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Sample records for network cortical simulation

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

    PubMed

    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. PMID:17873432

  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. 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. PMID:19506707

  5. Cortical Control of Affective Networks

    PubMed Central

    Kumar, Sunil; Black, Sherilynn J.; Hultman, Rainbo; Szabo, Steven T.; DeMaio, Kristine D.; Du, Jeanette; Katz, Brittany M.; Feng, Guoping; Covington, Herbert E.; Dzirasa, Kafui

    2013-01-01

    Transcranial magnetic stimulation and deep brain stimulation have emerged as therapeutic modalities for treatment refractory depression; however, little remains known regarding the circuitry that mediates the therapeutic effect of these approaches. Here we show that direct optogenetic stimulation of prefrontal cortex (PFC) descending projection neurons in mice engineered to express Chr2 in layer V pyramidal neurons (Thy1–Chr2 mice) models an antidepressant-like effect in mice subjected to a forced-swim test. Furthermore, we show that this PFC stimulation induces a long-lasting suppression of anxiety-like behavior (but not conditioned social avoidance) in socially stressed Thy1–Chr2 mice: an effect that is observed >10 d after the last stimulation. Finally, we use optogenetic stimulation and multicircuit recording techniques concurrently in Thy1–Chr2 mice to demonstrate that activation of cortical projection neurons entrains neural oscillatory activity and drives synchrony across limbic brain areas that regulate affect. Importantly, these neural oscillatory changes directly correlate with the temporally precise activation and suppression of limbic unit activity. Together, our findings show that the direct activation of cortical projection systems is sufficient to modulate activity across networks underlying affective regulation. They also suggest that optogenetic stimulation of cortical projection systems may serve as a viable therapeutic strategy for treating affective disorders. PMID:23325249

  6. Linking cortical network synchrony and excitability

    PubMed Central

    Meisel, Christian

    2016-01-01

    ABSTRACT Theoretical approaches based on dynamical systems theory can provide useful frameworks to guide experiments and analysis techniques when investigating cortical network activity. The notion of phase transitions between qualitatively different kinds of network dynamics has been such a framework inspiring novel approaches to neurophysiological data analysis over the recent years. One particular intriguing hypothesis has been that cortical networks reside in the vicinity of a phase transition. Although the final verdict on this hypothesis is still out, trying to understand cortex dynamics from this viewpoint has recently led to interesting insights on cortical network function with relevance for clinical practice. PMID:27065159

  7. The ontogeny of the cortical language network.

    PubMed

    Skeide, Michael A; Friederici, Angela D

    2016-05-01

    Language-processing functions follow heterogeneous developmental trajectories. The human embryo can already distinguish vowels in utero, but grammatical complexity is usually not fully mastered until at least 7 years of age. Examining the current literature, we propose that the ontogeny of the cortical language network can be roughly subdivided into two main developmental stages. In the first stage extending over the first 3 years of life, the infant rapidly acquires bottom-up processing capacities, which are primarily implemented bilaterally in the temporal cortices. In the second stage continuing into adolescence, top-down processes emerge gradually with the increasing functional selectivity and structural connectivity of the left inferior frontal cortex.

  8. Multiscale Modeling of Cortical Neural Networks

    NASA Astrophysics Data System (ADS)

    Torben-Nielsen, Benjamin; Stiefel, Klaus M.

    2009-09-01

    In this study, we describe efforts at modeling the electrophysiological dynamics of cortical networks in a multi-scale manner. Specifically, we describe the implementation of a network model composed of simple single-compartmental neuron models, in which a single complex multi-compartmental model of a pyramidal neuron is embedded. The network is capable of generating Δ (2 Hz, observed during deep sleep states) and γ (40 Hz, observed during wakefulness) oscillations, which are then imposed onto the multi-compartmental model, thus providing realistic, dynamic boundary conditions. We furthermore discuss the challenges and chances involved in multi-scale modeling of neural function.

  9. 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

  10. Functional Calcium Imaging in Developing Cortical Networks

    PubMed Central

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

    2011-01-01

    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

  11. 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

  12. Anatomical imbalance between cortical networks in autism.

    PubMed

    Watanabe, Takamitsu; Rees, Geraint

    2016-01-01

    Influential psychological models of autism spectrum disorder (ASD) have proposed that this prevalent developmental disorder results from impairment of global (integrative) information processing and overload of local (sensory) information. However, little neuroanatomical evidence consistent with this account has been reported. Here, we examined relative grey matter volumes (rGMVs) between three cortical networks, how they changed with age, and their relationship with core symptomatology. Using public neuroimaging data of high-functioning ASD males and age-/sex-/IQ-matched controls, we first identified age-associated atypical increases in rGMVs of the regions of two sensory systems (auditory and visual networks), and an age-related aberrant decrease in rGMV of a task-control system (fronto-parietal network, FPN) in ASD children. While the enlarged rGMV of the auditory network in ASD adults was associated with the severity of autistic socio-communicational core symptom, that of the visual network was instead correlated with the severity of restricted and repetitive behaviours in ASD. Notably, the atypically decreased rGMV of FPN predicted both of the two core symptoms. These findings suggest that disproportionate undergrowth of a task-control system (FPN) may be a common anatomical basis for the two ASD core symptoms, and relative overgrowth of the two different sensory systems selectively compounds the distinct symptoms.

  13. Anatomical imbalance between cortical networks in autism

    PubMed Central

    Watanabe, Takamitsu; Rees, Geraint

    2016-01-01

    Influential psychological models of autism spectrum disorder (ASD) have proposed that this prevalent developmental disorder results from impairment of global (integrative) information processing and overload of local (sensory) information. However, little neuroanatomical evidence consistent with this account has been reported. Here, we examined relative grey matter volumes (rGMVs) between three cortical networks, how they changed with age, and their relationship with core symptomatology. Using public neuroimaging data of high-functioning ASD males and age-/sex-/IQ-matched controls, we first identified age-associated atypical increases in rGMVs of the regions of two sensory systems (auditory and visual networks), and an age-related aberrant decrease in rGMV of a task-control system (fronto-parietal network, FPN) in ASD children. While the enlarged rGMV of the auditory network in ASD adults was associated with the severity of autistic socio-communicational core symptom, that of the visual network was instead correlated with the severity of restricted and repetitive behaviours in ASD. Notably, the atypically decreased rGMV of FPN predicted both of the two core symptoms. These findings suggest that disproportionate undergrowth of a task-control system (FPN) may be a common anatomical basis for the two ASD core symptoms, and relative overgrowth of the two different sensory systems selectively compounds the distinct symptoms. PMID:27484308

  14. Anatomical imbalance between cortical networks in autism.

    PubMed

    Watanabe, Takamitsu; Rees, Geraint

    2016-01-01

    Influential psychological models of autism spectrum disorder (ASD) have proposed that this prevalent developmental disorder results from impairment of global (integrative) information processing and overload of local (sensory) information. However, little neuroanatomical evidence consistent with this account has been reported. Here, we examined relative grey matter volumes (rGMVs) between three cortical networks, how they changed with age, and their relationship with core symptomatology. Using public neuroimaging data of high-functioning ASD males and age-/sex-/IQ-matched controls, we first identified age-associated atypical increases in rGMVs of the regions of two sensory systems (auditory and visual networks), and an age-related aberrant decrease in rGMV of a task-control system (fronto-parietal network, FPN) in ASD children. While the enlarged rGMV of the auditory network in ASD adults was associated with the severity of autistic socio-communicational core symptom, that of the visual network was instead correlated with the severity of restricted and repetitive behaviours in ASD. Notably, the atypically decreased rGMV of FPN predicted both of the two core symptoms. These findings suggest that disproportionate undergrowth of a task-control system (FPN) may be a common anatomical basis for the two ASD core symptoms, and relative overgrowth of the two different sensory systems selectively compounds the distinct symptoms. PMID:27484308

  15. 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…

  16. Striatal GABAergic and cortical glutamatergic neurons mediate contrasting effects of cannabinoids on cortical network synchrony.

