showed that local HG oscillations require high levels of synchrony to cross scales, and that this requirement is met at the microscopic scale, but not within macroscopic networks. Instead, we present evidence that HG power at the macroscale may result from harmonics of ongoing seizure activity. Ictal HG power marks the seizure core, but the generating mechanism can differ across spatial scales. PMID:27257623

Pharmacological modulation of pulvinar resting-state regional oscillations and network dynamics in major depression

PubMed Central

Tadayonnejad, Reza; Ajilore, Olusola; Mickey, Brian J.; Crane, Natania A.; Hsu, David T.; Kumar, Anand; Zubieta, Jon-Kar; Langenecker, Scott A.

2016-01-01

The pulvinar, the largest thalamus nucleus, has rich anatomical connections with several different cortical and subcortical regions suggesting its important involvement in high-level cognitive and emotional functions. Unfortunately, pulvinar dysfunction in psychiatric disorders particularly major depression disorder has not been thoroughly examined to date. In this study we explored the alterations in the baseline regional and network activities of the pulvinar in MDD by applying spectral analysis of resting-state oscillatory activity, functional connectivity and directed (effective) connectivity on resting-state fMRI data acquired from 20 healthy controls and 19 participants with MDD. Furthermore, we tested how pharmacological treatment with duloxetine can modulate the measured local and network variables in ten participants who completed treatment. Our results revealed a frequency-band dependent modulation of power spectrum characteristics of pulvinar regional oscillatory activity. At the network level, we found MDD is associated with aberrant causal interactions between pulvinar and several systems including default-mode and posterior insular networks. It was also shown that duloxetine treatment can correct or overcompensate the pathologic network behavior of the pulvinar. In conclusion, we suggest that pulvinar regional baseline oscillatory activity and its resting-state network dynamics are compromised in MDD and can be modulated therapeutically by pharmacological treatment. PMID:27148894

Correlated network of networks enhances robustness against catastrophic failures.

PubMed

Min, Byungjoon; Zheng, Muhua

2018-01-01

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule.

Correlated network of networks enhances robustness against catastrophic failures

PubMed Central

Zheng, Muhua

2018-01-01

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule. PMID:29668730

Expanding Local Cancer Clinical Trial Options: Analysis of the Economic Impact of the Midwest Cancer Alliance in Kansas

PubMed Central

Gafford, J. Atlee; Krebill, Hope; Lai, Sue Min; Christiadi; Doolittle, Gary C.

2017-01-01

Purpose Patients benefit from receiving cancer treatment closer to home when possible and at high-volume regional centers when specialized care is required. The purpose of this analysis was to estimate the economic impact of retaining more patients in-state for cancer clinical trials and care, which might offset some of the costs of establishing broader cancer trial and treatment networks. Method Kansas Cancer Registry data were used to estimate the number of patients retained in-state for cancer care following the expansion of local cancer clinical trial options through the Midwest Cancer Alliance based at the University of Kansas Medical Center. The 2014 economic impact of this enhanced local clinical trial network was estimated in four parts: Medical spending was estimated on the basis of National Cancer Institute cost-of-care estimates. Household travel cost savings were estimated as the difference between in-state and out-of-state travel costs. Trial-related grant income was calculated from administrative records. Indirect and induced economic benefits to the state were estimated using an economic impact model. Results The authors estimated that the enhanced local cancer clinical trial network resulted in approximately $6.9 million in additional economic activity in the state in 2014, or $362,000 per patient retained in-state. This estimate includes $3.6 million in direct spending and $3.3 million in indirect economic activity. The enhanced trial network also resulted in 45 additional jobs. Conclusions Retaining patients in-state for cancer care and clinical trial participation allows patients to remain closer to home for care and enhances the state economy. PMID:28253204

National Seismic Network of Georgia

NASA Astrophysics Data System (ADS)

Tumanova, N.; Kakhoberashvili, S.; Omarashvili, V.; Tserodze, M.; Akubardia, D.

2016-12-01

Georgia, as a part of the Southern Caucasus, is tectonically active and structurally complex region. It is one of the most active segments of the Alpine-Himalayan collision belt. The deformation and the associated seismicity are due to the continent-continent collision between the Arabian and Eurasian plates. Seismic Monitoring of country and the quality of seismic data is the major tool for the rapid response policy, population safety, basic scientific research and in the end for the sustainable development of the country. National Seismic Network of Georgia has been developing since the end of 19th century. Digital era of the network started from 2003. Recently continuous data streams from 25 stations acquired and analyzed in the real time. Data is combined to calculate rapid location and magnitude for the earthquake. Information for the bigger events (Ml>=3.5) is simultaneously transferred to the website of the monitoring center and to the related governmental agencies. To improve rapid earthquake location and magnitude estimation the seismic network was enhanced by installing additional 7 new stations. Each new station is equipped with coupled Broadband and Strong Motion seismometers and permanent GPS system as well. To select the sites for the 7 new base stations, we used standard network optimization techniques. To choose the optimal sites for new stations we've taken into account geometry of the existed seismic network, topographic conditions of the site. For each site we studied local geology (Vs30 was mandatory for each site), local noise level and seismic vault construction parameters. Due to the country elevation, stations were installed in the high mountains, no accessible in winter due to the heavy snow conditions. To secure online data transmission we used satellite data transmission as well as cell data network coverage from the different local companies. As a result we've already have the improved earthquake location and event magnitudes. We've analyzed data from each station to calculate signal-to-nose ratio. Comparing these calculations with the ones for the existed stations showed that signal-to-nose ratio for new stations has much better value. National Seismic Network of Georgia is planning to install more stations to improve seismic network coverage.

Assessing cortical synchronization during transcranial direct current stimulation: A graph-theoretical analysis.

PubMed

Mancini, Matteo; Brignani, Debora; Conforto, Silvia; Mauri, Piercarlo; Miniussi, Carlo; Pellicciari, Maria Concetta

2016-10-15

Transcranial direct current stimulation (tDCS) is a neuromodulation technique that can alter cortical excitability and modulate behaviour in a polarity-dependent way. Despite the widespread use of this method in the neuroscience field, its effects on ongoing local or global (network level) neuronal activity are still not foreseeable. A way to shed light on the neuronal mechanisms underlying the cortical connectivity changes induced by tDCS is provided by the combination of tDCS with electroencephalography (EEG). In this study, twelve healthy subjects underwent online tDCS-EEG recording (i.e., simultaneous), during resting-state, using 19 EEG channels. The protocol involved anodal, cathodal and sham stimulation conditions, with the active and the reference electrodes in the left frontocentral area (FC3) and on the forehead over the right eyebrow, respectively. The data were processed using a network model, based on graph theory and the synchronization likelihood. The resulting graphs were analysed for four frequency bands (theta, alpha, beta and gamma) to evaluate the presence of tDCS-induced differences in synchronization patterns and graph theory measures. The resting state network connectivity resulted altered during tDCS, in a polarity-specific manner for theta and alpha bands. Anodal tDCS weakened synchronization with respect to the baseline over the fronto-central areas in the left hemisphere, for theta band (p<0.05). In contrast, during cathodal tDCS a significant increase in inter-hemispheric synchronization connectivity was observed over the centro-parietal, centro-occipital and parieto-occipital areas for the alpha band (p<0.05). Local graph measures showed a tDCS-induced polarity-specific differences that regarded modifications of network activities rather than specific region properties. Our results show that applying tDCS during the resting state modulates local synchronization as well as network properties in slow frequency bands, in a polarity-specific manner. Copyright © 2016 Elsevier Inc. All rights reserved.

Observational investigation of ionospheric turbulent spectral content in relation to geomagnetic field variations and local seismicity

NASA Astrophysics Data System (ADS)

Contadakis, M. E.; Arambelos, D.; Asteriadis, G.; Pikridas, Ch.; Spatalas, S.; Chatzinikos, M.

2006-04-01

Atmospheric and underground explosions as well as shallow earthquakes producing strong vertical ground displacement, are known to produce pressure waves that propagates at infrasonic speeds in the atmosphere. At ionospheric altitudes these waves are coupled to ionospheric gravity waves and induce variations in the ionospheric electron density. On the other hand local lithospheric density, ion inhalation, temperature or electromagnetic field variations, produced by the local tectonic activity during the earthquake preparation period, induces near surface atmospheric variations and affect the ionospheric density through the Lithospher-Atmosphere- Ionosphere Coupling. That is the lithospheric near surface tectonic activity results to local pre- co- and post seismic disturbances on the ionospheric Total Electron Content (TEC). Nevertheless these disturbances are mixed with disturbances induced to the ionospher by a number of agents such as tropospheric jets, magnetic storms and sub-storms, solar activity, ionosphere-magnetosphere coupling etc, and a major problem is to discriminate the influence of those agents from the influence of the local tectonic activity. In this paper we present the results of the wavelet analysis of TVEC variations over a network of 4 GPS stations, depicted from EUREF-EPN network, covering the whole area of Greece. Our results indicate that 1) Disturbances with period higher than 3 hours have a Universal origin i.e. earth-tides, Aurora or Equatorial anomaly. 2) Disturbances with periods equal or smaller than 3 hours are of local origin. 3) Strong Variations of geomagnetic field affect the disturbances of all periods. 4) Disturbances with period 3 hours present a good coherency in the measurements of more than one GPS stations. In concluding disturbances with period equal or less than 3 hours are suitable for de

Spread of activation and deactivation in the brain: does age matter?

PubMed Central

Gordon, Brian A.; Tse, Chun-Yu; Gratton, Gabriele; Fabiani, Monica

2014-01-01

Cross-sectional aging functional MRI results are sometimes difficult to interpret, as standard measures of activation and deactivation may confound variations in signal amplitude and spread, which however, may be differentially affected by age-related changes in various anatomical and physiological factors. To disentangle these two types of measures, here we propose a novel method to obtain independent estimates of the peak amplitude and spread of the BOLD signal in areas activated (task-positive) and deactivated (task-negative) by a Sternberg task, in 14 younger and 28 older adults. The peak measures indicated that, compared to younger adults, older adults had increased activation of the task-positive network, but similar levels of deactivation in the task-negative network. Measures of signal spread revealed that older adults had an increased spread of activation in task-positive areas, but a starkly reduced spread of deactivation in task-negative areas. These effects were consistent across regions within each network. Further, there was greater variability in the anatomical localization of peak points in older adults, leading to reduced cross-subject overlap. These results reveal factors that may confound the interpretation of studies of aging. Additionally, spread measures may be linked to local connectivity phenomena and could be particularly useful to analyze age-related deactivation patterns, complementing the results obtained with standard peak and region of interest analyses. PMID:25360115

Monitoring the Restart of a High-Rate Wastewater Disposal Well in the Val d'Agri Oilfield (Italy)

NASA Astrophysics Data System (ADS)

De Gori, P.; Improta, L.; Moretti, M.; Colasanti, G.; Criscuoli, F.

2015-12-01

The Val d'Agri Quaternary basin in the Southern Apennine range of Italy hosts the largest inland oil field in Europe. Wastewater coming from the oil exploitation is re-injected by a high-rate disposal well into strongly fractured limestones of the hydrocarbon carbonate reservoir. Disposal activity has induced micro-seismicity since the beginning of injection in June 2006. Around 220 small magnitude events (ML < 2.3) were recorded between 2006 and 2013 by the trigger-mode monitoring local network managed by the oil company and by the National Seismic Network of Istituto Nazionale di Geofisica e Vulcanologia. The induced micro-seismicity illuminated a pre-existing high-angle fault located 1 km below the well. Since June 2006, wastewater has been re-injected with only short interruptions due acid stimulations. In January 2015 disposal activity was halted due to technical operations in the oil refinery and wastewater injection restarted after two weeks. We installed 5 short-period stations within 10 km of the disposal well to carefully monitor the re-start phase and the subsequent 3 months of disposal activity. This temporary network was complemented by stations of the National Seismic Network giving this final configuration:9 stations within 10 km of the well with the closest station 2 km apart, 13 stations within 20 km. Here we report on the preliminary analysis of the local earthquake recorded during the survey focusing on the events occurred in the injection area. The seismicity rate is compared with injection data.In spite of the dense network, we found that the rate of induced seismicity (both the number and energy of events) is very low when compared to the seismicity recorded during the first 5 years of injection activity carried out with comparable rate and pressure.

Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

PubMed

Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

2016-12-01

With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

Network dysfunction predicts speech production after left hemisphere stroke.

PubMed

Geranmayeh, Fatemeh; Leech, Robert; Wise, Richard J S

2016-03-09

To investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke. We conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses. Although activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production. Speech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior. © 2016 American Academy of Neurology.

Network dysfunction predicts speech production after left hemisphere stroke

PubMed Central

Leech, Robert; Wise, Richard J.S.

2016-01-01

Objective: To investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke. Methods: We conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses. Results: Although activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production. Conclusions: Speech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior. PMID:26962070

Online social activity reflects economic status

NASA Astrophysics Data System (ADS)

Liu, Jin-Hu; Wang, Jun; Shao, Junming; Zhou, Tao

2016-09-01

To characterize economic development and diagnose the economic health condition, several popular indices such as gross domestic product (GDP), industrial structure and income growth are widely applied. However, computing these indices based on traditional economic census is usually costly and resources consuming, and more importantly, following a long time delay. In this paper, we analyzed nearly 200 million users' activities for four consecutive years in the largest social network (Sina Microblog) in China, aiming at exploring latent relationships between the online social activities and local economic status. Results indicate that online social activity has a strong correlation with local economic development and industrial structure, and more interestingly, allows revealing the macro-economic structure instantaneously with nearly no cost. Beyond, this work also provides a new venue to identify risky signal in local economic structure.

Networking Activities and Perceptions of HIV Risk Among Male Migrant Market Vendors in China

PubMed Central

Wang, Wenqing; Muessig, Kathryn E.; Li, Mingqiang; Zhang, Yingxia

2013-01-01

HIV research among internal migrants in China has not fully explored the contexts and perceptions of “risk”. In 2011, urban markets in Liuzhou, China were mapped, and sixty male vendors, age 22 to 56, were selected for in-depth interviews on migration, social and family life, and perceptions and practices of sexual risk behavior. Participants were evenly divided among higher income shop and small stall vendors. All men were sexually active. Only the shop vendors reported non-marital sexual partners, including concurrent partners (n=15), commercial partners (n=10), and other sexual relationships (n=11). Shop vendors engaged in networking activities that facilitated commercial and non-commercial high-risk sex. Perceptions of HIV risk from commercial sex led some men to doubt the protective ability of condoms and rely on local (unproven) self-protection techniques. Networking activities played a role in high-risk sex and shaping migrants' risk perceptions and health practices. The networks created through these processes could also be used to facilitate health promotion activities. PMID:23572155

The Sub-Regional Functional Organization of Neocortical Irritative Epileptic Networks in Pediatric Epilepsy

PubMed Central

Janca, Radek; Krsek, Pavel; Jezdik, Petr; Cmejla, Roman; Tomasek, Martin; Komarek, Vladimir; Marusic, Petr; Jiruska, Premysl

2018-01-01

Between seizures, irritative network generates frequent brief synchronous activity, which manifests on the EEG as interictal epileptiform discharges (IEDs). Recent insights into the mechanism of IEDs at the microscopic level have demonstrated a high variance in the recruitment of neuronal populations generating IEDs and a high variability in the trajectories through which IEDs propagate across the brain. These phenomena represent one of the major constraints for precise characterization of network organization and for the utilization of IEDs during presurgical evaluations. We have developed a new approach to dissect human neocortical irritative networks and quantify their properties. We have demonstrated that irritative network has modular nature and it is composed of multiple independent sub-regions, each with specific IED propagation trajectories and differing in the extent of IED activity generated. The global activity of the irritative network is determined by long-term and circadian fluctuations in sub-region spatiotemporal properties. Also, the most active sub-region co-localizes with the seizure onset zone in 12/14 cases. This study demonstrates that principles of recruitment variability and propagation are conserved at the macroscopic level and that they determine irritative network properties in humans. Functional stratification of the irritative network increases the diagnostic yield of intracranial investigations with the potential to improve the outcomes of surgical treatment of neocortical epilepsy. PMID:29628910

A system for ubiquitous health monitoring in the bedroom via a Bluetooth network and wireless LAN.

PubMed

Choi, J M; Choi, B H; Seo, J W; Sohn, R H; Ryu, M S; Yi, W; Park, K S

2004-01-01

Advances in information technology have enabled ubiquitous health monitoring at home, which is particularly useful for patients, who have to live alone. We have focused on the automatic and unobtrusive measurement of biomedical signals and activities of patients. We have constructed wireless communication networks in order to transfer data. The networks consist of Bluetooth and Wireless Local Area Network (WLAN). In this paper, we present the concept of a ubiquitous-Bedroom (u-Bedroom) which is a part of a ubiquitous-House (u-House) and we present our systems for ubiquitous health monitoring.

Relative Differences in Resting-State Brain Connectivity Associated with Long Term Intensive Lifestyle Intervention

PubMed Central

Casanova, Ramon; Hayasaka, Satoru; Saldana, Santiago; Bryan, Nick R.; Demos, Kathryn E.; Desiderio, Lisa; Erickson, Kirk I.; Espeland, Mark A.; Nasrallah, Ilya M.; Wadden, Thomas; Laurienti, Paul J.

2016-01-01

A number of studies have reported that type 2 diabetes mellitus (T2DM) is associated with alterations in resting-state activity and connectivity in the brain. There is also evidence that interventions involving physical activity and weight loss may affect brain functional connectivity. In this study, we examined the effects of nearly 10 years of an intensive lifestyle intervention (ILI), designed to induce and sustain weight loss through lower caloric intake and increased physical activity, on resting-state networks in adults with T2DM. We performed a cross-sectional comparison of global and local characteristics from functional brain networks between individuals who had been randomly assigned to ILI or a control condition of health education and support. Upon examining brain networks from 312 participants (average age: 68.8 for ILI and 67.9 for controls), we found that ILI participants (N=160) had attenuated local efficiency at the network-level compared with controls (N=152). Although there was no group difference in the network-level global efficiency, we found that, among ILI participants, nodal global efficiency was elevated in left fusiform gyrus, right middle frontal gyrus, and pars opercularis of right inferior frontal gyrus. These effects were age-dependent, with more pronounced effects for older participants. Overall these results indicate that the individuals assigned to the ILI had brain networks with less regional and more global connectivity, particularly involving frontal lobes. Such patterns would support greater distributed information processing. Future studies are needed to determine if these differences are associated with age-related compensatory function in the ILI group or worse pathology in the control group. PMID:27685338

Structural and Functional Alterations in Neocortical Circuits after Mild Traumatic Brain Injury

NASA Astrophysics Data System (ADS)

Vascak, Michal

National concern over traumatic brain injury (TBI) is growing rapidly. Recent focus is on mild TBI (mTBI), which is the most prevalent injury level in both civilian and military demographics. A preeminent sequelae of mTBI is cognitive network disruption. Advanced neuroimaging of mTBI victims supports this premise, revealing alterations in activation and structure-function of excitatory and inhibitory neuronal systems, which are essential for network processing. However, clinical neuroimaging cannot resolve the cellular and molecular substrates underlying such changes. Therefore, to understand the full scope of mTBI-induced alterations it is necessary to study cortical networks on the microscopic level, where neurons form local networks that are the fundamental computational modules supporting cognition. Recently, in a well-controlled animal model of mTBI, we demonstrated in the excitatory pyramidal neuron system, isolated diffuse axonal injury (DAI), in concert with electrophysiological abnormalities in nearby intact (non-DAI) neurons. These findings were consistent with altered axon initial segment (AIS) intrinsic activity functionally associated with structural plasticity, and/or disturbances in extrinsic systems related to parvalbumin (PV)-expressing interneurons that form GABAergic synapses along the pyramidal neuron perisomatic/AIS domains. The AIS and perisomatic GABAergic synapses are domains critical for regulating neuronal activity and E-I balance. In this dissertation, we focus on the neocortical excitatory pyramidal neuron/inhibitory PV+ interneuron local network following mTBI. Our central hypothesis is that mTBI disrupts neuronal network structure and function causing imbalance of excitatory and inhibitory systems. To address this hypothesis we exploited transgenic and cre/lox mouse models of mTBI, employing approaches that couple state-of-the-art bioimaging with electrophysiology to determine the structuralfunctional alterations of excitatory and inhibitory systems in the neocortex.

3D electrode localization on wireless sensor networks for wearable BCI.

PubMed

Figueiredo, C P; Dias, N S; Hoffmann, K P; Mendes, P M

2008-01-01

This paper presents a solution for electrode localization on wearable BCI radio-enabled electrodes. Electrode positioning is a common issue in any electrical physiological recording. Although wireless node localization is a very active research topic, a precise method with few centimeters of range and a resolution in the order of millimeters is still to be found, since far-field measurements are very prone to error. The calculation of 3D coordinates for each electrode is based on anchorless range-based localization algorithms such as Multidimensional Scaling and Self-Positioning Algorithm. The implemented solution relies on the association of a small antenna to measure the magnetic field and a microcontroller to each electrode, which will be part of the wireless sensor network module. The implemented solution is suitable for EEG applications, namely the wearable BCI, with expected range of 20 cm and resolution of 5 mm.

Georgia-Armenia Transboarder seismicity studies

NASA Astrophysics Data System (ADS)

Godoladze, T.; Tvaradze, N.; Javakishvili, Z.; Elashvili, M.; Durgaryan, R.; Arakelyan, A.; Gevorgyan, M.

2012-12-01

In the presented study we performed Comprehensive seismic analyses for the Armenian-Georgian transboarder active seismic fault starting on Armenian territory, cutting the state boarder and having possibly northern termination on Adjara-Triealeti frontal structure in Georgia. In the scope of International projects: ISTC A-1418 "Open network of scientific Centers for mitigation risk of natural hazards in the Southern Caucasus and Central Asia" and NATO SfP- 983284 Project "Caucasus Seismic Emergency Response" in Akhalkalaki (Georgia) seismic center, Regional Summer school trainings and intensive filed investigations were conducted. Main goal was multidisciplinary study of the Javakheti fault structure and better understanding seismicity of the area. Young scientists from Turkey, Armenia, Azerbaijan and Georgia were participated in the deployment of temporal seismic network in order to monitor seisimity on the Javakheti highland and particularly delineate fault scarf and identify active seismic structures. In the scope of international collaboration the common seismic database has been created in the southern Caucasus and collected data from the field works is available now online. Javakheti highland, which is located in the central part of the Caucasus, belongs to the structure of the lesser Caucasus and represents a history of neotectonic volcanism existed in the area. Jasvakheti highland is seismicalu active region devastating from several severe earthquakes(1088, 1283, 1899…). Hypocenters located during analogue network were highly scattered and did not describe real pattern of seismicity of the highland. We relocated hypocenters of the region and improved local velocity model. The hypocenters derived from recently deployed local seismic network in the Javakheti highland, clearly identified seismically active structures. Fault plane solutions of analogue data of the Soviet times have been carefully analyzed and examined. Moment tensor inversion were preformed for the recent moderate size earthquakes and the results are in an agreement with paleo-trenching data showing normal fault mechanism on the south and strake slip on the northern edge of the fault. Local seismic tomography of Javakheti area has been performed in order to improve 3D structure of the region.

Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation.

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina; Zochowski, Michal

2007-03-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Structural network heterogeneities and network dynamics: A possible dynamical mechanism for hippocampal memory reactivation

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina R.; Zochowski, Michal

2007-01-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Image sensor system with bio-inspired efficient coding and adaptation.

PubMed

Okuno, Hirotsugu; Yagi, Tetsuya

2012-08-01

We designed and implemented an image sensor system equipped with three bio-inspired coding and adaptation strategies: logarithmic transform, local average subtraction, and feedback gain control. The system comprises a field-programmable gate array (FPGA), a resistive network, and active pixel sensors (APS), whose light intensity-voltage characteristics are controllable. The system employs multiple time-varying reset voltage signals for APS in order to realize multiple logarithmic intensity-voltage characteristics, which are controlled so that the entropy of the output image is maximized. The system also employs local average subtraction and gain control in order to obtain images with an appropriate contrast. The local average is calculated by the resistive network instantaneously. The designed system was successfully used to obtain appropriate images of objects that were subjected to large changes in illumination.

Climate Voices: Bridging Scientist Citizens and Local Communities across the United States

NASA Astrophysics Data System (ADS)

Wegner, K.; Ristvey, J. D., Jr.

2016-12-01

Based out of the University Corporation for Atmospheric Research (UCAR), the Climate Voices Science Speakers Network (climatevoices.org) has more than 400 participants across the United States that volunteer their time as scientist citizens in their local communities. Climate Voices experts engage in nonpartisan conversations about the local impacts of climate change with groups such as Rotary clubs, collaborate with faith-based groups on climate action initiatives, and disseminate their research findings to K-12 teachers and classrooms through webinars. To support their participants, Climate Voices develops partnerships with networks of community groups, provides trainings on how to engage these communities, and actively seeks community feedback. In this presentation, we will share case studies of science-community collaborations, including meta-analyses of collaborations and lessons learned.

Prediction of Biological Motion Perception Performance from Intrinsic Brain Network Regional Efficiency

PubMed Central

Wang, Zengjian; Zhang, Delong; Liang, Bishan; Chang, Song; Pan, Jinghua; Huang, Ruiwang; Liu, Ming

2016-01-01

Biological motion perception (BMP) refers to the ability to perceive the moving form of a human figure from a limited amount of stimuli, such as from a few point lights located on the joints of a moving body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants, for whom intrinsic brain networks were constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located in the Default Mode Network (DMN). Additionally, discrimination analysis showed that the local efficiency of certain regions such as the thalamus could be used to classify BMP performance across participants. Notably, the association pattern between network nodal efficiency and BMP was different from the association pattern of static directional/gender information perception. Overall, these findings show that intrinsic brain network efficiency may be considered a neural factor that explains BMP inter-individual variability. PMID:27853427

Different forms of effective connectivity in primate frontotemporal pathways.

PubMed

Petkov, Christopher I; Kikuchi, Yukiko; Milne, Alice E; Mishkin, Mortimer; Rauschecker, Josef P; Logothetis, Nikos K

2015-01-23

It is generally held that non-primary sensory regions of the brain have a strong impact on frontal cortex. However, the effective connectivity of pathways to frontal cortex is poorly understood. Here we microstimulate sites in the superior temporal and ventral frontal cortex of monkeys and use functional magnetic resonance imaging to evaluate the functional activity resulting from the stimulation of interconnected regions. Surprisingly, we find that, although certain earlier stages of auditory cortical processing can strongly activate frontal cortex, downstream auditory regions, such as voice-sensitive cortex, appear to functionally engage primarily an ipsilateral temporal lobe network. Stimulating other sites within this activated temporal lobe network shows strong activation of frontal cortex. The results indicate that the relative stage of sensory processing does not predict the level of functional access to the frontal lobes. Rather, certain brain regions engage local networks, only parts of which have a strong functional impact on frontal cortex.

Multistage WDM access architecture employing cascaded AWGs

NASA Astrophysics Data System (ADS)

El-Nahal, F. I.; Mears, R. J.

2009-03-01

Here we propose passive/active arrayed waveguide gratings (AWGs) with enhanced performance for system applications mainly in novel access architectures employing cascaded AWG technology. Two technologies were considered to achieve space wavelength switching in these networks. Firstly, a passive AWG with semiconductor optical amplifiers array, and secondly, an active AWG. Active AWG is an AWG with an array of phase modulators on its arrayed-waveguides section, where a programmable linear phase-profile or a phase hologram is applied across the arrayed-waveguide section. This results in a wavelength shift at the output section of the AWG. These architectures can address up to 6912 customers employing only 24 wavelengths, coarsely separated by 1.6 nm. Simulation results obtained here demonstrate that cascaded AWGs access architectures have a great potential in future local area networks. Furthermore, they indicate for the first time that active AWGs architectures are more efficient in routing signals to the destination optical network units than passive AWG architectures.

Different forms of effective connectivity in primate frontotemporal pathways

PubMed Central

Petkov, Christopher I.; Kikuchi, Yukiko; Milne, Alice E.; Mishkin, Mortimer; Rauschecker, Josef P.; Logothetis, Nikos K.

2015-01-01

It is generally held that non-primary sensory regions of the brain have a strong impact on frontal cortex. However, the effective connectivity of pathways to frontal cortex is poorly understood. Here we microstimulate sites in the superior temporal and ventral frontal cortex of monkeys and use functional magnetic resonance imaging to evaluate the functional activity resulting from the stimulation of interconnected regions. Surprisingly, we find that, although certain earlier stages of auditory cortical processing can strongly activate frontal cortex, downstream auditory regions, such as voice-sensitive cortex, appear to functionally engage primarily an ipsilateral temporal lobe network. Stimulating other sites within this activated temporal lobe network shows strong activation of frontal cortex. The results indicate that the relative stage of sensory processing does not predict the level of functional access to the frontal lobes. Rather, certain brain regions engage local networks, only parts of which have a strong functional impact on frontal cortex. PMID:25613079

Non-Hermitian localization in biological networks.

PubMed

Amir, Ariel; Hatano, Naomichi; Nelson, David R

2016-04-01

We explore the spectra and localization properties of the N-site banded one-dimensional non-Hermitian random matrices that arise naturally in sparse neural networks. Approximately equal numbers of random excitatory and inhibitory connections lead to spatially localized eigenfunctions and an intricate eigenvalue spectrum in the complex plane that controls the spontaneous activity and induced response. A finite fraction of the eigenvalues condense onto the real or imaginary axes. For large N, the spectrum has remarkable symmetries not only with respect to reflections across the real and imaginary axes but also with respect to 90^{∘} rotations, with an unusual anisotropic divergence in the localization length near the origin. When chains with periodic boundary conditions become directed, with a systematic directional bias superimposed on the randomness, a hole centered on the origin opens up in the density-of-states in the complex plane. All states are extended on the rim of this hole, while the localized eigenvalues outside the hole are unchanged. The bias-dependent shape of this hole tracks the bias-independent contours of constant localization length. We treat the large-N limit by a combination of direct numerical diagonalization and using transfer matrices, an approach that allows us to exploit an electrostatic analogy connecting the "charges" embodied in the eigenvalue distribution with the contours of constant localization length. We show that similar results are obtained for more realistic neural networks that obey "Dale's law" (each site is purely excitatory or inhibitory) and conclude with perturbation theory results that describe the limit of large directional bias, when all states are extended. Related problems arise in random ecological networks and in chains of artificial cells with randomly coupled gene expression patterns.

Non-Hermitian localization in biological networks

NASA Astrophysics Data System (ADS)

Amir, Ariel; Hatano, Naomichi; Nelson, David R.

2016-04-01

We explore the spectra and localization properties of the N -site banded one-dimensional non-Hermitian random matrices that arise naturally in sparse neural networks. Approximately equal numbers of random excitatory and inhibitory connections lead to spatially localized eigenfunctions and an intricate eigenvalue spectrum in the complex plane that controls the spontaneous activity and induced response. A finite fraction of the eigenvalues condense onto the real or imaginary axes. For large N , the spectrum has remarkable symmetries not only with respect to reflections across the real and imaginary axes but also with respect to 90∘ rotations, with an unusual anisotropic divergence in the localization length near the origin. When chains with periodic boundary conditions become directed, with a systematic directional bias superimposed on the randomness, a hole centered on the origin opens up in the density-of-states in the complex plane. All states are extended on the rim of this hole, while the localized eigenvalues outside the hole are unchanged. The bias-dependent shape of this hole tracks the bias-independent contours of constant localization length. We treat the large-N limit by a combination of direct numerical diagonalization and using transfer matrices, an approach that allows us to exploit an electrostatic analogy connecting the "charges" embodied in the eigenvalue distribution with the contours of constant localization length. We show that similar results are obtained for more realistic neural networks that obey "Dale's law" (each site is purely excitatory or inhibitory) and conclude with perturbation theory results that describe the limit of large directional bias, when all states are extended. Related problems arise in random ecological networks and in chains of artificial cells with randomly coupled gene expression patterns.

Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks

DTIC Science & Technology

2014-03-31

Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks M.M. Asadi H. Mahboubi A...2014 Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks Contract Report # AMBUSH.1.1 Contract...pi j /= 0. The sensor network considered in this work is composed of underwater sensors , which use acoustic waves for

Promoting and developing a trail network across suburban, rural, and urban communities.

PubMed

Schasberger, Michele G; Hussa, Carol S; Polgar, Michael F; McMonagle, Julie A; Burke, Sharon J; Gegaris, Andrew J

2009-12-01

The Wyoming Valley Wellness Trails Partnership received an Active Living by Design grant late in 2003 for a project centered on a growing trail network linking urban, suburban, and rural communities in northeast Pennsylvania, a former coal region, in order to increase physical activity among residents. The partnership conducted research, collected information, created promotional documents, worked with partners on events and programs, and participated in trail planning. Local trail organizations continued planning and construction toward developing a trail network. Other partners spearheaded policy change in schools and worksites and worked toward downtown revitalization. The partnership assisted these efforts by providing a forum in which organizations could meet. The partnership became a central resource for information about local parks, trails, and outdoor recreational activities. The partnership increased awareness and use of recreational facilities. Trail partners constructed 22 miles of walking and biking trails. The partnership took advantage of an allied effort that created organizational capacity for wellness in schools and worksites. Messages promoting social and entertainment benefits of physical activity were more successful than those promoting health benefits. The existence of multiple small, independent trail organizations can help advance trail development through concurrent development efforts. Urban, suburban, and rural residents' conceptions of walkability may differ. Trails provide options for recreational and transportation-related physical activity across urban, suburban, and rural landscapes that are supported by all constituents. Trail builders can be strong allies in bringing active living to suburban and rural places.

Increased Global Interaction Across Functional Brain Modules During Cognitive Emotion Regulation.

PubMed

Brandl, Felix; Mulej Bratec, Satja; Xie, Xiyao; Wohlschläger, Afra M; Riedl, Valentin; Meng, Chun; Sorg, Christian

2017-07-13

Cognitive emotion regulation (CER) enables humans to flexibly modulate their emotions. While local theories of CER neurobiology suggest interactions between specialized local brain circuits underlying CER, e.g., in subparts of amygdala and medial prefrontal cortices (mPFC), global theories hypothesize global interaction increases among larger functional brain modules comprising local circuits. We tested the global CER hypothesis using graph-based whole-brain network analysis of functional MRI data during aversive emotional processing with and without CER. During CER, global between-module interaction across stable functional network modules increased. Global interaction increase was particularly driven by subregions of amygdala and cuneus-nodes of highest nodal participation-that overlapped with CER-specific local activations, and by mPFC and posterior cingulate as relevant connector hubs. Results provide evidence for the global nature of human CER, complementing functional specialization of embedded local brain circuits during successful CER. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

TexNet seismic network performance and reported seismicity in West Texas

NASA Astrophysics Data System (ADS)

Savvaidis, A.; Lomax, A.; Aiken, C.; Young, B.; Huang, D.; Hennings, P.

2017-12-01

In 2015, the Texas State Legislature began funding the Texas Seismological Network (TexNet). Since then, 22 new permanent broadband three-component seismic stations have been added to 17 existing stations operated by various networks [US, N4, IM]. These stations together with 4 auxiliary stations, i.e. long term deployments of 20 sec portable stations, were deployed to provide a baseline of Texas seismicity. As soon as the deployment of the new permanent stations took place in West Texas, TexNet was able to detect and characterize smaller magnitude events than was possible before, i.e. M < 2.5. As a consequence, additional portable stations were installed in the area in order to better map the current seismicity level. During the different stages of station deployment, we monitored the seismic network performance and its ability to detect earthquake activity. We found that a key limitation to the network performance is industrial noise in West Texas. For example, during daytime, phase picking and event detection rates are much lower than during nighttime at noisy sites. Regarding seismicity, the high density portable station deployment close to the earthquake activity minimizes hypocentral location uncertainties. In addition, we examined the effects of different crustal velocity models in the area of study on hypocentral location using the local network first arrivals. Considerable differences in location were obtained, which shows the importance of local networks and/or reliable crustal velocity models for West Texas. Given the levels of seismicity in West Texas, a plan to continuously monitor the study area is under development.

