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Sample records for network cortical simulation

  1. Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures

    PubMed Central

    Miner, Daniel C.; Triesch, Jochen

    2014-01-01

    The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results. PMID:25414647

  2. Region-specific network plasticity in simulated and living cortical networks: comparison of the center of activity trajectory (CAT) with other statistics

    NASA Astrophysics Data System (ADS)

    Chao, Zenas C.; Bakkum, Douglas J.; Potter, Steve M.

    2007-09-01

    Electrically interfaced cortical networks cultured in vitro can be used as a model for studying the network mechanisms of learning and memory. Lasting changes in functional connectivity have been difficult to detect with extracellular multi-electrode arrays using standard firing rate statistics. We used both simulated and living networks to compare the ability of various statistics to quantify functional plasticity at the network level. Using a simulated integrate-and-fire neural network, we compared five established statistical methods to one of our own design, called center of activity trajectory (CAT). CAT, which depicts dynamics of the location-weighted average of spatiotemporal patterns of action potentials across the physical space of the neuronal circuitry, was the most sensitive statistic for detecting tetanus-induced plasticity in both simulated and living networks. By reducing the dimensionality of multi-unit data while still including spatial information, CAT allows efficient real-time computation of spatiotemporal activity patterns. Thus, CAT will be useful for studies in vivo or in vitro in which the locations of recording sites on multi-electrode probes are important.

  3. Brainlab: A Python Toolkit to Aid in the Design, Simulation, and Analysis of Spiking Neural Networks with the NeoCortical Simulator.

    PubMed

    Drewes, Rich; Zou, Quan; Goodman, Philip H

    2009-01-01

    Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading "glue" tool for managing all sorts of complex programmatic tasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS (NeoCortical Simulator) environment in particular. Brainlab is an integrated model-building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS.

  4. Mapping cortical mesoscopic networks of single spiking cortical or sub-cortical neurons.

    PubMed

    Xiao, Dongsheng; Vanni, Matthieu P; Mitelut, Catalin C; Chan, Allen W; LeDue, Jeffrey M; Xie, Yicheng; Chen, Andrew Cn; Swindale, Nicholas V; Murphy, Timothy H

    2017-02-04

    Understanding the basis of brain function requires knowledge of cortical operations over wide-spatial scales, but also within the context of single neurons. In vivo, wide-field GCaMP imaging and sub-cortical/cortical cellular electrophysiology were used in mice to investigate relationships between spontaneous single neuron spiking and mesoscopic cortical activity. We make use of a rich set of cortical activity motifs that are present in spontaneous activity in anesthetized and awake animals. A mesoscale spike-triggered averaging procedure allowed the identification of motifs that are preferentially linked to individual spiking neurons by employing genetically targeted indicators of neuronal activity. Thalamic neurons predicted and reported specific cycles of wide-scale cortical inhibition/excitation. In contrast, spike-triggered maps derived from single cortical neurons yielded spatio-temporal maps expected for regional cortical consensus function. This approach can define network relationships between any point source of neuronal spiking and mesoscale cortical maps.

  5. Large-scale cortical networks and cognition.

    PubMed

    Bressler, S L

    1995-03-01

    The well-known parcellation of the mammalian cerebral cortex into a large number of functionally distinct cytoarchitectonic areas presents a problem for understanding the complex cortical integrative functions that underlie cognition. How do cortical areas having unique individual functional properties cooperate to accomplish these complex operations? Do neurons distributed throughout the cerebral cortex act together in large-scale functional assemblages? This review examines the substantial body of evidence supporting the view that complex integrative functions are carried out by large-scale networks of cortical areas. Pathway tracing studies in non-human primates have revealed widely distributed networks of interconnected cortical areas, providing an anatomical substrate for large-scale parallel processing of information in the cerebral cortex. Functional coactivation of multiple cortical areas has been demonstrated by neurophysiological studies in non-human primates and several different cognitive functions have been shown to depend on multiple distributed areas by human neuropsychological studies. Electrophysiological studies on interareal synchronization have provided evidence that active neurons in different cortical areas may become not only coactive, but also functionally interdependent. The computational advantages of synchronization between cortical areas in large-scale networks have been elucidated by studies using artificial neural network models. Recent observations of time-varying multi-areal cortical synchronization suggest that the functional topology of a large-scale cortical network is dynamically reorganized during visuomotor behavior.

  6. Mapping cortical mesoscopic networks of single spiking cortical or sub-cortical neurons

    PubMed Central

    Xiao, Dongsheng; Vanni, Matthieu P; Mitelut, Catalin C; Chan, Allen W; LeDue, Jeffrey M; Xie, Yicheng; Chen, Andrew CN; Swindale, Nicholas V; Murphy, Timothy H

    2017-01-01

    Understanding the basis of brain function requires knowledge of cortical operations over wide-spatial scales, but also within the context of single neurons. In vivo, wide-field GCaMP imaging and sub-cortical/cortical cellular electrophysiology were used in mice to investigate relationships between spontaneous single neuron spiking and mesoscopic cortical activity. We make use of a rich set of cortical activity motifs that are present in spontaneous activity in anesthetized and awake animals. A mesoscale spike-triggered averaging procedure allowed the identification of motifs that are preferentially linked to individual spiking neurons by employing genetically targeted indicators of neuronal activity. Thalamic neurons predicted and reported specific cycles of wide-scale cortical inhibition/excitation. In contrast, spike-triggered maps derived from single cortical neurons yielded spatio-temporal maps expected for regional cortical consensus function. This approach can define network relationships between any point source of neuronal spiking and mesoscale cortical maps. DOI: http://dx.doi.org/10.7554/eLife.19976.001 PMID:28160463

  7. Selective adaptation in networks of cortical neurons.

    PubMed

    Eytan, Danny; Brenner, Naama; Marom, Shimon

    2003-10-15

    A key property of neural systems is their ability to adapt selectively to stimuli with different features. Using multisite electrical recordings from networks of cortical neurons developing ex vivo, we show that neurons adapt selectively to different stimuli invading the network. We focus on selective adaptation to frequent and rare stimuli; networks were stimulated at two sites with two different stimulus frequencies. When both stimuli were presented within the same period, neurons in the network attenuated their responsiveness to the more frequent input, whereas their responsiveness to the rarely delivered stimuli showed a marked average increase. The amplification of the response to rare stimuli required the presence of the other, more frequent stimulation source. By contrast, the decreased response to the frequent stimuli occurred regardless of the presence of the rare stimuli. Analysis of the response of single units suggests that both of these effects are caused by changes in synaptic transmission. By using synaptic blockers, we find that the increased responsiveness to the rarely stimulated site depends specifically on fast GABAergic transmission. Thus, excitatory synaptic depression, the inhibitory sub-network, and their balance play an active role in generating selective gain control. The observation that selective adaptation arises naturally in a network of cortical neurons developing ex vivo indicates that this is an inherent feature of spontaneously organizing cortical networks.

  8. Relationships between cortical myeloarchitecture and electrophysiological networks

    PubMed Central

    Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Mougin, Olivier E.; Geades, Nicolas; Singh, Krish D.; Morris, Peter G.; Gowland, Penny A.; Brookes, Matthew J.

    2016-01-01

    The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poorly understood. Recent animal work has demonstrated that electrical activity promotes myelination. Inspired by this, we test a hypothesis that gray-matter myelin is related to electrophysiological connectivity. Using ultra-high field MRI and the principle of structural covariance, we derive a structural network showing how myelin density differs across cortical regions and how separate regions can exhibit similar myeloarchitecture. Building upon recent evidence that neural oscillations mediate connectivity, we use magnetoencephalography to elucidate networks that represent the major electrophysiological pathways of communication in the brain. Finally, we show that a significant relationship exists between our functional and structural networks; this relationship differs as a function of neural oscillatory frequency and becomes stronger when integrating oscillations over frequency bands. Our study sheds light on the way in which cortical microstructure supports functional networks. Further, it paves the way for future investigations of the gray-matter structure/function relationship and its breakdown in pathology. PMID:27830650

  9. Parcellating cortical functional networks in individuals.

    PubMed

    Wang, Danhong; Buckner, Randy L; Fox, Michael D; Holt, Daphne J; Holmes, Avram J; Stoecklein, Sophia; Langs, Georg; Pan, Ruiqi; Qian, Tianyi; Li, Kuncheng; Baker, Justin T; Stufflebeam, Steven M; Wang, Kai; Wang, Xiaomin; Hong, Bo; Liu, Hesheng

    2015-12-01

    The capacity to identify the unique functional architecture of an individual's brain is a crucial step toward personalized medicine and understanding the neural basis of variation in human cognition and behavior. Here we developed a cortical parcellation approach to accurately map functional organization at the individual level using resting-state functional magnetic resonance imaging (fMRI). A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types, including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting potential for use in clinical applications.

  10. Parcellating Cortical Functional Networks in Individuals

    PubMed Central

    Wang, Danhong; Buckner, Randy L.; Fox, Michael D.; Holt, Daphne J.; Holmes, Avram J.; Stoecklein, Sophia; Langs, Georg; Pan, Ruiqi; Qian, Tianyi; Li, Kuncheng; Baker, Justin T.; Stufflebeam, Steven M.; Wang, Kai; Wang, Xiaomin; Hong, Bo; Liu, Hesheng

    2015-01-01

    The capacity to identify the unique functional architecture of an individual’s brain is a critical step towards personalized medicine and understanding the neural basis of variations in human cognition and behavior. Here, we developed a novel cortical parcellation approach to accurately map functional organization at the individual level using resting-state fMRI. A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting great potential for use in clinical applications. PMID:26551545

  11. Cortical Resonance Frequencies Emerge from Network Size and Connectivity

    PubMed Central

    Lea-Carnall, Caroline A.; Montemurro, Marcelo A.; Trujillo-Barreto, Nelson J.; Parkes, Laura M.; El-Deredy, Wael

    2016-01-01

    Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emergent property of the networks that interconnect them. Using a network model of loosely-coupled Wilson-Cowan oscillators to simulate a patch of cortical sheet, we demonstrate that the size of the activated network is inversely related to its resonance frequency. Further analysis of the parameter space indicated that the number of excitatory and inhibitory connections, as well as the average transmission delay between units, determined the resonance frequency. The model predicted that if an activated network within the visual cortex increased in size, the resonance frequency of the network would decrease. We tested this prediction experimentally using the steady-state visual evoked potential where we stimulated the visual cortex with different size stimuli at a range of driving frequencies. We demonstrate that the frequency corresponding to peak steady-state response inversely correlated with the size of the network. We conclude that although individual neurons possess resonance properties, oscillatory activity at the macroscopic level is strongly influenced by network interactions, and that the steady-state response can be used to investigate functional networks. PMID:26914905

  12. Functional calcium imaging in developing cortical networks.

    PubMed

    Dawitz, Julia; Kroon, Tim; Hjorth, J J Johannes; Meredith, Rhiannon M

    2011-10-22

    A hallmark pattern of activity in developing nervous systems is spontaneous, synchronized network activity. Synchronized activity has been observed in intact spinal cord, brainstem, retina, cortex and dissociated neuronal culture preparations. During periods of spontaneous activity, neurons depolarize to fire single or bursts of action potentials, activating many ion channels. Depolarization activates voltage-gated calcium channels on dendrites and spines that mediate calcium influx. Highly synchronized electrical activity has been measured from local neuronal networks using field electrodes. This technique enables high temporal sampling rates but lower spatial resolution due to integrated read-out of multiple neurons at one electrode. Single cell resolution of neuronal activity is possible using patch-clamp electrophysiology on single neurons to measure firing activity. However, the ability to measure from a network is limited to the number of neurons patched simultaneously, and typically is only one or two neurons. The use of calcium-dependent fluorescent indicator dyes has enabled the measurement of synchronized activity across a network of cells. This technique gives both high spatial resolution and sufficient temporal sampling to record spontaneous activity of the developing network. A key feature of newly-forming cortical and hippocampal networks during pre- and early postnatal development is spontaneous, synchronized neuronal activity (Katz & Shatz, 1996; Khaziphov & Luhmann, 2006). This correlated network activity is believed to be essential for the generation of functional circuits in the developing nervous system (Spitzer, 2006). In both primate and rodent brain, early electrical and calcium network waves are observed pre- and postnatally in vivo and in vitro (Adelsberger et al., 2005; Garaschuk et al., 2000; Lamblin et al., 1999). These early activity patterns, which are known to control several developmental processes including neuronal differentiation

  13. Serotonin modulation of cortical neurons and networks

    PubMed Central

    Celada, Pau; Puig, M. Victoria; Artigas, Francesc

    2013-01-01

    The serotonergic pathways originating in the dorsal and median raphe nuclei (DR and MnR, respectively) are critically involved in cortical function. Serotonin (5-HT), acting on postsynaptic and presynaptic receptors, is involved in cognition, mood, impulse control and motor functions by (1) modulating the activity of different neuronal types, and (2) varying the release of other neurotransmitters, such as glutamate, GABA, acetylcholine and dopamine. Also, 5-HT seems to play an important role in cortical development. Of all cortical regions, the frontal lobe is the area most enriched in serotonergic axons and 5-HT receptors. 5-HT and selective receptor agonists modulate the excitability of cortical neurons and their discharge rate through the activation of several receptor subtypes, of which the 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT3 subtypes play a major role. Little is known, however, on the role of other excitatory receptors moderately expressed in cortical areas, such as 5-HT2C, 5-HT4, 5-HT6, and 5-HT7. In vitro and in vivo studies suggest that 5-HT1A and 5-HT2A receptors are key players and exert opposite effects on the activity of pyramidal neurons in the medial prefrontal cortex (mPFC). The activation of 5-HT1A receptors in mPFC hyperpolarizes pyramidal neurons whereas that of 5-HT2A receptors results in neuronal depolarization, reduction of the afterhyperpolarization and increase of excitatory postsynaptic currents (EPSCs) and of discharge rate. 5-HT can also stimulate excitatory (5-HT2A and 5-HT3) and inhibitory (5-HT1A) receptors in GABA interneurons to modulate synaptic GABA inputs onto pyramidal neurons. Likewise, the pharmacological manipulation of various 5-HT receptors alters oscillatory activity in PFC, suggesting that 5-HT is also involved in the control of cortical network activity. A better understanding of the actions of 5-HT in PFC may help to develop treatments for mood and cognitive disorders associated with an abnormal function of the frontal lobe

  14. Serotonin modulation of cortical neurons and networks.

    PubMed

    Celada, Pau; Puig, M Victoria; Artigas, Francesc

    2013-01-01

    The serotonergic pathways originating in the dorsal and median raphe nuclei (DR and MnR, respectively) are critically involved in cortical function. Serotonin (5-HT), acting on postsynaptic and presynaptic receptors, is involved in cognition, mood, impulse control and motor functions by (1) modulating the activity of different neuronal types, and (2) varying the release of other neurotransmitters, such as glutamate, GABA, acetylcholine and dopamine. Also, 5-HT seems to play an important role in cortical development. Of all cortical regions, the frontal lobe is the area most enriched in serotonergic axons and 5-HT receptors. 5-HT and selective receptor agonists modulate the excitability of cortical neurons and their discharge rate through the activation of several receptor subtypes, of which the 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT3 subtypes play a major role. Little is known, however, on the role of other excitatory receptors moderately expressed in cortical areas, such as 5-HT2C, 5-HT4, 5-HT6, and 5-HT7. In vitro and in vivo studies suggest that 5-HT1A and 5-HT2A receptors are key players and exert opposite effects on the activity of pyramidal neurons in the medial prefrontal cortex (mPFC). The activation of 5-HT1A receptors in mPFC hyperpolarizes pyramidal neurons whereas that of 5-HT2A receptors results in neuronal depolarization, reduction of the afterhyperpolarization and increase of excitatory postsynaptic currents (EPSCs) and of discharge rate. 5-HT can also stimulate excitatory (5-HT2A and 5-HT3) and inhibitory (5-HT1A) receptors in GABA interneurons to modulate synaptic GABA inputs onto pyramidal neurons. Likewise, the pharmacological manipulation of various 5-HT receptors alters oscillatory activity in PFC, suggesting that 5-HT is also involved in the control of cortical network activity. A better understanding of the actions of 5-HT in PFC may help to develop treatments for mood and cognitive disorders associated with an abnormal function of the frontal lobe.

  15. Characterization of Early Cortical Neural Network ...

    EPA Pesticide Factsheets

    We examined the development of neural network activity using microelectrode array (MEA) recordings made in multi-well MEA plates (mwMEAs) over the first 12 days in vitro (DIV). In primary cortical cultures made from postnatal rats, action potential spiking activity was essentially absent on DIV 2 and developed rapidly between DIV 5 and 12. Spiking activity was primarily sporadic and unorganized at early DIV, and became progressively more organized with time in culture, with bursting parameters, synchrony and network bursting increasing between DIV 5 and 12. We selected 12 features to describe network activity and principal components analysis using these features demonstrated a general segregation of data by age at both the well and plate levels. Using a combination of random forest classifiers and Support Vector Machines, we demonstrated that 4 features (CV of within burst ISI, CV of IBI, network spike rate and burst rate) were sufficient to predict the age (either DIV 5, 7, 9 or 12) of each well recording with >65% accuracy. When restricting the classification problem to a binary decision, we found that classification improved dramatically, e.g. 95% accuracy for discriminating DIV 5 vs DIV 12 wells. Further, we present a novel resampling approach to determine the number of wells that might be needed for conducting comparisons of different treatments using mwMEA plates. Overall, these results demonstrate that network development on mwMEA plates is similar to

  16. Cortical Network for Reading Linear Words in an Alphasyllabary

    ERIC Educational Resources Information Center

    Das, Tanusree; Bapi, Raju S.; Padakannaya, Prakash; Singh, Nandini C.

    2011-01-01

    Functional imaging studies have established cortical networks for reading alphabetic, syllabic and logographic scripts. There is little information about the different cortical areas that participate in reading an alphasyllabary. We use functional brain imaging to study the reading network for Devanagari, an alphasyllabary. Similar to syllabic…

  17. Biophysical Model of Cortical Network Activity and the Influence of Electrical Stimulation

    DTIC Science & Technology

    2015-11-13

    parameters for seizure disruption using neural network simulations, Biological Cybernetics (08 2007) W.S. Anderson, P. Kudela, S. Weinberg, G.K...Bergey, P.J. Franaszczuk. Phase-dependent stimulation effects on bursting activity in a neural network cortical simulation, Epilepsy Research (07 2008...Epilepsy Research (06 2011) WS Anderson, F Azhar. Predicting Single-Neuron Activity in Locally Connected Networks , Neural Computation (05 2011

  18. The Convallis Rule for Unsupervised Learning in Cortical Networks

    PubMed Central

    Yger, Pierre; Harris, Kenneth D.

    2013-01-01

    The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the “Convallis rule”, mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex. PMID:24204224

  19. Emergence of Metastable State Dynamics in Interconnected Cortical Networks with Propagation Delays

    PubMed Central

    Kutchko, Katrina M.; Fröhlich, Flavio

    2013-01-01

    The importance of the large number of thin-diameter and unmyelinated axons that connect different cortical areas is unknown. The pronounced propagation delays in these axons may prevent synchronization of cortical networks and therefore hinder efficient information integration and processing. Yet, such global information integration across cortical areas is vital for higher cognitive function. We hypothesized that delays in communication between cortical areas can disrupt synchronization and therefore enhance the set of activity trajectories and computations interconnected networks can perform. To evaluate this hypothesis, we studied the effect of long-range cortical projections with propagation delays in interconnected large-scale cortical networks that exhibited spontaneous rhythmic activity. Long-range connections with delays caused the emergence of metastable, spatio-temporally distinct activity states between which the networks spontaneously transitioned. Interestingly, the observed activity patterns correspond to macroscopic network dynamics such as globally synchronized activity, propagating wave fronts, and spiral waves that have been previously observed in neurophysiological recordings from humans and animal models. Transient perturbations with simulated transcranial alternating current stimulation (tACS) confirmed the multistability of the interconnected networks by switching the networks between these metastable states. Our model thus proposes that slower long-range connections enrich the landscape of activity states and represent a parsimonious mechanism for the emergence of multistability in cortical networks. These results further provide a mechanistic link between the known deficits in connectivity and cortical state dynamics in neuropsychiatric illnesses such as schizophrenia and autism, as well as suggest non-invasive brain stimulation as an effective treatment for these illnesses. PMID:24204238

  20. Simulating Cortical Feedback Modulation as Changes in Excitation and Inhibition in a Cortical Circuit Model

    PubMed Central

    Murray, John D.; McCormick, David A.

    2016-01-01

    Abstract Cortical feedback pathways are hypothesized to distribute context-dependent signals during flexible behavior. Recent experimental work has attempted to understand the mechanisms by which cortical feedback inputs modulate their target regions. Within the mouse whisker sensorimotor system, cortical feedback stimulation modulates spontaneous activity and sensory responsiveness, leading to enhanced sensory representations. However, the cellular mechanisms underlying these effects are currently unknown. In this study we use a simplified neural circuit model, which includes two recurrent excitatory populations and global inhibition, to simulate cortical modulation. First, we demonstrate how changes in the strengths of excitation and inhibition alter the input–output processing responses of our model. Second, we compare these responses with experimental findings from cortical feedback stimulation. Our analyses predict that enhanced inhibition underlies the changes in spontaneous and sensory evoked activity observed experimentally. More generally, these analyses provide a framework for relating cellular and synaptic properties to emergent circuit function and dynamic modulation. PMID:27595137

  1. Damselfly Network Simulator

    SciTech Connect

    2014-04-01

    Damselfly is a model-based parallel network simulator. It can simulate communication patterns of High Performance Computing applications on different network topologies. It outputs steady-state network traffic for a communication pattern, which can help in studying network congestion and its impact on performance.

  2. Cortical Networks for Visual Self-Recognition

    NASA Astrophysics Data System (ADS)

    Sugiura, Motoaki

    This paper briefly reviews recent developments regarding the brain mechanisms of visual self-recognition. A special cognitive mechanism for visual self-recognition has been postulated based on behavioral and neuropsychological evidence, but its neural substrate remains controversial. Recent functional imaging studies suggest that multiple cortical mechanisms play self-specific roles during visual self-recognition, reconciling the existing controversy. Respective roles for the left occipitotemporal, right parietal, and frontal cortices in symbolic, visuospatial, and conceptual aspects of self-representation have been proposed.

  3. Cortical network architecture for context processing in primate brain

    PubMed Central

    Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

    2015-01-01

    Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition. DOI: http://dx.doi.org/10.7554/eLife.06121.001 PMID:26416139

  4. Hierarchical Organization of Human Cortical Networks in Health and Schizophrenia

    PubMed Central

    Bassett, Danielle S.; Bullmore, Edward; Verchinski, Beth A.; Mattay, Venkata S.; Weinberger, Daniel R.; Meyer-Lindenberg, Andreas

    2009-01-01

    The complex organization of connectivity in the human brain is incompletely understood. Recently, topological measures based on graph theory have provided a new approach to quantify large-scale cortical networks. These methods have been applied to anatomical connectivity data on non-human species and cortical networks have been shown to have small-world topology, associated with high local and global efficiency of information transfer. Anatomical networks derived from cortical thickness measurements have shown the same organizational properties of the healthy human brain, consistent with similar results reported in functional networks derived from resting state functional MRI and MEG data. Here we show, using anatomical networks derived from analysis of inter-regional covariation of gray matter volume in magnetic resonance imaging (MRI) data on 259 healthy volunteers, that classical divisions of cortex (multimodal, unimodal and transmodal) have some distinct topological attributes. While all cortical divisions shared non-random properties of small-worldness and efficient wiring (short mean Euclidean distance between connected regions), the multimodal network had a hierarchical organization, dominated by frontal hubs with low clustering, whereas the transmodal network was assortative. Moreover, in a sample of 203 people with schizophrenia, multimodal network organization was abnormal, as indicated by reduced hierarchy, the loss of frontal and the emergence of non-frontal hubs, and increased connection distance. We propose that the topological differences between divisions of normal cortex may represent the outcome of different growth processes for multimodal and transmodal networks; and that neurodevelopmental abnormalities in schizophrenia specifically impact multimodal cortical organization. PMID:18784304

  5. Tagging cortical networks in emotion: a topographical analysis

    PubMed Central

    Keil, Andreas; Costa, Vincent; Smith, J. Carson; Sabatinelli, Dean; McGinnis, E. Menton; Bradley, Margaret M.; Lang, Peter J.

    2013-01-01

    Viewing emotional pictures is associated with heightened perception and attention, indexed by a relative increase in visual cortical activity. Visual cortical modulation by emotion is hypothesized to reflect re-entrant connectivity originating in higher-order cortical and/or limbic structures. The present study used dense-array electroencephalography and individual brain anatomy to investigate functional coupling between the visual cortex and other cortical areas during affective picture viewing. Participants viewed pleasant, neutral, and unpleasant pictures that flickered at a rate of 10 Hz to evoke steady-state visual evoked potentials (ssVEPs) in the EEG. The spectral power of ssVEPs was quantified using Fourier transform, and cortical sources were estimated using beamformer spatial filters based on individual structural magnetic resonance images. In addition to lower-tier visual cortex, a network of occipito-temporal and parietal (bilateral precuneus, inferior parietal lobules) structures showed enhanced ssVEP power when participants viewed emotional (either pleasant or unpleasant), compared to neutral pictures. Functional coupling during emotional processing was enhanced between the bilateral occipital poles and a network of temporal (left middle/inferior temporal gyrus), parietal (bilateral parietal lobules), and frontal (left middle/inferior frontal gyrus) structures. These results converge with findings from hemodynamic analyses of emotional picture viewing and suggest that viewing emotionally engaging stimuli is associated with the formation of functional links between visual cortex and the cortical regions underlying attention modulation and preparation for action. PMID:21954087

  6. CAISSON: Interconnect Network Simulator

    NASA Technical Reports Server (NTRS)

    Springer, Paul L.

    2006-01-01

    Cray response to HPCS initiative. Model future petaflop computer interconnect. Parallel discrete event simulation techniques for large scale network simulation. Built on WarpIV engine. Run on laptop and Altix 3000. Can be sized up to 1000 simulated nodes per host node. Good parallel scaling characteristics. Flexible: multiple injectors, arbitration strategies, queue iterators, network topologies.

  7. Dynamic functional tuning of nonlinear cortical networks

    NASA Astrophysics Data System (ADS)

    Stetter, Martin

    2006-03-01

    The mammalian neocortex is a highly complex and nonlinear dynamic system. One of its most prominent features is an omnipresent spontaneous neuronal activity. Here the possible functional role of this global background for cognitive flexibility is studied in a prototypic mean-field model area. It is demonstrated that the level of global background current efficiently controls the stimulus-response threshold and the stability and properties of short-term memory states. Moreover, it can dynamically gate arbitrary cortical subnetworks, when applied to parts of the area as a weak bias signal. These results suggest a central functional role of the level of background activation: the dynamic functional tuning of neocortical circuits.

  8. Locus coeruleus stimulation recruits a broad cortical neuronal network and increases cortical perfusion.

    PubMed

    Toussay, Xavier; Basu, Kaustuv; Lacoste, Baptiste; Hamel, Edith

    2013-02-20

    The locus coeruleus (LC), the main source of brain noradrenalin (NA), modulates cortical activity, cerebral blood flow (CBF), glucose metabolism, and blood-brain barrier permeability. However, the role of the LC-NA system in the regulation of cortical CBF has remained elusive. This rat study shows that similar proportions (∼20%) of cortical pyramidal cells and GABA interneurons are contacted by LC-NA afferents on their cell soma or proximal dendrites. LC stimulation induced ipsilateral activation (c-Fos upregulation) of pyramidal cells and of a larger proportion (>36%) of interneurons that colocalize parvalbumin, somatostatin, or nitric oxide synthase compared with pyramidal cells expressing cyclooxygenase-2 (22%, p < 0.05) or vasoactive intestinal polypeptide-containing interneurons (16%, p < 0.01). Concurrently, LC stimulation elicited larger ipsilateral compared with contralateral increases in cortical CBF (52 vs 31%, p < 0.01). These CBF responses were almost abolished (-70%, p < 0.001) by cortical NA denervation with DSP-4 [N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine hydrochloride] and were significantly reduced by α- and β-adrenoceptor antagonists (-40%, p < 0.001 and -30%, p < 0.05, respectively). Blockade of glutamatergic or GABAergic neurotransmission with NMDA or GABA(A) receptor antagonists potently reduced the LC-induced hyperemic response (-56%, p < 0.001 or -47%, p < 0.05). Moreover, inhibition of astroglial metabolism (-35%, p < 0.01), vasoactive epoxyeicosatrienoic acids (EETs; -60%, p < 0.001) synthesis, large-conductance, calcium-operated (BK, -52%, p < 0.05), and inward-rectifier (Kir, -40%, p < 0.05) K+ channels primarily impaired the hyperemic response. The data demonstrate that LC stimulation recruits a broad network of cortical excitatory and inhibitory neurons resulting in increased cortical activity and that K+ fluxes and EET signaling mediate a large part of the hemodynamic response.

  9. Speech perception: linking comprehension across a cortical network.

    PubMed

    Ghazanfar, Asif A; Pinsk, Mark A

    2007-06-05

    Listening to speech amidst noise is facilitated by a variety of cues, including the predictable use of certain words in certain contexts. A recent fMRI study of the interaction between noise and semantic predictability has identified a cortical network involved in speech comprehension.

  10. Mapping human brain networks with cortico-cortical evoked potentials.

    PubMed

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

    2014-10-05

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

  11. Mapping human brain networks with cortico-cortical evoked potentials

    PubMed Central

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

    2014-01-01

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

  12. The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks.

    PubMed

    Landau, Itamar D; Egger, Robert; Dercksen, Vincent J; Oberlaender, Marcel; Sompolinsky, Haim

    2016-12-07

    Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits.

  13. Plasticity of recurring spatiotemporal activity patterns in cortical networks

    NASA Astrophysics Data System (ADS)

    Madhavan, Radhika; Chao, Zenas C.; Potter, Steve M.

    2007-09-01

    How do neurons encode and store information for long periods of time? Recurring patterns of activity have been reported in various cortical structures and were suggested to play a role in information processing and memory. To study the potential role of bursts of action potentials in memory mechanisms, we investigated patterns of spontaneous multi-single-unit activity in dissociated rat cortical cultures in vitro. Spontaneous spikes were recorded from networks of approximately 50 000 neurons and glia cultured on a grid of 60 extracellular substrate- embedded electrodes (multi-electrode arrays). These networks expressed spontaneous culture- wide bursting from approximately one week in vitro. During bursts, a large portion of the active electrodes showed elevated levels of firing. Spatiotemporal activity patterns within spontaneous bursts were clustered using a correlation-based clustering algorithm, and the occurrences of these burst clusters were tracked over several hours. This analysis revealed spatiotemporally diverse bursts occurring in well-defined patterns, which remained stable for several hours. Activity evoked by strong local tetanic stimulation resulted in significant changes in the occurrences of spontaneous bursts belonging to different clusters, indicating that the dynamical flow of information in the neuronal network had been altered. The diversity of spatiotemporal structure and long-term stability of spontaneous bursts together with their plastic nature strongly suggests that such network patterns could be used as codes for information transfer and the expression of memories stored in cortical networks.

  14. Time-course of cortical networks involved in working memory

    PubMed Central

    Luu, Phan; Caggiano, Daniel M.; Geyer, Alexandra; Lewis, Jenn; Cohn, Joseph; Tucker, Don M.

    2014-01-01

    Working memory (WM) is one of the most studied cognitive constructs. Although many neuroimaging studies have identified brain networks involved in WM, the time course of these networks remains unclear. In this paper we use dense-array electroencephalography (dEEG) to capture neural signals during performance of a standard WM task, the n-back task, and a blend of principal components analysis and independent components analysis (PCA/ICA) to statistically identify networks of WM and their time courses. Results reveal a visual cortex centric network, that also includes the posterior cingulate cortex, that is active prior to stimulus onset and that appears to reflect anticipatory, attention-related processes. After stimulus onset, the ventromedial prefrontal cortex, lateral prefrontal prefrontal cortex, and temporal poles become associated with the prestimulus network. This second network appears to reflect executive control processes. Following activation of the second network, the cortices of the temporo-parietal junction with the temporal lobe structures seen in the first and second networks re-engage. This third network appears to reflect activity of the ventral attention network involved in control of attentional reorientation. The results point to important temporal features of network dynamics that integrate multiple subsystems of the ventral attention network with the default mode network in the performance of working memory tasks. PMID:24523686

  15. Cortical Hubs Form a Module for Multisensory Integration on Top of the Hierarchy of Cortical Networks

    PubMed Central

    Zamora-López, Gorka; Zhou, Changsong; Kurths, Jürgen

    2009-01-01

    Sensory stimuli entering the nervous system follow particular paths of processing, typically separated (segregated) from the paths of other modal information. However, sensory perception, awareness and cognition emerge from the combination of information (integration). The corticocortical networks of cats and macaque monkeys display three prominent characteristics: (i) modular organisation (facilitating the segregation), (ii) abundant alternative processing paths and (iii) the presence of highly connected hubs. Here, we study in detail the organisation and potential function of the cortical hubs by graph analysis and information theoretical methods. We find that the cortical hubs form a spatially delocalised, but topologically central module with the capacity to integrate multisensory information in a collaborative manner. With this, we resolve the underlying anatomical substrate that supports the simultaneous capacity of the cortex to segregate and to integrate multisensory information. PMID:20428515

  16. Cortical hubs form a module for multisensory integration on top of the hierarchy of cortical networks.

    PubMed

    Zamora-López, Gorka; Zhou, Changsong; Kurths, Jürgen

    2010-01-01

    Sensory stimuli entering the nervous system follow particular paths of processing, typically separated (segregated) from the paths of other modal information. However, sensory perception, awareness and cognition emerge from the combination of information (integration). The corticocortical networks of cats and macaque monkeys display three prominent characteristics: (i) modular organisation (facilitating the segregation), (ii) abundant alternative processing paths and (iii) the presence of highly connected hubs. Here, we study in detail the organisation and potential function of the cortical hubs by graph analysis and information theoretical methods. We find that the cortical hubs form a spatially delocalised, but topologically central module with the capacity to integrate multisensory information in a collaborative manner. With this, we resolve the underlying anatomical substrate that supports the simultaneous capacity of the cortex to segregate and to integrate multisensory information.

  17. Stable propagation of synchronous spiking in cortical neural networks

    NASA Astrophysics Data System (ADS)

    Diesmann, Markus; Gewaltig, Marc-Oliver; Aertsen, Ad

    1999-12-01

    The classical view of neural coding has emphasized the importance of information carried by the rate at which neurons discharge action potentials. More recent proposals that information may be carried by precise spike timing have been challenged by the assumption that these neurons operate in a noisy fashion-presumably reflecting fluctuations in synaptic input-and, thus, incapable of transmitting signals with millisecond fidelity. Here we show that precisely synchronized action potentials can propagate within a model of cortical network activity that recapitulates many of the features of biological systems. An attractor, yielding a stable spiking precision in the (sub)millisecond range, governs the dynamics of synchronization. Our results indicate that a combinatorial neural code, based on rapid associations of groups of neurons co-ordinating their activity at the single spike level, is possible within a cortical-like network.

  18. Cortical deactivation induced by subcortical network dysfunction in limbic seizures

    PubMed Central

    Englot, Dario J.; Modi, Badri; Mishra, Asht M.; DeSalvo, Matthew; Hyder, Fahmeed; Blumenfeld, Hal

    2009-01-01

    Normal human consciousness may be impaired by two possible routes: direct reduced function in widespread cortical regions, or indirect disruption of subcortical activating systems. The route through which temporal lobe limbic seizures impair consciousness is not known. We recently developed an animal model which, like human limbic seizures, exhibits neocortical deactivation including cortical slow waves and reduced cortical cerebral blood flow (CBF). We now find through functional MRI (fMRI) that electrically-stimulated hippocampal seizures in rats cause increased activity in subcortical structures including the septal area and mediodorsal thalamus, along with reduced activity in frontal, cingulate, and retrosplenial cortex. Direct recordings from the hippocampus, septum, and medial thalamus demonstrated fast poly-spike activity associated with increased neuronal firing and CBF, while frontal cortex showed slow oscillations with decreased neuronal firing and CBF. Stimulation of septal area, but not hippocampus or medial thalamus, in the absence of a seizure resulted in cortical deactivation with slow oscillations and behavioral arrest, resembling changes seen during limbic seizures. Transecting the fornix, the major route from hippocampus to subcortical structures, abolished the negative cortical and behavioral effects of seizures. Cortical slow oscillations and behavioral arrest could be reconstituted in fornix-lesioned animals by inducing synchronous activity in the hippocampus and septal area, implying involvement of a downstream region converged upon by both structures. These findings suggest that limbic seizures may cause neocortical deactivation indirectly, through impaired subcortical function. If confirmed, subcortical networks may represent a target for therapies aimed at preserving consciousness in human temporal lobe seizures. PMID:19828814

  19. Pyramidal Neurons Are Not Generalizable Building Blocks of Cortical Networks

    PubMed Central

    Luebke, Jennifer I.

    2017-01-01

    A key challenge in cortical neuroscience is to gain a comprehensive understanding of how pyramidal neuron heterogeneity across different areas and species underlies the functional specialization of individual neurons, networks, and areas. Comparative studies have been important in this endeavor, providing data relevant to the question of which of the many inherent properties of individual pyramidal neurons are necessary and sufficient for species-specific network and areal function. In this mini review, the importance of pyramidal neuron structural properties for signaling are outlined, followed by a summary of our recent work comparing the structural features of mouse (C57/BL6 strain) and rhesus monkey layer 3 (L3) pyramidal neurons in primary visual and frontal association cortices and their implications for neuronal and areal function. Based on these and other published data, L3 pyramidal neurons plausibly might be considered broadly “generalizable” from one area to another in the mouse neocortex due to their many similarities, but major differences in the properties of these neurons in diverse areas in the rhesus monkey neocortex rules this out in the primate. Further, fundamental differences in the dendritic topology of mouse and rhesus monkey pyramidal neurons highlight the implausibility of straightforward scaling and/or extrapolation from mouse to primate neurons and cortical networks. PMID:28326020

  20. Self-organized criticality in cortical assemblies occurs in concurrent scale-free and small-world networks

    PubMed Central

    Massobrio, Paolo; Pasquale, Valentina; Martinoia, Sergio

    2015-01-01

    The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states. Although several attempts were accomplished to understand the origin of these dynamics, the underlying factors continue to be elusive. In this work, we specifically investigated the interplay between network topology and spontaneous dynamics within the framework of self-organized criticality (SOC). The obtained results support the hypothesis that the emergence of critical states occurs in specific complex network topologies. By combining multi-electrode recordings of spontaneous activity of in vitro cortical assemblies with theoretical models, we demonstrate that different ‘connectivity rules’ drive the network towards different dynamic states. In particular, scale-free architectures with different degree of small-worldness account better for the variability observed in experimental data, giving rise to different dynamic states. Moreover, in relationship with the balance between excitation and inhibition and percentage of inhibitory hubs, the simulated cortical networks fall in a critical regime. PMID:26030608

  1. Self-organized criticality in cortical assemblies occurs in concurrent scale-free and small-world networks.

    PubMed

    Massobrio, Paolo; Pasquale, Valentina; Martinoia, Sergio

    2015-06-01

    The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states. Although several attempts were accomplished to understand the origin of these dynamics, the underlying factors continue to be elusive. In this work, we specifically investigated the interplay between network topology and spontaneous dynamics within the framework of self-organized criticality (SOC). The obtained results support the hypothesis that the emergence of critical states occurs in specific complex network topologies. By combining multi-electrode recordings of spontaneous activity of in vitro cortical assemblies with theoretical models, we demonstrate that different 'connectivity rules' drive the network towards different dynamic states. In particular, scale-free architectures with different degree of small-worldness account better for the variability observed in experimental data, giving rise to different dynamic states. Moreover, in relationship with the balance between excitation and inhibition and percentage of inhibitory hubs, the simulated cortical networks fall in a critical regime.

  2. Spike phase synchronization in multiplex cortical neural networks

    NASA Astrophysics Data System (ADS)

    Jalili, Mahdi

    2017-01-01

    In this paper we study synchronizability of two multiplex cortical networks: whole-cortex of hermaphrodite C. elegans and posterior cortex in male C. elegans. These networks are composed of two connection layers: network of chemical synapses and the one formed by gap junctions. This work studies the contribution of each layer on the phase synchronization of non-identical spiking Hindmarsh-Rose neurons. The network of male C. elegans shows higher phase synchronization than its randomized version, while it is not the case for hermaphrodite type. The random networks in each layer are constructed such that the nodes have the same degree as the original network, thus providing an unbiased comparison. In male C. elegans, although the gap junction network is sparser than the chemical network, it shows higher contribution in the synchronization phenomenon. This is not the case in hermaphrodite type, which is mainly due to significant less density of gap junction layer (0.013) as compared to chemical layer (0.028). Also, the gap junction network in this type has stronger community structure than the chemical network, and this is another driving factor for its weaker synchronizability.

  3. Neural network model of cortical EEG response to olfactory stimuli

    NASA Astrophysics Data System (ADS)

    Dunbar, George L.; Van Toller, Steve

    1995-04-01

    We describe three experiments attempting to model differences in cortical EEG following stimulation with different odors. The data used in these experiments was obtained in previous studies, described briefly here. Subjects sit in an environmentally stabilized low odor cubicle. Twenty-eight electrodes are placed on the scalp and connect the subject to a neurosciences brain imager, which digitizes cortical EEG response. In a given trial, a specific odor is introduced, and the response recorded. In the first experiment, alpha wave data from a subset of ten electrodes and a single subject was used. In the original experiment, the subject was presented with a number of odors and the resulting brain electrical activity was resolved into 16 time slices (5 preceding presentation, 4 during presentation and 7 following presentation). Only data from frames 6, 7 and 8 (during presentation) was used here. A model was constructed to discriminate morning from afternoon responses. The network used measurements from 10 electrodes as input, and backpropagation was used for training. During training, the network was presented with responses to just one odor. Generalization was demonstrated for five other odors. The weights in the network have been analyzed and indicate a role for a specific group of electrode sites in this discrimination. The second experiment involved constructing a network to discriminate cortical EEG responses to two odors. In the original experiment from which we drew our data, fourteen subjects were presented with each odor once. Data from only the frame at first presentation of the odor were used here. Data from three subjects (chosen pseudo-randomly) was selected for use in the generalization phase and dropped from the training set. Output targets were constructed that took account of subjective ratings of `pleasantness.' A feed-forward network with twenty-eight input units was trained using data from the eleven remaining subjects, using conjugate gradient

  4. Prototyping distributed simulation networks

    NASA Technical Reports Server (NTRS)

    Doubleday, Dennis L.

    1990-01-01

    Durra is a declarative language designed to support application-level programming. The use of Durra is illustrated to describe a simple distributed application: a simulation of a collection of networked vehicle simulators. It is shown how the language is used to describe the application, its components and structure, and how the runtime executive provides for the execution of the application.

  5. The up and down states of cortical networks

    NASA Astrophysics Data System (ADS)

    Ghorbani, Maryam; Levine, Alex J.; Mehta, Mayank; Bruinsma, Robijn

    2011-03-01

    The cortical networks show a collective activity of alternating active and silent states known as up and down states during slow wave sleep or anesthesia. The mechanism of this spontaneous activity as well as the anesthesia or sleep are still not clear. Here, using a mean field approach, we present a simple model to study the spontaneous activity of a homogenous cortical network of excitatory and inhibitory neurons that are recurrently connected. A key new ingredient in this model is that the activity-dependant synaptic depression is considered only for the excitatory neurons. We find depending on the strength of the synaptic depression and synaptic efficacies, the phase space contains strange attractors or stable fixed points at active or quiescent regimes. At the strange attractor phase, we can have oscillations similar to up and down states with flat and noisy up states. Moreover, we show that by increasing the synaptic efficacy corresponding to the connections between the excitatory neurons, the characteristics of the up and down states change in agreement with the changes that we observe in the intracellular recordings of the membrane potential from the entorhinal cortex by varying the depth of anesthesia. Thus, we propose that by measuring the value of this synaptic efficacy, one can quantify the depth of anesthesia which is clinically very important. These findings provide a simple, analytical understanding of the spontaneous cortical dynamics.

  6. Spiking neural networks for cortical neuronal spike train decoding.

    PubMed

    Fang, Huijuan; Wang, Yongji; He, Jiping

    2010-04-01

    Recent investigation of cortical coding and computation indicates that temporal coding is probably a more biologically plausible scheme used by neurons than the rate coding used commonly in most published work. We propose and demonstrate in this letter that spiking neural networks (SNN), consisting of spiking neurons that propagate information by the timing of spikes, are a better alternative to the coding scheme based on spike frequency (histogram) alone. The SNN model analyzes cortical neural spike trains directly without losing temporal information for generating more reliable motor command for cortically controlled prosthetics. In this letter, we compared the temporal pattern classification result from the SNN approach with results generated from firing-rate-based approaches: conventional artificial neural networks, support vector machines, and linear regression. The results show that the SNN algorithm can achieve higher classification accuracy and identify the spiking activity related to movement control earlier than the other methods. Both are desirable characteristics for fast neural information processing and reliable control command pattern recognition for neuroprosthetic applications.

  7. Actin kinetics shapes cortical network structure and mechanics

    PubMed Central

    Fritzsche, Marco; Erlenkämper, Christoph; Moeendarbary, Emad; Charras, Guillaume; Kruse, Karsten

    2016-01-01

    The actin cortex of animal cells is the main determinant of cellular mechanics. The continuous turnover of cortical actin filaments enables cells to quickly respond to stimuli. Recent work has shown that most of the cortical actin is generated by only two actin nucleators, the Arp2/3 complex and the formin Diaph1. However, our understanding of their interplay, their kinetics, and the length distribution of the filaments that they nucleate within living cells is poor. Such knowledge is necessary for a thorough comprehension of cellular processes and cell mechanics from basic polymer physics principles. We determined cortical assembly rates in living cells by using single-molecule fluorescence imaging in combination with stochastic simulations. We find that formin-nucleated filaments are, on average, 10 times longer than Arp2/3-nucleated filaments. Although formin-generated filaments represent less than 10% of all actin filaments, mechanical measurements indicate that they are important determinants of cortical elasticity. Tuning the activity of actin nucleators to alter filament length distribution may thus be a mechanism allowing cells to adjust their macroscopic mechanical properties to their physiological needs. PMID:27152338

  8. Inhibitory control of correlated intrinsic variability in cortical networks

    PubMed Central

    Stringer, Carsen; Pachitariu, Marius; Steinmetz, Nicholas A; Okun, Michael; Bartho, Peter; Harris, Kenneth D; Sahani, Maneesh; Lesica, Nicholas A

    2016-01-01

    Cortical networks exhibit intrinsic dynamics that drive coordinated, large-scale fluctuations across neuronal populations and create noise correlations that impact sensory coding. To investigate the network-level mechanisms that underlie these dynamics, we developed novel computational techniques to fit a deterministic spiking network model directly to multi-neuron recordings from different rodent species, sensory modalities, and behavioral states. The model generated correlated variability without external noise and accurately reproduced the diverse activity patterns in our recordings. Analysis of the model parameters suggested that differences in noise correlations across recordings were due primarily to differences in the strength of feedback inhibition. Further analysis of our recordings confirmed that putative inhibitory neurons were indeed more active during desynchronized cortical states with weak noise correlations. Our results demonstrate that network models with intrinsically-generated variability can accurately reproduce the activity patterns observed in multi-neuron recordings and suggest that inhibition modulates the interactions between intrinsic dynamics and sensory inputs to control the strength of noise correlations. DOI: http://dx.doi.org/10.7554/eLife.19695.001 PMID:27926356

  9. Rich club neurons dominate Information Transfer in local cortical networks

    NASA Astrophysics Data System (ADS)

    Nigam, Sunny; Shimono, Masanori; Sporns, Olaf; Beggs, John

    2015-03-01

    The performance of complex networks depends on how they route their traffic. It is unknown how information is transferred in local cortical networks of hundreds of closely-spaced neurons. To address this, it is necessary to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512 electrode array (60 μm spacing) to record spontaneous activity at 20 kHz, simultaneously from up to 700 neurons in slice cultures of mouse somatosensory cortex for 1 hr at a time. We used transfer entropy to quantify directed information transfer (IT) between pairs of neurons. We found an approximately lognormal distribution of firing rates as reported in in-vivo. Pairwise information transfer strengths also were nearly lognormally distributed, similar to synaptic strengths. 20% of the neurons accounted for 70% of the total IT coming into, and going out of the network and were defined as rich nodes. These rich nodes were more densely and strongly connected to each other expected by chance, forming a rich club. This highly uneven distribution of IT has implications for the efficiency and robustness of local cortical networks, and gives clues to the plastic processes that shape them. JSPS.

  10. Functional cortical network in alpha band correlates with social bargaining.

    PubMed

    Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco

    2014-01-01

    Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals' alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts.

  11. Functional Cortical Network in Alpha Band Correlates with Social Bargaining

    PubMed Central

    Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco

    2014-01-01

    Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals’ alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts. PMID:25286240

  12. The Developmental Integration of Cortical Interneurons into a Functional Network

    PubMed Central

    Batista-Brito, Renata; Fishell, Gord

    2015-01-01

    The central goal of this manuscript is to survey our present knowledge of how cortical interneuron subtypes are generated. To achieve this, we will first define what is meant by subtype diversity. To this end, we begin by considering the mature properties that differentiate between the different populations of cortical interneurons. This requires us to address the difficulties involved in determining which characteristics allow particular interneurons to be assigned to distinct subclasses. Having grappled with this thorny issue, we will then proceed to review the progressive events in development involved in the generation of interneuron diversity. Starting with their origin and specification within the subpallium, we will follow them up through the first postnatal weeks during their integration into a functional network. Finally, we will conclude by calling the readers attention to the devastating consequences that result from developmental failures in the formation of inhibitory circuits within the cortex. PMID:19427517

  13. Roles of dynamic linkage of stable attractors across cortical networks in recalling long-term memory.

    PubMed

    Hoshino, Osamu; Zheng, MeiHong; Kuroiwa, Kazuharu

    2003-03-01

    We propose a neural network model for a category-association task. By simulating the model, neuronal relevance of cortical interactions to recalling long-term memory was investigated. The model consists of the left and right hemispheres, each of which has IT (inferotemporal cortex) and PC (prefrontal cortex) networks. Information about visual features and their categories were encoded into point attractors of the IT and PC networks, respectively. In the task, the IT network of the right hemisphere was stimulated with a cue feature. After a delay period, the IT network of the left hemisphere was simultaneously stimulated with the choice feature and an irrelevant feature. The cue and choice features belong to the same category, while the irrelevant feature belongs to another category. To complete the task, the IT network must select the point attractor corresponding to the choice feature. We demonstrate that the top-down pathway (PC-to-IT) triggers the retrieval of long-term memory of the choice feature from the IT, and the bottom-up pathway (IT-to-PC) contributes to the maintenance of the retrieved memory during the delay period. The key mechanism for the retrieval and maintenance of that memory is the dynamic linkage of attractors across separate cortical networks. We show that a single hemisphere is sufficient for the memory retrieval, but it is advantageous to use the two hemispheres because the retrieved memory is thereby retained with greater reliability until the brain chooses the choice feature.

  14. Cortical networks of procedural learning: evidence from cerebellar damage.

    PubMed

    Torriero, Sara; Oliveri, Massimiliano; Koch, Giacomo; Lo Gerfo, Emanuele; Salerno, Silvia; Petrosini, Laura; Caltagirone, Carlo

    2007-03-25

    The lateral cerebellum plays a critical role in procedural learning that goes beyond the strict motor control functions attributed to it. Patients with cerebellar damage show marked impairment in the acquisition of procedures, as revealed by their performance on the serial reaction time task (SRTT). Here we present the case of a patient affected by ischemic damage involving the left cerebellum who showed a selective deficit in procedural learning while performing the SRTT with the left hand. The deficit recovered when the cortical excitability of an extensive network involving both cerebellar hemispheres and the dorsolateral prefrontal cortex (DLPFC) was decreased by low-frequency repetitive transcranial magnetic stimulation (rTMS). Although inhibition of the right DLPFC or a control fronto-parietal region did not modify the patient's performance, inhibition of the right (unaffected) cerebellum and the left DLPFC markedly improved task performance. These findings could be explained by the modulation of a set of inhibitory and excitatory connections between the lateral cerebellum and the contralateral prefrontal area induced by rTMS. The presence of left cerebellar damage is likely associated with a reduced excitatory drive from sub-cortical left cerebellar nuclei towards the right DLPFC, causing reduced excitability of the right DLPFC and, conversely, unbalanced activation of the left DLPFC. Inhibition of the left DLPFC would reduce the unbalancing of cortical activation, thus explaining the observed selective recovery of procedural memory.

  15. Euchromatin histone methyltransferase 1 regulates cortical neuronal network development

    PubMed Central

    Bart Martens, Marijn; Frega, Monica; Classen, Jessica; Epping, Lisa; Bijvank, Elske; Benevento, Marco; van Bokhoven, Hans; Tiesinga, Paul; Schubert, Dirk; Nadif Kasri, Nael

    2016-01-01

    Heterozygous mutations or deletions in the human Euchromatin histone methyltransferase 1 (EHMT1) gene cause Kleefstra syndrome, a neurodevelopmental disorder that is characterized by autistic-like features and severe intellectual disability (ID). Neurodevelopmental disorders including ID and autism may be related to deficits in activity-dependent wiring of brain circuits during development. Although Kleefstra syndrome has been associated with dendritic and synaptic defects in mice and Drosophila, little is known about the role of EHMT1 in the development of cortical neuronal networks. Here we used micro-electrode arrays and whole-cell patch-clamp recordings to investigate the impact of EHMT1 deficiency at the network and single cell level. We show that EHMT1 deficiency impaired neural network activity during the transition from uncorrelated background action potential firing to synchronized network bursting. Spontaneous bursting and excitatory synaptic currents were transiently reduced, whereas miniature excitatory postsynaptic currents were not affected. Finally, we show that loss of function of EHMT1 ultimately resulted in less regular network bursting patterns later in development. These data suggest that the developmental impairments observed in EHMT1-deficient networks may result in a temporal misalignment between activity-dependent developmental processes thereby contributing to the pathophysiology of Kleefstra syndrome. PMID:27767173

  16. Transcallosal connectivity of the human cortical motor network.

    PubMed

    Ruddy, Kathy L; Leemans, Alexander; Carson, Richard G

    2017-04-01

    The organisational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualise white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has, therefore, remained elusive. We employed constrained spherical deconvolution (CSD) tractography-an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity-exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasised. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity.

  17. Simulated Associating Polymer Networks

    NASA Astrophysics Data System (ADS)

    Billen, Joris

    Telechelic associating polymer networks consist of polymer chains terminated by endgroups that have a different chemical composition than the polymer backbone. When dissolved in a solution, the endgroups cluster together to form aggregates. At low temperature, a strongly connected reversible network is formed and the system behaves like a gel. Telechelic networks are of interest since they are representative for biopolymer networks (e.g. F-actin) and are widely used in medical applications (e.g. hydrogels for tissue engineering, wound dressings) and consumer products (e.g. contact lenses, paint thickeners). In this thesis such systems are studied by means of a molecular dynamics/Monte Carlo simulation. At first, the system in rest is studied by means of graph theory. The changes in network topology upon cooling to the gel state, are characterized. Hereto an extensive study of the eigenvalue spectrum of the gel network is performed. As a result, an in-depth investigation of the eigenvalue spectra for spatial ER, scale-free, and small-world networks is carried out. Next, the gel under the application of a constant shear is studied, with a focus on shear banding and the changes in topology under shear. Finally, the relation between the gel transition and percolation is discussed.

  18. Neuronal avalanches imply maximum dynamic range in cortical networks at criticality.

    PubMed

    Shew, Woodrow L; Yang, Hongdian; Petermann, Thomas; Roy, Rajarshi; Plenz, Dietmar

    2009-12-09

    Spontaneous neuronal activity is a ubiquitous feature of cortex. Its spatiotemporal organization reflects past input and modulates future network output. Here we study whether a particular type of spontaneous activity is generated by a network that is optimized for input processing. Neuronal avalanches are a type of spontaneous activity observed in superficial cortical layers in vitro and in vivo with statistical properties expected from a network operating at "criticality." Theory predicts that criticality and, therefore, neuronal avalanches are optimal for input processing, but until now, this has not been tested in experiments. Here, we use cortex slice cultures grown on planar microelectrode arrays to demonstrate that cortical networks that generate neuronal avalanches benefit from a maximized dynamic range, i.e., the ability to respond to the greatest range of stimuli. By changing the ratio of excitation and inhibition in the cultures, we derive a network tuning curve for stimulus processing as a function of distance from criticality in agreement with predictions from our simulations. Our findings suggest that in the cortex, (1) balanced excitation and inhibition establishes criticality, which maximizes the range of inputs that can be processed, and (2) spontaneous activity and input processing are unified in the context of critical phenomena.

  19. Order-Based Representation in Random Networks of Cortical Neurons

    PubMed Central

    Kermany, Einat; Lyakhov, Vladimir; Zrenner, Christoph; Marom, Shimon

    2008-01-01

    The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen. PMID:19023409

  20. Processing of Feature Selectivity in Cortical Networks with Specific Connectivity

    PubMed Central

    Sadeh, Sadra; Clopath, Claudia; Rotter, Stefan

    2015-01-01

    Although non-specific at the onset of eye opening, networks in rodent visual cortex attain a non-random structure after eye opening, with a specific bias for connections between neurons of similar preferred orientations. As orientation selectivity is already present at eye opening, it remains unclear how this specificity in network wiring contributes to feature selectivity. Using large-scale inhibition-dominated spiking networks as a model, we show that feature-specific connectivity leads to a linear amplification of feedforward tuning, consistent with recent electrophysiological single-neuron recordings in rodent neocortex. Our results show that optimal amplification is achieved at an intermediate regime of specific connectivity. In this configuration a moderate increase of pairwise correlations is observed, consistent with recent experimental findings. Furthermore, we observed that feature-specific connectivity leads to the emergence of orientation-selective reverberating activity, and entails pattern completion in network responses. Our theoretical analysis provides a mechanistic understanding of subnetworks’ responses to visual stimuli, and casts light on the regime of operation of sensory cortices in the presence of specific connectivity. PMID:26083363

  1. 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.

  2. Depth-dependent flow and pressure characteristics in cortical microvascular networks

    PubMed Central

    Schmid, Franca; Kleinfeld, David; Jenny, Patrick; Weber, Bruno

    2017-01-01

    A better knowledge of the flow and pressure distribution in realistic microvascular networks is needed for improving our understanding of neurovascular coupling mechanisms and the related measurement techniques. Here, numerical simulations with discrete tracking of red blood cells (RBCs) are performed in three realistic microvascular networks from the mouse cerebral cortex. Our analysis is based on trajectories of individual RBCs and focuses on layer-specific flow phenomena until a cortical depth of 1 mm. The individual RBC trajectories reveal that in the capillary bed RBCs preferentially move in plane. Hence, the capillary flow field shows laminar patterns and a layer-specific analysis is valid. We demonstrate that for RBCs entering the capillary bed close to the cortical surface (< 400 μm) the largest pressure drop takes place in the capillaries (37%), while for deeper regions arterioles are responsible for 61% of the total pressure drop. Further flow characteristics, such as capillary transit time or RBC velocity, also vary significantly over cortical depth. Comparison of purely topological characteristics with flow-based ones shows that a combined interpretation of topology and flow is indispensable. Our results provide evidence that it is crucial to consider layer-specific differences for all investigations related to the flow and pressure distribution in the cortical vasculature. These findings support the hypothesis that for an efficient oxygen up-regulation at least two regulation mechanisms must be playing hand in hand, namely cerebral blood flow increase and microvascular flow homogenization. However, the contribution of both regulation mechanisms to oxygen up-regulation likely varies over depth. PMID:28196095

  3. Interhemispheric Connectivity Characterizes Cortical Reorganization in Motor-Related Networks After Cerebellar Lesions.