    PubMed

    Sales-Carbonell, Carola; Rueda-Orozco, Pavel E; Soria-Gómez, Edgar; Buzsáki, György; Marsicano, Giovanni; Robbe, David

    2013-01-01

    Activation of type 1 cannabinoid receptors (CB1R) decreases GABA and glutamate release in cortical and subcortical regions, with complex outcomes on cortical network activity. To date there have been few attempts to disentangle the region- and cell-specific mechanisms underlying the effects of cannabinoids on cortical network activity in vivo. Here we addressed this issue by combining in vivo electrophysiological recordings with local and systemic pharmacological manipulations in conditional mutant mice lacking CB1R expression in different neuronal populations. First we report that cannabinoids induce hypersynchronous thalamocortical oscillations while decreasing the amplitude of faster cortical oscillations. Then we demonstrate that CB1R at striatonigral synapses (basal ganglia direct pathway) mediate the thalamocortical hypersynchrony, whereas activation of CB1R expressed in cortical glutamatergic neurons decreases cortical synchrony. Finally we show that activation of CB1 expressed in cortical glutamatergic neurons limits the cannabinoid-induced thalamocortical hypersynchrony. By reporting that CB1R activations in cortical and subcortical regions have contrasting effects on cortical synchrony, our study bridges the gap between cellular and in vivo network effects of cannabinoids. Incidentally, the thalamocortical hypersynchrony we report suggests a potential mechanism to explain the sensory "high" experienced during recreational consumption of marijuana.

  17. Striatal GABAergic and cortical glutamatergic neurons mediate contrasting effects of cannabinoids on cortical network synchrony

    PubMed Central

    Sales-Carbonell, Carola; Rueda-Orozco, Pavel E.; Soria-Gómez, Edgar; Buzsáki, György; Marsicano, Giovanni; Robbe, David

    2013-01-01

    Activation of type 1 cannabinoid receptors (CB1R) decreases GABA and glutamate release in cortical and subcortical regions, with complex outcomes on cortical network activity. To date there have been few attempts to disentangle the region- and cell-specific mechanisms underlying the effects of cannabinoids on cortical network activity in vivo. Here we addressed this issue by combining in vivo electrophysiological recordings with local and systemic pharmacological manipulations in conditional mutant mice lacking CB1R expression in different neuronal populations. First we report that cannabinoids induce hypersynchronous thalamocortical oscillations while decreasing the amplitude of faster cortical oscillations. Then we demonstrate that CB1R at striatonigral synapses (basal ganglia direct pathway) mediate the thalamocortical hypersynchrony, whereas activation of CB1R expressed in cortical glutamatergic neurons decreases cortical synchrony. Finally we show that activation of CB1 expressed in cortical glutamatergic neurons limits the cannabinoid-induced thalamocortical hypersynchrony. By reporting that CB1R activations in cortical and subcortical regions have contrasting effects on cortical synchrony, our study bridges the gap between cellular and in vivo network effects of cannabinoids. Incidentally, the thalamocortical hypersynchrony we report suggests a potential mechanism to explain the sensory “high” experienced during recreational consumption of marijuana. PMID:23269835

  18. Resiliency of cortical neural networks against cascaded failures.

    PubMed

    Jalili, Mahdi

    2015-08-19

    Network tools have been extensively applied to study the properties of brain functional and anatomical networks. In this paper, resiliency of Caenorhabditis elegans cortical networks against cascaded failures is studied. To this end, directed network formed by chemical connections and undirected network formed by electrical couplings through gap junctions are considered. Furthermore, two types of C. elegans networks are studied: the whole cortical network of the hermaphrodite type and the network of the posterior cortex in male C. elegans. The results show that resiliency of hermaphrodite and male networks is different. The male cortical network of chemical synapses shows extensively weaker resiliency than the randomized counterparts, whereas there are some patchy differences for the gap junctions network. However, the chemical and electrical networks of hermaphrodite type show a completely different behavior. In this type, for a range of medium to large capacity parameter (load capacity of the nodes is proportional to their capacity parameter), the network of chemical connections has significantly less resiliency (P<0.001) than the randomized networks, whereas the network of gap junctions is more resilient (P<0.001) than the random ones. These results show different functionalities of chemical and electrical connections in the cortical networks of hermaphrodite C. elegans.

  19. Cortical network reorganization guided by sensory input features.

    PubMed

    Kilgard, Michael P; Pandya, Pritesh K; Engineer, Navzer D; Moucha, Raluca

    2002-12-01

    Sensory experience alters the functional organization of cortical networks. Previous studies using behavioral training motivated by aversive or rewarding stimuli have demonstrated that cortical plasticity is specific to salient inputs in the sensory environment. Sensory experience associated with electrical activation of the basal forebrain (BasF) generates similar input specific plasticity. By directly engaging plasticity mechanisms and avoiding extensive behavioral training, BasF stimulation makes it possible to efficiently explore how specific sensory features contribute to cortical plasticity. This review summarizes our observations that cortical networks employ a variety of strategies to improve the representation of the sensory environment. Different combinations of receptive-field, temporal, and spectrotemporal plasticity were generated in primary auditory cortex neurons depending on the pitch, modulation rate, and order of sounds paired with BasF stimulation. Simple tones led to map expansion, while modulated tones altered the maximum cortical following rate. Exposure to complex acoustic sequences led to the development of combination-sensitive responses. This remodeling of cortical response characteristics may reflect changes in intrinsic cellular mechanisms, synaptic efficacy, and local neuronal connectivity. The intricate relationship between the pattern of sensory activation and cortical plasticity suggests that network-level rules alter the functional organization of the cortex to generate the most behaviorally useful representation of the sensory environment.

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

    PubMed

    Zagha, Edward; Murray, John D; McCormick, David A

    2016-01-01

    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. 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.

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

    PubMed

    Zagha, Edward; Murray, John D; McCormick, David A

    2016-01-01

    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.

  3. 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

  4. An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

    PubMed Central

    Richert, Micah; Nageswaran, Jayram Moorkanikara; Dutt, Nikil; Krichmar, Jeffrey L.

    2011-01-01

    We have developed a spiking neural network simulator, which is both easy to use and computationally efficient, for the generation of large-scale computational neuroscience models. The simulator implements current or conductance based Izhikevich neuron networks, having spike-timing dependent plasticity and short-term plasticity. It uses a standard network construction interface. The simulator allows for execution on either GPUs or CPUs. The simulator, which is written in C/C++, allows for both fine grain and coarse grain specificity of a host of parameters. We demonstrate the ease of use and computational efficiency of this model by implementing a large-scale model of cortical areas V1, V4, and area MT. The complete model, which has 138,240 neurons and approximately 30 million synapses, runs in real-time on an off-the-shelf GPU. The simulator source code, as well as the source code for the cortical model examples is publicly available. PMID:22007166

  5. Graph analysis of cortical networks reveals complex anatomical communication substrate

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

    Sensory information entering the nervous system follows independent paths of processing such that specific features are individually detected. However, sensory perception, awareness, and cognition emerge from the combination of information. Here we have analyzed the corticocortical network of the cat, looking for the anatomical substrate which permits the simultaneous segregation and integration of information in the brain. We find that cortical communications are mainly governed by three topological factors of the underlying network: (i) a large density of connections, (ii) segregation of cortical areas into clusters, and (iii) the presence of highly connected hubs aiding the multisensory processing and integration. Statistical analysis of the shortest paths reveals that, while information is highly accessible to all cortical areas, the complexity of cortical information processing may arise from the rich and intricate alternative paths in which areas can influence each other.

  6. 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.

  7. 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

  8. 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

  9. Assessing cortical network properties using TMS-EEG.

    PubMed

    Rogasch, Nigel C; Fitzgerald, Paul B

    2013-07-01

    The past decade has seen significant developments in the concurrent use of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to directly assess cortical network properties such as excitability and connectivity in humans. New hardware solutions, improved EEG amplifier technology, and advanced data processing techniques have allowed substantial reduction of the TMS-induced artifact, which had previously rendered concurrent TMS-EEG impossible. Various physiological artifacts resulting from TMS have also been identified, and methods are being developed to either minimize or remove these sources of artifact. With these developments, TMS-EEG has unlocked regions of the cortex to researchers that were previously inaccessible to TMS. By recording the TMS-evoked response directly from the cortex, TMS-EEG provides information on the excitability, effective connectivity, and oscillatory tuning of a given cortical area, removing the need to infer such measurements from indirect measures. In the following review, we investigate the different online and offline methods for reducing artifacts in TMS-EEG recordings and the physiological information contained within the TMS-evoked cortical response. We then address the use of TMS-EEG to assess different cortical mechanisms such as cortical inhibition and neural plasticity, before briefly reviewing studies that have utilized TMS-EEG to explore cortical network properties at rest and during different functional brain states.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. Neural Synchrony in Cortical Networks: History, Concept and Current Status

    PubMed Central

    Uhlhaas, Peter J.; Pipa, Gordon; Lima, Bruss; Melloni, Lucia; Neuenschwander, Sergio; Nikolić, Danko; Singer, Wolf

