Metacommunity diversity depends on connectivity and patch arrangement in heterogeneous habitat networks

Connectivity is critical to the maintenance of biodiversity in fragmented landscapes, but its effects differ depending on the arrangement of linkages within a habitat network. Additionally, heterogeneity in habitat quality within the habitat network can alter patterns of diversity at local and regional scales in the metacommunity. Using a controlled experiment we examined the interactive effects of habitat connectivity, network form (linear vs square), and habitat patch quality on a moss‐inhabiting microarthropod community. We fragmented moss habitat while controlling for habitat loss, and altered habitat patch quality by regulating moisture conditions in landscapes differing in patch arrangement. Habitat patch quality had a significant effect on patterns of species richness, extinction, abundance and biomass. The effects of network form on diversity were strongest in heterogeneous landscapes. Gamma and beta diversity were greatest in continuous and linear landscapes. However, linear habitat networks showed marked patch specific edge effects that were detrimental to diversity under heterogeneous conditions. We provide direct evidence that habitat network structure impacts species community properties through mass effects, that are most evident when heterogeneity in habitat patch quality is present within the network. We conclude that habitat quality at the individual patch level and the distribution of high‐quality habitat within the network are important factors affecting biodiversity in metacommunities.     

Effects of non-synaptic neuronal interaction in cortex on synchronization and learning

During neural communication by means of action potentials, small electromagnetic (EM) fields are also generated. We use a three layered cortical neural network model to study the effects of EM fields and gap junctions on spatio-temporal network activity. We investigate the possible role of these effects in synchronizing activity, a phenomenon which has been observed in the olfactory cortex and the hippocampus. The simulation results support the notion that fast synchronization of activity in distant parts of the neural network are made possible by means of EM fields and/or gap junctions. The results also indicate that these effects, to a certain extent, are beneficial to system performance.     

Network Neighbors of Drug Targets Contribute to Drug Side-Effect Similarity

In pharmacology, it is essential to identify the molecular mechanisms of drug action in order to understand adverse side effects. These adverse side effects have been used to infer whether two drugs share a target protein. However, side-effect similarity of drugs could also be caused by their target proteins being close in a molecular network, which as such could cause similar downstream effects. In this study, we investigated the proportion of side-effect similarities that is due to targets that are close in the network compared to shared drug targets. We found that only a minor fraction of side-effect similarities (5.8 %) are caused by drugs targeting proteins close in the network, compared to side-effect similarities caused by overlapping drug targets (64%). Moreover, these targets that cause similar side effects are more often in a linear part of the network, having two or less interactions, than drug targets in general. Based on the examples, we gained novel insight into the molecular mechanisms of side effects associated with several drug targets. Looking forward, such analyses will be extremely useful in the process of drug development to better understand adverse side effects.     

Inhibition modifies the effects of slow calcium-activated potassium channels on epileptiform activity in a neuronal network model

Generation of epileptiform activity typically results from a change in the balance between network excitation and inhibition. Experimental evidence indicates that alterations of either synaptic activity or intrinsic membrane properties can produce increased network excitation. The slow Ca²⁺-activated K⁺ currents (sI_AHP) are important modulators of neuronal firing rate and excitability and have important established and potential roles in epileptogenesis. While the effects of changes in sI_AHP on individual neuronal excitability are readily studied and well established, the effects of such changes on network behavior are less well known. The experiments here utilize a defined small network model of multicompartment pyramidal cells and an inhibitory interneuron to study the effects of changes in sI_AHP on network behavior. The benefits of this model system include the ability to observe activity in all cells in a network and the effects of interactions of multiple simultaneous influences. In the model with no inhibitory interneuron, increasing sI_AHP results in progressively decreasing burst activity. Adding an inhibitory interneuron changes the observed effects; at modest inhibitory strengths, increasing sI_AHP in all network neurons actually results in increased network bursting (except at very high values). The duration of the burst activity is influenced by the length of delay in a feedback loop, with longer loops resulting in more prolonged bursting. These observations illustrate that the study of potential antiepileptogenic membrane effects must be extended to realistic networks. Network inhibition can dramatically alter the observations seen in pure excitatory networks.     