A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks

PubMed Central

Sweeney, Yann; Hellgren Kotaleski, Jeanette; Hennig, Matthias H.

2015-01-01

Gaseous neurotransmitters such as nitric oxide (NO) provide a unique and often overlooked mechanism for neurons to communicate through diffusion within a network, independent of synaptic connectivity. NO provides homeostatic control of intrinsic excitability. Here we conduct a theoretical investigation of the distinguishing roles of NO-mediated diffusive homeostasis in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis provide a robust mechanism for maintaining stable activity following perturbations. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that these properties are preserved when homeostatic and Hebbian plasticity are combined. These results suggest a mechanism for dynamically maintaining neural heterogeneity, and expose computational advantages of non-local homeostatic processes. PMID:26158556

Physical activity discrimination improvement using accelerometers and wireless sensor network localization - biomed 2013.

PubMed

Bashford, Gregory R; Burnfield, Judith M; Perez, Lance C

2013-01-01

Automating documentation of physical activity data (e.g., duration and speed of walking or propelling a wheelchair) into the electronic medical record (EMR) offers promise for improving efficiency of documentation and understanding of best practices in the rehabilitation and home health settings. Commercially available devices which could be used to automate documentation of physical activities are either cumbersome to wear or lack the specificity required to differentiate activities. We have designed a novel system to differentiate and quantify physical activities, using inexpensive accelerometer-based biomechanical data technology and wireless sensor networks, a technology combination that has not been used in a rehabilitation setting to date. As a first step, a feasibility study was performed where 14 healthy young adults (mean age = 22.6 ± 2.5 years, mean height = 173 ± 10.0 cm, mean mass = 70.7 ± 11.3 kg) carried out eight different activities while wearing a biaxial accelerometer sensor. Activities were performed at each participant’s self-selected pace during a single testing session in a controlled environment. Linear discriminant analysis was performed by extracting spectral parameters from the subjects’ accelerometer patterns. It is shown that physical activity classification alone results in an average accuracy of 49.5%, but when combined with rule-based constraints using a wireless sensor network with localization capabilities in an in silico simulated room, accuracy improves to 99.3%. When fully implemented, our technology package is expected to improve goal setting, treatment interventions and patient outcomes by enhancing clinicians’ understanding of patients’ physical performance within a day and across the rehabilitation program.

Our Selections and Decisions: Inherent Features of the Nervous System?

NASA Astrophysics Data System (ADS)

Rösler, Frank

The chapter summarizes findings on the neuronal bases of decisionmaking. Taking the phenomenon of selection it will be explained that systems built only from excitatory and inhibitory neuron (populations) have the emergent property of selecting between different alternatives. These considerations suggest that there exists a hierarchical architecture with central selection switches. However, in such a system, functions of selection and decision-making are not localized, but rather emerge from an interaction of several participating networks. These are, on the one hand, networks that process specific input and output representations and, on the other hand, networks that regulate the relative activation/inhibition of the specific input and output networks. These ideas are supported by recent empirical evidence. Moreover, other studies show that rather complex psychological variables, like subjective probability estimates, expected gains and losses, prediction errors, etc., do have biological correlates, i.e., they can be localized in time and space as activation states of neural networks and single cells. These findings suggest that selections and decisions are consequences of an architecture which, seen from a biological perspective, is fully deterministic. However, a transposition of such nomothetic functional principles into the idiographic domain, i.e., using them as elements for comprehensive 'mechanistic' explanations of individual decisions, seems not to be possible because of principle limitations. Therefore, individual decisions will remain predictable by means of probabilistic models alone.

Intrinsic and Extrinsic Neuromodulation of Olfactory Processing.

PubMed

Lizbinski, Kristyn M; Dacks, Andrew M

2017-01-01

Neuromodulation is a ubiquitous feature of neural systems, allowing flexible, context specific control over network dynamics. Neuromodulation was first described in invertebrate motor systems and early work established a basic dichotomy for neuromodulation as having either an intrinsic origin (i.e., neurons that participate in network coding) or an extrinsic origin (i.e., neurons from independent networks). In this conceptual dichotomy, intrinsic sources of neuromodulation provide a "memory" by adjusting network dynamics based upon previous and ongoing activation of the network itself, while extrinsic neuromodulators provide the context of ongoing activity of other neural networks. Although this dichotomy has been thoroughly considered in motor systems, it has received far less attention in sensory systems. In this review, we discuss intrinsic and extrinsic modulation in the context of olfactory processing in invertebrate and vertebrate model systems. We begin by discussing presynaptic modulation of olfactory sensory neurons by local interneurons (LNs) as a mechanism for gain control based on ongoing network activation. We then discuss the cell-class specific effects of serotonergic centrifugal neurons on olfactory processing. Finally, we briefly discuss the integration of intrinsic and extrinsic neuromodulation (metamodulation) as an effective mechanism for exerting global control over olfactory network dynamics. The heterogeneous nature of neuromodulation is a recurring theme throughout this review as the effects of both intrinsic and extrinsic modulation are generally non-uniform.

75 FR 19988 - Watercress Darter National Wildlife Refuge, Jefferson County, AL

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-16

... prominent as development activities occur in the city of Bessemer, Alabama. Watercress Darter NWR is a small.... Extensive resource sharing and networking with other protected areas, State and local government agencies...

Promoting active living in healthy cities of Europe.

PubMed

Faskunger, Johan

2013-10-01

Local governments in Europe have a vital role in promoting physical activity in the daily life of citizens. However, explicit investment in active living has been limited. One of the four core themes for Phase IV (2003-2008) of the World Health Organization (WHO) European Healthy Cities Network (WHO-EHCN) was to encourage local governments and their partners to implement programs in favor of active living. This study analyzes the performance of network cities during this period. Responses to a general evaluation questionnaire are analyzed by content according to a checklist, and categorized into themes and dimensions. Most cities viewed "active living" as an important issue for urban planning; to improve visual appeal, enhance social cohesion, create a more sustainable transport system to promote walkability and cyclability and to reduce inequalities in public health. Almost all member cities reported on existing policies that support the promotion of active living. However, only eight (of the 59) responding cities mentioned an integrated framework specific for active living. Many efforts to promote active living are nested in programs to prevent obesity among adults or children. Future challenges include establishing integrated policies specifically for active living, introducing a larger range of actions, as well as increasing funding and capacity to make a difference at the population level.

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

Earthquakes: Natural Science Museum and Civil Protection of Trento to inform citizens

NASA Astrophysics Data System (ADS)

Lauro, Claudia; Avanzini, Marco

2010-05-01

During 2009 the Natural Science Museum of Trento organized the exhibition "Attraction Earth: Earthquakes and Terrestrial Magnetism" in collaboration with the INGV (Italian National Institute of Geophysic and Volcanology). In this exhibition a particular sector has been devoted to the seismic activity and its monitoring in the Province of Trento. The purpose was to inform local people on the geological features of their territory, the monitoring activity carried out by the Civil Protection and the potential earthquake hazards, also in order to adopt a correct behaviour in case of seismic event. This sector, "The seismometric Trentino network", was organized by the Geological Service of the Trento Civil Protection and it is open till May 2010, both for general public and school students. For the latter, a particular education pack, realized by the Educational Department of the Museum and consisting of a guided tour coupled with the laboratory activity "Waves upside-down: seismology", is proposed. The whole exhibition has been also coupled with a cycle conferences targeted to adults, in which these topics have been explained by researchers and technicians of INGV and of Trento Geological Service. "The seismometric Trentino network" sector presents the daily monitoring activity of the Geological Service, that has been monitoring the seismic activity for the last 30 years, and describes the deep earth processes of the local territory, such as presence of tectonic discontinuities and their activity. It consists of display panels, a seismometer with rotating drums and a multimedia that reports the monitoring activity of the seismometric network, with real time connection to the various monitoring stations. This allows visitors to observe instantly the local seismic events recorded by each station. The seismometric network was established by the institutions of Trento Province after the earthquakes occurred in Friuli Venezia-Giulia and at Riva del Garda (1976). It started its activity in 1981 and consists of 7 stations equipped with seismometers and acquisition digital technology, working 24 hours per day. Moreover, a network of 9 accelerometers has been set up in the southern Trentino, where most of the seismic events are concentrated. All the information revealed in each station flow to the "Data Acquisition Central Office", where the data are checked, processed and recorded. The Geological Service manages the seismometric network, elaborates and publishes the information regarding the seismicity of the area and surroundings. In case of earthquake the "Seismic Alert", an automatic alarm system, is activated to Civil Protection purposes. The "Seismic Alert" is managed by "Antilope", the consortium of the Eastern Alpine seismometric networks. Moreover the seismotectonic is another research field carried out by this Geological Service, to investigate the formation mechanism of earthquakes and estimate the causative tectonic stress, in relation to the main tectonic structures of the region and of the whole Alpine chain. Hence the Trento study-case reported in this exhibition illustrates the general methodology used to understand the "seismic behaviour" of a region. At the end this exhibition sector also presents the activity of the Trento Civil Protection in the Abruzzo region, where a dramatic seismic event occurred on 6th April 2009, describing the investigation of the still occurring surface deformations. This activity is part of a general framework in which the Trento Province provided first aid and assistance to the local communities. The collaboration between the Natural Science Tridentino Museum and the Geological Service of Trento, already fruitful on field geological researches, has been also effective in this project of science communication. In the future the two institutions could collaborate in other main themes of the relationship between science and society, regarding the dissemination of Earth Sciences.

A Navy Shore Activity Manpower Planning System for Civilians. Technical Report No. 24.

ERIC Educational Resources Information Center

Niehaus, R. J.; Sholtz, D.

This report describes the U.S. Navy Shore Activity Manpower Planning System (SAMPS) advanced development research project. This effort is aimed at large-scale feasibility tests of manpower models for large Naval installations. These local planning systems are integrated with Navy-wide information systems on a data-communications network accessible…

Acoustic Source Localization via Time Difference of Arrival Estimation for Distributed Sensor Networks Using Tera-Scale Optical Core Devices

DOE PAGES

Imam, Neena; Barhen, Jacob

2009-01-01

For real-time acoustic source localization applications, one of the primary challenges is the considerable growth in computational complexity associated with the emergence of ever larger, active or passive, distributed sensor networks. These sensors rely heavily on battery-operated system components to achieve highly functional automation in signal and information processing. In order to keep communication requirements minimal, it is desirable to perform as much processing on the receiver platforms as possible. However, the complexity of the calculations needed to achieve accurate source localization increases dramatically with the size of sensor arrays, resulting in substantial growth of computational requirements that cannot bemore » readily met with standard hardware. One option to meet this challenge builds upon the emergence of digital optical-core devices. The objective of this work was to explore the implementation of key building block algorithms used in underwater source localization on the optical-core digital processing platform recently introduced by Lenslet Inc. This demonstration of considerably faster signal processing capability should be of substantial significance to the design and innovation of future generations of distributed sensor networks.« less

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks

PubMed Central

Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

2015-01-01

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns. PMID:26291608

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.

PubMed

Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

2015-08-01

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns.

How to include public health practice and practitioners in a European Network.

PubMed

Brusaferro, Silvio; Tricarico, Pierfrancesco

2017-10-01

There is a wide range of different Public Health (PH) activities and programs running in Europe. Besides the richness of national traditions, differences exist in numbers of programs, methods adopted, types of engaged professionals, available resources (including public investments), awareness to the problem and finally in health indicators among and within countries. Promoting networks of PH practices and practitioners strengthens the possibility to share knowledge across organizational, sectorial and geographic boundaries, promotes adaptation and local implementation, fosters innovation in the form of knowledge creation by developing more efficient new services and by sharing effective practices within and between organizations and sectors. Nevertheless, strengthening existing networks and promoting new ones requires coordinated efforts based on complex adaptive systems and network science rules, along with the engagement of local, national and European health authorities. Given these premises, networking promotion and development is a promising way to improve health and wealth to European citizens and communities. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Handedness- and brain size-related efficiency differences in small-world brain networks: a resting-state functional magnetic resonance imaging study.

PubMed

Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu

2015-05-01

The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical regions. Graph theory-based methods were employed to further analyze their topological properties. As expected, all participants demonstrated small-world topology, suggesting a highly efficient topological structure. Furthermore, we found that smaller brains showed higher local efficiency, whereas larger brains showed higher global efficiency, reflecting a suitable efficiency balance between local specialization and global integration of brain functional activity. Compared with right-handers, significant alterations in nodal efficiency were revealed in left-handers, involving the anterior and median cingulate gyrus, middle temporal gyrus, angular gyrus, and amygdala. Our findings indicated that the functional network organization in the human brain was associated with handedness and brain size.

Competition between global and local online social networks

NASA Astrophysics Data System (ADS)

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-01

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Competition between global and local online social networks.

PubMed

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-27

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Different propagation speeds of recalled sequences in plastic spiking neural networks

NASA Astrophysics Data System (ADS)

Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

2015-03-01

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

PubMed Central

2017-01-01

Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs) for robust movement decoding of Parkinson's disease (PD) and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value) at about 0.729 ± 0.16 for decoding movement from the resting state and about 0.671 ± 0.14 for decoding left and right visually cued movements. PMID:29201041

Multiple μ-stability of neural networks with unbounded time-varying delays.

PubMed

Wang, Lili; Chen, Tianping

2014-05-01

In this paper, we are concerned with a class of recurrent neural networks with unbounded time-varying delays. Based on the geometrical configuration of activation functions, the phase space R(n) can be divided into several Φη-type subsets. Accordingly, a new set of regions Ωη are proposed, and rigorous mathematical analysis is provided to derive the existence of equilibrium point and its local μ-stability in each Ωη. It concludes that the n-dimensional neural networks can exhibit at least 3(n) equilibrium points and 2(n) of them are μ-stable. Furthermore, due to the compatible property, a set of new conditions are presented to address the dynamics in the remaining 3(n)-2(n) subset regions. As direct applications of these results, we can get some criteria on the multiple exponential stability, multiple power stability, multiple log-stability, multiple log-log-stability and so on. In addition, the approach and results can also be extended to the neural networks with K-level nonlinear activation functions and unbounded time-varying delays, in which there can store (2K+1)(n) equilibrium points, (K+1)(n) of them are locally μ-stable. Numerical examples are given to illustrate the effectiveness of our results. Copyright © 2014 Elsevier Ltd. All rights reserved.

Local excitation-inhibition ratio for synfire chain propagation in feed-forward neuronal networks

NASA Astrophysics Data System (ADS)

Guo, Xinmeng; Yu, Haitao; Wang, Jiang; Liu, Jing; Cao, Yibin; Deng, Bin

2017-09-01

A leading hypothesis holds that spiking activity propagates along neuronal sub-populations which are connected in a feed-forward manner, and the propagation efficiency would be affected by the dynamics of sub-populations. In this paper, how the interaction between local excitation and inhibition effects on synfire chain propagation in feed-forward network (FFN) is investigated. The simulation results show that there is an appropriate excitation-inhibition (EI) ratio maximizing the performance of synfire chain propagation. The optimal EI ratio can significantly enhance the selectivity of FFN to synchronous signals, which thereby increases the stability to background noise. Moreover, the effect of network topology on synfire chain propagation is also investigated. It is found that synfire chain propagation can be maximized by an optimal interlayer linking probability. We also find that external noise is detrimental to synchrony propagation by inducing spiking jitter. The results presented in this paper may provide insights into the effects of network dynamics on neuronal computations.

43 CFR 2806.43 - How does BLM calculate rent for passive reflectors and local exchange networks?

Code of Federal Regulations, 2011 CFR

2011-10-01

... reflectors and local exchange networks? 2806.43 Section 2806.43 Public Lands: Interior Regulations Relating...-Of-Way § 2806.43 How does BLM calculate rent for passive reflectors and local exchange networks? (a) BLM calculates rent for passive reflectors and local exchange networks by using the same rent...

Introduction to Local Area Networks for Microcomputers — Characteristics, Costs, Implementation Considerations

PubMed Central

Haney, James P.

1984-01-01

The essence of a local area network (LAN) is that the whole is greater than the sum of its parts. A local area network can save in hardware costs when expensive peripherals are shared; it can save time when large blocks of data are rapidly exchanged among users. The need for more cost-effective and capable communications has inspired the emergence of rapidly developing markets and technologies for local area networks. The purpose of this paper is to provide an understanding of the characteristics, components, costs, and implementation considerations of local area networks. The paper does not compare or define specific vendor offerings; however, recent IBM announcements regarding local area networks are summarized in the last section of the paper.

Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

1997-01-01

A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

Multisector Health Policy Networks in 15 Large US Cities.

PubMed

Harris, Jenine K; Leider, J P; Carothers, Bobbi J; Castrucci, Brian C; Hearne, Shelley

2016-01-01

Local health departments (LHDs) have historically not prioritized policy development, although it is one of the 3 core areas they address. One strategy that may influence policy in LHD jurisdictions is the formation of partnerships across sectors to work together on local public health policy. We used a network approach to examine LHD local health policy partnerships across 15 large cities from the Big Cities Health Coalition. We surveyed the health departments and their partners about their working relationships in 5 policy areas: core local funding, tobacco control, obesity and chronic disease, violence and injury prevention, and infant mortality. Drawing on prior literature linking network structures with performance, we examined network density, transitivity, centralization and centrality, member diversity, and assortativity of ties. Networks included an average of 21.8 organizations. Nonprofits and government agencies made up the largest proportions of the networks, with 28.8% and 21.7% of network members, whereas for-profits and foundations made up the smallest proportions in all of the networks, with just 1.2% and 2.4% on average. Mean values of density, transitivity, diversity, assortativity, centralization, and centrality showed similarity across policy areas and most LHDs. The tobacco control and obesity/chronic disease networks were densest and most diverse, whereas the infant mortality policy networks were the most centralized and had the highest assortativity. Core local funding policy networks had lower scores than other policy area networks by most network measures. Urban LHDs partner with organizations from diverse sectors to conduct local public health policy work. Network structures are similar across policy areas jurisdictions. Obesity and chronic disease, tobacco control, and infant mortality networks had structures consistent with higher performing networks, whereas core local funding networks had structures consistent with lower performing networks.

Multisector Health Policy Networks in 15 Large US Cities

PubMed Central

Leider, J. P.; Carothers, Bobbi J.; Castrucci, Brian C.; Hearne, Shelley

2016-01-01

Context: Local health departments (LHDs) have historically not prioritized policy development, although it is one of the 3 core areas they address. One strategy that may influence policy in LHD jurisdictions is the formation of partnerships across sectors to work together on local public health policy. Design: We used a network approach to examine LHD local health policy partnerships across 15 large cities from the Big Cities Health Coalition. Setting/Participants: We surveyed the health departments and their partners about their working relationships in 5 policy areas: core local funding, tobacco control, obesity and chronic disease, violence and injury prevention, and infant mortality. Outcome Measures: Drawing on prior literature linking network structures with performance, we examined network density, transitivity, centralization and centrality, member diversity, and assortativity of ties. Results: Networks included an average of 21.8 organizations. Nonprofits and government agencies made up the largest proportions of the networks, with 28.8% and 21.7% of network members, whereas for-profits and foundations made up the smallest proportions in all of the networks, with just 1.2% and 2.4% on average. Mean values of density, transitivity, diversity, assortativity, centralization, and centrality showed similarity across policy areas and most LHDs. The tobacco control and obesity/chronic disease networks were densest and most diverse, whereas the infant mortality policy networks were the most centralized and had the highest assortativity. Core local funding policy networks had lower scores than other policy area networks by most network measures. Conclusion: Urban LHDs partner with organizations from diverse sectors to conduct local public health policy work. Network structures are similar across policy areas jurisdictions. Obesity and chronic disease, tobacco control, and infant mortality networks had structures consistent with higher performing networks, whereas core local funding networks had structures consistent with lower performing networks. PMID:26910868

Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks

PubMed Central

Garcia-Herranz, Manuel; Moro, Esteban; Cebrian, Manuel; Christakis, Nicholas A.; Fowler, James H.

2014-01-01

Recent research has focused on the monitoring of global–scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global–scale networks. PMID:24718030

Using friends as sensors to detect global-scale contagious outbreaks.

PubMed

Garcia-Herranz, Manuel; Moro, Esteban; Cebrian, Manuel; Christakis, Nicholas A; Fowler, James H

2014-01-01

Recent research has focused on the monitoring of global-scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global-scale networks.

The Prevention Research Centers Healthy Aging Research Network.

PubMed

Lang, Jason E; Anderson, Lynda; LoGerfo, James; Sharkey, Joseph; Belansky, Elaine; Bryant, Lucinda; Prohaska, Tom; Altpeter, Mary; Marshall, Victor; Satariano, William; Ivey, Susan; Bayles, Constance; Pluto, Delores; Wilcox, Sara; Goins, R Turner; Byrd, Robert C

2006-01-01

The Prevention Research Centers Healthy Aging Research Network (PRC-HAN), funded by the Centers for Disease Control and Prevention's (CDC's) Healthy Aging program, was created in 2001 to help develop partnerships and create a research agenda that promotes healthy aging. The nine universities that participate in the network use their expertise in aging research to collaborate with their communities and other partners to develop and implement health promotion interventions for older adults at the individual, organizational, environmental, and policy levels. The population of older adults in the United States is growing rapidly; approximately 20% of Americans will be aged 65 years or older by 2030. The health and economic impact of an aging society compel the CDC and the public health community to place increased emphasis on preventing unnecessary disease, disability, and injury among older Americans. The PRC-HAN has a broad research agenda that addresses health-promoting skills and behaviors, disease and syndrome topics, and knowledge domains. The network chose physical activity for older adults as its initial focus for research and has initiated two networkwide projects: a comprehensive, multisite survey that collected information on the capacity, content, and accessibility of physical activity programs for older adults and a peer-reviewed publication that describes the role of public health in promoting physical activity among older adults. In addition to participating in the core research area, each network member works independently with its community committee on PRC-HAN activities. As a result, the network is 1) expanding prevention research for older adults and their communities; 2) promoting the translation and dissemination of findings to key stakeholders; 3) strengthening PRC-HAN capacity through partnerships and expanded funding; and 4) stimulating the adoption of policies and programs by engaging policymakers, planners, and practitioners. In 2003, the PRC-HAN initiated an internal evaluation to better define the network's contributions to healthy aging, formalize internal processes, and better equip itself to serve as a model for other PRC thematic networks. The PRC-HAN is conducting a pilot evaluation for eventual inclusion in the PRC national evaluation. The PRC-HAN has established itself as an effective research network to promote healthy aging. It has developed trust and mutual respect among participants, forged strong ties to local communities, and shown the ability to combine its expertise in healthy aging with that of partners in national, state, and local organizations.

Temporal Interactions between Cortical Rhythms

PubMed Central

Roopun, Anita K.; Kramer, Mark A.; Carracedo, Lucy M.; Kaiser, Marcus; Davies, Ceri H.; Traub, Roger D.; Kopell, Nancy J.; Whittington, Miles A.

2008-01-01

Multiple local neuronal circuits support different, discrete frequencies of network rhythm in neocortex. Relationships between different frequencies correspond to mechanisms designed to minimise interference, couple activity via stable phase interactions, and control the amplitude of one frequency relative to the phase of another. These mechanisms are proposed to form a framework for spectral information processing. Individual local circuits can also transform their frequency through changes in intrinsic neuronal properties and interactions with other oscillating microcircuits. Here we discuss a frequency transformation in which activity in two co-active local circuits may combine sequentially to generate a third frequency whose period is the concatenation sum of the original two. With such an interaction, the intrinsic periodicity in each component local circuit is preserved – alternate, single periods of each original rhythm form one period of a new frequency – suggesting a robust mechanism for combining information processed on multiple concurrent spatiotemporal scales. PMID:19225587

Network of European regions using space technologies an update on the NEREUS constitution

NASA Astrophysics Data System (ADS)

Morelli, Marianna; Campostrini, Pierpaolo

2010-01-01

The EU and ESA space research and development programmes give a consolidated model for international cooperation. They represent a good framework to develop and enhance different initiatives at global, regional and local level. The impact of space activities covers different areas of interest such as: the development of Earth observation applications for environment monitoring and risk prevention and management, the development of satellite communications and information systems, the exploitation of global satellite positioning and navigation systems, the knowledge of the Universe, the utilisation of ground segment engineering. These activities involve also the regional and local governments. This is particularly evident if we look at the competences of the European regional governments. Several European regions deal with a number of issues in areas linked to space activities. In line with these reflections a number of European regional governments supported by the Committee of the Regions launched the idea to create a Network of European Regions Using Space technologies—NEREUS. This Network is an International non-profit association (AISBL— Association International Sans But Lucratif) under Belgian law. The aim of this paper is to review the course of the initiative since its launch in April 2006, giving an update of the work done for its constitution.

Balanced Cortical Microcircuitry for Spatial Working Memory Based on Corrective Feedback Control

PubMed Central

2014-01-01

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory–inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. PMID:24828633

Local-Area-Network Simulator

NASA Technical Reports Server (NTRS)

Gibson, Jim; Jordan, Joe; Grant, Terry

1990-01-01

Local Area Network Extensible Simulator (LANES) computer program provides method for simulating performance of high-speed local-area-network (LAN) technology. Developed as design and analysis software tool for networking computers on board proposed Space Station. Load, network, link, and physical layers of layered network architecture all modeled. Mathematically models according to different lower-layer protocols: Fiber Distributed Data Interface (FDDI) and Star*Bus. Written in FORTRAN 77.

How to Compress Sequential Memory Patterns into Periodic Oscillations: General Reduction Rules

PubMed Central

Zhang, Kechen

2017-01-01

A neural network with symmetric reciprocal connections always admits a Lyapunov function, whose minima correspond to the memory states stored in the network. Networks with suitable asymmetric connections can store and retrieve a sequence of memory patterns, but the dynamics of these networks cannot be characterized as readily as that of the symmetric networks due to the lack of established general methods. Here, a reduction method is developed for a class of asymmetric attractor networks that store sequences of activity patterns as associative memories, as in a Hopfield network. The method projects the original activity pattern of the network to a low-dimensional space such that sequential memory retrievals in the original network correspond to periodic oscillations in the reduced system. The reduced system is self-contained and provides quantitative information about the stability and speed of sequential memory retrievals in the original network. The time evolution of the overlaps between the network state and the stored memory patterns can also be determined from extended reduced systems. The reduction procedure can be summarized by a few reduction rules, which are applied to several network models, including coupled networks and networks with time-delayed connections, and the analytical solutions of the reduced systems are confirmed by numerical simulations of the original networks. Finally, a local learning rule that provides an approximation to the connection weights involving the pseudoinverse is also presented. PMID:24877729

Ultra-thin microporous/hybrid materials

DOEpatents

Jiang, Ying-Bing [Albuquerque, NM; Cecchi, Joseph L [Albuquerque, NM; Brinker, C Jeffrey [Albuquerque, NM

2012-05-29

Ultra-thin hybrid and/or microporous materials and methods for their fabrication are provided. In one embodiment, the exemplary hybrid membranes can be formed including successive surface activation and reaction steps on a porous support that is patterned or non-patterned. The surface activation can be performed using remote plasma exposure to locally activate the exterior surfaces of porous support. Organic/inorganic hybrid precursors such as organometallic silane precursors can be condensed on the locally activated exterior surfaces, whereby ALD reactions can then take place between the condensed hybrid precursors and a reactant. Various embodiments can also include an intermittent replacement of ALD precursors during the membrane formation so as to enhance the hybrid molecular network of the membranes.

Spatial spreading of infectious disease via local and national mobility networks in South Korea

NASA Astrophysics Data System (ADS)

Kwon, Okyu; Son, Woo-Sik

2017-12-01

We study the spread of infectious disease based on local- and national-scale mobility networks. We construct a local mobility network using data on urban bus services to estimate local-scale movement of people. We also construct a national mobility network from orientation-destination data of vehicular traffic between highway tollgates to evaluate national-scale movement of people. A metapopulation model is used to simulate the spread of epidemics. Thus, the number of infected people is simulated using a susceptible-infectious-recovered (SIR) model within the administrative division, and inter-division spread of infected people is determined through local and national mobility networks. In this paper, we consider two scenarios for epidemic spread. In the first, the infectious disease only spreads through local-scale movement of people, that is, the local mobility network. In the second, it spreads via both local and national mobility networks. For the former, the simulation results show infected people sequentially spread to neighboring divisions. Yet for the latter, we observe a faster spreading pattern to distant divisions. Thus, we confirm the national mobility network enhances synchronization among the incidence profiles of all administrative divisions.

The Alaska Volcano Observatory - Expanded Monitoring of Volcanoes Yields Results

USGS Publications Warehouse

Brantley, Steven R.; McGimsey, Robert G.; Neal, Christina A.

2004-01-01

Recent explosive eruptions at some of Alaska's 52 historically active volcanoes have significantly affected air traffic over the North Pacific, as well as Alaska's oil, power, and fishing industries and local communities. Since its founding in the late 1980s, the Alaska Volcano Observatory (AVO) has installed new monitoring networks and used satellite data to track activity at Alaska's volcanoes, providing timely warnings and monitoring of frequent eruptions to the aviation industry and the general public. To minimize impacts from future eruptions, scientists at AVO continue to assess volcano hazards and to expand monitoring networks.

Induction of c-Fos immunoreactivity in the amygdala of mice expressing anxiety-like behavior after local perfusion of veratrine in the prelimbic medial prefrontal cortex.

PubMed

Yamada, Misa; Saitoh, Akiyoshi; Ohashi, Masanori; Suzuki, Satoshi; Oka, Jun-Ichiro; Yamada, Mitsuhiko

2015-08-01

Local perfusion of the sodium channel activator veratrine in mouse prelimbic medial prefrontal cortex (PL) induced c-Fos immunoreactivity in the sub-regions of amygdala. Co-perfusion of the NMDA receptor antagonist MK-801 diminished the c-Fos expression. Significant correlations were observed between c-Fos immunoreactivity and behavioral measures in the open-field test. The PL stimulation activates a neural network projecting to the amygdala via NMDA receptor-mediated glutamatergic neurotransmission. Anxiety-like behavior induced after the PL stimulation may be partly mediated through the activation of amygdala.

Past, present and future improvements of the efficiency of the local seismic network of the geothermal reservoir of Casaglia, Ferrara (North Italy)

NASA Astrophysics Data System (ADS)

Abu Zeid, Nasser; Dall'olio, Lorella; Bignardi, Samuel; Santarato, Giovanni

2017-04-01

The microseismic network of Ferrara was established, in the beginning of 1990 and started its monitoring activity few months before the start of reservoir exploitation, for residential and industrial heating purposes, of the Casaglia geothermal site characterised by fluids of 100 °C: February 1990. The purpose was to monitor the natural seismicity so as to be able to discriminate it from possible induced ones due to exploitation activities which consists of a closed loop system composed of three boreholes: one for re-injection "Casaglia001" and two for pumping hot fluids. The microseismic network started, and still today, its monitoring activities with five vertical 2 Hz and one 3D seismometers model Mark products L4A/C distributed at reciprocal distances of about 5 to 7 km around the reservoir covering an area of 100 km^2. Since its beginning the monitoring activities proceeded almost continuously. However, due to technological limitations of the network HW, although sufficient to capture small magnitude earthquakes (near zero), the exponential increase of anthropogenic and electromagnetic noise degraded the monitoring capability of the network especially for small ones. To this end and as of 2007, the network control passed to the University of Ferrara, Department of Physics and Earth Sciences, the network HD for digitalisation and continuous data transmission was replaced with GURALP equipment's.. Since its establishment, few earthquakes occurred in the geothermal area with Ml < 1.5 and hypocentre depth > 5 km. However, following the Emilia sequence of 2012, and as an example we present and discuss the local earthquake (Ml 2.5) occurred in Casaglia (Ferrara, Italy) on September 3, 2015, in the vicinity of the borehole Casaglia1 used for fluid re-injection. In this case, both INGV national network and OGS NE-Italy regional networks provided similar information, with hypocenter at about 5-6 km North of the reservoir edge and about 16 km of depth. However, the same event, relocated by using also the microseismic data, felt within the reservoir area at 4-5 km depth, i.e. close to the geothermal reservoir. Still problems related to anthropogenic noise still present hence future improvements shall include the deepening of the existing boreholes to at least 100 m and the replacement of the seismometers with at least 1 Hz modern ones. Moreover, at least two or three stations shall be installed to fully be in line with recent Italian Guidelines that discipline the monitoring of industrial activities that exploits the subsurface.

Non ictal onset zone: A window to ictal dynamics.

PubMed

Afra, Pegah; Hanrahan, Sara J; Kellis, Spencer Sterling; House, Paul

2017-01-01

The focal and network concepts of epilepsy present different aspects of electroclinical phenomenon of seizures. Here, we present a 23-year-old man undergoing surgical evaluation with left fronto-temporal electrocorticography (ECoG) and microelectrode-array (MEA) in the middle temporal gyrus (MTG). We compare action-potential (AP) and local field potentials (LFP) recorded from MEA with ECoG. Seizure onset in the mesial-temporal lobe was characterized by changes in the pattern of AP-firing without clear changes in LFP or ECoG in MTG. This suggests simultaneous analysis of neuronal activity in differing spatial scales and frequency ranges provide complementary insights into how focal and network neurophysiological activity contribute to ictal activity.

Role of inhibitory control in modulating focal seizure spread.

PubMed

Liou, Jyun-You; Ma, Hongtao; Wenzel, Michael; Zhao, Mingrui; Baird-Daniel, Eliza; Smith, Elliot H; Daniel, Andy; Emerson, Ronald; Yuste, Rafael; Schwartz, Theodore H; Schevon, Catherine A

2018-05-10

Focal seizure propagation is classically thought to be spatially contiguous. However, distribution of seizures through a large-scale epileptic network has been theorized. Here, we used a multielectrode array, wide field calcium imaging, and two-photon calcium imaging to study focal seizure propagation pathways in an acute rodent neocortical 4-aminopyridine model. Although ictal neuronal bursts did not propagate beyond a 2-3-mm region, they were associated with hemisphere-wide field potential fluctuations and parvalbumin-positive interneuron activity outside the seizure focus. While bicuculline surface application enhanced contiguous seizure propagation, focal bicuculline microinjection at sites distant to the 4-aminopyridine focus resulted in epileptic network formation with maximal activity at the two foci. Our study suggests that both classical and epileptic network propagation can arise from localized inhibition defects, and that the network appearance can arise in the context of normal brain structure without requirement for pathological connectivity changes between sites.

Neuroendocrine and immune network re-modeling in chronic fatigue syndrome: an exploratory analysis.