    2009-01-01

    Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, the role of neural synchrony in cortical networks has been expanded to provide a general mechanism for the coordination of distributed neural activity patterns. In the current paper, we present an update of the status of this hypothesis through summarizing recent results from our laboratory that suggest important new insights regarding the mechanisms, function and relevance of this phenomenon. In the first part, we present recent results derived from animal experiments and mathematical simulations that provide novel explanations and mechanisms for zero and nero-zero phase lag synchronization. In the second part, we shall discuss the role of neural synchrony for expectancy during perceptual organization and its role in conscious experience. This will be followed by evidence that indicates that in addition to supporting conscious cognition, neural synchrony is abnormal in major brain disorders, such as schizophrenia and autism spectrum disorders. We conclude this paper with suggestions for further research as well as with critical issues that need to be addressed in future studies. PMID:19668703

  15. 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

  16. Cortical network models of impulse firing in the resting and active states predict cortical energetics.

    PubMed

    Bennett, Maxwell R; Farnell, Les; Gibson, William G; Lagopoulos, Jim

    2015-03-31

    Measurements of the cortical metabolic rate of glucose oxidation [CMR(glc(ox))] have provided a number of interesting and, in some cases, surprising observations. One is the decline in CMR(glc(ox)) during anesthesia and non-rapid eye movement (NREM) sleep, and another, the inverse relationship between the resting-state CMR(glc(ox)) and the transient following input from the thalamus. The recent establishment of a quantitative relationship between synaptic and action potential activity on the one hand and CMR(glc(ox)) on the other allows neural network models of such activity to probe for possible mechanistic explanations of these phenomena. We have carried out such investigations using cortical models consisting of networks of modules with excitatory and inhibitory neurons, each receiving excitatory inputs from outside the network in addition to intermodular connections. Modules may be taken as regions of cortical interest, the inputs from outside the network as arising from the thalamus, and the intermodular connections as long associational fibers. The model shows that the impulse frequency of different modules can differ from each other by less than 10%, consistent with the relatively uniform CMR(glc(ox)) observed across different regions of cortex. The model also shows that, if correlations of the average impulse rate between different modules decreases, there is a concomitant decrease in the average impulse rate in the modules, consistent with the observed drop in CMR(glc(ox)) in NREM sleep and under anesthesia. The model also explains why a transient thalamic input to sensory cortex gives rise to responses with amplitudes inversely dependent on the resting-state frequency, and therefore resting-state CMR(glc(ox)). PMID:25775588

  17. Qualia Could Arise from Information Processing in Local Cortical Networks

    PubMed Central

    Orpwood, Roger

    2013-01-01

    Re-entrant feedback, either within sensory cortex or arising from prefrontal areas, has been strongly linked to the emergence of consciousness, both in theoretical and experimental work. This idea, together with evidence for local micro-consciousness, suggests the generation of qualia could in some way result from local network activity under re-entrant activation. This paper explores the possibility by examining the processing of information by local cortical networks. It highlights the difference between the information structure (how the information is physically embodied), and the information message (what the information is about). It focuses on the network’s ability to recognize information structures amongst its inputs under conditions of extensive local feedback, and to then assign information messages to those structures. It is shown that if the re-entrant feedback enables the network to achieve an attractor state, then the message assigned in any given pass of information through the network is a representation of the message assigned in the previous pass-through of information. Based on this ability the paper argues that as information is repeatedly cycled through the network, the information message that is assigned evolves from a recognition of what the input structure is, to what it is like, to how it appears, to how it seems. It could enable individual networks to be the site of qualia generation. The paper goes on to show networks in cortical layers 2/3 and 5a have the connectivity required for the behavior proposed, and reviews some evidence for a link between such local cortical cyclic activity and conscious percepts. It concludes with some predictions based on the theory discussed. PMID:23504586

  18. Neural-Network Simulator

    NASA Technical Reports Server (NTRS)

    Mitchell, Paul H.

    1991-01-01

    F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

  19. Ultra-slow oscillations in cortical networks in vitro.

    PubMed

    Mok, S Y; Nadasdy, Z; Lim, Y M; Goh, S Y

    2012-03-29

    An ultra-slow oscillation (<0.01 Hz) in the network-wide activity of dissociated cortical networks is described in this article. This slow rhythm is characterized by the recurrence of clusters of large synchronized bursts of activity lasting approximately 1-3 min, separated by an almost equivalent interval of relatively smaller bursts. Such rhythmic activity was detected in cultures starting from the fourth week in vitro. Our analysis revealed that the propagation motifs of constituent bursts were strongly conserved across multiple oscillation cycles, and these motifs were more consistent at the electrode level compared with the neuronal level.

  20. Rational design of transcranial current stimulation (TCS) through mechanistic insights into cortical network dynamics.

    PubMed

    Fröhlich, Flavio; Schmidt, Stephen L

    2013-01-01

    Transcranial current stimulation (TCS) is a promising method of non-invasive brain stimulation to modulate cortical network dynamics. Preliminary studies have demonstrated the ability of TCS to enhance cognition and reduce symptoms in both neurological and psychiatric illnesses. Despite the encouraging results of these studies, the mechanisms by which TCS and endogenous network dynamics interact remain poorly understood. Here, we propose that the development of the next generation of TCS paradigms with increased efficacy requires such mechanistic understanding of how weak electric fields (EFs) imposed by TCS interact with the nonlinear dynamics of large-scale cortical networks. We highlight key recent advances in the study of the interaction dynamics between TCS and cortical network activity. In particular, we illustrate an interdisciplinary approach that bridges neurobiology and electrical engineering. We discuss the use of (1) hybrid biological-electronic experimental approaches to disentangle feedback interactions; (2) large-scale computer simulations for the study of weak global perturbations imposed by TCS; and (3) optogenetic manipulations informed by dynamic systems theory to probe network dynamics. Together, we here provide the foundation for the use of rational design for the development of the next generation of TCS neurotherapeutics. PMID:24324427

  1. 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

  2. Cortical Thinning and Altered Cortico-Cortical Structural Covariance of the Default Mode Network in Patients with Persistent Insomnia Symptoms

    PubMed Central

    Suh, Sooyeon; Kim, Hosung; Dang-Vu, Thien Thanh; Joo, Eunyeon; Shin, Chol

    2016-01-01

    Study Objectives: Recent studies have suggested that structural abnormalities in insomnia may be linked with alterations in the default-mode network (DMN). This study compared cortical thickness and structural connectivity linked to the DMN in patients with persistent insomnia (PI) and good sleepers (GS). Methods: The current study used a clinical subsample from the longitudinal community-based Korean Genome and Epidemiology Study (KoGES). Cortical thickness and structural connectivity linked to the DMN in patients with persistent insomnia symptoms (PIS; n = 57) were compared to good sleepers (GS; n = 40). All participants underwent MRI acquisition. Based on literature review, we selected cortical regions corresponding to the DMN. A seed-based structural covariance analysis measured cortical thickness correlation between each seed region of the DMN and other cortical areas. Association of cortical thickness and covariance with sleep quality and neuropsychological assessments were further assessed. Results: Compared to GS, cortical thinning was found in PIS in the anterior cingulate cortex, precentral cortex, and lateral prefrontal cortex. Decreased structural connectivity between anterior and posterior regions of the DMN was observed in the PIS group. Decreased structural covariance within the DMN was associated with higher PSQI scores. Cortical thinning in the lateral frontal lobe was related to poor performance in executive function in PIS. Conclusion: Disrupted structural covariance network in PIS might reflect malfunctioning of antero-posterior disconnection of the DMN during the wake to sleep transition that is commonly found during normal sleep. The observed structural network alteration may further implicate commonly observed sustained sleep difficulties and cognitive impairment in insomnia. Citation: Suh S, Kim H, Dang-Vu TT, Joo E, Shin C. Cortical thinning and altered cortico-cortical structural covariance of the default mode network in patients with

  3. 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. PMID:19922291

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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. PMID:17166525

  9. 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.