    PubMed

    De Vico Fallani, Fabrizio; Clausi, Silvia; Leggio, Maria; Chavez, Mario; Valencia, Miguel; Maglione, Anton Giulio; Babiloni, Fabio; Cincotti, Febo; Mattia, Donatella; Molinari, Marco

    2017-04-01

    Although cerebellar-cortical interactions have been studied extensively in animal models and humans using modern neuroimaging techniques, the effects of cerebellar stroke and focal lesions on cerebral cortical processing remain unknown. In the present study, we analyzed the large-scale functional connectivity at the cortical level by combining high-density electroencephalography (EEG) and source imaging techniques to evaluate and quantify the compensatory reorganization of brain networks after cerebellar damage. The experimental protocol comprised a repetitive finger extension task by 10 patients with unilateral focal cerebellar lesions and 10 matched healthy controls. A graph theoretical approach was used to investigate the functional reorganization of cortical networks. Our patients, compared with controls, exhibited significant differences at global and local topological level of their brain networks. An abnormal rise in small-world network efficiency was observed in the gamma band (30-40 Hz) during execution of the task, paralleled by increased long-range connectivity between cortical hemispheres. Our findings show that a pervasive reorganization of the brain network is associated with cerebellar focal damage and support the idea that the cerebellum boosts or refines cortical functions. Clinically, these results suggest that cortical changes after cerebellar damage are achieved through an increase in the interactions between remote cortical areas and that rehabilitation should aim to reshape functional activation patterns. Future studies should determine whether these hypotheses are limited to motor tasks or if they also apply to cerebro-cerebellar dysfunction in general.

  4. A possible basic cortical microcircuit called "cascaded inhibition." Results from cortical network models and recording experiments from striate simple cells.

    PubMed

    Wörgötter, F; Nelle, E; Li, B; Wang, L; Diao, Y

    1998-10-01

    The robust behavior, the degree of response linearity, and the aspect of contrast gain control in visual cortical simple cells are (amongst others) the result of the interplay between excitatory and inhibitory afferent and intracortical connections. The goal of this study was to suggest a simple intracortical connection pattern, which could also play a role in other cortical substructures, in order to generically obtain these desired effects within large physiological parameter ranges. To this end we explored the degree of linearity of spatial summation in visual simple cells experimentally and in different models based on half-wave rectifying cells ("push-pull models"). Visual cortical push-pull connection schemes originated from antagonistic motor-control models. Thus, this model class is widely applicable but normally requires a rather specific design. On the other hand we showed that a more generic version of a push-pull model, the so-called cascaded inhibitory intracortical connection scheme, which we implemented in a biologically realistic simulation, naturally explains much of the experimental data. We investigated the influence of the afferent and intracortical connection structure on the measured linearity of spatial summation in simple cells. The analysis made use of the relative modulation measure, which is easy to apply but is limited to moving sinusoidal grating stimuli. We introduced two basic push-pull models, where the order of threshold nonlinearity and linear summation is reversed. Very little difference is observed with the relative modulation measure for these models. Alterative models, like half-wave squaring models, were also briefly discussed. Of all model parameters, the ratio of excitation to inhibition in the simple cell exerts the most crucial influence on the relative modulation. Linearity deteriorates as soon as excitatory and inhibitory inputs are imbalanced and the relative modulation drops. This prediction was tested experimentally

  5. Functional Connectivity in Multiple Cortical Networks Is Associated with Performance Across Cognitive Domains in Older Adults

    PubMed Central

    Shaw, Emily E.; Schultz, Aaron P.; Sperling, Reisa A.

    2015-01-01

    Abstract Intrinsic functional connectivity MRI has become a widely used tool for measuring integrity in large-scale cortical networks. This study examined multiple cortical networks using Template-Based Rotation (TBR), a method that applies a priori network and nuisance component templates defined from an independent dataset to test datasets of interest. A priori templates were applied to a test dataset of 276 older adults (ages 65–90) from the Harvard Aging Brain Study to examine the relationship between multiple large-scale cortical networks and cognition. Factor scores derived from neuropsychological tests represented processing speed, executive function, and episodic memory. Resting-state BOLD data were acquired in two 6-min acquisitions on a 3-Tesla scanner and processed with TBR to extract individual-level metrics of network connectivity in multiple cortical networks. All results controlled for data quality metrics, including motion. Connectivity in multiple large-scale cortical networks was positively related to all cognitive domains, with a composite measure of general connectivity positively associated with general cognitive performance. Controlling for the correlations between networks, the frontoparietal control network (FPCN) and executive function demonstrated the only significant association, suggesting specificity in this relationship. Further analyses found that the FPCN mediated the relationships of the other networks with cognition, suggesting that this network may play a central role in understanding individual variation in cognition during aging. PMID:25827242

  6. Effective Suppression of Pathological Synchronization in Cortical Networks by Highly Heterogeneous Distribution of Inhibitory Connections

    PubMed Central

    Kada, Hisashi; Teramae, Jun-Nosuke; Tokuda, Isao T.

    2016-01-01

    Even without external random input, cortical networks in vivo sustain asynchronous irregular firing with low firing rate. In addition to detailed balance between excitatory and inhibitory activities, recent theoretical studies have revealed that another feature commonly observed in cortical networks, i.e., long-tailed distribution of excitatory synapses implying coexistence of many weak and a few extremely strong excitatory synapses, plays an essential role in realizing the self-sustained activity in recurrent networks of biologically plausible spiking neurons. The previous studies, however, have not considered highly non-random features of the synaptic connectivity, namely, bidirectional connections between cortical neurons are more common than expected by chance and strengths of synapses are positively correlated between pre- and postsynaptic neurons. The positive correlation of synaptic connections may destabilize asynchronous activity of networks with the long-tailed synaptic distribution and induce pathological synchronized firing among neurons. It remains unclear how the cortical network avoids such pathological synchronization. Here, we demonstrate that introduction of the correlated connections indeed gives rise to synchronized firings in a cortical network model with the long-tailed distribution. By using a simplified feed-forward network model of spiking neurons, we clarify the underlying mechanism of the synchronization. We then show that the synchronization can be efficiently suppressed by highly heterogeneous distribution, typically a lognormal distribution, of inhibitory-to-excitatory connection strengths in a recurrent network model of cortical neurons. PMID:27803659

  7. Cortical network dysfunction caused by a subtle defect of myelination

    PubMed Central

    Poggi, Giulia; Boretius, Susann; Möbius, Wiebke; Moschny, Nicole; Baudewig, Jürgen; Ruhwedel, Torben; Hassouna, Imam; Wieser, Georg L.; Werner, Hauke B.; Goebbels, Sandra

    2016-01-01

    Subtle white matter abnormalities have emerged as a hallmark of brain alterations in magnetic resonance imaging or upon autopsy of mentally ill subjects. However, it is unknown whether such reduction of white matter and myelin contributes to any disease‐relevant phenotype or simply constitutes an epiphenomenon, possibly even treatment‐related. Here, we have re‐analyzed Mbp heterozygous mice, the unaffected parental strain of shiverer, a classical neurological mutant. Between 2 and 20 months of age, Mbp+/‐ versus Mbp+/+ littermates were deeply phenotyped by combining extensive behavioral/cognitive testing with MRI, 1H‐MR spectroscopy, electron microscopy, and molecular techniques. Surprisingly, Mbp‐dependent myelination was significantly reduced in the prefrontal cortex. We also noticed a mild but progressive hypomyelination of the prefrontal corpus callosum and low‐grade inflammation. While most behavioral functions were preserved, Mbp+/‐ mice exhibited defects of sensorimotor gating, as evidenced by reduced prepulse‐inhibition, and a late‐onset catatonia phenotype. Thus, subtle but primary abnormalities of CNS myelin can be the cause of a persistent cortical network dysfunction including catatonia, features typical of neuropsychiatric conditions. GLIA 2016;64:2025–2040 PMID:27470661

  8. A large scale simulation of excitation propagation in layer 2/3 of primary and secondary visual cortices of mice.

    PubMed

    Ohtsu, Shoya; Nomura, Taishin; Uno, Shota; Maeda, Kazuki; Hayashida, Yuki; Yagi, Tetsuya

    2015-01-01

    Analyzing network architecture and spatio-temporal dynamics of the visual cortical areas can facilitate understanding visual information processing in the brain. Recently, several physiological experiments utilizing the fast in-vivo imaging technique have demonstrated that the primary visual cortex (V1) and the secondary visual cortex (V2) in mice exhibit complex properties of the responses to visual and electrical stimuli. In order to provide a tool for quantitatively analyzing such a complex dynamics of the cortices at the level of neurons and circuits, here, we constructed a physiologically plausible large-scale network model of the layers 2/3 of V1 and V2, composed of 14,056 multi-compartment neuron models. The Message-Passing-Interface-based parallel simulations of our network model were able to reproduce, at least quantitatively, the neural responses experimentally observed in mouse V1 and V2 with the voltage-sensitive dye imaging.

  9. Network Bursting Dynamics in Excitatory Cortical Neuron Cultures Results from the Combination of Different Adaptive Mechanism

    PubMed Central

    Masquelier, Timothée; Deco, Gustavo

    2013-01-01

    In the brain, synchronization among cells of an assembly is a common phenomenon, and thought to be functionally relevant. Here we used an in vitro experimental model of cell assemblies, cortical cultures, combined with numerical simulations of a spiking neural network (SNN) to investigate how and why spontaneous synchronization occurs. In order to deal with excitation only, we pharmacologically blocked GABAAergic transmission using bicuculline. Synchronous events in cortical cultures tend to involve almost every cell and to display relatively constant durations. We have thus named these “network spikes” (NS). The inter-NS-intervals (INSIs) proved to be a more interesting phenomenon. In most cortical cultures NSs typically come in series or bursts (“bursts of NSs”, BNS), with short (∼1 s) INSIs and separated by long silent intervals (tens of s), which leads to bimodal INSI distributions. This suggests that a facilitating mechanism is at work, presumably short-term synaptic facilitation, as well as two fatigue mechanisms: one with a short timescale, presumably short-term synaptic depression, and another one with a longer timescale, presumably cellular adaptation. We thus incorporated these three mechanisms into the SNN, which, indeed, produced realistic BNSs. Next, we systematically varied the recurrent excitation for various adaptation timescales. Strong excitability led to frequent, quasi-periodic BNSs (CV∼0), and weak excitability led to rare BNSs, approaching a Poisson process (CV∼1). Experimental cultures appear to operate within an intermediate weakly-synchronized regime (CV∼0.5), with an adaptation timescale in the 2–8 s range, and well described by a Poisson-with-refractory-period model. Taken together, our results demonstrate that the INSI statistics are indeed informative: they allowed us to infer the mechanisms at work, and many parameters that we cannot access experimentally. PMID:24146781

  10. Network bursting dynamics in excitatory cortical neuron cultures results from the combination of different adaptive mechanisms.

    PubMed

    Masquelier, Timothée; Deco, Gustavo

    2013-01-01

    In the brain, synchronization among cells of an assembly is a common phenomenon, and thought to be functionally relevant. Here we used an in vitro experimental model of cell assemblies, cortical cultures, combined with numerical simulations of a spiking neural network (SNN) to investigate how and why spontaneous synchronization occurs. In order to deal with excitation only, we pharmacologically blocked GABAAergic transmission using bicuculline. Synchronous events in cortical cultures tend to involve almost every cell and to display relatively constant durations. We have thus named these "network spikes" (NS). The inter-NS-intervals (INSIs) proved to be a more interesting phenomenon. In most cortical cultures NSs typically come in series or bursts ("bursts of NSs", BNS), with short (~1 s) INSIs and separated by long silent intervals (tens of s), which leads to bimodal INSI distributions. This suggests that a facilitating mechanism is at work, presumably short-term synaptic facilitation, as well as two fatigue mechanisms: one with a short timescale, presumably short-term synaptic depression, and another one with a longer timescale, presumably cellular adaptation. We thus incorporated these three mechanisms into the SNN, which, indeed, produced realistic BNSs. Next, we systematically varied the recurrent excitation for various adaptation timescales. Strong excitability led to frequent, quasi-periodic BNSs (CV~0), and weak excitability led to rare BNSs, approaching a Poisson process (CV~1). Experimental cultures appear to operate within an intermediate weakly-synchronized regime (CV~0.5), with an adaptation timescale in the 2-8 s range, and well described by a Poisson-with-refractory-period model. Taken together, our results demonstrate that the INSI statistics are indeed informative: they allowed us to infer the mechanisms at work, and many parameters that we cannot access experimentally.

  11. Multilaminar networks of cortical neurons integrate common inputs from sensory thalamus.

    PubMed

    Morgenstern, Nicolás A; Bourg, Jacques; Petreanu, Leopoldo

    2016-08-01

    Neurons in the thalamorecipient layers of sensory cortices integrate thalamic and recurrent cortical input. Cortical neurons form fine-scale, functionally cotuned networks, but whether interconnected cortical neurons within a column process common thalamocortical inputs is unknown. We tested how local and thalamocortical connectivity relate to each other by analyzing cofluctuations of evoked responses in cortical neurons after photostimulation of thalamocortical axons. We found that connected pairs of pyramidal neurons in layer (L) 4 of mouse visual cortex share more inputs from the dorsal lateral geniculate nucleus than nonconnected pairs. Vertically aligned connected pairs of L4 and L2/3 neurons were also preferentially contacted by the same thalamocortical axons. Our results provide a circuit mechanism for the observed amplification of sensory responses by L4 circuits. They also show that sensory information is concurrently processed in L4 and L2/3 by columnar networks of interconnected neurons contacted by the same thalamocortical axons.

  12. Neural network models for spatial data mining, map production, and cortical direction selectivity

    NASA Astrophysics Data System (ADS)

    Parsons, Olga

    A family of ARTMAP neural networks for incremental supervised learning has been developed over the last decade. The Sensor Exploitation Group of MIT Lincoln Laboratory (LL) has incorporated an early version of this network as the recognition engine of a hierarchical system for fusion and data mining of multiple registered geospatial images. The LL system has been successfully fielded, but it is limited to target vs. non-target identifications and does not produce whole maps. This dissertation expands the capabilities of the LL system so that it learns to identify arbitrarily many target classes at once and can thus produce a whole map. This new spatial data mining system is designed particularly to cope with the highly skewed class distributions of typical mapping problems. Specification of a consistent procedure and a benchmark testbed has permitted the evaluation of candidate recognition networks as well as pre- and post-processing and feature extraction options. The resulting default ARTMAP network and mapping methodology set a standard for a variety of related mapping problems and application domains. The second part of the dissertation investigates the development of cortical direction selectivity. The possible role of visual experience and oculomotor behavior in the maturation of cells in the primary visual cortex is studied. The responses of neurons in the thalamus and cortex of the cat are modeled when natural scenes are scanned by several types of eye movements. Inspired by the Hebbian-like synaptic plasticity, which is based upon correlations between cell activations, the second-order statistical structure of thalamo-cortical activity is examined. In the simulations, patterns of neural activity that lead to a correct refinement of cell responses are observed during visual fixation, when small ocular movements occur, but are not observed in the presence of large saccades. Simulations also replicate experiments in which kittens are reared under stroboscopic

  13. Convergence and divergence are mostly reciprocated properties of the connections in the network of cortical areas.

    PubMed

    Négyessy, László; Nepusz, Tamás; Zalányi, László; Bazsó, Fülöp

    2008-10-22

    Cognition is based on the integrated functioning of hierarchically organized cortical processing streams in a manner yet to be clarified. Because integration fundamentally depends on convergence and the complementary notion of divergence of the neuronal connections, we analysed integration by measuring the degree of convergence/divergence through the connections in the network of cortical areas. By introducing a new index, we explored the complementary convergent and divergent nature of connectional reciprocity and delineated the backward and forward cortical sub-networks for the first time. Integrative properties of the areas defined by the degree of convergence/divergence through their afferents and efferents exhibited distinctive characteristics at different levels of the cortical hierarchy. Areas previously identified as hubs exhibit information bottleneck properties. Cortical networks largely deviate from random graphs where convergence and divergence are balanced at low reciprocity level. In the cortex, which is dominated by reciprocal connections, balance appears only by further increasing the number of reciprocal connections. The results point to the decisive role of the optimal number and placement of reciprocal connections in large-scale cortical integration. Our findings also facilitate understanding of the functional interactions between the cortical areas and the information flow or its equivalents in highly recurrent natural and artificial networks.

  14. Distributed simulation of network protocols

    NASA Technical Reports Server (NTRS)

    Paterra, Frank; Overstreet, C. Michael; Maly, Kurt J.

    1990-01-01

    Simulations of high speed network protocols are very CPU intensive operations requiring very long run times. Very high speed network protocols (Gigabit/sec rates) require longer simulation runs in order to reach a steady state, while at the same time requiring additional CPU processing for each unit of time because of the data rates for the traffic being simulated. As protocol development proceeds and simulations provide insights into any problems associated with the protocol, the simulation model often must be changed to generate additional or finer statistical performance information. Iterating on this process is very time consuming due to the required run times for the simulation models. The results of the efforts to distribute a high speed ring network protocol, Carrier Sensed Multiple Access/Ring Network (CSMA/RN), are presented.

  15. Altered brain structural networks in attention deficit/hyperactivity disorder children revealed by cortical thickness.

    PubMed

    Liu, Tian; Chen, Yanni; Li, Chenxi; Li, Youjun; Wang, Jue

    2017-01-18

    This study investigated the cortical thickness and topological features of human brain anatomical networks related to attention deficit/hyperactivity disorder. Data were collected from 40 attention deficit/hyperactivity disorder children and 40 normal control children. Interregional correlation matrices were established by calculating the correlations of cortical thickness between all pairs of cortical regions (68 regions) of the whole brain. Further thresholds were applied to create binary matrices to construct a series of undirected and unweighted graphs, and global, local, and nodal efficiencies were computed as a function of the network cost. These experimental results revealed abnormal cortical thickness and correlations in attention deficit/hyperactivity disorder, and showed that the brain structural networks of attention deficit/hyperactivity disorder subjects had inefficient small-world topological features. Furthermore, their topological properties were altered abnormally. In particular, decreased global efficiency combined with increased local efficiency in attention deficit/hyperactivity disorder children led to a disorder-related shift of the network topological structure toward regular networks. In addition, nodal efficiency, cortical thickness, and correlation analyses revealed that several brain regions were altered in attention deficit/hyperactivity disorder patients. These findings are in accordance with a hypothesis of dysfunctional integration and segregation of the brain in patients with attention deficit/hyperactivity disorder and provide further evidence of brain dysfunction in attention deficit/hyperactivity disorder patients by observing cortical thickness on magnetic resonance imaging.

  16. Structure of Spontaneous UP and DOWN Transitions Self-Organizing in a Cortical Network Model

    PubMed Central

    Kang, Siu; Kitano, Katsunori; Fukai, Tomoki

    2008-01-01

    Synaptic plasticity is considered to play a crucial role in the experience-dependent self-organization of local cortical networks. In the absence of sensory stimuli, cerebral cortex exhibits spontaneous membrane potential transitions between an UP and a DOWN state. To reveal how cortical networks develop spontaneous activity, or conversely, how spontaneous activity structures cortical networks, we analyze the self-organization of a recurrent network model of excitatory and inhibitory neurons, which is realistic enough to replicate UP–DOWN states, with spike-timing-dependent plasticity (STDP). The individual neurons in the self-organized network exhibit a variety of temporal patterns in the two-state transitions. In addition, the model develops a feed-forward network-like structure that produces a diverse repertoire of precise sequences of the UP state. Our model shows that the self-organized activity well resembles the spontaneous activity of cortical networks if STDP is accompanied by the pruning of weak synapses. These results suggest that the two-state membrane potential transitions play an active role in structuring local cortical circuits. PMID:18369421

  17. Pragmatics in action: indirect requests engage theory of mind areas and the cortical motor network.

    PubMed

    van Ackeren, Markus J; Casasanto, Daniel; Bekkering, Harold; Hagoort, Peter; Rueschemeyer, Shirley-Ann

    2012-11-01

    Research from the past decade has shown that understanding the meaning of words and utterances (i.e., abstracted symbols) engages the same systems we used to perceive and interact with the physical world in a content-specific manner. For example, understanding the word "grasp" elicits activation in the cortical motor network, that is, part of the neural substrate involved in planned and executing a grasping action. In the embodied literature, cortical motor activation during language comprehension is thought to reflect motor simulation underlying conceptual knowledge [note that outside the embodied framework, other explanations for the link between action and language are offered, e.g., Mahon, B. Z., & Caramazza, A. A critical look at the embodied cognition hypothesis and a new proposal for grouding conceptual content. Journal of Physiology, 102, 59-70, 2008; Hagoort, P. On Broca, brain, and binding: A new framework. Trends in Cognitive Sciences, 9, 416-423, 2005]. Previous research has supported the view that the coupling between language and action is flexible, and reading an action-related word form is not sufficient for cortical motor activation [Van Dam, W. O., van Dijk, M., Bekkering, H., & Rueschemeyer, S.-A. Flexibility in embodied lexical-semantic representations. Human Brain Mapping, doi: 10.1002/hbm.21365, 2011]. The current study goes one step further by addressing the necessity of action-related word forms for motor activation during language comprehension. Subjects listened to indirect requests (IRs) for action during an fMRI session. IRs for action are speech acts in which access to an action concept is required, although it is not explicitly encoded in the language. For example, the utterance "It is hot here!" in a room with a window is likely to be interpreted as a request to open the window. However, the same utterance in a desert will be interpreted as a statement. The results indicate (1) that comprehension of IR sentences activates cortical

  18. Modeling and Simulations in Time Domain of a Stimulation Set-up for Cortical Applications

    PubMed Central

    Schweigmann, Michael; Kirchhoff, Frank; Koch, Klaus P.

    2016-01-01

    Electrical stimulation is used for example to treat neuronal disorders and depression with deep brain stimulation or transcranial electrical stimulation. Depending on the application, different electrodes are used and thus different electrical characteristics exist, which have to be handled by the stimulator. Without a measuring device the user would have to rely on the stimulator being able to deliver the needed stimulation signal. Therefore, the objective of this paper is to present a method to increase the level of confidence with characterization and modelling of the electrical behavior by using the example of one channel of our stimulation device for experimental use. In several simulation studies with an electrode model with values in a typical range for cortical applications the influence of the load onto the stimulator and the possibility to pre-estimate measuring signals in complex networks are shown. PMID:27478564

  19. Slow dynamics and high variability in balanced cortical networks with clustered connections.

    PubMed

    Litwin-Kumar, Ashok; Doiron, Brent

    2012-11-01

    Anatomical studies demonstrate that excitatory connections in cortex are not uniformly distributed across a network but instead exhibit clustering into groups of highly connected neurons. The implications of clustering for cortical activity are unclear. We studied the effect of clustered excitatory connections on the dynamics of neuronal networks that exhibited high spike time variability owing to a balance between excitation and inhibition. Even modest clustering substantially changed the behavior of these networks, introducing slow dynamics during which clusters of neurons transiently increased or decreased their firing rate. Consequently, neurons exhibited both fast spiking variability and slow firing rate fluctuations. A simplified model shows how stimuli bias networks toward particular activity states, thereby reducing firing rate variability as observed experimentally in many cortical areas. Our model thus relates cortical architecture to the reported variability in spontaneous and evoked spiking activity.

  20. Retrieval of high-fidelity memory arises from distributed cortical networks.

    PubMed

    Wais, Peter E; Jahanikia, Sahar; Steiner, Daniel; Stark, Craig E L; Gazzaley, Adam

    2017-04-01

    Medial temporal lobe (MTL) function is well established as necessary for memory of facts and events. It is likely that lateral cortical regions critically guide cognitive control processes to tune in high-fidelity details that are most relevant for memory retrieval. Here, convergent results from functional and structural MRI show that retrieval of detailed episodic memory arises from lateral cortical-MTL networks, including regions of inferior frontal and angular gyrii. Results also suggest that recognition of items based on low-fidelity, generalized information, rather than memory arising from retrieval of relevant episodic details, is not associated with functional connectivity between MTL and lateral cortical regions. Additionally, individual differences in microstructural properties in white matter pathways, associated with distributed MTL-cortical networks, are positively correlated with better performance on a mnemonic discrimination task.

  1. Cerebral-cortical networking and activation increase as a function of cognitive-motor task difficulty.

    PubMed

    Rietschel, Jeremy C; Miller, Matthew W; Gentili, Rodolphe J; Goodman, Ronald N; McDonald, Craig G; Hatfield, Bradley D

    2012-05-01

    Excessive increases in task difficulty typically result in marked attenuation of cognitive-motor performance. The psychomotor efficiency hypothesis suggests that poor performance is mediated by non-essential neural activity and cerebral cortical networking (inefficient cortical dynamics). This phenomenon may underlie the inverse relationship between excessive task difficulty and performance. However, investigation of the psychomotor efficiency hypothesis as it relates to task difficulty has not been conducted. The present study used electroencephalography (EEG) to examine cerebral cortical dynamics while participants were challenged with both Easy and Hard conditions during a cognitive-motor task (Tetris(®)). In accord with the psychomotor efficiency hypothesis, it was predicted that with increases in task difficulty, participants would demonstrate greater 'neural effort,' as indexed by EEG spectral power and cortical networking (i.e., EEG coherence) between the premotor (motor planning) region and sensory, executive, and motor regions. Increases in neural activation and cortical networking were observed during the Hard condition relative to the Easy condition, thus supporting the psychomotor efficiency hypothesis. To further determine the unique contributions of cognitive versus sensory-motor demands, a control experiment was conducted in which cognitive demand was increased while sensory-motor demand was held constant. This experiment revealed that regionally specific neural activation was influenced by changes in cognitive demand, whereas cortical networking to the motor planning region was sensitive only to changes in sensory-motor demand. Crucially, the present study is the first, to our knowledge, to characterize the separate impact of cognitive versus sensory-motor demands on cerebral cortical dynamics. The findings further inform the dynamics of the cortical processes that underlie the quality of cognitive-motor performance particularly with regard to task

  2. The maturation of cortical sleep rhythms and networks over early development

    PubMed Central

    Chu, CJ; Leahy, J; Pathmanathan, J; Kramer, MA; Cash, SS

    2014-01-01

    Objective Although neuronal activity drives all aspects of cortical development, how human brain rhythms spontaneously mature remains an active area of research. We sought to systematically evaluate the emergence of human brain rhythms and functional cortical networks over early development. Methods We examined cortical rhythms and coupling patterns from birth through adolescence in a large cohort of healthy children (n=384) using scalp electroencephalogram (EEG) in the sleep state. Results We found that the emergence of brain rhythms follows a stereotyped sequence over early development. In general, higher frequencies increase in prominence with striking regional specificity throughout development. The coordination of these rhythmic activities across brain regions follows a general pattern of maturation in which broadly distributed networks of low-frequency oscillations increase in density while networks of high frequency oscillations become sparser and more highly clustered. Conclusion Our results indicate that a predictable program directs the development of key rhythmic components and physiological brain networks over early development. Significance This work expands our knowledge of normal cortical development. The stereotyped neurophysiological processes observed at the level of rhythms and networks may provide a scaffolding to support critical periods of cognitive growth. Furthermore, these conserved patterns could provide a sensitive biomarker for cortical health across development. PMID:24418219

  3. Anesthetic actions of thiopental remain largely unaffected during cholinergic overstimulation in cultured cortical networks.

    PubMed

    Weimer, Isabel; Worek, Franz; Seeger, Thomas; Thiermann, Horst; Grasshoff, Christian; Antkowiak, Bernd; Balk, Monika

    2016-02-26

    In case of military or terrorist use of organophosphorus (OP) compounds victims are likely to suffer from not only intoxication but physical trauma as well. Appropriate emergency care may therefore include general anesthesia to allow life-saving surgical intervention. Since there is evidence that drug potency and efficacy of several anesthetics are attenuated by high concentrations of acetylcholine in the CNS, this study was designed to evaluate the anesthetic actions of thiopental during cholinergic overstimulation. Making use of organotypic slice cultures derived from the mouse neocortex, drug effects were assessed by extracellular voltage recordings of network activity at basal cholinergic tone and during simulated cholinergic crisis (high cholinergic tone). The latter was achieved by inhibition of acetylcholinesterases via soman and an ambient acetylcholine concentration of 10μM. The induction of cholinergic crisis in vitro increased the network activity of cortical neurons significantly. Surprisingly, differences in network activity between basal and high cholinergic tone became less pronounced with rising concentrations of thiopental and drug potency and efficacy were almost equivalent. These results clearly distinguish thiopental from previously tested general anesthetics and make it a promising candidate for in vivo studies to identify suitable anesthetics for victims of OP intoxication.

  4. A new bio-inspired stimulator to suppress hyper-synchronized neural firing in a cortical network.

    PubMed

    Amiri, Masoud; Amiri, Mahmood; Nazari, Soheila; Faez, Karim

    2016-12-07

    Hyper-synchronous neural oscillations are the character of several neurological diseases such as epilepsy. On the other hand, glial cells and particularly astrocytes can influence neural synchronization. Therefore, based on the recent researches, a new bio-inspired stimulator is proposed which basically is a dynamical model of the astrocyte biophysical model. The performance of the new stimulator is investigated on a large-scale, cortical network. Both excitatory and inhibitory synapses are also considered in the simulated spiking neural network. The simulation results show that the new stimulator has a good performance and is able to reduce recurrent abnormal excitability which in turn avoids the hyper-synchronous neural firing in the spiking neural network. In this way, the proposed stimulator has a demand controlled characteristic and is a good candidate for deep brain stimulation (DBS) technique to successfully suppress the neural hyper-synchronization.

  5. Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons

    PubMed Central

    Willmore, Ben D. B.; Cui, Zhanfeng; Schnupp, Jan W. H.; King, Andrew J.

    2016-01-01

    Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1–7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context. PMID:27835647

  6. Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

    PubMed

    Harper, Nicol S; Schoppe, Oliver; Willmore, Ben D B; Cui, Zhanfeng; Schnupp, Jan W H; King, Andrew J

    2016-11-01

    Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.

  7. Subthalamic stimulation modulates cortical motor network activity and synchronization in Parkinson's disease.

    PubMed

    Weiss, Daniel; Klotz, Rosa; Govindan, Rathinaswamy B; Scholten, Marlieke; Naros, Georgios; Ramos-Murguialday, Ander; Bunjes, Friedemann; Meisner, Christoph; Plewnia, Christian; Krüger, Rejko; Gharabaghi, Alireza

    2015-03-01

    Dynamic modulations of large-scale network activity and synchronization are inherent to a broad spectrum of cognitive processes and are disturbed in neuropsychiatric conditions including Parkinson's disease. Here, we set out to address the motor network activity and synchronization in Parkinson's disease and its modulation with subthalamic stimulation. To this end, 20 patients with idiopathic Parkinson's disease with subthalamic nucleus stimulation were analysed on externally cued right hand finger movements with 1.5-s interstimulus interval. Simultaneous recordings were obtained from electromyography on antagonistic muscles (right flexor digitorum and extensor digitorum) together with 64-channel electroencephalography. Time-frequency event-related spectral perturbations were assessed to determine cortical and muscular activity. Next, cross-spectra in the time-frequency domain were analysed to explore the cortico-cortical synchronization. The time-frequency modulations enabled us to select a time-frequency range relevant for motor processing. On these time-frequency windows, we developed an extension of the phase synchronization index to quantify the global cortico-cortical synchronization and to obtain topographic differentiations of distinct electrode sites with respect to their contributions to the global phase synchronization index. The spectral measures were used to predict clinical and reaction time outcome using regression analysis. We found that movement-related desynchronization of cortical activity in the upper alpha and beta range was significantly facilitated with 'stimulation on' compared to 'stimulation off' on electrodes over the bilateral parietal, sensorimotor, premotor, supplementary-motor, and prefrontal areas, including the bilateral inferior prefrontal areas. These spectral modulations enabled us to predict both clinical and reaction time improvement from subthalamic stimulation. With 'stimulation on', interhemispheric cortico-cortical

  8. Controlling instabilities in manipulation requires specific cortical-striatal-cerebellar networks

    PubMed Central

    Lau, Chad; Wang, Yang; Venkadesan, Madhusudhan; Valero-Cuevas, Francisco J.

    2011-01-01

    Dexterous manipulation requires both strength, the ability to produce fingertip forces of a specific magnitude, and dexterity, the ability to dynamically regulate the magnitude and direction of fingertip force vectors and finger motions. Although cortical activity in fronto-parietal networks has been established for stable grip and pinch forces, the cortical regulation in the dexterous control of unstable objects remains unknown. We used functional magnetic resonance imaging (fMRI) to interrogate cortical networks engaged in the control of four objects with increasing instabilities but requiring constant strength. In addition to expected activity in fronto-parietal networks we find that dexterous manipulation of increasingly unstable objects is associated with a linear increase in the amplitude of the BOLD signal in the basal ganglia (P = 0.007 and P = 0.023 for 2 compression tasks). A computational regression (connectivity) model identified independent subsets of cortical networks whose connection strengths were mutable and associated with object instability (P < 0.001). Our results suggest that in the presence of object instability, the basal ganglia may modulate the activity of premotor areas and subsequent motor output. This work, therefore, provides new evidence for the selectable cortical representation and execution of dynamic multifinger manipulation for grasp stability. PMID:21228301

  9. Computational Study of Subdural Cortical Stimulation: Effects of Simulating Anisotropic Conductivity on Activation of Cortical Neurons

    PubMed Central

    Seo, Hyeon; Kim, Donghyeon; Jun, Sung Chan

    2015-01-01

    Subdural cortical stimulation (SuCS) is an appealing method in the treatment of neurological disorders, and computational modeling studies of SuCS have been applied to determine the optimal design for electrotherapy. To achieve a better understanding of computational modeling on the stimulation effects of SuCS, the influence of anisotropic white matter conductivity on the activation of cortical neurons was investigated in a realistic head model. In this paper, we constructed pyramidal neuronal models (layers 3 and 5) that showed primary excitation of the corticospinal tract, and an anatomically realistic head model reflecting complex brain geometry. The anisotropic information was acquired from diffusion tensor magnetic resonance imaging (DT-MRI) and then applied to the white matter at various ratios of anisotropic conductivity. First, we compared the isotropic and anisotropic models; compared to the isotropic model, the anisotropic model showed that neurons were activated in the deeper bank during cathodal stimulation and in the wider crown during anodal stimulation. Second, several popular anisotropic principles were adapted to investigate the effects of variations in anisotropic information. We observed that excitation thresholds varied with anisotropic principles, especially with anodal stimulation. Overall, incorporating anisotropic conductivity into the anatomically realistic head model is critical for accurate estimation of neuronal responses; however, caution should be used in the selection of anisotropic information. PMID:26057524

  10. Alterations in cortical network oscillations and parvalbumin neurons in schizophrenia.

    PubMed

    Gonzalez-Burgos, Guillermo; Cho, Raymond Y; Lewis, David A

    2015-06-15

    Cognitive deficits are a core clinical feature of schizophrenia but respond poorly to available medications. Thus, understanding the neural basis of these deficits is crucial for the development of new therapeutic interventions. The types of cognitive processes affected in schizophrenia are thought to depend on the precisely timed transmission of information in cortical regions via synchronous oscillations at gamma band frequency. Here, we review 1) data from clinical studies suggesting that induction of frontal cortex gamma oscillations during tasks that engage cognitive or complex perceptual functions is attenuated in schizophrenia; 2) findings from basic neuroscience studies highlighting the features of parvalbumin-positive interneurons that are critical for gamma oscillation production; and 3) results from recent postmortem human brain studies providing additional molecular bases for parvalbumin-positive interneuron alterations in prefrontal cortical circuitry in schizophrenia.

  11. Alterations in Cortical Network Oscillations and Parvalbumin Neurons in Schizophrenia

    PubMed Central

    Gonzalez-Burgos, Guillermo; Cho, Raymond Y; Lewis, David A

    2015-01-01

    Cognitive deficits are a core clinical feature of schizophrenia but respond poorly to available medications. Thus, understanding the neural basis of these deficits is crucial for the development of new therapeutic interventions. The types of cognitive processes affected in schizophrenia are thought to depend on the precisely timed transmission of information in cortical regions via synchronous oscillations at gamma band frequency. Here, we review 1) data from clinical studies suggesting that induction of frontal cortex gamma oscillations during tasks that engage cognitive or complex perceptual functions is attenuated in schizophrenia, 2) findings from basic neuroscience studies highlighting the features of parvalbumin-positive (PV) interneurons that are critical for gamma oscillation production and 3) results from recent postmortem human brain studies providing additional molecular bases for PV interneuron alterations in prefrontal cortical circuitry in schizophrenia. PMID:25863358

  12. 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

  13. Graph properties of synchronized cortical networks during visual working memory maintenance.

    PubMed

    Palva, Satu; Monto, Simo; Palva, J Matias

    2010-02-15

    Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles.

  14. Altered Resting-State Functional Connectivity in Cortical Networks in Psychopathy

    PubMed Central

    Pujara, Maia S.; Motzkin, Julian C.; Newman, Joseph; Kiehl, Kent A.

    2015-01-01

    Psychopathy is a personality disorder characterized by callous antisocial behavior and criminal recidivism. Here we examine whether psychopathy is associated with alterations in functional connectivity in three large-scale cortical networks. Using fMRI in 142 adult male prison inmates, we computed resting-state functional connectivity using seeds from the default mode network, frontoparietal network, and cingulo-opercular network. To determine the specificity of our findings to these cortical networks, we also calculated functional connectivity using seeds from two comparison primary sensory networks: visual and auditory networks. Regression analyses related network connectivity to overall psychopathy scores and to subscores for the “factors” and “facets” of psychopathy: Factor 1, interpersonal/affective traits; Factor 2, lifestyle/antisocial traits; Facet 1, interpersonal; Facet 2, affective; Facet 3, lifestyle; Facet 4, antisocial. Overall psychopathy severity was associated with reduced functional connectivity between lateral parietal cortex and dorsal anterior cingulate cortex. The two factor scores exhibited contrasting relationships with functional connectivity: Factor 1 scores were associated with reduced functional connectivity in the three cortical networks, whereas Factor 2 scores were associated with heightened connectivity in the same networks. This dissociation was evident particularly in the functional connectivity between anterior insula and dorsal anterior cingulate cortex. The facet scores also demonstrated distinct patterns of connectivity. We found no associations between psychopathy scores and functional connectivity within visual or auditory networks. These findings provide novel evidence on the neural correlates of psychopathy and suggest that connectivity between cortical association hubs, such as the dorsal anterior cingulate cortex, may be a neurobiological marker of the disorder. PMID:25878280

  15. Small-world anatomical networks in the human brain revealed by cortical thickness from MRI.

    PubMed

    He, Yong; Chen, Zhang J; Evans, Alan C

    2007-10-01

    An important issue in neuroscience is the characterization for the underlying architectures of complex brain networks. However, little is known about the network of anatomical connections in the human brain. Here, we investigated large-scale anatomical connection patterns of the human cerebral cortex using cortical thickness measurements from magnetic resonance images. Two areas were considered anatomically connected if they showed statistically significant correlations in cortical thickness and we constructed the network of such connections using 124 brains from the International Consortium for Brain Mapping database. Significant short- and long-range connections were found in both intra- and interhemispheric regions, many of which were consistent with known neuroanatomical pathways measured by human diffusion imaging. More importantly, we showed that the human brain anatomical network had robust small-world properties with cohesive neighborhoods and short mean distances between regions that were insensitive to the selection of correlation thresholds. Additionally, we also found that this network and the probability of finding a connection between 2 regions for a given anatomical distance had both exponentially truncated power-law distributions. Our results demonstrated the basic organizational principles for the anatomical network in the human brain compatible with previous functional networks studies, which provides important implications of how functional brain states originate from their structural underpinnings. To our knowledge, this study provides the first report of small-world properties and degree distribution of anatomical networks in the human brain using cortical thickness measurements.

  16. Enhancing effects of flavored nutritive stimuli on cortical swallowing network activity

    PubMed Central

    Babaei, Arash; Kern, Mark; Antonik, Stephen; Mepani, Rachel; Ward, B. Douglas; Li, Shi-Jiang; Hyde, James

    2010-01-01

    A better understanding of the central control of the physiology of deglutition is necessary for devising interventions aimed at correcting pathophysiological conditions of swallowing. Positive modulation of the cortical swallowing network can have clinical ramifications in dysphagia due to central nervous system deficits. Our aim was to determine the effect of nutritive sensory input on the cortical swallowing network. In 14 healthy right-handed volunteers, we utilized a paradigm-driven protocol to quantify the number of activated voxels and their signal intensity within the left hemispheric cortical swallowing network by high-resolution functional MRI (fMRI) during five different swallowing conditions. Swallowing conditions included a dry swallow (saliva) and natural water-, lemon-, popcorn-, and chocolate-flavored liquid swallows. Each flavored liquid was presented simultaneously by its image, scent, and taste in random order and tested over three runs. fMRIs were analyzed in a blinded fashion. Average fMRI blood oxygenation level-dependent signal intensity and number of activated voxels during swallowing concurrent with nutritive gustatory, olfactory, and visual stimulations were significantly increased compared with dry/natural water swallows throughout the cortical swallowing network (P < 0.001 and P < 0.05, respectively). Subregion analysis showed the increased activity for flavored liquids in prefrontal, cingulate gyrus, and sensory/motor cortex, but not in precuneus and insula. Concurrent gustatory, olfactory, and visual nutritive stimulation enhances the activity of the cortical swallowing network. This finding may have clinical implications in management of swallowing disorders due to cortical lesions. PMID:20508154

  17. Parallel network simulations with NEURON.

    PubMed

    Migliore, M; Cannia, C; Lytton, W W; Markram, Henry; Hines, M L

    2006-10-01

    The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2,000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored.

  18. Network-state modulation of power-law frequency-scaling in visual cortical neurons.

    PubMed

    El Boustani, Sami; Marre, Olivier; Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves

    2009-09-01

    Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of V(m) activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the V(m) reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the "effective" connectivity responsible for the dynamical signature of the population signals measured

  19. Molecular Correlates of Cortical Network Modulation by Long-Term Sensory Experience in the Adult Rat Barrel Cortex

    ERIC Educational Resources Information Center

    Vallès, Astrid; Granic, Ivica; De Weerd, Peter; Martens, Gerard J. M.

    2014-01-01

    Modulation of cortical network connectivity is crucial for an adaptive response to experience. In the rat barrel cortex, long-term sensory stimulation induces cortical network modifications and neuronal response changes of which the molecular basis is unknown. Here, we show that long-term somatosensory stimulation by enriched environment…

  20. Morphological and Functional Differences between Athletes and Novices in Cortical Neuronal Networks

    PubMed Central

    Tan, Xiao-Ying; Pi, Yan-Ling; Wang, Jue; Li, Xue-Pei; Zhang, Lan-Lan; Dai, Wen; Zhu, Hua; Ni, Zhen; Zhang, Jian; Wu, Yin

    2017-01-01

    The cortical structural and functional differences in athletes and novices were investigated with a cross-sectional paradigm. We measured the gray matter volumes and resting-state functional connectivity in 21 basketball players and 21 novices with magnetic resonance imaging (MRI) techniques. It was found that gray matter volume in the left anterior insula (AI), inferior frontal gyrus (IFG), inferior parietal lobule (IPL) and right anterior cingulate cortex (ACC), precuneus is greater in basketball players than that in novices. These five brain regions were selected as the seed regions for testing the resting-state functional connectivity in the second experiment. We found higher functional connectivity in default mode network, salience network and executive control network in basketball players compared to novices. We conclude that the morphology and functional connectivity in cortical neuronal networks in athletes and novices are different. PMID:28101012

  1. Morphological and Functional Differences between Athletes and Novices in Cortical Neuronal Networks.

    PubMed

    Tan, Xiao-Ying; Pi, Yan-Ling; Wang, Jue; Li, Xue-Pei; Zhang, Lan-Lan; Dai, Wen; Zhu, Hua; Ni, Zhen; Zhang, Jian; Wu, Yin

    2016-01-01

    The cortical structural and functional differences in athletes and novices were investigated with a cross-sectional paradigm. We measured the gray matter volumes and resting-state functional connectivity in 21 basketball players and 21 novices with magnetic resonance imaging (MRI) techniques. It was found that gray matter volume in the left anterior insula (AI), inferior frontal gyrus (IFG), inferior parietal lobule (IPL) and right anterior cingulate cortex (ACC), precuneus is greater in basketball players than that in novices. These five brain regions were selected as the seed regions for testing the resting-state functional connectivity in the second experiment. We found higher functional connectivity in default mode network, salience network and executive control network in basketball players compared to novices. We conclude that the morphology and functional connectivity in cortical neuronal networks in athletes and novices are different.

  2. Cortical Thinning in Network-Associated Regions in Cognitively Normal and Below-Normal Range Schizophrenia

    PubMed Central

    Pinnock, Farena; Parlar, Melissa; Hawco, Colin; Hanford, Lindsay; Hall, Geoffrey B.

    2017-01-01

    This study assessed whether cortical thickness across the brain and regionally in terms of the default mode, salience, and central executive networks differentiates schizophrenia patients and healthy controls with normal range or below-normal range cognitive performance. Cognitive normality was defined using the MATRICS Consensus Cognitive Battery (MCCB) composite score (T = 50 ± 10) and structural magnetic resonance imaging was used to generate cortical thickness data. Whole brain analysis revealed that cognitively normal range controls (n = 39) had greater cortical thickness than both cognitively normal (n = 17) and below-normal range (n = 49) patients. Cognitively normal controls also demonstrated greater thickness than patients in regions associated with the default mode and salience, but not central executive networks. No differences on any thickness measure were found between cognitively normal range and below-normal range controls (n = 24) or between cognitively normal and below-normal range patients. In addition, structural covariance between network regions was high and similar across subgroups. Positive and negative symptom severity did not correlate with thickness values. Cortical thinning across the brain and regionally in relation to the default and salience networks may index shared aspects of the psychotic psychopathology that defines schizophrenia with no relation to cognitive impairment. PMID:28348889

  3. Characterization of Early Cortical Neural Network Development in Multiwell Microelectrode Array Plates

    EPA Science Inventory

    We examined the development of neural network activity using microelectrode array (MEA) recordings made in multi-well MEA plates (mwMEAs) over the first 12 days in vitro (DIV). In primary cortical cultures made from postnatal rats, action potential spiking activity was essentiall...

  4. Induction of Calcium Influx in Cortical Neural Networks by Nanomagnetic Forces.

    PubMed

    Tay, Andy; Kunze, Anja; Murray, Coleman; Di Carlo, Dino

    2016-02-23

    Nanomagnetic force stimulation with ferromagnetic nanoparticles was found to trigger calcium influx in cortical neural networks without observable cytotoxicity. Stimulated neural networks showed an average of 20% increment in calcium fluorescence signals and a heightened frequency in calcium spiking. These effects were also confined spatially to areas with engineered high magnetic field gradients. Furthermore, blockage of N-type calcium channels inhibited the stimulatory effects of the nanomagnetic forces, suggesting the role of mechano-sensitive ion channels in mediating calcium influx.

  5. Frontotemporal dementia and language networks: cortical thickness reduction is driven by dyslexia susceptibility genes

    PubMed Central

    Paternicó, Donata; Manes, Marta; Premi, Enrico; Cosseddu, Maura; Gazzina, Stefano; Alberici, Antonella; Archetti, Silvana; Bonomi, Elisa; Cotelli, Maria Sofia; Cotelli, Maria; Turla, Marinella; Micheli, Anna; Gasparotti, Roberto; Padovani, Alessandro; Borroni, Barbara

    2016-01-01

    Variations within genes associated with dyslexia result in a language network vulnerability, and in patients with Frontotemporal Dementia (FTD), language disturbances represent a disease core feature. Here we explored whether variations within three related-dyslexia genes, namely KIAA0319, DCDC2, and CNTNAP, might affect cortical thickness measures in FTD patients. 112 FTD patients underwent clinical and neuropsychological examination, genetic analyses and brain Magnetic Resonance Imaging (MRI). KIAA0319 rs17243157 G/A, DCDC2 rs793842 A/G and CNTNAP2 rs17236239 A/G genetic variations were assessed. Cortical thickness was analysed by Freesurfer. Patients carrying KIAA0319 A*(AG or AA) carriers showed greater cortical thickness atrophy in the left fusiform and inferior temporal gyri, compared to KIAA0319 GG (p ≤ 0.001). Patients carrying CNTNAP2 G*(GA or GG) showed reduced cortical thickness in the left insula thenCNTNAP2 AA carriers (p≤0.001). When patients with both at-risk polymorphisms were considered (KIAA0319 A* and CNTNAP2 G*), greater and addictive cortical thickness atrophy of the left insula and the inferior temporal gyrus was demonstrated (p ≤ 0.001). No significant effect of DCDC2 was found. In FTD, variations of KIAA0319 and CNTNAP2 genes were related to cortical thickness abnormalities in those brain areas involved in language abilities. These findings shed light on genetic predisposition in defining phenotypic variability in FTD. PMID:27484312

  6. Inter-synaptic learning of combination rules in a cortical network model

    PubMed Central

    Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

    2014-01-01

    Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network. PMID:25221529

  7. Molecular correlates of cortical network modulation by long-term sensory experience in the adult rat barrel cortex

    PubMed Central

    Vallès, Astrid; Granic, Ivica; De Weerd, Peter; Martens, Gerard J.M.

    2014-01-01

    Modulation of cortical network connectivity is crucial for an adaptive response to experience. In the rat barrel cortex, long-term sensory stimulation induces cortical network modifications and neuronal response changes of which the molecular basis is unknown. Here, we show that long-term somatosensory stimulation by enriched environment up-regulates cortical expression of neuropeptide mRNAs and down-regulates immediate-early gene (IEG) mRNAs specifically in the barrel cortex, and not in other brain regions. The present data suggest a central role of neuropeptides in the fine-tuning of sensory cortical circuits by long-term experience. PMID:25171421

  8. Ghrelin accelerates synapse formation and activity development in cultured cortical networks

    PubMed Central

    2014-01-01

    Background While ghrelin was initially related to appetite stimulation and growth hormone secretion, it also has a neuroprotective effect in neurodegenerative diseases and regulates cognitive function. The cellular basis of those processes is related to synaptic efficacy and plasticity. Previous studies have shown that ghrelin not only stimulates synapse formation in cultured cortical neurons and hippocampal slices, but also alters some of the electrophysiological properties of neurons in the hypothalamus, amygdala and other subcortical areas. However, direct evidence for ghrelin’s ability to modulate the activity in cortical neurons is not available yet. In this study, we investigated the effect of acylated ghrelin on the development of the activity level and activity patterns in cortical neurons, in relation to its effect on synaptogenesis. Additionally, we quantitatively evaluated the expression of the receptor for acylated ghrelin – growth hormone secretagogue receptor-1a (GHSR-1a) during development. Results We performed electrophysiology and immunohistochemistry on dissociated cortical cultures from neonates, treated chronically with acylated ghrelin. On average 76 ± 4.6% of the cortical neurons expressed GHSR-1a. Synapse density was found to be much higher in ghrelin treated cultures than in controls across all age groups (1, 2 or 3 weeks). In all cultures (control and ghrelin treated), network activity gradually increased until it reached a maximum after approximately 3 weeks, followed by a slight decrease towards a plateau. During early developmental stages (1–2 weeks), the activity was much higher in ghrelin treated cultures and consequently, they reached the plateau value almost a week earlier than controls. Conclusions Acylated ghrelin leads to earlier network formation and activation in cultured cortical neuronal networks, the latter being a possibly consequence of accelerated synaptogenesis. PMID:24742241

  9. From cognitive networks to seizures: Stimulus evoked dynamics in a coupled cortical network

    NASA Astrophysics Data System (ADS)

    Lee, Jaejin; Ermentrout, Bard; Bodner, Mark

    2013-12-01

    Epilepsy is one of the most common neuropathologies worldwide. Seizures arising in epilepsy or in seizure disorders are characterized generally by uncontrolled spread of excitation and electrical activity to a limited region or even over the entire cortex. While it is generally accepted that abnormal excessive firing and synchronization of neuron populations lead to seizures, little is known about the precise mechanisms underlying human epileptic seizures, the mechanisms of transitions from normal to paroxysmal activity, or about how seizures spread. Further complication arises in that seizures do not occur with a single type of dynamics but as many different phenotypes and genotypes with a range of patterns, synchronous oscillations, and time courses. The concept of preventing, terminating, or modulating seizures and/or paroxysmal activity through stimulation of brain has also received considerable attention. The ability of such stimulation to prevent or modulate such pathological activity may depend on identifiable parameters. In this work, firing rate networks with inhibitory and excitatory populations were modeled. Network parameters were chosen to model normal working memory behaviors. Two different models of cognitive activity were developed. The first model consists of a single network corresponding to a local area of the brain. The second incorporates two networks connected through sparser recurrent excitatory connectivity with transmission delays ranging from approximately 3 ms within local populations to 15 ms between populations residing in different cortical areas. The effect of excitatory stimulation to activate working memory behavior through selective persistent activation of populations is examined in the models, and the conditions and transition mechanisms through which that selective activation breaks down producing spreading paroxysmal activity and seizure states are characterized. Specifically, we determine critical parameters and architectural

  10. Cortical morphometry in frontoparietal and default mode networks in math-gifted adolescents.

    PubMed

    Navas-Sánchez, Francisco J; Carmona, Susana; Alemán-Gómez, Yasser; Sánchez-González, Javier; Guzmán-de-Villoria, Juan; Franco, Carolina; Robles, Olalla; Arango, Celso; Desco, Manuel

    2016-05-01

    Math-gifted subjects are characterized by above-age performance in intelligence tests, exceptional creativity, and high task commitment. Neuroimaging studies reveal enhanced functional brain organization and white matter microstructure in the frontoparietal executive network of math-gifted individuals. However, the cortical morphometry of these subjects remains largely unknown. The main goal of this study was to compare the cortical morphometry of math-gifted adolescents with that of an age- and IQ-matched control group. We used surface-based methods to perform a vertex-wise analysis of cortical thickness and surface area. Our results show that math-gifted adolescents present a thinner cortex and a larger surface area in key regions of the frontoparietal and default mode networks, which are involved in executive processing and creative thinking, respectively. The combination of reduced cortical thickness and larger surface area suggests above-age neural maturation of these networks in math-gifted individuals. Hum Brain Mapp 37:1893-1902, 2016. © 2016 Wiley Periodicals, Inc.

  11. The thalamo-cortical complex network correlates of chronic pain

    PubMed Central

    Zippo, Antonio G.; Valente, Maurizio; Caramenti, Gian Carlo; Biella, Gabriele E. M.

    2016-01-01

    Chronic pain (CP) is a condition with a large repertory of clinical signs and symptoms with diverse expressions. Though widely analyzed, an appraisal at the level of single neuron and neuronal networks in CP is however missing. The present research proposes an empirical and theoretic framework which identifies a complex network correlate nested in the somatosensory thalamocortical (TC) circuit in diverse CP models. In vivo simultaneous extracellular neuronal electrophysiological high-density recordings have been performed from the TC circuit in rats. Wide functional network statistics neatly discriminated CP from control animals identifying collective dynamical traits. In particular, a collapsed functional connectivity and an altered modular architecture of the thalamocortical circuit have been evidenced. These results envisage CP as a functional connectivity disorder and give the clue for unveiling innovative therapeutic strategies. PMID:27734895

  12. Dynamics of thalamo-cortical network oscillations and human perception.

    PubMed

    Ribary, Urs

    2005-01-01

    There is increasing evidence that human cognitive functions can be addressed from a robust neuroscience perspective. In particular, the distributed coherent electrical properties of central neuronal ensembles are considered to be a promising avenue of inquiry concerning global brain functions. The intrinsic oscillatory properties of neurons (Llinás, R. (1988) The intrinsic electrophysiological properties of mammalian neurons: Insights into central nervous system function. Science, 242: 1654-1664), supported by a large variety of voltage-gated ionic conductances are recognized to be the central elements in the generation of the temporal binding required for cognition. Research in neuroscience further indicates that oscillatory activity in the gamma band (25-50 Hz) can be correlated with both sensory acquisition and pre-motor planning, which are non-continuous functions in the time domain. From this perspective, gamma-band activity is viewed as serving a broad temporal binding function, where single-cell oscillators and the conduction time of the intervening pathways support large multicellular thalamo-cortical resonance that is closely linked with cognition and subjective experience. Our working hypothesis is that although dedicated units achieve sensory processing, the cognitive binding process is a common mechanism across modalities. Moreover, it is proposed that such time-dependent binding when altered, will result in modifications of the sensory motor integration that will affect and impair cognition and conscious perception.

  13. Cortical thinning of the attention and executive function networks in adults with attention-deficit/hyperactivity disorder.

    PubMed

    Makris, Nikos; Biederman, Joseph; Valera, Eve M; Bush, George; Kaiser, Jonathan; Kennedy, David N; Caviness, Verne S; Faraone, Stephen V; Seidman, Larry J

    2007-06-01

    Attention-deficit/hyperactivity disorder (ADHD) has been associated with structural alterations in brain networks influencing cognitive and motor behaviors. Volumetric studies in children identify abnormalities in cortical, striatal, callosal, and cerebellar regions. In a prior volumetric study, we found that ADHD adults had significantly smaller overall cortical gray matter, prefrontal, and anterior cingulate volumes than matched controls. Thickness and surface area are additional indicators of integrity of cytoarchitecture in the cortex. To expand upon our earlier results and further refine the regions of structural abnormality, we carried out a structural magnetic resonance imaging study of cortical thickness in the same sample of adults with ADHD (n = 24) and controls (n = 18), hypothesizing that the cortical networks underlying attention and executive function (EF) would be most affected. Compared with healthy adults, adults with ADHD showed selective thinning of cerebral cortex in the networks that subserve attention and EF. In the present study, we found significant cortical thinning in ADHD in a distinct cortical network supporting attention especially in the right hemisphere involving the inferior parietal lobule, the dorsolateral prefrontal, and the anterior cingulate cortices. This is the first documentation that ADHD in adults is associated with thinner cortex in the cortical networks that modulate attention and EF.

  14. The Causal Inference of Cortical Neural Networks during Music Improvisations

    PubMed Central

    Wan, Xiaogeng; Crüts, Björn; Jensen, Henrik Jeldtoft

    2014-01-01

    We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music) or in improvisation. Each piece of music was performed in two different modes: strict mode and “let-go” mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME), to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and “let-go” mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions. PMID:25489852

  15. The causal inference of cortical neural networks during music improvisations.

    PubMed

    Wan, Xiaogeng; Crüts, Björn; Jensen, Henrik Jeldtoft

    2014-01-01

    We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music) or in improvisation. Each piece of music was performed in two different modes: strict mode and "let-go" mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME), to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and "let-go" mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions.

  16. Integrated approach for studying adaptation mechanisms in the human somatosensory cortical network.

    PubMed

    Venkatesan, Lalit; Barlow, Steven M; Popescu, Mihai; Popescu, Anda

    2014-11-01

    Magnetoencephalography and independent component analysis (ICA) was utilized to study and characterize neural adaptation in the somatosensory cortical network. Repetitive punctate tactile stimuli were applied unilaterally to the dominant hand and face using a custom-built pneumatic stimulator called the TAC-Cell. ICA-based source estimation from the evoked neuromagnetic responses indicated cortical activity in the contralateral primary somatosensory cortex (SI) for face stimulation, while hand stimulation resulted in robust contralateral SI and posterior parietal cortex (PPC) activation. Activity was also observed in the secondary somatosensory cortical area (SII) with reduced amplitude and higher variability across subjects. There was a significant difference in adaptation rate between SI and higher-order somatosensory cortices for hand stimulation. Adaptation was significantly dependent on stimulus frequency and pulse index within the stimulus train for both hand and face stimulation. The peak latency of the activity was significantly dependent on stimulation site (hand vs. face) and cortical area (SI vs. PPC). The difference in the peak latency of activity in SI and PPC is presumed to reflect a hierarchical serial-processing mechanism in the somatosensory cortex.

  17. Simulations of a Microearthquake Network

    NASA Astrophysics Data System (ADS)

    Valtonen, O.; Uski, M.; Korja, A.; Tiira, T.; Kortström, J.

    2012-04-01

    Sites of vulnerable facilities, such as power plants, are required to be evaluated and monitored for possible earthquakes. Seismic networks having a recording capability for microearthquakes are well suited for acquiring more detailed information on local seismicity. When a dense, local seismic network is set up, numerous microearthquakes are expected to be recorded within a relatively short time period. Thus seismotectonic interpretation and seismic hazard evaluation of the area can be improved with the accurately locatable earthquakes recorded by the microearthquake network. This study gives an example of simulations of a local microearthquake network centred around a future power plant -site. The site area is characterised by low intraplate seismicity, with earthquake magnitudes rarely exceeding 4.0. The network is required to fulfil the preconditions of azimuthal coverage better than 180° and automatic event location capability down to ML~0 within the study area. Automatic event detection capability is simulated based on a relationship derived between event magnitude and maximum observation distance. The azimuthal coverage and the threshold magnitude are then computed for different station configurations and the results are presented as contour maps. An optimal configuration of ten seismograph stations is proposed for further on-site research. The threshold magnitude within the study area and the annual number of earthquakes detected by the network are estimated. Also the automatic earthquake location accuracy for horizontal coordinates and depth is approximated. Location accuracy can be further improved by the application of local velocity models and relative location schemes. Modifications to the optimal configuration are expected in the deployment phase, because the area is surrounded by industrial noise sources.