PubMed

Fuite, Jim; Vernon, Suzanne D; Broderick, Gordon

2008-12-01

This work investigates the significance of changes in association patterns linking indicators of neuroendocrine and immune activity in patients with chronic fatigue syndrome (CFS). Gene sets preferentially expressed in specific immune cell isolates were integrated with neuroendocrine data from a large population-based study. Co-expression patterns linking immune cell activity with hypothalamic-pituitary-adrenal (HPA), thyroidal (HPT) and gonadal (HPG) axis status were computed using mutual information criteria. Networks in control and CFS subjects were compared globally in terms of a weighted graph edit distance. Local re-modeling of node connectivity was quantified by node degree and eigenvector centrality measures. Results indicate statistically significant differences between CFS and control networks determined mainly by re-modeling around pituitary and thyroid nodes as well as an emergent immune sub-network. Findings align with known mechanisms of chronic inflammation and support possible immune-mediated loss of thyroid function in CFS exacerbated by blunted HPA axis responsiveness.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

PubMed

Reimann, Michael W; Nolte, Max; Scolamiero, Martina; Turner, Katharine; Perin, Rodrigo; Chindemi, Giuseppe; Dłotko, Paweł; Levi, Ran; Hess, Kathryn; Markram, Henry

2017-01-01

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

A New Stochastic Technique for Painlevé Equation-I Using Neural Network Optimized with Swarm Intelligence

PubMed Central

Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Ahmad, Siraj-ul-Islam; Qureshi, Ijaz Mansoor

2012-01-01

A methodology for solution of Painlevé equation-I is presented using computational intelligence technique based on neural networks and particle swarm optimization hybridized with active set algorithm. The mathematical model of the equation is developed with the help of linear combination of feed-forward artificial neural networks that define the unsupervised error of the model. This error is minimized subject to the availability of appropriate weights of the networks. The learning of the weights is carried out using particle swarm optimization algorithm used as a tool for viable global search method, hybridized with active set algorithm for rapid local convergence. The accuracy, convergence rate, and computational complexity of the scheme are analyzed based on large number of independents runs and their comprehensive statistical analysis. The comparative studies of the results obtained are made with MATHEMATICA solutions, as well as, with variational iteration method and homotopy perturbation method. PMID:22919371

Global dysrhythmia of cerebro-basal ganglia-cerebellar networks underlies motor tics following striatal disinhibition.

PubMed

McCairn, Kevin W; Iriki, Atsushi; Isoda, Masaki

2013-01-09

Motor tics, a cardinal symptom of Tourette syndrome (TS), are hypothesized to arise from abnormalities within cerebro-basal ganglia circuits. Yet noninvasive neuroimaging of TS has previously identified robust activation in the cerebellum. To date, electrophysiological properties of cerebellar activation and its role in basal ganglia-mediated tic expression remain unknown. We performed multisite, multielectrode recordings of single-unit activity and local field potentials from the cerebellum, basal ganglia, and primary motor cortex using a pharmacologic monkey model of motor tics/TS. Following microinjections of bicuculline into the sensorimotor putamen, periodic tics occurred predominantly in the orofacial region, and a sizable number of cerebellar neurons showed phasic changes in activity associated with tic episodes. Specifically, 64% of the recorded cerebellar cortex neurons exhibited increases in activity, and 85% of the dentate nucleus neurons displayed excitatory, inhibitory, or multiphasic responses. Critically, abnormal discharges of cerebellar cortex neurons and excitatory-type dentate neurons mostly preceded behavioral tic onset, indicating their central origins. Latencies of pathological activity in the cerebellum and primary motor cortex substantially overlapped, suggesting that aberrant signals may be traveling along divergent pathways to these structures from the basal ganglia. Furthermore, the occurrence of tic movement was most closely associated with local field potential spikes in the cerebellum and primary motor cortex, implying that these structures may function as a gate to release overt tic movements. These findings indicate that tic-generating networks in basal ganglia mediated tic disorders extend beyond classical cerebro-basal ganglia circuits, leading to global network dysrhythmia including cerebellar circuits.

Network interactions within the canine intrinsic cardiac nervous system: implications for reflex control of regional cardiac function

PubMed Central

Beaumont, Eric; Salavatian, Siamak; Southerland, E Marie; Vinet, Alain; Jacquemet, Vincent; Armour, J Andrew; Ardell, Jeffrey L

2013-01-01

The aims of the study were to determine how aggregates of intrinsic cardiac (IC) neurons transduce the cardiovascular milieu versus responding to changes in central neuronal drive and to determine IC network interactions subsequent to induced neural imbalances in the genesis of atrial fibrillation (AF). Activity from multiple IC neurons in the right atrial ganglionated plexus was recorded in eight anaesthetized canines using a 16-channel linear microelectrode array. Induced changes in IC neuronal activity were evaluated in response to: (1) focal cardiac mechanical distortion; (2) electrical activation of cervical vagi or stellate ganglia; (3) occlusion of the inferior vena cava or thoracic aorta; (4) transient ventricular ischaemia, and (5) neurally induced AF. Low level activity (ranging from 0 to 2.7 Hz) generated by 92 neurons was identified in basal states, activities that displayed functional interconnectivity. The majority (56%) of IC neurons so identified received indirect central inputs (vagus alone: 25%; stellate ganglion alone: 27%; both: 48%). Fifty per cent transduced the cardiac milieu responding to multimodal stressors applied to the great vessels or heart. Fifty per cent of IC neurons exhibited cardiac cycle periodicity, with activity occurring primarily in late diastole into isovolumetric contraction. Cardiac-related activity in IC neurons was primarily related to direct cardiac mechano-sensory inputs and indirect autonomic efferent inputs. In response to mediastinal nerve stimulation, most IC neurons became excessively activated; such network behaviour preceded and persisted throughout AF. It was concluded that stochastic interactions occur among IC local circuit neuronal populations in the control of regional cardiac function. Modulation of IC local circuit neuronal recruitment may represent a novel approach for the treatment of cardiac disease, including atrial arrhythmias. PMID:23818689

An analysis of current source density profiles activated by local stimulation in the mouse auditory cortex in vitro.

PubMed

Yamamura, Daiki; Sano, Ayaka; Tateno, Takashi

2017-03-15

To examine local network properties of the mouse auditory cortex in vitro, we recorded extracellular spatiotemporal laminar profiles driven by short electric local stimulation on a planar multielectrode array substrate. The recorded local field potentials were subsequently evaluated using current source density (CSD) analysis to identify sources and sinks. Current sinks are thought to be an indicator of net synaptic current in the small volume of cortex surrounding the recording site. Thus, CSD analysis combined with multielectrode arrays enabled us to compare mean synaptic activity in response to small current stimuli on a layer-by-layer basis. We also used senescence-accelerated mice (SAM), some strains of which show earlier onset of age-related hearing loss, to examine the characteristic spatiotemporal CSD profiles stimulated by electrodes in specific cortical layers. Thus, the CSD patterns were classified into several clusters based on stimulation sites in the cortical layers. We also found some differences in CSD patterns between the two SAM strains in terms of aging according to principle component analysis with dimension reduction. For simultaneous two-site stimulation, we modeled the obtained CSD profiles as a linear superposition of the CSD profiles to individual single-site stimulation. The model analysis indicated the nonlinearity of spatiotemporal integration over stimulus-driven activity in a layer-specific manner. Finally, on the basis of these results, we discuss the auditory cortex local network properties and the effects of aging on these mouse strains. Copyright © 2017 Elsevier B.V. All rights reserved.

A Smart City Application: A Fully Controlled Street Lighting Isle Based on Raspberry-Pi Card, a ZigBee Sensor Network and WiMAX

PubMed Central

Leccese, Fabio; Cagnetti, Marco; Trinca, Daniele

2014-01-01

A smart city application has been realized and tested. It is a fully remote controlled isle of lamp posts based on new technologies. It has been designed and organized in different hierarchical layers, which perform local activities to physically control the lamp posts and transmit information with another for remote control. Locally, each lamp post uses an electronic card for management and a ZigBee tlc network transmits data to a central control unit, which manages the whole isle. The central unit is realized with a Raspberry-Pi control card due to its good computing performance at very low price. Finally, a WiMAX connection was tested and used to remotely control the smart grid, thus overcoming the distance limitations of commercial Wi-Fi networks. The isle has been realized and tested for some months in the field. PMID:25529206

A smart city application: a fully controlled street lighting isle based on Raspberry-Pi card, a ZigBee sensor network and WiMAX.

PubMed

Leccese, Fabio; Cagnetti, Marco; Trinca, Daniele

2014-12-18

A smart city application has been realized and tested. It is a fully remote controlled isle of lamp posts based on new technologies. It has been designed and organized in different hierarchical layers, which perform local activities to physically control the lamp posts and transmit information with another for remote control. Locally, each lamp post uses an electronic card for management and a ZigBee tlc network transmits data to a central control unit, which manages the whole isle. The central unit is realized with a Raspberry-Pi control card due to its good computing performance at very low price. Finally, a WiMAX connection was tested and used to remotely control the smart grid, thus overcoming the distance limitations of commercial Wi-Fi networks. The isle has been realized and tested for some months in the field.

An Analysis of a System of Rural Regional Environmental Management Led by ‘a Group of University Students’

NASA Astrophysics Data System (ADS)

Nakajima, Masahiro; Nakamura, Masato; Hiroshige, Yutaka

This paper aims to analyze the formative processes and the current state of a collaboration between ‘outsiders’ and local residents in a System of Rural Regional Environmental management from the view point of human networks. The system seeks to solve the problem of abandoned farmlands led by a group of university students (outsiders). We chronologically classified a total of eighty-nine activities addressing the issue of abandoned farmlands by utilizing three concepts: ‘calculated devices’ (e.g. the making of relations between a group of university students and local residents and strengthening these relations), ‘assistance/participation’, and ‘voluntary interaction/desire’. Based on this analysis, we: 1) developed an understanding of the formative processes as well as the current state of the collaboration between a group of university students and twenty seven local residents from an individual perspective; 2) identified ten key individuals who played a significant role in the activities examined and revealed their characteristics and motivations; 3) suggest that an existing NPO and informal relations between the local residents played a major role in the formation of collaborative networks; 4) argue that the perceived characteristics of the students (e.g. ‘youthful’, ‘inexperienced’) and the Mori-Mori club (e.g. unstable) contributed to the maintenance and expansion of the collaboration between ‘outsiders’ and local residents.

Noise focusing and the emergence of coherent activity in neuronal cultures

NASA Astrophysics Data System (ADS)

Orlandi, Javier G.; Soriano, Jordi; Alvarez-Lacalle, Enrique; Teller, Sara; Casademunt, Jaume

2013-09-01

At early stages of development, neuronal cultures in vitro spontaneously reach a coherent state of collective firing in a pattern of nearly periodic global bursts. Although understanding the spontaneous activity of neuronal networks is of chief importance in neuroscience, the origin and nature of that pulsation has remained elusive. By combining high-resolution calcium imaging with modelling in silico, we show that this behaviour is controlled by the propagation of waves that nucleate randomly in a set of points that is specific to each culture and is selected by a non-trivial interplay between dynamics and topology. The phenomenon is explained by the noise focusing effect--a strong spatio-temporal localization of the noise dynamics that originates in the complex structure of avalanches of spontaneous activity. Results are relevant to neuronal tissues and to complex networks with integrate-and-fire dynamics and metric correlations, for instance, in rumour spreading on social networks.

Intrinsic and Extrinsic Neuromodulation of Olfactory Processing

PubMed Central

Lizbinski, Kristyn M.; Dacks, Andrew M.

2018-01-01

Neuromodulation is a ubiquitous feature of neural systems, allowing flexible, context specific control over network dynamics. Neuromodulation was first described in invertebrate motor systems and early work established a basic dichotomy for neuromodulation as having either an intrinsic origin (i.e., neurons that participate in network coding) or an extrinsic origin (i.e., neurons from independent networks). In this conceptual dichotomy, intrinsic sources of neuromodulation provide a “memory” by adjusting network dynamics based upon previous and ongoing activation of the network itself, while extrinsic neuromodulators provide the context of ongoing activity of other neural networks. Although this dichotomy has been thoroughly considered in motor systems, it has received far less attention in sensory systems. In this review, we discuss intrinsic and extrinsic modulation in the context of olfactory processing in invertebrate and vertebrate model systems. We begin by discussing presynaptic modulation of olfactory sensory neurons by local interneurons (LNs) as a mechanism for gain control based on ongoing network activation. We then discuss the cell-class specific effects of serotonergic centrifugal neurons on olfactory processing. Finally, we briefly discuss the integration of intrinsic and extrinsic neuromodulation (metamodulation) as an effective mechanism for exerting global control over olfactory network dynamics. The heterogeneous nature of neuromodulation is a recurring theme throughout this review as the effects of both intrinsic and extrinsic modulation are generally non-uniform. PMID:29375314

Real-time network traffic classification technique for wireless local area networks based on compressed sensing

NASA Astrophysics Data System (ADS)

Balouchestani, Mohammadreza

2017-05-01

Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

Healthy cities: overview of a WHO international program.

PubMed

Goldstein, G

2000-01-01

Health is the outcome of all the factors and activities impinging upon the lives of individuals and communities. The last decade has seen an emerging understanding within development circles that living conditions are greatly affected by local action, by the work of local government, and by community groups and organizations. In addressing health and environmental issues and making interventions, an integrated approach, based on 'settings', exemplified in the Healthy Cities approach, has proved most effective. A Healthy City project can involve people and organizations in the programs and activities that are needed for better health, and enables a city or neighborhood to mobilize the human and financial resources required to address many health and quality of life issues. The WHO program involves implementating city projects and networks in all regions of the world and serves as a vehicle for many health programs, including major disease control initiatives. Healthy City projects allow Ministries of Health to develop stronger partnerships with local government organizations (such as the Union of Local Authorities and its members, "Local Agenda 21" initiatives, and others). One focus for the program is the development of 'multi-'multi-city action plans' for major global priority issues, including AIDS, sanitation, women's health, and violence, to ensure that major public health programs are strengthened by wider community participation. It is recognized that city networking--at national, regional, and international levels--now must be better exploited by individual cities and municipalities to solve local health problems.

Development of the brain's structural network efficiency in early adolescence: A longitudinal DTI twin study.

PubMed

Koenis, Marinka M G; Brouwer, Rachel M; van den Heuvel, Martijn P; Mandl, René C W; van Soelen, Inge L C; Kahn, René S; Boomsma, Dorret I; Hulshoff Pol, Hilleke E

2015-12-01

The brain is a network and our intelligence depends in part on the efficiency of this network. The network of adolescents differs from that of adults suggesting developmental changes. However, whether the network changes over time at the individual level and, if so, how this relates to intelligence, is unresolved in adolescence. In addition, the influence of genetic factors in the developing network is not known. Therefore, in a longitudinal study of 162 healthy adolescent twins and their siblings (mean age at baseline 9.9 [range 9.0-15.0] years), we mapped local and global structural network efficiency of cerebral fiber pathways (weighted with mean FA and streamline count) and assessed intelligence over a three-year interval. We find that the efficiency of the brain's structural network is highly heritable (locally up to 74%). FA-based local and global efficiency increases during early adolescence. Streamline count based local efficiency both increases and decreases, and global efficiency reorganizes to a net decrease. Local FA-based efficiency was correlated to IQ. Moreover, increases in FA-based network efficiency (global and local) and decreases in streamline count based local efficiency are related to increases in intellectual functioning. Individual changes in intelligence and local FA-based efficiency appear to go hand in hand in frontal and temporal areas. More widespread local decreases in streamline count based efficiency (frontal cingulate and occipital) are correlated with increases in intelligence. We conclude that the teenage brain is a network in progress in which individual differences in maturation relate to level of intellectual functioning. © 2015 Wiley Periodicals, Inc.

Hybrid routing technique for a fault-tolerant, integrated information network

NASA Technical Reports Server (NTRS)

Meredith, B. D.

1986-01-01

The evolutionary growth of the space station and the diverse activities onboard are expected to require a hierarchy of integrated, local area networks capable of supporting data, voice, and video communications. In addition, fault-tolerant network operation is necessary to protect communications between critical systems attached to the net and to relieve the valuable human resources onboard the space station of time-critical data system repair tasks. A key issue for the design of the fault-tolerant, integrated network is the development of a robust routing algorithm which dynamically selects the optimum communication paths through the net. A routing technique is described that adapts to topological changes in the network to support fault-tolerant operation and system evolvability.

From sparse to dense and from assortative to disassortative in online social networks

PubMed Central

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-01-01

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks. PMID:24798703

From sparse to dense and from assortative to disassortative in online social networks.

PubMed

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-05-06

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.

ANZA Seismic Network- From Monitoring to Science

NASA Astrophysics Data System (ADS)

Vernon, F.; Eakin, J.; Martynov, V.; Newman, R.; Offield, G.; Hindley, A.; Astiz, L.

2007-05-01

The ANZA Seismic Network (http:eqinfo.ucsd.edu) utilizes broadband and strong motion sensors with 24-bit dataloggers combined with real-time telemetry to monitor local and regional seismicity in southernmost California. The ANZA network provides real-time data to the IRIS DMC, California Integrated Seismic Network (CISN), other regional networks, and the Advanced National Seismic System (ANSS), in addition to providing near real-time information and monitoring to the greater San Diego community. Twelve high dynamic range broadband and strong motion sensors adjacent to the San Jacinto Fault zone contribute data for earthquake source studies and continue the monitoring of the seismic activity of the San Jacinto fault initiated 24 years ago. Five additional stations are located in the San Diego region with one more station on San Clemente Island. The ANZA network uses the advance wireless networking capabilities of the NSF High Performance Wireless Research and Education Network (http:hpwren.ucsd.edu) to provide the communication infrastructure for the real-time telemetry of Anza seismic stations. The ANZA network uses the Antelope data acquisition software. The combination of high quality hardware, communications, and software allow for an annual network uptime in excess of 99.5% with a median annual station real-time data return rate of 99.3%. Approximately 90,000 events, dominantly local sources but including regional and teleseismic events, comprise the ANZA network waveform database. All waveform data and event data are managed using the Datascope relational database. The ANZA network data has been used in a variety of scientific research including detailed structure of the San Jacinto Fault Zone, earthquake source physics, spatial and temporal studies of aftershocks, array studies of teleseismic body waves, and array studies on the source of microseisms. To augment the location, detection, and high frequency observations of the seismic source spectrum from local earthquakes, the ANZA network is receiving real-time data from borehole arrays located at the UCSD Thornton Hospital, and from UCSB's Borrego Valley and Garner Valley Downhole Arrays. Finally the ANZA network is acquiring data from seven PBO sites each with 300 meter deep MEMs accelerometers, passive seismometers, and a borehole strainmeter.

An artificial network model for estimating the network structure underlying partially observed neuronal signals.

PubMed

Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

2014-01-01

Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction.

PubMed

Hellyer, Peter John; Clopath, Claudia; Kehagia, Angie A; Turkheimer, Federico E; Leech, Robert

2017-08-01

In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic mechanisms. We investigate roles for homeostatic plasticity both locally (local inhibition adjusting to balance excitatory input) as well as more globally (regional "task negative" activity that compensates for "task positive", sensory input in another region) balancing neural activity and leading to more stable behavior (trajectories through the environment). Our results suggest complementary functional roles for both local and macroscale mechanisms in maintaining neural and behavioral dynamics and a novel functional role for macroscopic "task-negative" patterns of activity (e.g., the default mode network).

[Sustainable Strategies for Health Promotion in Urban Districts].

PubMed

Große, J; Menkouo, C; Grande, G

2015-09-01

In a city district striving to sustainably develop into a healthy living environment for its residents, cooperation with locally active players as well as network management and the inclusion of citizens and local businesses as non-professional multipliers are particularly promising strategies for developing effective ways of promoting health and integrating them into existing structures in order to reach the target group. © Georg Thieme Verlag KG Stuttgart · New York.

Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs.

PubMed

Allain, Ariane; Chauvot de Beauchêne, Isaure; Langenfeld, Florent; Guarracino, Yann; Laine, Elodie; Tchertanov, Luba

2014-01-01

Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach - MOdular NETwork Analysis (MONETA) - based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins - a crucial basis to guide the discovery of next-generation allosteric drugs.

Crowdsourcing for large-scale mosquito (Diptera: Culicidae) sampling

USDA-ARS?s Scientific Manuscript database

Sampling a cosmopolitan mosquito (Diptera: Culicidae) species throughout its range is logistically challenging and extremely resource intensive. Mosquito control programmes and regional networks operate at the local level and often conduct sampling activities across much of North America. A method f...

Speed hysteresis and noise shaping of traveling fronts in neural fields: role of local circuitry and nonlocal connectivity

NASA Astrophysics Data System (ADS)

Capone, Cristiano; Mattia, Maurizio

2017-01-01

Neural field models are powerful tools to investigate the richness of spatiotemporal activity patterns like waves and bumps, emerging from the cerebral cortex. Understanding how spontaneous and evoked activity is related to the structure of underlying networks is of central interest to unfold how information is processed by these systems. Here we focus on the interplay between local properties like input-output gain function and recurrent synaptic self-excitation of cortical modules, and nonlocal intermodular synaptic couplings yielding to define a multiscale neural field. In this framework, we work out analytic expressions for the wave speed and the stochastic diffusion of propagating fronts uncovering the existence of an optimal balance between local and nonlocal connectivity which minimizes the fluctuations of the activation front propagation. Incorporating an activity-dependent adaptation of local excitability further highlights the independent role that local and nonlocal connectivity play in modulating the speed of propagation of the activation and silencing wavefronts, respectively. Inhomogeneities in space of local excitability give raise to a novel hysteresis phenomenon such that the speed of waves traveling in opposite directions display different velocities in the same location. Taken together these results provide insights on the multiscale organization of brain slow-waves measured during deep sleep and anesthesia.

Familiar Taste Induces Higher Dendritic Levels of Activity-Regulated Cytoskeleton-Associated Protein in the Insular Cortex than a Novel One

ERIC Educational Resources Information Center

Morin, Jean-Pascal; Quiroz, Cesar; Mendoza-Viveros, Lucia; Ramirez-Amaya, Victor; Bermudez-Rattoni, Federico

2011-01-01

The immediate early gene (IEG) "Arc" is known to play an important role in synaptic plasticity; its protein is locally translated in the dendrites where it has been involved in several types of plasticity mechanisms. Because of its tight coupling with neuronal activity, "Arc" has been widely used as a tool to tag behaviorally activated networks.…

Myosin II–interacting guanine nucleotide exchange factor promotes bleb retraction via stimulating cortex reassembly at the bleb membrane

PubMed Central

Jiao, Meng; Wu, Di; Wei, Qize

2018-01-01

Blebs are involved in various biological processes such as cell migration, cytokinesis, and apoptosis. While the expansion of blebs is largely an intracellular pressure-driven process, the retraction of blebs is believed to be driven by RhoA activation that leads to the reassembly of the actomyosin cortex at the bleb membrane. However, it is still poorly understood how RhoA is activated at the bleb membrane. Here, we provide evidence demonstrating that myosin II–interacting guanine nucleotide exchange factor (MYOGEF) is implicated in bleb retraction via stimulating RhoA activation and the reassembly of an actomyosin network at the bleb membrane during bleb retraction. Interaction of MYOGEF with ezrin, a well-known regulator of bleb retraction, is required for MYOGEF localization to retracting blebs. Notably, knockout of MYOGEF or ezrin not only disrupts RhoA activation at the bleb membrane, but also interferes with nonmuscle myosin II localization and activation, as well as actin polymerization in retracting blebs. Importantly, MYOGEF knockout slows down bleb retraction. We propose that ezrin interacts with MYOGEF and recruits it to retracting blebs, where MYOGEF activates RhoA and promotes the reassembly of the cortical actomyosin network at the bleb membrane, thus contributing to the regulation of bleb retraction. PMID:29321250

Whole genome siRNA cell-based screen links mitochondria to Akt signaling network through uncoupling of electron transport chain

PubMed Central

Senapedis, William T.; Kennedy, Caleb J.; Boyle, Patrick M.; Silver, Pamela A.

2011-01-01

Forkhead transcription factors (FOXOs) alter a diverse array of cellular processes including the cell cycle, oxidative stress resistance, and aging. Insulin/Akt activation directs phosphorylation and cytoplasmic sequestration of FOXO away from its target genes and serves as an endpoint of a complex signaling network. Using a human genome small interfering RNA (siRNA) library in a cell-based assay, we identified an extensive network of proteins involved in nuclear export, focal adhesion, and mitochondrial respiration not previously implicated in FOXO localization. Furthermore, a detailed examination of mitochondrial factors revealed that loss of uncoupling protein 5 (UCP5) modifies the energy balance and increases free radicals through up-regulation of uncoupling protein 3 (UCP3). The increased superoxide content induces c-Jun N-terminal kinase 1 (JNK1) kinase activity, which in turn affects FOXO localization through a compensatory dephosphorylation of Akt. The resulting nuclear FOXO increases expression of target genes, including mitochondrial superoxide dismutase. By connecting free radical defense and mitochondrial uncoupling to Akt/FOXO signaling, these results have implications in obesity and type 2 diabetes development and the potential for therapeutic intervention. PMID:21460183

Whole genome siRNA cell-based screen links mitochondria to Akt signaling network through uncoupling of electron transport chain.

PubMed

Senapedis, William T; Kennedy, Caleb J; Boyle, Patrick M; Silver, Pamela A

2011-05-15

Forkhead transcription factors (FOXOs) alter a diverse array of cellular processes including the cell cycle, oxidative stress resistance, and aging. Insulin/Akt activation directs phosphorylation and cytoplasmic sequestration of FOXO away from its target genes and serves as an endpoint of a complex signaling network. Using a human genome small interfering RNA (siRNA) library in a cell-based assay, we identified an extensive network of proteins involved in nuclear export, focal adhesion, and mitochondrial respiration not previously implicated in FOXO localization. Furthermore, a detailed examination of mitochondrial factors revealed that loss of uncoupling protein 5 (UCP5) modifies the energy balance and increases free radicals through up-regulation of uncoupling protein 3 (UCP3). The increased superoxide content induces c-Jun N-terminal kinase 1 (JNK1) kinase activity, which in turn affects FOXO localization through a compensatory dephosphorylation of Akt. The resulting nuclear FOXO increases expression of target genes, including mitochondrial superoxide dismutase. By connecting free radical defense and mitochondrial uncoupling to Akt/FOXO signaling, these results have implications in obesity and type 2 diabetes development and the potential for therapeutic intervention.

The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain Interaction during Cooperation: Evaluating Local Properties of Multiple-Brain Network.

PubMed

Sciaraffa, Nicolina; Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Colosimo, Alfredo; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

2017-07-21

Subjects' interaction is the core of most human activities. This is the reason why a lack of coordination is often the cause of missing goals, more than individual failure. While there are different subjective and objective measures to assess the level of mental effort required by subjects while facing a situation that is getting harder, that is, mental workload, to define an objective measure based on how and if team members are interacting is not so straightforward. In this study, behavioral, subjective and synchronized electroencephalographic data were collected from couples involved in a cooperative task to describe the relationship between task difficulty and team coordination, in the sense of interaction aimed at cooperatively performing the assignment. Multiple-brain connectivity analysis provided information about the whole interacting system. The results showed that averaged local properties of a brain network were affected by task difficulty. In particular, strength changed significantly with task difficulty and clustering coefficients strongly correlated with the workload itself. In particular, a higher workload corresponded to lower clustering values over the central and parietal brain areas. Such results has been interpreted as less efficient organization of the network when the subjects' activities, due to high workload tendencies, were less coordinated.

Does Physical Activity Mediate the Associations Between Local-Area Descriptive Norms, Built Environment Walkability, and Glycosylated Hemoglobin?

PubMed

Carroll, Suzanne J; Niyonsenga, Theo; Coffee, Neil T; Taylor, Anne W; Daniel, Mark

2017-08-23

Associations between local-area residential features and glycosylated hemoglobin (HbA 1c ) may be mediated by individual-level health behaviors. Such indirect effects have rarely been tested. This study assessed whether individual-level self-reported physical activity mediated the influence of local-area descriptive norms and objectively expressed walkability on 10-year change in HbA 1c . HbA 1c was assessed three times for adults in a 10-year population-based biomedical cohort ( n = 4056). Local-area norms specific to each participant were calculated, aggregating responses from a separate statewide surveillance survey for 1600 m road-network buffers centered on participant addresses (local prevalence of overweight/obesity (body mass index ≥25 kg/m²) and physical inactivity (<150 min/week)). Separate latent growth models estimated direct and indirect (through physical activity) effects of local-area exposures on change in HbA 1c , accounting for spatial clustering and covariates (individual-level age, sex, smoking status, marital status, employment and education, and area-level median household income). HbA 1c worsened over time. Local-area norms directly and indirectly predicted worsening HbA 1c trajectories. Walkability was directly and indirectly protective of worsening HbA 1c . Local-area descriptive norms and walkability influence cardiometabolic risk trajectory through individual-level physical activity. Efforts to reduce population cardiometabolic risk should consider the extent of local-area unhealthful behavioral norms and walkability in tailoring strategies to improve physical activity.

Does Physical Activity Mediate the Associations between Local-Area Descriptive Norms, Built Environment Walkability, and Glycosylated Hemoglobin?

PubMed Central

Daniel, Mark

2017-01-01

Associations between local-area residential features and glycosylated hemoglobin (HbA1c) may be mediated by individual-level health behaviors. Such indirect effects have rarely been tested. This study assessed whether individual-level self-reported physical activity mediated the influence of local-area descriptive norms and objectively expressed walkability on 10-year change in HbA1c. HbA1c was assessed three times for adults in a 10-year population-based biomedical cohort (n = 4056). Local-area norms specific to each participant were calculated, aggregating responses from a separate statewide surveillance survey for 1600 m road-network buffers centered on participant addresses (local prevalence of overweight/obesity (body mass index ≥25 kg/m2) and physical inactivity (<150 min/week)). Separate latent growth models estimated direct and indirect (through physical activity) effects of local-area exposures on change in HbA1c, accounting for spatial clustering and covariates (individual-level age, sex, smoking status, marital status, employment and education, and area-level median household income). HbA1c worsened over time. Local-area norms directly and indirectly predicted worsening HbA1c trajectories. Walkability was directly and indirectly protective of worsening HbA1c. Local-area descriptive norms and walkability influence cardiometabolic risk trajectory through individual-level physical activity. Efforts to reduce population cardiometabolic risk should consider the extent of local-area unhealthful behavioral norms and walkability in tailoring strategies to improve physical activity. PMID:28832552

Spontaneous and electrically modulated spatiotemporal dynamics of the neocortical slow oscillation and associated local fast activity.

PubMed

Greenberg, Anastasia; Dickson, Clayton T

2013-12-01

The neocortical slow oscillation (SO; ~1Hz) of non-REM sleep and anesthesia reflects synchronized network activity composed of alternating active and silent (ON/OFF) phases at the local network and cellular level. The SO itself shows self-organized spatiotemporal dynamics as it appears to originate at unique foci on each cycle and then propagates across the cortical surface. During sleep, this rhythm is relevant for neuroplastic processes mediating memory consolidation especially since its enhancement by slow, rhythmic electrical fields improves subsequent recall. However, the neurobiological mechanism by which spontaneous or enhanced SO activity might operate on memory traces is unknown. Here we show a series of original results, using cycle to cycle tracking across multiple neocortical sites in urethane anesthetized rats: The spontaneous spatiotemporal dynamics of the SO are complex, showing interfering propagation patterns in the anterior-to-posterior plane. These patterns compete for expression and tend to alternate following phase resets that take place during the silent OFF phase of the SO. Applying sinusoidal electrical field stimulation to the anterior pole of the cerebral cortex progressively entrained local field, gamma, and multi-unit activity at all sites, while disrupting the coordination of endogenous SO activity. Field stimulation also biased propagation in the anterior-to-posterior direction and more notably, enhanced the long-range gamma synchrony between cortical regions. These results are the first to show that changes to slow wave dynamics cause enhancements in high frequency cortico-cortical communication and provide mechanistic clues into how the SO is relevant for sleep-dependent memory consolidation. © 2013.

Network analysis of a regional fishery: Implications for management of natural resources, and recruitment and retention of anglers

USGS Publications Warehouse

Martin, Dustin R.; Shizuka, Daizaburo; Chizinski, Christopher J.; Pope, Kevin L.

2017-01-01

Angler groups and water-body types interact to create a complex social-ecological system. Network analysis could inform detailed mechanistic models on, and provide managers better information about, basic patterns of fishing activity. Differences in behavior and reservoir selection among angler groups in a regional fishery, the Salt Valley fishery in southeastern Nebraska, USA, were assessed using a combination of cluster and network analyses. The four angler groups assessed ranged from less active, unskilled anglers (group One) to highly active, very skilled anglers (group Four). Reservoir use patterns and the resulting network communities of these four angler groups differed; the number of reservoir communities for these groups ranged from two to three and appeared to be driven by reservoir location (group One), reservoir size and its associated attributes (groups Two and Four), or an interaction between reservoir size and location (group Three). Network analysis is a useful tool to describe differences in participation among angler groups within a regional fishery, and provides new insights about possible recruitment of anglers. For example, group One anglers fished reservoirs closer to home and had a greater probability of dropping out if local reservoir access were restricted.

Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2013-01-01

Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT) provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by ‘climbing’ activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification. PMID:23592967

Detecting large-scale networks in the human brain using high-density electroencephalography.

PubMed

Liu, Quanying; Farahibozorg, Seyedehrezvan; Porcaro, Camillo; Wenderoth, Nicole; Mantini, Dante

2017-09-01

High-density electroencephalography (hdEEG) is an emerging brain imaging technique that can be used to investigate fast dynamics of electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from reporting brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI). Here, we report for the first time a robust detection of brain networks from resting state (256-channel) hdEEG recordings. Specifically, we obtained 14 networks previously described in fMRI studies by means of realistic 12-layer head models and exact low-resolution brain electromagnetic tomography (eLORETA) source localization, together with independent component analysis (ICA) for functional connectivity analysis. Our analyses revealed three important methodological aspects. First, brain network reconstruction can be improved by performing source localization using the gray matter as source space, instead of the whole brain. Second, conducting EEG connectivity analyses in individual space rather than on concatenated datasets may be preferable, as it permits to incorporate realistic information on head modeling and electrode positioning. Third, the use of a wide frequency band leads to an unbiased and generally accurate reconstruction of several network maps, whereas filtering data in a narrow frequency band may enhance the detection of specific networks and penalize that of others. We hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research. Hum Brain Mapp 38:4631-4643, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation

PubMed Central

Mace, Michael; Pavese, Nicola; Borisyuk, Roman; Bain, Peter

2017-01-01

Essential tremor (ET), a movement disorder characterised by an uncontrollable shaking of the affected body part, is often professed to be the most common movement disorder, affecting up to one percent of adults over 40 years of age. The precise cause of ET is unknown, however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder. Deep brain stimulation (DBS) is a clinical therapy used to alleviate the symptoms of a number of movement disorders. DBS involves the surgical implantation of electrodes into specific nuclei in the brain. For ET the targeted region is the ventralis intermedius (Vim) nucleus of the thalamus. Though DBS is effective for treating ET, the mechanism through which the therapeutic effect is obtained is not understood. To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity, we take a computational modelling approach combined with electrophysiological data. The pathological brain activity was recorded intra-operatively via implanted DBS electrodes, whilst simultaneously recording muscle activity of the affected limbs. We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach. The modelled network exhibited oscillatory behaviour within the tremor frequency range, as did our electrophysiological data. By applying a DBS-like input we suppressed these oscillations. This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity, which could be one mechanism underlying the therapeutic benefit. PMID:28068428

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

PubMed Central

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo

2016-01-01

Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

PubMed

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

2016-12-01

Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.