  10. 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

  11. Columnar architecture improves noise robustness in a model cortical network.

    PubMed

    Bush, Paul C; Mainen, Zachary F

    2015-01-01

    Cortical columnar architecture was discovered decades ago yet there is no agreed upon explanation for its function. Indeed, some have suggested that it has no function, it is simply an epiphenomenon of developmental processes. To investigate this problem we have constructed a computer model of one square millimeter of layer 2/3 of the primary visual cortex (V1) of the cat. Model cells are connected according to data from recent paired cell studies, in particular the connection probability between pyramidal cells is inversely proportional both to the distance separating the cells and to the distance between the preferred parameters (features) of the cells. We find that these constraints, together with a columnar architecture, produce more tightly clustered populations of cells when compared to the random architecture seen in, for example, rodents. This causes the columnar network to converge more quickly and accurately on the pattern representing a particular stimulus in the presence of noise, suggesting that columnar connectivity functions to improve pattern recognition in cortical circuits. The model also suggests that synaptic failure, a phenomenon exhibited by weak synapses, may conserve metabolic resources by reducing transmitter release at these connections that do not contribute to network function.

  12. Taming desynchronized bursting with delays in the Macaque cortical network

    NASA Astrophysics Data System (ADS)

    Wang, Qing-Yun; Murks, Aleksandra; Perc, Matjaž; Lu, Qi-Shao

    2011-04-01

    Inhibitory coupled bursting Hindmarsh—Rose neurons are considered as constitutive units of the Macaque cortical network. In the absence of information transmission delay the bursting activity is desynchronized, giving rise to spatiotemporally disordered dynamics. This paper shows that the introduction of finite delays can lead to the synchronization of bursting and thus to the emergence of coherent propagating fronts of excitation in the space-time domain. Moreover, it shows that the type of synchronous bursting is uniquely determined by the delay length, with the transitions from one type to the other occurring in a step-like manner depending on the delay. Interestingly, as the delay is tuned close to the transition points, the synchronization deteriorates, which implies the coexistence of different bursting attractors. These phenomena can be observed by different but fixed coupling strengths, thus indicating a new role for information transmission delays in realistic neuronal networks.

  13. Population spikes in cortical networks during different functional states

    PubMed Central

    Mark, Shirley; Tsodyks, Misha

    2012-01-01

    Brain computational challenges vary between behavioral states. Engaged animals react according to incoming sensory information, while in relaxed and sleeping states consolidation of the learned information is believed to take place. Different states are characterized by different forms of cortical activity. We study a possible neuronal mechanism for generating these diverse dynamics and suggest their possible functional significance. Previous studies demonstrated that brief synchronized increase in a neural firing [Population Spikes (PS)] can be generated in homogenous recurrent neural networks with short-term synaptic depression (STD). Here we consider more realistic networks with clustered architecture. We show that the level of synchronization in neural activity can be controlled smoothly by network parameters. The network shifts from asynchronous activity to a regime in which clusters synchronized separately, then, the synchronization between the clusters increases gradually to fully synchronized state. We examine the effects of different synchrony levels on the transmission of information by the network. We find that the regime of intermediate synchronization is preferential for the flow of information between sparsely connected areas. Based on these results, we suggest that the regime of intermediate synchronization corresponds to engaged behavioral state of the animal, while global synchronization is exhibited during relaxed and sleeping states. PMID:22811663

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

    PubMed

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

    2009-12-01

    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.

  15. Slow oscillations during sleep coordinate interregional communication in cortical networks.

    PubMed

    Cox, Roy; van Driel, Joram; de Boer, Marieke; Talamini, Lucia M

    2014-12-10

    Large-amplitude sleep slow oscillations group faster neuronal oscillations and are of functional relevance for memory performance. However, relatively little is known about the impact of slow oscillations on functionally coupled networks. Here, we provide a comprehensive view on how human slow oscillatory dynamics influence various measures of brain processing. We demonstrate that slow oscillations coordinate interregional cortical communication, as assessed by phase synchrony in the sleep spindle frequency range and cross-frequency coupling between spindle and beta activity. Furthermore, we show that the organizing role of slow oscillations is restricted to circumscribed topographical areas. These findings add importantly to our basic understanding of the orchestrating role of slow oscillations. In addition, they are of considerable relevance for accounts of sleep-dependent memory reprocessing and consolidation. PMID:25505340

  16. [In vivo investigation of human brain networks by using cortico-cortical evoked potentials].

    PubMed

    Matsumoto, Riki; Kunieda, Takeharu; Ikeda, Akio

    2012-09-01

    A better understanding of seizure networks and the mechanisms underlying human higher cortical functions requires a detailed knowledge of neuronal connectivity. As it relates to higher cortical functions, such as language, in humans, studies performed in nonhuman primates are less relevant. By using subdural electrodes implanted for presurgical evaluation, we developed an in vivo electrical tract-tracing technique of cortico-cortical evoked potentials (CCEPs). Cortico-cortical connections could be traced by applying repetitive single-pulse electrical stimuli to a part of the cortices and recording evoked cortical potentials from adjacent and remote cortical regions by averaging electrocorticogram time-locked to stimulus onset. This technique has contributed to the understanding of human cortico-cortical networks involved in higher brain functions, such as language, praxis, and higher motor control. Establishing a CCEP connectivity map in the MNI standard space is also of academic importance, since a standardized CCEP connectivity map would provide a substantial reference for noninvasive network analyses. In addition to its importance in basic systems neuroscience, this method, in combination with conventional cortical mapping, could be used to clinically map functional brain systems by tracking cortico-cortical connections among functional cortical regions in individual patients. This approach may help identify the cortico-cortical network of a given function within the context of pathology and any resultant plasticity of brain systems. In relation to epileptogenicity, as CCEPs can be used as a measure of regional cortical excitability, stimulating the epileptic focus and recording CCEPs in adjacent areas could help evaluate cortical excitability at and around the focus.

  17. Dynamics of myosin II organization into cortical contractile networks and fibers

    NASA Astrophysics Data System (ADS)

    Nie, Wei; Wei, Ming-Tzo; Ou-Yang, Daniel; Jedlicka, Sabrina; Vavylonis, Dimitrios

    2014-03-01

    The morphology of adhered cells critically depends on the formation of a contractile meshwork of parallel and cross-linked stress fibers along the contacting surface. The motor activity and mini-filament assembly of non-muscle myosin II is an important component of cell-level cytoskeletal remodeling during mechanosensing. To monitor the dynamics of myosin II, we used confocal microscopy to image cultured HeLa cells that stably express myosin regulatory light chain tagged with GFP (MRLC-GFP). MRLC-GFP was monitored in time-lapse movies at steady state and during the response of cells to varying concentrations of blebbistatin which disrupts actomyosin stress fibers. Using image correlation spectroscopy analysis, we quantified the kinetics of disassembly and reassembly of actomyosin networks and compared them to studies by other groups. This analysis suggested that the following processes contribute to the assembly of cortical actomyosin into fibers: random myosin mini-filament assembly and disassembly along the cortex; myosin mini-filament aligning and contraction; stabilization of cortical myosin upon increasing contractile tension. We developed simple numerical simulations that include those processes. The results of simulations of cells at steady state and in response to blebbistatin capture some of the main features observed in the experiments. This study provides a framework to help interpret how different cortical myosin remodeling kinetics may contribute to different cell shape and rigidity depending on substrate stiffness.

  18. Can the activities of the large scale cortical network be expressed by neural energy? A brief review.

    PubMed

    Wang, Rubin; Zhu, Yating

    2016-02-01

    This paper mainly discusses and summarize that the changes of biological energy in the brain can be expressed by the biophysical energy we constructed. Different from the electrochemical energy, the biophysical energy proposed in the paper not only can be used to simulate the activity of neurons but also be used to simulate the neural activity of large scale cortical networks, so that the scientific nature of the neural energy coding was discussed.

  19. 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.

  20. Coarse-grained reduction and analysis of a network model of cortical response: I. Drifting grating stimuli.

    PubMed

    Shelley, Michael; McLaughlin, David

    2002-01-01

    We present a reduction of a large-scale network model of visual cortex developed by McLaughlin, Shapley, Shelley, and Wielaard. The reduction is from many integrate-and-fire neurons to a spatially coarse-grained system for firing rates of neuronal subpopulations. It accounts explicitly for spatially varying architecture, ordered cortical maps (such as orientation preference) that vary regularly across the cortical layer, and disordered cortical maps (such as spatial phase preference or stochastic input conductances) that may vary widely from cortical neuron to cortical neuron. The result of the reduction is a set of nonlinear spatiotemporal integral equations for "phase-averaged" firing rates of neuronal subpopulations across the model cortex, derived asymptotically from the full model without the addition of any extra phenomological constants. This reduced system is used to study the response of the model to drifting grating stimuli-where it is shown to be useful for numerical investigations that reproduce, at far less computational cost, the salient features of the point-neuron network and for analytical investigations that unveil cortical mechanisms behind the responses observed in the simulations of the large-scale computational model. For example, the reduced equations clearly show (1) phase averaging as the source of the time-invariance of cortico-cortical conductances, (2) the mechanisms in the model for higher firing rates and better orientation selectivity of simple cells which are near pinwheel centers, (3) the effects of the length-scales of cortico-cortical coupling, and (4) the role of noise in improving the contrast invariance of orientation selectivity. PMID:12053156

  1. Age-related alterations in the modular organization of structural cortical network by using cortical thickness from MRI.