  18. A Multisensory Cortical Network for Understanding Speech in Noise

    PubMed Central

    Bishop, Christopher W.; Miller, Lee M.

    2010-01-01

    In noisy environments, listeners tend to hear a speaker’s voice yet struggle to understand what is said. The most effective way to improve intelligibility in such conditions is to watch the speaker’s mouth movements. Here we identify the neural networks that distinguish understanding from merely hearing speech, and determine how the brain applies visual information to improve intelligibility. Using functional magnetic resonance imaging, we show that understanding speech-in-noise is supported by a network of brain areas including the left superior parietal lobule, the motor/premotor cortex, and the left anterior superior temporal sulcus (STS), a likely apex of the acoustic processing hierarchy. Multisensory integration likely improves comprehension through improved communication between the left temporal–occipital boundary, the left medial-temporal lobe, and the left STS. This demonstrates how the brain uses information from multiple modalities to improve speech comprehension in naturalistic, acoustically adverse conditions. PMID:18823249

  19. Self-organization and neuronal avalanches in networks of dissociated cortical neurons.

    PubMed

    Pasquale, V; Massobrio, P; Bologna, L L; Chiappalone, M; Martinoia, S

    2008-06-02

    Dissociated cortical neurons from rat embryos cultured onto micro-electrode arrays exhibit characteristic patterns of electrophysiological activity, ranging from isolated spikes in the first days of development to highly synchronized bursts after 3-4 weeks in vitro. In this work we analyzed these features by considering the approach proposed by the self-organized criticality theory: we found that networks of dissociated cortical neurons also generate spontaneous events of spreading activity, previously observed in cortical slices, in the form of neuronal avalanches. Choosing an appropriate time scale of observation to detect such neuronal avalanches, we studied the dynamics by considering the spontaneous activity during acute recordings in mature cultures and following the development of the network. We observed different behaviors, i.e. sub-critical, critical or super-critical distributions of avalanche sizes and durations, depending on both the age and the development of cultures. In order to clarify this variability, neuronal avalanches were correlated with other statistical parameters describing the global activity of the network. Criticality was found in correspondence to medium synchronization among bursts and high ratio between bursting and spiking activity. Then, the action of specific drugs affecting global bursting dynamics (i.e. acetylcholine and bicuculline) was investigated to confirm the correlation between criticality and regulated balance between synchronization and variability in the bursting activity. Finally, a computational model of neuronal network was developed in order to interpret the experimental results and understand which parameters (e.g. connectivity, excitability) influence the distribution of avalanches. In summary, cortical neurons preserve their capability to self-organize in an effective network even when dissociated and cultured in vitro. The distribution of avalanche features seems to be critical in those cultures displaying

  20. Cortical network functional connectivity in the descent to sleep.

    PubMed

    Larson-Prior, Linda J; Zempel, John M; Nolan, Tracy S; Prior, Fred W; Snyder, Abraham Z; Raichle, Marcus E

    2009-03-17

    Descent into sleep is accompanied by disengagement of the conscious brain from the external world. It follows that this process should be associated with reduced neural activity in regions of the brain known to mediate interaction with the environment. We examined blood oxygen dependent (BOLD) signal functional connectivity using conventional seed-based analyses in 3 primary sensory and 3 association networks as normal young adults transitioned from wakefulness to light sleep while lying immobile in the bore of a magnetic resonance imaging scanner. Functional connectivity was maintained in each network throughout all examined states of arousal. Indeed, correlations within the dorsal attention network modestly but significantly increased during light sleep compared to wakefulness. Moreover, our data suggest that neuronally mediated BOLD signal variance generally increases in light sleep. These results do not support the view that ongoing BOLD fluctuations primarily reflect unconstrained cognition. Rather, accumulating evidence supports the hypothesis that spontaneous BOLD fluctuations reflect processes that maintain the integrity of functional systems in the brain.

  1. Visual cortical areas of the mouse: comparison of parcellation and network structure with primates

    PubMed Central

    Laramée, Marie-Eve; Boire, Denis

    2015-01-01

    Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals. PMID:25620914

  2. Visual cortical areas of the mouse: comparison of parcellation and network structure with primates.

    PubMed

    Laramée, Marie-Eve; Boire, Denis

    2014-01-01

    Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals.

  3. Cultured networks of excitatory projection neurons and inhibitory interneurons for studying human cortical neurotoxicity.

    PubMed

    Xu, Jin-Chong; Fan, Jing; Wang, Xueqing; Eacker, Stephen M; Kam, Tae-In; Chen, Li; Yin, Xiling; Zhu, Juehua; Chi, Zhikai; Jiang, Haisong; Chen, Rong; Dawson, Ted M; Dawson, Valina L

    2016-04-06

    Translating neuroprotective treatments from discovery in cell and animal models to the clinic has proven challenging. To reduce the gap between basic studies of neurotoxicity and neuroprotection and clinically relevant therapies, we developed a human cortical neuron culture system from human embryonic stem cells or human inducible pluripotent stem cells that generated both excitatory and inhibitory neuronal networks resembling the composition of the human cortex. This methodology used timed administration of retinoic acid to FOXG1(+) neural precursor cells leading to differentiation of neuronal populations representative of the six cortical layers with both excitatory and inhibitory neuronal networks that were functional and homeostatically stable. In human cortical neuronal cultures, excitotoxicity or ischemia due to oxygen and glucose deprivation led to cell death that was dependent on N-methyl-D-aspartate (NMDA) receptors, nitric oxide (NO), and poly(ADP-ribose) polymerase (PARP) (a cell death pathway called parthanatos that is distinct from apoptosis, necroptosis, and other forms of cell death). Neuronal cell death was attenuated by PARP inhibitors that are currently in clinical trials for cancer treatment. This culture system provides a new platform for the study of human cortical neurotoxicity and suggests that PARP inhibitors may be useful for ameliorating excitotoxic and ischemic cell death in human neurons.

  4. Downregulation of Parvalbumin at Cortical GABA Synapses Reduces Network Gamma Oscillatory Activity

    PubMed Central

    Volman, Vladislav; Behrens, M. Margarita; Sejnowski, Terrence J.

    2012-01-01

    Postmortem and functional imaging studies of patients with psychiatric disorders, including schizophrenia, are consistent with a dysfunction of interneurons leading to compromised inhibitory control of network activity. Parvalbumin (PV)-expressing, fast-spiking interneurons interacting with pyramidal neurons generate cortical gamma oscillations (30 – 80 Hz) that synchronize cortical activity during cognitive processing. In postmortem studies of schizophrenia patients, these interneurons show reduced PV and glutamic acid decarboxylase 67 (GAD67), an enzyme that synthesizes GABA, but the consequences of this downregulation are unclear. We developed a biophysically realistic and detailed computational model of a cortical circuit including asynchronous release from GABAergic interneurons to investigate how reductions in PV and GABA affect gamma oscillations induced by sensory stimuli. Networks with reduced GABA were disinhibited and had altered gamma oscillations in response to stimulation; PV-deficient GABA synapses had increased asynchronous release of GABA, which decreased the level of excitation and reduced gamma-band activity. Combined reductions of PV and GABA resulted in a diminished gamma-band oscillatory activity in response to stimuli, similar to that observed in schizophrenia patients. Our results suggest a mechanism by which reduced GAD67 and PV in fast-spiking interneurons may contribute to cortical dysfunction in schizophrenia and related psychiatric disorders. PMID:22159125

  5. Subthalamic stimulation modulates cortical motor network activity and synchronization in Parkinson’s disease

    PubMed Central

    Klotz, Rosa; Govindan, Rathinaswamy B.; Scholten, Marlieke; Naros, Georgios; Ramos-Murguialday, Ander; Bunjes, Friedemann; Meisner, Christoph; Plewnia, Christian; Krüger, Rejko

    2015-01-01

    Dynamic modulations of large-scale network activity and synchronization are inherent to a broad spectrum of cognitive processes and are disturbed in neuropsychiatric conditions including Parkinson’s disease. Here, we set out to address the motor network activity and synchronization in Parkinson’s disease and its modulation with subthalamic stimulation. To this end, 20 patients with idiopathic Parkinson’s disease with subthalamic nucleus stimulation were analysed on externally cued right hand finger movements with 1.5-s interstimulus interval. Simultaneous recordings were obtained from electromyography on antagonistic muscles (right flexor digitorum and extensor digitorum) together with 64-channel electroencephalography. Time-frequency event-related spectral perturbations were assessed to determine cortical and muscular activity. Next, cross-spectra in the time-frequency domain were analysed to explore the cortico-cortical synchronization. The time-frequency modulations enabled us to select a time-frequency range relevant for motor processing. On these time-frequency windows, we developed an extension of the phase synchronization index to quantify the global cortico-cortical synchronization and to obtain topographic differentiations of distinct electrode sites with respect to their contributions to the global phase synchronization index. The spectral measures were used to predict clinical and reaction time outcome using regression analysis. We found that movement-related desynchronization of cortical activity in the upper alpha and beta range was significantly facilitated with ‘stimulation on’ compared to ‘stimulation off’ on electrodes over the bilateral parietal, sensorimotor, premotor, supplementary-motor, and prefrontal areas, including the bilateral inferior prefrontal areas. These spectral modulations enabled us to predict both clinical and reaction time improvement from subthalamic stimulation. With ‘stimulation on’, interhemispheric cortico-cortical

  6. Oscillations and Synchrony in Large-scale Cortical Network Models

    DTIC Science & Technology

    2008-06-17

    Intrinsic neuronal and circuit properties control the responses of large ensembles of neurons by creating spatiotemporal patterns of ...map-based models) to simulate the intrinsic dynamics of biological neurons . These phenomenological models were designed to capture the main response...function of parameters that affect synaptic interactions and intrinsic states of the neurons . Keywords

  7. Covert neurofeedback without awareness shapes cortical network spontaneous connectivity.

    PubMed

    Ramot, Michal; Grossman, Shany; Friedman, Doron; Malach, Rafael

    2016-04-26

    Recent advances in blood oxygen level-dependent-functional MRI (BOLD-fMRI)-based neurofeedback reveal that participants can modulate neuronal properties. However, it is unknown whether such training effects can be introduced in the absence of participants' awareness that they are being trained. Here, we show unconscious neurofeedback training, which consequently produced changes in functional connectivity, introduced in participants who received positive and negative rewards that were covertly coupled to activity in two category-selective visual cortex regions. The results indicate that brain networks can be modified even in the complete absence of intention and awareness of the learning situation, raising intriguing possibilities for clinical interventions.

  8. Extensive video-game experience alters cortical networks for complex visuomotor transformations.

    PubMed

    Granek, Joshua A; Gorbet, Diana J; Sergio, Lauren E

    2010-10-01

    Using event-related functional magnetic resonance imaging (fMRI), we examined the effect of video-game experience on the neural control of increasingly complex visuomotor tasks. Previously, skilled individuals have demonstrated the use of a more efficient movement control brain network, including the prefrontal, premotor, primary sensorimotor and parietal cortices. Our results extend and generalize this finding by documenting additional prefrontal cortex activity in experienced video gamers planning for complex eye-hand coordination tasks that are distinct from actual video-game play. These changes in activation between non-gamers and extensive gamers are putatively related to the increased online control and spatial attention required for complex visually guided reaching. These data suggest that the basic cortical network for processing complex visually guided reaching is altered by extensive video-game play.

  9. Mathematically gifted adolescents mobilize enhanced workspace configuration of theta cortical network during deductive reasoning.

    PubMed

    Zhang, L; Gan, J Q; Wang, H

    2015-03-19

    Previous studies have established the importance of the fronto-parietal brain network in the information processing of reasoning. At the level of cortical source analysis, this eletroencepalogram (EEG) study investigates the functional reorganization of the theta-band (4-8Hz) neurocognitive network of mathematically gifted adolescents during deductive reasoning. Depending on the dense increase of long-range phase synchronizations in the reasoning process, math-gifted adolescents show more significant adaptive reorganization and enhanced "workspace" configuration in the theta network as compared with average-ability control subjects. The salient areas are mainly located in the anterior cortical vertices of the fronto-parietal network. Further correlation analyses have shown that the enhanced workspace configuration with respect to the global topological metrics of the theta network in math-gifted subjects is correlated with the intensive frontal midline theta (fm theta) response that is related to strong neural effort for cognitive events. These results suggest that by investing more cognitive resources math-gifted adolescents temporally mobilize an enhanced task-related global neuronal workspace, which is manifested as a highly integrated fronto-parietal information processing network during the reasoning process.

  10. Altered Modular Organization of Structural Cortical Networks in Children with Autism

    PubMed Central

    Shi, Feng; Wang, Li; Peng, Ziwen; Wee, Chong-Yaw; Shen, Dinggang

    2013-01-01

    Autism is a complex developmental disability that characterized by deficits in social interaction, language skills, repetitive stereotyped behaviors and restricted interests. Although great heterogeneity exists, previous findings suggest that autism has atypical brain connectivity patterns and disrupted small-world network properties. However, the organizational alterations in the autistic brain network are still poorly understood. We explored possible organizational alterations of 49 autistic children and 51 typically developing controls, by investigating their brain network metrics that are constructed upon cortical thickness correlations. Three modules were identified in controls, including cortical regions associated with brain functions of executive strategic, spatial/auditory/visual, and self-reference/episodic memory. There are also three modules found in autistic children with similar patterns. Compared with controls, autism demonstrates significantly reduced gross network modularity, and a larger number of inter-module connections. However, the autistic brain network demonstrates increased intra- and inter-module connectivity in brain regions including middle frontal gyrus, inferior parietal gyrus, and cingulate, suggesting one underlying compensatory mechanism associated with brain functions of self-reference and episodic memory. Results also show that there is increased correlation strength between regions inside frontal lobe, as well as impaired correlation strength between frontotemporal and frontoparietal regions. This alteration of correlation strength may contribute to the organization alteration of network structures in autistic brains. PMID:23675456

  11. Regulating Cortical Oscillations in an Inhibition-Stabilized Network

    PubMed Central

    Jadi, Monika P.; Sejnowski, Terrence J.

    2014-01-01

    Understanding the anatomical and functional architecture of the brain is essential for designing neurally inspired intelligent systems. Theoretical and empirical studies suggest a role for narrowband oscillations in shaping the functional architecture of the brain through their role in coding and communication of information. Such oscillations are ubiquitous signals in the electrical activity recorded from the brain. In the cortex, oscillations detected in the gamma range (30–80 Hz) are modulated by behavioral states and sensory features in complex ways. How is this regulation achieved? Although several underlying principles for the genesis of these oscillations have been proposed, a unifying account for their regulation has remained elusive. In a network of excitatory and inhibitory neurons operating in an inhibition-stabilized regime, we show that strongly superlinear responses of inhibitory neurons facilitate bidirectional regulation of oscillation frequency and power. In such a network, the balance of drives to the excitatory and inhibitory populations determines how the power and frequency of oscillations are modulated. The model accounts for the puzzling increase in their frequency with the salience of visual stimuli, and a decrease with their size. Oscillations in our model grow stronger as the mean firing level is reduced, accounting for the size dependence of visually evoked gamma rhythms, and suggesting a role for oscillations in improving the signal-to-noise ratio (SNR) of signals in the brain. Empirically testing such predictions is still challenging, and implementing the proposed coding and communication strategies in neuromorphic systems could assist in our understanding of the biological system. PMID:24966414

  12. Reversible large–scale modification of cortical networks during neuroprosthetic control

    PubMed Central

    Ganguly, Karunesh; Wallis, Jonathan D.

    2012-01-01

    Brain-Machine Interfaces (BMI) provide a framework to study cortical dynamics and the neural correlates of learning. Neuroprosthetic control has been associated with tuning changes in specific neurons directly projecting to the BMI (hereafter ‘direct neurons’). However, little is known about the larger network dynamics. By monitoring ensembles of neurons that were either causally linked to BMI control or indirectly involved, here we show that proficient neuroprosthetic control is associated with large-scale modifications to the cortical network in macaque monkeys. Specifically, there were changes in the preferred direction of both direct and indirect neurons. Interestingly, with learning, there was a relative decrease in the net modulation of indirect neural activity in comparison to the direct activity. These widespread differential changes in the direct and indirect population activity were remarkably stable from one day to the next and readily coexisted with the long-standing cortical network for upper limb control. Thus, the process of learning BMI control is associated with differential modification of neural populations based on their specific relation to movement control. PMID:21499255

  13. Human brain networks in cognitive decline: a graph theoretical analysis of cortical connectivity from EEG data.

    PubMed

    Vecchio, Fabrizio; Miraglia, Francesca; Marra, Camillo; Quaranta, Davide; Vita, Maria Gabriella; Bramanti, Placido; Rossini, Paolo Maria

    2014-01-01

    The aim of this study was to investigate the neuronal network characteristics in physiological and pathological brain aging. A database of 378 participants divided in three groups was analyzed: Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal elderly (Nold) subjects. Through EEG recordings, cortical sources were evaluated by sLORETA software, while graph theory parameters (Characteristic Path Length λ, Clustering coefficient γ, and small-world network σ) were computed to the undirected and weighted networks, obtained by the lagged linear coherence evaluated by eLORETA software. EEG cortical sources from spectral analysis showed significant differences in delta, theta, and alpha 1 bands. Furthermore, the analysis of eLORETA cortical connectivity suggested that for the normalized Characteristic Path Length (λ) the pattern differences between normal cognition and dementia were observed in the theta band (MCI subjects are find similar to healthy subjects), while for the normalized Clustering coefficient (γ) a significant increment was found for AD group in delta, theta, and alpha 1 bands; finally, the small world (σ) parameter presented a significant interaction between AD and MCI groups showing a theta increase in MCI. The fact that AD patients respect the MCI subjects were significantly impaired in theta but not in alpha bands connectivity are in line with the hypothesis of an intermediate status of MCI between normal condition and overt dementia.

  14. Different categories of living and non-living sound-sources activate distinct cortical networks.

    PubMed

    Engel, Lauren R; Frum, Chris; Puce, Aina; Walker, Nathan A; Lewis, James W

    2009-10-01

    With regard to hearing perception, it remains unclear as to whether, or the extent to which, different conceptual categories of real-world sounds and related categorical knowledge are differentially represented in the brain. Semantic knowledge representations are reported to include the major divisions of living versus non-living things, plus more specific categories including animals, tools, biological motion, faces, and places-categories typically defined by their characteristic visual features. Here, we used functional magnetic resonance imaging (fMRI) to identify brain regions showing preferential activity to four categories of action sounds, which included non-vocal human and animal actions (living), plus mechanical and environmental sound-producing actions (non-living). The results showed a striking antero-posterior division in cortical representations for sounds produced by living versus non-living sources. Additionally, there were several significant differences by category, depending on whether the task was category-specific (e.g. human or not) versus non-specific (detect end-of-sound). In general, (1) human-produced sounds yielded robust activation in the bilateral posterior superior temporal sulci independent of task. Task demands modulated activation of left lateralized fronto-parietal regions, bilateral insular cortices, and sub-cortical regions previously implicated in observation-execution matching, consistent with "embodied" and mirror-neuron network representations subserving recognition. (2) Animal action sounds preferentially activated the bilateral posterior insulae. (3) Mechanical sounds activated the anterior superior temporal gyri and parahippocampal cortices. (4) Environmental sounds preferentially activated dorsal occipital and medial parietal cortices. Overall, this multi-level dissociation of networks for preferentially representing distinct sound-source categories provides novel support for grounded cognition models that may underlie

  15. Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm

    PubMed Central

    Dura-Bernal, Salvador; Zhou, Xianlian; Neymotin, Samuel A.; Przekwas, Andrzej; Francis, Joseph T.; Lytton, William W.

    2015-01-01

    Embedding computational models in the physical world is a critical step towards constraining their behavior and building practical applications. Here we aim to drive a realistic musculoskeletal arm model using a biomimetic cortical spiking model, and make a robot arm reproduce the same trajectories in real time. Our cortical model consisted of a 3-layered cortex, composed of several hundred spiking model-neurons, which display physiologically realistic dynamics. We interconnected the cortical model to a two-joint musculoskeletal model of a human arm, with realistic anatomical and biomechanical properties. The virtual arm received muscle excitations from the neuronal model, and fed back proprioceptive information, forming a closed-loop system. The cortical model was trained using spike timing-dependent reinforcement learning to drive the virtual arm in a 2D reaching task. Limb position was used to simultaneously control a robot arm using an improved network interface. Virtual arm muscle activations responded to motoneuron firing rates, with virtual arm muscles lengths encoded via population coding in the proprioceptive population. After training, the virtual arm performed reaching movements which were smoother and more realistic than those obtained using a simplistic arm model. This system provided access to both spiking network properties and to arm biophysical properties, including muscle forces. The use of a musculoskeletal virtual arm and the improved control system allowed the robot arm to perform movements which were smoother than those reported in our previous paper using a simplistic arm. This work provides a novel approach consisting of bidirectionally connecting a cortical model to a realistic virtual arm, and using the system output to drive a robotic arm in real time. Our techniques are applicable to the future development of brain neuroprosthetic control systems, and may enable enhanced brain-machine interfaces with the possibility for finer control of

  16. Cortical Spiking Network Interfaced with Virtual Musculoskeletal Arm and Robotic Arm.

    PubMed

    Dura-Bernal, Salvador; Zhou, Xianlian; Neymotin, Samuel A; Przekwas, Andrzej; Francis, Joseph T; Lytton, William W

    2015-01-01

    Embedding computational models in the physical world is a critical step towards constraining their behavior and building practical applications. Here we aim to drive a realistic musculoskeletal arm model using a biomimetic cortical spiking model, and make a robot arm reproduce the same trajectories in real time. Our cortical model consisted of a 3-layered cortex, composed of several hundred spiking model-neurons, which display physiologically realistic dynamics. We interconnected the cortical model to a two-joint musculoskeletal model of a human arm, with realistic anatomical and biomechanical properties. The virtual arm received muscle excitations from the neuronal model, and fed back proprioceptive information, forming a closed-loop system. The cortical model was trained using spike timing-dependent reinforcement learning to drive the virtual arm in a 2D reaching task. Limb position was used to simultaneously control a robot arm using an improved network interface. Virtual arm muscle activations responded to motoneuron firing rates, with virtual arm muscles lengths encoded via population coding in the proprioceptive population. After training, the virtual arm performed reaching movements which were smoother and more realistic than those obtained using a simplistic arm model. This system provided access to both spiking network properties and to arm biophysical properties, including muscle forces. The use of a musculoskeletal virtual arm and the improved control system allowed the robot arm to perform movements which were smoother than those reported in our previous paper using a simplistic arm. This work provides a novel approach consisting of bidirectionally connecting a cortical model to a realistic virtual arm, and using the system output to drive a robotic arm in real time. Our techniques are applicable to the future development of brain neuroprosthetic control systems, and may enable enhanced brain-machine interfaces with the possibility for finer control of

  17. Stimulation of the Posterior Cortical-Hippocampal Network Enhances Precision of Memory Recollection.

    PubMed

    Nilakantan, Aneesha S; Bridge, Donna J; Gagnon, Elise P; VanHaerents, Stephen A; Voss, Joel L

    2017-02-06

    Episodic memory is thought to critically depend on interaction of the hippocampus with distributed brain regions [1-3]. Specific contributions of distinct networks have been hypothesized, with the hippocampal posterior-medial (HPM) network implicated in the recollection of highly precise contextual and spatial information [3-6]. Current evidence for HPM specialization is mostly indirect, derived from correlative measures such as neural activity recordings. Here we tested the causal role of the HPM network in recollection using network-targeted noninvasive brain stimulation in humans, which has previously been shown to increase functional connectivity within the HPM network [7]. Effects of multiple-day electromagnetic stimulation were assessed using an object-location memory task that segregated recollection precision from general recollection success. HPM network-targeted stimulation produced lasting (∼24 hr) enhancement of recollection precision, without effects on general success. Canonical neural correlates of recollection [8-10] were also modulated by stimulation. Late-positive evoked potential amplitude and theta-alpha oscillatory power were reduced, suggesting that stimulation can improve memory through enhanced reactivation of detailed visuospatial information at retrieval. The HPM network was thus specifically implicated in the processing of fine-grained memory detail, supporting functional specialization of hippocampal-cortical networks. These findings demonstrate that brain networks can be causally linked to distinct and specific neurocognitive functions and suggest mechanisms for long-lasting changes in memory due to network-targeted stimulation.

  18. The Age of Cortical Neural Networks Affects Their Interactions with Magnetic Nanoparticles.

    PubMed

    Tay, Andy; Kunze, Anja; Jun, Dukwoo; Hoek, Eric; Di Carlo, Dino

    2016-07-01

    Despite increasing use of nanotechnology in neuroscience, the characterization of interactions between magnetic nanoparticles (MNPs) and primary cortical neural networks remains underdeveloped. In particular, how the age of primary neural networks affects MNP uptake and endocytosis is critical when considering MNP-based therapies for age-related diseases. Here, primary cortical neural networks are cultured up to 4 weeks and with CCL11/eotaxin, an age-inducing chemokine, to create aged neural networks. As the neural networks are aged, their association with membrane-bound starch-coated ferromagnetic nanoparticles (fMNPs) increases while their endocytic mechanisms are impaired, resulting in reduced internalization of chitosan-coated fMNPs. The age of the neurons also negates the neuroprotective effects of chitosan coatings on fMNPs, attributing to decreased intracellular trafficking and increased colocalization of MNPs with lysosomes. These findings demonstrate the importance of age and developmental stage of primary neural cells when developing in vitro models for fMNP therapeutics targeting age-related diseases.

  19. Cortical Networks Involved in Memory for Temporal Order.

    PubMed

    Manelis, Anna; Popov, Vencislav; Paynter, Christopher; Walsh, Matthew; Wheeler, Mark E; Vogt, Keith M; Reder, Lynne M

    2017-03-15

    We examined the neurobiological basis of temporal resetting, an aspect of temporal order memory, using a version of the delayed-match-to-multiple-sample task. While in an fMRI scanner, participants evaluated whether an item was novel or whether it had appeared before or after a reset event that signified the start of a new block of trials. Participants responded "old" to items that were repeated within the current block and "new" to both novel items and items that had last appeared before the reset event (pseudonew items). Medial-temporal, prefrontal, and occipital regions responded to absolute novelty of the stimulus-they differentiated between novel items and previously seen items, but not between old and pseudonew items. Activation for pseudonew items in the frontopolar and parietal regions, in contrast, was intermediate between old and new items. The posterior cingulate cortex extending to precuneus was the only region that showed complete temporal resetting, and its activation reflected whether an item was new or old according to the task instructions regardless of its familiarity. There was also a significant Condition (old/pseudonew) × Familiarity (second/third presentations) interaction effect on behavioral and neural measures. For pseudonew items, greater familiarity decreased response accuracy, increased RTs, increased ACC activation, and increased functional connectivity between ACC and the left frontal pole. The reverse was observed for old items. On the basis of these results, we propose a theoretical framework in which temporal resetting relies on an episodic retrieval network that is modulated by cognitive control and conflict resolution.

  20. Bayesian network classifiers for categorizing cortical GABAergic interneurons.

    PubMed

    Mihaljević, Bojan; Benavides-Piccione, Ruth; Bielza, Concha; DeFelipe, Javier; Larrañaga, Pedro

    2015-04-01

    An accepted classification of GABAergic interneurons of the cerebral cortex is a major goal in neuroscience. A recently proposed taxonomy based on patterns of axonal arborization promises to be a pragmatic method for achieving this goal. It involves characterizing interneurons according to five axonal arborization features, called F1-F5, and classifying them into a set of predefined types, most of which are established in the literature. Unfortunately, there is little consensus among expert neuroscientists regarding the morphological definitions of some of the proposed types. While supervised classifiers were able to categorize the interneurons in accordance with experts' assignments, their accuracy was limited because they were trained with disputed labels. Thus, here we automatically classify interneuron subsets with different label reliability thresholds (i.e., such that every cell's label is backed by at least a certain (threshold) number of experts). We quantify the cells with parameters of axonal and dendritic morphologies and, in order to predict the type, also with axonal features F1-F4 provided by the experts. Using Bayesian network classifiers, we accurately characterize and classify the interneurons and identify useful predictor variables. In particular, we discriminate among reliable examples of common basket, horse-tail, large basket, and Martinotti cells with up to 89.52% accuracy, and single out the number of branches at 180 μm from the soma, the convex hull 2D area, and the axonal features F1-F4 as especially useful predictors for distinguishing among these types. These results open up new possibilities for an objective and pragmatic classification of interneurons.

  1. Reinforce Networking Theory with OPNET Simulation

    ERIC Educational Resources Information Center

    Guo, Jinhua; Xiang, Weidong; Wang, Shengquan

    2007-01-01

    As networking systems have become more complex and expensive, hands-on experiments based on networking simulation have become essential for teaching the key computer networking topics to students. The simulation approach is the most cost effective and highly useful because it provides a virtual environment for an assortment of desirable features…

  2. Activity Changes Induced by Spatio-Temporally Correlated Stimuli in Cultured Cortical Networks

    NASA Astrophysics Data System (ADS)

    Takayama, Yuzo; Moriguchi, Hiroyuki; Jimbo, Yasuhiko

    Activity-dependent plasticity probably plays a key role in learning and memory in biological information processing systems. Though long-term potentiation and depression have been extensively studied in the filed of neuroscience, little is known on the mechanisms for integrating these modifications on network-wide activity changes. In this report, we studied effects of spatio-temporally correlated stimuli on the neuronal network activity. Rat cortical neurons were cultured on substrates with 64 embedded micro-electrodes and the evoked responses were extracellularly recorded and analyzed. We compared spatio-temporal patterns of the responses between before and after repetitive application of correlated stimuli. After the correlated stimuli, the networks showed significantly different responses from those in the initial states. The modified activity reflected structures of the repeatedly applied correlated stimuli. The results suggested that spatiotemporally correlated inputs systematically induced modification of synaptic strengths in neuronal networks, which could serve as an underlying mechanism of associative memory.

  3. Information capacity and transmission are maximized in balanced cortical networks with neuronal avalanches.

    PubMed

    Shew, Woodrow L; Yang, Hongdian; Yu, Shan; Roy, Rajarshi; Plenz, Dietmar

    2011-01-05

    The repertoire of neural activity patterns that a cortical network can produce constrains the ability of the network to transfer and process information. Here, we measured activity patterns obtained from multisite local field potential recordings in cortex cultures, urethane-anesthetized rats, and awake macaque monkeys. First, we quantified the information capacity of the pattern repertoire of ongoing and stimulus-evoked activity using Shannon entropy. Next, we quantified the efficacy of information transmission between stimulus and response using mutual information. By systematically changing the ratio of excitation/inhibition (E/I) in vitro and in a network model, we discovered that both information capacity and information transmission are maximized at a particular intermediate E/I, at which ongoing activity emerges as neuronal avalanches. Next, we used our in vitro and model results to correctly predict in vivo information capacity and interactions between neuronal groups during ongoing activity. Close agreement between our experiments and model suggest that neuronal avalanches and peak information capacity arise because of criticality and are general properties of cortical networks with balanced E/I.

  4. Spatially constrained adaptive rewiring in cortical networks creates spatially modular small world architectures.

    PubMed

    Jarman, Nicholas; Trengove, Chris; Steur, Erik; Tyukin, Ivan; van Leeuwen, Cees

    2014-12-01

    A modular small-world topology in functional and anatomical networks of the cortex is eminently suitable as an information processing architecture. This structure was shown in model studies to arise adaptively; it emerges through rewiring of network connections according to patterns of synchrony in ongoing oscillatory neural activity. However, in order to improve the applicability of such models to the cortex, spatial characteristics of cortical connectivity need to be respected, which were previously neglected. For this purpose we consider networks endowed with a metric by embedding them into a physical space. We provide an adaptive rewiring model with a spatial distance function and a corresponding spatially local rewiring bias. The spatially constrained adaptive rewiring principle is able to steer the evolving network topology to small world status, even more consistently so than without spatial constraints. Locally biased adaptive rewiring results in a spatial layout of the connectivity structure, in which topologically segregated modules correspond to spatially segregated regions, and these regions are linked by long-range connections. The principle of locally biased adaptive rewiring, thus, may explain both the topological connectivity structure and spatial distribution of connections between neuronal units in a large-scale cortical architecture.

  5. Aberrant Topological Patterns of Structural Cortical Networks in Psychogenic Erectile Dysfunction

    PubMed Central

    Zhao, Lu; Guan, Min; Zhu, Xiaobo; Karama, Sherif; Khundrakpam, Budhachandra; Wang, Meiyun; Dong, Minghao; Qin, Wei; Tian, Jie; Evans, Alan C.; Shi, Dapeng

    2015-01-01

    Male sexual arousal (SA) has been known as a multidimensional experience involving closely interrelated and coordinated neurobehavioral components that rely on widespread brain regions. Recent functional neuroimaging studies have shown relation between abnormal/altered dynamics in these circuits and male sexual dysfunction. However, alterations in the topological1 organization of structural brain networks in male sexual dysfunction are still unclear. Here, we used graph theory2 to investigate the topological properties of large-scale structural brain networks, which were constructed using inter-regional correlations of cortical thickness between 78 cortical regions in 40 patients with psychogenic erectile dysfunction (pED) and 39 normal controls. Compared with normal controls, pED patients exhibited a less optimal global topological organization with reduced global and increased local efficiencies. Our results suggest disrupted neural integration among distant brain regions in pED patients, consistent with previous reports of impaired white matter structure and abnormal functional integrity in pED. Additionally, disrupted global network topology in pED was observed to be primarily relevant to altered subnetwork and nodal properties within the networks mediating the cognitive, motivational and inhibitory processes of male SA, possibly indicating disrupted integration of these networks in the whole brain networks and might account for pED patients' abnormal cognitive, motivational and inhibitory processes for male SA. In total, our findings provide evidence for disrupted integrity in large-scale brain networks underlying the neurobehavioral processes of male SA in pED and provide new insights into the understanding of the pathophysiological mechanisms of pED. PMID:26733849

  6. Different categories of living and non-living sound-sources activate distinct cortical networks

    PubMed Central

    Engel, Lauren R.; Frum, Chris; Puce, Aina; Walker, Nathan A.; Lewis, James W.

    2009-01-01

    With regard to hearing perception, it remains unclear as to whether, or the extent to which, different conceptual categories of real-world sounds and related categorical knowledge are differentially represented in the brain. Semantic knowledge representations are reported to include the major divisions of living versus non-living things, plus more specific categories including animals, tools, biological motion, faces, and places—categories typically defined by their characteristic visual features. Here, we used functional magnetic resonance imaging (fMRI) to identify brain regions showing preferential activity to four categories of action sounds, which included non-vocal human and animal actions (living), plus mechanical and environmental sound-producing actions (non-living). The results showed a striking antero-posterior division in cortical representations for sounds produced by living versus non-living sources. Additionally, there were several significant differences by category, depending on whether the task was category-specific (e.g. human or not) versus non-specific (detect end-of-sound). In general, (1) human-produced sounds yielded robust activation in the bilateral posterior superior temporal sulci independent of task. Task demands modulated activation of left-lateralized fronto-parietal regions, bilateral insular cortices, and subcortical regions previously implicated in observation-execution matching, consistent with “embodied” and mirror-neuron network representations subserving recognition. (2) Animal action sounds preferentially activated the bilateral posterior insulae. (3) Mechanical sounds activated the anterior superior temporal gyri and parahippocampal cortices. (4) Environmental sounds preferentially activated dorsal occipital and medial parietal cortices. Overall, this multi-level dissociation of networks for preferentially representing distinct sound-source categories provides novel support for grounded cognition models that may

  7. Framework for Network Co-Simulation

    SciTech Connect

    Daily, Jeff; Ciraci, PNNL Selim; Fuller, PNNL Jason; Marinovici, PNNL Laurentiu; Fisher, PNNL Andrew; Lo, PNNL Chaomei; Hauer, PNNL Matthew

    2014-01-09

    The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations can be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.

  8. Brief wide-field photostimuli evoke and modulate oscillatory reverberating activity in cortical networks

    PubMed Central

    Pulizzi, Rocco; Musumeci, Gabriele; Van den Haute, Chris; Van De Vijver, Sebastiaan; Baekelandt, Veerle; Giugliano, Michele

    2016-01-01

    Cell assemblies manipulation by optogenetics is pivotal to advance neuroscience and neuroengineering. In in vivo applications, photostimulation often broadly addresses a population of cells simultaneously, leading to feed-forward and to reverberating responses in recurrent microcircuits. The former arise from direct activation of targets downstream, and are straightforward to interpret. The latter are consequence of feedback connectivity and may reflect a variety of time-scales and complex dynamical properties. We investigated wide-field photostimulation in cortical networks in vitro, employing substrate-integrated microelectrode arrays and long-term cultured neuronal networks. We characterized the effect of brief light pulses, while restricting the expression of channelrhodopsin to principal neurons. We evoked robust reverberating responses, oscillating in the physiological gamma frequency range, and found that such a frequency could be reliably manipulated varying the light pulse duration, not its intensity. By pharmacology, mathematical modelling, and intracellular recordings, we conclude that gamma oscillations likely emerge as in vivo from the excitatory-inhibitory interplay and that, unexpectedly, the light stimuli transiently facilitate excitatory synaptic transmission. Of relevance for in vitro models of (dys)functional cortical microcircuitry and in vivo manipulations of cell assemblies, we give for the first time evidence of network-level consequences of the alteration of synaptic physiology by optogenetics. PMID:27099182

  9. Cortical network for gaze control in humans revealed using multimodal MRI.

    PubMed

    Anderson, Elaine J; Jones, Derek K; O'Gorman, Ruth L; Leemans, Alexander; Catani, Marco; Husain, Masud

    2012-04-01

    Functional magnetic resonance imaging (fMRI) techniques allow definition of cortical nodes that are presumed to be components of large-scale distributed brain networks involved in cognitive processes. However, very few investigations examine whether such functionally defined areas are in fact structurally connected. Here, we used combined fMRI and diffusion MRI-based tractography to define the cortical network involved in saccadic eye movement control in humans. The results of this multimodal imaging approach demonstrate white matter pathways connecting the frontal eye fields and supplementary eye fields, consistent with the known connectivity of these regions in macaque monkeys. Importantly, however, these connections appeared to be more prominent in the right hemisphere of humans. In addition, there was evidence of a dorsal frontoparietal pathway connecting the frontal eye field and the inferior parietal lobe, also right hemisphere dominant, consistent with specialization of the right hemisphere for directed attention in humans. These findings demonstrate the utility and potential of using multimodal imaging techniques to define large-scale distributed brain networks, including those that demonstrate known hemispheric asymmetries in humans.

  10. Basal ganglia and cortical networks for sequential ordering and rhythm of complex movements

    PubMed Central

    Bednark, Jeffery G.; Campbell, Megan E. J.; Cunnington, Ross

    2015-01-01

    Voluntary actions require the concurrent engagement and coordinated control of complex temporal (e.g., rhythm) and ordinal motor processes. Using high-resolution functional magnetic resonance imaging (fMRI) and multi-voxel pattern analysis (MVPA), we sought to determine the degree to which these complex motor processes are dissociable in basal ganglia and cortical networks. We employed three different finger-tapping tasks that differed in the demand on the sequential temporal rhythm or sequential ordering of submovements. Our results demonstrate that sequential rhythm and sequential order tasks were partially dissociable based on activation differences. The sequential rhythm task activated a widespread network centered around the supplementary motor area (SMA) and basal-ganglia regions including the dorsomedial putamen and caudate nucleus, while the sequential order task preferentially activated a fronto-parietal network. There was also extensive overlap between sequential rhythm and sequential order tasks, with both tasks commonly activating bilateral premotor, supplementary motor, and superior/inferior parietal cortical regions, as well as regions of the caudate/putamen of the basal ganglia and the ventro-lateral thalamus. Importantly, within the cortical regions that were active for both complex movements, MVPA could accurately classify different patterns of activation for the sequential rhythm and sequential order tasks. In the basal ganglia, however, overlapping activation for the sequential rhythm and sequential order tasks, which was found in classic motor circuits of the putamen and ventro-lateral thalamus, could not be accurately differentiated by MVPA. Overall, our results highlight the convergent architecture of the motor system, where complex motor information that is spatially distributed in the cortex converges into a more compact representation in the basal ganglia. PMID:26283945

  11. The Impact of Cortical Lesions on Thalamo-Cortical Network Dynamics after Acute Ischaemic Stroke: A Combined Experimental and Theoretical Study

    PubMed Central

    van Wijngaarden, Joeri B. G.; Finnigan, Simon

    2016-01-01

    The neocortex and thalamus provide a core substrate for perception, cognition, and action, and are interconnected through different direct and indirect pathways that maintain specific dynamics associated with functional states including wakefulness and sleep. It has been shown that a lack of excitation, or enhanced subcortical inhibition, can disrupt this system and drive thalamic nuclei into an attractor state of low-frequency bursting and further entrainment of thalamo-cortical circuits, also called thalamo-cortical dysrhythmia (TCD). The question remains however whether similar TCD-like phenomena can arise with a cortical origin. For instance, in stroke, a cortical lesion could disrupt thalamo-cortical interactions through an attenuation of the excitatory drive onto the thalamus, creating an imbalance between excitation and inhibition that can lead to a state of TCD. Here we tested this hypothesis by comparing the resting-state EEG recordings of acute ischaemic stroke patients (N = 21) with those of healthy, age-matched control-subjects (N = 17). We observed that these patients displayed the hallmarks of TCD: a characteristic downward shift of dominant α-peaks in the EEG power spectra, together with increased power over the lower frequencies (δ and θ-range). Contrary to general observations in TCD, the patients also displayed a broad reduction in β-band activity. In order to explain the genesis of this stroke-induced TCD, we developed a biologically constrained model of a general thalamo-cortical module, allowing us to identify the specific cellular and network mechanisms involved. Our model showed that a lesion in the cortical component leads to sustained cell membrane hyperpolarization in the corresponding thalamic relay neurons, that in turn leads to the de-inactivation of voltage-gated T-type Ca2+-channels, switching neurons from tonic spiking to a pathological bursting regime. This thalamic bursting synchronises activity on a population level through

  12. Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects

    PubMed Central

    Zubler, Frederic; Hauri, Andreas; Pfister, Sabina; Bauer, Roman; Anderson, John C.; Whatley, Adrian M.; Douglas, Rodney J.

    2013-01-01

    Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms. PMID:23966845

  13. Simulating cortical development as a self constructing process: a novel multi-scale approach combining molecular and physical aspects.

    PubMed

    Zubler, Frederic; Hauri, Andreas; Pfister, Sabina; Bauer, Roman; Anderson, John C; Whatley, Adrian M; Douglas, Rodney J

    2013-01-01

    Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

  14. Meeting the memory challenges of brain-scale network simulation.

    PubMed

    Kunkel, Susanne; Potjans, Tobias C; Eppler, Jochen M; Plesser, Hans Ekkehard; Morrison, Abigail; Diesmann, Markus

    2011-01-01

    The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity, and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10(5) neurons with up to 10(9) synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been investigated in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Blue Gene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of neuronal simulators as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place. As a consequence, development cycles can be shorter and

  15. The Scaphoid Safe Zone: A Radiographic Simulation Study to Prevent Cortical Perforation Arising from Different Views

    PubMed Central

    Chang, Biao; Liu, Ruoxi; Zhu, Yun; Peng, Jiang; Zhao, Qing; Lu, Shibi

    2017-01-01

    Purpose The purpose of this study was to simulate and calculate the probability of iatrogenic perforation of the scaphoid cortical bone when internal fixation appeared to be safe on radiographs. The results will assist surgeons in determining proper screw placement. Methods Thirty scaphoids were reconstructed using computed tomography data and image-processing software. Different central axes were determined by the software to simulate the surgical views. The safe zone (SZ) and risk zone (RZ) were identified on the axial projection radiographs by comparing the scaphoid bone stenosis measured by the fluoroscopic radiographs with a three-dimensional reconstruction of the scaphoid stenosis. Each original axial projection radiograph was zoomed and compiled to match a calculated average image. The RZ, SZ, and probability of perforations in various quadrants were calculated. Results Using a volar view (approach), the mean risks of cortical perforation were 25% with screws and 36% with k-wires. Using a dorsal view (approach), the mean risks of cortical perforation were 18% with screws and 30% with k-wires. A high risk of perforation was detected at the ulnar–dorsal zone. Conclusion Surgeons should be wary of screws that appear to lie close to the scaphoid cortex on both anteroposterior (AP) and lateral radiographs, particularly in the ulnar–dorsal and radial–dorsal quadrants, because such screws are likely to perforate the cortex. The position of the internal fixator should be assessed using a diagram outlining the various SZs. Therapeutic, Level III. PMID:28114317

  16. The Alzheimer Structural Connectome: Changes in Cortical Network Topology with Increased Amyloid Plaque Burden

    PubMed Central

    Guidon, Arnaud; Doraiswamy, P. Murali; Roy Choudhury, Kingshuk; Liu, Chunlei; Petrella, Jeffrey R.

    2014-01-01

    ), independent of brain region. For every 0.1-unit increase in florbetapir SUVr, there was a 14% decrease in strength, an 11% decrease in weighted local efficiency, and a 9% decrease in weighted clustering coefficient, regardless of the analyzed cortical region or, in the case of weighted local efficiency and clustering coefficient, diagnostic group. Conclusion Increased amyloid burden, as measured with florbetapir PET imaging, is related to changes in the topology of the large-scale cortical network architecture of the brain, as measured with graph theoretical metrics of DTI tractography, even in the preclinical stages of AD. © RSNA, 2014 Online supplemental material is available for this article. PMID:24865310

  17. The global landscape of cognition: hierarchical aggregation as an organizational principle of human cortical networks and functions

    PubMed Central

    Taylor, P.; Hobbs, J. N.; Burroni, J.; Siegelmann, H. T.

    2015-01-01

    Though widely hypothesized, limited evidence exists that human brain functions organize in global gradients of abstraction starting from sensory cortical inputs. Hierarchical representation is accepted in computational networks, and tentatively in visual neuroscience, yet no direct holistic demonstrations exist in vivo. Our methods developed network models enriched with tiered directionality, by including input locations, a critical feature for localizing representation in networks generally. Grouped primary sensory cortices defined network inputs, displaying global connectivity to fused inputs. Depth-oriented networks guided analyses of fMRI databases (~17,000 experiments;~1/4 of fMRI literature). Formally, we tested whether network depth predicted localization of abstract versus concrete behaviors over the whole set of studied brain regions. For our results, new cortical graph metrics, termed network-depth, ranked all databased cognitive function activations by network-depth. Thus, we objectively sorted stratified landscapes of cognition, starting from grouped sensory inputs in parallel, progressing deeper into cortex. This exposed escalating amalgamation of function or abstraction with increasing network-depth, globally. Nearly 500 new participants confirmed our results. In conclusion, data-driven analyses defined a hierarchically ordered connectome, revealing a related continuum of cognitive function. Progressive functional abstraction over network depth may be a fundamental feature of brains, and is observed in artificial networks. PMID:26669858

  18. Maximal variability of phase synchrony in cortical networks with neuronal avalanches.

    PubMed

    Yang, Hongdian; Shew, Woodrow L; Roy, Rajarshi; Plenz, Dietmar

    2012-01-18

    Ongoing interactions among cortical neurons often manifest as network-level synchrony. Understanding the spatiotemporal dynamics of such spontaneous synchrony is important because it may (1) influence network response to input, (2) shape activity-dependent microcircuit structure, and (3) reveal fundamental network properties, such as an imbalance of excitation (E) and inhibition (I). Here we delineate the spatiotemporal character of spontaneous synchrony in rat cortex slice cultures and a computational model over a range of different E-I conditions including disfacilitated (antagonized AMPA, NMDA receptors), unperturbed, and disinhibited (antagonized GABA(A) receptors). Local field potential was recorded with multielectrode arrays during spontaneous burst activity. Synchrony among neuronal groups was quantified based on phase-locking among recording sites. As network excitability was increased from low to high, we discovered three phenomena at an intermediate excitability level: (1) onset of synchrony, (2) maximized variability of synchrony, and (3) neuronal avalanches. Our computational model predicted that these three features occur when the network operates near a unique balanced E-I condition called "criticality." These results were invariant to changes in the measurement spatial extent, spatial resolution, and frequency bands. Our findings indicate that moderate average synchrony, which is required to avoid pathology, occurs over a limited range of E-I conditions and emerges together with maximally variable synchrony. If variable synchrony is detrimental to cortical function, this is a cost paid for moderate average synchrony. However, if variable synchrony is beneficial, then by operating near criticality the cortex may doubly benefit from moderate mean and maximized variability of synchrony.

  19. Structural Organization of the Laryngeal Motor Cortical Network and Its Implication for Evolution of Speech Production

    PubMed Central

    Kumar, Veena; Croxson, Paula L.

    2016-01-01

    The laryngeal motor cortex (LMC) is essential for the production of learned vocal behaviors because bilateral damage to this area renders humans unable to speak but has no apparent effect on innate vocalizations such as human laughing and crying or monkey calls. Several hypotheses have been put forward attempting to explain the evolutionary changes from monkeys to humans that potentially led to enhanced LMC functionality for finer motor control of speech production. These views, however, remain limited to the position of the larynx area within the motor cortex, as well as its connections with the phonatory brainstem regions responsible for the direct control of laryngeal muscles. Using probabilistic diffusion tractography in healthy humans and rhesus monkeys, we show that, whereas the LMC structural network is largely comparable in both species, the LMC establishes nearly 7-fold stronger connectivity with the somatosensory and inferior parietal cortices in humans than in macaques. These findings suggest that important “hard-wired” components of the human LMC network controlling the laryngeal component of speech motor output evolved from an already existing, similar network in nonhuman primates. However, the evolution of enhanced LMC–parietal connections likely allowed for more complex synchrony of higher-order sensorimotor coordination, proprioceptive and tactile feedback, and modulation of learned voice for speech production. SIGNIFICANCE STATEMENT The role of the primary motor cortex in the formation of a comprehensive network controlling speech and language has been long underestimated and poorly studied. Here, we provide comparative and quantitative evidence for the significance of this region in the control of a highly learned and uniquely human behavior: speech production. From the viewpoint of structural network organization, we discuss potential evolutionary advances of enhanced temporoparietal cortical connections with the laryngeal motor cortex in

  20. Program Helps Simulate Neural Networks

    NASA Technical Reports Server (NTRS)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  1. Effects of Small-World Rewiring Probability and Noisy Synaptic Conductivity on Slow Waves: Cortical Network.

    PubMed

    Tekin, Ramazan; Tagluk, Mehmet Emin

    2017-03-01

    Physiological rhythms play a critical role in the functional development of living beings. Many biological functions are executed with an interaction of rhythms produced by internal characteristics of scores of cells. While synchronized oscillations may be associated with normal brain functions, anomalies in these oscillations may cause or relate the emergence of some neurological or neuropsychological pathologies. This study was designed to investigate the effects of topological structure and synaptic conductivity noise on the spatial synchronization and temporal rhythmicity of the waves generated by cells in the network. Because of holding the ability of clustering and randomizing with change of parameters, small-world (SW) network topology was chosen. The oscillatory activity of network was tried out by manipulating an insulated SW, cortical network model whose morphology is very close to real world. According to the obtained results, it was observed that at the optimal probabilistic rates of conductivity noise and rewiring of SW, powerful synchronized oscillatory small waves are generated in relation to the internal dynamics of cells, which are in line with the network's input. These two parameters were observed to be quite effective on the excitation-inhibition balance of the network. Accordingly, it may be suggested that the topological dynamics of SW and noisy synaptic conductivity may be associated with the normal and abnormal development of neurobiological structure.

  2. Dynamics and effective topology underlying synchronization in networks of cortical neurons.

    PubMed

    Eytan, Danny; Marom, Shimon

    2006-08-16

    Cognitive processes depend on synchronization and propagation of electrical activity within and between neuronal assemblies. In vivo measurements show that the size of individual assemblies depends on their function and varies considerably, but the timescale of assembly activation is in the range of 0.1-0.2 s and is primarily independent of assembly size. Here we use an in vitro experimental model of cortical assemblies to characterize the process underlying the timescale of synchronization, its relationship to the effective topology of connectivity within an assembly, and its impact on propagation of activity within and between assemblies. We show that the basic mode of assembly activation, "network spike," is a threshold-governed, synchronized population event of 0.1-0.2 s duration and follows the logistics of neuronal recruitment in an effectively scale-free connected network. Accordingly, the sequence of neuronal activation within a network spike is nonrandom and hierarchical; a small subset of neurons is consistently recruited tens of milliseconds before others. Theory predicts that scale-free topology allows for synchronization time that does not increase markedly with network size; our experiments with networks of different densities support this prediction. The activity of early-to-fire neurons reliably forecasts an upcoming network spike and provides means for expedited propagation between assemblies. We demonstrate this capacity by observing the dynamics of two artificially coupled assemblies in vitro, using neuronal activity of one as a trigger for electrical stimulation of the other.

  3. Inhibition of microRNA 128 promotes excitability of cultured cortical neuronal networks

    PubMed Central

    McSweeney, K. Melodi; Gussow, Ayal B.; Bradrick, Shelton S.; Dugger, Sarah A.; Gelfman, Sahar; Wang, Quanli; Petrovski, Slavé; Frankel, Wayne N.; Boland, Michael J.; Goldstein, David B.

    2016-01-01

    Cultured neuronal networks monitored with microelectrode arrays (MEAs) have been used widely to evaluate pharmaceutical compounds for potential neurotoxic effects. A newer application of MEAs has been in the development of in vitro models of neurological disease. Here, we directly evaluated the utility of MEAs to recapitulate in vivo phenotypes of mature microRNA-128 (miR-128) deficiency, which causes fatal seizures in mice. We show that inhibition of miR-128 results in significantly increased neuronal activity in cultured neuronal networks derived from primary mouse cortical neurons. These results support the utility of MEAs in developing in vitro models of neuroexcitability disorders, such as epilepsy, and further suggest that MEAs provide an effective tool for the rapid identification of microRNAs that promote seizures when dysregulated. PMID:27516621

  4. Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network.

    PubMed

    Gulsuner, Suleyman; Walsh, Tom; Watts, Amanda C; Lee, Ming K; Thornton, Anne M; Casadei, Silvia; Rippey, Caitlin; Shahin, Hashem; Nimgaonkar, Vishwajit L; Go, Rodney C P; Savage, Robert M; Swerdlow, Neal R; Gur, Raquel E; Braff, David L; King, Mary-Claire; McClellan, Jon M

    2013-08-01

    Genes disrupted in schizophrenia may be revealed by de novo mutations in affected persons from otherwise healthy families. Furthermore, during normal brain development, genes are expressed in patterns specific to developmental stage and neuroanatomical structure. We identified de novo mutations in persons with schizophrenia and then mapped the responsible genes onto transcriptome profiles of normal human brain tissues from age 13 weeks gestation to adulthood. In the dorsolateral and ventrolateral prefrontal cortex during fetal development, genes harboring damaging de novo mutations in schizophrenia formed a network significantly enriched for transcriptional coexpression and protein interaction. The 50 genes in the network function in neuronal migration, synaptic transmission, signaling, transcriptional regulation, and transport. These results suggest that disruptions of fetal prefrontal cortical neurogenesis are critical to the pathophysiology of schizophrenia. These results also support the feasibility of integrating genomic and transcriptome analyses to map critical neurodevelopmental processes in time and space in the brain.

  5. Inhibition of microRNA 128 promotes excitability of cultured cortical neuronal networks.

    PubMed

    McSweeney, K Melodi; Gussow, Ayal B; Bradrick, Shelton S; Dugger, Sarah A; Gelfman, Sahar; Wang, Quanli; Petrovski, Slavé; Frankel, Wayne N; Boland, Michael J; Goldstein, David B

    2016-10-01

    Cultured neuronal networks monitored with microelectrode arrays (MEAs) have been used widely to evaluate pharmaceutical compounds for potential neurotoxic effects. A newer application of MEAs has been in the development of in vitro models of neurological disease. Here, we directly evaluated the utility of MEAs to recapitulate in vivo phenotypes of mature microRNA-128 (miR-128) deficiency, which causes fatal seizures in mice. We show that inhibition of miR-128 results in significantly increased neuronal activity in cultured neuronal networks derived from primary mouse cortical neurons. These results support the utility of MEAs in developing in vitro models of neuroexcitability disorders, such as epilepsy, and further suggest that MEAs provide an effective tool for the rapid identification of microRNAs that promote seizures when dysregulated.

  6. Situating the default-mode network along a principal gradient of macroscale cortical organization.

    PubMed

    Margulies, Daniel S; Ghosh, Satrajit S; Goulas, Alexandros; Falkiewicz, Marcel; Huntenburg, Julia M; Langs, Georg; Bezgin, Gleb; Eickhoff, Simon B; Castellanos, F Xavier; Petrides, Michael; Jefferies, Elizabeth; Smallwood, Jonathan

    2016-11-01

    Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface-and are precisely equidistant-from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.

  7. Situating the default-mode network along a principal gradient of macroscale cortical organization

    PubMed Central

    Margulies, Daniel S.; Goulas, Alexandros; Falkiewicz, Marcel; Huntenburg, Julia M.; Langs, Georg; Bezgin, Gleb; Eickhoff, Simon B.; Castellanos, F. Xavier; Petrides, Michael; Jefferies, Elizabeth; Smallwood, Jonathan

    2016-01-01

    Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface—and are precisely equidistant—from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input. PMID:27791099

  8. Auditory cortical delta-entrainment interacts with oscillatory power in multiple fronto-parietal networks.

    PubMed

    Keitel, Anne; Ince, Robin A A; Gross, Joachim; Kayser, Christoph

    2017-02-15

    The timing of slow auditory cortical activity aligns to the rhythmic fluctuations in speech. This entrainment is considered to be a marker of the prosodic and syllabic encoding of speech, and has been shown to correlate with intelligibility. Yet, whether and how auditory cortical entrainment is influenced by the activity in other speech-relevant areas remains unknown. Using source-localized MEG data, we quantified the dependency of auditory entrainment on the state of oscillatory activity in fronto-parietal regions. We found that delta band entrainment interacted with the oscillatory activity in three distinct networks. First, entrainment in the left anterior superior temporal gyrus (STG) was modulated by beta power in orbitofrontal areas, possibly reflecting predictive top-down modulations of auditory encoding. Second, entrainment in the left Heschl's Gyrus and anterior STG was dependent on alpha power in central areas, in line with the importance of motor structures for phonological analysis. And third, entrainment in the right posterior STG modulated theta power in parietal areas, consistent with the engagement of semantic memory. These results illustrate the topographical network interactions of auditory delta entrainment and reveal distinct cross-frequency mechanisms by which entrainment can interact with different cognitive processes underlying speech perception.

  9. Ghrelin stimulates synaptic formation in cultured cortical networks in a dose-dependent manner.

    PubMed

    Stoyanova, Irina I; le Feber, Joost; Rutten, Wim L C

    2013-09-10

    Ghrelin was initially related to appetite stimulation and growth hormone secretion. However, it also has a neuroprotective effect in neurodegenerative diseases and regulates cognitive function. The cellular basis of these processes is related to synaptic efficacy and plasticity. Previous studies indicated that ghrelin has an excitatory effect on neuronal activity, and stimulates synaptic plasticity in vivo. Plasticity in the adult brain occurs in many different ways, including changes in synapse morphology and number. Therefore, we used in vitro neuronal cultures to investigate how ghrelin affects synaptogenesis. We used dissociated cortical cultures of newborn rats, chronically treated with different doses of ghrelin (0.5, 1, 1.5 and 2μM). After one-, two-, three- or four weeks cultures were immunostained for the presynaptic marker synaptophysin. In parallel, additional groups of non-treated cultures were immunostained for detection of ghrelin receptor (GHSR1). During development, GHSR1was increasingly expressed in all type of neurons, as well as the synaptophysin. Synaptic density depended on ghrelin concentration, and was much higher than in controls in all age groups. In conclusion, ghrelin leads to earlier network formation in dissociated cortical networks and an increase in number of synapses. The effect is probably mediated by GHSR1. These findings suggest that ghrelin may provide a novel therapeutic strategy for the treatment of disorders related to synaptic impairment.