Terrestrial origin of bacterial communities in complex boreal freshwater networks

Bacteria inhabiting boreal freshwaters are part of metacommunities where local assemblages are often linked by the flow of water in the landscape, yet the resulting spatial structure and the boundaries of the network metacommunity have never been explored. Here, we reconstruct the spatial structure of the bacterial metacommunity in a complex boreal aquatic network by determining the taxonomic composition of bacterial communities along the entire terrestrial/aquatic continuum, including soil and soilwaters, headwater streams, large rivers and lakes. We show that the network metacommunity has a directional spatial structure driven by a common terrestrial origin of aquatic communities, which are numerically dominated by taxa recruited from soils. Local community assembly is driven by variations along the hydrological continuum in the balance between mass effects and species sorting of terrestrial taxa, and seems further influenced by priority effects related to the spatial sequence of entry of soil bacteria into the network.     

AIM: A network model of attention in auditory cortex

Attentional modulation of cortical networks is critical for the cognitive flexibility required to process complex scenes. Current theoretical frameworks for attention are based almost exclusively on studies in visual cortex, where attentional effects are typically modest and excitatory. In contrast, attentional effects in auditory cortex can be large and suppressive. A theoretical framework for explaining attentional effects in auditory cortex is lacking, preventing a broader understanding of cortical mechanisms underlying attention. Here, we present a cortical network model of attention in primary auditory cortex (A1). A key mechanism in our network is attentional inhibitory modulation (AIM) of cortical inhibitory neurons. In this mechanism, top-down inhibitory neurons disinhibit bottom-up cortical circuits, a prominent circuit motif observed in sensory cortex. Our results reveal that the same underlying mechanisms in the AIM network can explain diverse attentional effects on both spatial and frequency tuning in A1. We find that a dominant effect of disinhibition on cortical tuning is suppressive, consistent with experimental observations. Functionally, the AIM network may play a key role in solving the cocktail party problem. We demonstrate how attention can guide the AIM network to monitor an acoustic scene, select a specific target, or switch to a different target, providing flexible outputs for solving the cocktail party problem.     

Modeling of Substance P and 5-HT Induced Synaptic Plasticity in the Lamprey Spinal CPG: Consequences for Network Pattern Generation

Consequences of synaptic plasticity in the lamprey spinal CPG are analyzed by means of simulations. This is motivated by the effects substance P (a tachykinin) and serotonin (5-hydroxytryptamin; 5-HT) have on synaptic transmission in the locomotor network. Activity-dependent synaptic depression and potentiation have recently been shown experimentally using paired intracellular recordings. Although normally activity-dependent plasticity presumably does not contribute to the patterning of network activity, this changes in the presence of the neuromodulators substance P and 5-HT, which evoke significant plasticity. Substance P can induce a faster and larger depression of inhibitory connections but potentiation of excitatory inputs, whereas 5-HT induces facilitation of both inhibitory and excitatory inputs. Changes in the amplitude of the first postsynaptic potential are also seen. These changes could thus be a potential mechanism underlying the modulatory role these substances have on the rhythmic network activity.The aim of the present study has been to implement the activity dependent synaptic depression and facilitation induced by substance P and 5-HT into two alternative models of the lamprey spinal locomotor network, one relying on reciprocal inhibition for bursting and one in which each hemicord is capable of oscillations. The consequences of the plasticity of inhibitory and excitatory connections are then explored on the network level.In the intact spinal cord, tachykinins and 5-HT, which can be endogenously released, increase and decrease the frequency of the alternating left-right burst pattern, respectively. The frequency decreasing effect of 5-HT has previously been explained based on its conductance decreasing effect on K _Ca underlying the postspike afterhyperpolarization (AHP). The present simulations show that short-term synaptic plasticity may have strong effects on frequency regulation in the lamprey spinal CPG. In the network model relying on reciprocal inhibition, the observed effects substance P and 5-HT have on network behavior (i.e., a frequency increase and decrease respectively) can to a substantial part be explained by their effects on the total extent and time dynamics of synaptic depression and facilitation. The cellular effects of these substances will in the 5-HT case further contribute to its network effect.     