    PubMed

    Chen, Zhang J; He, Yong; Rosa-Neto, Pedro; Gong, Gaolang; Evans, Alan C

    2011-05-01

    Normal aging is accompanied by various cognitive functional declines. Recent studies have revealed disruptions in the coordination of large-scale functional brain networks such as the default mode network in advanced aging. However, organizational alterations of the structural brain network at the system level in aging are still poorly understood. Here, using cortical thickness, we investigated the modular organization of the cortical structural networks in 102 young and 97 normal aging adults. Brain networks for both cohorts displayed a modular organization overlapping with functional domains such as executive and auditory/language processing. However, compared with the modular organization of young adults, the aging group demonstrated a significantly reduced modularity that might be indicative of reduced functional segregation in the aging brain. More importantly, the aging brain network exhibited reduced intra-/inter-module connectivity in modules corresponding to the executive function and the default mode network of young adults, which might be associated with the decline of cognitive functions in aging. Finally, we observed age-associated alterations in the regional characterization in terms of their intra/inter-module connectivity. Our results indicate that aging is associated with an altered modular organization in the structural brain networks and provide new evidence for disrupted integrity in the large-scale brain networks that underlie cognition.

  2. Oscillations in large-scale cortical networks: map-based model.

    PubMed

    Rulkov, N F; Timofeev, I; Bazhenov, M

    2004-01-01

    We develop a new computationally efficient approach for the analysis of complex large-scale neurobiological networks. Its key element is the use of a new phenomenological model of a neuron capable of replicating important spike pattern characteristics and designed in the form of a system of difference equations (a map). We developed a set of map-based models that replicate spiking activity of cortical fast spiking, regular spiking and intrinsically bursting neurons. Interconnected with synaptic currents these model neurons demonstrated responses very similar to those found with Hodgkin-Huxley models and in experiments. We illustrate the efficacy of this approach in simulations of one- and two-dimensional cortical network models consisting of regular spiking neurons and fast spiking interneurons to model sleep and activated states of the thalamocortical system. Our study suggests that map-based models can be widely used for large-scale simulations and that such models are especially useful for tasks where the modeling of specific firing patterns of different cell classes is important. PMID:15306740

  3. The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network Model

    PubMed Central

    Potjans, Tobias C.; Diesmann, Markus

    2014-01-01

    In the past decade, the cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. In parallel, modeling has been established as a tool to relate network structure to activity dynamics. While available comprehensive connectivity maps ( Thomson, West, et al. 2002; Binzegger et al. 2004) have been used in various computational studies, prominent features of the simulated activity such as the spontaneous firing rates do not match the experimental findings. Here, we analyze the properties of these maps to compile an integrated connectivity map, which additionally incorporates insights on the specific selection of target types. Based on this integrated map, we build a full-scale spiking network model of the local cortical microcircuit. The simulated spontaneous activity is asynchronous irregular and cell-type specific firing rates are in agreement with in vivo recordings in awake animals, including the low rate of layer 2/3 excitatory cells. The interplay of excitation and inhibition captures the flow of activity through cortical layers after transient thalamic stimulation. In conclusion, the integration of a large body of the available connectivity data enables us to expose the dynamical consequences of the cortical microcircuitry. PMID:23203991

  4. Numerical Simulation of Shock Wave Propagation in Fractured Cortical Bone

    NASA Astrophysics Data System (ADS)

    Padilla, Frédéric; Cleveland, Robin

    2009-04-01

    Shock waves (SW) are considered a promising method to treat bone non unions, but the associated mechanisms of action are not well understood. In this study, numerical simulations are used to quantify the stresses induced by SWs in cortical bone tissue. We use a 3D FDTD code to solve the linear lossless equations that describe wave propagation in solids and fluids. A 3D model of a fractured rat femur was obtained from micro-CT data with a resolution of 32 μm. The bone was subject to a plane SW pulse with a peak positive pressure of 40 MPa and peak negative pressure of -8 MPa. During the simulations the principal tensile stress and maximum shear stress were tracked throughout the bone. It was found that the simulated stresses in a transverse plane relative to the bone axis may reach values higher than the tensile and shear strength of the bone tissue (around 50 MPa). These results suggest that the stresses induced by the SW may be large enough to initiate local micro-fractures, which may in turn trigger the start of bone healing for the case of a non union.

  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

    Poggi, Giulia; Boretius, Susann; Möbius, Wiebke; Moschny, Nicole; Baudewig, Jürgen; Ruhwedel, Torben; Hassouna, Imam; Wieser, Georg L; Werner, Hauke B; Goebbels, Sandra; Nave, Klaus-Armin; Ehrenreich, Hannelore

    2016-11-01

    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. 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.

  9. 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.

  10. 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

  11. The strength of weak connections in the macaque cortico-cortical network.

    PubMed

    Goulas, Alexandros; Schaefer, Alexander; Margulies, Daniel S

    2015-09-01

    Examination of the cortico-cortical network of mammals has unraveled key topological features and their role in the function of the healthy and diseased brain. Recent findings from social and biological networks pinpoint the significant role of weak connections in network coherence and mediation of information from segregated parts of the network. In the current study, inspired by such findings and proposed architectures pertaining to social networks, we examine the structure of weak connections in the macaque cortico-cortical network by employing a tract-tracing dataset. We demonstrate that the cortico-cortical connections as a whole, as well as connections between segregated communities of brain areas, comply with the architecture suggested by the so-called strength-of-weak-ties hypothesis. However, we find that the wiring of these connections is not optimal with respect to the aforementioned architecture. This configuration is not attributable to a trade-off with factors known to constrain brain wiring, i.e., wiring cost and efficiency. Lastly, weak connections, but not strong ones, appear important for network cohesion. Our findings relate a topological property to the strength of cortico-cortical connections, highlight the prominent role of weak connections in the cortico-cortical structural network and pinpoint their potential functional significance. These findings suggest that certain neuroimaging studies, despite methodological challenges, should explicitly take them into account and not treat them as negligible. PMID:25035063

  12. Cortical Surface-Based Construction of Individual Structural Network with Application to Early Brain Development Study

    PubMed Central

    Meng, Yu; Li, Gang; Lin, Weili; Gilmore, John H.; Shen, Dinggang

    2016-01-01

    Analysis of anatomical covariance for cortex morphology in individual subjects plays an important role in the study of human brains. However, the approaches for constructing individual structural networks have not been well developed yet. Existing methods based on patch-wise image intensity similarity suffer from several major drawbacks, i.e., 1) violation of cortical topological properties, 2) sensitivity to intensity heterogeneity, and 3) influence by patch size heterogeneity. To overcome these limitations, this paper presents a novel cortical surface-based method for constructing individual structural networks. Specifically, our method first maps the cortical surfaces onto a standard spherical surface atlas and then uniformly samples vertices on the spherical surface as the nodes of the networks. The similarity between any two nodes is computed based on the biologically-meaningful cortical attributes (e.g., cortical thickness) in the spherical neighborhood of their sampled vertices. The connection between any two nodes is established only if the similarity is larger than a user-specified threshold. Through leveraging spherical cortical surface patches, our method generates biologically-meaningful individual networks that are comparable across ages and subjects. The proposed method has been applied to construct cortical-thickness networks for 73 healthy infants, with each infant having two MRI scans at 0 and 1 year of age. The constructed networks during the two ages were compared using various network metrics, such as degree, clustering coefficient, shortest path length, small world property, global efficiency, and local efficiency. Experimental results demonstrate that our method can effectively construct individual structural networks and reveal meaningful patterns in early brain development. PMID:27169140