Cytoskeletal Network Morphology Regulates Intracellular Transport Dynamics

PubMed Central

Ando, David; Korabel, Nickolay; Huang, Kerwyn Casey; Gopinathan, Ajay

2015-01-01

Intracellular transport is essential for maintaining proper cellular function in most eukaryotic cells, with perturbations in active transport resulting in several types of disease. Efficient delivery of critical cargos to specific locations is accomplished through a combination of passive diffusion and active transport by molecular motors that ballistically move along a network of cytoskeletal filaments. Although motor-based transport is known to be necessary to overcome cytoplasmic crowding and the limited range of diffusion within reasonable timescales, the topological features of the cytoskeletal network that regulate transport efficiency and robustness have not been established. Using a continuum diffusion model, we observed that the time required for cellular transport was minimized when the network was localized near the nucleus. In simulations that explicitly incorporated network spatial architectures, total filament mass was the primary driver of network transit times. However, filament traps that redirect cargo back to the nucleus caused large variations in network transport. Filament polarity was more important than filament orientation in reducing average transit times, and transport properties were optimized in networks with intermediate motor on and off rates. Our results provide important insights into the functional constraints on intracellular transport under which cells have evolved cytoskeletal structures, and have potential applications for enhancing reactions in biomimetic systems through rational transport network design. PMID:26488648

Spike frequency adaptation is a possible mechanism for control of attractor preference in auto-associative neural networks

NASA Astrophysics Data System (ADS)

Roach, James; Sander, Leonard; Zochowski, Michal

Auto-associative memory is the ability to retrieve a pattern from a small fraction of the pattern and is an important function of neural networks. Within this context, memories that are stored within the synaptic strengths of networks act as dynamical attractors for network firing patterns. In networks with many encoded memories, some attractors will be stronger than others. This presents the problem of how networks switch between attractors depending on the situation. We suggest that regulation of neuronal spike-frequency adaptation (SFA) provides a universal mechanism for network-wide attractor selectivity. Here we demonstrate in a Hopfield type attractor network that neurons minimal SFA will reliably activate in the pattern corresponding to a local attractor and that a moderate increase in SFA leads to the network to converge to the strongest attractor state. Furthermore, we show that on long time scales SFA allows for temporal sequences of activation to emerge. Finally, using a model of cholinergic modulation within the cortex we argue that dynamic regulation of attractor preference by SFA could be critical for the role of acetylcholine in attention or for arousal states in general. This work was supported by: NSF Graduate Research Fellowship Program under Grant No. DGE 1256260 (JPR), NSF CMMI 1029388 (MRZ) and NSF PoLS 1058034 (MRZ & LMS).

Desynchronization of slow oscillations in the basal ganglia during natural sleep.

PubMed

Mizrahi-Kliger, Aviv D; Kaplan, Alexander; Israel, Zvi; Bergman, Hagai

2018-05-01

Slow oscillations of neuronal activity alternating between firing and silence are a hallmark of slow-wave sleep (SWS). These oscillations reflect the default activity present in all mammalian species, and are ubiquitous to anesthesia, brain slice preparations, and neuronal cultures. In all these cases, neuronal firing is highly synchronous within local circuits, suggesting that oscillation-synchronization coupling may be a governing principle of sleep physiology regardless of anatomical connectivity. To investigate whether this principle applies to overall brain organization, we recorded the activity of individual neurons from basal ganglia (BG) structures and the thalamocortical (TC) network over 70 full nights of natural sleep in two vervet monkeys. During SWS, BG neurons manifested slow oscillations (∼0.5 Hz) in firing rate that were as prominent as in the TC network. However, in sharp contrast to any neural substrate explored thus far, the slow oscillations in all BG structures were completely desynchronized between individual neurons. Furthermore, whereas in the TC network single-cell spiking was locked to slow oscillations in the local field potential (LFP), the BG LFP exhibited only weak slow oscillatory activity and failed to entrain nearby cells. We thus show that synchrony is not inherent to slow oscillations, and propose that the BG desynchronization of slow oscillations could stem from its unique anatomy and functional connectivity. Finally, we posit that BG slow-oscillation desynchronization may further the reemergence of slow-oscillation traveling waves from multiple independent origins in the frontal cortex, thus significantly contributing to normal SWS.

TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks

USGS Publications Warehouse

Song, W.-Z.; Huang, R.; Shirazi, B.; Husent, R.L.

2009-01-01

Earlier sensor network MAC protocols focus on energy conservation in low-duty cycle applications, while some recent applications involve real-time high-data-rate signals. This motivates us to design an innovative localized TDMA MAC protocol to achieve high throughput and low congestion in data collection sensor networks, besides energy conservation. TreeMAC divides a time cycle into frames and frame into slots. Parent determines children's frame assigmnent based on their relative bandwidth demand, and each node calculates its own slot assignment based on its hop-count to the sink. This innovative 2-dimensional frame-slot assignment algorithm has the following nice theory properties. Firstly, given any node, at any time slot, there is at most one active sender in its neighborhood (includ ing itself). Secondly, the packet scheduling with TreelMAC is bufferless, which therefore minimizes the probability of network congestion. Thirdly, the data throughput to gateway is at least 1/3 of the optimum assuming reliable links. Our experiments on a 24 node test bed demonstrate that TreeMAC protocol significantly improves network throughput and energy efficiency, by comparing to the TinyOS's default CSMA MAC protocol and a recent TDMA MAC protocol Funneling-MAC[8]. ?? 2009 IEEE.

Simulating fiction: individual differences in literature comprehension revealed with FMRI.

PubMed

Nijhof, Annabel D; Willems, Roel M

2015-01-01

When we read literary fiction, we are transported to fictional places, and we feel and think along with the characters. Despite the importance of narrative in adult life and during development, the neurocognitive mechanisms underlying fiction comprehension are unclear. We used functional magnetic resonance imaging (fMRI) to investigate how individuals differently employ neural networks important for understanding others' beliefs and intentions (mentalizing), and for sensori-motor simulation while listening to excerpts from literary novels. Localizer tasks were used to localize both the cortical motor network and the mentalizing network in participants after they listened to excerpts from literary novels. Results show that participants who had high activation in anterior medial prefrontal cortex (aMPFC; part of the mentalizing network) when listening to mentalizing content of literary fiction, had lower motor cortex activity when they listened to action-related content of the story, and vice versa. This qualifies how people differ in their engagement with fiction: some people are mostly drawn into a story by mentalizing about the thoughts and beliefs of others, whereas others engage in literature by simulating more concrete events such as actions. This study provides on-line neural evidence for the existence of qualitatively different styles of moving into literary worlds, and adds to a growing body of literature showing the potential to study narrative comprehension with neuroimaging methods.

Overview of IMS infrasound station and engineering projects

NASA Astrophysics Data System (ADS)

Marty, J.; Doury, B.; Kramer, A.; Martysevich, P.

2015-12-01

The Provisional Technical Secretariat (PTS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBTO) has a continuous interest in enhancing its capability in acoustic source detection, localization and characterization. The infrasound component of the International Monitoring System (IMS) constitutes the only worldwide ground-based infrasound network. It consists of sixty stations, among which forty-eight are already certified and continuously transmit data to the International Data Centre (IDC) in Vienna, Austria. Each infrasound station is composed of an array of infrasound sensors capable of measuring micro-pressure changes produced at ground level by infrasonic waves. The characteristics of infrasonic waves are computed in near real-time by IDC automatic detection software and are used as an input to IDC source categorization and localization algorithms. The PTS is continuously working towards the completion and sustainment of the IMS infrasound network. The objective of this presentation is to review the main activities performed in the IMS infrasound network over the last five years. This includes construction, installation, certification, major upgrade and revalidation activities. Major technology development projects to improve the reliability and robustness of IMS infrasound stations as well as their compliance with IMS Operational Manual requirements will also be presented. This includes advances in array geometry, wind noise reduction, system calibration, meteorological data as well as power and communication infrastructures. Finally the impact of all these changes on the overall detection capability of the IMS infrasound network will be highlighted.

Simulating Fiction: Individual Differences in Literature Comprehension Revealed with fMRI

PubMed Central

Nijhof, Annabel D.; Willems, Roel M.

2015-01-01

When we read literary fiction, we are transported to fictional places, and we feel and think along with the characters. Despite the importance of narrative in adult life and during development, the neurocognitive mechanisms underlying fiction comprehension are unclear. We used functional magnetic resonance imaging (fMRI) to investigate how individuals differently employ neural networks important for understanding others’ beliefs and intentions (mentalizing), and for sensori-motor simulation while listening to excerpts from literary novels. Localizer tasks were used to localize both the cortical motor network and the mentalizing network in participants after they listened to excerpts from literary novels. Results show that participants who had high activation in anterior medial prefrontal cortex (aMPFC; part of the mentalizing network) when listening to mentalizing content of literary fiction, had lower motor cortex activity when they listened to action-related content of the story, and vice versa. This qualifies how people differ in their engagement with fiction: some people are mostly drawn into a story by mentalizing about the thoughts and beliefs of others, whereas others engage in literature by simulating more concrete events such as actions. This study provides on-line neural evidence for the existence of qualitatively different styles of moving into literary worlds, and adds to a growing body of literature showing the potential to study narrative comprehension with neuroimaging methods. PMID:25671708

Laboratory-based ROTEM(®) analysis: implementing pneumatic tube transport and real-time graphic transmission.

PubMed

Colucci, G; Giabbani, E; Barizzi, G; Urwyler, N; Alberio, L

2011-08-01

ROTEM(®) is considered a helpful point-of-care device to monitor blood coagulation. Centrally performed analysis is desirable but rapid transport of blood samples and real-time transmission of graphic results are an important prerequisite. The effect of sample transport through a pneumatic tube system on ROTEM(®) results is unknown. The aims of the present work were (i) to determine the influence of blood sample transport through a pneumatic tube system on ROTEM(®) parameters compared to manual transportation, and (ii) to verify whether graphic results can be transmitted on line via virtual network computing using local area network to the physician in charge of the patient. Single centre study with 30 normal volunteers. Two whole blood samples were transferred to the central haematology laboratory by either normal transport or pneumatic delivery. EXTEM, INTEM, FIBTEM and APTEM were analysed in parallel with two ROTEM(®) devices and compared. Connection between central laboratory, emergency and operating rooms was established using local area network. All collected ROTEM(®) parameters were within normal limits. No statistically significant differences between normal transport and pneumatic delivery were observed. Real-time transmission of the original ROTEM(®) curves using local area network is feasible and easy to establish. At our institution, transport of blood samples by pneumatic delivery does not influence ROTEM(®) parameters. Blood samples can be analysed centrally, and results transmitted live via virtual network computing to emergency or operating rooms. Prior to analyse blood samples centrally, the type of sample transport should be tested to exclude in vitro blood activation by local pneumatic transport system. © 2011 Blackwell Publishing Ltd.

Problem Articulation and the Processes of Assistance: An Activity Theoretic View of Mediation in Game Play

ERIC Educational Resources Information Center

Stone, Lynda D.; Gutierrez, Kris D.

2007-01-01

In this article, we study a local adaptation of the Fifth Dimension [Cole, M. (1996). "Cultural psychology: A once and future discipline." Cambridge: Cambridge University Press] known as Las Redes (i.e., Networks of Collaboration in the Fifth Dimension) to examine how the multiple activity systems of Las Redes, e.g. the undergraduate course and…

The congestion control algorithm based on queue management of each node in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Wei, Yifei; Chang, Lin; Wang, Yali; Wang, Gaoping

2016-12-01

This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. As the network load increases, local congestion of mobile ad hoc network may lead to network performance degradation, hot node's energy consumption increase even failure. If small energy nodes congested because of forwarding data packets, then when it is used as the source node will cause a lot of packet loss. This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. Controlling nodes buffer queue in different levels of congestion area probability by adjusting the upper limits and lower limits, thus nodes can adjust responsibility of forwarding data packets according to their own situation. The proposed algorithm will slow down the send rate hop by hop along the data package transmission direction from congestion node to source node so that to prevent further congestion from the source node. The simulation results show that, the algorithm can better play the data forwarding ability of strong nodes, protect the weak nodes, can effectively alleviate the network congestion situation.

Reframing coalitions as systems interventions: a network study exploring the contribution of a youth violence prevention coalition to broader system capacity.

PubMed

Bess, Kimberly D

2015-06-01

This longitudinal research conceptualizes community coalitions as events in local intervention systems (Hawe et al. in Am J Commun Psychol 43(3-4):267-276, 2009). It explores the potential contribution coalitions make, through the collaborative activities of their members, to the broader intervention systems in which they are embedded. Using social network analysis, it examines patterns of structural change in a network of 99 organizations focused on youth violence prevention (YVP) over a 5-year period in which 30 of the 99 organizations were involved in a local YVP Coalition. Both longitudinal modeling and cross sectional analyses are used to examine change in system capacity-strong interorganizational networks-related to patterns of network density, centralization, and hierarchy. Somewhat surprisingly, the study found that capacity in the broader YVP Intervention System actually diminished during the 5-year period of the coalition's operation, though part of the system-the sub-network that made up the YVP Coalition-was marginally strengthened. In this case, therefore, the evidence suggests that power and relational resources in the broader YVP Intervention System were redistributed. The article explores how the definition of capacity related to density and hierarchy may be contextually dependent. Implications for the role of coalitions in building system capacity are discussed.

Voice over internet protocol with prepaid calling card solutions

NASA Astrophysics Data System (ADS)

Gunadi, Tri

2001-07-01

The VoIP technology is growing up rapidly, it has big network impact on PT Telkom Indonesia, the bigger telecommunication operator in Indonesia. Telkom has adopted VoIP and one other technology, Intelligent Network (IN). We develop those technologies together in one service product, called Internet Prepaid Calling Card (IPCC). IPCC is becoming new breakthrough for the Indonesia telecommunication services especially on VoIP and Prepaid Calling Card solutions. Network architecture of Indonesia telecommunication consists of three layer, Local, Tandem and Trunck Exchange layer. Network development researches for IPCC architecture are focus on network overlay hierarchy, Internet and PSTN. With this design hierarchy the goal of Interworking PSTN, VoIP and IN calling card, become reality. Overlay design for IPCC is not on Trunck Exchange, this is the new architecture, these overlay on Tandem and Local Exchange, to make the faster call processing. The nodes added: Gateway (GW) and Card Management Center (CMC) The GW do interfacing between PSTN and Internet Network used ISDN-PRA and Ethernet. The other functions are making bridge on circuit (PSTN) with packet (VoIP) based and real time billing process. The CMC used for data storage, pin validation, report activation, tariff system, directory number and all the administration transaction. With two nodes added the IPCC service offered to the market.

The human factor: re-organisations in public health policy.

PubMed

Oliver, Kathryn; Everett, Martin; Verma, Arpana; de Vocht, Frank

2012-06-01

Public health policy-making activities are currently split between local authority and NHS organisations. Despite an increasing body of research on evidence-based policy (EBP), few studies explore the process of policy-making. Little is known about how policies are made in a local context, or how (scientific) evidence is used. Previous research has ignored the 'human element' in EBP. Social network analysis (SNA) techniques are becoming increasingly important in health policy. This paper describes an innovative study giving a fresh perspective on policy-making processes in public health. A social network analysis of public health policy making networks in Greater Manchester based on publicly available data (documents, websites and meeting papers) and an electronic survey, asking actors to nominate those who influenced their own views, those who were powerful, and those who were a source of evidence or information. Policy-making networks are described. Formal executive roles are loosely related to perceived influence and power. Evidence-seeking networks are less coherent, with key organisations not represented. These data indicate the importance of collaboration and good relationships between researchers and policy-makers, but few academic researchers with a direct impact on health policy were identified within the networks. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A Continuum Model of Actin Waves in Dictyostelium discoideum

PubMed Central

Khamviwath, Varunyu; Hu, Jifeng; Othmer, Hans G.

2013-01-01

Actin waves are complex dynamical patterns of the dendritic network of filamentous actin in eukaryotes. We developed a model of actin waves in PTEN-deficient Dictyostelium discoideum by deriving an approximation of the dynamics of discrete actin filaments and combining it with a signaling pathway that controls filament branching. This signaling pathway, together with the actin network, contains a positive feedback loop that drives the actin waves. Our model predicts the structure, composition, and dynamics of waves that are consistent with existing experimental evidence, as well as the biochemical dependence on various protein partners. Simulation suggests that actin waves are initiated when local actin network activity, caused by an independent process, exceeds a certain threshold. Moreover, diffusion of proteins that form a positive feedback loop with the actin network alone is sufficient for propagation of actin waves at the observed speed of . Decay of the wave back can be caused by scarcity of network components, and the shape of actin waves is highly dependent on the filament disassembly rate. The model allows retraction of actin waves and captures formation of new wave fronts in broken waves. Our results demonstrate that a delicate balance between a positive feedback, filament disassembly, and local availability of network components is essential for the complex dynamics of actin waves. PMID:23741312

Balanced cortical microcircuitry for spatial working memory based on corrective feedback control.

PubMed

Lim, Sukbin; Goldman, Mark S

2014-05-14

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory-inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. Copyright © 2014 the authors 0270-6474/14/346790-17$15.00/0.

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

Detecting causality in policy diffusion processes.

PubMed

Grabow, Carsten; Macinko, James; Silver, Diana; Porfiri, Maurizio

2016-08-01

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Detecting causality in policy diffusion processes

NASA Astrophysics Data System (ADS)

Grabow, Carsten; Macinko, James; Silver, Diana; Porfiri, Maurizio

2016-08-01

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Bi-periodicity evoked by periodic external inputs in delayed Cohen-Grossberg-type bidirectional associative memory networks

NASA Astrophysics Data System (ADS)

Cao, Jinde; Wang, Yanyan

2010-05-01

In this paper, the bi-periodicity issue is discussed for Cohen-Grossberg-type (CG-type) bidirectional associative memory (BAM) neural networks (NNs) with time-varying delays and standard activation functions. It is shown that the model considered in this paper has two periodic orbits located in saturation regions and they are locally exponentially stable. Meanwhile, some conditions are derived to ensure that, in any designated region, the model has a locally exponentially stable or globally exponentially attractive periodic orbit located in it. As a special case of bi-periodicity, some results are also presented for the system with constant external inputs. Finally, four examples are given to illustrate the effectiveness of the obtained results.

Dynamic information routing in complex networks

PubMed Central

Kirst, Christoph; Timme, Marc; Battaglia, Demian

2016-01-01

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

Rapid Postnatal Expansion of Neural Networks Occurs in an Environment of Altered Neurovascular and Neurometabolic Coupling.

PubMed

Kozberg, Mariel G; Ma, Ying; Shaik, Mohammed A; Kim, Sharon H; Hillman, Elizabeth M C

2016-06-22

In the adult brain, increases in neural activity lead to increases in local blood flow. However, many prior measurements of functional hemodynamics in the neonatal brain, including functional magnetic resonance imaging (fMRI) in human infants, have noted altered and even inverted hemodynamic responses to stimuli. Here, we demonstrate that localized neural activity in early postnatal mice does not evoke blood flow increases as in the adult brain, and elucidate the neural and metabolic correlates of these altered functional hemodynamics as a function of developmental age. Using wide-field GCaMP imaging, the development of neural responses to somatosensory stimulus is visualized over the entire bilaterally exposed cortex. Neural responses are observed to progress from tightly localized, unilateral maps to bilateral responses as interhemispheric connectivity becomes established. Simultaneous hemodynamic imaging confirms that spatiotemporally coupled functional hyperemia is not present during these early stages of postnatal brain development, and develops gradually as cortical connectivity is established. Exploring the consequences of this lack of functional hyperemia, measurements of oxidative metabolism via flavoprotein fluorescence suggest that neural activity depletes local oxygen to below baseline levels at early developmental stages. Analysis of hemoglobin oxygenation dynamics at the same age confirms oxygen depletion for both stimulus-evoked and resting-state neural activity. This state of unmet metabolic demand during neural network development poses new questions about the mechanisms of neurovascular development and its role in both normal and abnormal brain development. These results also provide important insights for the interpretation of fMRI studies of the developing brain. This work demonstrates that the postnatal development of neuronal connectivity is accompanied by development of the mechanisms that regulate local blood flow in response to neural activity. Novel in vivo imaging reveals that, in the developing mouse brain, strong and localized GCaMP neural responses to stimulus fail to evoke local blood flow increases, leading to a state in which oxygen levels become locally depleted. These results demonstrate that the development of cortical connectivity occurs in an environment of altered energy availability that itself may play a role in shaping normal brain development. These findings have important implications for understanding the pathophysiology of abnormal developmental trajectories, and for the interpretation of functional magnetic resonance imaging data acquired in the developing brain. Copyright © 2016 the authors 0270-6474/16/366704-14$15.00/0.

Ocean Sense: Student-Led, Real-Time Research at the Bottom of the Ocean - Without Leaving the Classroom

NASA Astrophysics Data System (ADS)

Pelz, M.; Hoeberechts, M.; McLean, M. A.; Riddell, D. J.; Ewing, N.; Brown, J. C.

2016-12-01

This presentation outlines the authentic research experiences created by Ocean Networks Canada's Ocean Sense program, a transformative education program that connects students and teachers with place-based, real-time data via the Internet. This program, developed in collaboration with community educators, features student-centric activities, clearly outlined learning outcomes, assessment tools and curriculum aligned content. Ocean Networks Canada (ONC), an initiative of the University of Victoria, develops, operates, and maintains cabled ocean observatory systems. Technologies developed on the world-leading NEPTUNE and VENUS observatories have been adapted for small coastal installations called "community observatories," which enable community members to directly monitor conditions in the local ocean environment. Data from these observatories are fundamental to lessons and activities in the Ocean Sense program. Marketed as Ocean Sense: Local observations, global connections, the program introduces middle and high school students to research methods in biology, oceanography and ocean engineering. It includes a variety of resources and opportunities to excite students and spark curiosity about the ocean environment. The program encourages students to connect their local observations to global ocean processes and the observations of students in other geographic regions. Connection to place and local relevance of the program is enhanced through an emphasis on Indigenous and place-based knowledge. The program promotes of cross-cultural learning with the inclusion of Indigenous knowledge of the ocean. Ocean Sense provides students with an authentic research experience by connecting them to real-time data, often within their own communities. Using the freely accessible data portal, students can curate the data they need from a range of instruments and time periods. Further, students are not restricted to their local community; if their question requires a greater range of data, they also have access to the other observatories in the network. Our presentation will explore the design, implementation and lessons learned from the ongoing development of the Ocean Sense program, from its inception to its current form today. Sample activities will be made available.

Local Spatial Obesity Analysis and Estimation Using Online Social Network Sensors.

PubMed

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

2018-03-15

Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively. Copyright © 2018. Published by Elsevier Inc.

Collecting and distributing wearable sensor data: an embedded personal area network to local area network gateway server.

PubMed

Neuhaeuser, Jakob; D'Angelo, Lorenzo T

2013-01-01

The goal of the concept and of the device presented in this contribution is to be able to collect sensor data from wearable sensors directly, automatically and wirelessly and to make them available over a wired local area network. Several concepts in e-health and telemedicine make use of portable and wearable sensors to collect movement or activity data. Usually these data are either collected via a wireless personal area network or using a connection to the user's smartphone. However, users might not carry smartphones on them while inside a residential building such as a nursing home or a hospital, but also within their home. Also, in such areas the use of other wireless communication technologies might be limited. The presented system is an embedded server which can be deployed in several rooms in order to ensure live data collection in bigger buildings. Also, the collection of data batches recorded out of range, as soon as a connection is established, is also possible. Both, the system concept and the realization are presented.

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems.

PubMed

Whitacre, James M; Bender, Axel

2010-06-15

A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

Percolation of localized attack on isolated and interdependent random networks

NASA Astrophysics Data System (ADS)

Shao, Shuai; Huang, Xuqing; Stanley, H. Eugene; Havlin, Shlomo

2014-03-01

Percolation properties of isolated and interdependent random networks have been investigated extensively. The focus of these studies has been on random attacks where each node in network is attacked with the same probability or targeted attack where each node is attacked with a probability being a function of its centrality, such as degree. Here we discuss a new type of realistic attacks which we call a localized attack where a group of neighboring nodes in the networks are attacked. We attack a randomly chosen node, its neighbors, and its neighbor of neighbors and so on, until removing a fraction (1 - p) of the network. This type of attack reflects damages due to localized disasters, such as earthquakes, floods and war zones in real-world networks. We study, both analytically and by simulations the impact of localized attack on percolation properties of random networks with arbitrary degree distributions and discuss in detail random regular (RR) networks, Erdős-Rényi (ER) networks and scale-free (SF) networks. We extend and generalize our theoretical and simulation results of single isolated networks to networks formed of interdependent networks.

Increasing social capital via local networks: analysis in the context of a surgical practice.

PubMed

Thakur, Anjani; Yang, Isaac; Lee, Michael Y; Goel, Arpan; Ashok, Ashwin; Fonkalsrud, Eric W

2002-09-01

The relationship between social capital (support, trust, patient awareness, and increased practice revenue) and local networks (university hospital) in communities has received little attention. The development of computer-based communication networks (social networks) has added a new dimension to the argument, posing the question of whether local networks can (re-)create social capital in local communities. This relationship is examined through a review of the literature on local networks and social capital and a surgeon's practice management from 1990 to 2001 with respect to repair of pectus chest deformities. With respect to pectus repair there was a consistent but small number of new referrals (15-20 new patients/year), lack of patient awareness (eight to 12 self-referred patients/year), and modest practice revenue. Since the inception of an Internet website (social network) dedicated to pectus repair in 1996 there has been increased social participation (n = 630 hits/year to the website); facilitation of spread of information through E-mail messages (n = 430 messages/year); and a greater participation of groups such as women, minorities, adults, and those with disability (n = 120 patients/year). The dissemination of information via the local network has also allowed an "outward movement" with increased participation by interconnecting communities (n = 698,300 global Internet participants based on statistical ratios). We conclude that local networks have enhanced social networks providing new grounds for the development of relationships based on choice and shared interest.

Dynamic Balance of Excitation and Inhibition in Human and Monkey Neocortex

NASA Astrophysics Data System (ADS)

Dehghani, Nima; Peyrache, Adrien; Telenczuk, Bartosz; Le van Quyen, Michel; Halgren, Eric; Cash, Sydney S.; Hatsopoulos, Nicholas G.; Destexhe, Alain

2016-03-01

Balance of excitation and inhibition is a fundamental feature of in vivo network activity and is important for its computations. However, its presence in the neocortex of higher mammals is not well established. We investigated the dynamics of excitation and inhibition using dense multielectrode recordings in humans and monkeys. We found that in all states of the wake-sleep cycle, excitatory and inhibitory ensembles are well balanced, and co-fluctuate with slight instantaneous deviations from perfect balance, mostly in slow-wave sleep. Remarkably, these correlated fluctuations are seen for many different temporal scales. The similarity of these computational features with a network model of self-generated balanced states suggests that such balanced activity is essentially generated by recurrent activity in the local network and is not due to external inputs. Finally, we find that this balance breaks down during seizures, where the temporal correlation of excitatory and inhibitory populations is disrupted. These results show that balanced activity is a feature of normal brain activity, and break down of the balance could be an important factor to define pathological states.

The Effect of Crosslinking on the Microscale Stress Response and Molecular Deformations in Actin Networks

NASA Astrophysics Data System (ADS)

Gurmessa, Bekele; Fitzpatrick, Robert; Valdivia, Jonathon; Anderson, Rae M. R.

Actin, the most abundant protein in eukaryotic cells, is a semi-flexible biopolymer in the cytoskeleton that plays a crucial structural and mechanical role in cell stability, motion and replication, as well as muscle contraction. Most of these mechanically driven structural changes in cells stem from the complex viscoelastic nature of entangled actin networks and the presence of a myriad of proteins that cross-link actin filaments. Despite their importance, the mechanical response of actin networks is not yet well understood, particularly at the molecular level. Here, we use optical trapping - coupled with fluorescence microscopy - to characterize the microscale stress response and induced filament deformations in entangled and cross-linked actin networks subject to localized mechanical perturbations. In particular, we actively drive a microsphere 10 microns through an entangled or cross- linked actin network at a constant speed and measure the resistive force that the deformed actin filaments exert on the bead during and following strain. We simultaneously visualize and track individual sparsely-labeled actin filaments to directly link force response to molecular deformations, and map the propagation of the initially localized perturbation field throughout the rest of the network (~100 um). By varying the concentration of actin and cross-linkers we directly determine the role of crosslinking and entanglements on the length and time scales of stress propagation, molecular deformation and relaxation mechanisms in actin networks.

Low-dimensional attractor for neural activity from local field potentials in optogenetic mice

PubMed Central

Oprisan, Sorinel A.; Lynn, Patrick E.; Tompa, Tamas; Lavin, Antonieta

2015-01-01

We used optogenetic mice to investigate possible nonlinear responses of the medial prefrontal cortex (mPFC) local network to light stimuli delivered by a 473 nm laser through a fiber optics. Every 2 s, a brief 10 ms light pulse was applied and the local field potentials (LFPs) were recorded with a 10 kHz sampling rate. The experiment was repeated 100 times and we only retained and analyzed data from six animals that showed stable and repeatable response to optical stimulations. The presence of nonlinearity in our data was checked using the null hypothesis that the data were linearly correlated in the temporal domain, but were random otherwise. For each trail, 100 surrogate data sets were generated and both time reversal asymmetry and false nearest neighbor (FNN) were used as discriminating statistics for the null hypothesis. We found that nonlinearity is present in all LFP data. The first 0.5 s of each 2 s LFP recording were dominated by the transient response of the networks. For each trial, we used the last 1.5 s of steady activity to measure the phase resetting induced by the brief 10 ms light stimulus. After correcting the LFPs for the effect of phase resetting, additional preprocessing was carried out using dendrograms to identify “similar” groups among LFP trials. We found that the steady dynamics of mPFC in response to light stimuli could be reconstructed in a three-dimensional phase space with topologically similar “8”-shaped attractors across different animals. Our results also open the possibility of designing a low-dimensional model for optical stimulation of the mPFC local network. PMID:26483665

Treatment effect of methylphenidate on intrinsic functional brain network in medication-naïve ADHD children: A multivariate analysis.

PubMed

Yoo, Jae Hyun; Kim, Dohyun; Choi, Jeewook; Jeong, Bumseok

2018-04-01

Methylphenidate is a first-line therapeutic option for treating attention-deficit/hyperactivity disorder (ADHD); however, elicited changes on resting-state functional networks (RSFNs) are not well understood. This study investigated the treatment effect of methylphenidate using a variety of RSFN analyses and explored the collaborative influences of treatment-relevant RSFN changes in children with ADHD. Resting-state functional magnetic resonance imaging was acquired from 20 medication-naïve ADHD children before methylphenidate treatment and twelve weeks later. Changes in large-scale functional connectivity were defined using independent component analysis with dual regression and graph theoretical analysis. The amplitude of low frequency fluctuation (ALFF) was measured to investigate local spontaneous activity alteration. Finally, significant findings were recruited to random forest regression to identify the feature subset that best explains symptom improvement. After twelve weeks of methylphenidate administration, large-scale connectivity was increased between the left fronto-parietal RSFN and the left insula cortex and the right fronto-parietal and the brainstem, while the clustering coefficient (CC) of the global network and nodes, the left fronto-parietal, cerebellum, and occipital pole-visual network, were decreased. ALFF was increased in the bilateral superior parietal cortex and decreased in the right inferior fronto-temporal area. The subset of the local and large-scale RSFN changes, including widespread ALFF changes, the CC of the global network and the cerebellum, could explain the 27.1% variance of the ADHD Rating Scale and 13.72% of the Conner's Parent Rating Scale. Our multivariate approach suggests that the neural mechanism of methylphenidate treatment could be associated with alteration of spontaneous activity in the superior parietal cortex or widespread brain regions as well as functional segregation of the large-scale intrinsic functional network.

Dynamic aftereffects in supplementary motor network following inhibitory transcranial magnetic stimulation protocols.

PubMed

Ji, Gong-Jun; Yu, Fengqiong; Liao, Wei; Wang, Kai

2017-04-01

The supplementary motor area (SMA) is a key node of the motor network. Inhibitory repetitive transcranial magnetic stimulation (rTMS) of the SMA can potentially improve movement disorders. However, the aftereffects of inhibitory rTMS on brain function remain largely unknown. Using a single-blind, crossover within-subject design, we investigated the role of aftereffects with two inhibitory rTMS protocols [1800 pulses of either 1-Hz repetitive stimulation or continuous theta burst stimulation (cTBS)] on the left SMA. A total of 19 healthy volunteers participated in the rTMS sessions on 2 separate days. Firstly, short-term aftereffects were estimated at three levels (functional connectivity, local activity, and network properties) by comparing the resting-state functional magnetic resonance imaging datasets (9min) acquired before and after each rTMS session. Local activity and network properties were not significantly altered by either protocol. Functional connectivity within the SMA network was increased (in the left paracentral gyrus) by 1-Hz stimulation and decreased (in the left inferior frontal gyrus and SMA/middle cingulate cortex) by cTBS. The subsequent three-way analysis of variance (site×time×protocol) did not show a significant interaction effect or "protocol" main effect, suggesting that the two protocols share an underlying mechanism. Secondly, sliding-window analysis was used to evaluate the dynamic features of aftereffects in the ~29min after the end of stimulation. Aftereffects were maintained for a maximum of 9.8 and 6.6min after the 1-Hz and cTBS protocols, respectively. In summary, this study revealed topographical and temporal aftereffects in the SMA network following inhibitory rTMS protocols, providing valuable information for their application in future neuroscience and clinical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

A study of the Immune Epitope Database for some fungi species using network topological indices.

PubMed

Vázquez-Prieto, Severo; Paniagua, Esperanza; Solana, Hugo; Ubeira, Florencio M; González-Díaz, Humberto

2017-08-01

In the last years, the encryption of system structure information with different network topological indices has been a very active field of research. In the present study, we assembled for the first time a complex network using data obtained from the Immune Epitope Database for fungi species, and we then considered the general topology, the node degree distribution, and the local structure of this network. We also calculated eight node centrality measures for the observed network and compared it with three theoretical models. In view of the results obtained, we may expect that the present approach can become a valuable tool to explore the complexity of this database, as well as for the storage, manipulation, comparison, and retrieval of information contained therein.

Microscale Spatiotemporal Dynamics during Neocortical Propagation of Human Focal Seizures

PubMed Central

Wagner, Fabien B.; Eskandar, Emad N.; Cosgrove, G. Rees; Madsen, Joseph R.; Blum, Andrew S.; Potter, N. Stevenson; Hochberg, Leigh R.; Cash, Sydney S.; Truccolo, Wilson

2015-01-01

Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4 × 4 mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) A newly developed stage segmentation method, applied to local field potentials (LFPs) and multi-unit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~ 2–3Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25–60 Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the MUA peak onset time (in seizures where such peak onset occurred) and changes in MUA or LFP propagation patterns. Overall, our findings indicate that the recruitment of neocortical territories into ictal activity undergo complex spatiotemporal dynamics evolving in slow discrete states, which are consistent across seizures within each patient. Furthermore, ictal states at finer spatiotemporal scales (individual SWDs or gamma oscillations) are organized by slower time-scale network dynamics evolving through these discrete stages. PMID:26279211

Cholinergic modulation of the parafacial respiratory group

PubMed Central

Boutin, Rozlyn C. T.; Alsahafi, Zaki

2016-01-01

Key points This study investigates the effects of cholinergic transmission on the expiratory oscillator, the parafacial respiratory group (pFRG) in urethane anaesthetized adult rats.Local inhibition of the acetyl cholinesterase enzyme induced activation of expiratory abdominal muscles and active expiration.Local application of the cholinomimetic carbachol elicited recruitment of late expiratory neurons, expiratory abdominal muscle activity and active expiration. This effect was antagonized by local application of the muscarinic antagonists scopolamine, J104129 and 4DAMP.We observed distinct physiological responses between the more medial chemosensitive region of the retrotrapezoid nucleus and the more lateral region of pFRG.These results support the hypothesis that pFRG is under cholinergic neuromodulation and the region surrounding the facial nucleus contains a group of neurons with distinct physiological roles. Abstract Active inspiration and expiration are opposing respiratory phases generated by two separate oscillators in the brainstem: inspiration driven by a neuronal network located in the preBötzinger complex (preBötC) and expiration driven by a neuronal network located in the parafacial respiratory group (pFRG). While continuous activity of the preBötC is necessary for maintaining ventilation, the pFRG behaves as a conditional expiratory oscillator, being silent in resting conditions and becoming rhythmically active in the presence of increased respiratory drive (e.g. hypoxia, hypercapnia, exercise and through release of inhibition). Recent evidence from our laboratory suggests that expiratory activity in the principal expiratory pump muscles, the abdominals, is modulated in a state‐dependent fashion, frequently occurring during periods of REM sleep. We hypothesized that acetylcholine, a neurotransmitter released in wakefulness and REM sleep by mesopontine structures, contributes to the activation of pFRG neurons and thus acts to promote the recruitment of expiratory abdominal muscle activity. We investigated the stimulatory effect of cholinergic neurotransmission on pFRG activity and recruitment of active expiration in vivo under anaesthesia. We demonstrate that local application of the acetylcholinesterase inhibitor physostigmine into the pFRG potentiated expiratory activity. Furthermore, local application of the cholinomimetic carbachol into the pFRG activated late expiratory neurons and induced long lasting rhythmic active expiration. This effect was completely abolished by pre‐application of the muscarinic antagonist scopolamine, and more selective M3 antagonists 4DAMP and J104129. We conclude that cholinergic muscarinic transmission contributes to excitation of pFRG neurons and promotes both active recruitment of abdominal muscles and active expiratory flow. PMID:27808424

Being connected to the local community through a Festival mobile application

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

Han, Kyungsik; Wirth, Richard; Hanrahan, Benjamin

In this paper we report our investigation into how using and interacting with a local festival mobile app enhanced users’ festival experiences and connected them to other local users and their community. We explored the relationship between users’ perceived basic affordances of mobile technology, perceived opportunities of the festival app, and three elements that sustain the local community — attachment, engagement, and social support networks. Based on the usage logs of 348 active users, as well as survey responses from 80 users, we present a mobile-mediated local community framework and found that engagement is a key mediator of mobile experiencesmore » and facets of community.« less

a Weighted Local-World Evolving Network Model Based on the Edge Weights Preferential Selection

NASA Astrophysics Data System (ADS)

Li, Ping; Zhao, Qingzhen; Wang, Haitang

2013-05-01

In this paper, we use the edge weights preferential attachment mechanism to build a new local-world evolutionary model for weighted networks. It is different from previous papers that the local-world of our model consists of edges instead of nodes. Each time step, we connect a new node to two existing nodes in the local-world through the edge weights preferential selection. Theoretical analysis and numerical simulations show that the scale of the local-world affect on the weight distribution, the strength distribution and the degree distribution. We give the simulations about the clustering coefficient and the dynamics of infectious diseases spreading. The weight dynamics of our network model can portray the structure of realistic networks such as neural network of the nematode C. elegans and Online Social Network.