Effects of channel bandwidth variation on performance of individual messages in spatially and temporally heterogeneous communication networks

As the domain of communication systems grows, heterogeneity among computers and subnetworks employed for a task also increases. Channel bandwidth available for a message on a communication network varies with time and link. This variation can have a significant effect on performance of an individual message and also that of the network as a whole. Therefore, it is important to understand effects of bandwidth heterogeneity on the network performance in order to optimally utilize a heterogeneous communication network. The ability to use such a network optimally is highly desirable in many applications such as network-based data-intensive high performance computing. The main goal of this paper is to analyze effects of temporal and spatial heterogeneity on performance of individual messages in detail via an extensive simulation, in terms of throughput, end-to-end delay, etc. Also, the problems of path selection and multi-path data transfer are considered to illustrate how the analysis results may be used in the future effort of optimizing the network performance by taking channel bandwidth heterogeneity into account.     

Towards more biological mutation operators in gene regulation studies

Genetic regulation is often viewed as a complex system whose properties emerge from the interaction of regulatory genes. One major paradigm for studying the complex dynamics of gene regulation uses directed graphs to explore structure, behaviour and evolvability. Mutation operators used in such studies typically involve the insertion and deletion of nodes, and the insertion, deletion and rewiring of links at the network level. These network-level mutational operators are sufficient to allow the statistical analysis of network structure, but impose limitations on the way networks are evolved. There are a wide variety of mutations in DNA sequences that have yet to be analysed for their network-level effects. By modelling an artificial genome at the level of nucleotide sequences and mapping it to a regulatory network, biologically grounded mutation operators can be mapped to network-level mutations. This paper analyses five such sequence level mutations (single-point mutation, transposition, inversion, deletion and gene duplication) for their effects at the network level. Using analytic and simulation techniques, we show that it is rarely the case that nodes and links are cleanly added or deleted, with even the simplest point mutation causing a wide variety of network-level modifications. As expected, the vast majority of simple (single-point) mutations are neutral, resulting in a neutral plateau from which a range of functional behaviours can be reached. By analysing the effects of sequence-level mutations at the network level of gene regulation, we aim to stimulate more careful consideration of mutation operators in gene regulation models than has previously been given.     

SPINE: a framework for signaling-regulatory pathway inference from cause-effect experiments

MOTIVATION: The complex program of gene expression allows the cell to cope with changing genetic, developmental and environmental conditions. The accumulating large-scale measurements of gene knockout effects and molecular interactions allow us to begin to uncover regulatory and signaling pathways within the cell that connect causal to affected genes on a network of physical interactions. RESULTS: We present a novel framework, SPINE, for Signaling-regulatory Pathway INferencE. The framework aims at explaining gene expression experiments in which a gene is knocked out and as a result multiple genes change their expression levels. To this end, an integrated network of protein-protein and protein-DNA interactions is constructed, and signaling pathways connecting the causal gene to the affected genes are searched for in this network. The reconstruction problem is translated into that of assigning an activation/repression attribute with each protein so as to explain (in expectation) a maximum number of the knockout effects observed. We provide an integer programming formulation for the latter problem and solve it using a commercial solver. We validate the method by applying it to a yeast subnetwork that is involved in mating. In cross-validation tests, SPINE obtains very high accuracy in predicting knockout effects (99%). Next, we apply SPINE to the entire yeast network to predict protein effects and reconstruct signaling and regulatory pathways. Overall, we are able to infer 861 paths with confidence and assign effects to 183 genes. The predicted effects are found to be in high agreement with current biological knowledge. AVAILABILITY: The algorithm and data are available at http://cs.tau.ac.il/~roded/SPINE.html.     