  13. Representation of somatosensory inputs within the cortical autonomic network.

    PubMed

    Goswami, Ruma; Frances, Maria Fernanda; Shoemaker, J Kevin

    2011-01-15

    Regions of the cortical autonomic network (CAN) are activated during muscle contraction. However, it is not known to what extent CAN activation patterns reflect muscle sensory inputs, top-down signals from the motor cortex, and/or motor drive to cardiovascular structures. The present study explored the functional representation of somatosensory afferent input within the CAN with an a priori interest in the insula and ventral medial prefrontal cortex (vMPFC) (n=12). Heart rate (HR) and functional MRI data were acquired during 1) 30s periods of electrical stimulation of the wrist flexors at sub-motor (SUB; Type I,II afferents) and 2) motor thresholds (MOT; Type I,II,III afferents), 3) volitional wrist flexion at 5% maximal voluntary contraction (MVC) to match the MOT tension (VOL5%), and 4) volitional handgrip at 35% MVC to elicit tachycardia (VOL35%). Compared with rest, HR did not change during SUB, MOT, or VOL5% but increased during VOL35% (p<0.001). High frequency HR variability was 29.42±18.87 ms(2) (mean±S.D.) at rest and 39.85±27.60 ms(2) during SUB (p=0.06). High frequency HR variability was decreased during VOL35% compared to rest (p≤0.005). SUB increased activity in the bilateral posterior insula, vMPFC, subgenual anterior cingulate cortex (ACC), mid-cingulate cortex (MCC), and posterior cingulate cortex. MOT increased activity in the left posterior insula and MCC. During VOL5%, activity increased in the right anterior-mid insula. VOL35% was associated with activity in the bilateral insula as well as vMPFC and subgenual ACC deactivation. These data suggest that the left posterior insula processes sensory input from muscle during passive conditions and specifically that Type I and/or II muscle afferent stimulation during SUB impacts the vMPFC and/or subgenual ACC, regions believed to be involved in brain default mode and parasympathetic activity. PMID:20884359

  14. 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

  15. 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

  16. 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

  17. Traumatic Brain Injury Increases Cortical Glutamate Network Activity by Compromising GABAergic Control

    PubMed Central

    Cantu, David; Walker, Kendall; Andresen, Lauren; Taylor-Weiner, Amaro; Hampton, David; Tesco, Giuseppina; Dulla, Chris G.

    2015-01-01

    Traumatic brain injury (TBI) is a major risk factor for developing pharmaco-resistant epilepsy. Although disruptions in brain circuitry are associated with TBI, the precise mechanisms by which brain injury leads to epileptiform network activity is unknown. Using controlled cortical impact (CCI) as a model of TBI, we examined how cortical excitability and glutamatergic signaling was altered following injury. We optically mapped cortical glutamate signaling using FRET-based glutamate biosensors, while simultaneously recording cortical field potentials in acute brain slices 2–4 weeks following CCI. Cortical electrical stimulation evoked polyphasic, epileptiform field potentials and disrupted the input–output relationship in deep layers of CCI-injured cortex. High-speed glutamate biosensor imaging showed that glutamate signaling was significantly increased in the injured cortex. Elevated glutamate responses correlated with epileptiform activity, were highest directly adjacent to the injury, and spread via deep cortical layers. Immunoreactivity for markers of GABAergic interneurons were significantly decreased throughout CCI cortex. Lastly, spontaneous inhibitory postsynaptic current frequency decreased and spontaneous excitatory postsynaptic current increased after CCI injury. Our results suggest that specific cortical neuronal microcircuits may initiate and facilitate the spread of epileptiform activity following TBI. Increased glutamatergic signaling due to loss of GABAergic control may provide a mechanism by which TBI can give rise to post-traumatic epilepsy. PMID:24610117

  18. Decreased centrality of cortical volume covariance networks in autism spectrum disorders.

    PubMed

    Balardin, Joana Bisol; Comfort, William Edgar; Daly, Eileen; Murphy, Clodagh; Andrews, Derek; Murphy, Declan G M; Ecker, Christine; Sato, João Ricardo

    2015-10-01

    Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions characterized by atypical structural and functional brain connectivity. Complex network analysis has been mainly used to describe altered network-level organization for functional systems and white matter tracts in ASD. However, atypical functional and structural connectivity are likely to be also linked to abnormal development of the correlated structure of cortical gray matter. Such covariations of gray matter are particularly well suited to the investigation of the complex cortical pathology of ASD, which is not confined to isolated brain regions but instead acts at the systems level. In this study, we examined network centrality properties of gray matter networks in adults with ASD (n = 84) and neurotypical controls (n = 84) using graph theoretical analysis. We derived a structural covariance network for each group using interregional correlation matrices of cortical volumes extracted from a surface-based parcellation scheme containing 68 cortical regions. Differences between groups in closeness network centrality measures were evaluated using permutation testing. We identified several brain regions in the medial frontal, parietal and temporo-occipital cortices with reductions in closeness centrality in ASD compared to controls. We also found an association between an increased number of autistic traits and reduced centrality of visual nodes in neurotypicals. Our study shows that ASD are accompanied by atypical organization of structural covariance networks by means of a decreased centrality of regions relevant for social and sensorimotor processing. These findings provide further evidence for the altered network-level connectivity model of ASD. PMID:26343606

  19. Decreased centrality of cortical volume covariance networks in autism spectrum disorders.

    PubMed

    Balardin, Joana Bisol; Comfort, William Edgar; Daly, Eileen; Murphy, Clodagh; Andrews, Derek; Murphy, Declan G M; Ecker, Christine; Sato, João Ricardo

    2015-10-01

    Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions characterized by atypical structural and functional brain connectivity. Complex network analysis has been mainly used to describe altered network-level organization for functional systems and white matter tracts in ASD. However, atypical functional and structural connectivity are likely to be also linked to abnormal development of the correlated structure of cortical gray matter. Such covariations of gray matter are particularly well suited to the investigation of the complex cortical pathology of ASD, which is not confined to isolated brain regions but instead acts at the systems level. In this study, we examined network centrality properties of gray matter networks in adults with ASD (n = 84) and neurotypical controls (n = 84) using graph theoretical analysis. We derived a structural covariance network for each group using interregional correlation matrices of cortical volumes extracted from a surface-based parcellation scheme containing 68 cortical regions. Differences between groups in closeness network centrality measures were evaluated using permutation testing. We identified several brain regions in the medial frontal, parietal and temporo-occipital cortices with reductions in closeness centrality in ASD compared to controls. We also found an association between an increased number of autistic traits and reduced centrality of visual nodes in neurotypicals. Our study shows that ASD are accompanied by atypical organization of structural covariance networks by means of a decreased centrality of regions relevant for social and sensorimotor processing. These findings provide further evidence for the altered network-level connectivity model of ASD.

  20. Topological Properties of Large-Scale Cortical Networks Based on Multiple Morphological Features in Amnestic Mild Cognitive Impairment

    PubMed Central

    Li, Qiongling; Li, Xinwei; Wang, Xuetong; Li, Yuxia; Li, Kuncheng; Yu, Yang; Yin, Changhao; Li, Shuyu; Han, Ying

    2016-01-01

    Previous studies have demonstrated that amnestic mild cognitive impairment (aMCI) has disrupted properties of large-scale cortical networks based on cortical thickness and gray matter volume. However, it is largely unknown whether the topological properties of cortical networks based on geometric measures (i.e., sulcal depth, curvature, and metric distortion) change in aMCI patients compared with normal controls because these geometric features of cerebral cortex may be related to its intrinsic connectivity. Here, we compare properties in cortical networks constructed by six different morphological features in 36 aMCI participants and 36 normal controls. Six cortical features (3 volumetric and 3 geometric features) were extracted for each participant, and brain abnormities in aMCI were identified by cortical network based on graph theory method. All the cortical networks showed small-world properties. Regions showing significant differences mainly located in the medial temporal lobe and supramarginal and right inferior parietal lobe. In addition, we also found that the cortical networks constructed by cortical thickness and sulcal depth showed significant differences between the two groups. Our results indicated that geometric measure (i.e., sulcal depth) can be used to construct network to discriminate individuals with aMCI from controls besides volumetric measures. PMID:27057360

  1. Altered resting-state functional connectivity in cortical networks in psychopathy.

    PubMed

    Philippi, Carissa L; Pujara, Maia S; Motzkin, Julian C; Newman, Joseph; Kiehl, Kent A; Koenigs, Michael

    2015-04-15

    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.