  10. Geometric-attributes-based segmentation of cortical bone slides using optimized neural networks.

    PubMed

    Hage, Ilige S; Hamade, Ramsey F

    2016-05-01

    In cortical bone, solid (lamellar and interstitial) matrix occupies space left over by porous microfeatures such as Haversian canals, lacunae, and canaliculi-containing clusters. In this work, pulse-coupled neural networks (PCNN) were used to automatically distinguish the microfeatures present in histology slides of cortical bone. The networks' parameters were optimized using particle swarm optimization (PSO). When forming the fitness functions for the PSO, we considered the microfeatures' geometric attributes-namely, their size (based on measures of elliptical perimeter or area), shape (based on measures of compactness or the ratio of minor axis length to major axis length), and a two-way combination of these two geometric attributes. This hybrid PCNN-PSO method was further enhanced for pulse evaluation by combination with yet another method, adaptive threshold (AT), where the PCNN algorithm is repeated until the best threshold is found corresponding to the maximum variance between two segmented regions. Together, this framework of using PCNN-PSO-AT constitutes, we believe, a novel framework in biomedical imaging. Using this framework and extracting microfeatures from only one training image, we successfully extracted microfeatures from other test images. The high fidelity of all resultant segments was established using quantitative metrics such as precision, specificity, and Dice indices.

  11. Frequency-selective control of cortical and subcortical networks by central thalamus

    PubMed Central

    Liu, Jia; Lee, Hyun Joo; Weitz, Andrew J; Fang, Zhongnan; Lin, Peter; Choy, ManKin; Fisher, Robert; Pinskiy, Vadim; Tolpygo, Alexander; Mitra, Partha; Schiff, Nicholas; Lee, Jin Hyung

    2015-01-01

    Central thalamus plays a critical role in forebrain arousal and organized behavior. However, network-level mechanisms that link its activity to brain state remain enigmatic. Here, we combined optogenetics, fMRI, electrophysiology, and video-EEG monitoring to characterize the central thalamus-driven global brain networks responsible for switching brain state. 40 and 100 Hz stimulations of central thalamus caused widespread activation of forebrain, including frontal cortex, sensorimotor cortex, and striatum, and transitioned the brain to a state of arousal in asleep rats. In contrast, 10 Hz stimulation evoked significantly less activation of forebrain, inhibition of sensory cortex, and behavioral arrest. To investigate possible mechanisms underlying the frequency-dependent cortical inhibition, we performed recordings in zona incerta, where 10, but not 40, Hz stimulation evoked spindle-like oscillations. Importantly, suppressing incertal activity during 10 Hz central thalamus stimulation reduced the evoked cortical inhibition. These findings identify key brain-wide dynamics underlying central thalamus arousal regulation. DOI: http://dx.doi.org/10.7554/eLife.09215.001 PMID:26652162

  12. Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

    PubMed

    Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

    2014-01-01

    Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

  13. 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

  14. Characterization of Early Cortical Neural Network Development in Multiwell Microelectrode Array Plates

    PubMed Central

    Cotterill, Ellese; Hall, Diana; Wallace, Kathleen; Mundy, William R.; Eglen, Stephen J.; Shafer, Timothy J.

    2016-01-01

    We examined neural network ontogeny using microelectrode array (MEA) recordings made in multiwell MEA (mwMEA) plates over the first 12 days in vitro (DIV). In primary cortical cultures, action potential spiking activity developed rapidly between DIV 5 and 12. Spiking was sporadic and unorganized at early DIV, and became progressively more organized with time, with bursting parameters, synchrony, and network bursting increasing between DIV 5 and 12. We selected 12 features to describe network activity; principal components analysis using these features demonstrated segregation of data by age at both the well and plate levels. Using random forest classifiers and support vector machines, we demonstrated that four features (coefficient of variation [CV] of within-burst interspike interval, CV of interburst interval, network spike rate, and burst rate) could predict the age of each well recording with >65% accuracy. When restricting the classification to a binary decision, accuracy improved to as high as 95%. Further, we present a novel resampling approach to determine the number of wells needed for comparing different treatments. Overall, these results demonstrate that network development on mwMEA plates is similar to development in single-well MEAs. The increased throughput of mwMEAs will facilitate screening drugs, chemicals, or disease states for effects on neurodevelopment. PMID:27028607

  15. Assessment of simulated and functional disuse on cortical bone by nuclear magnetic resonance

    NASA Astrophysics Data System (ADS)

    Ni, Qingwen; De Los Santos, Armando; Lam, Hoyan; Qin, Yi-Xian

    A nuclear magnetic resonance (NMR) spin ( T2) relaxation technique has been described for determining water distribution changes on turkey cortical bone tissue of simulated weightlessness (disuse) in vitro. The advantages of using NMR T2 relaxation techniques for bone water distribution are illustrated. The Carr-Purcell-Meiboom-Gill (CPMG) T2 relaxation data can be used to determine the porosity of bone, and can be inverted to T2 relaxation distribution, and this distribution then can be transformed to a pore size distribution with the longer relaxation times corresponding to larger pores. The free induction delay (FID) T2 relaxation data can be inverted to T2 relaxation distribution and this distribution then can be transformed to bound and mobile water distribution with the longest relaxation time corresponding to mobile water and the middle relaxation time corresponding to bound water. The technique is applied to quantify apparent changes in porosity, bound and mobile water in normal and disuse cortical bone. Overall bone porosity is determined using the calibrated NMR fluid volume from the proton relaxation data divided by overall bone volume. The NMR bound and mobile water changes were determined from cortical bone specimens obtained from normal and disuse turkey bones. Differences in porosity and water distribution were found between specimens from normal and disuse. Our results show that the ratio of the average bound to mobile water in bone from normal turkey is higher than in bone from disuse turkey, and the porosity is lower in normal than in disuse turkey. We also show that the average bone porosity multiplied by the ratio of bound to mobile water may be constant for both normal and disuse bone groups. Currently, the influence of water removal on the strength and toughness of cortical bone has been studied by some researchers. Therefore, the porosity, bound and mobile water distribution changes could provide further information directly related to bone

  16. Increased Functional Connectivity Between Subcortical and Cortical Resting-State Networks in Autism Spectrum Disorder

    PubMed Central

    Cerliani, Leonardo; Mennes, Maarten; Thomas, Rajat M.; Di Martino, Adriana; Thioux, Marc; Keysers, Christian

    2016-01-01

    Importance Individuals with autism spectrum disorder (ASD) exhibit severe difficulties in social interaction, motor coordination, behavioral flexibility, and atypical sensory processing, with considerable interindividual variability. This heterogeneous set of symptoms recently led to investigating the presence of abnormalities in the interaction across large-scale brain networks. To date, studies have focused either on constrained sets of brain regions or whole-brain analysis, rather than focusing on the interaction between brain networks. Objectives To compare the intrinsic functional connectivity between brain networks in a large sample of individuals with ASD and typically developing control subjects and to estimate to what extent group differences would predict autistic traits and reflect different developmental trajectories. Design, Setting, and Participants We studied 166 male individuals (mean age, 17.6 years; age range, 7-50 years) diagnosed as having DSM-IV-TR autism or Asperger syndrome and 193 typical developing male individuals (mean age, 16.9 years; age range, 6.5-39.4 years) using resting-state functional magnetic resonance imaging (MRI). Participants were matched for age, IQ, head motion, and eye status (open or closed) in the MRI scanner. We analyzed data from the Autism Brain Imaging Data Exchange (ABIDE), an aggregated MRI data set from 17 centers, made public in August 2012. Main Outcomes and Measures We estimated correlations between time courses of brain networks extracted using a data-driven method (independent component analysis). Subsequently, we associated estimates of interaction strength between networks with age and autistic traits indexed by the Social Responsiveness Scale. Results Relative to typically developing control participants, individuals with ASD showed increased functional connectivity between primary sensory networks and subcortical networks (thalamus and basal ganglia) (all t ≥ 3.13, P < .001 corrected). The strength of

  17. The quality of cortical network function recovery depends on localization and degree of axonal demyelination.

    PubMed

    Cerina, Manuela; Narayanan, Venu; Göbel, Kerstin; Bittner, Stefan; Ruck, Tobias; Meuth, Patrick; Herrmann, Alexander M; Stangel, Martin; Gudi, Viktoria; Skripuletz, Thomas; Daldrup, Thiemo; Wiendl, Heinz; Seidenbecher, Thomas; Ehling, Petra; Kleinschnitz, Christoph; Pape, Hans-Christian; Budde, Thomas; Meuth, Sven G

    2017-01-01

    Myelin loss is a severe pathological hallmark common to a number of neurodegenerative diseases, including multiple sclerosis (MS). Demyelination in the central nervous system appears in the form of lesions affecting both white and gray matter structures. The functional consequences of demyelination on neuronal network and brain function are not well understood. Current therapeutic strategies for ameliorating the course of such diseases usually focus on promoting remyelination, but the effectiveness of these approaches strongly depends on the timing in relation to the disease state. In this study, we sought to characterize the time course of sensory and behavioral alterations induced by de- and remyelination to establish a rational for the use of remyelination strategies. By taking advantage of animal models of general and focal demyelination, we tested the consequences of myelin loss on the functionality of the auditory thalamocortical system: a well-studied neuronal network consisting of both white and gray matter regions. We found that general demyelination was associated with a permanent loss of the tonotopic cortical organization in vivo, and the inability to induce tone-frequency-dependent conditioned behaviors, a status persisting after remyelination. Targeted, focal lysolecithin-induced lesions in the white matter fiber tract, but not in the gray matter regions of cortex, were fully reversible at the morphological, functional and behavioral level. These findings indicate that remyelination of white and gray matter lesions have a different functional regeneration potential, with the white matter being able to regain full functionality while cortical gray matter lesions suffer from permanently altered network function. Therefore therapeutic interventions aiming for remyelination have to consider both region- and time-dependent strategies.

  18. Dynamic cortical networks of verbal and spatial working memory: effects of memory load and task practice.

    PubMed

    McEvoy, L K; Smith, M E; Gevins, A

    1998-01-01

    Working memory (WM), the ability to briefly retain and manipulate information in mind, is central to intelligent behavior. Here we take advantage of the high temporal resolution of electrophysiological measures to obtain a millisecond timescale view of the activity induced in distributed cortical networks by tasks that impose significant WM demands. We examined how these networks are affected by the type and amount of information to be remembered, and by the amount of task practice. Evoked potentials (EPs) were obtained from eight subjects performing spatial and verbal versions of a visual n-back WM task (n = 1, 2, 3) on each of three testing days. In well-trained subjects, WM tasks elicited transient responses reflecting different subcomponents of task processing, including transient (lasting 0.02-0.3 s) task-sensitive and load-sensitive EPs, as well as sustained responses (lasting 1-1.5 s), including the prestimulus Contingent Negative Variation (CNV), and post-stimulus frontal and parietal Slow Waves. The transient responses, with the exception of the P300, differed between the verbal and spatial task versions, and between trials with different response requirements. The P300 and the Slow Waves were not affected by task version but were affected by increased WM load. These results suggest that WM emerges from the formation of a dynamic cortical network linking task-specific processes with non-specific, capacity-limited, higher-order attentional processes. Practice effects on the EPs suggested that practice led to the development of a more effective cognitive strategy for dealing with lower-order aspects of task processing, but did not diminish demands made on higher order processes. Thus a simple WM task is shown to be composed of numerous elementary subsecond neural processes whose characteristics vary with type and amount of information being remembered, and amount of practice.

  19. Posterior Cingulate, Precuneal & Retrosplenial Cortices: Cytology & Components of the Neural Network Correlates of Consciousness*

    PubMed Central

    Vogt, Brent A.; Laureys, Steven

    2008-01-01

    Neuronal aggregates involved in conscious awareness are not evenly distributed throughout the CNS but are comprised of key components referred to as the neural network correlates of consciousness (NNCC). A critical node in this network is the retrosplenial, posterior cingulate, and precuneal cortices (RSC/PCC/PrCC). The cytological and neurochemical composition of this region is reviewed in relation to the Brodmann map. This region has the highest level of brain glucose metabolism and cytochrome c oxidase activity. Monkey studies suggest that the anterior thalamic projection likely drives RSC and PCC metabolism and that the midbrain projection to the anteroventral thalamic nucleus is a key coupling site between the brainstem system for arousal and cortical systems for cognitive processing and awareness. The pivotal role of RSC/PCC/PrCC in consciousness is demonstrated with posterior cingulate epilepsy cases, midcingulate lesions that de-afferent this region and are associated with unilateral sensory neglect, observations from stroke and vegetative state patients, alterations in blood flow during sleep, and the actions of anesthetics. Since this region is critically involved in self reflection, it is not surprising that it is similarly a site for the NNCC. Interestingly, information processing during complex cognitive tasks and during aversive sensations such as pain induces efforts to terminate self reflection and result in decreased processing in PCC/PrCC. Finally, anatomical relations between the neural correlates of mind and NNCC in the cingulate gyrus do not appear to overlap and suggests that mental function and conscious awareness may be mediated by two neural networks. PMID:16186025

  20. A bilateral cortical network responds to pitch perturbations in speech feedback.

    PubMed

    Kort, Naomi S; Nagarajan, Srikantan S; Houde, John F

    2014-02-01

    Auditory feedback is used to monitor and correct for errors in speech production, and one of the clearest demonstrations of this is the pitch perturbation reflex. During ongoing phonation, speakers respond rapidly to shifts of the pitch of their auditory feedback, altering their pitch production to oppose the direction of the applied pitch shift. In this study, we examine the timing of activity within a network of brain regions thought to be involved in mediating this behavior. To isolate auditory feedback processing relevant for motor control of speech, we used magnetoencephalography (MEG) to compare neural responses to speech onset and to transient (400ms) pitch feedback perturbations during speaking with responses to identical acoustic stimuli during passive listening. We found overlapping, but distinct bilateral cortical networks involved in monitoring speech onset and feedback alterations in ongoing speech. Responses to speech onset during speaking were suppressed in bilateral auditory and left ventral supramarginal gyrus/posterior superior temporal sulcus (vSMG/pSTS). In contrast, during pitch perturbations, activity was enhanced in bilateral vSMG/pSTS, bilateral premotor cortex, right primary auditory cortex, and left higher order auditory cortex. We also found speaking-induced delays in responses to both unaltered and altered speech in bilateral primary and secondary auditory regions, left vSMG/pSTS and right premotor cortex. The network dynamics reveal the cortical processing involved in both detecting the speech error and updating the motor plan to create the new pitch output. These results implicate vSMG/pSTS as critical in both monitoring auditory feedback and initiating rapid compensation to feedback errors.

  1. Distinct cortical networks for the detection and identification of human body.

    PubMed

    Hodzic, Amra; Kaas, Amanda; Muckli, Lars; Stirn, Aglaja; Singer, Wolf

    2009-05-01

    In the human brain information about bodies and faces is processed in specialized cortical regions named EBA and FBA (extrastriate and fusiform body area) and OFA and FFA (occipital and fusiform face area), respectively. Here we investigate with functional magnetic resonance imaging (fMRI) the cortical areas responsible for the identification of individual bodies and the distinction between 'self' and 'others'. To this end we presented subjects with images of unfamiliar and familiar bodies and their own body. We identified separate coactivation networks for body-detection (processing body related information), body-identification (processing of information relating to individual bodies) and self-identification (distinction of self from others). Body detection involves the EBA in both hemispheres, and in the right hemisphere: the FBA and areas in the IPL (inferior parietal lobe). Body identification involves areas in the inferior frontal gyrus (IFG) of both hemispheres and in the right hemisphere areas in the medial frontal gyrus (MFG), in the cingulate gyrus (CG), in the central (CS) and the post-central sulcus (PCS), in the inferior parietal lobe (IPL) and the FBA. When the recognition of one's own body is contrasted to the identification of familiar bodies, differential activation is observed in areas of the inferior parietal lobe (IPL) and inferior parietal sulcus (IPS) of the right hemisphere, and in the posterior orbital gyrus (pOrbG) and in the lateral occipital gyrus (LOG) of the left hemisphere. Thus, identification of individual bodies and self-other distinction involve in addition to the classical occipito-parietal network a parieto-frontal network. Interestingly, the EBA shows no differential activation for distinctions between familiar or unfamiliar bodies or recognition of one's own body.

  2. Neuromodulation of thought: flexibilities and vulnerabilities in prefrontal cortical network synapses.

    PubMed

    Arnsten, Amy F T; Wang, Min J; Paspalas, Constantinos D

    2012-10-04

    This review describes unique neuromodulatory influences on working memory prefrontal cortical (PFC) circuits that coordinate cognitive strength with arousal state. Working memory arises from recurrent excitation within layer III PFC pyramidal cell NMDA circuits, which are afflicted in aging and schizophrenia. Neuromodulators rapidly and flexibly alter the efficacy of these synaptic connections, while leaving the synaptic architecture unchanged, a process called dynamic network connectivity (DNC). Increases in calcium-cAMP signaling open ion channels in long, thin spines, gating network connections. Inhibition of calcium-cAMP signaling by stimulating α2A-adrenoceptors on spines strengthens synaptic efficacy and increases network firing, whereas optimal stimulation of dopamine D1 receptors sculpts network inputs to refine mental representation. Generalized increases in calcium-cAMP signaling during fatigue or stress disengage dlPFC recurrent circuits, reduce firing and impair top-down cognition. Impaired DNC regulation contributes to age-related cognitive decline, while genetic insults to DNC proteins are commonly linked to schizophrenia.

  3. Neuromodulation of Thought: Flexibilities and Vulnerabilities in Prefrontal Cortical Network Synapses

    PubMed Central

    Arnsten, Amy F.T.; Wang, Min J.; Paspalas, Constantinos D.

    2012-01-01

    Summary In this review, we discuss how working memory prefrontal cortical (PFC) circuits are modulated differently than plastic changes in sensory/motor and subcortical circuits. Working memory arises from recurrent excitation within layer III PFC pyramidal cell NMDA circuits, which are afflicted in aging and schizophrenia. Neuromodulators rapidly and flexibly alter the efficacy of these synaptic connections, while leaving the synaptic architecture unchanged, a process called Dynamic Network Connectivity (DNC). Increases in calcium-cAMP signaling open ion channels in long, thin spines, gating network connections. Inhibition of calcium-cAMP signaling, e.g. by noradrenergic α2A-adrenoceptor stimulation on spines, strengthens synaptic efficacy and increases network firing, while optimal levels of dopamine D1 receptor stimulation sculpt network inputs to refine mental representation. Generalized increases in calcium-cAMP signaling during fatigue or stress disengage dlPFC recurrent circuits, reduce firing and impair top-down cognition. Impaired DNC regulation contributes to age-related cognitive decline, while genetic insults to DNC proteins are commonly linked to schizophrenia. PMID:23040817

  4. Network algorithmics and the emergence of information integration in cortical models

    NASA Astrophysics Data System (ADS)

    Nathan, Andre; Barbosa, Valmir C.

    2011-07-01

    An information-theoretic framework known as integrated information theory (IIT) has been introduced recently for the study of the emergence of consciousness in the brain [D. Balduzzi and G. Tononi, PLoS Comput. Biol.1553-734X10.1371/journal.pcbi.1000091 4, e1000091 (2008)]. IIT purports that this phenomenon is to be equated with the generation of information by the brain surpassing the information that the brain’s constituents already generate independently of one another. IIT is not fully plausible in its modeling assumptions nor is it testable due to severe combinatorial growth embedded in its key definitions. Here we introduce an alternative to IIT which, while inspired in similar information-theoretic principles, seeks to address some of IIT’s shortcomings to some extent. Our alternative framework uses the same network-algorithmic cortical model we introduced earlier [A. Nathan and V. C. Barbosa, Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.81.021916 81, 021916 (2010)] and, to allow for somewhat improved testability relative to IIT, adopts the well-known notions of information gain and total correlation applied to a set of variables representing the reachability of neurons by messages in the model’s dynamics. We argue that these two quantities relate to each other in such a way that can be used to quantify the system’s efficiency in generating information beyond that which does not depend on integration. We give computational results on our cortical model and on variants thereof that are either structurally random in the sense of an Erdős-Rényi random directed graph or structurally deterministic. We have found that our cortical model stands out with respect to the others in the sense that many of its instances are capable of integrating information more efficiently than most of those others’ instances.

  5. Network algorithmics and the emergence of information integration in cortical models.

    PubMed

    Nathan, Andre; Barbosa, Valmir C

    2011-07-01

    An information-theoretic framework known as integrated information theory (IIT) has been introduced recently for the study of the emergence of consciousness in the brain [D. Balduzzi and G. Tononi, PLoS Comput. Biol. 4, e1000091 (2008)]. IIT purports that this phenomenon is to be equated with the generation of information by the brain surpassing the information that the brain's constituents already generate independently of one another. IIT is not fully plausible in its modeling assumptions nor is it testable due to severe combinatorial growth embedded in its key definitions. Here we introduce an alternative to IIT which, while inspired in similar information-theoretic principles, seeks to address some of IIT's shortcomings to some extent. Our alternative framework uses the same network-algorithmic cortical model we introduced earlier [A. Nathan and V. C. Barbosa, Phys. Rev. E 81, 021916 (2010)] and, to allow for somewhat improved testability relative to IIT, adopts the well-known notions of information gain and total correlation applied to a set of variables representing the reachability of neurons by messages in the model's dynamics. We argue that these two quantities relate to each other in such a way that can be used to quantify the system's efficiency in generating information beyond that which does not depend on integration. We give computational results on our cortical model and on variants thereof that are either structurally random in the sense of an Erdős-Rényi random directed graph or structurally deterministic. We have found that our cortical model stands out with respect to the others in the sense that many of its instances are capable of integrating information more efficiently than most of those others' instances.

  6. Theta-burst Transcranial Magnetic Stimulation Alters the Functional Topography of the Cortical Motor Network

    PubMed Central

    NOH, Nor Azila; FUGGETTA, Giorgio; MANGANOTTI, Paolo

    2015-01-01

    Background: Transcranial magnetic stimulation (TMS) is a non-invasive tool that is able to modulate the electrical activity of the brain depending upon its protocol of stimulation. Theta burst stimulation (TBS) is a high-frequency TMS protocol that is able to induce prolonged plasticity changes in the brain. The induction of plasticity-like effects by TBS is useful in both experimental and therapeutic settings; however, the underlying neural mechanisms of this modulation remain unclear. The aim of this study was to investigate the effects of continuous TBS (cTBS) on the intrahemispheric and interhemispheric functional connectivity of the resting and active brain. Methods: A total of 26 healthy humans were randomly divided into two groups that received either real cTBS or sham (control) over the left primary motor cortex. Surface electroencephalogram (EEG) was used to quantify the changes of neural oscillations after cTBS at rest and after a choice reaction time test. The cTBS-induced EEG oscillations were computed using spectral analysis of event-related coherence (ERCoh) of theta (4–7.5 Hz), low alpha (8–9.5 Hz), high alpha (10–12.5 Hz), low beta (13–19.5 Hz), and high beta (20–30 Hz) brain rhythms. Results: We observed a global decrease in functional connectivity of the brain in the cTBS group when compared to sham in the low beta brain rhythm at rest and high beta brain rhythm during the active state. In particular, EEG spectral analysis revealed that high-frequency beta, a cortically generated brain rhythm, was the most sensitive band that was modulated by cTBS. Conclusion: Overall, our findings suggest that cTBS, a TMS protocol that mimics the mechanism of long-term depression of synaptic plasticity, modulates motor network oscillations primarily at the cortical level and might interfere with cortical information coding. PMID:27006636

  7. Abnormal dopaminergic modulation of striato-cortical networks underlies levodopa-induced dyskinesias in humans.

    PubMed

    Herz, Damian M; Haagensen, Brian N; Christensen, Mark S; Madsen, Kristoffer H; Rowe, James B; Løkkegaard, Annemette; Siebner, Hartwig R

    2015-06-01

    Dopaminergic signalling in the striatum contributes to reinforcement of actions and motivational enhancement of motor vigour. Parkinson's disease leads to progressive dopaminergic denervation of the striatum, impairing the function of cortico-basal ganglia networks. While levodopa therapy alleviates basal ganglia dysfunction in Parkinson's disease, it often elicits involuntary movements, referred to as levodopa-induced peak-of-dose dyskinesias. Here, we used a novel pharmacodynamic neuroimaging approach to identify the changes in cortico-basal ganglia connectivity that herald the emergence of levodopa-induced dyskinesias. Twenty-six patients with Parkinson's disease (age range: 51-84 years; 11 females) received a single dose of levodopa and then performed a task in which they had to produce or suppress a movement in response to visual cues. Task-related activity was continuously mapped with functional magnetic resonance imaging. Dynamic causal modelling was applied to assess levodopa-induced modulation of effective connectivity between the pre-supplementary motor area, primary motor cortex and putamen when patients suppressed a motor response. Bayesian model selection revealed that patients who later developed levodopa-induced dyskinesias, but not patients without dyskinesias, showed a linear increase in connectivity between the putamen and primary motor cortex after levodopa intake during movement suppression. Individual dyskinesia severity was predicted by levodopa-induced modulation of striato-cortical feedback connections from putamen to the pre-supplementary motor area (Pcorrected = 0.020) and primary motor cortex (Pcorrected = 0.044), but not feed-forward connections from the cortex to the putamen. Our results identify for the first time, aberrant dopaminergic modulation of striatal-cortical connectivity as a neural signature of levodopa-induced dyskinesias in humans. We argue that excessive striato-cortical connectivity in response to levodopa produces an

  8. Use of cortical neuronal networks for in vitro material biocompatibility testing.

    PubMed

    Charkhkar, Hamid; Frewin, Christopher; Nezafati, Maysam; Knaack, Gretchen L; Peixoto, Nathalia; Saddow, Stephen E; Pancrazio, Joseph J

    2014-03-15

    Neural interfaces aim to restore neurological function lost during disease or injury. Novel implantable neural interfaces increasingly capitalize on novel materials to achieve microscale coupling with the nervous system. Like any biomedical device, neural interfaces should consist of materials that exhibit biocompatibility in accordance with the international standard ISO10993-5, which describes in vitro testing involving fibroblasts where cytotoxicity serves as the main endpoint. In the present study, we examine the utility of living neuronal networks as functional assays for in vitro material biocompatibility, particularly for materials that comprise implantable neural interfaces. Embryonic mouse cortical tissue was cultured to form functional networks where spontaneous action potentials, or spikes, can be monitored non-invasively using a substrate-integrated microelectrode array. Taking advantage of such a platform, we exposed established positive and negative control materials to the neuronal networks in a consistent method with ISO 10993-5 guidance. Exposure to the negative controls, gold and polyethylene, did not significantly change the neuronal activity whereas the positive controls, copper and polyvinyl chloride (PVC), resulted in reduction of network spike rate. We also compared the functional assay with an established cytotoxicity measure using L929 fibroblast cells. Our findings indicate that neuronal networks exhibit enhanced sensitivity to positive control materials. In addition, we assessed functional neurotoxicity of tungsten, a common microelectrode material, and two conducting polymer formulations that have been used to modify microelectrode properties for in vivo recording and stimulation. These data suggest that cultured neuronal networks are a useful platform for evaluating the functional toxicity of materials intended for implantation in the nervous system.

  9. Predictions and simulations of cortical dynamics during natural sleep using a continuum approach

    NASA Astrophysics Data System (ADS)

    Wilson, M. T.; Steyn-Ross, M. L.; Steyn-Ross, D. A.; Sleigh, J. W.

    2005-11-01

    In this paper we use a continuum model in two spatial dimensions to study the dynamics of the cortex during natural sleep, including explicitly the effects of two key neuromodulators. The model predicts that a number of states could be available to the cortex. We identify two of these with slow-wave sleep and rapid eye movement (REM) sleep, and focus on the transition between the two. Eigenvalue analysis of the linearized model, together with simulations on a two-dimensional grid, show that a number of oscillatory states exist; the occurrence of these is particularly dependent upon the duration in time of the inhibitory postsynaptic potential. These oscillatory states are similar to the cortical slow oscillation and certain types of seizure. Power spectra are evaluated for different parameter sets and compare favorably with experiment. Grid simulations show that transitions between cortical states (e.g., slow-wave to REM) can be seeded at any point in space by random fluctuations in subcortical input.

  10. Predictions and simulations of cortical dynamics during natural sleep using a continuum approach.

    PubMed

    Wilson, M T; Steyn-Ross, M L; Steyn-Ross, D A; Sleigh, J W

    2005-11-01

    In this paper we use a continuum model in two spatial dimensions to study the dynamics of the cortex during natural sleep, including explicitly the effects of two key neuromodulators. The model predicts that a number of states could be available to the cortex. We identify two of these with slow-wave sleep and rapid eye movement (REM) sleep, and focus on the transition between the two. Eigenvalue analysis of the linearized model, together with simulations on a two-dimensional grid, show that a number of oscillatory states exist; the occurrence of these is particularly dependent upon the duration in time of the inhibitory postsynaptic potential. These oscillatory states are similar to the cortical slow oscillation and certain types of seizure. Power spectra are evaluated for different parameter sets and compare favorably with experiment. Grid simulations show that transitions between cortical states (e.g., slow-wave to REM) can be seeded at any point in space by random fluctuations in subcortical input.

  11. Neural network computer simulation of medical aerosols.

    PubMed

    Richardson, C J; Barlow, D J

    1996-06-01

    Preliminary investigations have been conducted to assess the potential for using artificial neural networks to simulate aerosol behaviour, with a view to employing this type of methodology in the evaluation and design of pulmonary drug-delivery systems. Details are presented of the general purpose software developed for these tasks; it implements a feed-forward back-propagation algorithm with weight decay and connection pruning, the user having complete run-time control of the network architecture and mode of training. A series of exploratory investigations is then reported in which different network structures and training strategies are assessed in terms of their ability to simulate known patterns of fluid flow in simple model systems. The first of these involves simulations of cellular automata-generated data for fluid flow through a partially obstructed two-dimensional pipe. The artificial neural networks are shown to be highly successful in simulating the behaviour of this simple linear system, but with important provisos relating to the information content of the training data and the criteria used to judge when the network is properly trained. A second set of investigations is then reported in which similar networks are used to simulate patterns of fluid flow through aerosol generation devices, using training data furnished through rigorous computational fluid dynamics modelling. These more complex three-dimensional systems are modelled with equal success. It is concluded that carefully tailored, well trained networks could provide valuable tools not just for predicting but also for analysing the spatial dynamics of pharmaceutical aerosols.

  12. Analytical characterization of spontaneous firing in networks of developing rat cultured cortical neurons

    NASA Astrophysics Data System (ADS)

    Tateno, Takashi; Kawana, Akio; Jimbo, Yasuhiko

    2002-05-01

    We have used a multiunit electrode array in extracellular recording to investigate changes in the firing patterns in networks of developing rat cortical neurons. The spontaneous activity of continual asynchronous firing or the alternation of asynchronous spikes and synchronous bursts changed over time so that activity in the later stages consisted exclusively of synchronized bursts. The spontaneous coordinated activity in bursts produced a variability in interburst interval (IBI) sequences that is referred to as ``form.'' The stochastic and nonlinear dynamical analysis of IBI sequences revealed that these sequences reflected a largely random process and that the form for relatively immature neurons was largely oscillatory while the form for the more mature neurons was Poisson-like. The observed IBI sequences thus showed changes in form associated with both the intrinsic properties of the developing cells and the neural response to correlated synaptic inputs due to interaction between the developing neural circuits.

  13. Differential effects of excitatory and inhibitory heterogeneity on the gain and asynchronous state of sparse cortical networks

    PubMed Central

    Mejias, Jorge F.; Longtin, André

    2014-01-01

    Recent experimental and theoretical studies have highlighted the importance of cell-to-cell differences in the dynamics and functions of neural networks, such as in different types of neural coding or synchronization. It is still not known, however, how neural heterogeneity can affect cortical computations, or impact the dynamics of typical cortical circuits constituted of sparse excitatory and inhibitory networks. In this work, we analytically and numerically study the dynamics of a typical cortical circuit with a certain level of neural heterogeneity. Our circuit includes realistic features found in real cortical populations, such as network sparseness, excitatory, and inhibitory subpopulations of neurons, and different cell-to-cell heterogeneities for each type of population in the system. We find highly differentiated roles for heterogeneity, depending on the subpopulation in which it is found. In particular, while heterogeneity among excitatory neurons non-linearly increases the mean firing rate and linearizes the f-I curves, heterogeneity among inhibitory neurons may decrease the network activity level and induces divisive gain effects in the f-I curves of the excitatory cells, providing an effective gain control mechanism to influence information flow. In addition, we compute the conditions for stability of the network activity, finding that the synchronization onset is robust to inhibitory heterogeneity, but it shifts to lower input levels for higher excitatory heterogeneity. Finally, we provide an extension of recently reported heterogeneity-induced mechanisms for signal detection under rate coding, and we explore the validity of our findings when multiple sources of heterogeneity are present. These results allow for a detailed characterization of the role of neural heterogeneity in asynchronous cortical networks. PMID:25309409

  14. Effects of Increasing Neuromuscular Electrical Stimulation Current Intensity on Cortical Sensorimotor Network Activation: A Time Domain fNIRS Study

    PubMed Central

    Zucchelli, Lucia; Perrey, Stephane; Contini, Davide; Caffini, Matteo; Spinelli, Lorenzo; Kerr, Graham; Quaresima, Valentina; Ferrari, Marco; Torricelli, Alessandro

    2015-01-01

    Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions. PMID:26158464

  15. Extending Transfer Entropy Improves Identification of Effective Connectivity in a Spiking Cortical Network Model

    PubMed Central

    Ito, Shinya; Hansen, Michael E.; Heiland, Randy; Lumsdaine, Andrew; Litke, Alan M.; Beggs, John M.

    2011-01-01

    Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to probe neural interactions at only a single time delay and at a message length of only a single time bin. This is problematic, as synaptic delays between cortical neurons, for example, range from one to tens of milliseconds. In addition, neurons produce bursts of spikes spanning multiple time bins. To address these issues, here we introduce a free software package that allows TE to be measured at multiple delays and message lengths. To assess performance, we applied these extensions of TE to a spiking cortical network model (Izhikevich, 2006) with known connectivity and a range of synaptic delays. For comparison, we also investigated single-delay TE, at a message length of one bin (D1TE), and cross-correlation (CC) methods. We found that D1TE could identify 36% of true connections when evaluated at a false positive rate of 1%. For extended versions of TE, this dramatically improved to 73% of true connections. In addition, the connections correctly identified by extended versions of TE accounted for 85% of the total synaptic weight in the network. Cross correlation methods generally performed more poorly than extended TE, but were useful when data length was short. A computational performance analysis demonstrated that the algorithm for extended TE, when used on currently available desktop computers, could extract effective connectivity from 1 hr recordings containing 200 neurons in ∼5 min. We conclude that extending TE to multiple delays and message lengths improves its ability to assess effective connectivity between spiking neurons. These extensions to TE soon could become practical tools for experimentalists who record hundreds of spiking neurons. PMID:22102894

  16. A cortical network underpinning the perceptual priority for rising intensity and auditory ``looming.''

    NASA Astrophysics Data System (ADS)

    Neuhoff, John G.; Bilecen, Deniz; Mustovic, Henrietta; Schachinger, Hartmut; Seifritz, Erich; Scheffler, Klaus; di Salle, Francesco

    2002-05-01

    Relative motion between a sound source and a listener creates a change in acoustic intensity that can be used to anticipate the source's approach. Humans have been shown to overestimate the intensity change of rising compared to falling intensity sounds and underestimate the time-to-contact of approaching sound sources. From an evolutionary perspective, this perceptual priority for looming sounds may represent an adaptive advantage that provides an increased margin of safety for responding to approaching auditory objects. Here, using functional magnetic resonance imaging, we show that the prioritization of rising contrasted with falling intensity sine-tones is grounded in a specific neural network. This network is predominantly composed of the superior temporal sulci, the middle temporal gyri, the right temporo-parietal junction, the motor and premotor cortices mainly on the right hemisphere, the left frontal operculum, and the left superior posterior cerebellar cortex. These regions are critical for the allocation of attention, the analysis of space, object recognition, and neurobehavioral preparation for action. Our results identify a widespread neural network underpinning the perceptual priority for looming sounds that can be used in translating sensory information into preparedness for adverse events and appropriate action. [Work supported by the Swiss and the American NSFs.

  17. Spatial learning and action planning in a prefrontal cortical network model.

    PubMed

    Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

    2011-05-01

    The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive "insight" capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates.

  18. Buffer Management Simulation in ATM Networks

    NASA Technical Reports Server (NTRS)

    Yaprak, E.; Xiao, Y.; Chronopoulos, A.; Chow, E.; Anneberg, L.

    1998-01-01

    This paper presents a simulation of a new dynamic buffer allocation management scheme in ATM networks. To achieve this objective, an algorithm that detects congestion and updates the dynamic buffer allocation scheme was developed for the OPNET simulation package via the creation of a new ATM module.

  19. Scalable Online Network Modeling and Simulation

    DTIC Science & Technology

    2005-08-01

    ONLINE NETWORK MODELING AND SIMULATION 6. AUTHOR(S) Boleslaw Szymanski, Shivkumar Kalyanaraman, Biplab Sikdar and Christopher Carothers 5...PI of this project, Prof. Kenneth Vastola, replaced later by co-PI, Prof. Biplab Sikdar . With significant progress in silicon technologies, storage...Winter Simulation Conference (WSC 󈧈), December 2004. 3. K. Chandrayana, S. Ramakrishnan, B. Sikdar , S. Kalyanaraman, On randomizing the sending

  20. Electronic Neural-Network Simulator

    NASA Technical Reports Server (NTRS)

    Moopenn, Alex W.; Thakoor, Anilkumar P.; Lambe, John J.

    1988-01-01

    Experimental circuits faster than simulation programs run on digital computers. Serial shift register routes clock pulses C1 to neurons in sequence. Clock pulses C2 interrogate neurons. Neuron interconnection information stored in simulated synapses. Can be expanded to greater complexity.

  1. Network simulations of optical illusions

    NASA Astrophysics Data System (ADS)

    Shinbrot, Troy; Lazo, Miguel Vivar; Siu, Theo

    We examine a dynamical network model of visual processing that reproduces several aspects of a well-known optical illusion, including subtle dependencies on curvature and scale. The model uses a genetic algorithm to construct the percept of an image, and we show that this percept evolves dynamically so as to produce the illusions reported. We find that the perceived illusions are hardwired into the model architecture and we propose that this approach may serve as an archetype to distinguish behaviors that are due to nature (i.e. a fixed network architecture) from those subject to nurture (that can be plastically altered through learning).

  2. Interaction of electrically evoked activity with intrinsic dynamics of cultured cortical networks with and without functional fast GABAergic synaptic transmission

    PubMed Central

    Baltz, Thomas; Voigt, Thomas

    2015-01-01

    The modulation of neuronal activity by means of electrical stimulation is a successful therapeutic approach for patients suffering from a variety of central nervous system disorders. Prototypic networks formed by cultured cortical neurons represent an important model system to gain general insights in the input–output relationships of neuronal tissue. These networks undergo a multitude of developmental changes during their maturation, such as the excitatory–inhibitory shift of the neurotransmitter GABA. Very few studies have addressed how the output properties to a given stimulus change with ongoing development. Here, we investigate input–output relationships of cultured cortical networks by probing cultures with and without functional GABAAergic synaptic transmission with a set of stimulation paradigms at various stages of maturation. On the cellular level, low stimulation rates (<15 Hz) led to reliable neuronal responses; higher rates were increasingly ineffective. Similarly, on the network level, lowest stimulation rates (<0.1 Hz) lead to maximal output rates at all ages, indicating a network wide refractory period after each stimulus. In cultures aged 3 weeks and older, a gradual recovery of the network excitability within tens of milliseconds was in contrast to an abrupt recovery after about 5 s in cultures with absent GABAAergic synaptic transmission. In these GABA deficient cultures evoked responses were prolonged and had multiple discharges. Furthermore, the network excitability changed periodically, with a very slow spontaneous change of the overall network activity in the minute range, which was not observed in cultures with absent GABAAergic synaptic transmission. The electrically evoked activity of cultured cortical networks, therefore, is governed by at least two potentially interacting mechanisms: A refractory period in the order of a few seconds and a very slow GABA dependent oscillation of the network excitability. PMID:26236196

  3. Network Modeling and Simulation (NEMSE)

    DTIC Science & Technology

    2013-07-01

    this figure, tunnels through the Internet using a Virtual Private Network (VPN) technique to one of the front end “ Condor “ computers. The VPN...connections are shown as heavy lines. Information Assurance (IA) considerations are handled between the Condor machines and “Ops”, “Tips”, and "Boss

  4. The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

    PubMed Central

    Neske, Garrett T.

    2016-01-01

    During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration. PMID:26834569

  5. Latency-Related Development of Functional Connections in Cultured Cortical Networks

    PubMed Central

    le Feber, J.; van Pelt, J.; Rutten, W.L.C.

    2009-01-01

    Abstract To study plasticity, we cultured cortical networks on multielectrode arrays, enabling simultaneous recording from multiple neurons. We used conditional firing probabilities to describe functional network connections by their strength and latency. These are abstract representations of neuronal pathways and may arise from direct pathways between two neurons or from a common input. Functional connections based on direct pathways should reflect synaptic properties. Therefore, we searched for long-term potentiation (this mechanism occurs in vivo when presynaptic action potentials precede postsynaptic ones with interspike intervals up to ∼20 ms) in vitro. To investigate if the strength of functional connections showed a similar latency-related development, we selected periods of monotonously increasing or decreasing strength. We observed increased incidence of short latencies (5–30 ms) during strengthening, whereas these rarely occurred during weakening. Furthermore, we saw an increased incidence of 40–65 ms latencies during weakening. Conversely, functional connections tended to strengthen in periods with short latency, whereas strengthening was significantly less than average during long latency. Our data suggest that functional connections contain information about synaptic connections, that conditional firing probability analysis is sensitive enough to detect it and that a substantial fraction of all functional connections is based on direct pathways. PMID:19383487

  6. Untangling perceptual memory: hysteresis and adaptation map into separate cortical networks.

    PubMed

    Schwiedrzik, Caspar M; Ruff, Christian C; Lazar, Andreea; Leitner, Frauke C; Singer, Wolf; Melloni, Lucia

    2014-05-01

    Perception is an active inferential process in which prior knowledge is combined with sensory input, the result of which determines the contents of awareness. Accordingly, previous experience is known to help the brain "decide" what to perceive. However, a critical aspect that has not been addressed is that previous experience can exert 2 opposing effects on perception: An attractive effect, sensitizing the brain to perceive the same again (hysteresis), or a repulsive effect, making it more likely to perceive something else (adaptation). We used functional magnetic resonance imaging and modeling to elucidate how the brain entertains these 2 opposing processes, and what determines the direction of such experience-dependent perceptual effects. We found that although affecting our perception concurrently, hysteresis and adaptation map into distinct cortical networks: a widespread network of higher-order visual and fronto-parietal areas was involved in perceptual stabilization, while adaptation was confined to early visual areas. This areal and hierarchical segregation may explain how the brain maintains the balance between exploiting redundancies and staying sensitive to new information. We provide a Bayesian model that accounts for the coexistence of hysteresis and adaptation by separating their causes into 2 distinct terms: Hysteresis alters the prior, whereas adaptation changes the sensory evidence (the likelihood function).

  7. Experimental and Computational Studies of Cortical Neural Network Properties Through Signal Processing

    NASA Astrophysics Data System (ADS)

    Clawson, Wesley Patrick

    Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized using mutual information between sensory input, visual stimulus, and neural response,. The primary finding of our experiments in the visual cortex in turtles and neuronal network modeling confirms this theoretical prediction. We show that sensory discrimination is maximized when visual cortex operates near criticality. In addition to presenting this primary finding in detail, this thesis will also address our preliminary results on change-point-detection in experimentally measured cortical dynamics.

  8. Mechanisms for Phase Shifting in Cortical Networks and their Role in Communication through Coherence

    PubMed Central

    Tiesinga, Paul H.; Sejnowski, Terrence J.

    2010-01-01

    In the primate visual cortex, the phase of spikes relative to oscillations in the local field potential (LFP) in the gamma frequency range (30–80 Hz) can be shifted by stimulus features such as orientation and thus the phase may carry information about stimulus identity. According to the principle of communication through coherence (CTC), the relative LFP phase between the LFPs in the sending and receiving circuits affects the effectiveness of the transmission. CTC predicts that phase shifting can be used for stimulus selection. We review and investigate phase shifting in models of periodically driven single neurons and compare it with phase shifting in models of cortical networks. In a single neuron, as the driving current is increased, the spike phase varies systematically while the firing rate remains constant. In a network model of reciprocally connected excitatory (E) and inhibitory (I) cells phase shifting occurs in response to both injection of constant depolarizing currents and to brief pulses to I cells. These simple models provide an account for phase-shifting observed experimentally and suggest a mechanism for implementing CTC. We discuss how this hypothesis can be tested experimentally using optogenetic techniques. PMID:21103013

  9. Optimal sensorimotor integration in recurrent cortical networks: a neural implementation of Kalman filters.

    PubMed

    Denève, Sophie; Duhamel, Jean-René; Pouget, Alexandre

    2007-05-23

    Several behavioral experiments suggest that the nervous system uses an internal model of the dynamics of the body to implement a close approximation to a Kalman filter. This filter can be used to perform a variety of tasks nearly optimally, such as predicting the sensory consequence of motor action, integrating sensory and body posture signals, and computing motor commands. We propose that the neural implementation of this Kalman filter involves recurrent basis function networks with attractor dynamics, a kind of architecture that can be readily mapped onto cortical circuits. In such networks, the tuning curves to variables such as arm velocity are remarkably noninvariant in the sense that the amplitude and width of the tuning curves of a given neuron can vary greatly depending on other variables such as the position of the arm or the reliability of the sensory feedback. This property could explain some puzzling properties of tuning curves in the motor and premotor cortex, and it leads to several new predictions.

  10. Untangling Perceptual Memory: Hysteresis and Adaptation Map into Separate Cortical Networks

    PubMed Central

    Schwiedrzik, Caspar M.; Ruff, Christian C.; Lazar, Andreea; Leitner, Frauke C.; Singer, Wolf; Melloni, Lucia

    2014-01-01

    Perception is an active inferential process in which prior knowledge is combined with sensory input, the result of which determines the contents of awareness. Accordingly, previous experience is known to help the brain “decide” what to perceive. However, a critical aspect that has not been addressed is that previous experience can exert 2 opposing effects on perception: An attractive effect, sensitizing the brain to perceive the same again (hysteresis), or a repulsive effect, making it more likely to perceive something else (adaptation). We used functional magnetic resonance imaging and modeling to elucidate how the brain entertains these 2 opposing processes, and what determines the direction of such experience-dependent perceptual effects. We found that although affecting our perception concurrently, hysteresis and adaptation map into distinct cortical networks: a widespread network of higher-order visual and fronto-parietal areas was involved in perceptual stabilization, while adaptation was confined to early visual areas. This areal and hierarchical segregation may explain how the brain maintains the balance between exploiting redundancies and staying sensitive to new information. We provide a Bayesian model that accounts for the coexistence of hysteresis and adaptation by separating their causes into 2 distinct terms: Hysteresis alters the prior, whereas adaptation changes the sensory evidence (the likelihood function). PMID:23236204

  11. Excitatory synaptic transmission and network activity are depressed following mechanical injury in cortical neurons

    PubMed Central

    Goforth, Paulette B.; Ren, Jianhua; Schwartz, Benjamin S.

    2011-01-01

    In vitro and in vivo traumatic brain injury (TBI) alter the function and expression of glutamate receptors, yet the combined effect of these alterations on cortical excitatory synaptic transmission is unclear. We examined the effect of in vitro mechanical injury on excitatory synaptic function in cultured cortical neurons by assaying synaptically driven intracellular free calcium ([Ca2+]i) oscillations in small neuronal networks as well as spontaneous and miniature excitatory postsynaptic currents (mEPSCs). We show that injury decreased the incidence and frequency of spontaneous neuronal [Ca2+]i oscillations for at least 2 days post-injury. The amplitude of the oscillations was reduced immediately and 2 days post-injury, although a transient rebound at 4 h post-injury was observed due to increased activity of N-methyl-d-aspartate (NMDARs) and calcium-permeable α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate receptors (CP-AMPARs). Increased CP-AMPAR function was abolished by the inhibition of protein synthesis. In parallel, mEPSC amplitude decreased immediately, 4 h, and 2 days post-injury, with a transient increase in the contribution of synaptic CP-AMPARs observed at 4 h post-injury. Decreased mEPSC amplitude was evident after injury, even if NMDARs and CP-AMPARs were blocked pharmacologically, suggesting the decrease reflected alterations in synaptic Glur2-containing, calcium-impermeable AMPARs. Despite the transient increase in CP-AMPAR activity that we observed, the overriding effect of mechanical injury was long-term depression of excitatory neurotransmission that would be expected to contribute to the cognitive deficits of TBI. PMID:21346214

  12. Excitatory synaptic transmission and network activity are depressed following mechanical injury in cortical neurons.

    PubMed

    Goforth, Paulette B; Ren, Jianhua; Schwartz, Benjamin S; Satin, Leslie S

    2011-05-01

    In vitro and in vivo traumatic brain injury (TBI) alter the function and expression of glutamate receptors, yet the combined effect of these alterations on cortical excitatory synaptic transmission is unclear. We examined the effect of in vitro mechanical injury on excitatory synaptic function in cultured cortical neurons by assaying synaptically driven intracellular free calcium ([Ca(2+)](i)) oscillations in small neuronal networks as well as spontaneous and miniature excitatory postsynaptic currents (mEPSCs). We show that injury decreased the incidence and frequency of spontaneous neuronal [Ca(2+)](i) oscillations for at least 2 days post-injury. The amplitude of the oscillations was reduced immediately and 2 days post-injury, although a transient rebound at 4 h post-injury was observed due to increased activity of N-methyl-d-aspartate (NMDARs) and calcium-permeable α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate receptors (CP-AMPARs). Increased CP-AMPAR function was abolished by the inhibition of protein synthesis. In parallel, mEPSC amplitude decreased immediately, 4 h, and 2 days post-injury, with a transient increase in the contribution of synaptic CP-AMPARs observed at 4 h post-injury. Decreased mEPSC amplitude was evident after injury, even if NMDARs and CP-AMPARs were blocked pharmacologically, suggesting the decrease reflected alterations in synaptic Glur2-containing, calcium-impermeable AMPARs. Despite the transient increase in CP-AMPAR activity that we observed, the overriding effect of mechanical injury was long-term depression of excitatory neurotransmission that would be expected to contribute to the cognitive deficits of TBI.

  13. Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations.

    PubMed

    Zazo, Javier; Macua, Sergio Valcarcel; Zazo, Santiago; Pérez, Marina; Pérez-Álvarez, Iván; Jiménez, Eugenio; Cardona, Laura; Brito, Joaquín Hernández; Quevedo, Eduardo

    2016-12-17

    In the first part of the paper, we modeled and characterized the underwater radio channel in shallowwaters. In the second part,we analyze the application requirements for an underwaterwireless sensor network (U-WSN) operating in the same environment and perform detailed simulations. We consider two localization applications, namely self-localization and navigation aid, and propose algorithms that work well under the specific constraints associated with U-WSN, namely low connectivity, low data rates and high packet loss probability. We propose an algorithm where the sensor nodes collaboratively estimate their unknown positions in the network using a low number of anchor nodes and distance measurements from the underwater channel. Once the network has been self-located, we consider a node estimating its position for underwater navigation communicating with neighboring nodes. We also propose a communication system and simulate the whole electromagnetic U-WSN in the Castalia simulator to evaluate the network performance, including propagation impairments (e.g., noise, interference), radio parameters (e.g., modulation scheme, bandwidth, transmit power), hardware limitations (e.g., clock drift, transmission buffer) and complete MAC and routing protocols. We also explain the changes that have to be done to Castalia in order to perform the simulations. In addition, we propose a parametric model of the communication channel that matches well with the results from the first part of this paper. Finally, we provide simulation results for some illustrative scenarios.

  14. Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations

    PubMed Central

    Zazo, Javier; Valcarcel Macua, Sergio; Zazo, Santiago; Pérez, Marina; Pérez-Álvarez, Iván; Jiménez, Eugenio; Cardona, Laura; Brito, Joaquín Hernández; Quevedo, Eduardo

    2016-01-01

    In the first part of the paper, we modeled and characterized the underwater radio channel in shallow waters. In the second part, we analyze the application requirements for an underwater wireless sensor network (U-WSN) operating in the same environment and perform detailed simulations. We consider two localization applications, namely self-localization and navigation aid, and propose algorithms that work well under the specific constraints associated with U-WSN, namely low connectivity, low data rates and high packet loss probability. We propose an algorithm where the sensor nodes collaboratively estimate their unknown positions in the network using a low number of anchor nodes and distance measurements from the underwater channel. Once the network has been self-located, we consider a node estimating its position for underwater navigation communicating with neighboring nodes. We also propose a communication system and simulate the whole electromagnetic U-WSN in the Castalia simulator to evaluate the network performance, including propagation impairments (e.g., noise, interference), radio parameters (e.g., modulation scheme, bandwidth, transmit power), hardware limitations (e.g., clock drift, transmission buffer) and complete MAC and routing protocols. We also explain the changes that have to be done to Castalia in order to perform the simulations. In addition, we propose a parametric model of the communication channel that matches well with the results from the first part of this paper. Finally, we provide simulation results for some illustrative scenarios. PMID:27999309

  15. Modeling and Simulation. III. Simulation of a Model for Development of Visual Cortical Specificity.

    DTIC Science & Technology

    1986-12-15

    of parameter values. Experiment, model, and simulation 5’ The simulations we consider mimic, in form, classic deprivation experiments. Kittens are...second paper of the series (ref. 8) reviews the results of numerous experiments on the neuronal development of kitten visual cortex. We have...restricted to a very limited range of oriented contours (see citations in ref. 8). Kittens were raised, for example, viewing only horizontal or only vertical

  16. Simulating Operation of a Complex Sensor Network

    NASA Technical Reports Server (NTRS)

    Jennings, Esther; Clare, Loren; Woo, Simon

    2008-01-01

    Simulation Tool for ASCTA Microsensor Network Architecture (STAMiNA) ["ASCTA" denotes the Advanced Sensors Collaborative Technology Alliance.] is a computer program for evaluating conceptual sensor networks deployed over terrain to provide military situational awareness. This or a similar program is needed because of the complexity of interactions among such diverse phenomena as sensing and communication portions of a network, deployment of sensor nodes, effects of terrain, data-fusion algorithms, and threat characteristics. STAMiNA is built upon a commercial network-simulator engine, with extensions to include both sensing and communication models in a discrete-event simulation environment. Users can define (1) a mission environment, including terrain features; (2) objects to be sensed; (3) placements and modalities of sensors, abilities of sensors to sense objects of various types, and sensor false alarm rates; (4) trajectories of threatening objects; (5) means of dissemination and fusion of data; and (6) various network configurations. By use of STAMiNA, one can simulate detection of targets through sensing, dissemination of information by various wireless communication subsystems under various scenarios, and fusion of information, incorporating such metrics as target-detection probabilities, false-alarm rates, and communication loads, and capturing effects of terrain and threat.

  17. CRF Network Simulations for the South

    NASA Technical Reports Server (NTRS)

    Titov, Oleg; Behrend, Dirk; Shu, Fengchun; MacMillan, Dan; Fey, Alan

    2010-01-01

    In order to monitor and improve the CRF in both the Southern Hemisphere and along the ecliptic, we perform various simulations using station networks based mostly on the Australian AuScope network, New Zealand s Warkworth antenna, and several Chinese antennas. The effect of other stations such as HartRAO and Kokee Park to enhance the East-West baseline coverage is also considered. It is anticipated that the simulation results will help IVS to decide on the composition of the CRF sessions of the IVS to be run from 2011 onward.

  18. Dynamic simulation of regulatory networks using SQUAD

    PubMed Central

    Di Cara, Alessandro; Garg, Abhishek; De Micheli, Giovanni; Xenarios, Ioannis; Mendoza, Luis

    2007-01-01

    Background The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. Results We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. Conclusion The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or

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

    PubMed Central

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

    2016-01-01

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

  20. Wireless Local Area Networks: Simulation and Analysis

    DTIC Science & Technology

    1998-06-01

    response, including the time for reviewing instruction, searching existing data sources , gathering and maintaining the data needed, and completing and...multiple paths that the electromagnetic waves travel (multi-path interference). This thesis presents two separate simulations. In the first, a realistic...examine the reliability of the wireless standard for the medium access control (MAC) layer, using CACI COMNET HJ network simulation software. This

  1. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism

    PubMed Central

    Willsey, A. Jeremy; Sanders, Stephan J.; Li, Mingfeng; Dong, Shan; Tebbenkamp, Andrew T.; Muhle, Rebecca A.; Reilly, Steven K.; Lin, Leon; Fertuzinhos, Sofia; Miller, Jeremy A.; Murtha, Michael T.; Bichsel, Candace; Niu, Wei; Cotney, Justin; Ercan-Sencicek, A. Gulhan; Gockley, Jake; Gupta, Abha; Han, Wenqi; He, Xin; Hoffman, Ellen; Klei, Lambertus; Lei, Jing; Liu, Wenzhong; Liu, Li; Lu, Cong; Xu, Xuming; Zhu, Ying; Mane, Shrikant M.; Lein, Edward S.; Wei, Liping; Noonan, James P.; Roeder, Kathryn; Devlin, Bernie; Šestan, Nenad; State, Matthew W.

    2013-01-01

    SUMMARY Autism spectrum disorder (ASD) is a complex developmental syndrome of unknown etiology. Recent studies employing exome- and genome-wide sequencing have identified nine high-confidence ASD (hcASD) genes. Working from the hypothesis that ASD-associated mutations in these biologically pleiotropic genes will disrupt intersecting developmental processes to contribute to a common phenotype, we have attempted to identify time periods, brain regions, and cell types in which these genes converge. We have constructed coexpression networks based on the hcASD “seed” genes, leveraging a rich expression data set encompassing multiple human brain regions across human development and into adulthood. By assessing enrichment of an independent set of probable ASD (pASD) genes, derived from the same sequencing studies, we demonstrate a key point of convergence in midfetal layer 5/6 cortical projection neurons. This approach informs when, where, and in what cell types mutations in these specific genes may be productively studied to clarify ASD pathophysiology. PMID:24267886

  2. Neuronal networks and mediators of cortical neurovascular coupling responses in normal and altered brain states.

    PubMed

    Lecrux, C; Hamel, E

    2016-10-05

    Brain imaging techniques that use vascular signals to map changes in neuronal activity, such as blood oxygenation level-dependent functional magnetic resonance imaging, rely on the spatial and temporal coupling between changes in neurophysiology and haemodynamics, known as 'neurovascular coupling (NVC)'. Accordingly, NVC responses, mapped by changes in brain haemodynamics, have been validated for different stimuli under physiological conditions. In the cerebral cortex, the networks of excitatory pyramidal cells and inhibitory interneurons generating the changes in neural activity and the key mediators that signal to the vascular unit have been identified for some incoming afferent pathways. The neural circuits recruited by whisker glutamatergic-, basal forebrain cholinergic- or locus coeruleus noradrenergic pathway stimulation were found to be highly specific and discriminative, particularly when comparing the two modulatory systems to the sensory response. However, it is largely unknown whether or not NVC is still reliable when brain states are altered or in disease conditions. This lack of knowledge is surprising since brain imaging is broadly used in humans and, ultimately, in conditions that deviate from baseline brain function. Using the whisker-to-barrel pathway as a model of NVC, we can interrogate the reliability of NVC under enhanced cholinergic or noradrenergic modulation of cortical circuits that alters brain states.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

  3. Irreversible loss of a subpopulation of cortical interneurons in the absence of glutamatergic network activity.

    PubMed

    de Lima, Ana Dolabela; Opitz, Thoralf; Voigt, Thomas

    2004-06-01

    In the cerebral cortex of mammals, gamma-aminobutyric acid (GABA)ergic neurons represent 15-25% of all neurons, depending on the species and area being examined. Because converging evidence suggests that activity may play an important role in the neuritic maturation and synaptic function of GABAergic neurons, it is feasible that activity plays a role in the regulation of the proportion of GABAergic neurons. Here we provide direct evidence that early in cortical development activity blockade may deplete the network of a subpopulation of GABA immunoreactive neurons characterized by their small size and late generation in vitro. In a period of time coinciding with the emergence of synchronous network activity, the survival and morphological differentiation of GABAergic neurons was influenced by long-term blockade of synaptic activity. While GABA(A) receptor antagonists had a minor promoting effect on interneuronal survival during the second week in vitro, antagonists of ionotropic glutamate receptors strongly impaired survival and differentiation of immature GABAergic interneurons. Interneuronal loss was more severe when N-methyl-D-aspartate receptors were blocked than after blockade of alpha-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA)/kainate receptors. The decrease in the density of GABAergic neurons was irreversible, but could be prevented by the simultaneous addition of brain-derived neurotrophic factor (BDNF). These results suggest that there is a narrow time window during neocortical development when glutamatergic activity, and specially NMDA receptor stimulation, is crucial to assure survival and maturation of a subpopulation of late developing GABAergic interneurons.