Effect of acute stretch injury on action potential and network activity of rat neocortical neurons in culture.

PubMed

Magou, George C; Pfister, Bryan J; Berlin, Joshua R

2015-10-22

The basis for acute seizures following traumatic brain injury (TBI) remains unclear. Animal models of TBI have revealed acute hyperexcitablility in cortical neurons that could underlie seizure activity, but studying initiating events causing hyperexcitability is difficult in these models. In vitro models of stretch injury with cultured cortical neurons, a surrogate for TBI, allow facile investigation of cellular changes after injury but they have only demonstrated post-injury hypoexcitability. The goal of this study was to determine if neuronal hyperexcitability could be triggered by in vitro stretch injury. Controlled uniaxial stretch injury was delivered to a spatially delimited region of a spontaneously active network of cultured rat cortical neurons, yielding a region of stretch-injured neurons and adjacent regions of non-stretched neurons that did not directly experience stretch injury. Spontaneous electrical activity was measured in non-stretched and stretch-injured neurons, and in control neuronal networks not subjected to stretch injury. Non-stretched neurons in stretch-injured cultures displayed a three-fold increase in action potential firing rate and bursting activity 30-60 min post-injury. Stretch-injured neurons, however, displayed dramatically lower rates of action potential firing and bursting. These results demonstrate that acute hyperexcitability can be observed in non-stretched neurons located in regions adjacent to the site of stretch injury, consistent with reports that seizure activity can arise from regions surrounding the site of localized brain injury. Thus, this in vitro procedure for localized neuronal stretch injury may provide a model to study the earliest cellular changes in neuronal function associated with acute post-traumatic seizures. Copyright © 2015. Published by Elsevier B.V.

Networking CD-ROMs: The Decision Maker's Guide to Local Area Network Solutions.

ERIC Educational Resources Information Center

Elshami, Ahmed M.

In an era when patrons want access to CD-ROM resources but few libraries can afford to buy multiple copies, CD-ROM local area networks (LANs) are emerging as a cost-effective way to provide shared access. To help librarians make informed decisions, this manual offers information on: (1) the basics of LANs, a "local area network primer";…

Localization and Spreading of Diseases in Complex Networks

NASA Astrophysics Data System (ADS)

Goltsev, A. V.; Dorogovtsev, S. N.; Oliveira, J. G.; Mendes, J. F. F.

2012-09-01

Using the susceptible-infected-susceptible model on unweighted and weighted networks, we consider the disease localization phenomenon. In contrast to the well-recognized point of view that diseases infect a finite fraction of vertices right above the epidemic threshold, we show that diseases can be localized on a finite number of vertices, where hubs and edges with large weights are centers of localization. Our results follow from the analysis of standard models of networks and empirical data for real-world networks.

Hierarchy of Information Processing in the Brain: A Novel 'Intrinsic Ignition' Framework.

PubMed

Deco, Gustavo; Kringelbach, Morten L

2017-06-07

A general theory of brain function has to be able to explain local and non-local network computations over space and time. We propose a new framework to capture the key principles of how local activity influences global computation, i.e., describing the propagation of information and thus the broadness of communication driven by local activity. More specifically, we consider the diversity in space (nodes or brain regions) over time using the concept of intrinsic ignition, which are naturally occurring intrinsic perturbations reflecting the capability of a given brain area to propagate neuronal activity to other regions in a given brain state. Characterizing the profile of intrinsic ignition for a given brain state provides insight into the precise nature of hierarchical information processing. Combining this data-driven method with a causal whole-brain computational model can provide novel insights into the imbalance of brain states found in neuropsychiatric disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

Confinement regulates complex biochemical networks: initiation of blood clotting by "diffusion acting".

PubMed

Shen, Feng; Pompano, Rebecca R; Kastrup, Christian J; Ismagilov, Rustem F

2009-10-21

This study shows that environmental confinement strongly affects the activation of nonlinear reaction networks, such as blood coagulation (clotting), by small quantities of activators. Blood coagulation is sensitive to the local concentration of soluble activators, initiating only when the activators surpass a threshold concentration, and therefore is regulated by mass transport phenomena such as flow and diffusion. Here, diffusion was limited by decreasing the size of microfluidic chambers, and it was found that microparticles carrying either the classical stimulus, tissue factor, or a bacterial stimulus, Bacillus cereus, initiated coagulation of human platelet-poor plasma only when confined. A simple analytical argument and numerical model were used to describe the mechanism for this phenomenon: confinement causes diffusible activators to accumulate locally and surpass the threshold concentration. To interpret the results, a dimensionless confinement number, Cn, was used to describe whether a stimulus was confined, and a Damköhler number, Da(2), was used to describe whether a subthreshold stimulus could initiate coagulation. In the context of initiation of coagulation by bacteria, this mechanism can be thought of as "diffusion acting", which is distinct from "diffusion sensing". The ability of confinement and diffusion acting to change the outcome of coagulation suggests that confinement should also regulate other biological "on" and "off" processes that are controlled by thresholds.

Advanced Algorithms for Local Routing Strategy on Complex Networks

PubMed Central

Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K.; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

2016-01-01

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks. PMID:27434502

Advanced Algorithms for Local Routing Strategy on Complex Networks.

PubMed

Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

2016-01-01

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70-90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks.

Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models.

PubMed

Mazzoni, Alberto; Lindén, Henrik; Cuntz, Hermann; Lansner, Anders; Panzeri, Stefano; Einevoll, Gaute T

2015-12-01

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

PubMed Central

Cuntz, Hermann; Lansner, Anders; Panzeri, Stefano; Einevoll, Gaute T.

2015-01-01

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best “LFP proxy”, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with “ground-truth” LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo. PMID:26657024

Verification of the Usefulness of the Trimble Rtx Extended Satellite Technology with the Xfill Function in the Local Network Implementing Rtk Measurements

NASA Astrophysics Data System (ADS)

Siejka, Zbigniew

2014-12-01

The paper presents the method of satellite measurements, which gives users the ability of GNSS continuous precise positioning in real time, even in the case of short interruptions in receiving the correction of the local ground system of measurements support. The proposed method is a combination of two satellite positioning technologies RTN GNSS and RTX Extended. In technology RTX Extended the xFill function was used for precise positioning in real time and in the local reference system. This function provides the ability to perform measurement without the need for constant communication with the ground support satellite system. Test measurements were performed on a test basis located in Krakow, and RTN GNSS positioning was done based on the national network of reference stations of the ASGEUPOS. The solution allows for short (up to 5 minutes) interruptions in radio or internet communication. When the primary stream of RTN correction is not available, then the global corrections Trimble xFill broadcasted by satellite are used. The new technology uses in the real-time data from the global network of tracking stations and contributes significantly to improving the quality and efficiency of surveying works. At present according to the authors, technology Trimble CenterPoint RTX can guarantee repeatability of measurements not worse than 3.8 cm (Trimble Survey Division, 2012). In the paper the comparative analysis of measurement results between the two technologies was performed: RTN carried out in the classic way, which was based on the corrections of the terrestrial local network of the Polish system of active geodetic network (ASG-EUPOS) and RTK xFill technology. The results were related to the data of test network, established as error free. The research gave satisfactory results and confirmed the great potential of the use of the new technology in the geodetic work realization. By combining these two technologies of GNSS surveying the user can greatly improve the overall performance of real-time positioning.

Why Join an Art Education Organization?: Part 1

ERIC Educational Resources Information Center

Passmore, Kaye

2006-01-01

In this article, the author discusses several good reasons for belonging to local, state, and national professional art education organizations. When one actively participates, he/she develops networks with other art educators. Professional organizations provide opportunities for professional development, service, and leadership. One's teaching…

User recommendation in healthcare social media by assessing user similarity in heterogeneous network.

PubMed

Jiang, Ling; Yang, Christopher C

2017-09-01

The rapid growth of online health social websites has captured a vast amount of healthcare information and made the information easy to access for health consumers. E-patients often use these social websites for informational and emotional support. However, health consumers could be easily overwhelmed by the overloaded information. Healthcare information searching can be very difficult for consumers, not to mention most of them are not skilled information searcher. In this work, we investigate the approaches for measuring user similarity in online health social websites. By recommending similar users to consumers, we can help them to seek informational and emotional support in a more efficient way. We propose to represent the healthcare social media data as a heterogeneous healthcare information network and introduce the local and global structural approaches for measuring user similarity in a heterogeneous network. We compare the proposed structural approaches with the content-based approach. Experiments were conducted on a dataset collected from a popular online health social website, and the results showed that content-based approach performed better for inactive users, while structural approaches performed better for active users. Moreover, global structural approach outperformed local structural approach for all user groups. In addition, we conducted experiments on local and global structural approaches using different weight schemas for the edges in the network. Leverage performed the best for both local and global approaches. Finally, we integrated different approaches and demonstrated that hybrid method yielded better performance than the individual approach. The results indicate that content-based methods can effectively capture the similarity of inactive users who usually have focused interests, while structural methods can achieve better performance when rich structural information is available. Local structural approach only considers direct connections between nodes in the network, while global structural approach takes the indirect connections into account. Therefore, the global similarity approach can deal with sparse networks and capture the implicit similarity between two users. Different approaches may capture different aspects of the similarity relationship between two users. When we combine different methods together, we could achieve a better performance than using each individual method. Copyright © 2017 Elsevier B.V. All rights reserved.

Cell shape and negative links in regulatory motifs together control spatial information flow in signaling networks.

PubMed

Neves, Susana R; Tsokas, Panayiotis; Sarkar, Anamika; Grace, Elizabeth A; Rangamani, Padmini; Taubenfeld, Stephen M; Alberini, Cristina M; Schaff, James C; Blitzer, Robert D; Moraru, Ion I; Iyengar, Ravi

2008-05-16

The role of cell size and shape in controlling local intracellular signaling reactions, and how this spatial information originates and is propagated, is not well understood. We have used partial differential equations to model the flow of spatial information from the beta-adrenergic receptor to MAPK1,2 through the cAMP/PKA/B-Raf/MAPK1,2 network in neurons using real geometries. The numerical simulations indicated that cell shape controls the dynamics of local biochemical activity of signal-modulated negative regulators, such as phosphodiesterases and protein phosphatases within regulatory loops to determine the size of microdomains of activated signaling components. The model prediction that negative regulators control the flow of spatial information to downstream components was verified experimentally in rat hippocampal slices. These results suggest a mechanism by which cellular geometry, the presence of regulatory loops with negative regulators, and key reaction rates all together control spatial information transfer and microdomain characteristics within cells.

Domain-General Brain Regions Do Not Track Linguistic Input as Closely as Language-Selective Regions.

PubMed

Blank, Idan A; Fedorenko, Evelina

2017-10-11

Language comprehension engages a cortical network of left frontal and temporal regions. Activity in this network is language-selective, showing virtually no modulation by nonlinguistic tasks. In addition, language comprehension engages a second network consisting of bilateral frontal, parietal, cingulate, and insular regions. Activity in this "multiple demand" (MD) network scales with comprehension difficulty, but also with cognitive effort across a wide range of nonlinguistic tasks in a domain-general fashion. Given the functional dissociation between the language and MD networks, their respective contributions to comprehension are likely distinct, yet such differences remain elusive. Prior neuroimaging studies have suggested that activity in each network covaries with some linguistic features that, behaviorally, influence on-line processing and comprehension. This sensitivity of the language and MD networks to local input characteristics has often been interpreted, implicitly or explicitly, as evidence that both networks track linguistic input closely, and in a manner consistent across individuals. Here, we used fMRI to directly test this assumption by comparing the BOLD signal time courses in each network across different people ( n = 45, men and women) listening to the same story. Language network activity showed fewer individual differences, indicative of closer input tracking, whereas MD network activity was more idiosyncratic and, moreover, showed lower reliability within an individual across repetitions of a story. These findings constrain cognitive models of language comprehension by suggesting a novel distinction between the processes implemented in the language and MD networks. SIGNIFICANCE STATEMENT Language comprehension recruits both language-specific mechanisms and domain-general mechanisms that are engaged in many cognitive processes. In the human cortex, language-selective mechanisms are implemented in the left-lateralized "core language network", whereas domain-general mechanisms are implemented in the bilateral "multiple demand" (MD) network. Here, we report the first direct comparison of the respective contributions of these networks to naturalistic story comprehension. Using a novel combination of neuroimaging approaches we find that MD regions track stories less closely than language regions. This finding constrains the possible contributions of the MD network to comprehension, contrasts with accounts positing that this network has continuous access to linguistic input, and suggests a new typology of comprehension processes based on their extent of input tracking. Copyright © 2017 the authors 0270-6474/17/3710000-13$15.00/0.

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.

The Teen Science Café Network

NASA Astrophysics Data System (ADS)

Hall, M.; Mayhew, M. A.

2013-12-01

The 'Teen Cafè' phenomenon grew out of an NSF-funded experiment to bring the Cafè Scientifique model for engagement of the public with science and scientists to high school teenagers. Cafè Scientifique New Mexico (cafènm.org), now in its seventh year, has proven highly popular with high school teens for much the same reason as for adult Cafè programs: the blend of socializing in an attractive venue and interaction with a scientist on an interesting science topic. Teen Cafés also include exploration of the topic with hands-on activities. The success of the model has led to the creation of the national Teen Science Cafè Network (teensciencecafe.org. This first year of the new program, four 'Founding Members' of the Network-- in Florida, Colorado, North Carolina, and the St. Louis, Missouri region--started up Teen Cafè programs. Each applied the model with a unique flair appropriate to local institutions and demographics. Each Member in the Network runs Cafès in multiple local venues. We are now gearing up for our second year, and the Network is growing. Our Teen Cafè topics have covered a very wide range, from belly-button biodiversity to cyber-security to patterns of mega-earthquakes to a day in the life of a teen dolphin to corals on acid to emergency room medicine to alternative fuel cars. Presenters have come from a great variety of local institutions. Though they are popular with teens because they are fun and interesting, our evaluations have demonstrated that the programs are having a significant impact on participating teens' understanding of the nature of science, the work that scientists do, and the importance of science to their daily lives. We are also having success in training scientists to communicate effectively with this public audience. Presenters report strong satisfaction with their resulting quality of science communication. A surprising number have reported that their experience with the program has led them to think in a new way about the significance of their own research and how best to communicate it. In addition to Members who offer Teen Cafés, we have Affiliate Organizations, including professional societies and research centers, which are actively helping us introduce the Teen Science Café model to their membership. Rather than being a collection of static, independent entities, Network Members and Affiliate Organizations are part of a dynamic network, a community of practice with active sharing of lessons learned, ideas for Café topics and formats, professional development in communicating with the public, expertise in social media, and many other resources. We want the Network as a whole to be much greater than the sum of its parts. To ensure the integrity of the Network, we are exploring strategies for effective growth, mechanisms for continual professional development for Café leaders, and collaborative approaches to sustainability. Any organization wishing to start a Teen Cafè can do so by registering on the Teen Science Café Network website and agreeing to adhere to five 'Core Design Principles.' We have resources to help others start a Teen Café, as it is part of the ethic of the Network that existing Members will actively help new Members start and successfully run a Teen Café program.

Screening the Molecular Framework Underlying Local Dendritic mRNA Translation

PubMed Central

Namjoshi, Sanjeev V.; Raab-Graham, Kimberly F.

2017-01-01

In the last decade, bioinformatic analyses of high-throughput proteomics and transcriptomics data have enabled researchers to gain insight into the molecular networks that may underlie lasting changes in synaptic efficacy. Development and utilization of these techniques have advanced the field of learning and memory significantly. It is now possible to move from the study of activity-dependent changes of a single protein to modeling entire network changes that require local protein synthesis. This data revolution has necessitated the development of alternative computational and statistical techniques to analyze and understand the patterns contained within. Thus, the focus of this review is to provide a synopsis of the journey and evolution toward big data techniques to address still unanswered questions regarding how synapses are modified to strengthen neuronal circuits. We first review the seminal studies that demonstrated the pivotal role played by local mRNA translation as the mechanism underlying the enhancement of enduring synaptic activity. In the interest of those who are new to the field, we provide a brief overview of molecular biology and biochemical techniques utilized for sample preparation to identify locally translated proteins using RNA sequencing and proteomics, as well as the computational approaches used to analyze these data. While many mRNAs have been identified, few have been shown to be locally synthesized. To this end, we review techniques currently being utilized to visualize new protein synthesis, a task that has proven to be the most difficult aspect of the field. Finally, we provide examples of future applications to test the physiological relevance of locally synthesized proteins identified by big data approaches. PMID:28286470

Theorems and application of local activity of CNN with five state variables and one port.

PubMed

Xiong, Gang; Dong, Xisong; Xie, Li; Yang, Thomas

2012-01-01

Coupled nonlinear dynamical systems have been widely studied recently. However, the dynamical properties of these systems are difficult to deal with. The local activity of cellular neural network (CNN) has provided a powerful tool for studying the emergence of complex patterns in a homogeneous lattice, which is composed of coupled cells. In this paper, the analytical criteria for the local activity in reaction-diffusion CNN with five state variables and one port are presented, which consists of four theorems, including a serial of inequalities involving CNN parameters. These theorems can be used for calculating the bifurcation diagram to determine or analyze the emergence of complex dynamic patterns, such as chaos. As a case study, a reaction-diffusion CNN of hepatitis B Virus (HBV) mutation-selection model is analyzed and simulated, the bifurcation diagram is calculated. Using the diagram, numerical simulations of this CNN model provide reasonable explanations of complex mutant phenomena during therapy. Therefore, it is demonstrated that the local activity of CNN provides a practical tool for the complex dynamics study of some coupled nonlinear systems.

Anti-correlated cortical networks arise from spontaneous neuronal dynamics at slow timescales.

PubMed

Kodama, Nathan X; Feng, Tianyi; Ullett, James J; Chiel, Hillel J; Sivakumar, Siddharth S; Galán, Roberto F

2018-01-12

In the highly interconnected architectures of the cerebral cortex, recurrent intracortical loops disproportionately outnumber thalamo-cortical inputs. These networks are also capable of generating neuronal activity without feedforward sensory drive. It is unknown, however, what spatiotemporal patterns may be solely attributed to intrinsic connections of the local cortical network. Using high-density microelectrode arrays, here we show that in the isolated, primary somatosensory cortex of mice, neuronal firing fluctuates on timescales from milliseconds to tens of seconds. Slower firing fluctuations reveal two spatially distinct neuronal ensembles, which correspond to superficial and deeper layers. These ensembles are anti-correlated: when one fires more, the other fires less and vice versa. This interplay is clearest at timescales of several seconds and is therefore consistent with shifts between active sensing and anticipatory behavioral states in mice.

Synchronous inhibitory potentials precede seizure-like events in acute models of focal limbic seizures.

PubMed

Uva, Laura; Breschi, Gian Luca; Gnatkovsky, Vadym; Taverna, Stefano; de Curtis, Marco

2015-02-18

Interictal spikes in models of focal seizures and epilepsies are sustained by the synchronous activation of glutamatergic and GABAergic networks. The nature of population spikes associated with seizure initiation (pre-ictal spikes; PSs) is still undetermined. We analyzed the networks involved in the generation of both interictal and PSs in acute models of limbic cortex ictogenesis induced by pharmacological manipulations. Simultaneous extracellular and intracellular recordings from both principal cells and interneurons were performed in the medial entorhinal cortex of the in vitro isolated guinea pig brain during focal interictal and ictal discharges induced in the limbic network by intracortical and brief arterial infusions of either bicuculline methiodide (BMI) or 4-aminopyridine (4AP). Local application of BMI in the entorhinal cortex did not induce seizure-like events (SLEs), but did generate periodic interictal spikes sensitive to the glutamatergic non-NMDA receptor antagonist DNQX. Unlike local applications, arterial perfusion of either BMI or 4AP induced focal limbic SLEs. PSs just ahead of SLE were associated with hyperpolarizing potentials coupled with a complete blockade of firing in principal cells and burst discharges in putative interneurons. Interictal population spikes recorded from principal neurons between two SLEs correlated with a depolarizing potential. We demonstrate in two models of acute limbic SLE that PS events are different from interictal spikes and are sustained by synchronous activation of inhibitory networks. Our findings support a prominent role of synchronous network inhibition in the initiation of a focal seizure. Copyright © 2015 the authors 0270-6474/15/353048-08$15.00/0.

A range-based predictive localization algorithm for WSID networks

NASA Astrophysics Data System (ADS)

Liu, Yuan; Chen, Junjie; Li, Gang

2017-11-01

Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

PhysDoc: A Distributed Network of Physics Institutions: Collecting, Indexing, and Searching High Quality Documents by Using Harvest; The Dublin Core Metadata Initiative: Mission, Current Activities, and Future Directions; Information Services for Higher Education: A New Competitive Space; Intellectual Property Conservancies.

ERIC Educational Resources Information Center

Severiens, Thomas; Hohlfeld, Michael; Zimmermann, Kerstin; Hilf, Eberhard R.; von Ossietzky, Carl; Weibel, Stuart L.; Koch, Traugott; Hughes, Carol Ann; Bearman, David

2000-01-01

Includes four articles that discuss a variety to topics, including a distributed network of physics institutions documents called PhysDocs which harvests information from the local Web-servers of professional physics institutions; the Dublin Core metadata initiative; information services for higher education in a competitive environment; and…

Grand Forks - East Grand Forks Urban Water Resources Study. Flood Control Appendix.

DTIC Science & Technology

1981-07-01

Reach 4) is served by an extensive network of roads 4 ,! and railroads. U.S. Highway -2, Demers Avenue, and Minnesota Avenue pro- vide easy access to...their current focus of employment and social activity. It would require the construction of a new transportation and utility network at immense local...115 205 (1) See figure 4. (2) Outside study area; not to be devoped . Table 2 - Estimated peak runoff 10-year frequency Peak flow Existing Future

Differential Modulation of Spontaneous and Evoked Thalamocortical Network Activity by Acetylcholine Level In Vitro

PubMed Central

Wester, Jason C.

2013-01-01

Different levels of cholinergic neuromodulatory tone have been hypothesized to set the state of cortical circuits either to one dominated by local cortical recurrent activity (low ACh) or to one dependent on thalamic input (high ACh). High ACh levels depress intracortical but facilitate thalamocortical synapses, whereas low levels potentiate intracortical synapses. Furthermore, recent work has implicated the thalamus in controlling cortical network state during waking and attention, when ACh levels are highest. To test this hypothesis, we used rat thalamocortical slices maintained in medium to generate spontaneous up- and down-states and applied different ACh concentrations to slices in which thalamocortical connections were either maintained or severed. The effects on spontaneous and evoked up-states were measured using voltage-sensitive dye imaging, intracellular recordings, local field potentials, and single/multiunit activity. We found that high ACh can increase the frequency of spontaneous up-states, but reduces their duration in slices with intact thalamocortical connections. Strikingly, when thalamic connections are severed, high ACh instead greatly reduces or abolishes spontaneous up-states. Furthermore, high ACh reduces the spatial propagation, velocity, and depolarization amplitude of evoked up-states. In contrast, low ACh dramatically increases up-state frequency regardless of the presence or absence of intact thalamocortical connections and does not reduce the duration, spatial propagation, or velocity of evoked up-states. Therefore, our data support the hypothesis that strong cholinergic modulation increases the influence, and thus the signal-to-noise ratio, of afferent input over local cortical activity and that lower cholinergic tone enhances recurrent cortical activity regardless of thalamic input. PMID:24198382

Contributions of diverse excitatory and inhibitory neurons to recurrent network activity in cerebral cortex.

PubMed

Neske, Garrett T; Patrick, Saundra L; Connors, Barry W

2015-01-21

The recurrent synaptic architecture of neocortex allows for self-generated network activity. One form of such activity is the Up state, in which neurons transiently receive barrages of excitatory and inhibitory synaptic inputs that depolarize many neurons to spike threshold before returning to a relatively quiescent Down state. The extent to which different cell types participate in Up states is still unclear. Inhibitory interneurons have particularly diverse intrinsic properties and synaptic connections with the local network, suggesting that different interneurons might play different roles in activated network states. We have studied the firing, subthreshold behavior, and synaptic conductances of identified cell types during Up and Down states in layers 5 and 2/3 in mouse barrel cortex in vitro. We recorded from pyramidal cells and interneurons expressing parvalbumin (PV), somatostatin (SOM), vasoactive intestinal peptide (VIP), or neuropeptide Y. PV cells were the most active interneuron subtype during the Up state, yet the other subtypes also received substantial synaptic conductances and often generated spikes. In all cell types except PV cells, the beginning of the Up state was dominated by synaptic inhibition, which decreased thereafter; excitation was more persistent, suggesting that inhibition is not the dominant force in terminating Up states. Compared with barrel cortex, SOM and VIP cells were much less active in entorhinal cortex during Up states. Our results provide a measure of functional connectivity of various neuron types in barrel cortex and suggest differential roles for interneuron types in the generation and control of persistent network activity. Copyright © 2015 the authors 0270-6474/15/351089-17$15.00/0.

Contesting Technologies in the Networked Society: A Case Study of Hydraulic Fracturing and Shale Development

NASA Astrophysics Data System (ADS)

Hopke, Jill E.

In this dissertation, I study the network structure and content of a transnational movement against hydraulic fracturing and shale development, Global Frackdown. I apply a relational perspective to the study of role of digital technologies in transnational political organizing. I examine the structure of the social movement through analysis of hyperlinking patterns and qualitative analysis of the content of the ties in one strand of the movement. I explicate three actor types: coordinator, broker, and hyper-local. This research intervenes in the paradigm that considers international actors as the key nodes to understanding transnational advocacy networks. I argue this focus on the international scale obscures the role of globally minded local groups in mediating global issues back to the hyper-local scale. While international NGOs play a coordinating role, local groups with a global worldview can connect transnational movements to the hyper-local scale by networking with groups that are too small to appear in a transnational network. I also examine the movement's messaging on the social media platform Twitter. Findings show that Global Frackdown tweeters engage in framing practices of: movement convergence and solidarity, declarative and targeted engagement, prefabricated messaging, and multilingual tweeting. The episodic, loosely-coordinated and often personalized, transnational framing practices of Global Frackdown tweeters support core organizers' goal of promoting the globalness of activism to ban fracking. Global Frackdown activists use Twitter as a tool to advance the movement and to bolster its moral authority, as well as to forge linkages between localized groups on a transnational scale. Lastly, I study the relative prominence of negative messaging about shale development in relation to pro-shale messaging on Twitter across five hashtags (#fracking, #globalfrackdown, #natgas, #shale, and #shalegas). I analyze the top actors tweeting using the #fracking hashtag and receiving mentions with the hashtag. Results show statistically significant differences in the sentiment about shale development across the five hashtags. Results also indicate that the discourse on the main contested hashtag #fracking is dominated by activists, both individual activists and organizations.

Physics of Financial Markets: Can we Understand the Unpredictable Phenomenon of Flash Crashes

NASA Astrophysics Data System (ADS)

Stanley, H. Eugene

2015-03-01

Dangerous vulnerability is hiding in complex systems. Indeed, disasters ranging from abrupt financial ``flash crashes'' and large-scale power outages to sudden death among the elderly dramatically exemplify this fact. While we can understand the cause of most events in complex systems, sudden unexpected ``black swans'' whether in economics or in the ``physicists world'' cry out for insight. To design more resilient systems we will describe recent results seeking understanding of these black swans. In many real-world phenomena, such as brain seizures in neuroscience or sudden market crashes in finance, after an inactive period of time a significant part of the damaged network is capable of spontaneously becoming active again. The process often occurs repeatedly. To model this marked network recovery, we examine the effect of local node recoveries and stochastic contiguous spreading, and find that they can lead to the spontaneous emergence of macroscopic ``phase-flipping'' phenomena. The fraction of active nodes switches back and forth between the two network collective modes characterized by high network activity and low network activity. Furthermore, the system exhibits a strong hysteresis behavior analogous to phase transitions near a critical point [A. Majdandzic, B. Podobnik, S. V. Buldyrev, D. Y. Kenett, S. Havlin, and H. E. Stanley, ``Spontaneous Recovery in Dynamic Networks,'' Nature Physics 10, 34 (2014)]. This work was carried out in collaboration with a number of colleagues, chief among whom are A. Majdanzic, B. Podobnik, S. V. Buldyrev, D. Y. Kenett, and S. Havlin.

How structure sculpts function: Unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure

NASA Astrophysics Data System (ADS)

Bettinardi, R. G.; Deco, G.; Karlaftis, V. M.; Van Hartevelt, T. J.; Fernandes, H. M.; Kourtzi, Z.; Kringelbach, M. L.; Zamora-López, G.

2017-04-01

Intrinsic brain activity is characterized by highly organized co-activations between different regions, forming clustered spatial patterns referred to as resting-state networks. The observed co-activation patterns are sustained by the intricate fabric of millions of interconnected neurons constituting the brain's wiring diagram. However, as for other real networks, the relationship between the connectional structure and the emergent collective dynamics still evades complete understanding. Here, we show that it is possible to estimate the expected pair-wise correlations that a network tends to generate thanks to the underlying path structure. We start from the assumption that in order for two nodes to exhibit correlated activity, they must be exposed to similar input patterns from the entire network. We then acknowledge that information rarely spreads only along a unique route but rather travels along all possible paths. In real networks, the strength of local perturbations tends to decay as they propagate away from the sources, leading to a progressive attenuation of the original information content and, thus, of their influence. Accordingly, we define a novel graph measure, topological similarity, which quantifies the propensity of two nodes to dynamically correlate as a function of the resemblance of the overall influences they are expected to receive due to the underlying structure of the network. Applied to the human brain, we find that the similarity of whole-network inputs, estimated from the topology of the anatomical connectome, plays an important role in sculpting the backbone pattern of time-average correlations observed at rest.

A local structure model for network analysis

DOE PAGES

Casleton, Emily; Nordman, Daniel; Kaiser, Mark

2017-04-01

The statistical analysis of networks is a popular research topic with ever widening applications. Exponential random graph models (ERGMs), which specify a model through interpretable, global network features, are common for this purpose. In this study we introduce a new class of models for network analysis, called local structure graph models (LSGMs). In contrast to an ERGM, a LSGM specifies a network model through local features and allows for an interpretable and controllable local dependence structure. In particular, LSGMs are formulated by a set of full conditional distributions for each network edge, e.g., the probability of edge presence/absence, depending onmore » neighborhoods of other edges. Additional model features are introduced to aid in specification and to help alleviate a common issue (occurring also with ERGMs) of model degeneracy. Finally, the proposed models are demonstrated on a network of tornadoes in Arkansas where a LSGM is shown to perform significantly better than a model without local dependence.« less

A local structure model for network analysis

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

Casleton, Emily; Nordman, Daniel; Kaiser, Mark

The statistical analysis of networks is a popular research topic with ever widening applications. Exponential random graph models (ERGMs), which specify a model through interpretable, global network features, are common for this purpose. In this study we introduce a new class of models for network analysis, called local structure graph models (LSGMs). In contrast to an ERGM, a LSGM specifies a network model through local features and allows for an interpretable and controllable local dependence structure. In particular, LSGMs are formulated by a set of full conditional distributions for each network edge, e.g., the probability of edge presence/absence, depending onmore » neighborhoods of other edges. Additional model features are introduced to aid in specification and to help alleviate a common issue (occurring also with ERGMs) of model degeneracy. Finally, the proposed models are demonstrated on a network of tornadoes in Arkansas where a LSGM is shown to perform significantly better than a model without local dependence.« less

Distributed Transforms for Efficient Data Gathering in Sensor Networks

NASA Technical Reports Server (NTRS)

Ortega, Antonio (Inventor); Shen, Godwin (Inventor); Narang, Sunil K. (Inventor); Perez-Trufero, Javier (Inventor)

2014-01-01

Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.

Collective network routing

DOEpatents

Hoenicke, Dirk

2014-12-02

Disclosed are a unified method and apparatus to classify, route, and process injected data packets into a network so as to belong to a plurality of logical networks, each implementing a specific flow of data on top of a common physical network. The method allows to locally identify collectives of packets for local processing, such as the computation of the sum, difference, maximum, minimum, or other logical operations among the identified packet collective. Packets are injected together with a class-attribute and an opcode attribute. Network routers, employing the described method, use the packet attributes to look-up the class-specific route information from a local route table, which contains the local incoming and outgoing directions as part of the specifically implemented global data flow of the particular virtual network.

An Investigation of Synchrony in Transport Networks

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.; Alexandrov, Natalia M.; Holroyd, Michael J.

2007-01-01

The cumulative degree distributions of transport networks, such as air transportation networks and respiratory neuronal networks, follow power laws. The significance of power laws with respect to other network performance measures, such as throughput and synchronization, remains an open question. Evolving methods for the analysis and design of air transportation networks must address network performance in the face of increasing demands and the need to contain and control local network disturbances, such as congestion. Toward this end, we investigate functional relationships that govern the performance of transport networks; for example, the links between the first nontrivial eigenvalue of a network's Laplacian matrix - a quantitative measure of network synchronizability - and other global network parameters. In particular, among networks with a fixed degree distribution and fixed network assortativity (a measure of a network's preference to attach nodes based on a similarity or difference), those with the small eigenvalue are shown to be poor synchronizers, to have much longer shortest paths and to have greater clustering in comparison to those with large. A simulation of a respiratory network adds data to our investigation. This study is a beginning step in developing metrics and design variables for the analysis and active design of air transport networks.