  2. A mechanism for ultra-slow oscillations in the cortical default network.

    PubMed

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

    2011-02-01

    When the brain is in its noncognitive "idling" state, functional MRI measurements reveal the activation of default cortical networks whose activity is suppressed during cognitive processing. This default or background mode is characterized by ultra-slow BOLD oscillations (∼0.05 Hz), signaling extremely slow cycling in cortical metabolic demand across distinct cortical regions. Here we describe a model of the cortex which predicts that slow cycling of cortical activity can arise naturally as a result of nonlinear interactions between temporal (Hopf) and spatial (Turing) instabilities. The Hopf instability is triggered by delays in the inhibitory postsynaptic response, while the Turing instability is precipitated by increases in the strength of the gap-junction coupling between interneurons. We comment on possible implications for slow dendritic computation and information processing. PMID:20821063

  3. Parallel Cortical Networks Formed by Modular Organization of Primary Motor Cortex Outputs.

    PubMed

    Hamadjida, Adjia; Dea, Melvin; Deffeyes, Joan; Quessy, Stephan; Dancause, Numa

    2016-07-11

    In primates, the refinement of motor behaviors, in particular hand use, is associated with the establishment of more direct projections from primary motor cortex (M1) onto cervical motoneurons [1, 2] and the appearance of additional premotor and sensory cortical areas [3]. All of these areas have reciprocal connections with M1 [4-7]. Thus, during the evolution of the sensorimotor network, the number of interlocutors with which M1 interacts has tremendously increased. It is not clear how these additional interconnections are organized in relation to one another within the hand representation of M1. This is important because the organization of connections between M1 and phylogenetically newer and specialized cortical areas is likely to be key to the increased repertoire of hand movements in primates. In cebus monkeys, we used injections of retrograde tracers into the hand representation of different cortical areas of the sensorimotor network (ventral and dorsal premotor areas [PMv and PMd], supplementary motor area [SMA], and posterior parietal cortex [area 5]), and we analyzed the pattern of labeled neurons within the hand representation of M1. Instead of being uniformly dispersed across M1, neurons sending projections to each distant cortical area were largely segregated in different subregions of M1. These data support the view that primates split the cortical real estate of M1 into modules, each preferentially interconnected with a particular cortical area within the sensorimotor network. This modular organization could sustain parallel processing of interactions with multiple specialized cortical areas to increase the behavioral repertoire of the hand. PMID:27322001

  4. Parallel Cortical Networks Formed by Modular Organization of Primary Motor Cortex Outputs.

    PubMed

    Hamadjida, Adjia; Dea, Melvin; Deffeyes, Joan; Quessy, Stephan; Dancause, Numa

    2016-07-11

    In primates, the refinement of motor behaviors, in particular hand use, is associated with the establishment of more direct projections from primary motor cortex (M1) onto cervical motoneurons [1, 2] and the appearance of additional premotor and sensory cortical areas [3]. All of these areas have reciprocal connections with M1 [4-7]. Thus, during the evolution of the sensorimotor network, the number of interlocutors with which M1 interacts has tremendously increased. It is not clear how these additional interconnections are organized in relation to one another within the hand representation of M1. This is important because the organization of connections between M1 and phylogenetically newer and specialized cortical areas is likely to be key to the increased repertoire of hand movements in primates. In cebus monkeys, we used injections of retrograde tracers into the hand representation of different cortical areas of the sensorimotor network (ventral and dorsal premotor areas [PMv and PMd], supplementary motor area [SMA], and posterior parietal cortex [area 5]), and we analyzed the pattern of labeled neurons within the hand representation of M1. Instead of being uniformly dispersed across M1, neurons sending projections to each distant cortical area were largely segregated in different subregions of M1. These data support the view that primates split the cortical real estate of M1 into modules, each preferentially interconnected with a particular cortical area within the sensorimotor network. This modular organization could sustain parallel processing of interactions with multiple specialized cortical areas to increase the behavioral repertoire of the hand.

  5. 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…

  6. Network-State Modulation of Power-Law Frequency-Scaling in Visual Cortical Neurons

    PubMed Central

    Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves

    2009-01-01

    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 Vm 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 Vm 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

  7. 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

  8. High-resolution magnetoencephalographic functional mapping of the cortical network mediating intentional movement.

    PubMed

    Amo, Carlos; Boyajian, Robert A; Romine, John S; Otis, Shirley M

    2007-04-01

    Magnetoencephalography (MEG) is a sensitive technique that can detect and map cortical electrophysiologic activations with high spatial (mm) and temporal (msecs) resolutions. We used 148-channel whole-head MEG to record the activation sequence for the somatosensory and motor cortical network during cued hand movements in a healthy 39-yr-old subject. The complex sequence and topography of cortical activations were superimposed onto the subject's brain magnetic resonance images. Frontal premotor and supplementary motor and cingulate areas activated well before the primary motor area and again repetitively from 200 msecs onward with activations alternating repeatedly between frontal and parietal areas. The network's very close functional integration of supplementary motor areas suggests how brain injury that is localized to these regions, but not to the primary motor area itself, can disrupt integrity of movement, and why preservation of functional integrity of some areas traditionally viewed as extramotor may be necessary for recovery from neurologic disability.

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

    PubMed

    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

  10. 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

  11. 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

  12. 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

  13. Visual cortical mechanisms of perceptual grouping: interacting layers, networks, columns, and maps.

    PubMed

    Ross, W D; Grossberg, S; Mingolla, E

    2000-07-01

    The visual cortex has a laminar organization whose circuits form functional columns in cortical maps. How this laminar architecture supports visual percepts is not well understood. A neural model proposes how the laminar circuits of V1 and V2 generate perceptual groupings that maintain sensitivity to the contrasts and spatial organization of scenic cues. The model can decisively choose which groupings cohere and survive, even while balanced excitatory and inhibitory interactions preserve contrast-sensitive measures of local boundary likelihood or strength. In the model, excitatory inputs from lateral geniculate nucleus (LGN) activate layers 4 and 6 of V1. Layer 6 activates an on-center off-surround network of inputs to layer 4. Together these layer 4 inputs preserve analog sensitivity to LGN input contrasts. Layer 4 cells excite pyramidal cells in layer 2/3, which activate monosynaptic long-range horizontal excitatory connections between layer 2/3 pyramidal cells, and short-range disynaptic inhibitory connections mediated by smooth stellate cells. These interactions support inward perceptual grouping between two or more boundary inducers, but not outward grouping from a single inducer. These boundary signals feed back to layer 4 via the layer 6-to-4 on-center off-surround network. This folded feedback joins cells in different layers into functional columns while selecting winning groupings. Layer 6 in V1 also sends top-down signals to LGN using an on-center off-surround network, which suppresses LGN cells that do not receive feedback, while selecting, enhancing, and synchronizing activity of those that do. The model is used to simulate psychophysical and neurophysiological data about perceptual grouping, including various Gestalt grouping laws.

  14. From cognitive networks to seizures: stimulus evoked dynamics in a coupled cortical network.

    PubMed

    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

  15. 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

  16. 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.

  17. 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. PMID:26917433

  18. Surface area and cortical thickness descriptors reveal different attributes of the structural human brain networks.

    PubMed

    Sanabria-Diaz, Gretel; Melie-García, Lester; Iturria-Medina, Yasser; Alemán-Gómez, Yasser; Hernández-González, Gertrudis; Valdés-Urrutia, Lourdes; Galán, Lídice; Valdés-Sosa, Pedro

    2010-05-01

    Recently, a related morphometry-based connection concept has been introduced using local mean cortical thickness and volume to study the underlying complex architecture of the brain networks. In this article, the surface area is employed as a morphometric descriptor to study the concurrent changes between brain structures and to build binarized connectivity graphs. The statistical similarity in surface area between pair of regions was measured by computing the partial correlation coefficient across 186 normal subjects of the Cuban Human Brain Mapping Project. We demonstrated that connectivity matrices obtained follow a small-world behavior for two different parcellations of the brain gray matter. The properties of the connectivity matrices were compared to the matrices obtained using the mean cortical thickness for the same cortical parcellations. The topology of the cortical thickness and surface area networks were statistically different, demonstrating that both capture distinct properties of the interaction or different aspects of the same interaction (mechanical, anatomical, chemical, etc.) between brain structures. This finding could be explained by the fact that each descriptor is driven by distinct cellular mechanisms as result of a distinct genetic origin. To our knowledge, this is the first time that surface area is used to study the morphological connectivity of brain networks. PMID:20083210

  19. Functional networks in parallel with cortical development associate with executive functions in children.

    PubMed

    Zhong, Jidan; Rifkin-Graboi, Anne; Ta, Anh Tuan; Yap, Kar Lai; Chuang, Kai-Hsiang; Meaney, Michael J; Qiu, Anqi

    2014-07-01

    Children begin performing similarly to adults on tasks requiring executive functions in late childhood, a transition that is probably due to neuroanatomical fine-tuning processes, including myelination and synaptic pruning. In parallel to such structural changes in neuroanatomical organization, development of functional organization may also be associated with cognitive behaviors in children. We examined 6- to 10-year-old children's cortical thickness, functional organization, and cognitive performance. We used structural magnetic resonance imaging (MRI) to identify areas with cortical thinning, resting-state fMRI to identify functional organization in parallel to cortical development, and working memory/response inhibition tasks to assess executive functioning. We found that neuroanatomical changes in the form of cortical thinning spread over bilateral frontal, parietal, and occipital regions. These regions were engaged in 3 functional networks: sensorimotor and auditory, executive control, and default mode network. Furthermore, we found that working memory and response inhibition only associated with regional functional connectivity, but not topological organization (i.e., local and global efficiency of information transfer) of these functional networks. Interestingly, functional connections associated with "bottom-up" as opposed to "top-down" processing were more clearly related to children's performance on working memory and response inhibition, implying an important role for brain systems involved in late childhood. PMID:23448875

  20. 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.