  4. Simulating fish assemblages in riverine networks

    EPA Science Inventory

    We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

  5. Representation of vehicle location in networked simulations

    NASA Astrophysics Data System (ADS)

    Lin, Kuo-Chi; Goldiez, Brian; Ng, Huat

    In a networked simulation environment, it is vital to assure that all vehicles maintain a consistent representation of the geometry between themselves and between vehicles and the terrain over which they operate. Hence, all vehicles should be able to convert their position and orientation to common coordinates. Three coordinate systems, geocentric, geodetic, and topocentric, and the transformation from one system to another are analyzed.

  6. Large-scale cortical networks estimated from scalp EEG signals during performance of goal-directed motor tasks.

    PubMed

    De Vico Fallani, F; Astolfi, L; Cincotti, F; Mattia, D; Maglione, A G; Vecchiato, G; Toppi, J; Della Penna, F; Salinari, S; Babiloni, F; Zouridakis, G

    2010-01-01

    The evaluation of the topological properties of brain networks is an emergent research topic, since the estimated cerebral connectivity patterns often have relatively large size and complex structure. Since a graph is a mathematical representation of a network, the use of a theoretical graph approach would describe concisely the topological features of the functional brain connectivity network estimated using neuroimaging techniques. In the present study, we analyze the changes in brain synchronization networks using high-resolution EEG signals obtained during performance of a complex goal-directed visuomotor task. Our results show that the cortical network is more stable when subjects reach the goal than when they fail by hitting an obstacle. These findings suggest the presence of a possible cerebral "marker" for motor actions that result in successful reaching of a target.

  7. LANES - LOCAL AREA NETWORK EXTENSIBLE SIMULATOR

    NASA Technical Reports Server (NTRS)

    Gibson, J.

    1994-01-01

    The Local Area Network Extensible Simulator (LANES) provides a method for simulating the performance of high speed local area network (LAN) technology. LANES was developed as a design and analysis tool for networking on board the Space Station. The load, network, link and physical layers of a layered network architecture are all modeled. LANES models to different lower-layer protocols, the Fiber Distributed Data Interface (FDDI) and the Star*Bus. The load and network layers are included in the model as a means of introducing upper-layer processing delays associated with message transmission; they do not model any particular protocols. FDDI is an American National Standard and an International Organization for Standardization (ISO) draft standard for a 100 megabit-per-second fiber-optic token ring. Specifications for the LANES model of FDDI are taken from the Draft Proposed American National Standard FDDI Token Ring Media Access Control (MAC), document number X3T9.5/83-16 Rev. 10, February 28, 1986. This is a mature document describing the FDDI media-access-control protocol. Star*Bus, also known as the Fiber Optic Demonstration System, is a protocol for a 100 megabit-per-second fiber-optic star-topology LAN. This protocol, along with a hardware prototype, was developed by Sperry Corporation under contract to NASA Goddard Space Flight Center as a candidate LAN protocol for the Space Station. LANES can be used to analyze performance of a networking system based on either FDDI or Star*Bus under a variety of loading conditions. Delays due to upper-layer processing can easily be nullified, allowing analysis of FDDI or Star*Bus as stand-alone protocols. LANES is a parameter-driven simulation; it provides considerable flexibility in specifying both protocol an run-time parameters. Code has been optimized for fast execution and detailed tracing facilities have been included. LANES was written in FORTRAN 77 for implementation on a DEC VAX under VMS 4.6. It consists of two

  8. Realistic computer network simulation for network intrusion detection dataset generation

    NASA Astrophysics Data System (ADS)

    Payer, Garrett

    2015-05-01

    The KDD-99 Cup dataset is dead. While it can continue to be used as a toy example, the age of this dataset makes it all but useless for intrusion detection research and data mining. Many of the attacks used within the dataset are obsolete and do not reflect the features important for intrusion detection in today's networks. Creating a new dataset encompassing a large cross section of the attacks found on the Internet today could be useful, but would eventually fall to the same problem as the KDD-99 Cup; its usefulness would diminish after a period of time. To continue research into intrusion detection, the generation of new datasets needs to be as dynamic and as quick as the attacker. Simply examining existing network traffic and using domain experts such as intrusion analysts to label traffic is inefficient, expensive, and not scalable. The only viable methodology is simulation using technologies including virtualization, attack-toolsets such as Metasploit and Armitage, and sophisticated emulation of threat and user behavior. Simulating actual user behavior and network intrusion events dynamically not only allows researchers to vary scenarios quickly, but enables online testing of intrusion detection mechanisms by interacting with data as it is generated. As new threat behaviors are identified, they can be added to the simulation to make quicker determinations as to the effectiveness of existing and ongoing network intrusion technology, methodology and models.

  9. Simulating Autonomous Telecommunication Networks for Space Exploration

    NASA Technical Reports Server (NTRS)

    Segui, John S.; Jennings, Esther H.

    2008-01-01

    Currently, most interplanetary telecommunication systems require human intervention for command and control. However, considering the range from near Earth to deep space missions, combined with the increase in the number of nodes and advancements in processing capabilities, the benefits from communication autonomy will be immense. Likewise, greater mission science autonomy brings the need for unscheduled, unpredictable communication and network routing. While the terrestrial Internet protocols are highly developed their suitability for space exploration has been questioned. JPL has developed the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to help characterize network designs and protocols. The results will allow future mission planners to better understand the trade offs of communication protocols. This paper discusses various issues with interplanetary network and simulation results of interplanetary networking protocols.

  10. Prefrontal cortical network activity: Opposite effects of psychedelic hallucinogens and D1/D5 dopamine receptor activation.

    PubMed

    Lambe, E K; Aghajanian, G K

    2007-03-30

    The fine-tuning of network activity provides a modulating influence on how information is processed and interpreted in the brain. Here, we use brain slices of rat prefrontal cortex to study how recurrent network activity is affected by neuromodulators known to alter normal cortical function. We previously determined that glutamate spillover and stimulation of extrasynaptic N-methyl-d-aspartic acid (NMDA) receptors are required to support hallucinogen-induced cortical network activity. Since microdialysis studies suggest that psychedelic hallucinogens and dopamine D1/D5 receptor agonists have opposite effects on extracellular glutamate in prefrontal cortex, we hypothesized that these two families of psychoactive drugs would have opposite effects on cortical network activity. We found that network activity can be enhanced by 2,5-dimethoxy-4-iodoamphetamine (DOI) (a psychedelic hallucinogen that is a partial agonist of 5-HT(2A/2C) receptors) and suppressed by the selective D1/D5 agonist SKF 38393. This suppression could be mimicked by direct activation of adenylyl cyclase with forskolin or by addition of a cAMP analog. These findings are consistent with previous work showing that activation of adenylyl cyclase can upregulate neuronal glutamate transporters, thereby decreasing synaptic spillover of glutamate. Consistent with this hypothesis, a low concentration of the glutamate transporter inhibitor threo-beta-benzoylaspartic acid (TBOA) restored electrically-evoked recurrent activity in the presence of a selective D1/D5 agonist, whereas recurrent activity in the presence of a low level of the GABA(A) antagonist bicuculline was not resistant to suppression by the D1/D5 agonist. The tempering of network UP states by D1/D5 receptor activation may have implications for the proposed use of D1/D5 agonists in the treatment of schizophrenia.

  11. Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.

    PubMed

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

    2011-01-01

    The speed-accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time.

  12. Integrating botnet simulations with network centric warfare simulations

    NASA Astrophysics Data System (ADS)

    Stytz, Martin R.; Banks, Sheila B.

    2010-04-01

    "Botnets," or "bot armies," are large groups of remotely controlled malicious software designed and operated in order to conduct attacks against government and civilian targets. Bot armies are one of the most serious security threats to networks and computer systems in operation today. Botnets are remotely operated by botmasters who can launch large-scale malicious network activity. While bot army activity has, to date, been largely limited to fraud, blackmail, and other criminal activity, their potential for causing large-scale damage to the entire internet and launching large-scale, coordinated attacks on government computers, networks, and data gathering operations has been underestimated. This paper will not discuss how to build bots but instead discuss ways to use simulation to address the threats they pose. This paper suggests means for addressing the need to provide botnet defense training based upon existing simulation environments and discusses the capabilities needed for training systems for botnet activities. In this paper we discuss botnet technologies and review the capabilities that underlie this threat to network, information, and computer security. The second section of the paper contains background information about bot armies and their foundational technologies. The third section contains a discussion of the techniques we developed for estimating botnet bandwidth consumption and our approach for simulating botnet activities. The fourth section contains a summary and suggestions for additional research.

  13. Biomolecular Network Simulator: Software for Stochastic Simulations of Biomolecular Reaction Networks on Supercomputers

    NASA Astrophysics Data System (ADS)

    Chushak, Yaroslav; Foy, Brent; Frazier, John

    2008-03-01

    At the functional level, all biological processes in cells can be represented as a series of biochemical reactions that are stochastic in nature. We have developed a software package called Biomolecular Network Simulator (BNS) that uses a stochastic approach to model and simulate complex biomolecular reaction networks. Two simulation algorithms - the exact Gillespie stochastic simulation algorithm and the approximate adaptive tau-leaping algorithm - are implemented for generating Monte Carlo trajectories that describe the evolution of a system of biochemical reactions. The software uses a combination of MATLAB and C-coded functions and is parallelized with the Message Passing Interface (MPI) library to run on multiprocessor architectures. We will present a brief description of the Biomolecular Network Simulator software along with some examples.

  14. The brain's router: a cortical network model of serial processing in the primate brain.

    PubMed

    Zylberberg, Ariel; Fernández Slezak, Diego; Roelfsema, Pieter R; Dehaene, Stanislas; Sigman, Mariano

    2010-04-29

    The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100-500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a "router" network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates.

  15. Simulation of photosynthetic production using neural network

    NASA Astrophysics Data System (ADS)

    Kmet, Tibor; Kmetova, Maria

    2013-10-01

    This paper deals with neural network based optimal control synthesis for solving optimal control problems with control and state constraints and discrete time delay. The optimal control problem is transcribed into nonlinear programming problem which is implemented with adaptive critic neural network. This approach is applicable to a wide class of nonlinear systems. The proposed simulation methods is illustrated by the optimal control problem of photosynthetic production described by discrete time delay differential equations. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

  16. Simulation study of axial ultrasonic wave propagation in heterogeneous bovine cortical bone.

    PubMed

    Hata, Toshiho; Nagatani, Yoshiki; Takano, Koki; Matsukawa, Mami

    2016-11-01

    The effect of the heterogeneity of the long cortical bone is an important factor when applying the axial transmission technique. In this study, the axial longitudinal wave velocity distributions in specimens from the mid-shaft of a bovine femur were measured, in the MHz range. Bilinear interpolation and the piecewise cubic Hermite interpolating polynomial method were used to construct three-dimensional (3D) axial velocity models with a resolution of 40 μm. By assuming the uniaxial anisotropy of the bone and using the results of previous experimental studies [Yamato, Matsukawa, Yanagitani, Yamazaki, Mizukawa, and Nagano (2008b). Calcified Tissue Int. 82, 162-169; Nakatsuji, Yamamoto, Suga, Yanagitani, Matsukawa, Yamazaki, and Matsuyama (2011). Jpn. J. Appl. Phys. 50, 07HF18], the distributions of all elastic moduli were estimated to obtain a 3D heterogeneous bone model and a uniform model. In the heterogeneous model, moduli at the surface were smaller than those inside the model. The elastic finite-difference time-domain method was used to simulate axial ultrasonic wave propagation in these models. In the heterogeneous model, the wavefront of the first arriving signal (FAS) was dependent on the heterogeneity, and the FAS velocity depended on the measured position. These phenomena were not observed in the uniform model.

  17. Convergence and extension at gastrulation require a myosin IIB dependent cortical actin network

    PubMed Central

    Skoglund, Paul; Rolo, Ana; Chen, Xuejun; Gumbiner, Barry M.; Keller, Ray

    2009-01-01

    Summary Force-producing convergence (narrowing) and extension (lengthening) of tissues by active intercalation of cells along the axis of convergence play a major role in axial morphogenesis during development of both vertebrate and invertebrate embryos, and failure of these processes in human embryos leads to embryonic defects including spina bifida and anencephaly. Here we use Xenopus laevis, a system in which the polarized cell motility that drives this active cell intercalation has been related to development of forces that close the blastopore and elongate the body axis, to examine the role of myosin IIB in convergence and extension. We find that myosin IIB is localized in the cortex of intercalating cells, and that morpholino knockdown of this myosin isoform shows that it is essential for maintenance of a stereotypical, cortical actin cytoskeleton that we visualize with time-lapse fluorescent confocal microscopy. We show that this actin network consists of foci or nodes connected by cables and is polarized relative to the embryonic axis, preferentially cyclically shortening and lengthening parallel to the axis of cell polarization, elongation, and intercalation, and also parallel to the axis of convergence forces during gastrulation. MHC-B-depletion results in disruption of this polarized cytoskeleton, loss of the polarized protrusive activity characteristic of intercalating cells, eventual loss of cell-cell and cell matrix adhesion, and dose-dependent failure of blastopore closure, arguably because of failure to develop convergence forces parallel to the myosin IIB-dependent dynamics of the actin cytoskeleton. These findings bridge the gap between a molecular-scale motor protein and tissue-scale embryonic morphogenesis. PMID:18550716

  18. Appetitive associative learning recruits a distinct network with cortical, striatal, and hypothalamic regions

    PubMed Central

    Cole, Sindy; Hobin, Michael P.; Petrovich, Gorica D.

    2014-01-01

    The amygdala, prefrontal cortex, striatum and other connected forebrain areas are important for reward-associated learning and subsequent behaviors. How these structurally and functionally dissociable regions are recruited during initial learning, however, is unclear. Recently, we showed amygdalar nuclei were differentially recruited across different stages of cue-food associations in a Pavlovian conditioning paradigm. Here, we systematically examined Fos induction in the forebrain, including areas associated with the amygdala, during early (day 1) and late (day 10) training sessions of cue-food conditioning. During training, rats in the conditioned group received tone-food pairings, while controls received presentations of the tone alone in the conditioning chamber followed by food delivery in their home cage. We found that a small subset of telencephalic and hypothalamic regions were differentially recruited during the early and late stages of training, suggesting evidence of learning induced plasticity. Initial tone-food pairings recruited solely the amygdala, while late tone-food pairings came to induce Fos in distinct areas within the medial and lateral prefrontal cortex, the dorsal striatum, and the hypothalamus (lateral hypothalamus and paraventricular nucleus). Furthermore, within the perifornical lateral hypothalamus, tone-food pairings selectively recruited neurons that produce the orexigenic neuropeptide orexin/hypocretin. These data show a functional map of the forebrain areas recruited by appetitive associative learning and dependent on experience. These selectively activated regions include interconnected prefrontal, striatal, and hypothalamic regions that form a discrete but distributed network that is well placed to simultaneously inform cortical (cognitive) processing and behavioral (motivational) control during cue-food learning. PMID:25463526

  19. Distinct Spatiotemporal Activation Patterns of the Perirhinal-Entorhinal Network in Response to Cortical and Amygdala Input

    PubMed Central

    Willems, Janske G. P.; Wadman, Wytse J.; Cappaert, Natalie L. M.

    2016-01-01

    The perirhinal (PER) and entorhinal cortex (EC) receive input from the agranular insular cortex (AiP) and the subcortical lateral amygdala (LA) and the main output area is the hippocampus. Information transfer through the PER/EC network however, is not always guaranteed. It is hypothesized that this network actively regulates the (sub)cortical activity transfer to the hippocampal network and that the inhibitory system is involved in this function. This study determined the recruitment by the AiP and LA afferents in PER/EC network with the use of voltage sensitive dye (VSD) imaging in horizontal mouse brain slices. Electrical stimulation (500 μA) of the AiP induced activity that gradually propagated predominantly in the rostro-caudal direction: from the PER to the lateral EC (LEC). In the presence of 1 μM of the competitive γ-aminobutyric acid (GABAA) receptor antagonist bicuculline, AiP stimulation recruited the medial EC (MEC) as well. In contrast, LA stimulation (500 μA) only induced activity in the deep layers of the PER. In the presence of bicuculline, the initial population activity in the PER propagated further towards the superficial layers and the EC after a delay. The latency of evoked responses decreased with increasing stimulus intensities (50–500 μA) for both the AiP and LA stimuli. The stimulation threshold for evoking responses in the PER/EC network was higher for the LA than for the AiP. This study showed that the extent of the PER/EC network activation depends on release of inhibition. When GABAA dependent inhibition is reduced, both the AiP and the LA activate spatially overlapping regions, although in a distinct spatiotemporal fashion. It is therefore hypothesized that the inhibitory network regulates excitatory activity from both cortical and subcortical areas that has to be transmitted through the PER/EC network. PMID:27378860

  20. Modeling and Performance Simulation of the Mass Storage Network Environment

    NASA Technical Reports Server (NTRS)

    Kim, Chan M.; Sang, Janche

    2000-01-01

    This paper describes the application of modeling and simulation in evaluating and predicting the performance of the mass storage network environment. Network traffic is generated to mimic the realistic pattern of file transfer, electronic mail, and web browsing. The behavior and performance of the mass storage network and a typical client-server Local Area Network (LAN) are investigated by modeling and simulation. Performance characteristics in throughput and delay demonstrate the important role of modeling and simulation in network engineering and capacity planning.

  1. Cortical imaging on a head template: a simulation study using a resistor mesh model (RMM).

    PubMed

    Chauveau, Nicolas; Franceries, Xavier; Aubry, Florent; Celsis, Pierre; Rigaud, Bernard

    2008-09-01

    The T1 head template model used in Statistical Parametric Mapping Version 2000 (SPM2), was segmented into five layers (scalp, skull, CSF, grey and white matter) and implemented in 2 mm voxels. We designed a resistor mesh model (RMM), based on the finite volume method (FVM) to simulate the electrical properties of this head model along the three axes for each voxel. Then, we introduced four dipoles of high eccentricity (about 0.8) in this RMM, separately and simultaneously, to compute the potentials for two sets of conductivities. We used the direct cortical imaging technique (CIT) to recover the simulated dipoles, using 60 or 107 electrodes and with or without addition of Gaussian white noise (GWN). The use of realistic conductivities gave better CIT results than standard conductivities, lowering the blurring effect on scalp potentials and displaying more accurate position areas when CIT was applied to single dipoles. Simultaneous dipoles were less accurately localized, but good qualitative and stable quantitative results were obtained up to 5% noise level for 107 electrodes and up to 10% noise level for 60 electrodes, showing that a compromise must be found to optimize both the number of electrodes and the noise level. With the RMM defined in 2 mm voxels, the standard 128-electrode cap and 5% noise appears to be the upper limit providing reliable source positions when direct CIT is used. The admittance matrix defining the RMM is easy to modify so as to adapt to different conductivities. The next step will be the adaptation of individual real head T2 images to the RMM template and the introduction of anisotropy using diffusion imaging (DI).

  2. Increased interictal cerebral glucose metabolism in a cortical-subcortical network in drug naive patients with cryptogenic temporal lobe epilepsy.

    PubMed Central

    Franceschi, M; Lucignani, G; Del Sole, A; Grana, C; Bressi, S; Minicucci, F; Messa, C; Canevini, M P; Fazio, F

    1995-01-01

    Positron emission tomography with [18F]-2-fluoro-2-deoxy-D-glucose ([18F]FDG) has been used to assess the pattern of cerebral metabolism in different types of epilepsies. However, PET with [18F]FDG has never been used to evaluate drug naive patients with cryptogenic temporal lobe epilepsy, in whom the mechanism of origin and diffusion of the epileptic discharge may differ from that underlying other epilepsies. In a group of patients with cryptogenic temporal lobe epilepsy, never treated with antiepileptic drugs, evidence has been found of significant interictal glucose hypermetabolism in a bilateral neural network including the temporal lobes, thalami, basal ganglia, and cingular cortices. The metabolism in these areas and frontal lateral cortex enables the correct classification of all patients with temporal lobe epilepsy and controls by discriminant function analysis. Other cortical areas--namely, frontal basal and lateral, temporal mesial, and cerebellar cortices--had bilateral increases of glucose metabolism ranging from 10 to 15% of normal controls, although lacking stringent statistical significance. This metabolic pattern could represent a pathophysiological state of hyperactivity predisposing to epileptic discharge generation or diffusion, or else a network of inhibitory circuits activated to prevent the diffusion of the epileptic discharge. PMID:7561924

  3. Simulation of integrated optical network (IPON) properties

    NASA Astrophysics Data System (ADS)

    Siska, Petr; Koudelka, Petr; Latal, Jan; Vitasek, Jan; Kepak, Stanislav; Vašinek, Vladimír.

    2014-09-01

    There is an increasing pressure nowadays on the efficient use of existing ICT infrastructure in order to provide the latest services for corporate customers or end users. With the increase in number of services, requirements for optical networks of all hierarchies are increasing as well. This increase in the requirements, however, involves risks which must be faced by Internet service providers. These include the maximum use of spectral range, bandwidth and reachable distance, suppression of dispersion effect, route planning efficiency, CAPEX and OPEX costs management, or successful combination of technologies of deployed networks. The aim of this article is to present the problems associated with interconnection of WDM-PON and ver.2 EPON (IEEE 802.3ah standard). The entire simulation is based on real parameters, which were provided by the manufacturers of the technologies and then measured in the laboratory. Then we were able to perform simulations based on more realistic features of these technologies.

  4. Regional vulnerability of longitudinal cortical association connectivity: Associated with structural network topology alterations in preterm children with cerebral palsy.

    PubMed

    Ceschin, Rafael; Lee, Vince K; Schmithorst, Vince; Panigrahy, Ashok

    2015-01-01

    Preterm born children with spastic diplegia type of cerebral palsy and white matter injury or periventricular leukomalacia (PVL), are known to have motor, visual and cognitive impairments. Most diffusion tensor imaging (DTI) studies performed in this group have demonstrated widespread abnormalities using averaged deterministic tractography and voxel-based DTI measurements. Little is known about structural network correlates of white matter topography and reorganization in preterm cerebral palsy, despite the availability of new therapies and the need for brain imaging biomarkers. Here, we combined novel post-processing methodology of probabilistic tractography data in this preterm cohort to improve spatial and regional delineation of longitudinal cortical association tract abnormalities using an along-tract approach, and compared these data to structural DTI cortical network topology analysis. DTI images were acquired on 16 preterm children with cerebral palsy (mean age 5.6 ± 4) and 75 healthy controls (mean age 5.7 ± 3.4). Despite mean tract analysis, Tract-Based Spatial Statistics (TBSS) and voxel-based morphometry (VBM) demonstrating diffusely reduced fractional anisotropy (FA) reduction in all white matter tracts, the along-tract analysis improved the detection of regional tract vulnerability. The along-tract map-structural network topology correlates revealed two associations: (1) reduced regional posterior-anterior gradient in FA of the longitudinal visual cortical association tracts (inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, optic radiation, posterior thalamic radiation) correlated with reduced posterior-anterior gradient of intra-regional (nodal efficiency) metrics with relative sparing of frontal and temporal regions; and (2) reduced regional FA within frontal-thalamic-striatal white matter pathways (anterior limb/anterior thalamic radiation, superior longitudinal fasciculus and cortical spinal tract) correlated with

  5. Resilience Simulation for Water, Power & Road Networks

    NASA Astrophysics Data System (ADS)

    Clark, S. S.; Seager, T. P.; Chester, M.; Eisenberg, D. A.; Sweet, D.; Linkov, I.

    2014-12-01

    The increasing frequency, scale, and damages associated with recent catastrophic events has called for a shift in focus from evading losses through risk analysis to improving threat preparation, planning, absorption, recovery, and adaptation through resilience. However, neither underlying theory nor analytic tools have kept pace with resilience rhetoric. As a consequence, current approaches to engineering resilience analysis often conflate resilience and robustness or collapse into a deeper commitment to the risk analytic paradigm proven problematic in the first place. This research seeks a generalizable understanding of resilience that is applicable in multiple disciplinary contexts. We adopt a unique investigative perspective by coupling social and technical analysis with human subjects research to discover the adaptive actions, ideas and decisions that contribute to resilience in three socio-technical infrastructure systems: electric power, water, and roadways. Our research integrates physical models representing network objects with examination of the knowledge systems and social interactions revealed by human subjects making decisions in a simulated crisis environment. To ensure a diversity of contexts, we model electric power, water, roadway and knowledge networks for Phoenix AZ and Indianapolis IN. We synthesize this in a new computer-based Resilient Infrastructure Simulation Environment (RISE) to allow individuals, groups (including students) and experts to test different network design configurations and crisis response approaches. By observing simulated failures and best performances, we expect a generalizable understanding of resilience may emerge that yields a measureable understanding of the sensing, anticipating, adapting, and learning processes that are essential to resilient organizations.

  6. Stochastic Simulation of Biomolecular Reaction Networks Using the Biomolecular Network Simulator Software

    DTIC Science & Technology

    2008-02-01

    investigate the simulation of a biomolecular reaction network with BNS, a simple model of a generic self-assembling catalytic ligation reaction in a...Amino Acid Pools Nucleotide Triphosphate Pools Nucleotide Monophosphate Pools Ligation Reaction 1551 517 7 RESULTS Simulation of exemplar...and reaction r8 is the catalytic ligation reaction . In figures 5(B) through 5(F), both the time-averaged event rate for a single simulation run

  7. Large Scale Cortical Functional Networks Associated with Slow-Wave and Spindle-Burst-Related Spontaneous Activity

    PubMed Central

    McVea, David A.; Murphy, Timothy H.; Mohajerani, Majid H.

    2016-01-01

    Cortical sensory systems are active with rich patterns of activity during sleep and under light anesthesia. Remarkably, this activity shares many characteristics with those present when the awake brain responds to sensory stimuli. We review two specific forms of such activity: slow-wave activity (SWA) in the adult brain and spindle bursts in developing brain. SWA is composed of 0.5–4 Hz resting potential fluctuations. Although these fluctuations synchronize wide regions of cortex, recent large-scale imaging has shown spatial details of their distribution that reflect underlying cortical structural projections and networks. These networks are regulated, as prior awake experiences alter both the spatial and temporal features of SWA in subsequent sleep. Activity patterns of the immature brain, however, are very different from those of the adult. SWA is absent, and the dominant pattern is spindle bursts, intermittent high frequency oscillations superimposed on slower depolarizations within sensory cortices. These bursts are driven by intrinsic brain activity, which act to generate peripheral inputs, for example via limb twitches. They are present within developing sensory cortex before they are mature enough to exhibit directed movements and respond to external stimuli. Like in the adult, these patterns resemble those evoked by sensory stimulation when awake. It is suggested that spindle-burst activity is generated purposefully by the developing nervous system as a proxy for true external stimuli. While the sleep-related functions of both slow-wave and spindle-burst activity may not be entirely clear, they reflect robust regulated phenomena which can engage select wide-spread cortical circuits. These circuits are similar to those activated during sensory processing and volitional events. We highlight these two patterns of brain activity because both are prominent and well-studied forms of spontaneous activity that will yield valuable insights into brain function in

  8. Boolean network simulations for life scientists.

    PubMed

    Albert, István; Thakar, Juilee; Li, Song; Zhang, Ranran; Albert, Réka

    2008-11-14

    Modern life sciences research increasingly relies on computational solutions, from large scale data analyses to theoretical modeling. Within the theoretical models Boolean networks occupy an increasing role as they are eminently suited at mapping biological observations and hypotheses into a mathematical formalism. The conceptual underpinnings of Boolean modeling are very accessible even without a background in quantitative sciences, yet it allows life scientists to describe and explore a wide range of surprisingly complex phenomena. In this paper we provide a clear overview of the concepts used in Boolean simulations, present a software library that can perform these simulations based on simple text inputs and give three case studies. The large scale simulations in these case studies demonstrate the Boolean paradigms and their applicability as well as the advanced features and complex use cases that our software package allows. Our software is distributed via a liberal Open Source license and is freely accessible from http://booleannet.googlecode.com.

  9. Mesoscopic Simulations of Crosslinked Polymer Networks

    NASA Astrophysics Data System (ADS)

    Megariotis, Grigorios; Vogiatzis, Georgios G.; Schneider, Ludwig; Müller, Marcus; Theodorou, Doros N.

    2016-08-01

    A new methodology and the corresponding C++ code for mesoscopic simulations of elastomers are presented. The test system, crosslinked ds-1’4-polyisoprene’ is simulated with a Brownian Dynamics/kinetic Monte Carlo algorithm as a dense liquid of soft, coarse-grained beads, each representing 5-10 Kuhn segments. From the thermodynamic point of view, the system is described by a Helmholtz free-energy containing contributions from entropic springs between successive beads along a chain, slip-springs representing entanglements between beads on different chains, and non-bonded interactions. The methodology is employed for the calculation of the stress relaxation function from simulations of several microseconds at equilibrium, as well as for the prediction of stress-strain curves of crosslinked polymer networks under deformation.

  10. Variation at NRG1 genotype related to modulation of small-world properties of the functional cortical network.

    PubMed

    Lubeiro, Alba; Gomez-Pilar, Javier; Martín, Oscar; Palomino, Aitor; Fernández, Myriam; González-Pinto, Ana; Poza, Jesús; Hornero, Roberto; Molina, Vicente

    2017-02-01

    Functional brain networks possess significant small-world (SW) properties. Genetic variation relevant to both inhibitory and excitatory transmission may contribute to modulate these properties. In healthy controls, genotypic variation in Neuregulin 1 (NRG1) related to the risk of psychosis (risk alleles) would contribute to functional SW modulation of the cortical network. Electroencephalographic activity during an odd-ball task was recorded in 144 healthy controls. Then, small-worldness (SWn) was calculated in five frequency bands (i.e., theta, alpha, beta1, beta2 and gamma) for baseline (from -300 to the stimulus onset) and response (150-450 ms post-target stimulus) windows. The SWn modulation was defined as the difference in SWn between both windows. Association between SWn modulation and carrying the risk allele for three single nucleotide polymorphisms (SNP) of NRG1 (i.e., rs6468119, rs6994992 and rs7005606) was assessed. A significant association between three SNPs of NRG1 and the SWn modulation was found, specifically: NRG1 rs6468119 in alpha and beta1 bands; NRG1 rs6994992 in theta band; and NRG1 rs7005606 in theta and beta1 bands. Genetic variation at NRG1 may influence functional brain connectivity through the modulation of SWn properties of the cortical network.

  11. Human cortical control of hand movements: parietofrontal networks for reaching, grasping, and pointing.

    PubMed

    Filimon, Flavia

    2010-08-01

    In primates, control of the limb depends on many cortical areas. Whereas specialized parietofrontal circuits have been proposed for different movements in macaques, functional neuroimaging in humans has revealed widespread, overlapping activations for hand and eye movements and for movements such as reaching and grasping. This review examines the involvement of frontal and parietal areas in hand and arm movements in humans as revealed with functional neuroimaging. The degree of functional specialization, possible homologies with macaque cortical regions, and differences between frontal and posterior parietal areas are discussed, as well as a possible organization of hand movements with respect to different spatial reference frames. The available evidence supports a cortical organization along gradients of sensory (visual to somatosensory) and effector (eye to hand) preferences.

  12. Self-organized two-state membrane potential transitions in a network of realistically modeled cortical neurons.

    PubMed

    Kang, Siu; Kitano, Katsunori; Fukai, Tomoki

    2004-04-01

    Recent studies have revealed that in vivo cortical neurons show spontaneous transitions between two subthreshold levels of the membrane potentials, 'up' and 'down' states. The neural mechanism of generating those spontaneous states transitions, however, remains unclear. Recent electrophysiological studies have suggested that those state transitions may occur through activation of a hyperpolarization-activated cation current (H-current), possibly by inhibitory synaptic inputs. Here, we demonstrate that two-state membrane potential fluctuations similar to those exhibited by in vivo neurons can be generated through a spike-timing-dependent self-organizing process in a network of inhibitory neurons and excitatory neurons expressing the H-current.

  13. The cortical cytoskeletal network and cell-wall dynamics in the unicellular charophycean green alga Penium margaritaceum

    PubMed Central

    Ochs, Julie; LaRue, Therese; Tinaz, Berke; Yongue, Camille; Domozych, David S.

    2014-01-01

    Background and Aims Penium margaritaceum is a unicellular charophycean green alga with a unique bi-directional polar expansion mechanism that occurs at the central isthmus zone prior to cell division. This entails the focused deposition of cell-wall polymers coordinated by the activities of components of the endomembrane system and cytoskeletal networks. The goal of this study was to elucidate the structural organization of the cortical cytoskeletal network during the cell cycle and identify its specific functional roles during key cell-wall developmental events: pre-division expansion and cell division. Methods Microtubules and actin filaments were labelled during various cell cycle phases with an anti-tubulin antibody and rhodamine phalloidin, respectively. Chemically induced disruption of the cytoskeleton was used to elucidate specific functional roles of microtubules and actin during cell expansion and division. Correlation of cytoskeletal dynamics with cell-wall development included live cell labelling with wall polymer-specific antibodies and electron microscopy. Key Results The cortical cytoplasm of Penium is highlighted by a band of microtubules found at the cell isthmus, i.e. the site of pre-division wall expansion. This band, along with an associated, transient band of actin filaments, probably acts to direct the deposition of new wall material and to mark the plane of the future cell division. Two additional bands of microtubules, which we identify as satellite bands, arise from the isthmus microtubular band at the onset of expansion and displace toward the poles during expansion, ultimately marking the isthmus of future daughter cells. Treatment with microtubule and actin perturbation agents reversibly stops cell division. Conclusions The cortical cytoplasm of Penium contains distinct bands of microtubules and actin filaments that persist through the cell cycle. One of these bands, termed the isthmus microtubule band, or IMB, marks the site of both pre

  14. Breaking the Excitation-Inhibition Balance Makes the Cortical Network's Space-Time Dynamics Distinguish Simple Visual Scenes

    PubMed Central

    Roland, Per E.; Bonde, Lars H.; Forsberg, Lars E.; Harvey, Michael A.

    2017-01-01

    Brain dynamics are often taken to be temporal dynamics of spiking and membrane potentials in a balanced network. Almost all evidence for a balanced network comes from recordings of cell bodies of few single neurons, neglecting more than 99% of the cortical network. We examined the space-time dynamics of excitation and inhibition simultaneously in dendrites and axons over four visual areas of ferrets exposed to visual scenes with stationary and moving objects. The visual stimuli broke the tight balance between excitation and inhibition such that the network exhibited longer episodes of net excitation subsequently balanced by net inhibition, in contrast to a balanced network. Locally in all four areas the amount of net inhibition matched the amount of net excitation with a delay of 125 ms. The space-time dynamics of excitation-inhibition evolved to reduce the complexity of neuron interactions over the whole network to a flow on a low-(3)-dimensional manifold within 80 ms. In contrast to the pure temporal dynamics, the low dimensional flow evolved to distinguish the simple visual scenes. PMID:28377701

  15. Mobile-ip Aeronautical Network Simulation Study

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Tran, Diepchi T.

    2001-01-01

    NASA is interested in applying mobile Internet protocol (mobile-ip) technologies to its space and aeronautics programs. In particular, mobile-ip will play a major role in the Advanced Aeronautic Transportation Technology (AATT), the Weather Information Communication (WINCOMM), and the Small Aircraft Transportation System (SATS) aeronautics programs. This report presents the results of a simulation study of mobile-ip for an aeronautical network. The study was performed to determine the performance of the transmission control protocol (TCP) in a mobile-ip environment and to gain an understanding of how long delays, handoffs, and noisy channels affect mobile-ip performance.

  16. Learning in innovation networks: Some simulation experiments

    NASA Astrophysics Data System (ADS)

    Gilbert, Nigel; Ahrweiler, Petra; Pyka, Andreas

    2007-05-01

    According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning.

  17. ICCS network simulation LDRD project final report summary

    SciTech Connect

    Bryant, B

    1999-01-09

    A critical component of the NIF Integrated Computer Controls System (ICCS) is the local area network (LAN) that enables timely and reliable communication between control applications running on the 600+ computer systems distributed throughout the NIF facility. This project analyzed critical portions of the NIF ICCS network (referred to as "the network" in this report) applying the OPNET Modeler discrete event simulation package to model and simulate network operation and the Network Associates Distributed Sniffer network analyzer to collect actual network performance data in the ICCS Testbed. These tools were selected and procured for use on this project. Simulations and initial network analysis indicate that the network is capable of meeting system requirements. ICCS application software is currently in development, so test software was used to collect performance data. As application software is tested in the Testbed environment, more accurate timing information can be collected which will allow for more accurate large-scale simulations.

  18. Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

    DOE PAGES

    Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; ...

    2013-01-01

    Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determinedmore » the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.« less

  19. Oscillatory neuronal activity reflects lexical-semantic feature integration within and across sensory modalities in distributed cortical networks.

    PubMed

    van Ackeren, Markus J; Schneider, Till R; Müsch, Kathrin; Rueschemeyer, Shirley-Ann

    2014-10-22

    Research from the previous decade suggests that word meaning is partially stored in distributed modality-specific cortical networks. However, little is known about the mechanisms by which semantic content from multiple modalities is integrated into a coherent multisensory representation. Therefore we aimed to characterize differences between integration of lexical-semantic information from a single modality compared with two sensory modalities. We used magnetoencephalography in humans to investigate changes in oscillatory neuronal activity while participants verified two features for a given target word (e.g., "bus"). Feature pairs consisted of either two features from the same modality (visual: "red," "big") or different modalities (auditory and visual: "red," "loud"). The results suggest that integrating modality-specific features of the target word is associated with enhanced high-frequency power (80-120 Hz), while integrating features from different modalities is associated with a sustained increase in low-frequency power (2-8 Hz). Source reconstruction revealed a peak in the anterior temporal lobe for low-frequency and high-frequency effects. These results suggest that integrating lexical-semantic knowledge at different cortical scales is reflected in frequency-specific oscillatory neuronal activity in unisensory and multisensory association networks.

  20. Computer Simulation of Metallo-Supramolecular Networks

    NASA Astrophysics Data System (ADS)

    Wang, Shihu; Chen, Chun-Chung; Dormidontova, Elena

    2009-03-01

    Using Monte Carlo simulation we studied formation of reversible metallo-supramolecular networks based on 3:1 ligand-metal complexes between end-functionalized oligomers and metal ions. The fraction of 1:1, 2:1 and 3:1 ligand-metal complexes was obtained and analyzed using an analytical approach as a function of oligomer concentration, c and metal-to-oligomer ratio. We found that at low concentration the maximum in the number-average molecular weight is achieved near the stoichiometric composition and it shifts to higher metal-to- oligomer ratios at larger concentrations. Predictions are made regarding the onset of network formation, which occurs in a limited range of metal-to-oligomer ratios at sufficiently large oligomer concentrations. The average molecular weight between effective crosslinks decreases with oligomer concentration and reaches its minimum at the stoichiometric composition, where the high-frequency elastic plateau modulus approaches its maximal value. At high oligomer concentrations the plateau modulus follows a c^1.8 concentration dependence, similar to recent experimental results for metallo-supramolecular networks.

  1. Advancing the boundaries of high-connectivity network simulation with distributed computing.

    PubMed

    Morrison, Abigail; Mehring, Carsten; Geisel, Theo; Aertsen, A D; Diesmann, Markus

    2005-08-01

    The availability of efficient and reliable simulation tools is one of the mission-critical technologies in the fast-moving field of computational neuroscience. Research indicates that higher brain functions emerge from large and complex cortical networks and their interactions. The large number of elements (neurons) combined with the high connectivity (synapses) of the biological network and the specific type of interactions impose severe constraints on the explorable system size that previously have been hard to overcome. Here we present a collection of new techniques combined to a coherent simulation tool removing the fundamental obstacle in the computational study of biological neural networks: the enormous number of synaptic contacts per neuron. Distributing an individual simulation over multiple computers enables the investigation of networks orders of magnitude larger than previously possible. The software scales excellently on a wide range of tested hardware, so it can be used in an interactive and iterative fashion for the development of ideas, and results can be produced quickly even for very large networks. In contrast to earlier approaches, a wide class of neuron models and synaptic dynamics can be represented.

  2. Programmable multi-node quantum network design and simulation

    NASA Astrophysics Data System (ADS)

    Dasari, Venkat R.; Sadlier, Ronald J.; Prout, Ryan; Williams, Brian P.; Humble, Travis S.

    2016-05-01

    Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to write network applications and to build functional network designs. OpenFlow is a key protocol widely adopted to build programmable networks because of its programmability, flexibility and ability to interconnect heterogeneous network devices. We simulate the functional topology of a multi-node quantum network that uses programmable network principles to manage quantum metadata for protocols such as teleportation, superdense coding, and quantum key distribution. We first show how the OpenFlow protocol can manage the quantum metadata needed to control the quantum channel. We then use numerical simulation to demonstrate robust programmability of a quantum switch via the OpenFlow network controller while executing an application of superdense coding. We describe the software framework implemented to carry out these simulations and we discuss near-term efforts to realize these applications.

  3. Progressive deterioration of thalamic nuclei relates to cortical network decline in schizophrenia.

    PubMed

    Cobia, Derin J; Smith, Matthew J; Salinas, Ilse; Ng, Charlene; Gado, Mokhtar; Csernansky, John G; Wang, Lei

    2017-02-01

    Thalamic abnormalities are considered part of the complex pathophysiology of schizophrenia, particularly the involvement of specific thalamic nuclei. The goals of this study were to: introduce a novel atlas-based parcellation scheme for defining various thalamic nuclei; compare their integrity in a schizophrenia sample against healthy individuals at baseline and follow-up time points, as well as rates of change over time; examine relationships between the nuclei and abnormalities in known connected cortical regions; and finally, to determine if schizophrenia-related thalamic nuclei changes relate to cognitive functioning and clinical symptoms. Subjects were from a larger longitudinal 2-year follow-up study, schizophrenia (n=20) and healthy individuals (n=20) were group-matched for age, gender, and recent-alcohol use. We used high-dimensional brain mapping to obtain thalamic morphology, and applied a novel atlas-based method for delineating anterior, mediodorsal, and pulvinar nuclei. Results from cross sectional GLMs revealed group differences in bilateral mediodorsal and anterior nuclei, while longitudinal models revealed significant group-by-time interactions for the mediodorsal and pulvinar nuclei. Cortical correlations were the strongest for the pulvinar in frontal, temporal and parietal regions, followed by the mediodorsal nucleus in frontal regions, but none in the anterior nucleus. Thalamic measures did not correlate with cognitive and clinical scores at any time point or longitudinally. Overall, findings revealed a pattern of persistent progressive abnormalities in thalamic nuclei that relate to advancing cortical decline in schizophrenia, but not with measures of behavior.

  4. Behavioral training reverses global cortical network dysfunction induced by perinatal antidepressant exposure

    PubMed Central

    Zhou, Xiaoming; Lu, Jordan Y.-F.; Darling, Ryan D.; Simpson, Kimberly L.; Zhu, Xiaoqing; Wang, Fang; Yu, Liping; Sun, Xinde; Merzenich, Michael M.; Lin, Rick C. S.

    2015-01-01

    Abnormal cortical circuitry and function as well as distortions in the modulatory neurological processes controlling cortical plasticity have been argued to underlie the origin of autism. Here, we chemically distorted those processes using an antidepressant drug-exposure model to generate developmental neurological distortions like those characteristics expressed in autism, and then intensively trained altered young rodents to evaluate the potential for neuroplasticity-driven renormalization. We found that young rats that were injected s.c. with the antidepressant citalopram from postnatal d 1–10 displayed impaired neuronal repetition-rate following capacity in the primary auditory cortex (A1). With a focus on recovering grossly degraded auditory system processing in this model, we showed that targeted temporal processing deficits induced by early-life antidepressant exposure within the A1 were almost completely reversed through implementation of a simple behavioral training strategy (i.e., a modified go/no-go repetition-rate discrimination task). Degraded parvalbumin inhibitory GABAergic neurons and the fast inhibitory actions that they control were also renormalized by training. Importantly, antidepressant-induced degradation of serotonergic and dopaminergic neuromodulatory systems regulating cortical neuroplasticity was sharply reversed. These findings bear important implications for neuroplasticity-based therapeutics in autistic patients. PMID:25646455

  5. Switching auditory attention using spatial and non-spatial features recruits different cortical networks.

    PubMed

    Larson, Eric; Lee, Adrian K C

    2014-01-01

    Switching attention between different stimuli of interest based on particular task demands is important in many everyday settings. In audition in particular, switching attention between different speakers of interest that are talking concurrently is often necessary for effective communication. Recently, it has been shown by multiple studies that auditory selective attention suppresses the representation of unwanted streams in auditory cortical areas in favor of the target stream of interest. However, the neural processing that guides this selective attention process is not well understood. Here we investigated the cortical mechanisms involved in switching attention based on two different types of auditory features. By combining magneto- and electro-encephalography (M-EEG) with an anatomical MRI constraint, we examined the cortical dynamics involved in switching auditory attention based on either spatial or pitch features. We designed a paradigm where listeners were cued in the beginning of each trial to switch or maintain attention halfway through the presentation of concurrent target and masker streams. By allowing listeners time to switch during a gap in the continuous target and masker stimuli, we were able to isolate the mechanisms involved in endogenous, top-down attention switching. Our results show a double dissociation between the involvement of right temporoparietal junction (RTPJ) and the left inferior parietal supramarginal part (LIPSP) in tasks requiring listeners to switch attention based on space and pitch features, respectively, suggesting that switching attention based on these features involves at least partially separate processes or behavioral strategies.

  6. Sparse and powerful cortical spikes.

    PubMed

    Wolfe, Jason; Houweling, Arthur R; Brecht, Michael

    2010-06-01

    Activity in cortical networks is heterogeneous, sparse and often precisely timed. The functional significance of sparseness and precise spike timing is debated, but our understanding of the developmental and synaptic mechanisms that shape neuronal discharge patterns has improved. Evidence for highly specialized, selective and abstract cortical response properties is accumulating. Singe-cell stimulation experiments demonstrate a high sensitivity of cortical networks to the action potentials of some, but not all, single neurons. It is unclear how this sensitivity of cortical networks to small perturbations comes about and whether it is a generic property of cortex. The unforeseen sensitivity to cortical spikes puts serious constraints on the nature of neural coding schemes.

  7. Temporal Genetic Modifications after Controlled Cortical Impact—Understanding Traumatic Brain Injury through a Systematic Network Approach

    PubMed Central

    Wong, Yung-Hao; Wu, Chia-Chou; Wu, John Chung-Che; Lai, Hsien-Yong; Chen, Kai-Yun; Jheng, Bo-Ren; Chen, Mien-Cheng; Chang, Tzu-Hao; Chen, Bor-Sen

    2016-01-01

    Traumatic brain injury (TBI) is a primary injury caused by external physical force and also a secondary injury caused by biological processes such as metabolic, cellular, and other molecular events that eventually lead to brain cell death, tissue and nerve damage, and atrophy. It is a common disease process (as opposed to an event) that causes disabilities and high death rates. In order to treat all the repercussions of this injury, treatment becomes increasingly complex and difficult throughout the evolution of a TBI. Using high-throughput microarray data, we developed a systems biology approach to explore potential molecular mechanisms at four time points post-TBI (4, 8, 24, and 72 h), using a controlled cortical impact (CCI) model. We identified 27, 50, 48, and 59 significant proteins as network biomarkers at these four time points, respectively. We present their network structures to illustrate the protein–protein interactions (PPIs). We also identified UBC (Ubiquitin C), SUMO1, CDKN1A (cyclindependent kinase inhibitor 1A), and MYC as the core network biomarkers at the four time points, respectively. Using the functional analytical tool MetaCore™, we explored regulatory mechanisms and biological processes and conducted a statistical analysis of the four networks. The analytical results support some recent findings regarding TBI and provide additional guidance and directions for future research. PMID:26861311

  8. Integrated workflows for spiking neuronal network simulations.

    PubMed

    Antolík, Ján; Davison, Andrew P

    2013-01-01

    The increasing availability of computational resources is enabling more detailed, realistic modeling in computational neuroscience, resulting in a shift toward more heterogeneous models of neuronal circuits, and employment of complex experimental protocols. This poses a challenge for existing tool chains, as the set of tools involved in a typical modeler's workflow is expanding concomitantly, with growing complexity in the metadata flowing between them. For many parts of the workflow, a range of tools is available; however, numerous areas lack dedicated tools, while integration of existing tools is limited. This forces modelers to either handle the workflow manually, leading to errors, or to write substantial amounts of code to automate parts of the workflow, in both cases reducing their productivity. To address these issues, we have developed Mozaik: a workflow system for spiking neuronal network simulations written in Python. Mozaik integrates model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualization into a single automated workflow, ensuring that all relevant metadata are available to all workflow components. It is based on several existing tools, including PyNN, Neo, and Matplotlib. It offers a declarative way to specify models and recording configurations using hierarchically organized configuration files. Mozaik automatically records all data together with all relevant metadata about the experimental context, allowing automation of the analysis and visualization stages. Mozaik has a modular architecture, and the existing modules are designed to be extensible with minimal programming effort. Mozaik increases the productivity of running virtual experiments on highly structured neuronal networks by automating the entire experimental cycle, while increasing the reliability of modeling studies by relieving the user from manual handling of the flow of metadata between the individual workflow stages.

  9. A Possible Role of Prolonged Whirling Episodes on Structural Plasticity of the Cortical Networks and Altered Vertigo Perception: The Cortex of Sufi Whirling Dervishes

    PubMed Central

    Cakmak, Yusuf O.; Ekinci, Gazanfer; Heinecke, Armin; Çavdar, Safiye

    2017-01-01

    Although minutes of a spinning episode may induce vertigo in the healthy human, as a result of a possible perceptional plasticity, Sufi Whirling Dervishes (SWDs) can spin continuously for an hour without a vertigo perception.This unique long term vestibular system stimulation presents a potential human model to clarify the cortical networks underlying the resistance against vertigo. This study, therefore, aimed to investigate the potential structural cortical plasticity in SWDs. Magnetic resonance imaging (MRI) of 10 SWDs and 10 controls were obtained, using a 3T scanner. Cortical thickness in the whole cortex was calculated. Results demonstrated significantly thinner cortical areas for SWD subjects compared with the control group in the hubs of the default mode network (DMN), as well as in the motion perception and discrimination areas including the right dorsolateral prefrontal cortex (DLPFC), the right lingual gyrus and the left visual area 5 (V5)/middle temporal (MT) and the left fusiform gyrus. In conclusion, this is the first report that warrants the potential relationship of the motion/body perception related cortical networks and the prolonged term of whirling ability without vertigo or dizziness. PMID:28167905

  10. Virtual Cortical Resection Reveals Push-Pull Network Control Preceding Seizure Evolution.

    PubMed

    Khambhati, Ankit N; Davis, Kathryn A; Lucas, Timothy H; Litt, Brian; Bassett, Danielle S

    2016-09-07

    In ∼20 million people with drug-resistant epilepsy, focal seizures originating in dysfunctional brain networks will often evolve and spread to surrounding tissue, disrupting function in otherwise normal brain regions. To identify network control mechanisms that regulate seizure spread, we developed a novel tool for pinpointing brain regions that facilitate synchronization in the epileptic network. Our method measures the impact of virtually resecting putative control regions on synchronization in a validated model of the human epileptic network. By applying our technique to time-varying functional networks, we identified brain regions whose topological role is to synchronize or desynchronize the epileptic network. Our results suggest that greater antagonistic push-pull interaction between synchronizing and desynchronizing brain regions better constrains seizure spread. These methods, while applied here to epilepsy, are generalizable to other brain networks and have wide applicability in isolating and mapping functional drivers of brain dynamics in health and disease.

  11. Molecular Dynamics Simulations of Network Glasses

    NASA Astrophysics Data System (ADS)

    Drabold, David A.

    The following sections are included: * Introduction and Background * History and use of MD * The role of the potential * Scope of the method * Use of a priori information * Appraising a model * MD Method * Equations of motion * Energy minimization and equilibration * Deeper or global minima * Simulated annealing * Genetic algorithms * Activation-relaxation technique * Alternate dynamics * Modeling infinite systems: Periodic boundary conditions * The Interatomic Interactions * Overview * Empirical classical potentials * Potentials from electronic structure * The tight-binding method * Approximate methods based on tight-binding * First principles * Local basis: "ab initio tight binding" * Plane-waves: Car-Parrinello methods * Efficient ab initio methods for large systems * The need for locality of electron states in real space * Avoiding explicit orthogonalization * Connecting Simulation to Experiment * Structure * Network dynamics * Computing the harmonic modes * Dynamical autocorrelation functions * Dynamical structure factor * Electronic structure * Density of states * Thermal modulation of the electron states * Transport * Applications * g-GeSe2 * g-GexSe1-x glasses * Amorphous carbon surface * Where to Get Codes to Get Started * Acknowledgments * References

  12. The Role of Oscillations and Synchrony in Cortical Networks and Their Putative Relevance for the Pathophysiology of Schizophrenia

    PubMed Central

    Uhlhaas, Peter J.; Haenschel, Corinna; Nikolić, Danko; Singer, Wolf

    2008-01-01

    Neural oscillations and their synchronization may represent a versatile signal to realize flexible communication within and between cortical areas. By now, there is extensive evidence to suggest that cognitive functions depending on coordination of distributed neural responses, such as perceptual grouping, attention-dependent stimulus selection, subsystem integration, working memory, and consciousness, are associated with synchronized oscillatory activity in the theta-, alpha-, beta-, and gamma-band, suggesting a functional mechanism of neural oscillations in cortical networks. In addition to their role in normal brain functioning, there is increasing evidence that altered oscillatory activity may be associated with certain neuropsychiatric disorders, such as schizophrenia, that involve dysfunctional cognition and behavior. In the following article, we aim to summarize the evidence on the role of neural oscillations during normal brain functioning and their relationship to cognitive processes. In the second part, we review research that has examined oscillatory activity during cognitive and behavioral tasks in schizophrenia. These studies suggest that schizophrenia involves abnormal oscillations and synchrony that are related to cognitive dysfunctions and some of the symptoms of the disorder. Perspectives for future research will be discussed in relationship to methodological issues, the utility of neural oscillations as a biomarker, and the neurodevelopmental hypothesis of schizophrenia. PMID:18562344

  13. Information diversity in structure and dynamics of simulated neuronal networks.

    PubMed

    Mäki-Marttunen, Tuomo; Aćimović, Jugoslava; Nykter, Matti; Kesseli, Juha; Ruohonen, Keijo; Yli-Harja, Olli; Linne, Marja-Leena

    2011-01-01

    Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neuronal network is studied using the normalized compression distance. To describe the structure, a scheme for generating distance-dependent networks with identical in-degree distribution but variable strength of dependence on distance is presented. The resulting network structure classes possess differing path length and clustering coefficient distributions. In parallel, comparable realistic neuronal networks are generated with NETMORPH simulator and similar analysis is done on them. To describe the dynamics, network spike trains are simulated using different network structures and their bursting behaviors are analyzed. For the simulation of the network activity the Izhikevich model of spiking neurons is used together with the Tsodyks model of dynamical synapses. We show that the structure of the simulated neuronal networks affects the spontaneous bursting activity when measured with bursting frequency and a set of intraburst measures: the more locally connected networks produce more and longer bursts than the more random networks. The information diversity of the structure of a network is greatest in the most locally connected networks, smallest in random networks, and somewhere in between in the networks between order and disorder. As for the dynamics, the most locally connected networks and some of the in-between networks produce the most complex intraburst spike trains. The same result also holds for sparser of the two considered network densities in the case of full spike trains.

  14. Scale-Dependent Variability and Quantitative Regimes in Graph-Theoretic Representations of Human Cortical Networks

    PubMed Central

    Irimia, Andrei

    2016-01-01

    Abstract Studying brain connectivity is important due to potential differences in brain circuitry between health and disease. One drawback of graph-theoretic approaches to this is that their results are dependent on the spatial scale at which brain circuitry is examined and explicitly on how vertices and edges are defined in network models. To investigate this, magnetic resonance and diffusion tensor images were acquired from 136 healthy adults, and each subject's cortex was parceled into as many as 50,000 regions. Regions were represented as nodes in a reconstructed network representation, and interregional connectivity was inferred via deterministic tractography. Network model behavior was explored as a function of nodal number and connectivity weighing. Three distinct regimes of quantitative behavior assumed by network models as a function of spatial scale are identified, and their existence may be modulated by the spatial folding scale of the cortex. The maximum number of network nodes used to model human brain circuitry in this study (∼50,000) is larger than in previous macroscale neuroimaging studies. Results suggest that network model properties vary appreciably as a function of vertex assignment convention and edge weighing scheme and that graph-theoretic analysis results should not be compared across spatial scales without appropriate understanding of how spatial scale and model topology modulate network model properties. These findings have implications for comparing macro- to mesoscale studies of brain network models and understanding how choosing network-theoretic parameters affects the interpretation of brain connectivity studies. PMID:26596775

  15. Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

    PubMed Central

    Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

    2016-01-01

    The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

  16. Enriched encoding: reward motivation organizes cortical networks for hippocampal detection of unexpected events.

    PubMed

    Murty, Vishnu P; Adcock, R Alison

    2014-08-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical-hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions-a potentially unique contribution of the hippocampus to reward learning.

  17. In vivo multi-photon nanosurgery on cortical neurons: focusing on network organization

    NASA Astrophysics Data System (ADS)

    Sacconi, L.; O'Connor, R. P.; Jasaitis, A.; Masi, A.; Buffelli, M.; Pavone, F. S.

    2008-02-01

    Two-photon microscopy has been used to perform high spatial resolution imaging of spine plasticity in the intact neocortex of living mice. Multi-photon absorption has also been used as a tool for the selective disruption of cellular structures in living cells and simple organisms. In this work we exploit the spatial localization of multi-photon excitation to perform selective lesions on the neuronal processes of cortical neurons in living mice expressing fluorescent proteins. This methodology was applied to dissect single dendrites with sub-micrometric precision without causing any visible collateral damage to the surrounding neuronal structures. The spatial precision of this method was demonstrated by ablating individual dendritic spines, while sparing the adjacent spines and the structural integrity of the dendrite. The morphological consequences were then characterized with time lapse 3D two-photon imaging over a period of minutes to days after the procedure. Here we present the results of our systematic study of the morphological response of cortical pyramidal neurons to nanosurgical perturbations. Dendritic branches were followed after transecting distal segments, whilst the plasticity and remodeling of individual dendritic spines on a given branch was also followed after removing of a subset of spines.

  18. Simulation of reliability in multiserver computer networks

    NASA Astrophysics Data System (ADS)

    Minkevičius, Saulius

    2012-11-01

    The performance in terms of reliability of computer multiserver networks motivates this paper. The probability limit theorem is derived on the extreme queue length in open multiserver queueing networks in heavy traffic and applied to a reliability model for multiserver computer networks where we relate the time of failure of a multiserver computer network to the system parameters.

  19. Inter-individual variability in cortical excitability and motor network connectivity following multiple blocks of rTMS

    PubMed Central

    Nettekoven, Charlotte; Volz, Lukas J.; Leimbach, Martha; Pool, Eva-Maria; Rehme, Anne K.; Eickhoff, Simon B.; Fink, Gereon R.; Grefkes, Christian

    2016-01-01

    The responsiveness to non-invasive neuromodulation protocols shows high inter-individual variability, the reasons of which remain poorly understood. We here tested whether the response to intermittent theta-burst stimulation (iTBS) – an effective repetitive transcranial magnetic stimulation (rTMS) protocol for increasing cortical excitability – depends on network properties of the cortical motor system. We furthermore investigated whether the responsiveness to iTBS is dose-dependent. To this end, we used a sham-stimulation controlled, single-blinded within-subject design testing for the relationship between iTBS aftereffects and (i) motor-evoked potentials (MEPs) as well as (ii) resting-state functional connectivity (rsFC) in 16 healthy subjects. In each session, three blocks of iTBS were applied, separated by 15 min. We found that non-responders (subjects not showing an MEP increase of ≥10% after one iTBS block) featured stronger rsFC between the stimulated primary motor cortex (M1) and premotor areas before stimulation compared to responders. However, only the group of responders showed increases in rsFC and MEPs, while most non-responders remained close to baseline levels after all three blocks of iTBS. Importantly, there was still a large amount of variability in both groups. Our data suggest that responsiveness to iTBS at the local level (i.e., M1 excitability) depends upon the pre-interventional network connectivity of the stimulated region. Of note, increasing iTBS dose did not turn non-responders into responders. The finding that higher levels of pre-interventional connectivity precluded a response to iTBS could reflect a ceiling effect underlying non-responsiveness to iTBS at the systems level. PMID:26052083

  20. Disruptions in small-world cortical functional connectivity network during an auditory oddball paradigm task in patients with schizophrenia.