Domain-General Brain Regions Do Not Track Linguistic Input as Closely as Language-Selective Regions

PubMed Central

Fedorenko, Evelina

2017-01-01

Language comprehension engages a cortical network of left frontal and temporal regions. Activity in this network is language-selective, showing virtually no modulation by nonlinguistic tasks. In addition, language comprehension engages a second network consisting of bilateral frontal, parietal, cingulate, and insular regions. Activity in this “multiple demand” (MD) network scales with comprehension difficulty, but also with cognitive effort across a wide range of nonlinguistic tasks in a domain-general fashion. Given the functional dissociation between the language and MD networks, their respective contributions to comprehension are likely distinct, yet such differences remain elusive. Prior neuroimaging studies have suggested that activity in each network covaries with some linguistic features that, behaviorally, influence on-line processing and comprehension. This sensitivity of the language and MD networks to local input characteristics has often been interpreted, implicitly or explicitly, as evidence that both networks track linguistic input closely, and in a manner consistent across individuals. Here, we used fMRI to directly test this assumption by comparing the BOLD signal time courses in each network across different people (n = 45, men and women) listening to the same story. Language network activity showed fewer individual differences, indicative of closer input tracking, whereas MD network activity was more idiosyncratic and, moreover, showed lower reliability within an individual across repetitions of a story. These findings constrain cognitive models of language comprehension by suggesting a novel distinction between the processes implemented in the language and MD networks. SIGNIFICANCE STATEMENT Language comprehension recruits both language-specific mechanisms and domain-general mechanisms that are engaged in many cognitive processes. In the human cortex, language-selective mechanisms are implemented in the left-lateralized “core language network”, whereas domain-general mechanisms are implemented in the bilateral “multiple demand” (MD) network. Here, we report the first direct comparison of the respective contributions of these networks to naturalistic story comprehension. Using a novel combination of neuroimaging approaches we find that MD regions track stories less closely than language regions. This finding constrains the possible contributions of the MD network to comprehension, contrasts with accounts positing that this network has continuous access to linguistic input, and suggests a new typology of comprehension processes based on their extent of input tracking. PMID:28871034

Noise-sustained synchronization between electrically coupled FitzHugh-Nagumo networks

NASA Astrophysics Data System (ADS)

Cascallares, Guadalupe; Sánchez, Alejandro D.; dell'Erba, Matías G.; Izús, Gonzalo G.

2015-09-01

We investigate the capability of electrical synapses to transmit the noise-sustained network activity from one network to another. The particular setup we consider is two identical rings with excitable FitzHugh-Nagumo cell dynamics and nearest-neighbor antiphase intra-ring coupling, electrically coupled between corresponding nodes. The whole system is submitted to independent local additive Gaussian white noises with common intensity η, but only one ring is externally forced by a global adiabatic subthreshold harmonic signal. We then seek conditions for a particular noise level to promote synchronized stable firing patterns. By running numerical integrations with increasing η, we observe the excitation activity to become spatiotemporally self-organized, until η is so strong that spoils sync between networks for a given value of the electric coupling strength. By means of a four-cell model and calculating the stationary probability distribution, we obtain a (signal-dependent) non-equilibrium potential landscape which explains qualitatively the observed regimes, and whose barrier heights give a good estimate of the optimal noise intensity for the sync between networks.

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City.

PubMed

Yang, Wan; Olson, Donald R; Shaman, Jeffrey

2016-11-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast.

Local Area Networks and the Learning Lab of the Future.

ERIC Educational Resources Information Center

Ebersole, Dennis C.

1987-01-01

Considers educational applications of local area computer networks and discusses industry standards for design established by the International Standards Organization (ISO) and Institute of Electrical and Electronic Engineers (IEEE). A futuristic view of a learning laboratory using a local area network is presented. (Author/LRW)

Design of double fuzzy clustering-driven context neural networks.

PubMed

Kim, Eun-Hu; Oh, Sung-Kwun; Pedrycz, Witold

2018-08-01

In this study, we introduce a novel category of double fuzzy clustering-driven context neural networks (DFCCNNs). The study is focused on the development of advanced design methodologies for redesigning the structure of conventional fuzzy clustering-based neural networks. The conventional fuzzy clustering-based neural networks typically focus on dividing the input space into several local spaces (implied by clusters). In contrast, the proposed DFCCNNs take into account two distinct local spaces called context and cluster spaces, respectively. Cluster space refers to the local space positioned in the input space whereas context space concerns a local space formed in the output space. Through partitioning the output space into several local spaces, each context space is used as the desired (target) local output to construct local models. To complete this, the proposed network includes a new context layer for reasoning about context space in the output space. In this sense, Fuzzy C-Means (FCM) clustering is useful to form local spaces in both input and output spaces. The first one is used in order to form clusters and train weights positioned between the input and hidden layer, whereas the other one is applied to the output space to form context spaces. The key features of the proposed DFCCNNs can be enumerated as follows: (i) the parameters between the input layer and hidden layer are built through FCM clustering. The connections (weights) are specified as constant terms being in fact the centers of the clusters. The membership functions (represented through the partition matrix) produced by the FCM are used as activation functions located at the hidden layer of the "conventional" neural networks. (ii) Following the hidden layer, a context layer is formed to approximate the context space of the output variable and each node in context layer means individual local model. The outputs of the context layer are specified as a combination of both weights formed as linear function and the outputs of the hidden layer. The weights are updated using the least square estimation (LSE)-based method. (iii) At the output layer, the outputs of context layer are decoded to produce the corresponding numeric output. At this time, the weighted average is used and the weights are also adjusted with the use of the LSE scheme. From the viewpoint of performance improvement, the proposed design methodologies are discussed and experimented with the aid of benchmark machine learning datasets. Through the experiments, it is shown that the generalization abilities of the proposed DFCCNNs are better than those of the conventional FCNNs reported in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Network properties of interstitial cells of Cajal affect intestinal pacemaker activity and motor patterns, according to a mathematical model of weakly coupled oscillators.

PubMed

Wei, Ruihan; Parsons, Sean P; Huizinga, Jan D

2017-03-01

What is the central question of this study? What are the effects of interstitial cells of Cajal (ICC) network perturbations on intestinal pacemaker activity and motor patterns? What is the main finding and its importance? Two-dimensional modelling of the ICC pacemaker activity according to a phase model of weakly coupled oscillators showed that network properties (coupling strength between oscillators, frequency gradient and frequency noise) strongly influence pacemaker network activity and subsequent motor patterns. The model explains motor patterns observed in physiological conditions and provides predictions and testable hypotheses for effects of ICC loss and frequency modulation on the motor patterns. Interstitial cells of Cajal (ICC) are the pacemaker cells of gut motility and are associated with motility disorders. Interstitial cells of Cajal form a network, but the contributions of its network properties to gut physiology and dysfunction are poorly understood. We modelled an ICC network as a two-dimensional network of weakly coupled oscillators with a frequency gradient and showed changes over time in video and graphical formats. Model parameters were obtained from slow-wave-driven contraction patterns in the mouse intestine and pacemaker slow-wave activities from the cat intestine. Marked changes in propagating oscillation patterns (including changes from propagation to non-propagating) were observed by changing network parameters (coupling strength between oscillators, the frequency gradient and frequency noise), which affected synchronization, propagation velocity and occurrence of dislocations (termination of an oscillation). Complete uncoupling of a circumferential ring of oscillators caused the proximal and distal section to desynchronize, but complete synchronization was maintained with only a single oscillator connecting the sections with high enough coupling. The network of oscillators could withstand loss; even with 40% of oscillators lost randomly within the network, significant synchronization and anterograde propagation remained. A local increase in pacemaker frequency diminished anterograde propagation; the effects were strongly dependent on location, frequency gradient and coupling strength. In summary, the model puts forth the hypothesis that fundamental changes in oscillation patterns (ICC slow-wave activity or circular muscle contractions) can occur through physiological modulation of network properties. Strong evidence is provided to accept the ICC network as a system of coupled oscillators. © 2016 The Authors. Experimental Physiology © 2016 The Physiological Society.

Macroscopic and microscopic spectral properties of brain networks during local and global synchronization

NASA Astrophysics Data System (ADS)

Maksimenko, Vladimir A.; Lüttjohann, Annika; Makarov, Vladimir V.; Goremyko, Mikhail V.; Koronovskii, Alexey A.; Nedaivozov, Vladimir; Runnova, Anastasia E.; van Luijtelaar, Gilles; Hramov, Alexander E.; Boccaletti, Stefano

2017-07-01

We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of a network from the measurements and the processing of macroscopic signals. Starting from a network model of Kuramoto phase oscillators, which evolve adaptively according to homophilic and homeostatic adaptive principles, we give evidence that the increase of synchronization within groups of nodes (and the corresponding formation of synchronous clusters) causes also the defragmentation of the wavelet energy spectrum of the macroscopic signal. Our methodology is then applied to getting a glance into the microscopic interactions occurring in a neurophysiological system, namely, in the thalamocortical neural network of an epileptic brain of a rat, where the group electrical activity is registered by means of multichannel EEG. We demonstrate that it is possible to infer the degree of interaction between the interconnected regions of the brain during different types of brain activities and to estimate the regions' participation in the generation of the different levels of consciousness.

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.

The HOX genes are expressed, in vivo, in human tooth germs: in vitro cAMP exposure of dental pulp cells results in parallel HOX network activation and neuronal differentiation.

PubMed

D'Antò, Vincenzo; Cantile, Monica; D'Armiento, Maria; Schiavo, Giulia; Spagnuolo, Gianrico; Terracciano, Luigi; Vecchione, Raffaela; Cillo, Clemente

2006-03-01

Homeobox-containing genes play a crucial role in odontogenesis. After the detection of Dlx and Msx genes in overlapping domains along maxillary and mandibular processes, a homeobox odontogenic code has been proposed to explain the interaction between different homeobox genes during dental lamina patterning. No role has so far been assigned to the Hox gene network in the homeobox odontogenic code due to studies on specific Hox genes and evolutionary considerations. Despite its involvement in early patterning during embryonal development, the HOX gene network, the most repeat-poor regions of the human genome, controls the phenotype identity of adult eukaryotic cells. Here, according to our results, the HOX gene network appears to be active in human tooth germs between 18 and 24 weeks of development. The immunohistochemical localization of specific HOX proteins mostly concerns the epithelial tooth germ compartment. Furthermore, only a few genes of the network are active in embryonal retromolar tissues, as well as in ectomesenchymal dental pulp cells (DPC) grown in vitro from adult human molar. Exposure of DPCs to cAMP induces the expression of from three to nine total HOX genes of the network in parallel with phenotype modifications with traits of neuronal differentiation. Our observations suggest that: (i) by combining its component genes, the HOX gene network determines the phenotype identity of epithelial and ectomesenchymal cells interacting in the generation of human tooth germ; (ii) cAMP treatment activates the HOX network and induces, in parallel, a neuronal-like phenotype in human primary ectomesenchymal dental pulp cells. 2005 Wiley-Liss, Inc.

Contemporary data communications and local networking principles

NASA Astrophysics Data System (ADS)

Chartrand, G. A.

1982-08-01

The most important issue of data communications today is networking which can be roughly divided into two catagories: local networking; and distributed processing. The most sought after aspect of local networking is office automation. Office automation really is the grand unification of all local communications and not of a new type of business office as the name might imply. This unification is the ability to have voice, data, and video carried by the same medium and managed by the same network resources. There are many different ways this unification can be done, and many manufacturers are designing systems to accomplish the task. Distributed processing attempts to share resources between computer systems and peripheral subsystems from the same or different manufacturers. There are several companies that are trying to solve both networking problems with the same network architecture.

Surface dynamics and mechanics in liquid crystal polymer coatings

NASA Astrophysics Data System (ADS)

Liu, Danqing; Broer, Dirk J.

2015-03-01

Based on liquid crystal networks we developed `smart' coatings with responsive surface topographies. Either by prepatterning or by the formation of self-organized structures they can be switched on and off in a pre-designed manner. Here we provide an overview of our methods to generate coatings that form surface structures upon the actuation by light. The coating oscillates between a flat surface and a surface with pre-designed 3D micro-patterns by modulating a light source. With recent developments in solid state lighting, light is an attractive trigger medium as it can be integrated in a device for local control or can be used remotely for flood or localized exposure. The basic principle of formation of surface topographies is based on the change of molecular organization in ordered liquid crystal polymer networks. The change in order leads to anisotropic dimensional changes with contraction along the director and expansion to the two perpendicular directions and an increase in volume by the formation of free volume. These two effects work in concert to provide local expansion and contraction in the coating steered by the local direction of molecular orientation. The surface deformation, expressed as the height difference between the activated regions and the non-activated regions divided by the initial film thickness, is of the order of 20%. Switching occurs immediately when the light is switched `on' and `off' and takes several tens of seconds.

Mechano-genetic DNA hydrogels as a simple, reconstituted model to probe the effect of active fluctuations on gene transcription

NASA Astrophysics Data System (ADS)

Nguyen, Dan; Saleh, Omar

Active fluctuations - non-directed fluctuations attributable, not to thermal energy, but to non-equilibrium processes - are thought to influence biology by increasing the diffusive motion of biomolecules. Dense DNA regions within cells (i.e. chromatin) are expected to exhibit such phenomena, as they are cross-linked networks that continually experience propagating forces arising from dynamic cellular activity. Additional agitation within these gene-encoding DNA networks could have potential genetic consequences. By changing the local mobility of transcriptional machinery and regulatory proteins towards/from their binding sites, and thereby influencing transcription rates, active fluctuations could prove to be a physical means of modulating gene expression. To begin probing this effect, we construct genetic DNA hydrogels, as a simple, reconstituted model of chromatin, and quantify transcriptional output from these hydrogels in the presence/absence of active fluctuations.

Impact of Photosensitizers Activation on Intracellular Trafficking and Viscosity

PubMed Central

Aubertin, Kelly; Bonneau, Stéphanie; Silva, Amanda K. A.; Bacri, Jean-Claude; Gallet, François; Wilhelm, Claire

2013-01-01

The intracellular microenvironment is essential for the efficiency of photo-induced therapies, as short-lived reactive oxygen species generated must diffuse through their intracellular surrounding medium to reach their cellular target. Here, by combining measurements of local cytoplasmic dissipation and active trafficking, we found that photosensitizers activation induced small changes in surrounding viscosity but a massive decrease in diffusion. These effects are the signature of a return to thermodynamic equilibrium of the system after photo-activation and correlated with depolymerization of the microtubule network, as shown in a reconstituted system. These mechanical measurements were performed with two intracellular photosensitizing chlorins having similar quantum yield of singlet oxygen production but different intracellular localizations (cytoplasmic for mTHPC, endosomal for TPCS2a). These two agents demonstrated different intracellular impact. PMID:24386423

Delivery of video-on-demand services using local storages within passive optical networks.

PubMed

Abeywickrama, Sandu; Wong, Elaine

2013-01-28

At present, distributed storage systems have been widely studied to alleviate Internet traffic build-up caused by high-bandwidth, on-demand applications. Distributed storage arrays located locally within the passive optical network were previously proposed to deliver Video-on-Demand services. As an added feature, a popularity-aware caching algorithm was also proposed to dynamically maintain the most popular videos in the storage arrays of such local storages. In this paper, we present a new dynamic bandwidth allocation algorithm to improve Video-on-Demand services over passive optical networks using local storages. The algorithm exploits the use of standard control packets to reduce the time taken for the initial request communication between the customer and the central office, and to maintain the set of popular movies in the local storage. We conduct packet level simulations to perform a comparative analysis of the Quality-of-Service attributes between two passive optical networks, namely the conventional passive optical network and one that is equipped with a local storage. Results from our analysis highlight that strategic placement of a local storage inside the network enables the services to be delivered with improved Quality-of-Service to the customer. We further formulate power consumption models of both architectures to examine the trade-off between enhanced Quality-of-Service performance versus the increased power requirement from implementing a local storage within the network.

HRD Motif as the Central Hub of the Signaling Network for Activation Loop Autophosphorylation in Abl Kinase.

PubMed

La Sala, Giuseppina; Riccardi, Laura; Gaspari, Roberto; Cavalli, Andrea; Hantschel, Oliver; De Vivo, Marco

2016-11-08

A number of structural factors modulate the activity of Abelson (Abl) tyrosine kinase, whose deregulation is often related to oncogenic processes. First, only the open conformation of the Abl kinase domain's activation loop (A-loop) favors ATP binding to the catalytic cleft. In this regard, the trans-autophosphorylation of the Y412 residue, which is located along the A-loop, favors the stability of the open conformation, in turn enhancing Abl activity. Another key factor for full Abl activity is the formation of active conformations of the catalytic DFG motif in the Abl kinase domain. Furthermore, binding of the SH2 domain to the N-lobe of the Abl kinase was recently demonstrated to have a long-range allosteric effect on the stabilization of the A-loop open state. Intriguingly, these distinct structural factors imply a complex signal transmission network for controlling the A-loop's flexibility and conformational preference for optimal Abl function. However, the exact dynamical features of this signal transmission network structure remain unclear. Here, we report on microsecond-long molecular dynamics coupled with enhanced sampling simulations of multiple Abl model systems, in the presence or absence of the SH2 domain and with the DFG motif flipped in two ways (in or out conformation). Through comparative analysis, our simulations augment the interpretation of the existing Abl experimental data, revealing a dynamical network of interactions that interconnect SH2 domain binding with A-loop plasticity and Y412 autophosphorylation in Abl. This signaling network engages the DFG motif and, importantly, other conserved structural elements of the kinase domain, namely, the EPK-ELK H-bond network and the HRD motif. Our results show that the signal propagation for modulating the A-loop spatial localization is highly dependent on the HRD motif conformation, which thus acts as the central hub of this (allosteric) signaling network controlling Abl activation and function.

Modulation of the brain's functional network architecture in the transition from wake to sleep

PubMed Central

Larson-Prior, Linda J.; Power, Jonathan D.; Vincent, Justin L.; Nolan, Tracy S.; Coalson, Rebecca S.; Zempel, John; Snyder, Abraham Z.; Schlaggar, Bradley L.; Raichle, Marcus E.; Petersen, Steven E.

2013-01-01

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes. PMID:21854969

Regional and local networks of horizontal control, Cerro Prieto geothermal area

USGS Publications Warehouse

Massey, B.L.

1979-01-01

The Cerro Prieto geothermal area in the Mexicali Valley 30 km southeast of Mexicali, Baja California, is probably deforming due to (1) the extraction of large volumes of steam and hot water, and (2) active tectonism. Two networks of precise horizontal control were established in Mexicali Valley by the U.S. Geological Survey in 1977 - 1978 to measure both types of movement as they occur. These networks consisted of (1) a regional trilateration net brought into the mountain ranges west of the geothermal area from survey stations on an existing U.S. Geological Survey crustal-strain network north of the international border, and (2) a local net tied to stations in the regional net and encompassing the area of present and planned geothermal production. Survey lines in this net were selected to span areas of probable ground-surface movements in and around the geothermal area. Electronic distance measuring (EDM) instruments, operating with a modulated laser beam, were used to measure the distances between stations in both networks. The regional net was run using a highly precise long-range EDM instrument, helicopters for transportation of men and equipment to inaccessible stations on mountain peaks, and a fixed wing airplane flying along the line of sight. Precision of measurements with this complex long-range system approached 0-2 ppm of line length. The local net was measured with a medium-range EDM instrument requiring minimal ancillary equipment. Precision of measurements with this less complex system approached 3 ppm for the shorter line lengths. The detection and analysis of ground-surface movements resulting from tectonic strains or induced by geothermal fluid withdrawal is dependent on subsequent resurveys of these networks. ?? 1979.

TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks

USGS Publications Warehouse

Song, W.-Z.; Huang, R.; Shirazi, B.; LaHusen, R.

2009-01-01

Earlier sensor network MAC protocols focus on energy conservation in low-duty cycle applications, while some recent applications involve real-time high-data-rate signals. This motivates us to design an innovative localized TDMA MAC protocol to achieve high throughput and low congestion in data collection sensor networks, besides energy conservation. TreeMAC divides a time cycle into frames and each frame into slots. A parent node determines the children's frame assignment based on their relative bandwidth demand, and each node calculates its own slot assignment based on its hop-count to the sink. This innovative 2-dimensional frame-slot assignment algorithm has the following nice theory properties. First, given any node, at any time slot, there is at most one active sender in its neighborhood (including itself). Second, the packet scheduling with TreeMAC is bufferless, which therefore minimizes the probability of network congestion. Third, the data throughput to the gateway is at least 1/3 of the optimum assuming reliable links. Our experiments on a 24-node testbed show that TreeMAC protocol significantly improves network throughput, fairness, and energy efficiency compared to TinyOS's default CSMA MAC protocol and a recent TDMA MAC protocol Funneling-MAC. Partial results of this paper were published in Song, Huang, Shirazi and Lahusen [W.-Z. Song, R. Huang, B. Shirazi, and R. Lahusen, TreeMAC: Localized TDMA MAC protocol for high-throughput and fairness in sensor networks, in: The 7th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom, March 2009]. Our new contributions include analyses of the performance of TreeMAC from various aspects. We also present more implementation detail and evaluate TreeMAC from other aspects. ?? 2009 Elsevier B.V.

CEREBRA: a 3-D visualization tool for brain network extracted from fMRI data.

PubMed

Nasir, Baris; Yarman Vural, Fatos T

2016-08-01

In this paper, we introduce a new tool, CEREBRA, to visualize the 3D network of human brain, extracted from the fMRI data. The tool aims to analyze the brain connectivity by representing the selected voxels as the nodes of the network. The edge weights among the voxels are estimated by considering the relationships among the voxel time series. The tool enables the researchers to observe the active brain regions and the interactions among them by using graph theoretic measures, such as, the edge weight and node degree distributions. CEREBRA provides an interactive interface with basic display and editing options for the researchers to study their hypotheses about the connectivity of the brain network. CEREBRA interactively simplifies the network by selecting the active voxels and the most correlated edge weights. The researchers may remove the voxels and edges by using local and global thresholds selected on the window. The built-in graph reduction algorithms are then eliminate the irrelevant regions, voxels and edges and display various properties of the network. The toolbox is capable of space-time representation of the voxel time series and estimated arc weights by using the animated heat maps.

77 FR 18856 - Atchafalaya National Wildlife Refuge, LA; Final Comprehensive Conservation Plan and Finding of No...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-28

... local, state, and regional newspapers, six online media outlets, and two local radio networks. Copies of... Atchafalaya; The Nature Conservancy; Gulf Restoration Network; Atchafalaya Basinkeeper; Louisiana Crawfish... Environmental Action Network; and local citizens. Selected Alternative The Draft CCP/EA identified and evaluated...

Citizen-sensor-networks to confront government decision-makers: Two lessons from the Netherlands.

PubMed

Carton, Linda; Ache, Peter

2017-07-01

This paper presents one emerging social-technical innovation: The evolution of citizen-sensor-networks where citizens organize themselves from the 'bottom up', for the sake of confronting governance officials with measured information about environmental qualities. We have observed how citizen-sensor-networks have been initiated in the Netherlands in cases where official government monitoring and business organizations leave gaps. The formed citizen-sensor-networks collect information about issues that affect the local community in their quality-of-living. In particular, two community initiatives are described where the sensed environmental information, on noise pollution and gas-extraction induced earthquakes respectively, is published through networked geographic information methods. Both community initiatives pioneered in developing an approach that comprises the combined setting-up of sensor data flows, real-time map portals and community organization. Two particular cases are analyzed to trace the emergence and network operation of such 'networked geo-information tools' in practice: (1) The Groningen earthquake monitor, and (2) The Airplane Monitor Schiphol. In both cases, environmental 'externalities' of spatial-economic activities play an important role, having economic dimensions of national importance (e.g. gas extraction and national airport development) while simultaneously affecting the regional community with environmental consequences. The monitoring systems analyzed in this paper are established bottom-up, by citizens for citizens, to serve as 'information power' in dialogue with government institutions. The goal of this paper is to gain insight in how these citizen-sensor-networks come about: how the idea for establishing a sensor network originated, how their value gets recognized and adopted in the overall 'system of governance'; to what extent they bring countervailing power against vested interests and established discourses to the table and influence power-laden conflicts over environmental pressures; and whether or not they achieve (some form of) institutionalization and, ultimately, policy change. We find that the studied-citizen-sensor networks gain strength by uniting efforts and activities in crowdsourcing data, providing factual, 'objectivized data' or 'evidence' of the situation 'on the ground' on a matter of local community-wide concern. By filling an information need of the local community, a process of 'collective sense-making' combined with citizen empowerment could grow, which influenced societal discourse and challenged prevailing truth-claims of public institutions. In both cases similar, 'competing' web-portals were developed in response, both by the gas-extraction company and the airport. But with the citizen-sensor-networks alongside, we conclude there is a shift in power balance involved between government and affected communities, as the government no longer has information monopoly on environmental measurements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Collaborative field research and training in occupational health and ergonomics.

PubMed

Kogi, K

1998-01-01

Networking collaborative research and training in Asian developing countries includes three types of joint activities: field studies of workplace potentials for better safety and health, intensive action training for improvement of working conditions in small enterprises, and action-oriented workshops on low-cost improvements for managers, workers, and farmers. These activities were aimed at identifying workable strategies for making locally adjusted improvements in occupational health and ergonomics. Many improvements have resulted as direct outcomes. Most these improvements were multifaceted, low-cost, and practicable using local skills. Three common features of these interactive processes seem important in facilitating realistic improvements: 1) voluntary approaches building on local achievements; 2) the use of practical methods for identifying multiple improvements; and 3) participatory steps for achieving low-cost results first. The effective use of group work tools is crucial. Stepwise training packages have thus proven useful for promoting local problem-solving interventions based on voluntary initiatives.

Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model

PubMed Central

Farinella, Matteo; Ruedt, Daniel T.; Gleeson, Padraig; Lanore, Frederic; Silver, R. Angus

2014-01-01

In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such ‘background’ synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a ‘balanced’ background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales. PMID:24763087

Modeling Large-Scale Networks Using Virtual Machines and Physical Appliances

DTIC Science & Technology

2014-01-27

downloaded and run locally. The lab solution couldn’t be based on ActiveX because the military Report Documentation Page Form ApprovedOMB No. 0704-0188...unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 disallowed ActiveX support on...its systems, which made running an RDP client over ActiveX not possible. The challenges the SEI encountered in delivering the instruction were

Closed-Loop Estimation of Retinal Network Sensitivity by Local Empirical Linearization

PubMed Central

2018-01-01

Abstract Understanding how sensory systems process information depends crucially on identifying which features of the stimulus drive the response of sensory neurons, and which ones leave their response invariant. This task is made difficult by the many nonlinearities that shape sensory processing. Here, we present a novel perturbative approach to understand information processing by sensory neurons, where we linearize their collective response locally in stimulus space. We added small perturbations to reference stimuli and tested if they triggered visible changes in the responses, adapting their amplitude according to the previous responses with closed-loop experiments. We developed a local linear model that accurately predicts the sensitivity of the neural responses to these perturbations. Applying this approach to the rat retina, we estimated the optimal performance of a neural decoder and showed that the nonlinear sensitivity of the retina is consistent with an efficient encoding of stimulus information. Our approach can be used to characterize experimentally the sensitivity of neural systems to external stimuli locally, quantify experimentally the capacity of neural networks to encode sensory information, and relate their activity to behavior. PMID:29379871

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

The Energy Landscape Analysis of Cancer Mutations in Protein Kinases

PubMed Central

Dixit, Anshuman; Verkhivker, Gennady M.

2011-01-01

The growing interest in quantifying the molecular basis of protein kinase activation and allosteric regulation by cancer mutations has fueled computational studies of allosteric signaling in protein kinases. In the present study, we combined computer simulations and the energy landscape analysis of protein kinases to characterize the interplay between oncogenic mutations and locally frustrated sites as important catalysts of allostetric kinase activation. While structurally rigid kinase core constitutes a minimally frustrated hub of the catalytic domain, locally frustrated residue clusters, whose interaction networks are not energetically optimized, are prone to dynamic modulation and could enable allosteric conformational transitions. The results of this study have shown that the energy landscape effect of oncogenic mutations may be allosteric eliciting global changes in the spatial distribution of highly frustrated residues. We have found that mutation-induced allosteric signaling may involve a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. The presented study has demonstrated that activation cancer mutations may affect the thermodynamic equilibrium between kinase states by allosterically altering the distribution of locally frustrated sites and increasing the local frustration in the inactive form, while eliminating locally frustrated sites and restoring structural rigidity of the active form. The energy landsape analysis of protein kinases and the proposed role of locally frustrated sites in activation mechanisms may have useful implications for bioinformatics-based screening and detection of functional sites critical for allosteric regulation in complex biomolecular systems. PMID:21998754

Cytoskeletal Network Morphology Regulates Intracellular Transport Dynamics.

PubMed

Ando, David; Korabel, Nickolay; Huang, Kerwyn Casey; Gopinathan, Ajay

2015-10-20

Intracellular transport is essential for maintaining proper cellular function in most eukaryotic cells, with perturbations in active transport resulting in several types of disease. Efficient delivery of critical cargos to specific locations is accomplished through a combination of passive diffusion and active transport by molecular motors that ballistically move along a network of cytoskeletal filaments. Although motor-based transport is known to be necessary to overcome cytoplasmic crowding and the limited range of diffusion within reasonable timescales, the topological features of the cytoskeletal network that regulate transport efficiency and robustness have not been established. Using a continuum diffusion model, we observed that the time required for cellular transport was minimized when the network was localized near the nucleus. In simulations that explicitly incorporated network spatial architectures, total filament mass was the primary driver of network transit times. However, filament traps that redirect cargo back to the nucleus caused large variations in network transport. Filament polarity was more important than filament orientation in reducing average transit times, and transport properties were optimized in networks with intermediate motor on and off rates. Our results provide important insights into the functional constraints on intracellular transport under which cells have evolved cytoskeletal structures, and have potential applications for enhancing reactions in biomimetic systems through rational transport network design. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Co-percolation to tune conductive behaviour in dynamical metallic nanowire networks.

PubMed

Fairfield, J A; Rocha, C G; O'Callaghan, C; Ferreira, M S; Boland, J J

2016-11-03

Nanowire networks act as self-healing smart materials, whose sheet resistance can be tuned via an externally applied voltage stimulus. This memristive response occurs due to modification of junction resistances to form a connectivity path across the lowest barrier junctions in the network. While most network studies have been performed on expensive noble metal nanowires like silver, networks of inexpensive nickel nanowires with a nickel oxide coating can also demonstrate resistive switching, a common feature of metal oxides with filamentary conduction. However, networks made from solely nickel nanowires have high operation voltages which prohibit large-scale material applications. Here we show, using both experiment and simulation, that a heterogeneous network of nickel and silver nanowires allows optimization of the activation voltage, as well as tuning of the conduction behavior to be either resistive switching, memristive, or a combination of both. Small percentages of silver nanowires, below the percolation threshold, induce these changes in electrical behaviour, even for low area coverage and hence very transparent films. Silver nanowires act as current concentrators, amplifying conductivity locally as shown in our computational dynamical activation framework for networks of junctions. These results demonstrate that a heterogeneous nanowire network can act as a cost-effective adaptive material with minimal use of noble metal nanowires, without losing memristive behaviour that is essential for smart sensing and neuromorphic applications.

A water-resources data-network evaluation for Monterey County, California; Phase 3, Northern Salinas River drainage basin

USGS Publications Warehouse

Templin, W.E.; Schluter, R.C.

1990-01-01

This report evaluates existing data collection networks and possible additional data collection to monitor quantity and quality of precipitation, surface water, and groundwater in the northern Salinas River drainage basin, California. Of the 34 precipitation stations identified, 20 were active and are concentrated in the northwestern part of the study area. No precipitation quality networks were identified, but possible data collection efforts include monitoring for acid rain and pesticides. Six of ten stream-gaging stations are active. Two surface water quality sites are sampled for suspended sediment, specific conductance, and chloride; one U.S. Geological Survey NASOAN site and one site operated by California Department of Water Resources make up the four active sampling locations; reactivation of 45 inactive surface water quality sites might help to achieve objectives described in the report. Three local networks measure water levels in 318 wells monthly, during peak irrigation, and at the end of the irrigation season. Water quality conditions are monitored in 379 wells; samples are collected in summer to monitor saltwater intrusion near Castroville and are also collected annually throughout the study area for analysis of chloride, specific conductance, and nitrate. An ideal baseline network would be an evenly spaced grid of index wells with a density of one per section. When baseline conditions are established, representative wells within the network could be monitored periodically according to specific data needs. (USGS)

Resting state electrical brain activity and connectivity in fibromyalgia

PubMed Central

Vanneste, Sven; Ost, Jan; Van Havenbergh, Tony; De Ridder, Dirk

2017-01-01

The exact mechanism underlying fibromyalgia is unknown, but increased facilitatory modulation and/or dysfunctional descending inhibitory pathway activity are posited as possible mechanisms contributing to sensitization of the central nervous system. The primary goal of this study is to identify a fibromyalgia neural circuit that can account for these abnormalities in central pain. The second goal is to gain a better understanding of the functional connectivity between the default and the executive attention network (salience network plus dorsal lateral prefrontal cortex) in fibromyalgia. We examine neural activity associated with fibromyalgia (N = 44) and compare these with healthy controls (N = 44) using resting state source localized EEG. Our data support an important role of the pregenual anterior cingulate cortex but also suggest that the degree of activation and the degree of integration between different brain areas is important. The inhibition of the connectivity between the dorsal lateral prefrontal cortex and the posterior cingulate cortex on the pain inhibitory pathway seems to be limited by decreased functional connectivity with the pregenual anterior cingulate cortex. Our data highlight the functional dynamics of brain regions integrated in brain networks in fibromyalgia patients. PMID:28650974

Service Demand Discovery Mechanism for Mobile Social Networks.

PubMed

Wu, Dapeng; Yan, Junjie; Wang, Honggang; Wang, Ruyan

2016-11-23

In the last few years, the service demand for wireless data over mobile networks has continually been soaring at a rapid pace. Thereinto, in Mobile Social Networks (MSNs), users can discover adjacent users for establishing temporary local connection and thus sharing already downloaded contents with each other to offload the service demand. Due to the partitioned topology, intermittent connection and social feature in such a network, the service demand discovery is challenging. In particular, the service demand discovery is exploited to identify the best relay user through the service registration, service selection and service activation. In order to maximize the utilization of limited network resources, a hybrid service demand discovery architecture, such as a Virtual Dictionary User (VDU) is proposed in this paper. Based on the historical data of movement, users can discover their relationships with others. Subsequently, according to the users activity, VDU is selected to facilitate the service registration procedure. Further, the service information outside of a home community can be obtained through the Global Active User (GAU) to support the service selection. To provide the Quality of Service (QoS), the Service Providing User (SPU) is chosen among multiple candidates. Numerical results show that, when compared with other classical service algorithms, the proposed scheme can improve the successful service demand discovery ratio by 25% under reduced overheads.

Gap junctions between CA3 pyramidal cells contribute to network synchronization in neonatal hippocampus.

PubMed

Molchanova, Svetlana M; Huupponen, Johanna; Lauri, Sari E; Taira, Tomi

2016-08-01

Direct electrical coupling between neurons through gap junctions is prominent during development, when synaptic connectivity is scarce, providing the additional intercellular connectivity. However, functional studies of gap junctions are hampered by the unspecificity of pharmacological tools available. Here we have investigated gap-junctional coupling between CA3 pyramidal cells in neonatal hippocampus and its contribution to early network activity. Four different gap junction inhibitors, including the general blocker carbenoxolone, decreased the frequency of network activity bursts in CA3 area of hippocampus of P3-6 rats, suggesting the involvement of electrical connections in the generation of spontaneous network activity. In CA3 pyramidal cells, spikelets evoked by local stimulation of stratum oriens, were inhibited by carbenoxolone, but not by inhibitors of glutamatergic and GABAergic synaptic transmission, signifying the presence of electrical connectivity through axo-axonic gap junctions. Carbenoxolone also decreased the success rate of firing antidromic action potentials in response to stimulation, and changed the pattern of spontaneous action potential firing of CA3 pyramidal cells. Altogether, these data suggest that electrical coupling of CA3 pyramidal cells contribute to the generation of the early network events in neonatal hippocampus by modulating their firing pattern and synchronization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Localization Strategies in WSNs as applied to Landslide Monitoring (Invited)

NASA Astrophysics Data System (ADS)

Massa, A.; Robol, F.; Polo, A.; Giarola, E.; Viani, F.