A Highlights from MBoC Selection: Protein kinase C activation decreases peripheral actin network density and increases central nonmuscle myosin II contractility in neuronal growth cones

Protein kinase C (PKC) can dramatically alter cell structure and motility via effects on actin filament networks. In neurons, PKC activation has been implicated in repulsive guidance responses and inhibition of axon regeneration; however, the cytoskeletal mechanisms underlying these effects are not well understood. Here we investigate the acute effects of PKC activation on actin network structure and dynamics in large Aplysia neuronal growth cones. We provide evidence of a novel two-tiered mechanism of PKC action: 1) PKC activity enhances myosin II regulatory light chain phosphorylation and C-kinase–potentiated protein phosphatase inhibitor phosphorylation. These effects are correlated with increased contractility in the central cytoplasmic domain. 2) PKC activation results in significant reduction of P-domain actin network density accompanied by Arp2/3 complex delocalization from the leading edge and increased rates of retrograde actin network flow. Our results show that PKC activation strongly affects both actin polymerization and myosin II contractility. This synergistic mode of action is relevant to understanding the pleiotropic reported effects of PKC on neuronal growth and regeneration.     

Smooth muscle length adaptation and actin filament length: a network model of the cytoskeletal dysregulation

Length adaptation of the airway smooth muscle cell is attributable to cytoskeletal remodeling. It has been proposed that dysregulated actin filaments may become longer in asthma, and that such elongation would prevent a parallel-to-series transition of contractile units, thus precluding the well-known beneficial effects of deep inspirations and tidal breathing. To test the potential effect that actin filament elongation could have in overall muscle mechanics, we present an extremely simple model. The cytoskeleton is represented as a 2-D network of links (contractile filaments) connecting nodes (adhesion plaques). Such a network evolves in discrete time steps by forming and dissolving links in a stochastic fashion. Links are formed by idealized contractile units whose properties are either those from normal or elongated actin filaments. Oscillations were then imposed on the network to evaluate both the effects of breathing and length adaptation. In response to length oscillation, a network with longer actin filaments showed smaller decreases of force, smaller increases in compliance, and higher shortening velocities. Taken together, these changes correspond to a network that is refractory to the effects of breathing and therefore approximates an asthmatic scenario. Thus, an extremely simple model seems to capture some relatively complex mechanics of airway smooth muscle, supporting the idea that dysregulation of actin filament length may contribute to excessive airway narrowing.     

Mechanical Cell–Cell Communication in Fibrous Networks: The Importance of Network Geometry

Cells contracting in extracellular matrix (ECM) can transmit stress over long distances, communicating their position and orientation to cells many tens of micrometres away. Such phenomena are not observed when cells are seeded on substrates with linear elastic properties, such as polyacrylamide (PA) gel. The ability for fibrous substrates to support far reaching stress and strain fields has implications for many physiological processes, while the mechanical properties of ECM are central to several pathological processes, including tumour invasion and fibrosis. Theoretical models have investigated the properties of ECM in a variety of network geometries. However, the effects of network architecture on mechanical cell–cell communication have received little attention. This work investigates the effects of geometry on network mechanics, and thus the ability for cells to communicate mechanically through different networks. Cell-derived displacement fields are quantified for various network geometries while controlling for network topology, cross-link density and micromechanical properties. We find that the heterogeneity of response, fibre alignment, and substrate displacement fields are sensitive to network choice. Further, we show that certain geometries support mechanical communication over longer distances than others. As such, we predict that the choice of network geometry is important in fundamental modelling of cell–cell interactions in fibrous substrates, as well as in experimental settings, where mechanical signalling at the cellular scale plays an important role. This work thus informs the construction of theoretical models for substrate mechanics and experimental explorations of mechanical cell–cell communication.     

Synchronization of neuron population subject to steady DC electric field induced by magnetic stimulation

Electric fields, which are ubiquitous in the context of neurons, are induced either by external electromagnetic fields or by endogenous electric activities. Clinical evidences point out that magnetic stimulation can induce an electric field that modulates rhythmic activity of special brain tissue, which are associated with most brain functions, including normal and pathological physiological mechanisms. Recently, the studies about the relationship between clinical treatment for psychiatric disorders and magnetic stimulation have been investigated extensively. However, further development of these techniques is limited due to the lack of understanding of the underlying mechanisms supporting the interaction between the electric field induced by magnetic stimulus and brain tissue. In this paper, the effects of steady DC electric field induced by magnetic stimulation on the coherence of an interneuronal network are investigated. Different behaviors have been observed in the network with different topologies (i.e., random and small-world network, modular network). It is found that the coherence displays a peak or a plateau when the induced electric field varies between the parameter range we defined. The coherence of the neuronal systems depends extensively on the network structure and parameters. All these parameters play a key role in determining the range for the induced electric field to synchronize network activities. The presented results could have important implications for the scientific theoretical studies regarding the effects of magnetic stimulation on human brain.     