    PubMed

    Shim, Miseon; Kim, Do-Won; Lee, Seung-Hwan; Im, Chang-Hwan

    2014-07-01

    P300 deficits in patients with schizophrenia have previously been investigated using EEGs recorded during auditory oddball tasks. However, small-world cortical functional networks during auditory oddball tasks and their relationships with symptom severity scores in schizophrenia have not yet been investigated. In this study, the small-world characteristics of source-level functional connectivity networks of EEG responses elicited by an auditory oddball paradigm were evaluated using two representative graph-theoretical measures, clustering coefficient and path length. EEG signals from 34 patients with schizophrenia and 34 healthy controls were recorded while each subject was asked to attend to oddball tones. The results showed reduced clustering coefficients and increased path lengths in patients with schizophrenia, suggesting that the small-world functional network is disrupted in patients with schizophrenia. In addition, the negative and cognitive symptom components of positive and negative symptom scales were negatively correlated with the clustering coefficient and positively correlated with path length, demonstrating that both indices are indicators of symptom severity in patients with schizophrenia. Our study results suggest that disrupted small-world characteristics are potential biomarkers for patients with schizophrenia.

  1. Evaluation methods of a middleware for networked surgical simulations.

    PubMed

    Cai, Qingbo; Liberatore, Vincenzo; Cavuşoğlu, M Cenk; Yoo, Youngjin

    2006-01-01

    Distributed surgical virtual environments are desirable since they substantially extend the accessibility of computational resources by network communication. However, network conditions critically affects the quality of a networked surgical simulation in terms of bandwidth limit, delays, and packet losses, etc. A solution to this problem is to introduce a middleware between the simulation application and the network so that it can take actions to enhance the user-perceived simulation performance. To comprehensively assess the effectiveness of such a middleware, we propose several evaluation methods in this paper, i.e., semi-automatic evaluation, middleware overhead measurement, and usability test.

  2. A Circuit Simulation Technique for Congested Network Traffic Assignment Problem

    NASA Astrophysics Data System (ADS)

    Cho, Hsun-Jung; Huang, Heng

    2007-12-01

    The relation between electrical circuit and traffic network has been proposed by Sasaki and Inouye, but they proposed link cost function is a linear function which cannot present the congestion situation. Cho and Huang extended the link cost function to a nonlinear function which can explain the congested network. In this paper, we proposed a foremost and novel approach to solve the traffic assignment problem (TAP) by simulating the electrical circuit network which consists of nonlinear link cost function models. Comparing with the solutions of Frank-Wolfe algorithm, the simulation results are nearly identical. Thus, the simulation of a network circuit model can be applied to solve network traffic assignment problems. Finally, two examples are proposed, and the results confirmed that electrical circuit simulation is workable in solving congested network traffic assignment problems.

  3. DELTAMETHRIN AND ESFENVALERATE INHIBIT SPONTANEOUS NETWORK ACTIVITY IN RAT CORTICAL NEURONS IN VITRO.

    EPA Science Inventory

    Understanding pyrethroid actions on neuronal networks will help to establish a mode of action for these compounds, which is needed for cumulative risk decisions under the Food Quality Protection Act of 1996. However, pyrethroid effects on spontaneous activity in networks of inter...

  4. Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study.

    PubMed

    Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Heute, U; Deuschl, G; Raethjen, J; Muthuraman, Muthuraman

    2016-09-01

    Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a

  5. Simulation of Lunar Surface Communications Network Exploration Scenarios

    NASA Technical Reports Server (NTRS)

    Linsky, Thomas W.; Bhasin, Kul B.; White, Alex; Palangala, Srihari

    2006-01-01

    Simulations and modeling of surface-based communications networks provides a rapid and cost effective means of requirement analysis, protocol assessments, and tradeoff studies. Robust testing in especially important for exploration systems, where the cost of deployment is high and systems cannot be easily replaced or repaired. However, simulation of the envisioned exploration networks cannot be achieved using commercial off the shelf network simulation software. Models for the nonstandard, non-COTS protocols used aboard space systems are not readily available. This paper will address the simulation of realistic scenarios representative of the activities which will take place on the surface of the Moon, including selection of candidate network architectures, and the development of an integrated simulation tool using OPNET modeler capable of faithfully modeling those communications scenarios in the variable delay, dynamic surface environments. Scenarios for exploration missions, OPNET development, limitations, and simulations results will be provided and discussed.

  6. Low Frequency Activity of Cortical Networks on Microelectrode Arrays is Differentially Altered by Bicuculline and Carbaryl

    EPA Science Inventory

    Thousands of chemicals need to be characterized for their neurotoxicity potential. Neurons grown on microelectrode arrays (MEAs) are an in vitro model used to screen chemicals for functional effects on neuronal networks. Typically, after removal of low frequency components, effec...

  7. Modeling and Simulation Network Data Standards

    DTIC Science & Technology

    2011-09-30

    Century, Joint Network Analysis Tool, and OPNET . The Architecture Integration Management Division (AIMD), the Army Materiel Systems Analysis Activity...baseline to develop enhancements in data transfers in future projects. 15. SUBJECT TERMS AWARS, COMBATXXI, JNAT, OPNET , network data standards, M&S...B-1 Appendix C. Joint Network Analysis Tool (JNAT) .............................................................. C-1 Appendix D. OPNET

  8. Studies of stimulus parameters for seizure disruption using neural network simulations

    PubMed Central

    Kudela, Pawel; Cho, Ryan J.; Bergey, Gregory K.; Franaszczuk, Piotr

    2009-01-01

    A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic modality. The model consists of an approximately 800 μm × 800 μm region of simulated cortex, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. The cell dynamics are governed by a modified version of the Hodgkin-Huxley equations in single compartment format. Axonal connections are patterned after histological data and published models of local cortical wiring. Stimulation induced action potentials take place at the axon initial segments, according to threshold requirements on the applied electric field distribution. Stimulation induced action potentials in horizontal axonal branches are also separately simulated. The calculations are performed on a 16 node distributed 32-bit processor system. Clear differences in seizure evolution are presented for stimulated versus the undisturbed rhythmic activity. Data is provided for frequency dependent stimulation effects demonstrating a plateau effect of stimulation efficacy as the applied frequency is increased from 60 Hz to 200 Hz. Timing of the stimulation with respect to the underlying rhythmic activity demonstrates a phase dependent sensitivity. Electrode height and position effects are also presented. Using a dipole stimulation electrode arrangement, clear orientation effects of the dipole with respect to the model connectivity is also demonstrated. A sensitivity analysis of these results as a function of the stimulation threshold is also provided. PMID:17619199

  9. Stochastic Computations in Cortical Microcircuit Models

    PubMed Central

    Maass, Wolfgang

    2013-01-01

    Experimental data from neuroscience suggest that a substantial amount of knowledge is stored in the brain in the form of probability distributions over network states and trajectories of network states. We provide a theoretical foundation for this hypothesis by showing that even very detailed models for cortical microcircuits, with data-based diverse nonlinear neurons and synapses, have a stationary distribution of network states and trajectories of network states to which they converge exponentially fast from any initial state. We demonstrate that this convergence holds in spite of the non-reversibility of the stochastic dynamics of cortical microcircuits. We further show that, in the presence of background network oscillations, separate stationary distributions emerge for different phases of the oscillation, in accordance with experimentally reported phase-specific codes. We complement these theoretical results by computer simulations that investigate resulting computation times for typical probabilistic inference tasks on these internally stored distributions, such as marginalization or marginal maximum-a-posteriori estimation. Furthermore, we show that the inherent stochastic dynamics of generic cortical microcircuits enables them to quickly generate approximate solutions to difficult constraint satisfaction problems, where stored knowledge and current inputs jointly constrain possible solutions. This provides a powerful new computing paradigm for networks of spiking neurons, that also throws new light on how networks of neurons in the brain could carry out complex computational tasks such as prediction, imagination, memory recall and problem solving. PMID:24244126

  10. Simulated, Emulated, and Physical Investigative Analysis (SEPIA) of networked systems.

    SciTech Connect

    Burton, David P.; Van Leeuwen, Brian P.; McDonald, Michael James; Onunkwo, Uzoma A.; Tarman, Thomas David; Urias, Vincent E.

    2009-09-01

    This report describes recent progress made in developing and utilizing hybrid Simulated, Emulated, and Physical Investigative Analysis (SEPIA) environments. Many organizations require advanced tools to analyze their information system's security, reliability, and resilience against cyber attack. Today's security analysis utilize real systems such as computers, network routers and other network equipment, computer emulations (e.g., virtual machines) and simulation models separately to analyze interplay between threats and safeguards. In contrast, this work developed new methods to combine these three approaches to provide integrated hybrid SEPIA environments. Our SEPIA environments enable an analyst to rapidly configure hybrid environments to pass network traffic and perform, from the outside, like real networks. This provides higher fidelity representations of key network nodes while still leveraging the scalability and cost advantages of simulation tools. The result is to rapidly produce large yet relatively low-cost multi-fidelity SEPIA networks of computers and routers that let analysts quickly investigate threats and test protection approaches.

  11. Higherorder neural network group models for financial simulation.

    PubMed

    Zhang, M; Zhang, J C; Fulcher, J

    2000-04-01

    Real world financial data is often discontinuous and non-smooth. If we attempt to use neural networks to simulate such functions, then accuracy will be a problem. Neural network group models perform this function much better. Both Polynomial Higher Order Neural network Group (PHONG) and Trigonometric polynomial Higher Order Neural network Group (THONG) models are developed. These HONG models are open box, convergent models capable of approximating any kind of piecewise continuous function, to any degree of accuracy. Moreover they are capable of handling higher frequency, higher order non-linear and discontinuous data. Results obtained using a Higher Order Neural network Group financial simulator are presented, which confirm that HONG group models converge without difficulty, and are considerably more accurate than neural network models (more specifically, around twice as good for prediction, and a factor of four improvement in the case of simulation).

  12. Prefrontal Cortical Network Connections: Key Site of Vulnerability in Stress and Schizophrenia

    PubMed Central

    Arnsten, Amy F.T.

    2011-01-01

    The symptoms of schizophrenia involve profound dysfunction of the prefrontal cortex (PFC). PFC networks create our “mental sketch pad”, and PFC dysfunction contributes to symptoms such as cognitive deficits, thought disorder, delusions and hallucinations. Neuropathological studies of schizophrenia have shown marked loss of dendritic spines in deep layer III, the sublayer where PFC microcircuits reside. The microcircuits consist of recurrent excitatory pyramidal cell networks that interconnect on spines, and excite each other via NMDA receptor signaling. The pyramidal cell persistent firing is sculpted by lateral inhibition from GABAergic basket and chandelier cells, thus creating tuned, persistent firing needed for accurate representational knowledge (i.e. working memory). The strength of pyramidal cell network connections is markedly and flexibly altered by intracellular signaling pathways in dendritic spines, a process called Dynamic Network Connectivity (DNC). DNC proteins such as HCN channels are concentrated on dendritic spines in deep layer III. Under optimal conditions, network inputs to pyramidal cells are strengthened by noradrenergic alpha-2A inhibition of cAMP-HCN channel signaling, and sculpted by dopamine D1-cAMP-HCN channel weakening of inappropriate inputs. However, with stress exposure, high levels of cAMP-HCN channel signaling produces a collapse in network firing. With chronic stress exposure, spines reduce in size and are lost, and this process involves increased PKC signaling. Importantly, molecules that normally strengthen PFC networks connections and/or reverse the stress response, are often genetically altered in schizophrenia. As exposure to stress is a key factor in the precipitation of schizophrenic symptoms, these dysregulated signaling pathways in deep layer III may interact with already vulnerable circuitry to cause spine loss and the descent into illness. PMID:21345366

  13. Cortical rich club regions can organize state-dependent functional network formation by engaging in oscillatory behavior.

    PubMed

    Senden, Mario; Reuter, Niels; van den Heuvel, Martijn P; Goebel, Rainer; Deco, Gustavo

    2017-02-01

    Cognition is hypothesized to require the globally coordinated, functionally relevant integration of otherwise segregated information processing carried out by specialized brain regions. Studies of the macroscopic connectome as well as recent neuroimaging and neuromodeling research have suggested a densely connected collective of cortical hubs, termed the rich club, to provide a central workspace for such integration. In order for rich club regions to fulfill this role they must dispose of a dynamic mechanism by which they can actively shape networks of brain regions whose information processing needs to be integrated. A potential candidate for such a mechanism comes in the form of oscillations which might be employed to establish communication channels among relevant brain regions. We explore this possibility using an integrative approach combining whole-brain computational modeling with neuroimaging, wherein we investigate the local dynamics model brain regions need to exhibit in order to fit (dynamic) network behavior empirically observed for resting as well as a range of task states. We find that rich club regions largely exhibit oscillations during task performance but not during rest. Furthermore, oscillations exhibited by rich club regions can harmonize a set of asynchronous brain regions thus supporting functional coupling among them. These findings are in line with the hypothesis that the rich club can actively shape integration using oscillations.

  14. Extending the Cortical Grasping Network: Pre-supplementary Motor Neuron Activity During Vision and Grasping of Objects

    PubMed Central

    Lanzilotto, Marco; Livi, Alessandro; Maranesi, Monica; Gerbella, Marzio; Barz, Falk; Ruther, Patrick; Fogassi, Leonardo; Rizzolatti, Giacomo; Bonini, Luca

    2016-01-01

    Grasping relies on a network of parieto-frontal areas lying on the dorsolateral and dorsomedial parts of the hemispheres. However, the initiation and sequencing of voluntary actions also requires the contribution of mesial premotor regions, particularly the pre-supplementary motor area F6. We recorded 233 F6 neurons from 2 monkeys with chronic linear multishank neural probes during reaching–grasping visuomotor tasks. We showed that F6 neurons play a role in the control of forelimb movements and some of them (26%) exhibit visual and/or motor specificity for the target object. Interestingly, area F6 neurons form 2 functionally distinct populations, showing either visually-triggered or movement-related bursts of activity, in contrast to the sustained visual-to-motor activity displayed by ventral premotor area F5 neurons recorded in the same animals and with the same task during previous studies. These findings suggest that F6 plays a role in object grasping and extend existing models of the cortical grasping network. PMID:27733538

  15. Segmentation of histology slides of cortical bone using pulse coupled neural networks optimized by particle-swarm optimization.

    PubMed

    Hage, Ilige S; Hamade, Ramsey F

    2013-01-01

    The aim of this study is to automatically discern the micro-features in histology slides of cortical bone using pulse coupled neural networks (PCNN). To the best knowledge of the authors, utilizing PCNN in such an application has not been reported in the literature and, as such, constitutes a novel application. The network parameters are optimized using particle swarm optimization (PSO) where the PSO fitness function was introduced as the entropy and energy of the bone micro-constituents extracted from a training image. Another novel contribution is combining the above with the method of adaptive threshold (T) where the PCNN algorithm is repeated until the best threshold T is found corresponding to the maximum variance between two segmented regions. To illustrate the quality of resulting segmentation according to this methodology, a comparison of the entropy/energy obtained of each pulse is reported. Suitable quality metrics (precision rate, sensitivity, specificity, accuracy, and dice) were used to benchmark the resulting segments against those found by a more traditional method namely K-means. The quality of the segments revealed by this methodology was found to be of much superior quality. Another testament to the quality of this methodology was that the images resulting from testing pulses were found to be of similarly good quality to those of the training images.

  16. Field-programmable gate array implementation of a probabilistic neural network for motor cortical decoding in rats.

    PubMed

    Zhou, Fan; Liu, Jun; Yu, Yi; Tian, Xiang; Liu, Hui; Hao, Yaoyao; Zhang, Shaomin; Chen, Weidong; Dai, Jianhua; Zheng, Xiaoxiang

    2010-01-15

    A practical brain-machine interface (BMI) requires real-time decoding algorithms to be realised in a portable device rather than a personal computer. In this article, a field-programmable gate array (FPGA) implementation of a probabilistic neural network (PNN) is proposed and developed to decode motor cortical ensemble recordings in rats performing a lever-pressing task for water rewards. A chronic 16-channel microelectrode array was implanted into the primary motor cortex of the rat to record neural activity, and the pressure signal of the lever were recorded simultaneously. To decode the pressure value from neural activity, both Matlab-based and FPGA-based mapping algorithms using a PNN were implemented and evaluated. In the FPGA architecture, training data of the network were stored in random access memory (RAM) blocks and multiply-add operations were realised by on-chip DSP48E slices. In the approximation of the activation function, a Taylor series and a look-up table (LUT) are used to achieve an accurate approximation. The results of FPGA implementation are as accurate as the realisation of Matlab, but the running speed is 37.9 times faster. This novel and feasible method indicates that the performance of current FPGAs is competent for portable BMI applications.

  17. Extending the Cortical Grasping Network: Pre-supplementary Motor Neuron Activity During Vision and Grasping of Objects.

    PubMed

    Lanzilotto, Marco; Livi, Alessandro; Maranesi, Monica; Gerbella, Marzio; Barz, Falk; Ruther, Patrick; Fogassi, Leonardo; Rizzolatti, Giacomo; Bonini, Luca

    2016-12-01

    Grasping relies on a network of parieto-frontal areas lying on the dorsolateral and dorsomedial parts of the hemispheres. However, the initiation and sequencing of voluntary actions also requires the contribution of mesial premotor regions, particularly the pre-supplementary motor area F6. We recorded 233 F6 neurons from 2 monkeys with chronic linear multishank neural probes during reaching-grasping visuomotor tasks. We showed that F6 neurons play a role in the control of forelimb movements and some of them (26%) exhibit visual and/or motor specificity for the target object. Interestingly, area F6 neurons form 2 functionally distinct populations, showing either visually-triggered or movement-related bursts of activity, in contrast to the sustained visual-to-motor activity displayed by ventral premotor area F5 neurons recorded in the same animals and with the same task during previous studies. These findings suggest that F6 plays a role in object grasping and extend existing models of the cortical grasping network.

  18. Repeated stimulation of cultured networks of rat cortical neurons induces parallel memory traces

    PubMed Central

    Witteveen, Tim; van Veenendaal, Tamar M.; Dijkstra, Jelle

    2015-01-01

    During systems consolidation, memories are spontaneously replayed favoring information transfer from hippocampus to neocortex. However, at present no empirically supported mechanism to accomplish a transfer of memory from hippocampal to extra-hippocampal sites has been offered. We used cultured neuronal networks on multielectrode arrays and small-scale computational models to study the effect of memory replay on the formation of memory traces. We show that input-deprived networks develop an activity⇔connectivity balance where dominant activity patterns support current connectivity. Electrical stimulation at one electrode disturbs this balance and induces connectivity changes. Intrinsic forces in recurrent networks lead to a new equilibrium with activity patterns that include the stimulus response. The new connectivity is no longer disrupted by this stimulus, indicating that networks memorize it. A different stimulus again induces connectivity changes upon first application but not subsequently, demonstrating the formation of a second memory trace. Returning to the first stimulus does not affect connectivity, indicating parallel storage of both traces. A computer model robustly reproduced experimental results, suggesting that spike-timing-dependent plasticity and short time depression suffice to store parallel memory traces, even in networks without particular circuitry constraints. PMID:26572650

  19. Dynamics of a Cortical Neural Network Based on a Simple Model

    NASA Astrophysics Data System (ADS)

    Qu, Jing-Yi; Wang, Ru-Bin

    2012-08-01

    The collective dynamics of a randomly connected neuronal network motivated by the anatomy of a mammalian cortex based on a simple model are studied. This simple model can not only reproduce the rich behaviors of biological neurons but also has only two equations and one nonlinear term. By varying some key parameters, such as the connection weights of neurons, the external current injection and the noise of intensity, this neuronal network will exhibit various collective behaviors. It is demonstrated that the synchronization status of the neuronal network has a strong relationship with the key parameters and the external current has more influence on the spiking of inhibitory neurons than that of excitatory neurons. These results may be instructive in understanding the collective dynamics of a mammalian cortex.

  20. Graphical user interface for wireless sensor networks simulator

    NASA Astrophysics Data System (ADS)

    Paczesny, Tomasz; Paczesny, Daniel; Weremczuk, Jerzy

    2008-01-01

    Wireless Sensor Networks (WSN) are currently very popular area of development. It can be suited in many applications form military through environment monitoring, healthcare, home automation and others. Those networks, when working in dynamic, ad-hoc model, need effective protocols which must differ from common computer networks algorithms. Research on those protocols would be difficult without simulation tool, because real applications often use many nodes and tests on such a big networks take much effort and costs. The paper presents Graphical User Interface (GUI) for simulator which is dedicated for WSN studies, especially in routing and data link protocols evaluation.

  1. Enriched Encoding: Reward Motivation Organizes Cortical Networks for Hippocampal Detection of Unexpected Events

    PubMed Central

    Murty, Vishnu P.; Adcock, R. Alison

    2014-01-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical–hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions—a potentially unique contribution of the hippocampus to reward learning. PMID:23529005

  2. Functional magnetic resonance imaging adaptation reveals the cortical networks for processing grasp-relevant object properties.

    PubMed

    Monaco, Simona; Chen, Ying; Medendorp, W P; Crawford, J D; Fiehler, Katja; Henriques, Denise Y P

    2014-06-01

    Grasping behaviors require the selection of grasp-relevant object dimensions, independent of overall object size. Previous neuroimaging studies found that the intraparietal cortex processes object size, but it is unknown whether the graspable dimension (i.e., grasp axis between selected points on the object) or the overall size of objects triggers activation in that region. We used functional magnetic resonance imaging adaptation to investigate human brain areas involved in processing the grasp-relevant dimension of real 3-dimensional objects in grasping and viewing tasks. Trials consisted of 2 sequential stimuli in which the object's grasp-relevant dimension, its global size, or both were novel or repeated. We found that calcarine and extrastriate visual areas adapted to object size regardless of the grasp-relevant dimension during viewing tasks. In contrast, the superior parietal occipital cortex (SPOC) and lateral occipital complex of the left hemisphere adapted to the grasp-relevant dimension regardless of object size and task. Finally, the dorsal premotor cortex adapted to the grasp-relevant dimension in grasping, but not in viewing, tasks, suggesting that motor processing was complete at this stage. Taken together, our results provide a complete cortical circuit for progressive transformation of general object properties into grasp-related responses.

  3. Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations.

    PubMed

    Gollo, Leonardo L; Zalesky, Andrew; Hutchison, R Matthew; van den Heuvel, Martijn; Breakspear, Michael

    2015-05-19

    For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously--elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow timescales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding 'feeder' cortical regions shows unstable, rapidly fluctuating dynamics likely to be crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.

  4. Afferent inputs to cortical fast-spiking interneurons organize pyramidal cell network oscillations at high-gamma frequencies (60–200 Hz)

    PubMed Central

    Crone, Nathan E.; Franaszczuk, Piotr J.

    2014-01-01

    High-gamma activity, ranging in frequency between ∼60 Hz and 200 Hz, has been observed in local field potential, electrocorticography, EEG and magnetoencephalography signals during cortical activation, in a variety of functional brain systems. The origin of these signals is yet unknown. Using computational modeling, we show that a cortical network model receiving thalamic input generates high-gamma responses comparable to those observed in local field potential recorded in monkey somatosensory cortex during vibrotactile stimulation. These high-gamma oscillations appear to be mediated mostly by an excited population of inhibitory fast-spiking interneurons firing at high-gamma frequencies and pacing excitatory regular-spiking pyramidal cells, which fire at lower rates but in phase with the population rhythm. The physiological correlates of high-gamma activity, in this model of local cortical circuits, appear to be similar to those proposed for hippocampal ripples generated by subsets of interneurons that regulate the discharge of principal cells. PMID:25210164

  5. A Flexible System for Simulating Aeronautical Telecommunication Network

    NASA Technical Reports Server (NTRS)

    Maly, Kurt; Overstreet, C. M.; Andey, R.

    1998-01-01

    At Old Dominion University, we have built Aeronautical Telecommunication Network (ATN) Simulator with NASA being the fund provider. It provides a means to evaluate the impact of modified router scheduling algorithms on the network efficiency, to perform capacity studies on various network topologies and to monitor and study various aspects of ATN through graphical user interface (GUI). In this paper we describe briefly about the proposed ATN model and our abstraction of this model. Later we describe our simulator architecture highlighting some of the design specifications, scheduling algorithms and user interface. At the end, we have provided the results of performance studies on this simulator.

  6. Interfacing Network Simulations and Empirical Data

    DTIC Science & Technology

    2009-05-01

    rely on various empirical datasets and provide analytical results on the nature and structure of the social networks observed in them. 15. SUBJECT...become an important analytic tool for analyzing terrorist networks, friendly command and control structures , arms trade, biological warfare, and the...1979; Wasserman, 1994). SNA thus relies heavily on graph theory to make predictions about network structure . Nodes are defined in terms of a

  7. Repeated Stimulation of Cultured Networks of Rat Cortical Neurons Induces Parallel Memory Traces

    ERIC Educational Resources Information Center

    le Feber, Joost; Witteveen, Tim; van Veenendaal, Tamar M.; Dijkstra, Jelle

    2015-01-01

    During systems consolidation, memories are spontaneously replayed favoring information transfer from hippocampus to neocortex. However, at present no empirically supported mechanism to accomplish a transfer of memory from hippocampal to extra-hippocampal sites has been offered. We used cultured neuronal networks on multielectrode arrays and…

  8. A neural network simulation package in CLIPS

    NASA Technical Reports Server (NTRS)

    Bhatnagar, Himanshu; Krolak, Patrick D.; Mcgee, Brenda J.; Coleman, John

    1990-01-01

    The intrinsic similarity between the firing of a rule and the firing of a neuron has been captured in this research to provide a neural network development system within an existing production system (CLIPS). A very important by-product of this research has been the emergence of an integrated technique of using rule based systems in conjunction with the neural networks to solve complex problems. The systems provides a tool kit for an integrated use of the two techniques and is also extendible to accommodate other AI techniques like the semantic networks, connectionist networks, and even the petri nets. This integrated technique can be very useful in solving complex AI problems.

  9. Task complexity and location specific changes of cortical thickness in executive and salience networks after working memory training

    PubMed Central

    Metzler-Baddeley, Claudia; Caeyenberghs, Karen; Foley, Sonya; Jones, Derek K.

    2016-01-01

    Novel activities and experiences shape the brain's structure and organisation and, hence, our behaviour. However, evidence from structural plasticity studies remains mixed and the neural correlates of learning and practice are still poorly understood. We conducted a robustly designed study into grey matter plasticity following 2 months of working memory training. We generated a priori hypotheses regarding the location of plastic effects across three cognitive control networks (executive, anterior salience and basal ganglia networks), and compared the effects of adaptive training (n = 20) with a well-matched active control group (n = 20) which differed in training complexity and included extensive cognitive assessment before and after the training. Adaptive training relative to control activities resulted in a complex pattern of subtle and localised structural changes: Training was associated with increases in cortical thickness in right-lateralised executive regions, notably the right caudal middle frontal cortex, as well as increases in the volume of the left pallidum. In addition the training group showed reductions of thickness in the right insula, which were correlated with training-induced improvements in backward digit span performance. Unexpectedly, control activities were associated with reductions in thickness in the right pars triangularis. These results suggest that the direction of activity-induced plastic changes depend on the level of training complexity as well as brain location. These observations are consistent with the view that the brain responds dynamically to environmental demands by focusing resources on task relevant networks and eliminating irrelevant processing for the purpose of energy reduction. PMID:26806288

  10. Parallel discrete-event simulation of FCFS stochastic queueing networks

    NASA Technical Reports Server (NTRS)

    Nicol, David M.

    1988-01-01

    Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

  11. A GIS Tool for simulating Nitrogen transport along schematic Network

    NASA Astrophysics Data System (ADS)

    Tavakoly, A. A.; Maidment, D. R.; Yang, Z.; Whiteaker, T.; David, C. H.; Johnson, S.

    2012-12-01

    An automated method called the Arc Hydro Schematic Processor has been developed for water process computation on schematic networks formed from the NHDPlus and similar GIS river networks. The sechemtaic network represents the hydrologic feature on the ground and is a network of links and nodes. SchemaNodes show hydrologic features, such as catchments or stream junctions. SchemaLinks prescripe the connections between nodes. The schematic processor uses the schematic network to pass informatin through a watershed and move water or pollutants dwonstream. In addition, the schematic processor has a capability to use additional programming applied to the passed and/or received values and manipulating data trough network. This paper describes how the schemtic processor can be used to simulate nitrogen transport and transformation on river networks. For this purpose the nitrogen loads is estimated on the NHDPlus river network using the Schematic Processor coupled with the river routing model for the Texas Gulf Coast Hydrologic Region.

  12. Attaining Realistic Simulations of Mobile Ad-hoc Networks

    DTIC Science & Technology

    2010-06-01

    Optimized 2-8 Network Engineering Tools ( OPNET ) [33], and Global Mobile Information Systems Simulation Library (GloMoSim) [30]. NS and GloMoSim are...both provided as open use software to researchers, whereas OPNET is a commercial simulation engine. While all of these engines can simulate MANETs, the...key environmental and technical aspects have yet to be accurately modeled in any of the major simulation engines such as OPNET Modeler, NS-2, or

  13. A Network Contention Model for the Extreme-scale Simulator

    SciTech Connect

    Engelmann, Christian; Naughton III, Thomas J

    2015-01-01

    The Extreme-scale Simulator (xSim) is a performance investigation toolkit for high-performance computing (HPC) hardware/software co-design. It permits running a HPC application with millions of concurrent execution threads, while observing its performance in a simulated extreme-scale system. This paper details a newly developed network modeling feature for xSim, eliminating the shortcomings of the existing network modeling capabilities. The approach takes a different path for implementing network contention and bandwidth capacity modeling using a less synchronous and accurate enough model design. With the new network modeling feature, xSim is able to simulate on-chip and on-node networks with reasonable accuracy and overheads.

  14. Segmentation of nanotomographic cortical bone images for quantitative characterization of the osteoctyte lacuno-canalicular network

    NASA Astrophysics Data System (ADS)

    Ciani, A.; Guizar-Sicairos, M.; Diaz, A.; Holler, M.; Pallu, S.; Achiou, Z.; Jennane, R.; Toumi, H.; Lespessailles, E.; Kewish, C. M.

    2016-01-01

    A newly developed data processing method able to characterize the osteocytes lacuno-canalicular network (LCN) is presented. Osteocytes are the most abundant cells in the bone, living in spaces called lacunae embedded inside the bone matrix and connected to each other with an extensive network of canals that allows for the exchange of nutrients and for mechanotransduction functions. The geometrical three-dimensional (3D) architecture is increasingly thought to be related to the macroscopic strength or failure of the bone and it is becoming the focus for investigating widely spread diseases such as osteoporosis. To obtain 3D LCN images non-destructively has been out of reach until recently, since tens-of-nanometers scale resolution is required. Ptychographic tomography was validated for bone imaging in [1], showing clearly the LCN. The method presented here was applied to 3D ptychographic tomographic images in order to extract morphological and geometrical parameters of the lacuno-canalicular structures.

  15. Synaptic and Network Mechanisms of Sparse and Reliable Visual Cortical Activity during Nonclassical Receptive Field Stimulation

    PubMed Central

    Haider, Bilal; Krause, Matthew R.; Duque, Alvaro; Yu, Yuguo; Touryan, Jonathan; Mazer, James A.; McCormick, David A.

    2011-01-01

    SUMMARY During natural vision, the entire visual field is stimulated by images rich in spatiotemporal structure. Although many visual system studies restrict stimuli to the classical receptive field (CRF), it is known that costimulation of the CRF and the surrounding nonclassical receptive field (nCRF) increases neuronal response sparseness. The cellular and network mechanisms underlying increased response sparseness remain largely unexplored. Here we show that combined CRF + nCRF stimulation increases the sparseness, reliability, and precision of spiking and membrane potential responses in classical regular spiking (RSC) pyramidal neurons of cat primary visual cortex. Conversely, fast-spiking interneurons exhibit increased activity and decreased selectivity during CRF + nCRF stimulation. The increased sparseness and reliability of RSC neuron spiking is associated with increased inhibitory barrages and narrower visually evoked synaptic potentials. Our experimental observations were replicated with a simple computational model, suggesting that network interactions among neuronal subtypes ultimately sharpen recurrent excitation, producing specific and reliable visual responses. PMID:20152117

  16. Segmentation of nanotomographic cortical bone images for quantitative characterization of the osteoctyte lacuno-canalicular network

    SciTech Connect

    Ciani, A.; Kewish, C. M.; Guizar-Sicairos, M.; Diaz, A.; Holler, M.; Pallu, S.; Achiou, Z.; Jennane, R.; Toumi, H.; Lespessailles, E.

    2016-01-28

    A newly developed data processing method able to characterize the osteocytes lacuno-canalicular network (LCN) is presented. Osteocytes are the most abundant cells in the bone, living in spaces called lacunae embedded inside the bone matrix and connected to each other with an extensive network of canals that allows for the exchange of nutrients and for mechanotransduction functions. The geometrical three-dimensional (3D) architecture is increasingly thought to be related to the macroscopic strength or failure of the bone and it is becoming the focus for investigating widely spread diseases such as osteoporosis. To obtain 3D LCN images non-destructively has been out of reach until recently, since tens-of-nanometers scale resolution is required. Ptychographic tomography was validated for bone imaging in [1], showing clearly the LCN. The method presented here was applied to 3D ptychographic tomographic images in order to extract morphological and geometrical parameters of the lacuno-canalicular structures.

  17. Relating Cortical Atrophy in Temporal Lobe Epilepsy with Graph Diffusion-Based Network Models

    PubMed Central

    Abdelnour, Farras; Mueller, Susanne; Raj, Ashish

    2015-01-01

    Mesial temporal lobe epilepsy (TLE) is characterized by stereotyped origination and spread pattern of epileptogenic activity, which is reflected in stereotyped topographic distribution of neuronal atrophy on magnetic resonance imaging (MRI). Both epileptogenic activity and atrophy spread appear to follow white matter connections. We model the networked spread of activity and atrophy in TLE from first principles via two simple first order network diffusion models. Atrophy distribution is modeled as a simple consequence of the propagation of epileptogenic activity in one model, and as a progressive degenerative process in the other. We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no). Statistical validation at the group level suggests high correlation with measured atrophy (R = 0.586 for TLE-MTS, R = 0.283 for TLE-no). We conclude that atrophy spread model out-performs the hyperactivity spread model. These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning. PMID:26513579

  18. Lightweight simulation of air traffic control using simple temporal networks

    NASA Technical Reports Server (NTRS)

    Knight, Russell

    2005-01-01

    We provide a formulation of the air traffic control problem and a solver for this problem that makes use of temporal constraint networks and simple geometric reasoning. We provide results showing that this approach is practical for realistic simulated problems.

  19. Using automatic programming for simulating reliability network models

    NASA Technical Reports Server (NTRS)

    Tseng, Fan T.; Schroer, Bernard J.; Zhang, S. X.; Wolfsberger, John W.

    1988-01-01

    This paper presents the development of an automatic programming system for assisting modelers of reliability networks to define problems and then automatically generate the corresponding code in the target simulation language GPSS/PC.

  20. A chronometric functional sub-network in the thalamo-cortical system regulates the flow of neural information necessary for conscious cognitive processes.

    PubMed

    León-Domínguez, Umberto; Vela-Bueno, Antonio; Froufé-Torres, Manuel; León-Carrión, Jose

    2013-06-01

    The thalamo-cortical system has been defined as a neural network associated with consciousness. While there seems to be wide agreement that the thalamo-cortical system directly intervenes in vigilance and arousal, a divergence of opinion persists regarding its intervention in the control of other cognitive processes necessary for consciousness. In the present manuscript, we provide a review of recent scientific findings on the thalamo-cortical system and its role in the control and regulation of the flow of neural information necessary for conscious cognitive processes. We suggest that the axis formed by the medial prefrontal cortex and different thalamic nuclei (reticular nucleus, intralaminar nucleus, and midline nucleus), represents a core component for consciousness. This axis regulates different cerebral structures which allow basic cognitive processes like attention, arousal and memory to emerge. In order to produce a synchronized coherent response, neural communication between cerebral structures must have exact timing (chronometry). Thus, a chronometric functional sub-network within the thalamo-cortical system keeps us in an optimal and continuous functional state, allowing high-order cognitive processes, essential to awareness and qualia, to take place.

  1. Ranking important nodes in complex networks by simulated annealing

    NASA Astrophysics Data System (ADS)

    Sun, Yu; Yao, Pei-Yang; Wan, Lu-Jun; Shen, Jian; Zhong, Yun

    2017-02-01

    In this paper, based on simulated annealing a new method to rank important nodes in complex networks is presented. First, the concept of an importance sequence (IS) to describe the relative importance of nodes in complex networks is defined. Then, a measure used to evaluate the reasonability of an IS is designed. By comparing an IS and the measure of its reasonability to a state of complex networks and the energy of the state, respectively, the method finds the ground state of complex networks by simulated annealing. In other words, the method can construct a most reasonable IS. The results of experiments on real and artificial networks show that this ranking method not only is effective but also can be applied to different kinds of complex networks. Project supported by the National Natural Science Foundation of China (Grant No. 61573017) and the Natural Science Foundation of Shaanxi Province, China (Grant No. 2016JQ6062).

  2. Simulation study of magnetic resonance imaging-guided cortically constrained diffuse optical tomography of human brain function

    NASA Astrophysics Data System (ADS)

    Boas, David A.; Dale, Anders M.

    2005-04-01

    Diffuse optical imaging can measure brain activity noninvasively in humans through the scalp and skull by measuring the light intensity modulation arising from localized-activity-induced absorption changes within the cortex. Spatial resolution and localization accuracy are currently limited by measurement geometry to approximately 3 cm in the plane parallel to the scalp. Depth resolution is a more significant challenge owing to the limited angle tomography permitted by reflectance-only measurements. We combine previously established concepts for improving image quality and demonstrate, through simulation studies, their application for improving the image quality of adult human brain function. We show in a three-dimensional human head model that localization accuracy is significantly improved by the addition of measurements that provide overlapping samples of brain tissue. However, the reconstructed absorption contrast is significantly underestimated because its depth is underestimated. We show that the absorption contrast amplitude accuracy can be significantly improved by providing a cortical spatial constraint in the image reconstruction to obtain a better depth localization. The cortical constraint makes physiological sense since the brain-activity-induced absorption changes are occurring in the cortex and not in the scalp, skull, and cerebral spinal fluid. This spatial constraint is provided by segmentation of coregistered structural magnetic resonance imaging (MRI). However, the absorption contrast deep within the cortex is reconstructed superficially, resulting in an underestimation of the absorption contrast. The synthesis of techniques described here indicates that multimodality imaging of brain function with diffuse optical imaging and MRI has the potential to provide more quantitative estimates of the total and deoxyhemoglobin response to brain activation, which is currently not provided by either method independently. However, issues of depth resolution

  3. Evoked cortical activity and speech recognition as a function of the number of simulated cochlear implant channels

    PubMed Central

    Friesen, L.M; Tremblay, K.L.; Rohila, N.; Wright, R.A.; Shannon, R.V.; Başkent, D.; Rubinstein, J.T.

    2009-01-01

    Objectives 1) to determine if consonant-vowel-consonant (CVC) syllables from the Hillenbrand et al. [1995] test could be used to evoke cortical far field response patterns in humans, 2) to characterize the effects of cochlear implant-simulated channel number on the perception and physiological detection of these same CVC stimuli, and 3) to define the relationship between perception and the morphology of the physiological responses evoked by these speech stimuli. Methods Ten normal hearing monolingual English speaking adults were tested. Unprocessed CVC naturally spoken syllables, containing medial vowels, as well as processed versions (2, 4, 8, 12, and 16 spectral channels) were used for behavioral and physiological testing. Results 1) CVC stimuli evoked a series of overlapping P1-N1-P2 cortical responses. 2) Amplitude of P1-N1-P2 responses increased as neural conduction time (latency) decreased with increases in the number of spectral channels. Perception of the CVC stimuli improved with increasing number of spectral channels. 3) Coinciding changes in P1-N1-P2 morphology did not significantly correlate with changes in perception. Conclusions P1-N1-P2 responses can be recorded using CVC syllables and there is an effect of channel number on the latency and amplitude of these responses, as well as on vowel identification. However, the physiological detection of the acoustic changes does not fully account for the perceptual performance of these same syllables. Significance These results provide evidence that it is possible to use vocoded CVC stimuli to learn more about the physiological detection of acoustic changes contained within speech syllables, as well as to explore brain-behavior relationships. PMID:19250865

  4. Individual-specific multi-scale finite element simulation of cortical bone of human proximal femur

    SciTech Connect

    Ascenzi, Maria-Grazia; Kardas, Dieter; Nackenhorst, Udo; Keyak, Joyce H.

    2013-07-01

    We present an innovative method to perform multi-scale finite element analyses of the cortical component of the femur using the individual’s (1) computed tomography scan; and (2) a bone specimen obtained in conjunction with orthopedic surgery. The method enables study of micro-structural characteristics regulating strains and stresses under physiological loading conditions. The analysis of the micro-structural scenarios that cause variation of strain and stress is the first step in understanding the elevated strains and stresses in bone tissue, which are indicative of higher likelihood of micro-crack formation in bone, implicated in consequent remodeling or macroscopic bone fracture. Evidence that micro-structure varies with clinical history and contributes in significant, but poorly understood, ways to bone function, motivates the method’s development, as does need for software tools to investigate relationships between macroscopic loading and micro-structure. Three applications – varying region of interest, bone mineral density, and orientation of collagen type I, illustrate the method. We show, in comparison between physiological loading and simple compression of a patient’s femur, that strains computed at the multi-scale model’s micro-level: (i) differ; and (ii) depend on local collagen-apatite orientation and degree of calcification. Our findings confirm the strain concentration role of osteocyte lacunae, important for mechano-transduction. We hypothesize occurrence of micro-crack formation, leading either to remodeling or macroscopic fracture, when the computed strains exceed the elastic range observed in micro-structural testing.

  5. Simultaneous EEG and fMRI reveals a causally connected subcortical-cortical network during reward anticipation.

    PubMed

    Plichta, Michael M; Wolf, Isabella; Hohmann, Sarah; Baumeister, Sarah; Boecker, Regina; Schwarz, Adam J; Zangl, Maria; Mier, Daniela; Diener, Carsten; Meyer, Patric; Holz, Nathalie; Ruf, Matthias; Gerchen, Martin F; Bernal-Casas, David; Kolev, Vasil; Yordanova, Juliana; Flor, Herta; Laucht, Manfred; Banaschewski, Tobias; Kirsch, Peter; Meyer-Lindenberg, Andreas; Brandeis, Daniel

    2013-09-04

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been used to study the neural correlates of reward anticipation, but the interrelation of EEG and fMRI measures remains unknown. The goal of the present study was to investigate this relationship in response to a well established reward anticipation paradigm using simultaneous EEG-fMRI recording in healthy human subjects. Analysis of causal interactions between the thalamus (THAL), ventral-striatum (VS), and supplementary motor area (SMA), using both mediator analysis and dynamic causal modeling, revealed that (1) THAL fMRI blood oxygenation level-dependent (BOLD) activity is mediating intermodal correlations between the EEG contingent negative variation (CNV) signal and the fMRI BOLD signal in SMA and VS, (2) the underlying causal connectivity network consists of top-down regulation from SMA to VS and SMA to THAL along with an excitatory information flow through a THAL→VS→SMA route during reward anticipation, and (3) the EEG CNV signal is best predicted by a combination of THAL fMRI BOLD response and strength of top-down regulation from SMA to VS and SMA to THAL. Collectively, these findings represent a likely neurobiological mechanism mapping a primarily subcortical process, i.e., reward anticipation, onto a cortical signature.

  6. Measurement of saturation processes in glutamatergic and GABAergic synapse densities during long-term development of cultured rat cortical networks.

    PubMed

    Ito, Daisuke; Komatsu, Takumi; Gohara, Kazutoshi

    2013-10-09

    The aim of this study was to clarify the saturation processes of excitatory and inhibitory synapse densities during the long-term development of cultured neuronal networks. For this purpose, we performed a long-term culture of rat cortical cells for 35 days in vitro (DIV). During this culture period, we labeled glutamatergic and GABAergic synapses separately using antibodies against vesicular glutamate transporter 1 (VGluT1) and vesicular transporter of γ-aminobutyric acid (VGAT). The densities and distributions of both types of synaptic terminals were measured simultaneously. Observations and subsequent measurements of immunofluorescence demonstrated that the densities of both types of antibody-labeled terminals increased gradually from 7 to 21-28 DIV. The densities did not show a further increase at 35 DIV and tended to become saturated. Triple staining with VGluT1, VGAT, and microtubule-associated protein 2 (MAP2) enabled analysis of the distribution of both types of synapses, and revealed that the densities of the two types of synaptic terminals on somata were not significantly different, but that glutamatergic synapses predominated on the dendrites during long-term culture. However, some neurons did not fall within this distribution, suggesting differences in synapse distribution on target neurons. The electrical activity also showed an initial increase and subsequent saturation of the firing rate and synchronized burst rate during long-term culture, and the number of days of culture to saturation from the initial increase followed the same pattern under this culture condition.

  7. Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks

    PubMed Central

    DeMarse, Thomas B.; Pan, Liangbin; Alagapan, Sankaraleengam; Brewer, Gregory J.; Wheeler, Bruce C.

    2016-01-01

    Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura’s and van Rossum’s spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous

  8. Influence of slow oscillation on hippocampal activity and ripples through cortico-hippocampal synaptic interactions, analyzed by a cortical-CA3-CA1 network model

    PubMed Central

    Taxidis, Jiannis; Mizuseki, Kenji; Mason, Robert; Owen, Markus R.

    2013-01-01

    Hippocampal sharp wave-ripple complexes (SWRs) involve the synchronous discharge of thousands of cells throughout the CA3-CA1-subiculum-entorhinal cortex axis. Their strong transient output affects cortical targets, rendering SWRs a possible means for memory transfer from the hippocampus to the neocortex for long-term storage. Neurophysiological observations of hippocampal activity modulation by the cortical slow oscillation (SO) during deep sleep and anesthesia, and correlations between ripples and UP states, support the role of SWRs in memory consolidation through a cortico-hippocampal feedback loop. We couple a cortical network exhibiting SO with a hippocampal CA3-CA1 computational network model exhibiting SWRs, in order to model such cortico-hippocampal correlations and uncover important parameters and coupling mechanisms controlling them. The cortical oscillatory output entrains the CA3 network via connections representing the mossy fiber input, and the CA1 network via the temporoammonic pathway (TA). The spiking activity in CA3 and CA1 is shown to depend on the excitation-to-inhibition ratio, induced by combining the two hippocampal inputs, with mossy fiber input controlling the UP-state correlation of CA3 population bursts and corresponding SWRs, whereas the temporoammonic input affects the overall CA1 spiking activity. Ripple characteristics and pyramidal spiking participation to SWRs are shaped by the strength of the Schaffer collateral drive. A set of in vivo recordings from the rat hippocampus confirms a model-predicted segregation of pyramidal cells into subgroups according to the SO state where they preferentially fire and their response to SWRs. These groups can potentially play distinct functional roles in the replay of spike sequences. PMID:23386827

  9. Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks

    PubMed Central

    Garofalo, Matteo; Nieus, Thierry; Massobrio, Paolo; Martinoia, Sergio

    2009-01-01

    Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these “connectivity methods” on neuronal network models at an increasing level of complexity and evaluated the performance in terms of ROC (Receiver Operating Characteristic) and PPC (Positive Precision Curve), a new defined complementary method specifically developed for functional links identification. Then, the algorithms better estimated the actual connectivity of the network models, were used to extract functional connectivity from cultured cortical networks coupled to MEAs. Among the proposed approaches, Transfer Entropy and Joint-Entropy showed the best results suggesting those methods as good candidates to extract functional links in actual neuronal networks from multi-site recordings. PMID:19652720

  10. PyNN: A Common Interface for Neuronal Network Simulators

    PubMed Central

    Davison, Andrew P.; Brüderle, Daniel; Eppler, Jochen; Kremkow, Jens; Muller, Eilif; Pecevski, Dejan; Perrinet, Laurent; Yger, Pierre

    2008-01-01

    Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. This impedes communication between investigators and makes it harder to reproduce and build on the work of others. On the other hand, simulation results can be cross-checked between different simulators, giving greater confidence in their correctness, and each simulator has different optimizations, so the most appropriate simulator can be chosen for a given modelling task. A common programming interface to multiple simulators would reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware). PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators. PyNN is open-source software and is available from http://neuralensemble.org/PyNN. PMID:19194529

  11. Efficient event-driven simulations shed new light on microtubule organization in the plant cortical array

    NASA Astrophysics Data System (ADS)

    Tindemans, Simon H.; Deinum, Eva E.; Lindeboom, Jelmer J.; Mulder, Bela M.

    2014-04-01

    The dynamics of the plant microtubule cytoskeleton is a paradigmatic example of the complex spatiotemporal processes characterising life at the cellular scale. This system is composed of large numbers of spatially extended particles, each endowed with its own intrinsic stochastic dynamics, and is capable of non-equilibrium self-organisation through collisional interactions of these particles. To elucidate the behaviour of such a complex system requires not only conceptual advances, but also the development of appropriate computational tools to simulate it. As the number of parameters involved is large and the behaviour is stochastic, it is essential that these simulations be fast enough to allow for an exploration of the phase space and the gathering of sufficient statistics to accurately pin down the average behaviour as well as the magnitude of fluctuations around it. Here we describe a simulation approach that meets this requirement by adopting an event-driven methodology that encompasses both the spontaneous stochastic changes in microtubule state as well as the deterministic collisions. In contrast with finite time step simulations this technique is intrinsically exact, as well as several orders of magnitude faster, which enables ordinary PC hardware to simulate systems of ˜ 10^3 microtubules on a time scale ˜ 10^{3} faster than real time. In addition we present new tools for the analysis of microtubule trajectories on curved surfaces. We illustrate the use of these methods by addressing a number of outstanding issues regarding the importance of various parameters on the transition from an isotropic to an aligned and oriented state.

  12. Separate cortical networks involved in music perception: preliminary functional MRI evidence for modularity of music processing.

    PubMed

    Schmithorst, Vincent J

    2005-04-01

    Music perception is a quite complex cognitive task, involving the perception and integration of various elements including melody, harmony, pitch, rhythm, and timbre. A preliminary functional MRI investigation of music perception was performed, using a simplified passive listening task. Group independent component analysis (ICA) was used to separate out various components involved in music processing, as the hemodynamic responses are not known a priori. Various components consistent with auditory processing, expressive language, syntactic processing, and visual association were found. The results are discussed in light of various hypotheses regarding modularity of music processing and its overlap with language processing. The results suggest that, while some networks overlap with ones used for language processing, music processing may involve its own domain-specific processing subsystems.

  13. A gene network simulator to assess reverse engineering algorithms.

    PubMed

    Di Camillo, Barbara; Toffolo, Gianna; Cobelli, Claudio

    2009-03-01

    In the context of reverse engineering of biological networks, simulators are helpful to test and compare the accuracy of different reverse-engineering approaches in a variety of experimental conditions. A novel gene-network simulator is presented that resembles some of the main features of transcriptional regulatory networks related to topology, interaction among regulators of transcription, and expression dynamics. The simulator generates network topology according to the current knowledge of biological network organization, including scale-free distribution of the connectivity and clustering coefficient independent of the number of nodes in the network. It uses fuzzy logic to represent interactions among the regulators of each gene, integrated with differential equations to generate continuous data, comparable to real data for variety and dynamic complexity. Finally, the simulator accounts for saturation in the response to regulation and transcription activation thresholds and shows robustness to perturbations. It therefore provides a reliable and versatile test bed for reverse engineering algorithms applied to microarray data. Since the simulator describes regulatory interactions and expression dynamics as two distinct, although interconnected aspects of regulation, it can also be used to test reverse engineering approaches that use both microarray and protein-protein interaction data in the process of learning. A first software release is available at http://www.dei.unipd.it/~dicamill/software/netsim as an R programming language package.

  14. Combined exposure to simulated microgravity and acute or chronic radiation reduces neuronal network integrity and cell survival

    NASA Astrophysics Data System (ADS)

    Benotmane, Rafi

    During orbital or interplanetary space flights, astronauts are exposed to cosmic radiations and microgravity. This study aimed at assessing the effect of these combined conditions on neuronal network density, cell morphology and survival, using well-connected mouse cortical neuron cultures. To this end, neurons were exposed to acute low and high doses of low LET (X-rays) radiation or to chronic low dose-rate of high LET neutron irradiation (Californium-252), under the simulated microgravity generated by the Random Positioning Machine (RPM, Dutch space). High content image analysis of cortical neurons positive for the neuronal marker βIII-tubulin unveiled a reduced neuronal network integrity and connectivity, and an altered cell morphology after exposure to acute/chronic radiation or to simulated microgravity. Additionally, in both conditions, a defect in DNA-repair efficiency was revealed by an increased number of γH2AX-positive foci, as well as an increased number of Annexin V-positive apoptotic neurons. Of interest, when combining both simulated space conditions, we noted a synergistic effect on neuronal network density, neuronal morphology, cell survival and DNA repair. Furthermore, these observations are in agreement with preliminary gene expression data, revealing modulations in cytoskeletal and apoptosis-related genes after exposure to simulated microgravity. In conclusion, the observed in vitro changes in neuronal network integrity and cell survival induced by space simulated conditions provide us with mechanistic understanding to evaluate health risks and the development of countermeasures to prevent neurological disorders in astronauts over long-term space travels. Acknowledgements: This work is supported partly by the EU-FP7 projects CEREBRAD (n° 295552)

  15. Delay Tolerant Networking - Bundle Protocol Simulation

    NASA Technical Reports Server (NTRS)

    SeGui, John; Jenning, Esther

    2006-01-01

    In this paper, we report on the addition of MACHETE models needed to support DTN, namely: the Bundle Protocol (BP) model. To illustrate the useof MACHETE with the additional DTN model, we provide an example simulation to benchmark its performance. We demonstrate the use of the DTN protocol and discuss statistics gathered concerning the total time needed to simulate numerous bundle transmissions.

  16. Simulating and Synthesizing Substructures Using Neural Network and Genetic Algorithms

    NASA Technical Reports Server (NTRS)

    Liu, Youhua; Kapania, Rakesh K.; VanLandingham, Hugh F.

    1997-01-01

    The feasibility of simulating and synthesizing substructures by computational neural network models is illustrated by investigating a statically indeterminate beam, using both a 1-D and a 2-D plane stress modelling. The beam can be decomposed into two cantilevers with free-end loads. By training neural networks to simulate the cantilever responses to different loads, the original beam problem can be solved as a match-up between two subsystems under compatible interface conditions. The genetic algorithms are successfully used to solve the match-up problem. Simulated results are found in good agreement with the analytical or FEM solutions.

  17. Documentation for the token ring network simulation system

    NASA Technical Reports Server (NTRS)

    Peden, Jeffery H.; Weaver, Alfred C.

    1990-01-01

    A manual is presented which describes the language features of the Token Ring Network Simulation System. The simulation system is a powerful simulation tool for token ring networks which allows the specification of various Medium Access Control (MAC) layer protocols as well as the specification of various features of upper layer ISO protocols. In addition to these features, it also allows the user to specify message and station classes virtually to any degree of detail desired. The choice of a language instead of an interactive system to specify network parameters was dictated by both flexibility and time considerations. The language was developed specifically for the simulation system, and is very simple. It is also user friendly in that language elements which do not apply to the case at hand are ignored rather than treated as errors.

  18. Urban traffic-network performance: flow theory and simulation experiments

    SciTech Connect

    Williams, J.C.

    1986-01-01

    Performance models for urban street networks were developed to describe the response of a traffic network to given travel-demand levels. The three basic traffic flow variables, speed, flow, and concentration, are defined at the network level, and three model systems are proposed. Each system consists of a series of interrelated, consistent functions between the three basic traffic-flow variables as well as the fraction of stopped vehicles in the network. These models are subsequently compared with the results of microscopic simulation of a small test network. The sensitivity of one of the model systems to a variety of network features was also explored. Three categories of features were considered, with the specific features tested listed in parentheses: network topology (block length and street width), traffic control (traffic signal coordination), and traffic characteristics (level of inter-vehicular interaction). Finally, a fundamental issue concerning the estimation of two network-level parameters (from a nonlinear relation in the two-fluid theory) was examined. The principal concern was that of comparability of these parameters when estimated with information from a single vehicle (or small group of vehicles), as done in conjunction with previous field studies, and when estimated with network-level information (i.e., all the vehicles), as is possible with simulation.

  19. From Spinal Central Pattern Generators to Cortical Network: Integrated BCI for Walking Rehabilitation

    PubMed Central

    Cheron, G.; Duvinage, M.; De Saedeleer, C.; Castermans, T.; Bengoetxea, A.; Petieau, M.; Seetharaman, K.; Hoellinger, T.; Dan, B.; Dutoit, T.; Sylos Labini, F.; Lacquaniti, F.; Ivanenko, Y.

    2012-01-01

    Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy. PMID:22272380

  20. From spinal central pattern generators to cortical network: integrated BCI for walking rehabilitation.

    PubMed

    Cheron, G; Duvinage, M; De Saedeleer, C; Castermans, T; Bengoetxea, A; Petieau, M; Seetharaman, K; Hoellinger, T; Dan, B; Dutoit, T; Sylos Labini, F; Lacquaniti, F; Ivanenko, Y

    2012-01-01

    Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

  1. Cortical Network Modeling for Inverse Kinematic Computation of an Anthropomorphic Finger

    PubMed Central

    Gentili, Rodolphe J.; Oh, Hyuk; Molina, Javier; Contreras-Vidal, José L.

    2014-01-01

    The performance of reaching movements to visual targets requires complex kinematic mechanisms such as redundant, multijointed, anthropomorphic actuators and thus is a difficult problem since the relationship between sensory and motor coordinates is highly nonlinear. In this article, we present a neural model able to learn the inverse kinematics of a simulated anthropomorphic robot finger (ShadowHand™ finger) having four degrees of freedom while performing 3D reaching movements. The results revealed that this neural model was able to control accurately and robustly the finger when performing single 3D reaching movements as well as more complex patterns of motion while generating kinematics comparable to those observed in human. The long term goal of this research is to design a bio-mimetic controller providing adaptive, robust and flexible control of dexterous robotic/prosthetics hands. PMID:22256258

  2. Cortical network modeling for inverse kinematic computation of an anthropomorphic finger.

    PubMed

    Gentili, Rodolphe J; Oh, Hyuk; Molina, Javier; Contreras-Vidal, José L

    2011-01-01

    The performance of reaching movements to visual targets requires complex kinematic mechanisms such as redundant, multijointed, anthropomorphic actuators and thus is a difficult problem since the relationship between sensory and motor coordinates is highly nonlinear. In this article, we present a neural model able to learn the inverse kinematics of a simulated anthropomorphic robot finger (ShadowHand™ finger) having four degrees of freedom while performing 3D reaching movements. The results revealed that this neural model was able to control accurately and robustly the finger when performing single 3D reaching movements as well as more complex patterns of motion while generating kinematics comparable to those observed in human. The long term goal of this research is to design a bio-mimetic controller providing adaptive, robust and flexible control of dexterous robotic/prosthetics hands.

  3. Petri-Net Simulations of Communications Networks.

    DTIC Science & Technology

    1980-03-01

    Experimental Packet Padre Network .......................... 39 3. The Fort Bragg Testbed .................... 41 I. PUTTTR7 IMPLICATIONS... rol .)vcord); 699 z:Cbol-;,mameptr); * 700 if((checkznamnestz~l)1:T 1 (check~nameszil)W:0)4 701 rnqOK3051-y3,2e) 702 703 else I 704 if (cm’ecWnae.s It

  4. Integrated Circuit For Simulation Of Neural Network

    NASA Technical Reports Server (NTRS)

    Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.

    1988-01-01

    Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.

  5. Artificial neural network simulation of battery performance

    SciTech Connect

    O`Gorman, C.C.; Ingersoll, D.; Jungst, R.G.; Paez, T.L.