2013-12-01

In the last years, heterogeneous integrated smart systems based on wireless sensor network (WSN) technology have been developed at the ELEDIA Research Center of the University of Trento [1]. One of the key features of WSNs as applied to distributed monitoring is that, while the capabilities of each single sensor node is limited, the implementation of cooperative schemes throughout the whole network enables the solution of even complex tasks, as the landslide monitoring. The capability of localizing targets respect to the position of the sensor nodes turns out to be fundamental in those application fields where relative movements arise. The main properties like the target typology, the movement characteristics, and the required localization resolution are different changing the reference scenario. However, the common key issue is still the localization of moving targets within the area covered by the sensor network. Many experiences were preparatory for the challenging activities in the field of landslide monitoring where the basic idea is mostly that of detecting slight soil movements. Among them, some examples of WSN-based systems experimentally applied to the localization of people [2] and wildlife [3] have been proposed. More recently, the WSN backbone as well as the investigated sensing technologies have been customized for monitoring superficial movements of the soil. The relative positions of wireless sensor nodes deployed where high probability of landslide exists is carefully monitored to forecast dangerous events. Multiple sensors like ultrasound, laser, high precision GPS, for the precise measurement of relative distances between the nodes of the network and the absolute positions respect to reference targets have been integrated in a prototype system. The millimeter accuracy in the position estimation enables the detection of small soil modifications and to infer the superficial evolution profile of the landslide. This information locally acquired also represent a fine tuning of large scale satellite acquisitions, usually adopted for remote sensing of landslides. The integration of dense and frequent WSN data within satellite image analysis will enhance the sensing capabilities leading to a multi-resolution and an highly space-time calibrated system. The WSN-based system has been preliminary tested in controlled environments in the ELEDIA laboratories and is now installed in a real test site where an active landslide is evolving. Preliminary data are here presented to assess the feasibility of the investigated solution in landslide monitoring and event forecasting. REFERENCES [1] M. Benedetti, L. Ioriatti, M. Martinelli, and F. Viani, 'Wireless sensor network: a pervasive technology for earth observation,' in IEEE Journal of Selected Topics in App. Earth Obs. And Remote Sens., vol. 3, no. 4, pp. 488-497, 2010. [2] F. Viani, M. Donelli, P. Rocca, G. Oliveri, D. Trinchero, and A. Massa, 'Localization, tracking and imaging of targets in wireless sensor networks,' Radio Science, vol. 46, no. 5, 2011. [3] F. Viani, F. Robol, M. Salucci, E. Giarola, S. De Vigili, M. Rocca, F. Boldrini, G. Benedetti, and A. Massa, 'WSN-based early alert system for preventing wildlife-vehicle collisions in Alps regions - From the laboratory test to the real-world implementation,' 7th European Conference on Antennas and Propagation 2013 (EUCAP2013), Gothenburg, Sweden, April 8-12, 2013.

Theta and gamma coordination of hippocampal networks during waking and rapid eye movement sleep.

PubMed

Montgomery, Sean M; Sirota, Anton; Buzsáki, György

2008-06-25

Rapid eye movement (REM) sleep has been considered a paradoxical state because, despite the high behavioral threshold to arousing perturbations, gross physiological patterns in the forebrain resemble those of waking states. To understand how intrahippocampal networks interact during REM sleep, we used 96 site silicon probes to record from different hippocampal subregions and compared the patterns of activity during waking exploration and REM sleep. Dentate/CA3 theta and gamma synchrony was significantly higher during REM sleep compared with active waking. In contrast, gamma power in CA1 and CA3-CA1 gamma coherence showed significant decreases in REM sleep. Changes in unit firing rhythmicity and unit-field coherence specified the local generation of these patterns. Although these patterns of hippocampal network coordination characterized the more common tonic periods of REM sleep (approximately 95% of total REM), we also detected large phasic bursts of local field potential power in the dentate molecular layer that were accompanied by transient increases in the firing of dentate and CA1 neurons. In contrast to tonic REM periods, phasic REM epochs were characterized by higher theta and gamma synchrony among the dentate, CA3, and CA1 regions. These data suggest enhanced dentate processing, but limited CA3-CA1 coordination during tonic REM sleep. In contrast, phasic bursts of activity during REM sleep may provide windows of opportunity to synchronize the hippocampal trisynaptic loop and increase output to cortical targets. We hypothesize that tonic REM sleep may support off-line mnemonic processing, whereas phasic bursts of activity during REM may promote memory consolidation.

The brain's resting-state activity is shaped by synchronized cross-frequency coupling of neural oscillations

PubMed Central

Florin, Esther; Baillet, Sylvain

2015-01-01

Functional imaging of the resting brain consistently reveals broad motifs of correlated blood oxygen level dependent (BOLD) activity that engage cerebral regions from distinct functional systems. Yet, the neurophysiological processes underlying these organized, large-scale fluctuations remain to be uncovered. Using magnetoencephalography (MEG) imaging during rest in 12 healthy subjects we analyse the resting state networks and their underlying neurophysiology. We first demonstrate non-invasively that cortical occurrences of high-frequency oscillatory activity are conditioned to the phase of slower spontaneous fluctuations in neural ensembles. We further show that resting-state networks emerge from synchronized phase-amplitude coupling across the brain. Overall, these findings suggest a unified principle of local-to-global neural signaling for long-range brain communication. PMID:25680519

[Social environment and social network: extent and resources of the daily life of elderly persons].

PubMed

Marbach, J H

2001-08-01

The study asks for factors determining the activity space of the aged. Indicators of old people's activities space are the number of their outdoor activities and their use of the local supply of public facilities. Controversial hypothesis are won from ecological gerontology and psychological attachment theory. At issue in the first place is how personal social networks mold older people's outdoor behavior. Another hypothesis assumes social support of the elderly to be exposed to the laws of reciprocity. The study makes use of a poll titled "life-organization of older people" that was conducted by the German Youth Institute in 1993. Respondents were German 55- to 79-year-olds (N = 4130). Analyses rely on multifactorial analyses of variance. Results back attachment theory and the reciprocity thesis.

Methods and utility of EEG-fMRI in epilepsy

PubMed Central

Lemieux, Louis; Chaudhary, Umair Javaid

2015-01-01

Brain activity data in general and more specifically in epilepsy can be represented as a matrix that includes measures of electrophysiology, anatomy and behaviour. Each of these sub-matrices has a complex interaction depending upon the brain state i.e., rest, cognition, seizures and interictal periods. This interaction presents significant challenges for interpretation but also potential for developing further insights into individual event types. Successful treatments in epilepsy hinge on unravelling these complexities, and also on the sensitivity and specificity of methods that characterize the nature and localization of underlying physiological and pathological networks. Limitations of pharmacological and surgical treatments call for refinement and elaboration of methods to improve our capability to localise the generators of seizure activity and our understanding of the neurobiology of epilepsy. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI), by potentially circumventing some of the limitations of EEG in terms of sensitivity, can allow the mapping of haemodynamic networks over the entire brain related to specific spontaneous and triggered epileptic events in humans, and thereby provide new localising information. In this work we review the published literature, and discuss the methods and utility of EEG-fMRI in localising the generators of epileptic activity. We draw on our experience and that of other groups, to summarise the spectrum of information provided by an increasing number of EEG-fMRI case-series, case studies and group studies in patients with epilepsy, for its potential role to elucidate epileptic generators and networks. We conclude that EEG-fMRI provides a multidimensional view that contributes valuable clinical information to localize the epileptic focus with potential important implications for the surgical treatment of some patients with drug-resistant epilepsy, and insights into the resting state and cognitive network dynamics. PMID:25853087

Transient synchronization of hippocampo-striato-thalamo-cortical networks during sleep spindle oscillations induces motor memory consolidation.

PubMed

Boutin, Arnaud; Pinsard, Basile; Boré, Arnaud; Carrier, Julie; Fogel, Stuart M; Doyon, Julien

2018-04-01

Sleep benefits motor memory consolidation. This mnemonic process is thought to be mediated by thalamo-cortical spindle activity during NREM-stage2 sleep episodes as well as changes in striatal and hippocampal activity. However, direct experimental evidence supporting the contribution of such sleep-dependent physiological mechanisms to motor memory consolidation in humans is lacking. In the present study, we combined EEG and fMRI sleep recordings following practice of a motor sequence learning (MSL) task to determine whether spindle oscillations support sleep-dependent motor memory consolidation by transiently synchronizing and coordinating specialized cortical and subcortical networks. To that end, we conducted EEG source reconstruction on spindle epochs in both cortical and subcortical regions using novel deep-source localization techniques. Coherence-based metrics were adopted to estimate functional connectivity between cortical and subcortical structures over specific frequency bands. Our findings not only confirm the critical and functional role of NREM-stage2 sleep spindles in motor skill consolidation, but provide first-time evidence that spindle oscillations [11-17 Hz] may be involved in sleep-dependent motor memory consolidation by locally reactivating and functionally binding specific task-relevant cortical and subcortical regions within networks including the hippocampus, putamen, thalamus and motor-related cortical regions. Copyright © 2018 Elsevier Inc. All rights reserved.

Rational Modular RNA Engineering Based on In Vivo Profiling of Structural Accessibility.

PubMed

Leistra, Abigail N; Amador, Paul; Buvanendiran, Aishwarya; Moon-Walker, Alex; Contreras, Lydia M

2017-12-15

Bacterial small RNAs (sRNAs) have been established as powerful parts for controlling gene expression. However, development and application of engineered sRNAs has primarily focused on regulating novel synthetic targets. In this work, we demonstrate a rational modular RNA engineering approach that uses in vivo structural accessibility measurements to tune the regulatory activity of a multisubstrate sRNA for differential control of its native target network. Employing the CsrB global sRNA regulator as a model system, we use published in vivo structural accessibility data to infer the contribution of its local structures (substructures) to function and select a subset for engineering. We then modularly recombine the selected substructures, differentially representing those of presumed high or low functional contribution, to build a library of 21 CsrB variants. Using fluorescent translational reporter assays, we demonstrate that the CsrB variants achieve a 5-fold gradient of control of well-characterized Csr network targets. Interestingly, results suggest that less conserved local structures within long, multisubstrate sRNAs may represent better targets for rational engineering than their well-conserved counterparts. Lastly, mapping the impact of sRNA variants on a signature Csr network phenotype indicates the potential of this approach for tuning the activity of global sRNA regulators in the context of metabolic engineering applications.

Validating the Why/How Contrast for Functional MRI Studies of Theory of Mind

PubMed Central

Spunt, Robert P.; Adolphs, Ralph

2014-01-01

The ability to impute mental states to others, or Theory of Mind (ToM), has been the subject of hundreds of neuroimaging studies. Although reviews and meta-analyses of these studies have concluded that ToM recruits a coherent brain network, mounting evidence suggests that this network is an abstraction based on pooling data from numerous studies, most of which use different behavioral tasks to investigate ToM. Problematically, this means that no single behavioral task can be used to reliably measure ToM Network function as currently conceived. To make ToM Network function scientifically tractable, we need standardized tasks capable of reliably measuring specific aspects of its functioning. Here, our goal is to validate the Why/How Task for this purpose. Several prior studies have found that when compared to answering how-questions about another person's behavior, answering why-questions about that same behavior activates a network that is anatomically consistent with meta-analytic definitions of the ToM Network. In the version of the Why/How Task presented here, participants answer yes/no Why (e.g., Is the person helping someone?) and How (e.g., Is the person lifting something?) questions about pretested photographs of naturalistic human behaviors. Across three fMRI studies, we show that the task elicits reliable performance measurements and modulates a left-lateralized network that is consistently localized across studies. While this network is convergent with meta-analyses of ToM studies, it is largely distinct from the network identified by the widely used False-Belief Localizer, the most common ToM task. Our new task is publicly available, and can be used as an efficient functional localizer to provide reliable identification of single-subject responses in most regions of the network. Our results validate the Why/How Task, both as a standardized protocol capable of producing maximally comparable data across studies, and as a flexible foundation for programmatic research on the neurobiological foundations of a basic manifestation of human ToM. PMID:24844746

Comparisons of Neuronal and Excitatory Network Properties between the Rat Brainstem Nuclei that Participate in Vertical and Horizontal Gaze Holding

PubMed Central

Sugimura, Taketoshi; Yanagawa, Yuchio

2017-01-01

Gaze holding is primarily controlled by neural structures including the prepositus hypoglossi nucleus (PHN) for horizontal gaze and the interstitial nucleus of Cajal (INC) for vertical and torsional gaze. In contrast to the accumulating findings of the PHN, there is no report regarding the membrane properties of INC neurons or the local networks in the INC. In this study, to verify whether the neural structure of the INC is similar to that of the PHN, we investigated the neuronal and network properties of the INC using whole-cell recordings in rat brainstem slices. Three types of afterhyperpolarization (AHP) profiles and five firing patterns observed in PHN neurons were also observed in INC neurons. However, the overall distributions based on the AHP profile and the firing patterns of INC neurons were different from those of PHN neurons. The application of burst stimulation to a nearby site of a recorded INC neuron induced an increase in the frequency of spontaneous EPSCs. The duration of the increased EPSC frequency of INC neurons was not significantly different from that of PHN neurons. The percent of duration reduction induced by a Ca2+-permeable AMPA (CP-AMPA) receptor antagonist was significantly smaller in the INC than in the PHN. These findings suggest that local excitatory networks that activate sustained EPSC responses also exist in the INC, but their activation mechanisms including the contribution of CP-AMPA receptors differ between the INC and the PHN. PMID:28966973

Career development through local chapter involvement: perspectives from chapter members.

PubMed

Thomas, Melissa; Inniss-Richter, Zipporah; Mata, Holly; Cottrell, Randall R

2013-07-01

The importance of career development in professional organizations has been noted in the literature. Personal and professional benefits of membership regardless of discipline can be found across the career spectrum from student to executive. The benefits of professional membership with respect to career development in local chapter organizations have seldom been studied. Local chapter participation may offer significant career development opportunities for the practitioner, faculty member, and student. The purpose of this study was to explore the importance of local chapter involvement to the career development of health education practitioners. An 18-item questionnaire was disseminated to the membership of three local SOPHE (Society for Public Health Education) chapters that explored the level of local chapter involvement and the impact of how specific professional development activities impacted career development. The results of the survey highlighted the importance of continuing education programs, networking, and leadership experience in developing one's career that are offered by local SOPHE chapter involvement. Making a positive impact in the community and earning the respect of one's peers were most often reported as indicators of career success. These factors can directly impact local chapter participation. Career development can certainly be enhanced by active participation in the local chapter of a professional association.

Towards Online Multiresolution Community Detection in Large-Scale Networks

PubMed Central

Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim

2011-01-01

The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325

Percolation of localized attack on complex networks

NASA Astrophysics Data System (ADS)

Shao, Shuai; Huang, Xuqing; Stanley, H. Eugene; Havlin, Shlomo

2015-02-01

The robustness of complex networks against node failure and malicious attack has been of interest for decades, while most of the research has focused on random attack or hub-targeted attack. In many real-world scenarios, however, attacks are neither random nor hub-targeted, but localized, where a group of neighboring nodes in a network are attacked and fail. In this paper we develop a percolation framework to analytically and numerically study the robustness of complex networks against such localized attack. In particular, we investigate this robustness in Erdős-Rényi networks, random-regular networks, and scale-free networks. Our results provide insight into how to better protect networks, enhance cybersecurity, and facilitate the design of more robust infrastructures.

Apparatus and method for data communication in an energy distribution network

DOEpatents

Hussain, Mohsin; LaPorte, Brock; Uebel, Udo; Zia, Aftab

2014-07-08

A system for communicating information on an energy distribution network is disclosed. In one embodiment, the system includes a local supervisor on a communication network, wherein the local supervisor can collect data from one or more energy generation/monitoring devices. The system also includes a command center on the communication network, wherein the command center can generate one or more commands for controlling the one or more energy generation devices. The local supervisor can periodically transmit a data signal indicative of the data to the command center via a first channel of the communication network at a first interval. The local supervisor can also periodically transmit a request for a command to the command center via a second channel of the communication network at a second interval shorter than the first interval. This channel configuration provides effective data communication without a significant increase in the use of network resources.

Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics

PubMed Central

Sale, Martin V.; Lord, Anton; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B.

2015-01-01

Normal brain function depends on a dynamic balance between local specialization and large-scale integration. It remains unclear, however, how local changes in functionally specialized areas can influence integrated activity across larger brain networks. By combining transcranial magnetic stimulation with resting-state functional magnetic resonance imaging, we tested for changes in large-scale integration following the application of excitatory or inhibitory stimulation on the human motor cortex. After local inhibitory stimulation, regions encompassing the sensorimotor module concurrently increased their internal integration and decreased their communication with other modules of the brain. There were no such changes in modular dynamics following excitatory stimulation of the same area of motor cortex nor were there changes in the configuration and interactions between core brain hubs after excitatory or inhibitory stimulation of the same area. These results suggest the existence of selective mechanisms that integrate local changes in neural activity, while preserving ongoing communication between brain hubs. PMID:25717162

How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness.

PubMed

Naro, Antonino; Leo, Antonino; Manuli, Alfredo; Cannavò, Antonino; Bramanti, Alessia; Bramanti, Placido; Calabrò, Rocco Salvatore

2017-05-04

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model

PubMed Central

Demont-Guignard, Sophie; Benquet, Pascal; Gerber, Urs; Wendling, Fabrice

2009-01-01

The pathophysiological interpretation of EEG signals recorded with depth electrodes (i.e. local field potentials, LFPs) during interictal (between seizures) or ictal (during seizures) periods is fundamental in the pre-surgical evaluation of patients with drug-resistant epilepsy. Our objective was to explain specific shape features of interictal spikes in the hippocampus (observed in LFPs) in terms of cell and network-related parameters of neuronal circuits that generate these events. We developed a neural network model based on “minimal” but biologically-relevant neuron models interconnected through GABAergic and glutamatergic synapses that reproduces the main physiological features of the CA1 subfield. Simulated LFPs were obtained by solving the forward problem (dipole theory) from networks including a large number (~3000) of cells. Insertion of appropriate parameters allowed the model to simulate events that closely resemble actual epileptic spikes. Moreover, the shape of the early fast component (‘spike’) and the late slow component (‘negative wave’) was linked to the relative contribution of glutamatergic and GABAergic synaptic currents in pyramidal cells. In addition, the model provides insights about the sensitivity of electrode localization with respect to recorded tissue volume and about the relationship between the LFP and the intracellular activity of principal cells and interneurons represented in the network. PMID:19651549

Complexity in neuronal noise depends on network interconnectivity.

PubMed

Serletis, Demitre; Zalay, Osbert C; Valiante, Taufik A; Bardakjian, Berj L; Carlen, Peter L

2011-06-01

"Noise," or noise-like activity (NLA), defines background electrical membrane potential fluctuations at the cellular level of the nervous system, comprising an important aspect of brain dynamics. Using whole-cell voltage recordings from fast-spiking stratum oriens interneurons and stratum pyramidale neurons located in the CA3 region of the intact mouse hippocampus, we applied complexity measures from dynamical systems theory (i.e., 1/f(γ) noise and correlation dimension) and found evidence for complexity in neuronal NLA, ranging from high- to low-complexity dynamics. Importantly, these high- and low-complexity signal features were largely dependent on gap junction and chemical synaptic transmission. Progressive neuronal isolation from the surrounding local network via gap junction blockade (abolishing gap junction-dependent spikelets) and then chemical synaptic blockade (abolishing excitatory and inhibitory post-synaptic potentials), or the reverse order of these treatments, resulted in emergence of high-complexity NLA dynamics. Restoring local network interconnectivity via blockade washout resulted in resolution to low-complexity behavior. These results suggest that the observed increase in background NLA complexity is the result of reduced network interconnectivity, thereby highlighting the potential importance of the NLA signal to the study of network state transitions arising in normal and abnormal brain dynamics (such as in epilepsy, for example).

KIDLINK: A Challenging and Safe Place for Children across the World.

ERIC Educational Resources Information Center

Burleigh, Mike; Weeg, Patti

1993-01-01

Describes the activities of KIDLINK, an international electronic conferencing system that was developed to establish communication between children 10 to 15 years old around the world using the Internet and other computer networks. A list of local KIDLINK contacts in 29 countries is included. (LRW)

Tribal Science 2017 Webinar Series: Arctic Research, One Health and the Local Environmental Observer (LEO) Network: Ongoing Activities and Expansion to Lower 48

EPA Pesticide Factsheets

The U.S. EPA Sustainable and Healthy Communities Seminar Series presents the Tribal Science Webinar Series that will look to develop a forum for discussion of the complex environmental issues facing many tribal and indigenous communities.

Tweeting Your Own Horn

ERIC Educational Resources Information Center

Butler, Kevin

2010-01-01

This article describes how some school districts are using social networking Web sites like Twitter and Facebook to tout their accomplishments and communicate with the public. In addition to informing users of upcoming school events and showing pictures from school activities, a district's Facebook site has links to local news stories about…

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

Effects of local and global network connectivity on synergistic epidemics

NASA Astrophysics Data System (ADS)

Broder-Rodgers, David; Pérez-Reche, Francisco J.; Taraskin, Sergei N.

2015-12-01

Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

Effects of local and global network connectivity on synergistic epidemics.

PubMed

Broder-Rodgers, David; Pérez-Reche, Francisco J; Taraskin, Sergei N

2015-12-01

Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

Earthquake Swarm in Armutlu Peninsula, Eastern Marmara Region, Turkey

NASA Astrophysics Data System (ADS)

Yavuz, Evrim; Çaka, Deniz; Tunç, Berna; Serkan Irmak, T.; Woith, Heiko; Cesca, Simone; Lühr, Birger-Gottfried; Barış, Şerif

2015-04-01

The most active fault system of Turkey is North Anatolian Fault Zone and caused two large earthquakes in 1999. These two earthquakes affected the eastern Marmara region destructively. Unbroken part of the North Anatolian Fault Zone crosses north of Armutlu Peninsula on east-west direction. This branch has been also located quite close to Istanbul known as a megacity with its high population, economic and social aspects. A new cluster of microseismic activity occurred in the direct vicinity southeastern of the Yalova Termal area. Activity started on August 2, 2014 with a series of micro events, and then on August 3, 2014 a local magnitude is 4.1 event occurred, more than 1000 in the followed until August 31, 2014. Thus we call this tentatively a swarm-like activity. Therefore, investigation of the micro-earthquake activity of the Armutlu Peninsula has become important to understand the relationship between the occurrence of micro-earthquakes and the tectonic structure of the region. For these reasons, Armutlu Network (ARNET), installed end of 2005 and equipped with currently 27 active seismic stations operating by Kocaeli University Earth and Space Sciences Research Center (ESSRC) and Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum (GFZ), is a very dense network tool able to record even micro-earthquakes in this region. In the 30 days period of August 02 to 31, 2014 Kandilli Observatory and Earthquake Research Institute (KOERI) announced 120 local earthquakes ranging magnitudes between 0.7 and 4.1, but ARNET provided more than 1000 earthquakes for analyzes at the same time period. In this study, earthquakes of the swarm area and vicinity regions determined by ARNET were investigated. The focal mechanism of the August 03, 2014 22:22:42 (GMT) earthquake with local magnitude (Ml) 4.0 is obtained by the moment tensor solution. According to the solution, it discriminates a normal faulting with dextral component. The obtained focal mechanism solution is conformable with the features of local faults in the region. The spatial vicinity of the earthquake swarm and the Yalova geothermal area may suggest a physical link between the ongoing exploitation of the reservoir and the earthquake activity. Keywords: Earthquake swarm, Armutlu Peninsula, ARNET, geothermal activity

Learning and coding in biological neural networks

NASA Astrophysics Data System (ADS)

Fiete, Ila Rani

How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and theoretical results on the scalability of this rule show that learning with stochastic gradient ascent may be adequately fast to explain learning in the bird. Finally, we address the more general issue of the scalability of stochastic gradient learning on quadratic cost surfaces in linear systems, as a function of system size and task characteristics, by deriving analytical expressions for the learning curves.

Compressive sensing of high betweenness centrality nodes in networks

NASA Astrophysics Data System (ADS)

Mahyar, Hamidreza; Hasheminezhad, Rouzbeh; Ghalebi K., Elahe; Nazemian, Ali; Grosu, Radu; Movaghar, Ali; Rabiee, Hamid R.

2018-05-01

Betweenness centrality is a prominent centrality measure expressing importance of a node within a network, in terms of the fraction of shortest paths passing through that node. Nodes with high betweenness centrality have significant impacts on the spread of influence and idea in social networks, the user activity in mobile phone networks, the contagion process in biological networks, and the bottlenecks in communication networks. Thus, identifying k-highest betweenness centrality nodes in networks will be of great interest in many applications. In this paper, we introduce CS-HiBet, a new method to efficiently detect top- k betweenness centrality nodes in networks, using compressive sensing. CS-HiBet can perform as a distributed algorithm by using only the local information at each node. Hence, it is applicable to large real-world and unknown networks in which the global approaches are usually unrealizable. The performance of the proposed method is evaluated by extensive simulations on several synthetic and real-world networks. The experimental results demonstrate that CS-HiBet outperforms the best existing methods with notable improvements.

Membrane Properties and the Balance between Excitation and Inhibition Control Gamma-Frequency Oscillations Arising from Feedback Inhibition

PubMed Central

Economo, Michael N.; White, John A.

2012-01-01

Computational studies as well as in vivo and in vitro results have shown that many cortical neurons fire in a highly irregular manner and at low average firing rates. These patterns seem to persist even when highly rhythmic signals are recorded by local field potential electrodes or other methods that quantify the summed behavior of a local population. Models of the 30–80 Hz gamma rhythm in which network oscillations arise through ‘stochastic synchrony’ capture the variability observed in the spike output of single cells while preserving network-level organization. We extend upon these results by constructing model networks constrained by experimental measurements and using them to probe the effect of biophysical parameters on network-level activity. We find in simulations that gamma-frequency oscillations are enabled by a high level of incoherent synaptic conductance input, similar to the barrage of noisy synaptic input that cortical neurons have been shown to receive in vivo. This incoherent synaptic input increases the emergent network frequency by shortening the time scale of the membrane in excitatory neurons and by reducing the temporal separation between excitation and inhibition due to decreased spike latency in inhibitory neurons. These mechanisms are demonstrated in simulations and in vitro current-clamp and dynamic-clamp experiments. Simulation results further indicate that the membrane potential noise amplitude has a large impact on network frequency and that the balance between excitatory and inhibitory currents controls network stability and sensitivity to external inputs. PMID:22275859

Local Jurisdictions and Active Shooters: Building Networks, Building Capacities

DTIC Science & Technology

2010-12-01

coordination will be the foundation for identifying relevant sources and materials on the armed active shooter assault. This research will also benefit...CONCLUSION In summary, the literature review identified relevant sources and materials on the importance of an armed attack. While an armed assault...armed with the following: dozens of explosive devices of varying potency, seven knives, two Savage-Stevens 12 gauge double- barrel shotguns with the

Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures

PubMed Central

Vanleer, Ann C; Blanco, Justin A; Wagenaar, Joost B; Viventi, Jonathan; Contreras, Diego; Litt, Brian

2016-01-01

Objective Current mapping of epileptic networks in patients prior to epilepsy surgery utilizes electrode arrays with sparse spatial sampling (∼1.0 cm inter-electrode spacing). Recent research demonstrates that sub-millimeter, cortical-column-scale domains have a role in seizure generation that may be clinically significant. We use high-resolution, active, flexible surface electrode arrays with 500 μm inter-electrode spacing to explore epileptiform local field potential spike propagation patterns in two dimensions recorded from subdural micro-electrocorticographic signals in vivo in cat. In this study, we aimed to develop methods to quantitatively characterize the spatiotemporal dynamics of epileptiform activity at high-resolution. Approach We topically administered a GABA-antagonist, picrotoxin, to induce acute neocortical epileptiform activity leading up to discrete electrographic seizures. We extracted features from local field potential spikes to characterize spatiotemporal patterns in these events. We then tested the hypothesis that two dimensional spike patterns during seizures were different from those between seizures. Main results We showed that spatially correlated events can be used to distinguish ictal versus interictal spikes. Significance We conclude that sub-millimeter-scale spatiotemporal spike patterns reveal network dynamics that are invisible to standard clinical recordings and contain information related to seizure-state. PMID:26859260

Activity-dependent stochastic resonance in recurrent neuronal networks

NASA Astrophysics Data System (ADS)

Volman, Vladislav

2009-03-01

An important source of noise for neuronal networks is that of the stochastic nature of synaptic transmission. In particular, there can occur spontaneous asynchronous release of neurotransmitter at a rate that is strongly dependent on the presynaptic Ca2+ concentration and hence strongly dependent on the rate of spike induced Ca2+. Here it is shown that this noise can lead to a new form of stochastic resonance for local circuits consisting of roughly 100 neurons - a ``microcolumn''- coupled via noisy plastic synapses. Furthermore, due to the plastic coupling and activity-dependent noise component, the detection of weak stimuli will also depend on the structure of the latter. In addition, the circuit can exhibit short-term memory, by which we mean that spiking will continue to occur for a transient period following removal of the stimulus. These results can be directly tested in experiments on cultured networks.

CBL-CIPK network for calcium signaling in higher plants

NASA Astrophysics Data System (ADS)

Luan, Sheng

Plants sense their environment by signaling mechanisms involving calcium. Calcium signals are encoded by a complex set of parameters and decoded by a large number of proteins including the more recently discovered CBL-CIPK network. The calcium-binding CBL proteins specifi-cally interact with a family of protein kinases CIPKs and regulate the activity and subcellular localization of these kinases, leading to the modification of kinase substrates. This represents a paradigm shift as compared to a calcium signaling mechanism from yeast and animals. One example of CBL-CIPK signaling pathways is the low-potassium response of Arabidopsis roots. When grown in low-K medium, plants develop stronger K-uptake capacity adapting to the low-K condition. Recent studies show that the increased K-uptake is caused by activation of a specific K-channel by the CBL-CIPK network. A working model for this regulatory pathway will be discussed in the context of calcium coding and decoding processes.

The Joint Fire Science Program Fire Exchange Network: Facilitating Knowledge Exchange About Wildland Fire Science Across the U.S.

NASA Astrophysics Data System (ADS)

York, A.; Blocksome, C.; Cheng, T.; Creighton, J.; Edwards, G.; Frederick, S.; Giardina, C. P.; Goebel, P. C.; Gucker, C.; Kobziar, L.; Lane, E.; Leis, S.; Long, A.; Maier, C.; Marschall, J.; McGowan-Stinski, J.; Mohr, H.; MontBlanc, E.; Pellant, M.; Pickett, E.; Seesholtz, D.; Skowronski, N.; Stambaugh, M. C.; Stephens, S.; Thode, A.; Trainor, S. F.; Waldrop, T.; Wolfson, B.; Wright, V.; Zedler, P.

2014-12-01

The Joint Fire Science Program's (JFSP) Fire Exchange Network is actively working to accelerate the awareness, understanding, and adoption of wildland fire science information by federal, tribal, state, local, and private stakeholders within ecologically similar regions. Our network of 15 regional exchanges provides timely, accurate, and regionally relevant science-based information to assist with fire management challenges. Regional activities, through which we engage fire and resource managers, scientists, and private landowners, include online newsletters and announcements, social media, regionally focused web-based clearinghouses of relevant science, field trips and demonstration sites, workshops and conferences, webinars and online training, and syntheses and fact sheets. Exchanges also help investigators design research that is relevant to regional management needs and assist with technology transfer to management audiences. This poster provides an introduction to and map of the regional exchanges.

Effective connectivity of facial expression network by using Granger causality analysis

NASA Astrophysics Data System (ADS)

Zhang, Hui; Li, Xiaoting

2013-10-01

Functional magnetic resonance imaging (fMRI) is an advanced non-invasive data acquisition technique to investigate the neural activity in human brain. In addition to localize the functional brain regions that is activated by specific cognitive task, fMRI can also be utilized to measure the task-related functional interactions among the active regions of interest (ROI) in the brain. Among the variety of analysis tools proposed for modeling the connectivity of brain regions, Granger causality analysis (GCA) measure the directions of information interactions by looking for the lagged effect among the brain regions. In this study, we use fMRI and Granger Causality analysis to investigate the effective connectivity of brain network induced by viewing several kinds of expressional faces. We focus on four kinds of facial expression stimuli: fearful, angry, happy and neutral faces. Five face selective regions of interest are localized and the effective connectivity within these regions is measured for the expressional faces. Our result based on 8 subjects showed that there is significant effective connectivity from STS to amygdala, from amygdala to OFA, aFFA and pFFA, from STS to aFFA and from pFFA to aFFA. This result suggested that there is an information flow from the STS to the amygdala when perusing expressional faces. This emotional expressional information flow that is conveyed by STS and amygdala, flow back to the face selective regions in occipital-temporal lobes, which constructed a emotional face processing network.

Telecommunications and navigation systems design for manned Mars exploration missions

NASA Astrophysics Data System (ADS)

Hall, Justin R.; Hastrup, Rolf C.

1989-06-01

This paper discusses typical manned Mars exploration needs for telecommunications, including preliminary navigation support functions. It is a brief progress report on an ongoing study program within the current NASA JPL Deep Space Network (DSN) activities. A typical Mars exploration case is defined, and support approaches comparing microwave and optical frequency performance for both local in situ and Mars-earth links are described. Optical telecommunication and navigation technology development opportunities in a Mars exploration program are also identified. A local Mars system telecommunication relay and navigation capability for service support of all Mars missions has been proposed as part of an overall solar system communications network. The effects of light-time delay and occultations on real-time mission decision-making are discussed; the availability of increased local mass data storage may be more important than increasing peak data rates to earth. The long-term frequency use plan will most likely include a mix of microwave, millimeter-wave and optical link capabilities to meet a variety of deep space mission needs.

Telecommunications and navigation systems design for manned Mars exploration missions

NASA Technical Reports Server (NTRS)

Hall, Justin R.; Hastrup, Rolf C.

1989-01-01

This paper discusses typical manned Mars exploration needs for telecommunications, including preliminary navigation support functions. It is a brief progress report on an ongoing study program within the current NASA JPL Deep Space Network (DSN) activities. A typical Mars exploration case is defined, and support approaches comparing microwave and optical frequency performance for both local in situ and Mars-earth links are described. Optical telecommunication and navigation technology development opportunities in a Mars exploration program are also identified. A local Mars system telecommunication relay and navigation capability for service support of all Mars missions has been proposed as part of an overall solar system communications network. The effects of light-time delay and occultations on real-time mission decision-making are discussed; the availability of increased local mass data storage may be more important than increasing peak data rates to earth. The long-term frequency use plan will most likely include a mix of microwave, millimeter-wave and optical link capabilities to meet a variety of deep space mission needs.

Mechanisms of perceptual organization provide auto-zoom and auto-localization for attention to objects

PubMed Central

Mihalas, Stefan; Dong, Yi; von der Heydt, Rüdiger; Niebur, Ernst

2011-01-01

Visual attention is often understood as a modulatory field acting at early stages of processing, but the mechanisms that direct and fit the field to the attended object are not known. We show that a purely spatial attention field propagating downward in the neuronal network responsible for perceptual organization will be reshaped, repositioned, and sharpened to match the object's shape and scale. Key features of the model are grouping neurons integrating local features into coherent tentative objects, excitatory feedback to the same local feature neurons that caused grouping neuron activation, and inhibition between incompatible interpretations both at the local feature level and at the object representation level. PMID:21502489

Local domains of motor cortical activity revealed by fiber-optic calcium recordings in behaving nonhuman primates.