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step‐wise boosted regression trees based on 250 m raster grid cells. Species‐specific models were built for both ‘moderate’ and ‘extreme’ future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7–2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56–85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts.     

Intracellular spatial localization regulated by the microtubule network

The commonly recognized mechanisms for spatial regulation inside the cell are membrane-bounded compartmentalization and biochemical association with subcellular organelles. We use computational modeling to investigate another spatial regulation mechanism mediated by the microtubule network in the cell. Our results demonstrate that the mitotic spindle can impose strong sequestration and concentration effects on molecules with binding affinity for microtubules, especially dynein-directed cargoes. The model can recapitulate the essence of three experimental observations on distinct microtubule network morphologies: the sequestration of germ plasm components by the mitotic spindles in the Drosophila syncytial embryo, the asymmetric cell division initiated by the time delay in centrosome maturation in the Drosophila neuroblast, and the diffusional block between neighboring energids in the Drosophila syncytial embryo. Our model thus suggests that the cell cycle-dependent changes in the microtubule network are critical for achieving different spatial regulation effects. The microtubule network provides a spatially extensive docking platform for molecules and gives rise to a "structured cytoplasm", in contrast to a free and fluid environment.     

Long-Term Dynamical Constraints on Pharmacologically Evoked Potentiation Imply Activity Conservation within In Vitro Hippocampal Networks

This paper describes a long-term study of network dynamics from in vitro, cultured hippocampal neurons after a pharmacological induction of synaptic potentiation. We plate a suspension of hippocampal neurons on an array of extracellular electrodes and record electrical activity in the absence of the drugs several days after treatment. While previous studies have reported on potentiation lasting up to a few hours after treatment, to the best of our knowledge, this is the first report to characterize the network effects of a potentiating mechanism several days after treatment. Using this reduced, two-dimensional in vitro network of hippocampal neurons, we show that the effects of potentiation are persistent over time but are modulated under a conservation of spike principle. We suggest that this conservation principle might be mediated by the appearance of a resonant inter-spike interval that prevents the network from advancing towards a state of hyperexcitability.     

Acetylcholine and associative memory in the piriform cortex

The significance of cholinergic modulation for associative memory performance in the piriform cortex was examined in a study combining cellular neurophysiology in brain slices with realistic biophysical network simulations. Three different physiological effects of acetylcholine were identified at the single-cell level: suppression of neuronal adaptation, suppression of synaptic transmission in the intrinsic fibers layer, and activity-dependent increase in synaptic strength. Biophysical simulations show how these three effects are joined together to enhance learning and recall performance of the cortical network. Furthermore, our data suggest that activity-dependent synaptic decay during learning is a crucial factor in determining learning capability of the cortical network. Accordingly, it is predicted that acetylcholine should also enhance long-term depression in the piriform cortex.     

Using HIV transmission networks to investigate community effects in HIV prevention trials

Effective population screening of HIV and prevention of HIV transmission are only part of the global fight against AIDS. Community-level effects, for example those aimed at thwarting future transmission, are potential outcomes of treatment and may be important in stemming the epidemic. However, current clinical trial designs are incapable of detecting a reduction in future transmission due to treatment. We took advantage of the fact that HIV is an evolving pathogen whose transmission network can be reconstructed using genetic sequence information to address this shortcoming. Here, we use an HIV transmission network inferred from recently infected men who have sex with men (MSM) in San Diego, California. We developed and tested a network-based statistic for measuring treatment effects using simulated clinical trials on our inferred transmission network. We explored the statistical power of this network-based statistic against conventional efficacy measures and find that when future transmission is reduced, the potential for increased statistical power can be realized. Furthermore, our simulations demonstrate that the network statistic is able to detect community-level effects (e.g., reduction in onward transmission) of HIV treatment in a clinical trial setting. This study demonstrates the potential utility of a network-based statistical metric when investigating HIV treatment options as a method to reduce onward transmission in a clinical trial setting.