    1998-12-31

    Although they appear deceptively simple, batteries embody a complex set of interacting physical and chemical processes. While the discrete engineering characteristics of a battery such as the physical dimensions of the individual components, are relatively straightforward to define explicitly, their myriad chemical and physical processes, including interactions, are much more difficult to accurately represent. Within this category are the diffusive and solubility characteristics of individual species, reaction kinetics and mechanisms of primary chemical species as well as intermediates, and growth and morphology characteristics of reaction products as influenced by environmental and operational use profiles. For this reason, development of analytical models that can consistently predict the performance of a battery has only been partially successful, even though significant resources have been applied to this problem. As an alternative approach, the authors have begun development of a non-phenomenological model for battery systems based on artificial neural networks. Both recurrent and non-recurrent forms of these networks have been successfully used to develop accurate representations of battery behavior. The connectionist normalized linear spline (CMLS) network has been implemented with a self-organizing layer to model a battery system with the generalized radial basis function net. Concurrently, efforts are under way to use the feedforward back propagation network to map the {open_quotes}state{close_quotes} of a battery system. Because of the complexity of battery systems, accurate representation of the input and output parameters has proven to be very important. This paper describes these initial feasibility studies as well as the current models and makes comparisons between predicted and actual performance.

  6. Functional brain network organisation of children between 2 and 5 years derived from reconstructed activity of cortical sources of high-density EEG recordings.

    PubMed

    Bathelt, Joe; O'Reilly, Helen; Clayden, Jonathan D; Cross, J Helen; de Haan, Michelle

    2013-11-15

    There is increasing interest in applying connectivity analysis to brain measures (Rubinov and Sporns, 2010), but most studies have relied on fMRI, which substantially limits the participant groups and numbers that can be studied. High-density EEG recordings offer a comparatively inexpensive easy-to-use alternative, but require channel-level connectivity analysis which currently lacks a common analytic framework and is very limited in spatial resolution. To address this problem, we have developed a new technique for studies of network development that overcomes the spatial constraint and obtains functional networks of cortical areas by using EEG source reconstruction with age-matched average MRI templates (He et al., 1999). In contrast to previously reported channel-level analysis, this approach provides information about the cortical areas most likely to be involved in the network as well as their functional relationship (Babiloni et al., 2005; De Vico Fallani et al., 2007). In this study, we applied source reconstruction with age-matched templates to task-free high-density EEG recordings in typically-developing children between 2 and 6 years of age (O'Reilly, 2012). Graph theory was then applied to the association strengths of 68 cortical regions of interest based on the Desikan-Killiany atlas. We found linear increases of mean node degree, mean clustering coefficient and maximum betweenness centrality between 2 years and 6 years of age. Characteristic path length was negatively correlated with age. The correlation of the network measures with age indicates network development towards more closely integrated networks similar to reports from other imaging modalities (Fair et al., 2008; Power et al., 2010). We also applied eigenvalue decomposition to obtain functional modules (Clayden et al., 2013). Connection strength within these modules did not change with age, and the modules resembled hub networks previously described for MRI (Hagmann et al., 2010; Power et al

  7. Constructing circular phylogenetic networks from weighted quartets using simulated annealing.

    PubMed

    Eslahchi, Changiz; Hassanzadeh, Reza; Mottaghi, Ehsan; Habibi, Mahnaz; Pezeshk, Hamid; Sadeghi, Mehdi

    2012-02-01

    In this paper, we present a heuristic algorithm based on the simulated annealing, SAQ-Net, as a method for constructing phylogenetic networks from weighted quartets. Similar to QNet algorithm, SAQ-Net constructs a collection of circular weighted splits of the taxa set. This collection is represented by a split network. In order to show that SAQ-Net performs better than QNet, we apply these algorithm to both the simulated and actual data sets containing salmonella, Bees, Primates and Rubber data sets. Then we draw phylogenetic networks corresponding to outputs of these algorithms using SplitsTree4 and compare the results. We find that SAQ-Net produces a better circular ordering and phylogenetic networks than QNet in most cases. SAQ-Net has been implemented in Matlab and is available for download at http://bioinf.cs.ipm.ac.ir/softwares/saq.net.

  8. SIMULATING FISH ASSEMBLAGE DYNAMICS IN RIVER NETWORKS

    EPA Science Inventory

    My recently retired colleague, Joan Baker, and I have developed a prototype computer simulation model for studying the effects of human and non-human alterations of habitats and species availability on fish assemblage populations. The fish assemblage model, written in R, is a sp...

  9. Network Visualization of Conformational Sampling during Molecular Dynamics Simulation

    PubMed Central

    Ahlstrom, Logan S.; Baker, Joseph Lee; Ehrlich, Kent; Campbell, Zachary T.; Patel, Sunita; Vorontsov, Ivan I.; Tama, Florence; Miyashita, Osamu

    2013-01-01

    Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone. We compare the results of network visualization against 11 clustering algorithms and principal component conformer plots. Several MD simulations of proteins undergoing different conformational changes demonstrate the effectiveness of networks in reaching functional conclusions. PMID:24211466

  10. Neural Network Simulation Package from Ohio State University

    SciTech Connect

    Wickham, K.L.

    1990-08-01

    This report describes the Neural Network Simulation Package acquired from Ohio State University. The package known as Neural Shell V2.1 was evaluated and benchmarked at the INEL Supercomputing Center (ISC). The emphasis was on the Back Propagation Net which is currently considered one of the more promising types of neural networks. This report also provides additional documentation that may be helpful to anyone using the package.

  11. Enhancing the NS-2 Network Simulator for Near Real-Time Control Feedback and Distributed Simulation

    DTIC Science & Technology

    2009-03-21

    introduction of a mediator to synchronize events is often used. Branicky et al [5] outlines a framework for co-simulation with a networked control system providing...accessed on Nov 4, 2008. Http://www.boost.org/. 5. Branicky, Michael, Vincenzo Liberatore, and Stephen M. Phillips. “ Networked Control System Co

  12. F77NNS - A FORTRAN-77 NEURAL NETWORK SIMULATOR

    NASA Technical Reports Server (NTRS)

    Mitchell, P. H.

    1994-01-01

    F77NNS (A FORTRAN-77 Neural Network Simulator) simulates the popular back error propagation neural network. F77NNS is an ANSI-77 FORTRAN program designed to take advantage of vectorization when run on machines having this capability, but it will run on any computer with an ANSI-77 FORTRAN Compiler. Artificial neural networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to biological nerve cells. Problems which involve pattern matching or system modeling readily fit the class of problems which F77NNS is designed to solve. The program's formulation trains a neural network using Rumelhart's back-propagation algorithm. Typically the nodes of a network are grouped together into clumps called layers. A network will generally have an input layer through which the various environmental stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. The back-propagation training algorithm can require massive computational resources to implement a large network such as a network capable of learning text-to-phoneme pronunciation rules as in the famous Sehnowski experiment. The Sehnowski neural network learns to pronounce 1000 common English words. The standard input data defines the specific inputs that control the type of run to be made, and input files define the NN in terms of the layers and nodes, as well as the input/output (I/O) pairs. The program has a restart capability so that a neural network can be solved in stages suitable to the user's resources and desires. F77NNS allows the user to customize the patterns of connections between layers of a network. The size of the neural network to be solved is limited only by the amount of random access memory (RAM) available to the

  13. High Fidelity Simulations of Large-Scale Wireless Networks

    SciTech Connect

    Onunkwo, Uzoma; Benz, Zachary

    2015-11-01

    The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.

  14. The Development of Neural Synchrony and Large-Scale Cortical Networks During Adolescence: Relevance for the Pathophysiology of Schizophrenia and Neurodevelopmental Hypothesis

    PubMed Central

    Uhlhaas, Peter J.; Singer, Wolf

    2011-01-01

    Recent data from developmental cognitive neuroscience highlight the profound changes in the organization and function of cortical networks during the transition from adolescence to adulthood. While previous studies have focused on the development of gray and white matter, recent evidence suggests that brain maturation during adolescence extends to fundamental changes in the properties of cortical circuits that in turn promote the precise temporal coding of neural activity. In the current article, we will highlight modifications in the amplitude and synchrony of neural oscillations during adolescence that may be crucial for the emergence of cognitive deficits and psychotic symptoms in schizophrenia. Specifically, we will suggest that schizophrenia is associated with impaired parameters of synchronous oscillations that undergo changes during late brain maturation, suggesting an important role of adolescent brain development for the understanding, treatment, and prevention of the disorder. PMID:21505118

  15. The development of neural synchrony and large-scale cortical networks during adolescence: relevance for the pathophysiology of schizophrenia and neurodevelopmental hypothesis.

    PubMed

    Uhlhaas, Peter J; Singer, Wolf

    2011-05-01

    Recent data from developmental cognitive neuroscience highlight the profound changes in the organization and function of cortical networks during the transition from adolescence to adulthood. While previous studies have focused on the development of gray and white matter, recent evidence suggests that brain maturation during adolescence extends to fundamental changes in the properties of cortical circuits that in turn promote the precise temporal coding of neural activity. In the current article, we will highlight modifications in the amplitude and synchrony of neural oscillations during adolescence that may be crucial for the emergence of cognitive deficits and psychotic symptoms in schizophrenia. Specifically, we will suggest that schizophrenia is associated with impaired parameters of synchronous oscillations that undergo changes during late brain maturation, suggesting an important role of adolescent brain development for the understanding, treatment, and prevention of the disorder.

  16. Simulation of nonlinear random vibrations using artificial neural networks

    SciTech Connect

    Paez, T.L.; Tucker, S.; O`Gorman, C.

    1997-02-01

    The simulation of mechanical system random vibrations is important in structural dynamics, but it is particularly difficult when the system under consideration is nonlinear. Artificial neural networks provide a useful tool for the modeling of nonlinear systems, however, such modeling may be inefficient or insufficiently accurate when the system under consideration is complex. This paper shows that there are several transformations that can be used to uncouple and simplify the components of motion of a complex nonlinear system, thereby making its modeling and random vibration simulation, via component modeling with artificial neural networks, a much simpler problem. A numerical example is presented.

  17. A Discussion of Metrics for Parallelized Army Mobile ad hoc Network Simulations

    DTIC Science & Technology

    2011-09-01

    years including Yet Another Network Simulator (YANS), ns-2 and ns-3, OPNET , and ROSS (4–8). All of these approaches employ a discrete event simulator (DES...adding NetDMF awareness to the COMPOSER toolkit. Commercial tools, such as OPNET , also maintain a suite of tools for analysis of network simulation...Network Simulator-3 (ns-3). [6] Chang, X. Network Simulations with OPNET . In Winter Simulation Conference, 1999. [7] Khosa, I.; Haider, U.; Mosood, H

  18. [Cortical blindness].

    PubMed

    Chokron, S

    2014-02-01

    Cortical blindness refers to a visual loss induced by a bilateral occipital lesion. The very strong cooperation between psychophysics, cognitive psychology, neurophysiology and neuropsychology these latter twenty years as well as recent progress in cerebral imagery have led to a better understanding of neurovisual deficits, such as cortical blindness. It thus becomes possible now to propose an earlier diagnosis of cortical blindness as well as new perspectives for rehabilitation in children as well as in adults. On the other hand, studying complex neurovisual deficits, such as cortical blindness is a way to infer normal functioning of the visual system.

  19. Introducing FNCS: Framework for Network Co-Simulation

    ScienceCinema

    None

    2016-07-12

    This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

  20. Introducing FNCS: Framework for Network Co-Simulation

    SciTech Connect

    2014-10-23

    This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

  1. Panel Review of Long-Haul Networking in Distributed Simulation

    DTIC Science & Technology

    1990-06-01

    Second R&D Research and Development RISC Reduced Instruction Set Computer SAF Semi -Automated Forces SDI Strategic Defense Initiative SIMNET Simulator...Suggestions for meeting the needs of long-haul networking in ADST included the following: • Generate objects simulated for semi -automated and fully-automated...grows less than linearly with the number of objects; (c) The percentage of fully-automated forces (FAFs) 0 and semi -automated forces (SAFs) will grow as

  2. Representing Dynamic Social Networks in Discrete Event Social Simulation

    DTIC Science & Technology

    2010-12-01

    applied settings in the areas of marketing and behavior modification programs (exercise adoption, smoking cessation) ( Icek Ajzen 2006). The model has an...society. The action choice component of the conceptual model is based on the theory of planned behavior (TPB) (I. Ajzen 1991). The TPB states that an...information networks into military simulations. In Pro- ceedings of the 40th Conference on Winter Simulation. pp. 133–144. Ajzen , I. 1991. The theory of

  3. An artificial neural network based groundwater flow and transport simulator

    SciTech Connect

    Krom, T.D.; Rosbjerg, D.

    1998-07-01

    Artificial neural networks are investigated as a tool for the simulation of contaminant loss and recovery in three-dimensional heterogeneous groundwater flow and contaminant transport modeling. These methods have useful applications in expert system development, knowledge base development and optimization of groundwater pollution remediation. The numerical model runs used to develop the artificial neural networks can be re-used to develop artificial neural networks to address alternative optimization problems or changed formulations of the constraints and or objective function under optimization. Artificial neural networks have been analyzed with the goal of estimating objectives which normally require the use of traditional flow and transport codes: such as contaminant recovery, contaminant loss (unrecovered) and remediation failure. The inputs to the artificial neutral networks are variable pumping withdrawal rates at fairly unconstrained 3-D locations. A forward-feed backwards error propagation artificial neural network architecture is used. The significance of the size of the training set, network architecture, and network weight optimization algorithm with respect to the estimation accuracy and objective are shown to be important. Finally, the quality of the weight optimization is studied via cross-validation techniques. This is demonstrated to be a useful method for judging training performance for strongly under-described systems.

  4. Transmission network expansion planning with simulation optimization

    SciTech Connect

    Bent, Russell W; Berscheid, Alan; Toole, G. Loren

    2010-01-01

    Within the electric power literatW''e the transmi ssion expansion planning problem (TNEP) refers to the problem of how to upgrade an electric power network to meet future demands. As this problem is a complex, non-linear, and non-convex optimization problem, researchers have traditionally focused on approximate models. Often, their approaches are tightly coupled to the approximation choice. Until recently, these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (i.e. large amounts of limited control, renewable generation) that necessitates new optimization techniques. In this paper, we propose a generalization of the powerful Limited Discrepancy Search (LDS) that encapsulates the complexity in a black box that may be queJied for information about the quality of a proposed expansion. This allows the development of a new optimization algOlitlun that is independent of the underlying power model.

  5. Simulating fish assemblages in riverine networks - September 2013

    EPA Science Inventory

    We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

  6. Improving a Computer Networks Course Using the Partov Simulation Engine

    ERIC Educational Resources Information Center

    Momeni, B.; Kharrazi, M.

    2012-01-01

    Computer networks courses are hard to teach as there are many details in the protocols and techniques involved that are difficult to grasp. Employing programming assignments as part of the course helps students to obtain a better understanding and gain further insight into the theoretical lectures. In this paper, the Partov simulation engine and…

  7. Using SPEEDES to simulate the blue gene interconnect network

    NASA Technical Reports Server (NTRS)

    Springer, P.; Upchurch, E.

    2003-01-01

    JPL and the Center for Advanced Computer Architecture (CACR) is conducting application and simulation analyses of BG/L in order to establish a range of effectiveness for the Blue Gene/L MPP architecture in performing important classes of computations and to determine the design sensitivity of the global interconnect network in support of real world ASCI application execution.

  8. Artificial Neural Network Metamodels of Stochastic Computer Simulations

    DTIC Science & Technology

    1994-08-10

    Networks, Vol. 5 (1992), pp. 207-220. 55 Haykin, Op. Cit., pp. 190-191. 56 Gon, M. and Tesi , A., "On the Problem of Local Minima in Backpropagation," IEEE...Simulation Experiments: Taguchi Methods and Response Surface Metamodels, by J. Ramberg, S. Sanchez , P. Sanchez , and L. Hollick" (Piscataway, New Jersey

  9. Distributed simulation using a real-time shared memory network

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.

    1993-01-01

    The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

  10. Towards effective flow simulations in realistic discrete fracture networks

    NASA Astrophysics Data System (ADS)

    Berrone, Stefano; Pieraccini, Sandra; Scialò, Stefano

    2016-04-01

    We focus on the simulation of underground flow in fractured media, modeled by means of Discrete Fracture Networks. Focusing on a new recent numerical approach proposed by the authors for tackling the problem avoiding mesh generation problems, we further improve the new family of methods making a step further towards effective simulations of large, multi-scale, heterogeneous networks. Namely, we tackle the imposition of Dirichlet boundary conditions in weak form, in such a way that geometrical complexity of the DFN is not an issue; we effectively solve DFN problems with fracture transmissivities spanning many orders of magnitude and approaching zero; furthermore, we address several numerical issues for improving the numerical solution also in quite challenging networks.

  11. Persistent patterns of interconnection in time-varying cortical networks estimated from high-resolution EEG recordings in humans during a simple motor act

    NASA Astrophysics Data System (ADS)

    DeVico Fallani, F.; Latora, V.; Astolfi, L.; Cincotti, F.; Mattia, D.; Marciani, M. G.; Salinari, S.; Colosimo, A.; Babiloni, F.

    2008-06-01

    In this work, a novel approach based on the estimate of time-varying graph indices is proposed in order to capture the basic schemes of communication within the functional brain networks during a simple motor act. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high-resolution EEG techniques. From the cortical signals of different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive partial directed coherence. The time-varying connectivity estimation returns a series of networks evolving during the examined task which can be summarized and interpreted with the aid of mathematical indices based on graph theory. The combination of all these methods is demonstrated on a set of high-resolution EEG data recorded from a group of healthy subjects performing a simple foot movement. It can be anticipated that the combination of the time-varying connectivity with the theoretical graph analysis is able to reveal precious information about the interconnections of the cerebral network as the significant persistence of mutual links and three-node motifs.

  12. Unaltered Network Activity and Interneuronal Firing During Spontaneous Cortical Dynamics In Vivo in a Mouse Model of Severe Myoclonic Epilepsy of Infancy

    PubMed Central

    De Stasi, Angela Michela; Farisello, Pasqualina; Marcon, Iacopo; Cavallari, Stefano; Forli, Angelo; Vecchia, Dania; Losi, Gabriele; Mantegazza, Massimo; Panzeri, Stefano; Carmignoto, Giorgio; Bacci, Alberto; Fellin, Tommaso

    2016-01-01

    Severe myoclonic epilepsy of infancy (SMEI) is associated with loss of function of the SCN1A gene encoding the NaV1.1 sodium channel isoform. Previous studies in Scn1a−/+ mice during the pre-epileptic period reported selective reduction in interneuron excitability and proposed this as the main pathological mechanism underlying SMEI. Yet, the functional consequences of this interneuronal dysfunction at the circuit level in vivo are unknown. Here, we investigated whether Scn1a−/+ mice showed alterations in cortical network function. We found that various forms of spontaneous network activity were similar in Scn1a−/+ during the pre-epileptic period compared with wild-type (WT) in vivo. Importantly, in brain slices from Scn1a−/+ mice, the excitability of parvalbumin (PV) and somatostatin (SST) interneurons was reduced, epileptiform activity propagated more rapidly, and complex synaptic changes were observed. However, in vivo, optogenetic reduction of firing in PV or SST cells in WT mice modified ongoing network activities, and juxtasomal recordings from identified PV and SST interneurons showed unaffected interneuronal firing during spontaneous cortical dynamics in Scn1a−/+ compared with WT. These results demonstrate that interneuronal hypoexcitability is not observed in Scn1a−/+ mice during spontaneous activities in vivo and suggest that additional mechanisms may contribute to homeostatic rearrangements and the pathogenesis of SMEI. PMID:26819275

  13. A dynamic network involving M1-S1, SII-insular, medial insular, and cingulate cortices controls muscular activity during an isometric contraction reaction time task.

    PubMed

    Jouanin, Jean-Claude; Pérès, Michel; Ducorps, Antoine; Renault, Bernard

    2009-02-01

    Magnetoencephalographic, electromyographic (EMG), work, and reaction time (RT) were recorded from nine subjects during visually triggered intermittent isometric contractions of the middle finger under two conditions: unloaded and loaded (30% of maximal voluntary contraction). The effect of muscle fatigue was studied over three consecutive periods under both conditions. In the loaded condition, the motor evoked field triggered by the EMG onset decreased with fatigue, whereas movement-evoked fields (MEFs) increased (P < 0.01). Fatigue was demonstrated in the loaded condition, since (i) RT increased due to an increase in the electromechanical delay (P < 0.002); (ii) work decreased from Periods 1 to 3 (P < 0.005), while (iii) the myoelectric RMS amplitude of both flexor digitorum superficialis and extensor muscles increased (P < 0.003) and (iv) during Period 3, the spectral deflection of the EMG median frequency of the FDS muscle decreased (P < 0.001). In the unloaded condition and at the beginning of the loaded condition, a parallel network including M1-S1, posterior SII-insular, and posterior cingulate cortices accounted for the MEF activities. However, under the effect of fatigue, medial insular and posterior cingulate cortices drove this network. Moreover, changes in the location of insular and M1-S1 activations were significantly correlated with muscle fatigue (increase of RMS-EMG; P < 0.03 and P < 0.01, respectively). These results demonstrate that a plastic network controls the strength of the motor command as fatigue occurs: sensory information, pain, and exhaustion act through activation of the medial insular and posterior cingulate cortices to decrease the motor command in order to preserve muscle efficiency and integrity.

  14. Spontaneous EEG alpha oscillation interacts with positive and negative BOLD responses in the visual-auditory cortices and default-mode network.

    PubMed

    Mayhew, Stephen D; Ostwald, Dirk; Porcaro, Camillo; Bagshaw, Andrew P

    2013-08-01

    The human brain is continually, dynamically active and spontaneous fluctuations in this activity play a functional role in affecting both behavioural and neuronal responses. However, the mechanisms through which this occurs remain poorly understood. Simultaneous EEG-fMRI is a promising technique to study how spontaneous activity modulates the brain's response to stimulation, as temporal indices of ongoing cortical excitability can be integrated with spatially localised evoked responses. Here we demonstrate an interaction between the ongoing power of the electrophysiological alpha oscillation and the magnitude of both positive (PBR) and negative (NBR) fMRI responses to two contrasts of visual checkerboard reversal. Furthermore, the amplitude of pre-stimulus EEG alpha-power significantly modulated the amplitude and shape of subsequent PBR and NBR to the visual stimulus. A nonlinear reduction of visual PBR and an enhancement of auditory NBR and default-mode network NBR were observed in trials preceded by high alpha-power. These modulated areas formed a functionally connected network during a separate resting-state recording. Our findings suggest that the "baseline" state of the brain exhibits considerable trial-to-trial variability which arises from fluctuations in the balance of cortical inhibition/excitation that are represented by respective increases/decreases in the power of the EEG alpha oscillation. The consequence of this spontaneous electrophysiological variability is modulated amplitudes of both PBR and NBR to stimulation. Fluctuations in alpha-power may subserve a functional relationship in the visual-auditory network, acting as mediator for both short and long-range cortical inhibition, the strength of which is represented in part by NBR.

  15. Simulation of Attacks for Security in Wireless Sensor Network

    PubMed Central

    Diaz, Alvaro; Sanchez, Pablo

    2016-01-01

    The increasing complexity and low-power constraints of current Wireless Sensor Networks (WSN) require efficient methodologies for network simulation and embedded software performance analysis of nodes. In addition, security is also a very important feature that has to be addressed in most WSNs, since they may work with sensitive data and operate in hostile unattended environments. In this paper, a methodology for security analysis of Wireless Sensor Networks is presented. The methodology allows designing attack-aware embedded software/firmware or attack countermeasures to provide security in WSNs. The proposed methodology includes attacker modeling and attack simulation with performance analysis (node’s software execution time and power consumption estimation). After an analysis of different WSN attack types, an attacker model is proposed. This model defines three different types of attackers that can emulate most WSN attacks. In addition, this paper presents a virtual platform that is able to model the node hardware, embedded software and basic wireless channel features. This virtual simulation analyzes the embedded software behavior and node power consumption while it takes into account the network deployment and topology. Additionally, this simulator integrates the previously mentioned attacker model. Thus, the impact of attacks on power consumption and software behavior/execution-time can be analyzed. This provides developers with essential information about the effects that one or multiple attacks could have on the network, helping them to develop more secure WSN systems. This WSN attack simulator is an essential element of the attack-aware embedded software development methodology that is also introduced in this work. PMID:27869710

  16. Simulation of Attacks for Security in Wireless Sensor Network.

    PubMed

    Diaz, Alvaro; Sanchez, Pablo

    2016-11-18

    The increasing complexity and low-power constraints of current Wireless Sensor Networks (WSN) require efficient methodologies for network simulation and embedded software performance analysis of nodes. In addition, security is also a very important feature that has to be addressed in most WSNs, since they may work with sensitive data and operate in hostile unattended environments. In this paper, a methodology for security analysis of Wireless Sensor Networks is presented. The methodology allows designing attack-aware embedded software/firmware or attack countermeasures to provide security in WSNs. The proposed methodology includes attacker modeling and attack simulation with performance analysis (node's software execution time and power consumption estimation). After an analysis of different WSN attack types, an attacker model is proposed. This model defines three different types of attackers that can emulate most WSN attacks. In addition, this paper presents a virtual platform that is able to model the node hardware, embedded software and basic wireless channel features. This virtual simulation analyzes the embedded software behavior and node power consumption while it takes into account the network deployment and topology. Additionally, this simulator integrates the previously mentioned attacker model. Thus, the impact of attacks on power consumption and software behavior/execution-time can be analyzed. This provides developers with essential information about the effects that one or multiple attacks could have on the network, helping them to develop more secure WSN systems. This WSN attack simulator is an essential element of the attack-aware embedded software development methodology that is also introduced in this work.

  17. Conservative parallel simulation of priority class queueing networks

    NASA Technical Reports Server (NTRS)

    Nicol, David M.

    1990-01-01

    A conservative synchronization protocol is described for the parallel simulation of queueing networks having C job priority classes, where a job's class is fixed. This problem has long vexed designers of conservative synchronization protocols because of its seemingly poor ability to compute lookahead: the time of the next departure. For, a job in service having low priority can be preempted at any time by an arrival having higher priority and an arbitrarily small service time. The solution is to skew the event generation activity so that the events for higher priority jobs are generated farther ahead in simulated time than lower priority jobs. Thus, when a lower priority job enters service for the first time, all the higher priority jobs that may preempt it are already known and the job's departure time can be exactly predicted. Finally, the protocol was analyzed and it was demonstrated that good performance can be expected on the simulation of large queueing networks.

  18. Analysis of Cortical Flow Models In Vivo

    PubMed Central

    Benink, Hélène A.; Mandato, Craig A.; Bement, William M.

    2000-01-01

    Cortical flow, the directed movement of cortical F-actin and cortical organelles, is a basic cellular motility process. Microtubules are thought to somehow direct cortical flow, but whether they do so by stimulating or inhibiting contraction of the cortical actin cytoskeleton is the subject of debate. Treatment of Xenopus oocytes with phorbol 12-myristate 13-acetate (PMA) triggers cortical flow toward the animal pole of the oocyte; this flow is suppressed by microtubules. To determine how this suppression occurs and whether it can control the direction of cortical flow, oocytes were subjected to localized manipulation of either the contractile stimulus (PMA) or microtubules. Localized PMA application resulted in redirection of cortical flow toward the site of application, as judged by movement of cortical pigment granules, cortical F-actin, and cortical myosin-2A. Such redirected flow was accelerated by microtubule depolymerization, showing that the suppression of cortical flow by microtubules is independent of the direction of flow. Direct observation of cortical F-actin by time-lapse confocal analysis in combination with photobleaching showed that cortical flow is driven by contraction of the cortical F-actin network and that microtubules suppress this contraction. The oocyte germinal vesicle serves as a microtubule organizing center in Xenopus oocytes; experimental displacement of the germinal vesicle toward the animal pole resulted in localized flow away from the animal pole. The results show that 1) cortical flow is directed toward areas of localized contraction of the cortical F-actin cytoskeleton; 2) microtubules suppress cortical flow by inhibiting contraction of the cortical F-actin cytoskeleton; and 3) localized, microtubule-dependent suppression of actomyosin-based contraction can control the direction of cortical flow. We discuss these findings in light of current models of cortical flow. PMID:10930453

  19. Development of a heterogeneous microwave network fade simulation tool applicable to networks that span Europe

    NASA Astrophysics Data System (ADS)

    Paulson, Kevin S.; Basarudin, Hafiz

    2011-08-01

    Several research groups in Europe are developing joint channel simulators for arbitrarily complex networks of terrestrial and slant path, microwave telecommunications links. Currently, the Hull Rain Fade Network Simulator (HRFNS) developed at University of Hull can simulate rain fade on arbitrary terrestrial networks in the southern United Kingdom, producing joint rain fade time series with a 10 s integration time. This paper reports on work to broaden the function of the existing HRFNS to include slant paths such as Earth-space links and communications to high altitude platforms and unmanned airborne systems. The area of application of the new simulation tool is being extended to the whole of Europe, and other fade mechanisms are being included. Nimrod/OPERA has been chosen as the input meteorological data sets for the new system to simulate rain fade. Zero-degree isotherm heights taken from NCEP/NCAR Reanalysis Data are used in conjunction with the Eden-Bacon sleet (wet snow) model to introduce melting layer effects. Other fading mechanisms, including cloud fade, scintillation and absorption losses by atmospheric gasses, can be added to the simulator. The simulator is tested against ITU-R models for rain fade distribution experienced by terrestrial and Earth-space links in the southern United Kingdom. Statistics of fade dynamics, i.e., fade slope and fade duration, for a simulated Earth-space link are compared to International Telecommunication Union models.

  20. ESIM_DSN Web-Enabled Distributed Simulation Network

    NASA Technical Reports Server (NTRS)

    Bedrossian, Nazareth; Novotny, John

    2002-01-01

    In this paper, the eSim(sup DSN) approach to achieve distributed simulation capability using the Internet is presented. With this approach a complete simulation can be assembled from component subsystems that run on different computers. The subsystems interact with each other via the Internet The distributed simulation uses a hub-and-spoke type network topology. It provides the ability to dynamically link simulation subsystem models to different computers as well as the ability to assign a particular model to each computer. A proof-of-concept demonstrator is also presented. The eSim(sup DSN) demonstrator can be accessed at http://www.jsc.draper.com/esim which hosts various examples of Web enabled simulations.

  1. Multiscale Quantum Mechanics/Molecular Mechanics Simulations with Neural Networks.

    PubMed

    Shen, Lin; Wu, Jingheng; Yang, Weitao

    2016-10-11

    Molecular dynamics simulation with multiscale quantum mechanics/molecular mechanics (QM/MM) methods is a very powerful tool for understanding the mechanism of chemical and biological processes in solution or enzymes. However, its computational cost can be too high for many biochemical systems because of the large number of ab initio QM calculations. Semiempirical QM/MM simulations have much higher efficiency. Its accuracy can be improved with a correction to reach the ab initio QM/MM level. The computational cost on the ab initio calculation for the correction determines the efficiency. In this paper we developed a neural network method for QM/MM calculation as an extension of the neural-network representation reported by Behler and Parrinello. With this approach, the potential energy of any configuration along the reaction path for a given QM/MM system can be predicted at the ab initio QM/MM level based on the semiempirical QM/MM simulations. We further applied this method to three reactions in water to calculate the free energy changes. The free-energy profile obtained from the semiempirical QM/MM simulation is corrected to the ab initio QM/MM level with the potential energies predicted with the constructed neural network. The results are in excellent accordance with the reference data that are obtained from the ab initio QM/MM molecular dynamics simulation or corrected with direct ab initio QM/MM potential energies. Compared with the correction using direct ab initio QM/MM potential energies, our method shows a speed-up of 1 or 2 orders of magnitude. It demonstrates that the neural network method combined with the semiempirical QM/MM calculation can be an efficient and reliable strategy for chemical reaction simulations.

  2. Modeling and simulation of the USAVRE network and radiology operations

    NASA Astrophysics Data System (ADS)

    Martinez, Ralph; Bradford, Daniel Q.; Hatch, Jay; Sochan, John; Chimiak, William J.

    1998-07-01

    The U.S. Army Medical Command, lead by the Brooke Army Medical Center, has embarked on a visionary project. The U.S. Army Virtual Radiology Environment (USAVRE) is a CONUS-based network that connects all the Army's major medical centers and Regional Medical Commands (RMC). The purpose of the USAVRE is to improve the quality, access, and cost of radiology services in the Army via the use of state-of-the-art medical imaging, computer, and networking technologies. The USAVRE contains multimedia viewing workstations; database archive systems are based on a distributed computing environment using Common Object Request Broker Architecture (CORBA) middleware protocols. The underlying telecommunications network is an ATM-based backbone network that connects the RMC regional networks and PACS networks at medical centers and RMC clinics. This project is a collaborative effort between Army, university, and industry centers with expertise in teleradiology and Global PACS applications. This paper describes a model and simulation of the USAVRE for performance evaluation purposes. As a first step the results of a Technology Assessment and Requirements Analysis (TARA) -- an analysis of the workload in Army radiology departments, their equipment and their staffing. Using the TARA data and other workload information, we have developed a very detailed analysis of the workload and workflow patterns of our Medical Treatment Facilities. We are embarking on modeling and simulation strategies, which will form the foundation for the VRE network. The workload analysis is performed for each radiology modality in a RMC site. The workload consists of the number of examinations per modality, type of images per exam, number of images per exam, and size of images. The frequency for store and forward cases, second readings, and interactive consultation cases are also determined. These parameters are translated into the model described below. The model for the USAVRE is hierarchical in nature

  3. Simulation model for flow of neutrophils in pulmonary capillary network.

    PubMed

    Shirai, Atsushi; Fujita, Ryo; Hayase, Toshiyuki

    2005-01-01

    The concentration of neutrophils in the pulmonary microvasculature is higher than in systemic large vessels. It is thought that the high concentration of neutrophils facilitates their effective recruitment to sites of inflammation. Thus, in order to understand the role of neutrophils in the immune system, it is important to clarify their flow characteristics in the pulmonary microvasculature. In previous studies, we numerically investigated the motion of a neutrophil through a single capillary segment modeled by a moderate axisymmetric constriction in a straight pipe, developing a mathematical model for the prediction of the transit time of the cell through the segment. In the present study, this model was extended for application to network simulation of the motion of neutrophils. First, we numerically investigated shape recovery of a neutrophil after expulsion from a narrow capillary segment. This process was modeled in two different phases: elastic recovery and viscous recovery. The resulting model was combined with the previously developed models to simulate motion of the cells and plasma flow in a capillary network. A numerical simulation of the motion of neutrophils and plasma flow in a simple lattice capillary network showed that neutrophils were widely dispersed in the network with an increased concentration.

  4. Computer Simulations of Bottlebrush Melts and Soft Networks

    NASA Astrophysics Data System (ADS)

    Cao, Zhen; Carrillo, Jan-Michael; Sheiko, Sergei; Dobrynin, Andrey

    We have studied dense bottlebrush systems in a melt and network state using a combination of the molecular dynamics simulations and analytical calculations. Our simulations show that the bottlebrush macromolecules in a melt behave as ideal chains with the effective Kuhn length bK. The bottlebrush induced bending rigidity is due to redistribution of the side chains upon backbone bending. Kuhn length of the bottlebrushes increases with increasing the side-chain degree of polymerization nsc as bK ~nsc0 . 46 . This model of bottlebrush macromolecules is extended to describe mechanical properties of bottlebrush networks in linear and nonlinear deformation regimes. In the linear deformation regime, the network shear modulus scales with the degree of polymerization of the side chains as G0 ~nsc + 1 - 1 as long as the ratio of the Kuhn length to the size of the fully extended bottlebrush backbone between crosslinks, Rmax, is smaller than unity, bK /Rmax < < 1 . Bottlebrush networks with bK /Rmax ~ 1 demonstrate behavior similar to that of networks of semiflexible chains with G0 ~nsc- 0 . 5 . In the nonlinear deformation regime, the deformation dependent shear modulus is a universal function of the first strain invariant I1 and bottlebrush backbone deformation ratio β describing stretching ability of the bottlebrush backbone between crosslinks. Nsf DMR-1409710 DMR-1436201.

  5. Computer Simulations of Bottle Brushes: From Melts to Soft Networks

    DOE PAGES

    Cao, Zhen; Carrillo, Jan-Michael Y.; Sheiko, Sergei S.; ...

    2015-07-13

    We use a combination of Molecular dynamics simulations and analytical calculations, and study dens bottle-brush systems in a melt and network State. Analysis of our simulation results shows that bottle-brush macromolecules in melt behave as ideal chains with effective Kuhn length bK. Simulations show that the bottle-brush-induced bending rigidity is due to an entropy decrease caused by redistribution of the side chains upon backbone bending. The Kuhn length of the bottle:brushes increases with increasing the side-chain degree of polymerization nsc as bK proportional to nsc0.46. Moreover, this model of bottle brush macromolecules is extended to describe mechanical properties of bottlemore » brush networks in linear and nonlinear deformation regimes. In the linear deformation regime, the network shear modulus scales with the degree of polymerization of the side chains as G0 proportional to (nsc + 1)-1 as long as the ratio of the Kuhn length, bK, to the size of the fully extended bottle-brush backbone between cross-links, R-max, is smaller than unity, bK/Rmax << 1. Bottle-brush networks With bK/Rmax proportional to 1 demonstrate behavior similar to that of networks Of semiflexible chains with G0 proportional to nsc-0.5. Finally, in the nonlinear network deformation regime, the deformation-dependent shear modulus is a universal function of the first strain invariant I1 and bottle-brush backbone deformation ratio beta describing stretching ability of the bottle-brush backbone between cross-links.« less

  6. Computer Simulations of Bottle Brushes: From Melts to Soft Networks

    SciTech Connect

    Cao, Zhen; Carrillo, Jan-Michael Y.; Sheiko, Sergei S.; Dobrynin, Andrey V.

    2015-07-13

    We use a combination of Molecular dynamics simulations and analytical calculations, and study dens bottle-brush systems in a melt and network State. Analysis of our simulation results shows that bottle-brush macromolecules in melt behave as ideal chains with effective Kuhn length bK. Simulations show that the bottle-brush-induced bending rigidity is due to an entropy decrease caused by redistribution of the side chains upon backbone bending. The Kuhn length of the bottle:brushes increases with increasing the side-chain degree of polymerization nsc as bK proportional to nsc0.46. Moreover, this model of bottle brush macromolecules is extended to describe mechanical properties of bottle brush networks in linear and nonlinear deformation regimes. In the linear deformation regime, the network shear modulus scales with the degree of polymerization of the side chains as G0 proportional to (nsc + 1)-1 as long as the ratio of the Kuhn length, bK, to the size of the fully extended bottle-brush backbone between cross-links, R-max, is smaller than unity, bK/Rmax << 1. Bottle-brush networks With bK/Rmax proportional to 1 demonstrate behavior similar to that of networks Of semiflexible chains with G0 proportional to nsc-0.5. Finally, in the nonlinear network deformation regime, the deformation-dependent shear modulus is a universal function of the first strain invariant I1 and bottle-brush backbone deformation ratio beta describing stretching ability of the bottle-brush backbone between cross-links.

  7. High Speed Networking and Large-scale Simulation in Geodynamics

    NASA Technical Reports Server (NTRS)

    Kuang, Weijia; Gary, Patrick; Seablom, Michael; Truszkowski, Walt; Odubiyi, Jide; Jiang, Weiyuan; Liu, Dong

    2004-01-01

    Large-scale numerical simulation has been one of the most important approaches for understanding global geodynamical processes. In this approach, peta-scale floating point operations (pflops) are often required to carry out a single physically-meaningful numerical experiment. For example, to model convective flow in the Earth's core and generation of the geomagnetic field (geodynamo), simulation for one magnetic free-decay time (approximately 15000 years) with a modest resolution of 150 in three spatial dimensions would require approximately 0.2 pflops. If such a numerical model is used to predict geomagnetic secular variation over decades and longer, with e.g. an ensemble Kalman filter assimilation approach, approximately 30 (and perhaps more) independent simulations of similar scales would be needed for one data assimilation analysis. Obviously, such a simulation would require an enormous computing resource that exceeds the capacity of a single facility currently available at our disposal. One solution is to utilize a very fast network (e.g. 10Gb optical networks) and available middleware (e.g. Globus Toolkit) to allocate available but often heterogeneous resources for such large-scale computing efforts. At NASA GSFC, we are experimenting with such an approach by networking several clusters for geomagnetic data assimilation research. We shall present our initial testing results in the meeting.

  8. On the Strategy of Simulating a GGOS Network

    NASA Astrophysics Data System (ADS)

    Schuh, Harald; Koenig, Rolf; Ampatzidis, Dimitrios; Glaser, Susanne; Flechtner, Frank; Nilsson, Tobias; Heinkelmann, Robert

    2015-04-01

    GGOS-SIM ("Simulation of the Global Geodetic Observing System") is a joint project of the TU Berlin (TUB) and the GFZ German Research Centre for Geosciences. GGOS-SIM aims at creating a tool to simulate the realization of the Terrestrial Reference System from the space-geodetic observations space geodetic techniques: Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS), Global Navigation Satellite System (GNSS), Satellite Laser Ranging (SLR), and Very Long Baseline Interferometry (VLBI). In particular the effects of the space segment, the ground network, the local ties on ground and in space, and technical developments shall be assessed with respect to the goals of GGOS, i.e. point positions with 1 mm and velocities with 1 mm/a accuracy globally. For this we set up the observation scenario which consists of the ground networks, the space segments, and the observation types. We discuss our set-up of the standard networks of each space-geodetic technique and their space segments, and we infer accuracy and availability of the observations from real world data. Then we describe the strategy on how the simulations can be conducted so that the results become realistic. This also concerns the trade-off in choosing the dynamic, geometric, and correction models for simulation and recovery

  9. Simulating market dynamics: interactions between consumer psychology and social networks.

    PubMed

    Janssen, Marco A; Jager, Wander

    2003-01-01

    Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

  10. On-off intermittency of thalamo-cortical neuronal network oscillations in the electroencephalogram of rodents with genetic predisposition to absence epilepsy

    NASA Astrophysics Data System (ADS)

    Hramov, Alexander E.; Grubov, Vadim V.; Pavlov, Alexey N.; Sitnikova, Evgenija Yu.; Koronovskii, Alexey A.; Runnova, Anastasija E.; Shurugina, Sveltlana A.; Ivanov, Alexey V.

    2013-02-01

    Spike-wave discharges are electroencephalographic hallmarks of absence epilepsy. Spike-wave discharges are known to originate from thalamo-cortical neuronal network that normally produces sleep spindle oscillations. Although both sleep spindles and spike-wave discharges are considered as thalamo-cortical oscillations, functional relationship between them is still uncertain. The present study describes temporal dynamics of spike-wave discharges and sleep spindles as determined in long-time electroencephalograms (EEG) recorded in WAG/Rij rat model of absence epilepsy. We have proposed the wavelet-based method for the automatic detection of spike-wave discharges, sleep spindles (10-15Hz) and 5-9Hz oscillations in EEG. It was found that non-linear dynamics of spike-wave discharges and sleep spindles fits well to the law of 'on-off intermittency'. Intermittency in sleep spindles and spike-wave discharges implies that (1) temporal dynamics of these oscillations are deterministic in nature, and (2) it might be controlled by a system-level mechanism responsible for circadian modulation of neuronal network activity.

  11. Spatiotemporal 16p11.2 protein network implicates cortical late mid-fetal brain development and KCTD13-Cul3-RhoA pathway in psychiatric diseases.

    PubMed

    Lin, Guan Ning; Corominas, Roser; Lemmens, Irma; Yang, Xinping; Tavernier, Jan; Hill, David E; Vidal, Marc; Sebat, Jonathan; Iakoucheva, Lilia M

    2015-02-18

    The psychiatric disorders autism and schizophrenia have a strong genetic component, and copy number variants (CNVs) are firmly implicated. Recurrent deletions and duplications of chromosome 16p11.2 confer a high risk for both diseases, but the pathways disrupted by this CNV are poorly defined. Here we investigate the dynamics of the 16p11.2 network by integrating physical interactions of 16p11.2 proteins with spatiotemporal gene expression from the developing human brain. We observe profound changes in protein interaction networks throughout different stages of brain development and/or in different brain regions. We identify the late mid-fetal period of cortical development as most critical for establishing the connectivity of 16p11.2 proteins with their co-expressed partners. Furthermore, our results suggest that the regulation of the KCTD13-Cul3-RhoA pathway in layer 4 of the inner cortical plate is crucial for controlling brain size and connectivity and that its dysregulation by de novo mutations may be a potential determinant of 16p11.2 CNV deletion and duplication phenotypes.

  12. Axonal and somatic filtering of antidromically evoked cortical excitation by simulated deep brain stimulation in rat brain

    PubMed Central

    Chomiak, T; Hu, B

    2007-01-01

    Antidromic cortical excitation has been implicated as a contributing mechanism for high-frequency deep brain stimulation (DBS). Here, we examined the reliability of antidromic responses of type 2 corticofugal fibres in rat over a stimulation frequency range compatible to the DBS used in humans. We activated antidromically individual layer V neurones by stimulating their two subcortical axonal branches. We found that antidromic cortical excitation is not as reliable as generally assumed. Whereas the fast conducting branches of a type 2 axon in the highly myelinated brainstem region follow high-frequency stimulation, the slower conducting fibres in the poorly myelinated thalamic region function as low-pass filters. These fibres fail to transmit consecutive antidromic spikes at the beginning of high-frequency stimulation, but are able to maintain a steady low-frequency (6–12 Hz) spike output during the stimulation. In addition, antidromic responses evoked from both branches are rarely present in cortical neurones with a more hyperpolarized membrane potential. Our data indicate that axon-mediated antidromic excitation in the cortex is strongly influenced by the myelo-architecture of the stimulation site and the excitability of individual cortical neurones. PMID:17170044

  13. Correlated EEG Signals Simulation Based on Artificial Neural Networks.

    PubMed

    Tomasevic, Nikola M; Neskovic, Aleksandar M; Neskovic, Natasa J

    2016-09-30

    In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed method is based on the principles of artificial neural networks (ANN). Contrary to the existing EEG data simulators, the ANN-based approach was leveraged solely on the experimentally acquired EEG data. More precisely, measured EEG data were utilized to optimize the simulator which consisted of two ANN models (each model responsible for generation of one EEG sequence). In order to acquire the EEG recordings, the measurement campaign was carried out on a healthy awake adult having no cognitive, physical or mental load. For the evaluation of the proposed approach, comprehensive quantitative and qualitative statistical analysis was performed considering probability distribution, correlation properties and spectral characteristics of generated EEG processes. The obtained results clearly indicated the satisfactory agreement with the measurement data.

  14. Pore connectivity, electrical conductivity, and partial water saturation: Network simulations

    NASA Astrophysics Data System (ADS)

    Li, M.; Tang, Y. B.; Bernabé, Y.; Zhao, J. Z.; Li, X. F.; Bai, X. Y.; Zhang, L. H.

    2015-06-01

    The electrical conductivity of brine-saturated rock is predominantly dependent on the geometry and topology of the pore space. When a resistive second phase (e.g., air in the vadose zone and oil/gas in hydrocarbon reservoirs) displaces the brine, the geometry and topology of the pore space occupied by the electrically conductive phase are changed. We investigated the effect of these changes on the electrical conductivity of rock partially saturated with brine. We simulated drainage and imbibition as invasion and bond percolation processes, respectively, in pipe networks assumed to be perfectly water-wet. The simulations included the formation of a water film in the pipes invaded by the nonwetting fluid. During simulated drainage/imbibition, we measured the changes in resistivity index as well as a number of relevant microstructural parameters describing the portion of the pore space saturated with water. Except Euler topological number, all quantities considered here showed a significant level of "universality," i.e., insensitivity to the type of lattice used (simple cubic, body-centered cubic, or face-centered cubic). Hence, the coordination number of the pore network appears to be a more effective measure of connectivity than Euler number. In general, the simulated resistivity index did not obey Archie's simple power law. In log-log scale, the resistivity index curves displayed a substantial downward or upward curvature depending on the presence or absence of a water film. Our network simulations compared relatively well with experimental data sets, which were obtained using experimental conditions and procedures consistent with the simulations. Finally, we verified that the connectivity/heterogeneity model proposed by Bernabé et al. (2011) could be extended to the partial brine saturation case when water films were not present.

  15. Simulation of nonlinear strutures with artificial neural networks

    SciTech Connect

    Paez, T.L.

    1996-03-01

    Structural system simulation is important in analysis, design, testing, control, and other areas, but it is particularly difficult when the system under consideration is nonlinear. Artificial neural networks offer a useful tool for the modeling of nonlinear systems, however, such modeling may be inefficient or insufficiently accurate when the system under consideration is complex. This paper shows that there are several transformations that can be used to uncouple and simplify the components of motion of a complex nonlinear system, thereby making its modeling and simulation a much simpler problem. A numerical example is also presented.

  16. NCC Simulation Model: Simulating the operations of the network control center, phase 2

    NASA Technical Reports Server (NTRS)

    Benjamin, Norman M.; Paul, Arthur S.; Gill, Tepper L.

    1992-01-01

    The simulation of the network control center (NCC) is in the second phase of development. This phase seeks to further develop the work performed in phase one. Phase one concentrated on the computer systems and interconnecting network. The focus of phase two will be the implementation of the network message dialogues and the resources controlled by the NCC. These resources are requested, initiated, monitored and analyzed via network messages. In the NCC network messages are presented in the form of packets that are routed across the network. These packets are generated, encoded, decoded and processed by the network host processors that generate and service the message traffic on the network that connects these hosts. As a result, the message traffic is used to characterize the work done by the NCC and the connected network. Phase one of the model development represented the NCC as a network of bi-directional single server queues and message generating sources. The generators represented the external segment processors. The served based queues represented the host processors. The NCC model consists of the internal and external processors which generate message traffic on the network that links these hosts. To fully realize the objective of phase two it is necessary to identify and model the processes in each internal processor. These processes live in the operating system of the internal host computers and handle tasks such as high speed message exchanging, ISN and NFE interface, event monitoring, network monitoring, and message logging. Inter process communication is achieved through the operating system facilities. The overall performance of the host is determined by its ability to service messages generated by both internal and external processors.

  17. Simulation Modeling and Performance Evaluation of Space Networks

    NASA Technical Reports Server (NTRS)

    Jennings, Esther H.; Segui, John

    2006-01-01

    In space exploration missions, the coordinated use of spacecraft as communication relays increases the efficiency of the endeavors. To conduct trade-off studies of the performance and resource usage of different communication protocols and network designs, JPL designed a comprehensive extendable tool, the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE). The design and development of MACHETE began in 2000 and is constantly evolving. Currently, MACHETE contains Consultative Committee for Space Data Systems (CCSDS) protocol standards such as Proximity-1, Advanced Orbiting Systems (AOS), Packet Telemetry/Telecommand, Space Communications Protocol Specification (SCPS), and the CCSDS File Delivery Protocol (CFDP). MACHETE uses the Aerospace Corporation s Satellite Orbital Analysis Program (SOAP) to generate the orbital geometry information and contact opportunities. Matlab scripts provide the link characteristics. At the core of MACHETE is a discrete event simulator, QualNet. Delay Tolerant Networking (DTN) is an end-to-end architecture providing communication in and/or through highly stressed networking environments. Stressed networking environments include those with intermittent connectivity, large and/or variable delays, and high bit error rates. To provide its services, the DTN protocols reside at the application layer of the constituent internets, forming a store-and-forward overlay network. The key capabilities of the bundling protocols include custody-based reliability, ability to cope with intermittent connectivity, ability to take advantage of scheduled and opportunistic connectivity, and late binding of names to addresses. In this presentation, we report on the addition of MACHETE models needed to support DTN, namely: the Bundle Protocol (BP) model. To illustrate the use of MACHETE with the additional DTN model, we provide an example simulation to benchmark its performance. We demonstrate the use of the DTN protocol

  18. Wireless Vital Sign Sensor Network Simulations for Mass Casualty Response

    DTIC Science & Technology

    2013-11-27

    Casualty, Network Simulation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT: Unclassified 18. NUMBER OF PAGES 19 19a. NAME OF... security takes priority over medical treatment of the wounded, so it assumed that only two responders are available to provide medical care during...in ZigBee products. Since ZigBee software stacks are widely available and since a standard exists for ZigBee use in healthcare, it is a very

  19. Cortical commands in active touch.

    PubMed

    Brecht, Michael

    2006-01-01

    The neocortex is an enormous network of extensively interconnected neurons. It has become clear that the computations performed by individual cortical neurons will critically depend on the quantitative composition of cortical activity. Here we discuss quantitative aspects of cortical activity and modes of cortical processing in the context of rodent active touch. Through in vivo whole-cell recordings one observes widespread subthreshold and very sparse evoked action potential (AP) activity in the somatosensory cortex both for passive whisker deflection in anaesthetized animals and during active whisker movements in awake animals. Neurons of the somatosensory cortex become either suppressed during whisking or activated by an efference copy of whisker movement signal that depolarize cells at certain phases of the whisking cycle. To probe the read out of cortical motor commands we applied intracellular stimulation in rat whisker motor cortex. We find that APs in individual cortical neurons can evoke long sequences of small whisker movements. The capacity of an individual neuron to evoke movements is most astonishing given the large number of neurons in whisker motor cortex. Thus, few cortical APs may suffice to control motor behaviour and such APs can be translated into action with the utmost precision. We conclude that there is very widespread subthreshold cortical activity and very sparse, highly specific cortical AP activity.

  20. Simulation study of unmanned aerial vehicle communication networks addressing bandwidth disruptions

    NASA Astrophysics Data System (ADS)

    Wei, Sixiao; Ge, Linqiang; Yu, Wei; Chen, Genshe; Pham, Khanh; Blasch, Erik; Shen, Dan; Lu, Chao

    2014-06-01

    To date, Unmanned Aerial Vehicles (UAVs) have been widely used for numerous applications. UAVs can directly connect to ground stations or satellites to transfer data. Multiple UAVs can communicate and cooperate with each other and then construct an ad-hoc network. Multi-UAV systems have the potential to provide reliable and timely services for end users in addition to satellite networks. In this paper, we conduct a simulation study for evaluating the network performance of multi-UAV systems and satellite networks using the ns-2 networking simulation tool. Our simulation results show that UAV communication networks can achieve better network performance than satellite networks and with a lower cost and increased timeliness. We also investigate security resiliency of UAV networks. As a case study, we simulate false data injection attacks against UAV communication networks in ns-2 and demonstrate the impact of false data injection attacks on network performance.

  1. Ship electric propulsion simulator based on networking technology

    NASA Astrophysics Data System (ADS)

    Zheng, Huayao; Huang, Xuewu; Chen, Jutao; Lu, Binquan

    2006-11-01

    According the new ship building tense, a novel electric propulsion simulator (EPS) had been developed in Marine Simulation Center of SMU. The architecture, software function and FCS network technology of EPS and integrated power system (IPS) were described. In allusion to the POD propeller in ship, a special physical model was built. The POD power was supplied from the simulative 6.6 kV Medium Voltage Main Switchboard, its control could be realized in local or remote mode. Through LAN, the simulated feature information of EPS will pass to the physical POD model, which would reflect the real thruster working status in different sea conditions. The software includes vessel-propeller math module, thruster control system, distribution and emergency integrated management, double closed loop control system, vessel static water resistance and dynamic software; instructor main control software. The monitor and control system is realized by real time data collection system and CAN bus technology. During the construction, most devices such as monitor panels and intelligent meters, are developed in lab which were based on embedded microcomputer system with CAN interface to link the network. They had also successfully used in practice and would be suitable for the future demands of digitalization ship.

  2. Causal measures of structure and plasticity in simulated and living neural networks.

    PubMed

    Cadotte, Alex J; DeMarse, Thomas B; He, Ping; Ding, Mingzhou

    2008-10-07

    A major goal of neuroscience is to understand the relationship between neural structures and their function. Recording of neural activity with arrays of electrodes is a primary tool employed toward this goal. However, the relationships among the neural activity recorded by these arrays are often highly complex making it problematic to accurately quantify a network's structural information and then relate that structure to its function. Current statistical methods including cross correlation and coherence have achieved only modest success in characterizing the structural connectivity. Over the last decade an alternative technique known as Granger causality is emerging within neuroscience. This technique, borrowed from the field of economics, provides a strong mathematical foundation based on linear auto-regression to detect and quantify "causal" relationships among different time series. This paper presents a combination of three Granger based analytical methods that can quickly provide a relatively complete representation of the causal structure within a neural network. These are a simple pairwise Granger causality metric, a conditional metric, and a little known computationally inexpensive subtractive conditional method. Each causal metric is first described and evaluated in a series of biologically plausible neural simulations. We then demonstrate how Granger causality can detect and quantify changes in the strength of those relationships during plasticity using 60 channel spike train data from an in vitro cortical network measured on a microelectrode array. We show that these metrics can not only detect the presence of causal relationships, they also provide crucial information about the strength and direction of that relationship, particularly when that relationship maybe changing during plasticity. Although we focus on the analysis of multichannel spike train data the metrics we describe are applicable to any stationary time series in which causal

  3. Efficiently passing messages in distributed spiking neural network simulation.

    PubMed

    Thibeault, Corey M; Minkovich, Kirill; O'Brien, Michael J; Harris, Frederick C; Srinivasa, Narayan

    2013-01-01

    Efficiently passing spiking messages in a neural model is an important aspect of high-performance simulation. As the scale of networks has increased so has the size of the computing systems required to simulate them. In addition, the information exchange of these resources has become more of an impediment to performance. In this paper we explore spike message passing using different mechanisms provided by the Message Passing Interface (MPI). A specific implementation, MVAPICH, designed for high-performance clusters with Infiniband hardware is employed. The focus is on providing information about these mechanisms for users of commodity high-performance spiking simulators. In addition, a novel hybrid method for spike exchange was implemented and benchmarked.

  4. GiPSiNet: an open source/open architecture network middleware for surgical simulations.

    PubMed

    Liberatore, Vincenzo; Cavuşoğlu, M Cenk; Cai, Qingbo

    2006-01-01

    In this paper, we present the design and techniques of GiPSiNet, an open source/open architecture network middleware being developed for surgical simulations. GiPSiNet extends GiPSi (General Interactive Physical Simulation Interface), our framework for developing organ level surgical simulations, to network environments. This network extension is non-trivial, since the network settings pose several serious problems for distributed surgical virtual environments such as band-width limit, delays, and packet losses. Our goal is to enhance the quality (fidelity and realism) of networked simulations in the absence of network QoS (Quality of Service) through the GiPSiNet middleware.

  5. Frontotemporal oxyhemoglobin dynamics predict performance accuracy of dance simulation gameplay: temporal characteristics of top-down and bottom-up cortical activities.

    PubMed

    Ono, Yumie; Nomoto, Yasunori; Tanaka, Shohei; Sato, Keisuke; Shimada, Sotaro; Tachibana, Atsumichi; Bronner, Shaw; Noah, J Adam

    2014-01-15

    We utilized the high temporal resolution of functional near-infrared spectroscopy to explore how sensory input (visual and rhythmic auditory cues) are processed in the cortical areas of multimodal integration to achieve coordinated motor output during unrestricted dance simulation gameplay. Using an open source clone of the dance simulation video game, Dance Dance Revolution, two cortical regions of interest were selected for study, the middle temporal gyrus (MTG) and the frontopolar cortex (FPC). We hypothesized that activity in the FPC would indicate top-down regulatory mechanisms of motor behavior; while that in the MTG would be sustained due to bottom-up integration of visual and auditory cues throughout the task. We also hypothesized that a correlation would exist between behavioral performance and the temporal patterns of the hemodynamic responses in these regions of interest. Results indicated that greater temporal accuracy of dance steps positively correlated with persistent activation of the MTG and with cumulative suppression of the FPC. When auditory cues were eliminated from the simulation, modifications in cortical responses were found depending on the gameplay performance. In the MTG, high-performance players showed an increase but low-performance players displayed a decrease in cumulative amount of the oxygenated hemoglobin response in the no music condition compared to that in the music condition. In the FPC, high-performance players showed relatively small variance in the activity regardless of the presence of auditory cues, while low-performance players showed larger differences in the activity between the no music and music conditions. These results suggest that the MTG plays an important role in the successful integration of visual and rhythmic cues and the FPC may work as top-down control to compensate for insufficient integrative ability of visual and rhythmic cues in the MTG. The relative relationships between these cortical areas indicated

  6. Ketamine Dysregulates the Amplitude and Connectivity of High-Frequency Oscillations in Cortical-Subcortical Networks in Humans: Evidence From Resting-State Magnetoencephalography-Recordings.