PubMed

Adelsberger, Helmuth; Zainos, Antonio; Alvarez, Manuel; Romo, Ranulfo; Konnerth, Arthur

2014-01-07

Brain mapping experiments involving electrical microstimulation indicate that the primary motor cortex (M1) directly regulates muscle contraction and thereby controls specific movements. Possibly, M1 contains a small circuit "map" of the body that is formed by discrete local networks that code for specific movements. Alternatively, movements may be controlled by distributed, larger-scale overlapping circuits. Because of technical limitations, it remained unclear how movement-determining circuits are organized in M1. Here we introduce a method that allows the functional mapping of small local neuronal circuits in awake behaving nonhuman primates. For this purpose, we combined optic-fiber-based calcium recordings of neuronal activity and cortical microstimulation. The method requires targeted bulk loading of synthetic calcium indicators (e.g., OGB-1 AM) for the staining of neuronal microdomains. The tip of a thin (200 µm) optical fiber can detect the coherent activity of a small cluster of neurons, but is insensitive to the asynchronous activity of individual cells. By combining such optical recordings with microstimulation at two well-separated sites of M1, we demonstrate that local cortical activity was tightly associated with distinct and stereotypical simple movements. Increasing stimulation intensity increased both the amplitude of the movements and the level of neuronal activity. Importantly, the activity remained local, without invading the recording domain of the second optical fiber. Furthermore, there was clear response specificity at the two recording sites in a trained behavioral task. Thus, the results provide support for movement control in M1 by local neuronal clusters that are organized in discrete cortical domains.

Robustness and structure of complex networks

NASA Astrophysics Data System (ADS)

Shao, Shuai

This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks are much more vulnerable to localized attack compared with random attack. In the second part, we extend the tree-like generating function method to incorporating clustering structure in complex networks. We study the robustness of a complex network system, especially a network of networks (NON) with clustering structure in each network. We find that the system becomes less robust as we increase the clustering coefficient of each network. For a partially dependent network system, we also find that the influence of the clustering coefficient on network robustness decreases as we decrease the coupling strength, and the critical coupling strength qc, at which the first-order phase transition changes to second-order, increases as we increase the clustering coefficient.

Local Area Networks (The Printout).

ERIC Educational Resources Information Center

Aron, Helen; Balajthy, Ernest

1989-01-01

Describes the Local Area Network (LAN), a project in which students used LAN-based word processing and electronic mail software as the center of a writing process approach. Discusses the advantages and disadvantages of networking. (MM)

Hemispheric asymmetry of electroencephalography-based functional brain networks.

PubMed

Jalili, Mahdi

2014-11-12

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Functional cliques in the amygdala and related brain networks driven by fear assessment acquired during movie viewing.

PubMed

Kinreich, Sivan; Intrator, Nathan; Hendler, Talma

2011-01-01

One of the greatest challenges involved in studying the brain mechanisms of fear is capturing the individual's unique instantaneous experience. Brain imaging studies to date commonly sacrifice valuable information regarding the individual real-time conscious experience, especially when focusing on elucidating the amygdala's activity. Here, we assumed that by using a minimally intrusive cue along with applying a robust clustering approach to probe the amygdala, it would be possible to rate fear in real time and to derive the related network of activation. During functional magnetic resonance imaging scanning, healthy volunteers viewed two excerpts from horror movies and were periodically auditory cued to rate their instantaneous experience of "I'm scared." Using graph theory and community mathematical concepts, data-driven clustering of the fear-related functional cliques in the amygdala was performed guided by the individually marked periods of heightened fear. Individually tailored functions derived from these amygdala activation cliques were subsequently applied as general linear model predictors to a whole-brain analysis to reveal the correlated networks. Our results suggest that by using a localized robust clustering approach, it is possible to probe activation in the right dorsal amygdala that is directly related to individual real-time emotional experience. Moreover, this fear-evoked amygdala revealed two opposing networks of co-activation and co-deactivation, which correspond to vigilance and rest-related circuits, respectively.

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

NASA Astrophysics Data System (ADS)

Prisk, T. R.; Hoffmann, C.; Kolesnikov, A. I.; Mamontov, E.; Podlesnyak, A. A.; Wang, X.; Kent, P. R. C.; Anovitz, L. M.

2018-05-01

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factor reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10-100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.

Mapping and mining interictal pathological gamma (30–100 Hz) oscillations with clinical intracranial EEG in patients with epilepsy

PubMed Central

Smart, Otis; Maus, Douglas; Marsh, Eric; Dlugos, Dennis; Litt, Brian; Meador, Kimford

2012-01-01

Localizing an epileptic network is essential for guiding neurosurgery and antiepileptic medical devices as well as elucidating mechanisms that may explain seizure-generation and epilepsy. There is increasing evidence that pathological oscillations may be specific to diseased networks in patients with epilepsy and that these oscillations may be a key biomarker for generating and indentifying epileptic networks. We present a semi-automated method that detects, maps, and mines pathological gamma (30–100 Hz) oscillations (PGOs) in human epileptic brain to possibly localize epileptic networks. We apply the method to standard clinical iEEG (<100 Hz) with interictal PGOs and seizures from six patients with medically refractory epilepsy. We demonstrate that electrodes with consistent PGO discharges do not always coincide with clinically determined seizure onset zone (SOZ) electrodes but at times PGO-dense electrodes include secondary seizure-areas (SS) or even areas without seizures (NS). In 4/5 patients with epilepsy surgery, we observe poor (Engel Class 4) post-surgical outcomes and identify more PGO-activity in SS or NS than in SOZ. Additional studies are needed to further clarify the role of PGOs in epileptic brain. PMID:23105174

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

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

Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

DOE PAGES

Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.; ...

2018-05-09

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less

Choline-mediated modulation of hippocampal sharp wave-ripple complexes in vitro.

PubMed

Fischer, Viktoria; Both, Martin; Draguhn, Andreas; Egorov, Alexei V

2014-06-01

The cholinergic system is critically involved in the modulation of cognitive functions, including learning and memory. Acetylcholine acts through muscarinic (mAChRs) and nicotinic receptors (nAChRs), which are both abundantly expressed in the hippocampus. Previous evidence indicates that choline, the precursor and degradation product of Acetylcholine, can itself activate nAChRs and thereby affects intrinsic and synaptic neuronal functions. Here, we asked whether the cellular actions of choline directly affect hippocampal network activity. Using mouse hippocampal slices we found that choline efficiently suppresses spontaneously occurring sharp wave-ripple complexes (SPW-R) and can induce gamma oscillations. In addition, choline reduces synaptic transmission between hippocampal subfields CA3 and CA1. Surprisingly, these effects are mediated by activation of both mAChRs and α7-containing nAChRs. Most nicotinic effects became only apparent after local, fast application of choline, indicating rapid desensitization kinetics of nAChRs. Effects were still present following block of choline uptake and are, therefore, likely because of direct actions of choline at the respective receptors. Together, choline turns out to be a potent regulator of patterned network activity within the hippocampus. These actions may be of importance for understanding state transitions in normal and pathologically altered neuronal networks. In this study we asked whether choline, the precursor and degradation product of acetylcholine, directly affects hippocampal network activity. Using mouse hippocampal slices we found that choline efficiently suppresses spontaneously occurring sharp wave-ripple complexes (SPW-R). In addition, choline reduces synaptic transmission between hippocampal subfields. These effects are mediated by direct activation of muscarinic as well as nicotinic cholinergic pathways. Together, choline turns out to be a potent regulator of patterned activity within hippocampal networks. © 2014 International Society for Neurochemistry.

Connectionist Models: Proceedings of the Summer School Held in San Diego, California on 1990

DTIC Science & Technology

1990-01-01

modes: control network continues activation spreading based There is the sequential version and the parallel version on the actual inputs instead of...ent). 2. Execute all motoric actions based on activations of r a ent.The parallel version of the algorithm is local in time, units in A. Update the...a- movements that help o recognize an entering person.) tions like ’move focus left’, ’rotate focus’ are based on the activations of the C’s output

Relations between macropore network characteristics and the degree of preferential solute transport

NASA Astrophysics Data System (ADS)

Larsbo, M.; Koestel, J.; Jarvis, N.

2014-12-01

The characteristics of the soil macropore network determine the potential for fast transport of agrochemicals and contaminants through the soil. The objective of this study was to examine the relationships between macropore network characteristics, hydraulic properties and state variables and measures of preferential transport. Experiments were carried out under near-saturated conditions on undisturbed columns sampled from four agricultural topsoils of contrasting texture and structure. Macropore network characteristics were computed from 3-D X-ray tomography images of the soil pore system. Non-reactive solute transport experiments were carried out at five steady-state water flow rates from 2 to 12 mm h-1. The degree of preferential transport was evaluated by the normalised 5% solute arrival time and the apparent dispersivity calculated from the resulting breakthrough curves. Near-saturated hydraulic conductivities were measured on the same samples using a tension disc infiltrometer placed on top of the columns. Results showed that many of the macropore network characteristics were inter-correlated. For example, large macroporosities were associated with larger specific macropore surface areas and better local connectivity of the macropore network. Generally, an increased flow rate resulted in earlier solute breakthrough and a shifting of the arrival of peak concentration towards smaller drained volumes. Columns with smaller macroporosities, poorer local connectivity of the macropore network and smaller near-saturated hydraulic conductivities exhibited a greater degree of preferential transport. This can be explained by the fact that, with only two exceptions, global (i.e. sample scale) continuity of the macropore network was still preserved at low macroporosities. Thus, for any given flow rate, pores of larger diameter were actively conducting solute in soils of smaller near-saturated hydraulic conductivity. This was associated with larger local transport velocities and, hence, less time for equilibration between the macropores and the surrounding matrix which made the transport more preferential. Conversely, the large specific macropore surface area and well-connected macropore networks associated with columns with large macroporosities limit the degree of preferential transport because they increase the diffusive flux between macropores and the soil matrix and they increase the near-saturated hydraulic conductivity. The normalised 5% arrival times were most strongly correlated with the estimated hydraulic state variables (e.g. with the degree of saturation in the macropores R2 = 0.589), since these combine into one measure the effects of irrigation rate and the near-saturated hydraulic conductivity function, which in turn implicitly depends on the volume, size distribution, global continuity, local connectivity and tortuosity of the macropore network.

News Release: USDA Joins Fair Food Network, State and Local Partners to

Science.gov Websites

Promote Nutrition Resources for Lead-Affected Flint Residents - PHE You may be trying to access Joins Fair Food Network, State and Local Partners to Promote Nutrition Resources for Lead-Affected Flint Residents News Release: USDA Joins Fair Food Network, State and Local Partners to Promote Nutrition

The Structure of Policy Networks for Injury and Violence Prevention in 15 US Cities

PubMed Central

Jonson-Reid, Melissa; Carothers, Bobbi J.; Fowler, Patrick

2017-01-01

Objectives: Changes in policy can reduce violence and injury; however, little is known about how partnerships among organizations influence policy development, adoption, and implementation. To understand partnerships among organizations working on injury and violence prevention (IVP) policy, we examined IVP policy networks in 15 large US cities. Methods: In summer 2014, we recruited 15 local health departments (LHDs) to participate in the study. They identified an average of 28.9 local partners (SD = 10.2) working on IVP policy. In late 2014, we sent survey questionnaires to 434 organizations, including the 15 LHDs and their local partners, about their partnerships and the importance of each organization to local IVP policy efforts; 319 participated. We used network methods to examine the composition and structure of the policy networks. Results: Each IVP policy network included the LHD and an average of 21.3 (SD = 6.9) local partners. On average, nonprofit organizations constituted 50.7% of networks, followed by government agencies (26.3%), schools and universities (11.8%), coalitions (11.2%), voluntary organizations (9.6%), hospitals (8.5%), foundations (2.2%), and for-profit organizations (0.7%). Government agencies were perceived as important by the highest proportion of partners. Perceived importance was significantly associated with forming partnerships in most networks; odds ratios ranged from 1.07 (95% CI, 1.02-1.13) to 2.35 (95% CI, 1.68-3.28). Organization type was significantly associated with partnership formation in most networks after controlling for an organization’s importance to the network. Conclusions: Several strategies could strengthen local IVP policy networks, including (1) developing connections with partners from sectors that are not well integrated into the networks and (2) encouraging indirect or less formal connections with important but missing partners and partner types. PMID:28426291

The Structure of Policy Networks for Injury and Violence Prevention in 15 US Cities.

PubMed

Harris, Jenine K; Jonson-Reid, Melissa; Carothers, Bobbi J; Fowler, Patrick

Changes in policy can reduce violence and injury; however, little is known about how partnerships among organizations influence policy development, adoption, and implementation. To understand partnerships among organizations working on injury and violence prevention (IVP) policy, we examined IVP policy networks in 15 large US cities. In summer 2014, we recruited 15 local health departments (LHDs) to participate in the study. They identified an average of 28.9 local partners (SD = 10.2) working on IVP policy. In late 2014, we sent survey questionnaires to 434 organizations, including the 15 LHDs and their local partners, about their partnerships and the importance of each organization to local IVP policy efforts; 319 participated. We used network methods to examine the composition and structure of the policy networks. Each IVP policy network included the LHD and an average of 21.3 (SD = 6.9) local partners. On average, nonprofit organizations constituted 50.7% of networks, followed by government agencies (26.3%), schools and universities (11.8%), coalitions (11.2%), voluntary organizations (9.6%), hospitals (8.5%), foundations (2.2%), and for-profit organizations (0.7%). Government agencies were perceived as important by the highest proportion of partners. Perceived importance was significantly associated with forming partnerships in most networks; odds ratios ranged from 1.07 (95% CI, 1.02-1.13) to 2.35 (95% CI, 1.68-3.28). Organization type was significantly associated with partnership formation in most networks after controlling for an organization's importance to the network. Several strategies could strengthen local IVP policy networks, including (1) developing connections with partners from sectors that are not well integrated into the networks and (2) encouraging indirect or less formal connections with important but missing partners and partner types.

Abnormal functional global and local brain connectivity in female patients with anorexia nervosa

PubMed Central

Geisler, Daniel; Borchardt, Viola; Lord, Anton R.; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A.; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

2016-01-01

Background Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. Methods To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Results Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. Limitations The present results may be limited to the methods applied during preprocessing and network construction. Conclusion We demonstrated anorexia nervosa–related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger. PMID:26252451

Abnormal functional global and local brain connectivity in female patients with anorexia nervosa.

PubMed

Geisler, Daniel; Borchardt, Viola; Lord, Anton R; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

2016-01-01

Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. The present results may be limited to the methods applied during preprocessing and network construction. We demonstrated anorexia nervosa-related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger.

Neural Oscillations and Synchrony in Brain Dysfunction and Neuropsychiatric Disorders: It's About Time.

PubMed

Mathalon, Daniel H; Sohal, Vikaas S

2015-08-01

Neural oscillations are rhythmic fluctuations over time in the activity or excitability of single neurons, local neuronal populations or "assemblies," and/or multiple regionally distributed neuronal assemblies. Synchronized oscillations among large numbers of neurons are evident in electrocorticographic, electroencephalographic, magnetoencephalographic, and local field potential recordings and are generally understood to depend on inhibition that paces assemblies of excitatory neurons to produce alternating temporal windows of reduced and increased excitability. Synchronization of neural oscillations is supported by the extensive networks of local and long-range feedforward and feedback bidirectional connections between neurons. Here, we review some of the major methods and measures used to characterize neural oscillations, with a focus on gamma oscillations. Distinctions are drawn between stimulus-independent oscillations recorded during resting states or intervals between task events, stimulus-induced oscillations that are time locked but not phase locked to stimuli, and stimulus-evoked oscillations that are both time and phase locked to stimuli. Synchrony of oscillations between recording sites, and between the amplitudes and phases of oscillations of different frequencies (cross-frequency coupling), is described and illustrated. Molecular mechanisms underlying gamma oscillations are also reviewed. Ultimately, understanding the temporal organization of neuronal network activity, including interactions between neural oscillations, is critical for elucidating brain dysfunction in neuropsychiatric disorders.

Communication Dynamics in Finite Capacity Social Networks

NASA Astrophysics Data System (ADS)

Haerter, Jan O.; Jamtveit, Bjørn; Mathiesen, Joachim

2012-10-01

In communication networks, structure and dynamics are tightly coupled. The structure controls the flow of information and is itself shaped by the dynamical process of information exchanged between nodes. In order to reconcile structure and dynamics, a generic model, based on the local interaction between nodes, is considered for the communication in large social networks. In agreement with data from a large human organization, we show that the flow is non-Markovian and controlled by the temporal limitations of individuals. We confirm the versatility of our model by predicting simultaneously the degree-dependent node activity, the balance between information input and output of nodes, and the degree distribution. Finally, we quantify the limitations to network analysis when it is based on data sampled over a finite period of time.

Incoherent feedforward control governs adaptation of activated ras in a eukaryotic chemotaxis pathway.

PubMed

Takeda, Kosuke; Shao, Danying; Adler, Micha; Charest, Pascale G; Loomis, William F; Levine, Herbert; Groisman, Alex; Rappel, Wouter-Jan; Firtel, Richard A

2012-01-03

Adaptation in signaling systems, during which the output returns to a fixed baseline after a change in the input, often involves negative feedback loops and plays a crucial role in eukaryotic chemotaxis. We determined the dynamical response to a uniform change in chemoattractant concentration of a eukaryotic chemotaxis pathway immediately downstream from G protein-coupled receptors. The response of an activated Ras showed near-perfect adaptation, leading us to attempt to fit the results using mathematical models for the two possible simple network topologies that can provide perfect adaptation. Only the incoherent feedforward network accurately described the experimental results. This analysis revealed that adaptation in this Ras pathway is achieved through the proportional activation of upstream components and not through negative feedback loops. Furthermore, these results are consistent with a local excitation, global inhibition mechanism for gradient sensing, possibly with a Ras guanosine triphosphatase-activating protein acting as a global inhibitor.

Functional connectivity mapping of regions associated with self- and other-processing.

PubMed

Murray, Ryan J; Debbané, Martin; Fox, Peter T; Bzdok, Danilo; Eickhoff, Simon B

2015-04-01

Neuroscience literature increasingly suggests a conceptual self composed of interacting neural regions, rather than independent local activations, yet such claims have yet to be investigated. We, thus, combined task-dependent meta-analytic connectivity modeling (MACM) with task-independent resting-state (RS) connectivity analysis to delineate the neural network of the self, across both states. Given psychological evidence implicating the self's interdependence on social information, we also delineated the neural network underlying conceptual other-processing. To elucidate the relation between the self-/other-networks and their function, we mined the MACM metadata to generate a cognitive-behavioral profile for an empirically identified region specific to conceptual self, the pregenual anterior cingulate (pACC), and conceptual other, posterior cingulate/precuneus (PCC/PC). Mining of 7,200 published, task-dependent, neuroimaging studies, using healthy human subjects, yielded 193 studies activating the self-related seed and were conjoined with RS connectivity analysis to delineate a differentiated self-network composed of the pACC (seed) and anterior insula, relative to other functional connectivity. Additionally, 106 studies activating the other-related seed were conjoined with RS connectivity analysis to delineate a differentiated other-network of PCC/PC (seed) and angular gyrus/temporoparietal junction, relative to self-functional connectivity. The self-network seed related to emotional conflict resolution and motivational processing, whereas the other-network seed related to socially oriented processing and contextual information integration. Notably, our findings revealed shared RS connectivity between ensuing self-/other-networks within the ventromedial prefrontal cortex and medial orbitofrontal cortex, suggesting self-updating via integration of self-relevant social information. We, therefore, present initial neurobiological evidence corroborating the increasing claims of an intricate self-network, the architecture of which may promote social value processing. © 2014 Wiley Periodicals, Inc.

Confinement Regulates Complex Biochemical Networks: Initiation of Blood Clotting by “Diffusion Acting”

PubMed Central

Shen, Feng; Pompano, Rebecca R.; Kastrup, Christian J.; Ismagilov, Rustem F.

2009-01-01

Abstract This study shows that environmental confinement strongly affects the activation of nonlinear reaction networks, such as blood coagulation (clotting), by small quantities of activators. Blood coagulation is sensitive to the local concentration of soluble activators, initiating only when the activators surpass a threshold concentration, and therefore is regulated by mass transport phenomena such as flow and diffusion. Here, diffusion was limited by decreasing the size of microfluidic chambers, and it was found that microparticles carrying either the classical stimulus, tissue factor, or a bacterial stimulus, Bacillus cereus, initiated coagulation of human platelet-poor plasma only when confined. A simple analytical argument and numerical model were used to describe the mechanism for this phenomenon: confinement causes diffusible activators to accumulate locally and surpass the threshold concentration. To interpret the results, a dimensionless confinement number, Cn, was used to describe whether a stimulus was confined, and a Damköhler number, Da2, was used to describe whether a subthreshold stimulus could initiate coagulation. In the context of initiation of coagulation by bacteria, this mechanism can be thought of as “diffusion acting”, which is distinct from “diffusion sensing”. The ability of confinement and diffusion acting to change the outcome of coagulation suggests that confinement should also regulate other biological “on” and “off” processes that are controlled by thresholds. PMID:19843446

CD-ROM and Local Area Networks.

ERIC Educational Resources Information Center

Marks, Kenneth E.; And Others

1993-01-01

This special section on local area networks includes three articles: (1) a description of migration at Joyner Library, East Carolina University (North Carolina) to a new network server; (2) a discussion of factors to consider for network planning in school libraries; and (3) a directory of companies supplying cable, hardware, software, and…

Intelligent routing protocol for ad hoc wireless network

NASA Astrophysics Data System (ADS)

Peng, Chaorong; Chen, Chang Wen

2006-05-01

A novel routing scheme for mobile ad hoc networks (MANETs), which combines hybrid and multi-inter-routing path properties with a distributed topology discovery route mechanism using control agents is proposed in this paper. In recent years, a variety of hybrid routing protocols for Mobile Ad hoc wireless networks (MANETs) have been developed. Which is proactively maintains routing information for a local neighborhood, while reactively acquiring routes to destinations beyond the global. The hybrid protocol reduces routing discovery latency and the end-to-end delay by providing high connectivity without requiring much of the scarce network capacity. On the other side the hybrid routing protocols in MANETs likes Zone Routing Protocol still need route "re-discover" time when a route between zones link break. Sine the topology update information needs to be broadcast routing request on local zone. Due to this delay, the routing protocol may not be applicable for real-time data and multimedia communication. We utilize the advantages of a clustering organization and multi-routing path in routing protocol to achieve several goals at the same time. Firstly, IRP efficiently saves network bandwidth and reduces route reconstruction time when a routing path fails. The IRP protocol does not require global periodic routing advertisements, local control agents will automatically monitor and repair broke links. Secondly, it efficiently reduces congestion and traffic "bottlenecks" for ClusterHeads in clustering network. Thirdly, it reduces significant overheads associated with maintaining clusters. Fourthly, it improves clusters stability due to dynamic topology changing frequently. In this paper, we present the Intelligent Routing Protocol. First, we discuss the problem of routing in ad hoc networks and the motivation of IRP. We describe the hierarchical architecture of IRP. We describe the routing process and illustrate it with an example. Further, we describe the control manage mechanisms, which are used to control active route and reduce the traffic amount in the route discovery procedure. Finial, the numerical experiments are given to show the effectiveness of IRP routing protocol.

A Low Cost Micro-Computer Based Local Area Network for Medical Office and Medical Center Automation

PubMed Central

Epstein, Mel H.; Epstein, Lynn H.; Emerson, Ron G.

1984-01-01

A Low Cost Micro-computer based Local Area Network for medical office automation is described which makes use of an array of multiple and different personal computers interconnected by a local area network. Each computer on the network functions as fully potent workstations for data entry and report generation. The network allows each workstation complete access to the entire database. Additionally, designated computers may serve as access ports for remote terminals. Through “Gateways” the network may serve as a front end for a large mainframe, or may interface with another network. The system provides for the medical office environment the expandability and flexibility of a multi-terminal mainframe system at a far lower cost without sacrifice of performance.

Research on social communication network evolution based on topology potential distribution

NASA Astrophysics Data System (ADS)

Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng

2011-12-01

Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.

Competing dynamic phases of active polymer networks

NASA Astrophysics Data System (ADS)

Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Local Estimators for Spacecraft Formation Flying

NASA Technical Reports Server (NTRS)

Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Nabi, Marzieh

2011-01-01

A formation estimation architecture for formation flying builds upon the local information exchange among multiple local estimators. Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are needed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms should rely on a local information-exchange network, relaxing the assumptions on existing algorithms. In this research, it was shown that only local observability is required to design a formation estimator and control law. The approach relies on breaking up the overall information-exchange network into sequence of local subnetworks, and invoking an agreement-type filter to reach consensus among local estimators within each local network. State estimates were obtained by a set of local measurements that were passed through a set of communicating Kalman filters to reach an overall state estimation for the formation. An optimization approach was also presented by means of which diffused estimates over the network can be incorporated in the local estimates obtained by each estimator via local measurements. This approach compares favorably with that obtained by a centralized Kalman filter, which requires complete knowledge of the raw measurement available to each estimator.

Risk management communication system between a local government and residents using several network systems and terminal devices

NASA Astrophysics Data System (ADS)

Ohyama, Takashi; Enomoto, Hiroyuki; Takei, Yuichiro; Maeda, Yuji

2009-05-01

Most of Japan's local governments utilize municipal disaster-management radio communications systems to communicate information on disasters or terrorism to residents. The national government is progressing in efforts toward digitalization by local governments of these systems, but only a small number (approx. 10%) have introduced such equipment due to its requiring large amounts of investment. On the other hand, many local governments are moving forward in installation of optical fiber networks for the purpose of eliminating the "digital divide." We herein propose a communication system as an alternative or supplement to municipal disaster-management radio communications systems, which utilizes municipal optical fiber networks, the internet and similar networks and terminals. The system utilizes the multiple existing networks and is capable of instantly distributing to all residents, and controlling, risk management information. We describe the system overview and the field trials conducted with a local government using this system.

QoS-aware health monitoring system using cloud-based WBANs.

PubMed

Almashaqbeh, Ghada; Hayajneh, Thaier; Vasilakos, Athanasios V; Mohd, Bassam J

2014-10-01

Wireless Body Area Networks (WBANs) are amongst the best options for remote health monitoring. However, as standalone systems WBANs have many limitations due to the large amount of processed data, mobility of monitored users, and the network coverage area. Integrating WBANs with cloud computing provides effective solutions to these problems and promotes the performance of WBANs based systems. Accordingly, in this paper we propose a cloud-based real-time remote health monitoring system for tracking the health status of non-hospitalized patients while practicing their daily activities. Compared with existing cloud-based WBAN frameworks, we divide the cloud into local one, that includes the monitored users and local medical staff, and a global one that includes the outer world. The performance of the proposed framework is optimized by reducing congestion, interference, and data delivery delay while supporting users' mobility. Several novel techniques and algorithms are proposed to accomplish our objective. First, the concept of data classification and aggregation is utilized to avoid clogging the network with unnecessary data traffic. Second, a dynamic channel assignment policy is developed to distribute the WBANs associated with the users on the available frequency channels to manage interference. Third, a delay-aware routing metric is proposed to be used by the local cloud in its multi-hop communication to speed up the reporting process of the health-related data. Fourth, the delay-aware metric is further utilized by the association protocols used by the WBANs to connect with the local cloud. Finally, the system with all the proposed techniques and algorithms is evaluated using extensive ns-2 simulations. The simulation results show superior performance of the proposed architecture in optimizing the end-to-end delay, handling the increased interference levels, maximizing the network capacity, and tracking user's mobility.

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks.

PubMed

Chen, Pengpeng; Ma, Honglu; Gao, Shouwan; Huang, Yan

2015-11-24

Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes' positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes' positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes' relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks.

A Datacenter Backstage: The Knowledge that Supports the Brazilian Seismic Network

NASA Astrophysics Data System (ADS)

Calhau, J.; Assumpcao, M.; Collaço, B.; Bianchi, M.; Pirchiner, M.

2015-12-01

Historically, Brazilian seismology never had a clear strategic vision about how its data should be acquired, evaluated, stored and shared. Without a data management plan, data (for any practical purpose) could be lost, resulting in a non-uniform coverage that will reduce any chance of local and international collaboration, i.e., data will never become scientific knowledge. Since 2009, huge efforts from four different institutions are establishing the new permanent Brazilian Seismographic Network (RSBR), mainly with resources from PETROBRAS, the Brazilian Government oil company. Four FDSN sub-networks currently compose RSBR, with a total of 80 permanent stations. BL and BR codes (from BRASIS subnet) with 47 stations maintained by University of Sao Paulo (USP) and University of Brasilia (UnB) respectively; NB code (RSISNE subnet), with 16 stations deployed by University of Rio Grande do Norte (UFRN); and ON code (RSIS subnet), with 18 stations operated by the National Observatory (ON) in Rio de Janeiro. Most stations transmit data in real-time via satellite or cell-phone links. Each node acquires its own stations locally, and data is real-time shared using SeedLink. Archived data is distributed via ArcLink and/or FDSNWS services. All nodes use the SeisComP3 system for real-time processing and as a levering back-end. Open-source solutions like Seiscomp3 require some homemade tools to be developed, to help solve the most common daily problems of a data management center: local magnitude into the real-time earthquake processor, website plugins, regional earthquake catalog, contribution with ISC catalog, quality-control tools, data request tools, etc. The main data products and community activities include: kml files, data availability plots, request charts, summer school courses, an Open Lab Day and news interviews. Finally, a good effort was made to establish BRASIS sub-network and the whole RSBR as a unified project, that serves as a communication channel between individuals operating local networks.

Real-time community detection in full social networks on a laptop

PubMed Central

Chamberlain, Benjamin Paul; Levy-Kramer, Josh; Humby, Clive

2018-01-01

For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide free services that are valued by billions of people globally. PMID:29342158

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City

PubMed Central

2016-01-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast. PMID:27855155

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier

PubMed Central

Akram, M. Usman; Khan, Shoab A.; Javed, Muhammad Younus

2014-01-01

National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network. PMID:25136674

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Becoming Heritage: A Place-Making Study of Old Neighbourhood Marketplace in Bandung

NASA Astrophysics Data System (ADS)

Ekomadyo, A. S.; Nurfadillah, A.; Kartamihardja, A.; Cungwin, A. J.

2018-05-01

The urban architectural heritages of Bandung represents the city’s historical layers. A unique urban architectural element found in Bandung is the heritage neighborhood marketplace. In the style of European post-renaissance urban design, a heritage neighborhood marketplace is initially designed as housing clusters with open spaces as neighborhood centre to create community privacy. But along the time, the neighborhood centre open their enclosed spaces and landmark buildings, transforming itself into small marketplaces with intensively daily activities. Through everyday place-making methods, this article investigates the history and meaning of neighborhood marketplace as everyday urban artefacts through observation, historical study, and interview. The study reveals are three main forces assembling the current form of neighborhood marketplaces in Bandung: Dutch-Indies colonialization, Chinese society trading network, and local traders’ tradition. Dutch-Indies colonialization in Bandung brought European architectural knowledge into neighborhood morphological design that contributed well-defined urban spaces. The Chinese trading network has been at place since the diaspora era and is still continued until now, bridging past and present life through economic activities. Local traders, who came after Dutch-Indies colonialization, fill the empty spaces of neighborhood centres with intensive formal and informal economic activities. Bandung heritage neighborhood marketplaces represent the city’s urban constellation, where global and local political-economic and socio-cultural forces meet in an urban process. Here, the urban heritage is redefined as living artefacts experienced in everyday urban life. Keywords: urban heritage, place making, neighborhood marketplace, Bandung, urban assemblage, living artefacts.

Resource redistribution in polydomous ant nest networks: local or global?

PubMed Central

Franks, Daniel W.; Robinson, Elva J.H.

2014-01-01

An important problem facing organisms in a heterogeneous environment is how to redistribute resources to where they are required. This is particularly complex in social insect societies as resources have to be moved both from the environment into the nest and between individuals within the nest. Polydomous ant colonies are split between multiple spatially separated, but socially connected, nests. Whether, and how, resources are redistributed between nests in polydomous colonies is unknown. We analyzed the nest networks of the facultatively polydomous wood ant Formica lugubris. Our results indicate that resource redistribution in polydomous F. lugubris colonies is organized at the local level between neighboring nests and not at the colony level. We found that internest trails connecting nests that differed more in their amount of foraging were stronger than trails between nests with more equal foraging activity. This indicates that resources are being exchanged directly from nests with a foraging excess to nests that require resources. In contrast, we found no significant relationships between nest properties, such as size and amount of foraging, and network measures such as centrality and connectedness. This indicates an absence of a colony-level resource exchange. This is a clear example of a complex behavior emerging as a result of local interactions between parts of a system. PMID:25214755

Carbon footprint of organic beef meat from farm to fork: A case study of short supply chain.

PubMed

Vitali, A; Grossi, G; Martino, G; Bernabucci, U; Nardone, A; Lacetera, N

2018-04-24

Sustainability of food systems is one of the big challenges of humans kind in the next years. Local food networks, especially the organic ones, are growing worldwide and few information is known about their carbon footprint. This study was aimed to assess greenhouse gases (GHG) emissions associated to organic local beef supply chain with a cradle to grave approach. The study pointed out an overall burden of 24.46 kg CO 2 eq./kg of cooked meat. The breeding and fattening phase accounted 86% of the total emissions and resulted the main hot spot throughout the whole chain. Enteric methane emission was the greatest source of GHG at farm gate (47%). The consumption of meat at home was the second hot spot throughout the chain (9%) and cooking process was the main source within this stage (72%). Retail and slaughtering activities accounted for 4.1% and 1.1% on the whole supply chain, respectively. The identification of GHG hot spots associated to organic beef meat produced and consumed in a local food network may stimulate the debate on environmental issues among the actors involved in the network and direct them toward processes, choices and habits less carbon polluting. This article is protected by copyright. All rights reserved.

Locally induced neuronal synchrony precisely propagates to specific cortical areas without rhythm distortion.

PubMed

Toda, Haruo; Kawasaki, Keisuke; Sato, Sho; Horie, Masao; Nakahara, Kiyoshi; Bepari, Asim K; Sawahata, Hirohito; Suzuki, Takafumi; Okado, Haruo; Takebayashi, Hirohide; Hasegawa, Isao

2018-05-16

Propagation of oscillatory spike firing activity at specific frequencies plays an important role in distributed cortical networks. However, there is limited evidence for how such frequency-specific signals are induced or how the signal spectra of the propagating signals are modulated during across-layer (radial) and inter-areal (tangential) neuronal interactions. To directly evaluate the direction specificity of spectral changes in a spiking cortical network, we selectively photostimulated infragranular excitatory neurons in the rat primary visual cortex (V1) at a supra-threshold level with various frequencies, and recorded local field potentials (LFPs) at the infragranular stimulation site, the cortical surface site immediately above the stimulation site in V1, and cortical surface sites outside V1. We found a significant reduction of LFP powers during radial propagation, especially at high-frequency stimulation conditions. Moreover, low-gamma-band dominant rhythms were transiently induced during radial propagation. Contrastingly, inter-areal LFP propagation, directed to specific cortical sites, accompanied no significant signal reduction nor gamma-band power induction. We propose an anisotropic mechanism for signal processing in the spiking cortical network, in which the neuronal rhythms are locally induced/modulated along the radial direction, and then propagate without distortion via intrinsic horizontal connections for spatiotemporally precise, inter-areal communication.