    PubMed

    Rivolta, Davide; Heidegger, Tonio; Scheller, Bertram; Sauer, Andreas; Schaum, Michael; Birkner, Katharina; Singer, Wolf; Wibral, Michael; Uhlhaas, Peter J

    2015-09-01

    Hypofunctioning of the N-methyl-D-aspartate receptor (NMDA-R) has been prominently implicated in the pathophysiology of schizophrenia (ScZ). The current study tested the effects of ketamine, a dissociative anesthetic and NMDA-R antagonist, on resting-state activity recorded with magnetoencephalography (MEG) in healthy volunteers. In a single-blind cross-over design, each participant (n = 12) received, on 2 different sessions, a subanesthetic dose of S-ketamine (0.006 mg/Kg) and saline injection. MEG-data were analyzed at sensor- and source-level in the beta (13-30 Hz) and gamma (30-90 Hz) frequency ranges. In addition, connectivity analysis at source-level was performed using transfer entropy (TE). Ketamine increased gamma-power while beta-band activity was decreased. Specifically, elevated 30-90 Hz activity was pronounced in subcortical (thalamus and hippocampus) and cortical (frontal and temporal cortex) regions, whilst reductions in beta-band power were localized to the precuneus, cerebellum, anterior cingulate, temporal and visual cortex. TE analysis demonstrated increased information transfer in a thalamo-cortical network after ketamine administration. The findings are consistent with the pronounced dysregulation of high-frequency oscillations following the inhibition of NMDA-R in animal models of ScZ as well as with evidence from electroencephalogram-data in ScZ-patients and increased functional connectivity during early illness stages. Moreover, our data highlight the potential contribution of thalamo-cortical connectivity patterns towards ketamine-induced neuronal dysregulation, which may be relevant for the understanding of ScZ as a disorder of disinhibition of neural circuits.

  7. A rigorous framework for multiscale simulation of stochastic cellular networks

    PubMed Central

    Chevalier, Michael W.; El-Samad, Hana

    2009-01-01

    Noise and stochasticity are fundamental to biology and derive from the very nature of biochemical reactions where thermal motion of molecules translates into randomness in the sequence and timing of reactions. This randomness leads to cell-cell variability even in clonal populations. Stochastic biochemical networks are modeled as continuous time discrete state Markov processes whose probability density functions evolve according to a chemical master equation (CME). The CME is not solvable but for the simplest cases, and one has to resort to kinetic Monte Carlo techniques to simulate the stochastic trajectories of the biochemical network under study. A commonly used such algorithm is the stochastic simulation algorithm (SSA). Because it tracks every biochemical reaction that occurs in a given system, the SSA presents computational difficulties especially when there is a vast disparity in the timescales of the reactions or in the number of molecules involved in these reactions. This is common in cellular networks, and many approximation algorithms have evolved to alleviate the computational burdens of the SSA. Here, we present a rigorously derived modified CME framework based on the partition of a biochemically reacting system into restricted and unrestricted reactions. Although this modified CME decomposition is as analytically difficult as the original CME, it can be naturally used to generate a hierarchy of approximations at different levels of accuracy. Most importantly, some previously derived algorithms are demonstrated to be limiting cases of our formulation. We apply our methods to biologically relevant test systems to demonstrate their accuracy and efficiency. PMID:19673546

  8. Quantum versus simulated annealing in wireless interference network optimization.

    PubMed

    Wang, Chi; Chen, Huo; Jonckheere, Edmond

    2016-05-16

    Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking-more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed.

  9. Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

    PubMed Central

    Palma, Jesse; Grossberg, Stephen; Versace, Massimiliano

    2012-01-01

    Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM). Theorems in the 1970's showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP) currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh) can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 ms or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all (WTA) stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners when the network

  10. Leader neurons in leaky integrate and fire neural network simulations.

    PubMed

    Zbinden, Cyrille

    2011-10-01

    In this paper, we highlight the topological properties of leader neurons whose existence is an experimental fact. Several experimental studies show the existence of leader neurons in population bursts of activity in 2D living neural networks (Eytan and Marom, J Neurosci 26(33):8465-8476, 2006; Eckmann et al., New J Phys 10(015011), 2008). A leader neuron is defined as a neuron which fires at the beginning of a burst (respectively network spike) more often than we expect by chance considering its mean firing rate. This means that leader neurons have some burst triggering power beyond a chance-level statistical effect. In this study, we characterize these leader neuron properties. This naturally leads us to simulate neural 2D networks. To build our simulations, we choose the leaky integrate and fire (lIF) neuron model (Gerstner and Kistler 2002; Cessac, J Math Biol 56(3):311-345, 2008), which allows fast simulations (Izhikevich, IEEE Trans Neural Netw 15(5):1063-1070, 2004; Gerstner and Naud, Science 326:379-380, 2009). The dynamics of our lIF model has got stable leader neurons in the burst population that we simulate. These leader neurons are excitatory neurons and have a low membrane potential firing threshold. Except for these two first properties, the conditions required for a neuron to be a leader neuron are difficult to identify and seem to depend on several parameters involved in the simulations themselves. However, a detailed linear analysis shows a trend of the properties required for a neuron to be a leader neuron. Our main finding is: A leader neuron sends signals to many excitatory neurons as well as to few inhibitory neurons and a leader neuron receives only signals from few other excitatory neurons. Our linear analysis exhibits five essential properties of leader neurons each with different relative importance. This means that considering a given neural network with a fixed mean number of connections per neuron, our analysis gives us a way of

  11. Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?

    NASA Astrophysics Data System (ADS)

    Fels, Meike; Bauer, Robert; Gharabaghi, Alireza

    2015-08-01

    Objective. Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns. Approach. We assessed the perceived workload with the NASA Task Load Index in twenty-one subjects who were exposed to two different feedback tasks in a cross-over design: (i) brain-robot interface (BRI) with haptic/proprioceptive feedback of sensorimotor oscillations related to motor imagery, and (ii) control of neuromuscular activity with feedback of the electromyography (EMG) of the same hand. We also used electroencephalography to examine the cortical activation patterns beforehand in resting state and during the training session of each task. Main results. The workload profile of BRI feedback differed from EMG feedback and was particularly characterized by the experience of frustration. The frustration level was highly correlated across tasks, suggesting subject-related relevance of this workload component. Those subjects who were specifically challenged by the respective tasks could be detected by an interhemispheric alpha-band network in resting state before the training and by their sensorimotor theta-band activation pattern during the exercise. Significance. Neurophysiological profiles in resting state and during the exercise may provide task-independent workload markers for monitoring and matching participants’ ability and task difficulty of neurofeedback interventions.

  12. Inactivation of the Anterior Cingulate Reveals Enhanced Reliance on Cortical Networks for Remote Spatial Memory Retrieval after Sequential Memory Processing

    PubMed Central

    Wartman, Brianne C.; Gabel, Jennifer; Holahan, Matthew R.

    2014-01-01

    One system consolidation model suggests that as time passes, ensembles of cortical neurons form strong connections to represent remote memories. In this model, the anterior cingulate cortex (ACC) serves as a cortical region that represents remote memories. However, there is debate as to whether remote spatial memories go through this systems consolidation process and come to rely on the ACC. The present experiment examined whether increasing the processing demand on the hippocampus, by sequential training on two spatial tasks, would more fully engage the ACC during retrieval of a remote spatial memory. In this scenario, inactivation of the ACC at a remote time point was hypothesized to produce a severe memory deficit if rats had been trained on two, sequential spatial tasks. Rats were trained on a water maze (WM) task only or a WM task followed by a radial arm maze task. A WM probe test was given recently or remotely to all rats. Prior to the probe test, rats received an injection of saline or muscimol into the ACC. A subtle deficit in probe performance was found at the remote time point in the group trained on only one spatial task and treated with muscimol. In the group trained on two spatial tasks and treated with muscimol, a subtle deficit in probe performance was noted at the recent time point and a substantial deficit in probe performance was observed at the remote time point. c-Fos labeling in the hippocampus revealed more labeling in the CA1 region in all remotely tested groups than recently tested groups. Findings suggest that spatial remote memories come to rely more fully on the ACC when hippocampal processing requirements are increased. Results also suggest continued involvement of the hippocampus in spatial memory retrieval along with a progressive strengthening of cortical connections as time progresses. PMID:25279556

  13. A Network Scheduling Model for Distributed Control Simulation

    NASA Technical Reports Server (NTRS)

    Culley, Dennis; Thomas, George; Aretskin-Hariton, Eliot

    2016-01-01

    Distributed engine control is a hardware technology that radically alters the architecture for aircraft engine control systems. Of its own accord, it does not change the function of control, rather it seeks to address the implementation issues for weight-constrained vehicles that can limit overall system performance and increase life-cycle cost. However, an inherent feature of this technology, digital communication networks, alters the flow of information between critical elements of the closed-loop control. Whereas control information has been available continuously in conventional centralized control architectures through virtue of analog signaling, moving forward, it will be transmitted digitally in serial fashion over the network(s) in distributed control architectures. An underlying effect is that all of the control information arrives asynchronously and may not be available every loop interval of the controller, therefore it must be scheduled. This paper proposes a methodology for modeling the nominal data flow over these networks and examines the resulting impact for an aero turbine engine system simulation.

  14. The design and simulation test of wireless antenna protection network

    NASA Astrophysics Data System (ADS)

    Chen, Zipeng; Dai, Yawen; Li, Peng; Li, Zhuoqiu

    2013-03-01

    In this paper, a wireless antenna protection program has been designed. In the program, the TVS diode was used as the first lever for protection, and the π-type high pass filtering network as the second lever. As a result, the program not only has the traditional function of ESD protection, which can avoid the high voltage damage to the internal circuit, but also achieves the purpose of load matching, ensuring the signal source not to distort. The ADS simulation software was used to test the ability of this program for filtering and impedance matching, which proved the feasibility of this program. The wireless antenna protection network has been practically used, and its' performance of anti-electromagnetic interference has been validated.

  15. Network simulation using the simulation language for alternate modeling (SLAM 2)

    NASA Technical Reports Server (NTRS)

    Shen, S.; Morris, D. W.

    1983-01-01

    The simulation language for alternate modeling (SLAM 2) is a general purpose language that combines network, discrete event, and continuous modeling capabilities in a single language system. The efficacy of the system's network modeling is examined and discussed. Examples are given of the symbolism that is used, and an example problem and model are derived. The results are discussed in terms of the ease of programming, special features, and system limitations. The system offers many features which allow rapid model development and provides an informative standardized output. The system also has limitations which may cause undetected errors and misleading reports unless the user is aware of these programming characteristics.

  16. Three-phase flow simulations in discrete fracture networks

    NASA Astrophysics Data System (ADS)

    Geiger, S.; Niessner, J.; Matthai, S. K.; Helmig, R.

    2006-12-01

    Fractures are often the key conduits for fluid flow in otherwise low permeability rocks. Their presence in hydrocarbon reservoirs leads to complex production histories, unpredictable coupling of wells, rapidly changing flow rates, possibly early water breakthrough, and low final recovery. Recently, it has been demonstrated that a combination of finite volume and finite element discretization is well suited to model incompressible, immiscible two-phase flow in 3D discrete fracture networks (DFN) representing complexly fractured rocks. Such an approach has been commercialized in Golder Associates' FracMan Reservoir Edition software. For realistic reservoir simulations, however, it would be desirable if a third compressible gas phase can be included which is often present at reservoir conditions. Here we present the extension of an existing node-centred finite volume - finite element (FEFV) discretization for the efficient and accurate simulations of three-component - three-phase flow in geologically realistic representations of fractured porous media. Two possible types of fracture networks can be used: In 2D, they are detailed geometrical representations of fractured rock masses mapped in field studies. In 3D, they are geologically constrained, stochastically generated discrete fracture networks. Flow and transport can be simulated for fractures only or for fractures and matrix combined. The governing equations are solved decoupled using an implicit-pressure, explicit-saturation (IMPES) approach. Flux and concentration terms can be treated with higher-order accuracy in the finite volume scheme to preserve shock fronts. The method is locally mass conservative and works on unstructured, spatially refined grids. Flash calculations are carried out by a new description of the Black-Oil model. Capillary and gravity effects are included in this formulation. The robustness and accuracy of this formulation is shown in several applications. First, grid convergence is

  17. Network Flow Simulation of Fluid Transients in Rocket Propulsion Systems

    NASA Technical Reports Server (NTRS)

    Bandyopadhyay, Alak; Hamill, Brian; Ramachandran, Narayanan; Majumdar, Alok

    2011-01-01

    Fluid transients, also known as water hammer, can have a significant impact on the design and operation of both spacecraft and launch vehicle propulsion systems. These transients often occur at system activation and shutdown. The pressure rise due to sudden opening and closing of valves of propulsion feed lines can cause serious damage during activation and shutdown of propulsion systems. During activation (valve opening) and shutdown (valve closing), pressure surges must be predicted accurately to ensure structural integrity of the propulsion system fluid network. In the current work, a network flow simulation software (Generalized Fluid System Simulation Program) based on Finite Volume Method has been used to predict the pressure surges in the feed line due to both valve closing and valve opening using two separate geometrical configurations. The valve opening pressure surge results are compared with experimental data available in the literature and the numerical results compared very well within reasonable accuracy (< 5%) for a wide range of inlet-to-initial pressure ratios. A Fast Fourier Transform is preformed on the pressure oscillations to predict the various modal frequencies of the pressure wave. The shutdown problem, i.e. valve closing problem, the simulation results are compared with the results of Method of Characteristics. Most rocket engines experience a longitudinal acceleration, known as "pogo" during the later stage of engine burn. In the shutdown example problem, an accumulator has been used in the feed system to demonstrate the "pogo" mitigation effects in the feed system of propellant. The simulation results using GFSSP compared very well with the results of Method of Characteristics.

  18. Coarse-graining stochastic biochemical networks: adiabaticity and fast simulations

    SciTech Connect

    Nemenman, Ilya; Sinitsyn, Nikolai; Hengartner, Nick

    2008-01-01

    We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical kinetics networks, which rests on elimination of fast chemical species without a loss of information about mesoscoplc, non-Poissonian fluctuations of the slow ones. Our approach, which is similar to the Born-Oppenhelmer approximation in quantum mechanics, follows from the stochastic path Integral representation of the cumulant generating function of reaction events. In applications with a small number of chemIcal reactions, It produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, Interpretable representation and can be used for coarse-grained numerical simulation schemes with a small computational complexity and yet high accuracy. As an example, we derive the coarse-grained description for a chain of biochemical reactions, and show that the coarse-grained and the microscopic simulations are in an agreement, but the coarse-gralned simulations are three orders of magnitude faster.

  19. Quantum versus simulated annealing in wireless interference network optimization

    NASA Astrophysics Data System (ADS)

    Wang, Chi; Chen, Huo; Jonckheere, Edmond

    2016-05-01

    Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking—more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed.

  20. Quantum versus simulated annealing in wireless interference network optimization

    PubMed Central

    Wang, Chi; Chen, Huo; Jonckheere, Edmond

    2016-01-01

    Quantum annealing (QA) serves as a specialized optimizer that is able to solve many NP-hard problems and that is believed to have a theoretical advantage over simulated annealing (SA) via quantum tunneling. With the introduction of the D-Wave programmable quantum annealer, a considerable amount of effort has been devoted to detect and quantify quantum speedup. While the debate over speedup remains inconclusive as of now, instead of attempting to show general quantum advantage, here, we focus on a novel real-world application of D-Wave in wireless networking—more specifically, the scheduling of the activation of the air-links for maximum throughput subject to interference avoidance near network nodes. In addition, D-Wave implementation is made error insensitive by a novel Hamiltonian extra penalty weight adjustment that enlarges the gap and substantially reduces the occurrence of interference violations resulting from inevitable spin bias and coupling errors. The major result of this paper is that quantum annealing benefits more than simulated annealing from this gap expansion process, both in terms of ST99 speedup and network queue occupancy. It is the hope that this could become a real-word application niche where potential benefits of quantum annealing could be objectively assessed. PMID:27181056

  1. Orexin-dependent activation of layer VIb enhances cortical network activity and integration of non-specific thalamocortical inputs.

    PubMed

    Hay, Y Audrey; Andjelic, Sofija; Badr, Sammy; Lambolez, Bertrand

    2015-11-01

    Neocortical layer VI is critically involved in thalamocortical activity changes during the sleep/wake cycle. It receives dense projections from thalamic nuclei sensitive to the wake-promoting neuropeptides orexins, and its deepest part, layer VIb, is the only cortical lamina reactive to orexins. This convergence of wake-promoting inputs prompted us to investigate how layer VIb can modulate cortical arousal, using patch-clamp recordings and optogenetics in rat brain slices. We found that the majority of layer VIb neurons were excited by nicotinic agonists and orexin through the activation of nicotinic receptors containing α4-α5-β2 subunits and OX2 receptor, respectively. Specific effects of orexin on layer VIb neurons were potentiated by low nicotine concentrations and we used this paradigm to explore their intracortical projections. Co-application of nicotine and orexin increased the frequency of excitatory post-synaptic currents in the ipsilateral cortex, with maximal effect in infragranular layers and minimal effect in layer IV, as well as in the contralateral cortex. The ability of layer VIb to relay thalamocortical inputs was tested using photostimulation of channelrhodopsin-expressing fibers from the orexin-sensitive rhomboid nucleus in the parietal cortex. Photostimulation induced robust excitatory currents in layer VIa neurons that were not pre-synaptically modulated by orexin, but exhibited a delayed, orexin-dependent, component. Activation of layer VIb by orexin enhanced the reliability and spike-timing precision of layer VIa responses to rhomboid inputs. These results indicate that layer VIb acts as an orexin-gated excitatory feedforward loop that potentiates thalamocortical arousal.

  2. A Simulation of Cooperation and Competition in Insurgent Networks

    NASA Astrophysics Data System (ADS)

    Gabbay, Michael

    2014-03-01

    Insurgencies are often characterized by multiple groups who share a common foe in the national government but have independent organizations which may differ with respect to social identities, ideologies, strategies, and their use of violence. These groups may cooperate in various ways such as conducting joint attacks, pooling resources, and establishing formal alliances or mergers. However, they may also compete with each other over popular support, recruitment of fighters, funding, allies, and ultimately military dominance. A network coevolution model of insurgent factional dynamics is presented which accounts for factors driving cooperation and competition. The model is formulated as a system of coupled ODEs which evolves network ties between insurgent groups along with group policies concerning the targets of violence. Simulation results are presented showing sharp transitions in network structure as model parameters are varied. Connections are drawn between the model results and empirical data from the Iraqi insurgency. This work was supported by the Office of Naval Research under grant N00014-13-1-0381.

  3. Network condition simulator for benchmarking sewer deterioration models.

    PubMed

    Scheidegger, A; Hug, T; Rieckermann, J; Maurer, M

    2011-10-15

    An accurate description of aging and deterioration of urban drainage systems is necessary for optimal investment and rehabilitation planning. Due to a general lack of suitable datasets, network condition models are rarely validated, and if so with varying levels of success. We therefore propose a novel network condition simulator (NetCoS) that produces a synthetic population of sewer sections with a given condition-class distribution. NetCoS can be used to benchmark deterioration models and guide utilities in the selection of appropriate models and data management strategies. The underlying probabilistic model considers three main processes: a) deterioration, b) replacement policy, and c) expansions of the sewer network. The deterioration model features a semi-Markov chain that uses transition probabilities based on user-defined survival functions. The replacement policy is approximated with a condition-class dependent probability of replacing a sewer pipe. The model then simulates the course of the sewer sections from the installation of the first line to the present, adding new pipes based on the defined replacement and expansion program. We demonstrate the usefulness of NetCoS in two examples where we quantify the influence of incomplete data and inspection frequency on the parameter estimation of a cohort survival model and a Markov deterioration model. Our results show that typical available sewer inventory data with discarded historical data overestimate the average life expectancy by up to 200 years. Although NetCoS cannot prove the validity of a particular deterioration model, it is useful to reveal its possible limitations and shortcomings and quantifies the effects of missing or uncertain data. Future developments should include additional processes, for example to investigate the long-term effect of pipe rehabilitation measures, such as inliners.

  4. Climate and change: simulating flooding impacts on urban transport network

    NASA Astrophysics Data System (ADS)

    Pregnolato, Maria; Ford, Alistair; Dawson, Richard

    2015-04-01

    National-scale climate projections indicate that in the future there will be hotter and drier summers, warmer and wetter winters, together with rising sea levels. The frequency of extreme weather events is expected to increase, causing severe damage to the built environment and disruption of infrastructures (Dawson, 2007), whilst population growth and changed demographics are placing new demands on urban infrastructure. It is therefore essential to ensure infrastructure networks are robust to these changes. This research addresses these challenges by focussing on the development of probabilistic tools for managing risk by modelling urban transport networks within the context of extreme weather events. This paper presents a methodology to investigate the impacts of extreme weather events on urban environment, in particular infrastructure networks, through a combination of climate simulations and spatial representations. By overlaying spatial data on hazard thresholds from a flood model and a flood safety function, mitigated by potential adaptation strategies, different levels of disruption to commuting journeys on road networks are evaluated. The method follows the Catastrophe Modelling approach and it consists of a spatial model, combining deterministic loss models and probabilistic risk assessment techniques. It can be applied to present conditions as well as future uncertain scenarios, allowing the examination of the impacts alongside socio-economic and climate changes. The hazard is determined by simulating free surface water flooding, with the software CityCAT (Glenis et al., 2013). The outputs are overlapped to the spatial locations of a simple network model in GIS, which uses journey-to-work (JTW) observations, supplemented with speed and capacity information. To calculate the disruptive effect of flooding on transport networks, a function relating water depth to safe driving car speed has been developed by combining data from experimental reports (Morris et

  5. Brain fingerprints of olfaction: a novel structural method for assessing olfactory cortical networks in health and disease

    PubMed Central

    Fjaeldstad, A.; Fernandes, H. M.; Van Hartevelt, T. J.; Gleesborg, C.; Møller, A.; Ovesen, T.; Kringelbach, M. L.

    2017-01-01

    Olfactory deficits are a common (often prodromal) symptom of neurodegenerative or psychiatric disorders. As such, olfaction could have great potential as an early biomarker of disease, for example using neuroimaging to investigate the breakdown of structural connectivity profile of the primary olfactory networks. We investigated the suitability for this purpose in two existing neuroimaging maps of olfactory networks. We found problems with both existing neuroimaging maps in terms of their structural connectivity to known secondary olfactory networks. Based on these findings, we were able to merge the existing maps to a new template map of olfactory networks with connections to all key secondary olfactory networks. We introduce a new method that combines diffusion tensor imaging with probabilistic tractography and pattern recognition techniques. This method can obtain comprehensive and reliable fingerprints of the structural connectivity underlying the neural processing of olfactory stimuli in normosmic adults. Combining the novel proposed method for structural fingerprinting with the template map of olfactory networks has great potential to be used for future neuroimaging investigations of olfactory function in disease. With time, the proposed method may even come to serve as structural biomarker for early detection of disease. PMID:28195241

  6. Experimental investigations and finite element simulation of cutting heat in vibrational and conventional drilling of cortical bone.

    PubMed

    Wang, Yu; Cao, Meng; Zhao, Xiangrui; Zhu, Gang; McClean, Colin; Zhao, Yuanyuan; Fan, Yubo

    2014-11-01

    Heat generated during bone drilling could cause irreversible thermal damage, which can lead to bone necrosis or even osteomyelitis. In this study, vibrational drilling was applied to fresh bovine bones to investigate the cutting heat in comparison with conventional drilling through experimental investigation and finite element analysis (FEA). The influence of vibrational frequency and amplitude on cutting heat generation and conduction were studied. The experimental results showed that, compared with the conventional drilling, vibrational drilling could significantly reduce the cutting temperature in drilling of cortical bone (P<0.05): the cutting temperature tended to decrease with increasing vibrational frequency and amplitude. The FEA results also showed that the vibrational amplitude holds a significant effect on the cutting heat conduction.

  7. DISCRETE EVENT SIMULATION OF OPTICAL SWITCH MATRIX PERFORMANCE IN COMPUTER NETWORKS

    SciTech Connect

    Imam, Neena; Poole, Stephen W

    2013-01-01

    In this paper, we present application of a Discrete Event Simulator (DES) for performance modeling of optical switching devices in computer networks. Network simulators are valuable tools in situations where one cannot investigate the system directly. This situation may arise if the system under study does not exist yet or the cost of studying the system directly is prohibitive. Most available network simulators are based on the paradigm of discrete-event-based simulation. As computer networks become increasingly larger and more complex, sophisticated DES tool chains have become available for both commercial and academic research. Some well-known simulators are NS2, NS3, OPNET, and OMNEST. For this research, we have applied OMNEST for the purpose of simulating multi-wavelength performance of optical switch matrices in computer interconnection networks. Our results suggest that the application of DES to computer interconnection networks provides valuable insight in device performance and aids in topology and system optimization.

  8. The trans-species core SELF: the emergence of active cultural and neuro-ecological agents through self-related processing within subcortical-cortical midline networks.

    PubMed

    Panksepp, Jaak; Northoff, Georg

    2009-03-01

    The nature of "the self" has been one of the central problems in philosophy and more recently in neuroscience. This raises various questions: (i) Can we attribute a self to animals? (ii) Do animals and humans share certain aspects of their core selves, yielding a trans-species concept of self? (iii) What are the neural processes that underlie a possible trans-species concept of self? (iv) What are the developmental aspects and do they result in various levels of self-representation? Drawing on recent literature from both human and animal research, we suggest a trans-species concept of self that is based upon what has been called a "core-self" which can be described by self-related processing (SRP) as a specific mode of interaction between organism and environment. When we refer to specific neural networks, we will here refer to the underlying system as the "core-SELF." The core-SELF provides primordial neural coordinates that represent organisms as living creatures-at the lowest level this elaborates interoceptive states along with raw emotional feelings (i.e., the intentions in action of a primordial core-SELF) while higher medial cortical levels facilitate affective-cognitive integration (yielding a fully-developed nomothetic core-self). Developmentally, SRP allows stimuli from the environment to be related and linked to organismic needs, signaled and processed within core-self structures within subcorical-cortical midline structures (SCMS) that provide the foundation for epigenetic emergence of ecologically framed, higher idiographic forms of selfhood across different individuals within a species. These functions ultimately operate as a coordinated network. We postulate that core SRP operates automatically, is deeply affective, and is developmentally and epigenetically connected to sensory-motor and higher cognitive abilities. This core-self is mediated by SCMS, embedded in visceral and instinctual representations of the body that are well integrated with basic

  9. Visualization and simulation of bubble growth in pore networks

    SciTech Connect

    Li, Xuehai; Yortsos, Y.C.

    1994-03-01

    Bubble nucleation and bubble growth in porous media is an important problem encountered in processes, such as pressure depletion and boiling. To understand its basic aspects, experiments and numerical simulations in micromodel geometries were undertaken. Experiments of bubble growth by pressure depletion were carried out in 2-D etched-glass micromodels and in Hele-Shaw cells. Nucleation of bubbles and the subsequent growth of gas clusters were visualized. Contrary to the bulk or to Hele-Shaw cells, gas clusters in the micromodel have irregular and ramified shapes and share many of the features of an external invasion process (e.g. of percolation during drainage). A pore network numerical model was developed to simulate the growth of multiple gas clusters under various conditions. The model is based on the solution of the convection-diffusions equation and also accounts for capillary and viscous forces, which play an important role in determining the growth patterns. Numerical simulation resulted in good agreement with the experimental results.

  10. Multi-level characterization of human femoral cortices and their underlying osteocyte network reveal trends in quality of young, aged, osteoporotic and antiresorptive-treated bone.

    PubMed

    Milovanovic, Petar; Zimmermann, Elizabeth A; Riedel, Christoph; vom Scheidt, Annika; Herzog, Lydia; Krause, Matthias; Djonic, Danijela; Djuric, Marija; Püschel, Klaus; Amling, Michael; Ritchie, Robert O; Busse, Björn

    2015-03-01

    Characterization of bone's hierarchical structure in aging, disease and treatment conditions is imperative to understand the architectural and compositional modifications to the material and its mechanical integrity. Here, cortical bone sections from 30 female proximal femurs - a frequent fracture site - were rigorously assessed to characterize the osteocyte lacunar network, osteon density and patterns of bone matrix mineralization by backscatter-electron imaging and Fourier-transform infrared spectroscopy in relation to mechanical properties obtained by reference-point indentation. We show that young, healthy bone revealed the highest resistance to mechanical loading (indentation) along with higher mineralization and preserved osteocyte-lacunar characteristics. In contrast, aging and osteoporosis significantly alter bone material properties, where impairment of the osteocyte-lacunar network was evident through accumulation of hypermineralized osteocyte lacunae with aging and even more in osteoporosis, highlighting increased osteocyte apoptosis and reduced mechanical competence. But antiresorptive treatment led to fewer mineralized lacunae and fewer but larger osteons signifying rejuvenated bone. In summary, multiple structural and compositional changes to the bone material were identified leading to decay or maintenance of bone quality in disease, health and treatment conditions. Clearly, antiresorptive treatment reflected favorable effects on the multifunctional osteocytic cells that are a prerequisite for bone's structural, metabolic and mechanosensory integrity.

  11. Arabidopsis SYT1 maintains stability of cortical endoplasmic reticulum networks and VAP27-1-enriched endoplasmic reticulum–plasma membrane contact sites

    PubMed Central

    Siao, Wei; Wang, Pengwei; Voigt, Boris; Hussey, Patrick J.; Baluska, Frantisek

    2016-01-01

    Arabidopsis synaptotagmin 1 (SYT1) is localized on the endoplasmic reticulum–plasma membrane (ER–PM) contact sites in leaf and root cells. The ER–PM localization of Arabidopsis SYT1 resembles that of the extended synaptotagmins (E-SYTs) in animal cells. In mammals, E-SYTs have been shown to regulate calcium signaling, lipid transfer, and endocytosis. Arabidopsis SYT1 was reported to be essential for maintaining cell integrity and virus movement. This study provides detailed insight into the subcellular localization of SYT1 and VAP27-1, another ER–PM-tethering protein. SYT1 and VAP27-1 were shown to be localized on distinct ER–PM contact sites. The VAP27-1-enriched ER–PM contact sites (V-EPCSs) were always in contact with the SYT1-enriched ER–PM contact sites (S-EPCSs). The V-EPCSs still existed in the leaf epidermal cells of the SYT1 null mutant; however, they were less stable than those in the wild type. The polygonal networks of cortical ER disassembled and the mobility of VAP27-1 protein on the ER–PM contact sites increased in leaf cells of the SYT1 null mutant. These results suggest that SYT1 is responsible for stabilizing the ER network and V-EPCSs. PMID:27811083

  12. Activation of a residual cortical network during painful stimulation in long-term postanoxic vegetative state: a 15O-H2O PET study.

    PubMed

    Kassubek, Jan; Juengling, Freimut D; Els, Thomas; Spreer, Joachim; Herpers, Martin; Krause, Thomas; Moser, Ernst; Lücking, Carl H

    2003-08-15

    Survivors of prolonged cerebral anoxia often remain in the persistent vegetative state (PVS). In this study, long-term PVS patients were investigated by 15O-H(2)O PET to analyze their central processing of pain. The study was approved by the local Ethics Committee, the experiments were performed in accordance with the Helsinki Declaration of 2000. Seven patients remaining in PVS of anoxic origin for a mean of 1.6 years (range 0.25-4 years) were investigated. We performed functional PET of the brain using 15O-labelled water during electrical nociceptive stimulation. Additionally, a brain metabolism study using 18F-fluorodeoxyglucose (FDG) PET and multi-sequence MRI (including a 3-D data set) were acquired in all patients. PET data were analyzed by means of Statistical Parametric Mapping (SPM99) and coregistered to a study-specific brain template. MRI and FDG PET showed severe cortical impairment at the structural and the functional level, that is, general atrophy of various degrees and a widespread significant hypometabolism, respectively. Pain-induced activation (hyperperfusion) was found in the posterior insula/secondary somatosensory cortex (SII), postcentral gyrus/primary somatosensory cortex (SI), and the cingulate cortex contralateral to the stimulus and in the posterior insula ipsilateral to the stimulus (P<0.05, small-volume-corrected). No additional areas of the complex pain-processing matrix were significantly activated. In conclusion, the regional activity found at the cortical level indicates that a residual pain-related cerebral network remains active in long-term PVS patients.

  13. Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease

    PubMed Central

    Nunez, Paul L.; Srinivasan, Ramesh

    2013-01-01

    The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628

  14. Category search speeds up face-selective fMRI responses in a non-hierarchical cortical face network.

    PubMed

    Jiang, Fang; Badler, Jeremy B; Righi, Giulia; Rossion, Bruno

    2015-05-01

    The human brain is extremely efficient at detecting faces in complex visual scenes, but the spatio-temporal dynamics of this remarkable ability, and how it is influenced by category-search, remain largely unknown. In the present study, human subjects were shown gradually-emerging images of faces or cars in visual scenes, while neural activity was recorded using functional magnetic resonance imaging (fMRI). Category search was manipulated by the instruction to indicate the presence of either a face or a car, in different blocks, as soon as an exemplar of the target category was detected in the visual scene. The category selectivity of most face-selective areas was enhanced when participants were instructed to report the presence of faces in gradually decreasing noise stimuli. Conversely, the same regions showed much less selectivity when participants were instructed instead to detect cars. When "face" was the target category, the fusiform face area (FFA) showed consistently earlier differentiation of face versus car stimuli than did the "occipital face area" (OFA). When "car" was the target category, only the FFA showed differentiation of face versus car stimuli. These observations provide further challenges for hierarchical models of cortical face processing and show that during gradual revealing of information, selective category-search may decrease the required amount of information, enhancing and speeding up category-selective responses in the human brain.

  15. An AKT3-FOXG1-Reelin Network Underlies Defective Migration in Human Focal Malformations of Cortical Development

    PubMed Central

    Baek, Seung Tae; Copeland, Brett; Yun, Eun-Jin; Kwon, Seok-Kyu; Guemez-Gamboa, Alicia; Schaffer, Ashleigh E.; Kim, Sangwoo; Kang, Hoon-Chul; Song, Saera; Mathern, Gary W.; Gleeson, Joseph G.

    2016-01-01

    Focal malformations of cortical development (FMCD) account for the majority of drug-resistant pediatric epilepsy. Postzygotic somatic mutations activating the PI3K-AKT-mTOR pathway are found in a wide range of brain diseases, including FMCD. It remains unclear how a mutation in a small fraction of cells can disrupt the architecture of the entire hemisphere. We show that, within human FMCD brain, cells showing activation of this pathway were enriched for the mutation. Introducing the FMCD mutation into mouse brain resulted in electrographic seizures and impaired hemispheric architecture. Mutation-expressing neural progenitors showed reelin misexpression, which led to a non-cell autonomous migration defect in neighboring cells, due at least in part to FOXG1-mediated de-repression of reelin transcription. Treatments aimed at blocking downstream AKT signaling or inactivating reelin restored migration. These findings suggest a central AKT-FOXG1-Reelin signaling pathway in FMCD, and support pathway inhibitors as potential treatments or therapies for some forms of focal epilepsy. PMID:26523971

  16. Primitive chain network simulations for asymmetric star polymers

    NASA Astrophysics Data System (ADS)

    Masubuchi, Yuichi; Yaoita, Takatoshi; Matsumiya, Yumi; Watanabe, Hiroshi

    2011-05-01

    For branched polymers, the curvilinear motion of the branch point along the backbone is a significant relaxation source but details of this motion have not been well understood. This study conducts multi-chain sliplink simulations to examine effects of the spatial fluctuation and curvilinear hopping of the branch point on the viscoelastic relaxation. The simulation is based on the primitive chain network model that allows the spatial fluctuations of sliplink and branch point and the chain sliding along the backbone according to the subchain tension, chemical potential gradients, drag force against medium, and random force. The sliplinks are created and/or disrupted through the motion of chain ends. The curvilinear hopping of the branch point along the backbone is allowed to occur when all sliplinks on a branched arm are lost. The simulations considering the fluctuation and the hopping of the branch point described well the viscoelastic data for symmetric and asymmetric star polymers with a parameter set common to the linear polymer. On the other hand, the simulations without the branch point motion predicted unreasonably slow relaxation for asymmetric star polymers. For asymmetric star polymers, further tests with and without the branch point hopping revealed that the hopping is much less important compared to the branch point fluctuation when the lengths of the short and long backbone arms are not very different and the waiting time for the branch point hopping (time for removal of all sliplinks on the short arm) is larger than the backbone relaxation time. Although this waiting time changes with the hopping condition, the above results suggest a significance of the branch point fluctuation in the actual relaxation of branch polymers.

  17. Satellite range delay simulator for a matrix-switched time division multiple-access network simulator

    NASA Technical Reports Server (NTRS)

    Nagy, Lawrence A.

    1989-01-01

    The Systems Integration, Test, and Evaluation (SITE) facility at NASA Lewis Research Center is presently configured as a satellite-switched time division multiple access (SS-TDMA) network simulator. The purpose of SITE is to demonstrate and evaluate advanced communication satellite technologies, presently embodied by POC components developed under NASA contracts in addition to other hardware, such as ground terminals, designed and built in-house at NASA Lewis. Each ground terminal in a satellite communications system will experience a different aspect of the satellite's motion due mainly to daily tidal effects and station keeping, hence a different duration and rate of variation in the range delay. As a result of this and other effects such as local oscillator instability, each ground terminal must constantly adjust its transmit burst timing so that data bursts from separate ground terminals arrive at the satellite in their assigned time slots, preventing overlap and keeping the system in synchronism. On the receiving end, ground terminals must synchronize their local clocks using reference transmissions received through the satellite link. A feature of the SITE facility is its capability to simulate the varying propagation delays and associated Doppler frequency shifts that the ground terminals in the network have to cope with. Delay is achieved by means of two NASA Lewis designed and built range delay simulator (RDS) systems, each independently controlled locally with front panel switches or remotely by an experiment control and monitor (EC/M) computer.

  18. Study and Simulation of Traffic Behavior in Cellular Network

    NASA Astrophysics Data System (ADS)

    Madhup, D. K.; Shrestha, C. L.; Sharma, R. K.

    2007-07-01

    Cellular radio systems accommodate a large number of users with a limited radio spectrum. The concept of trunking allows a large number of users to share the relatively small number of channels in a cell by providing access to each user, on demand, from a pool of available channels. Traffic engineering deals with provisioning of communication circuits in a given area for a number of subscribers with a required grade of service. Traffic in any cell depends upon the number of users, the average request rate and average call duration. Certain number of channels is required for the required GOS. To design an optimum capacity cellular system, traffic behavior on that system is important. The number of channel required can be estimated by using Erlang formula and Erlang table. Erlang table is not always useful to calculate the probability of blocking in various complex scenarios such as channel borrowing strategies. When the total number of channel available in a given cell are divided to serve partly for newly generated calls and partly for handover calls, and if they use dynamic channel assignment strategies like channel borrowing, then the probability of blocking can't be calculated from Erlang table. Simulation model of the behavior help us to determine the blocking and the channel utilization while using various channel assignment strategies. The title "Study and Simulation of Traffic Behavior in Cellular Network" entail the study of the blocking probability of traffic in cellular network for static channel assignment strategies and dynamic channel borrowing strategies through MATLAB programming language and graphic user interface (GUI). The result shows that the dynamic scheme can perform better than static maximizing the overall utilization of the circuits and minimizing the overall blocking.

  19. Nicotinic receptor activation in human cerebral cortical interneurons: a mechanism for inhibition and disinhibition of neuronal networks.

    PubMed

    Alkondon, M; Pereira, E F; Eisenberg, H M; Albuquerque, E X

    2000-01-01

    Cholinergic control of the activity of human cerebral cortical circuits has long been thought to be accounted for by the interaction of acetylcholine (ACh) with muscarinic receptors. Here we report the discovery of functional nicotinic receptors (nAChRs) in interneurons of the human cerebral cortex and discuss the physiological and clinical implications of these findings. The whole-cell mode of the patch-clamp technique was used to record responses triggered by U-tube application of the nonselective agonist ACh and of the alpha7-nAChR-selective agonist choline to interneurons visualized by means of infrared-assisted videomicroscopy in slices of the human cerebral cortex. Choline induced rapidly desensitizing whole-cell currents that, being sensitive to blockade by methyllycaconitine (MLA; 50 nM), were most likely subserved by an alpha7-like nAChR. In contrast, ACh evoked slowly decaying whole-cell currents that, being sensitive to blockade by dihydro-beta-erythroidine (DHbetaE; 10 microM), were most likely subserved by an alpha4beta2-like nAChR. Application of ACh (but not choline) to the slices also triggered GABAergic postsynaptic currents (PSCs). Evidence is provided that ACh-evoked PSCs are the result of activation of alpha4beta2-like nAChRs present in preterminal axon segments and/or in presynaptic terminals of interneurons. Thus, nAChRs can relay inhibitory and/or disinhibitory signals to pyramidal neurons and thereby modulate the activity of neuronal circuits in the human cerebral cortex. These mechanisms, which appear to be retained across species, can account for the involvement of nAChRs in cognitive functions and in certain neuropathological conditions.

  20. Task-dependent changes of motor cortical network excitability during precision grip compared to isolated finger contraction.

    PubMed

    Kouchtir-Devanne, Nezha; Capaday, Charles; Cassim, François; Derambure, Philippe; Devanne, Hervé

    2012-03-01

    The purpose of this study was to determine whether task-dependent differences in corticospinal pathway excitability occur in going from isolated contractions of the index finger to its coordinated activity with the thumb. Focal transcranial magnetic stimulation (TMS) was used to measure input-output (I/O) curves--a measure of corticospinal pathway excitability--of the contralateral first dorsal interosseus (FDI) muscle in 21 healthy subjects performing two isometric motor tasks: index abduction and precision grip. The level of FDI electromyographic (EMG) activity was kept constant across tasks. The amplitude of the FDI motor evoked potentials (MEPs) and the duration of FDI silent period (SP) were plotted against TMS stimulus intensity and fitted, respectively, to a Boltzmann sigmoidal function. The plateau level of the FDI MEP amplitude I/O curve increased by an average of 40% during the precision grip compared with index abduction. Likewise, the steepness of the curve, as measured by the value of the maximum slope, increased by nearly 70%. By contrast, all I/O curve parameters [plateau, stimulus intensity required to obtain 50% of maximum response (S(50)), and slope] of SP duration were similar between the two tasks. Short- and long-latency intracortical inhibitions (SICI and LICI, respectively) were also measured in each task. Both measures of inhibition decreased during precision grip compared with the isolated contraction. The results demonstrate that the motor cortical circuits controlling index and thumb muscles become functionally coupled when the muscles are used synergistically and this may be due, at least in part, to a decrease of intracortical inhibition and an increase of recurrent excitation.

  1. Simulating unsteady flow and sediment transport in vegetated channel network

    NASA Astrophysics Data System (ADS)

    Bai, Yang; Duan, Jennifer G.

    2014-07-01

    This paper presents a one-dimensional model for simulating flood routing and sediment transport over mobile alluvium in a vegetated channel network. The modified St. Venant equations together with the governing equations for suspended sediment and bed load transport were solved simultaneously to obtain flow properties and sediment transport rate. The Godunov-type finite volume method is employed to discretize the governing equations. Then, the Exner equation was solved for bed elevation change. Since sediment transport is non-equilibrium when bed is degrading or aggrading, a recovery coefficient for suspended sediment and an adaptation length for bed load transport were used to quantify the differences between equilibrium and non-equilibrium sediment transport rate. The influence of vegetation on floodplain and main channel was accounted for by adjusting resistance terms in the momentum equations for flow field. A procedure to separate the grain resistance from the total resistance was proposed and implemented to calculate sediment transport rate. The model was tested by a flume experiment case and an unprecedented flood event occurred in the Santa Cruz River, Tucson, Arizona, in July 2006. Simulated results of flow discharge and bed elevation changes showed satisfactory agreements with the measurements. The impacts of vegetation density on sediment transport and significance of non-equilibrium sediment transport model were discussed.

  2. On the continuous differentiability of inter-spike intervals of synaptically connected cortical spiking neurons in a neuronal network.

    PubMed

    Kumar, Gautam; Kothare, Mayuresh V

    2013-12-01

    We derive conditions for continuous differentiability of inter-spike intervals (ISIs) of spiking neurons with respect to parameters (decision variables) of an external stimulating input current that drives a recurrent network of synaptically connected neurons. The dynamical behavior of individual neurons is represented by a class of discontinuous single-neuron models. We report here that ISIs of neurons in the network are continuously differentiable with respect to decision variables if (1) a continuously differentiable trajectory of the membrane potential exists between consecutive action potentials with respect to time and decision variables and (2) the partial derivative of the membrane potential of spiking neurons with respect to time is not equal to the partial derivative of their firing threshold with respect to time at the time of action potentials. Our theoretical results are supported by showing fulfillment of these conditions for a class of known bidimensional spiking neuron models.

  3. The dorsal prefrontal and dorsal anterior cingulate cortices exert complementary network signatures during encoding and retrieval in associative memory.

    PubMed

    Woodcock, Eric A; White, Richard; Diwadkar, Vaibhav A

    2015-09-01

    Cognitive control includes processes that facilitate execution of effortful cognitive tasks, including associative memory. Regions implicated in cognitive control during associative memory include the dorsal prefrontal (dPFC) and dorsal anterior cingulate cortex (dACC). Here we investigated the relative degrees of network-related interactions originating in the dPFC and dACC during oscillating phases of associative memory: encoding and cued retrieval. Volunteers completed an established object-location associative memory paradigm during fMRI. Psychophysiological interactions modeled modulatory network interactions from the dPFC and dACC during memory encoding and retrieval. Results were evaluated in second level analyses of variance with seed region and memory process as factors. Each seed exerted differentiable modulatory effects during encoding and retrieval. The dACC exhibited greater modulation (than the dPFC) on the fusiform and parahippocampal gyrus during encoding, while the dPFC exhibited greater modulation (than the dACC) on the fusiform, hippocampus, dPFC and basal ganglia. During retrieval, the dPFC exhibited greater modulation (than the dACC) on the parahippocampal gyrus, hippocampus, superior parietal lobule, and dPFC. The most notable finding was a seed by process interaction indicating that the dACC and the dPFC exerted complementary modulatory control on the hippocampus during each of the associative memory processes. These results provide evidence for differentiable, yet complementary, control-related modulation by the dACC and dPFC, while establishing the primacy of dPFC in exerting network control during both associative memory phases. Our approach and findings are relevant for understanding basic processes in human memory and psychiatric disorders that impact associative memory-related networks.

  4. Not only … but also: REM sleep creates and NREM Stage 2 instantiates landmark junctions in cortical memory networks.

    PubMed

    Llewellyn, Sue; Hobson, J Allan

    2015-07-01

    This article argues both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep contribute to overnight episodic memory processes but their roles differ. Episodic memory may have evolved from memory for spatial navigation in animals and humans. Equally, mnemonic navigation in world and mental space may rely on fundamentally equivalent processes. Consequently, the basic spatial network characteristics of pathways which meet at omnidirectional nodes or junctions may be conserved in episodic brain networks. A pathway is formally identified with the unidirectional, sequential phases of an episodic memory. In contrast, the function of omnidirectional junctions is not well understood. In evolutionary terms, both animals and early humans undertook tours to a series of landmark junctions, to take advantage of resources (food, water and shelter), whilst trying to avoid predators. Such tours required memory for emotionally significant landmark resource-place-danger associations and the spatial relationships amongst these landmarks. In consequence, these tours may have driven the evolution of both spatial and episodic memory. The environment is dynamic. Resource-place associations are liable to shift and new resource-rich landmarks may be discovered, these changes may require re-wiring in neural networks. To realise these changes, REM may perform an associative, emotional encoding function between memory networks, engendering an omnidirectional landmark junction which is instantiated in the cortex during NREM Stage 2. In sum, REM may preplay associated elements of past episodes (rather than replay individual episodes), to engender an unconscious representation which can be used by the animal on approach to a landmark junction in wake.

  5. Spatio-temporal electrical stimuli shape behavior of an embodied cortical network in a goal-directed learning task

    PubMed Central

    Bakkum, Douglas J; Chao, Zenas C; Potter, Steve M

    2008-01-01

    We developed an adaptive training algorithm, whereby an in vitro neocortical network learned to modulate its dynamics and achieve pre-determined activity states within tens of minutes through the application of patterned training stimuli using a multi-electrode array. A priori knowledge of functional connectivity was not necessary. Instead, effective training sequences were continuously discovered and refined based on real-time feedback of performance. The short-term neural dynamics in response to training became engraved in the network, requiring progressively fewer training stimuli to achieve successful behavior in a movement task. After 2 h of training, plasticity remained significantly greater than the baseline for 80 min (p-value <0.01). Interestingly, a given sequence of effective training stimuli did not induce significant plasticity (p-value = 0.82) or desired behavior, when replayed to the network and no longer contingent on feedback. Our results encourage an in vivo investigation of how targeted multi-site artificial stimulation of the brain, contingent on the activity of the body or even of the brain itself could treat neurological disorders by gradually shaping functional connectivity. PMID:18714127

  6. Designing laboratory wind simulations using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Križan, Josip; Gašparac, Goran; Kozmar, Hrvoje; Antonić, Oleg; Grisogono, Branko

    2015-05-01

    While experiments in boundary layer wind tunnels remain to be a major research tool in wind engineering and environmental aerodynamics, designing the modeling hardware required for a proper atmospheric boundary layer (ABL) simulation can be costly and time consuming. Hence, possibilities are sought to speed-up this process and make it more time-efficient. In this study, two artificial neural networks (ANNs) are developed to determine an optimal design of the Counihan hardware, i.e., castellated barrier wall, vortex generators, and surface roughness, in order to simulate the ABL flow developing above urban, suburban, and rural terrains, as previous ANN models were created for one terrain type only. A standard procedure is used in developing those two ANNs in order to further enhance best-practice possibilities rather than to improve existing ANN designing methodology. In total, experimental results obtained using 23 different hardware setups are used when creating ANNs. In those tests, basic barrier height, barrier castellation height, spacing density, and height of surface roughness elements are the parameters that were varied to create satisfactory ABL simulations. The first ANN was used for the estimation of mean wind velocity, turbulent Reynolds stress, turbulence intensity, and length scales, while the second one was used for the estimation of the power spectral density of velocity fluctuations. This extensive set of studied flow and turbulence parameters is unmatched in comparison to the previous relevant studies, as it includes here turbulence intensity and power spectral density of velocity fluctuations in all three directions, as well as the Reynolds stress profiles and turbulence length scales. Modeling results agree well with experiments for all terrain types, particularly in the lower ABL within the height range of the most engineering structures, while exhibiting sensitivity to abrupt changes and data scattering in profiles of wind-tunnel results. The

  7. The Virtual Brain: a simulator of primate brain network dynamics

    PubMed Central

    Sanz Leon, Paula; Knock, Stuart A.; Woodman, M. Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

    2013-01-01

    We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. PMID:23781198

  8. The Virtual Brain: a simulator of primate brain network dynamics.

    PubMed

    Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

    2013-01-01

    We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.

  9. Simulating Issue Networks in Small Classes using the World Wide Web.

    ERIC Educational Resources Information Center

    Josefson, Jim; Casey, Kelly

    2000-01-01

    Provides background information on simulations and active learning. Discusses the use of simulations in political science courses. Describes a simulation exercise where students performed specific institutional role playing, simulating the workings of a single congressional issue network, based on the reauthorization of the Endangered Species Act.…

  10. Satellite-matrix-switched, time-division-multiple-access network simulator

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Andro, Monty; Nagy, Lawrence A.; Budinger, James M.; Shalkhauser, Mary JO

    1990-01-01

    A versatile experimental Ka-band network simulator has been implemented at the NASA Lewis Research Center to demonstrate and evaluate a satellite-matrix-switched, time-division-multiple-access (SMS-TDMA) network and to evaluate future digital ground terminals and radiofrequency (RF) components. The simulator was implemented by using proof-of-concept RF components developed under NASA contracts and digital ground terminal and link simulation hardware developed at Lewis. This simulator provides many unique capabilities such as satellite range delay and variation simulation and rain fade simulation. All network parameters (e.g., signal-to-noise ratio, satellite range variation rate, burst density, and rain fade) are controlled and monitored by a central computer. The simulator is presently configured as a three-ground-terminal SMS-TDMA network.

  11. Satellite-matrix-switched, time-division-multiple-access network simulator

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Andro, Monty; Nagy, Lawrence A.; Budinger, James M.; Shalkhauser, Mary JO

    1989-01-01

    A versatile experimental Ka-band network simulator has been implemented at the NASA Lewis Research Center to demonstrate and evaluate a satellite-matrix-switched, time-division-multiple-access (SMS-TDMA) network and to evaluate future digital ground terminals and radiofrequency (RF) components. The simulator was implemented by using proof-of-concept RF components developed under NASA contracts and digital ground terminal and link simulation hardware developed at Lewis. This simulator provides many unique capabilities such as satellite range delay and variation simulation and rain fade simulation. All network parameters (e.g., signal-to-noise ratio, satellite range variation rate, burst density, and rain fade) are controlled and monitored by a central computer. The simulator is presently configured as a three-ground-terminal SMS-TDMA network.

  12. Orchestration of “Presto” and “Largo” Synchrony in Up-Down Activity of Cortical Networks

    PubMed Central

    Gullo, Francesca; Mazzetti, Samanta; Maffezzoli, Andrea; Dossi, Elena; Lecchi, Marzia; Amadeo, Alida; Krajewski, Jeffrey; Wanke, Enzo

    2010-01-01

    It has been demonstrated using single-cell and multiunit electrophysiology in layer III entorhinal cortex and disinhibited hippocampal CA3 slices that the balancing of the up-down activity is characterized by both GABAA and GABAB mechanisms. Here we report novel results obtained using multi-electrode array (60 electrodes) simultaneous recordings from reverberating postnatal neocortical networks containing 19.2 ± 1.4% GABAergic neurons, typical of intact tissue. We observed that in each spontaneous active-state the total number of spikes in identified clusters of excitatory and inhibitory neurons is almost equal, thus suggesting a balanced average activity. Interestingly, in the active-state, the early phase is sustained by only 10% of the total spikes and the firing rate follows a sigmoidal regenerative mode up to peak at 35 ms with the number of excitatory spikes greater than inhibitory, therefore indicating an early unbalance. Concentration-response pharmacology of up- and down-state lifetimes in clusters of excitatory (n = 1067) and inhibitory (n = 305) cells suggests that, besides the GABAA and GABAB mechanisms, others such as GAT-1-mediated uptake, Ih, INaP and IM ion channel activity, robustly govern both up- and down-activity. Some drugs resulted to affect up- and/or down-states with different IC50s, providing evidence that various mechanisms are involved. These results should reinforce not only the role of synchrony in CNS networks, but also the recognized analogies between the Hodgkin–Huxley action potential and the population bursts as basic mechanisms for originating membrane excitability and CNS network synchronization, respectively. PMID:20461235

  13. Taming Wild Horses: The Need for Virtual Time-based Scheduling of VMs in Network Simulations

    SciTech Connect

    Yoginath, Srikanth B; Perumalla, Kalyan S; Henz, Brian J

    2012-01-01

    The next generation of scalable network simulators employ virtual machines (VMs) to act as high-fidelity models of traffic producer/consumer nodes in simulated networks. However, network simulations could be inaccurate if VMs are not scheduled according to virtual time, especially when many VMs are hosted per simulator core in a multi-core simulator environment. Since VMs are by default free-running, on the outset, it is not clear if, and to what extent, their untamed execution affects the results in simulated scenarios. Here, we provide the first quantitative basis for establishing the need for generalized virtual time scheduling of VMs in network simulators, based on an actual prototyped implementations. To exercise breadth, our system is tested with multiple disparate applications: (a) a set of message passing parallel programs, (b) a computer worm propagation phenomenon, and (c) a mobile ad-hoc wireless network simulation. We define and use error metrics and benchmarks in scaled tests to empirically report the poor match of traditional, fairness-based VM scheduling to VM-based network simulation, and also clearly show the better performance of our simulation-specific scheduler, with up to 64 VMs hosted on a 12-core simulator node.

  14. Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON.

    PubMed

    Lytton, William W; Seidenstein, Alexandra H; Dura-Bernal, Salvador; McDougal, Robert A; Schürmann, Felix; Hines, Michael L

    2016-10-01

    Large multiscale neuronal network simulations are of increasing value as more big data are gathered about brain wiring and organization under the auspices of a current major research initiative, such as Brain Research through Advancing Innovative Neurotechnologies. The development of these models requires new simulation technologies. We describe here the current use of the NEURON simulator with message passing interface (MPI) for simulation in the domain of moderately large networks on commonly available high-performance computers (HPCs). We discuss the basic layout of such simulations, including the methods of simulation setup, the run-time spike-passing paradigm, and postsimulation data storage and data management approaches. Using the Neuroscience Gateway, a portal for computational neuroscience that provides access to large HPCs, we benchmark simulations of neuronal networks of different sizes (500-100,000 cells), and using different numbers of nodes (1-256). We compare three types of networks, composed of either Izhikevich integrate-and-fire neurons (I&F), single-compartment Hodgkin-Huxley (HH) cells, or a hybrid network with half of each. Results show simulation run time increased approximately linearly with network size and decreased almost linearly with the number of nodes. Networks with I&F neurons were faster than HH networks, although differences were small since all tested cells were point neurons with a single compartment.

  15. Understanding the Dynamics of MOOC Discussion Forums with Simulation Investigation for Empirical Network Analysis (SIENA)

    ERIC Educational Resources Information Center

    Zhang, Jingjing; Skryabin, Maxim; Song, Xiongwei

    2016-01-01

    This study attempts to make inferences about the mechanisms that drive network change over time. It adopts simulation investigation for empirical network analysis to examine the patterns and evolution of relationships formed in the context of a massive open online course (MOOC) discussion forum. Four network effects--"homophily,"…

  16. Modeling the contributions of Ca2+ flows to spontaneous Ca2+ oscillations and cortical spreading depression-triggered Ca2+ waves in astrocyte networks.

    PubMed

    Li, Bing; Chen, Shangbin; Zeng, Shaoqun; Luo, Qingming; Li, Pengcheng

    2012-01-01

    Astrocytes participate in brain functions through Ca(2+) signals, including Ca(2+) waves and Ca(2+) oscillations. Currently the mechanisms of Ca(2+) signals in astrocytes are not fully clear. Here, we present a computational model to specify the relative contributions of different Ca(2+) flows between the extracellular space, the cytoplasm and the endoplasmic reticulum of astrocytes to the generation of spontaneous Ca(2+) oscillations (CASs) and cortical spreading depression (CSD)-triggered Ca(2+) waves (CSDCWs) in a one-dimensional astrocyte network. This model shows that CASs depend primarily on Ca(2+) released from internal stores of astrocytes, and CSDCWs depend mainly on voltage-gated Ca(2+) influx. It predicts that voltage-gated Ca(2+) influx is able to generate Ca(2+) waves during the process of CSD even after depleting internal Ca(2+) stores. Furthermore, the model investigates the interactions between CASs and CSDCWs and shows that the pass of CSDCWs suppresses CASs, whereas CASs do not prevent the generation of CSDCWs. This work quantitatively analyzes the generation of astrocytic Ca(2+) signals and indicates different mechanisms underlying CSDCWs and non-CSDCWs. Research on the different types of Ca(2+) signals might help to understand the ways by which astrocytes participate in information processing in brain functions.

  17. Early asymmetries in maternal transcript distribution associated with a cortical microtubule network and a polar body in the beetle Tribolium castaneum.

    PubMed

    Peel, Andrew D; Averof, Michalis

    2010-11-01

    The localization of maternal mRNAs during oogenesis plays a central role in axial specification in some insects. Here we describe a polar body-associated asymmetry in maternal transcript distribution in pre-blastoderm eggs of the beetle Tribolium castaneum. Since the position of the polar body marks the future dorsal side of the embryo, we have investigated whether this asymmetry in mRNA distribution plays a role in dorsal-ventral axis specification. Whilst our results suggest polar body-associated transcripts do not play a significant role in specifying the DV axis, at least during early embryogenesis, we do find that the polar body is closely associated with a cortical microtubule network (CMN), which may play a role in the localization of transcripts during oogenesis. Transcripts of the gene T.c.pangolin co-localize with the CMN at the time of their anterior localization during oogenesis and their anterior localization is disrupted by the microtubule-depolymerizing agent colcemid.

  18. Unified Approach to Modeling and Simulation of Space Communication Networks and