  1. 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

  2. Cortical EEG oscillations and network connectivity as efficacy indices for assessing drugs with cognition enhancing potential.

    PubMed

    Ahnaou, A; Huysmans, H; Jacobs, T; Drinkenburg, W H I M

    2014-11-01

    Synchronization of electroencephalographic (EEG) oscillations represents a core mechanism for cortical and subcortical networks, and disturbance in neural synchrony underlies cognitive processing deficits in neurological and neuropsychiatric disorders. Here, we investigated the effects of cognition enhancers (donepezil, rivastigmine, tacrine, galantamine and memantine), which are approved for symptomatic treatment of dementia, on EEG oscillations and network connectivity in conscious rats chronically instrumented with epidural electrodes in different cortical areas. Next, EEG network indices of cognitive impairments with the muscarinic receptor antagonist scopolamine were modeled. Lastly, we examined the efficacy of cognition enhancers to normalize those aberrant oscillations. Cognition enhancers elicited systematic ("fingerprint") enhancement of cortical slow theta (4.5-6 Hz) and gamma (30.5-50 Hz) oscillations correlated with lower activity levels. Principal component analysis (PCA) revealed a compact cluster that corresponds to shared underlying mechanisms as compared to different drug classes. Functional network connectivity revealed consistent elevated coherent slow theta activity in parieto-occipital and between interhemispheric cortical areas. In rats instrumented with depth hippocampal CA1-CA3 electrodes, donepezil elicited similar oscillatory and coherent activities in cortico-hippocampal networks. When combined with scopolamine, the cognition enhancers attenuated the leftward shift in coherent slow delta activity. Such a consistent shift in EEG coherence into slow oscillations associated with altered slow theta and gamma oscillations may underlie cognitive deficits in scopolamine-treated animals, whereas enhanced coherent slow theta and gamma activity may be a relevant mechanism by which cognition enhancers exert their beneficial effect on plasticity and cognitive processes. The findings underscore that PCA and network connectivity are valuable tools to

  3. 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. PMID:25489852

  4. 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

  5. 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.

  6. Optimized neural coding? Control mechanisms in large cortical networks implemented by connectivity changes

    PubMed Central

    Cross, Katy A.; Iacoboni, Marco

    2011-01-01

    Using functional magnetic resonance imaging, we show that a distributed fronto-parietal visuomotor integration network is recruited to overcome automatic responses to both biological and non-biological cues. Activity levels in these areas are similar for both cue types. The functional connectivity of this network, however, reveals differential coupling with thalamus and precuneus (biological cues) and extrastriate cortex (non biological cues). This suggests that a set of cortical areas equally activated in two tasks may accomplish task goals differently depending on their network interactions. This supports models of brain organization that emphasize efficient coding through changing patterns of integration between regions of specialized function. PMID:21976418

  7. Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

    NASA Astrophysics Data System (ADS)

    Stoop, Ralph; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi

    2013-03-01

    We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic—intercolumnar—scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.

  8. In Vivo Mapping of Cortical Columnar Networks in the Monkey with Focal Electrical and Optical Stimulation

    PubMed Central

    Roe, Anna Wang; Chernov, Mykyta M.; Friedman, Robert M.; Chen, Gang

    2015-01-01

    There are currently largescale efforts to understand the brain as a connection machine. However, there has been little emphasis on understanding connection patterns between functionally specific cortical columns. Here, we review development and application of focal electrical and optical stimulation methods combined with optical imaging and fMRI mapping in the non-human primate. These new approaches, when applied systematically on a large scale, will elucidate functionally specific intra-areal and inter-areal network connection patterns. Such functionally specific network data can provide accurate views of brain network topology. PMID:26635539

  9. 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.

  10. Music lexical networks: the cortical organization of music recognition.

    PubMed

    Peretz, Isabelle; Gosselin, Nathalie; Belin, Pascal; Zatorre, Robert J; Plailly, Jane; Tillmann, Barbara

    2009-07-01

    Successful recognition of a familiar tune depends on a selection procedure that takes place in a memory system that contains all the representations of the specific musical phrases to which one has been exposed during one's lifetime. We refer to this memory system as the musical lexicon. The goal of the study was to identify its neural correlates. The brains of students with little musical training were scanned with functional magnetic resonance imaging (fMRI) while the student listened to familiar musical themes, unfamiliar music, and random tones. The familiar themes were selected from instrumental pieces well-known to the participants; the unfamiliar music was the retrograde version of the familiar themes, which the participants did not recognize; and the random sequences contained the same musical tones but in a random order. All stimuli were synthesized and played with the sound of a piano, thereby keeping low-level acoustical factors similar across conditions. The comparison of cerebral responses to familiar versus unfamiliar music reveals focal activation in the right superior temporal sulcus (STS). Re-analysis of the data obtained in a previous study by Plailly et al. also points to the STS as the critical region involved in musical memories. The neuroimaging data further suggest that these auditory memories are tightly coupled with action (singing), by showing left activation in the planum temporale, in the supplementary motor area (SMA), and in the inferior frontal gyrus. Such a cortical organization of music recognition is analogous to the dorsal stream model of speech processing proposed by Hickok and Poeppel.

  11. A cortical integrate-and-fire neural network model for blind decoding of visual prosthetic stimulation.

    PubMed

    Eiber, Calvin D; Morley, John W; Lovell, Nigel H; Suaning, Gregg J

    2014-01-01

    We present a computational model of the optic pathway which has been adapted to simulate cortical responses to visual-prosthetic stimulation. This model reproduces the statistically observed distributions of spikes for cortical recordings of sham and maximum-intensity stimuli, while simultaneously generating cellular receptive fields consistent with those observed using traditional visual neuroscience methods. By inverting this model to generate candidate phosphenes which could generate the responses observed to novel stimulation strategies, we hope to aid the development of said strategies in-vivo before being deployed in clinical settings. PMID:25570306

  12. Cortical thickness and oscillatory phase resetting: a proposed mechanism of salience network dysfunction in schizophrenia.

    PubMed

    Palaniyappan, L; Doege, K; Mallikarjun, P; Liddle, E; Francis-Liddle, P

    2012-01-01

    Schizophrenia is characterised by both electrophysiological abnormalities and consistent changes in the structure of cortical grey matter. But the relationship between these two observations is largely unknown. Structural changes reported in schizophrenia include reduced grey matter volume, thickness and surface area in several cortical regions, but most frequently in the insula and anterior cingulate cortex. These two regions together constitute an intrinsic brain circuit known as the "Salience Network", which has a key role in stimulus processing. During stimulus processing tasks, evoked activity is noted using electroencephalography (EEG). Phase resetting of ongoing oscillations contributes to this evoked activity. Neuronal oscillations play a crucial role in cerebral recruitment during cognitive tasks, and influencing the oscillatory phase can modulate cortical excitability and the transition between various cognitive states. At a network level, such a transition or switch is thought to be enabled by the Salience Network. In this study, we investigated the relationship between the cortical thickness in the Salience Network (measured using MRI) and the degree of phase resetting observed during an oddball task (measured using EEG) in 18 medicated male patients in a clinically stable phase of schizophrenia and 20 age and gender matched healthy controls. We obtained a measure of partial phase resetting after a stimulus is presented, and a second measure representing mean evoked activity, using the methods proposed by Martinez-Montes. Using MRI analysis, we have firstly shown that there is a significant loss of cortical thickness of regions that constitute the Salience Network in patients with schizophrenia. EEG analysis revealed that in healthy controls, the expected relationship between phase resetting and evoked electrical activity is observed, but in patients with schizophrenia the theta phase resetting is a weak predictor of the activity evoked by attending to

  13. Cortical thickness and oscillatory phase resetting: a proposed mechanism of salience network dysfunction in schizophrenia.

    PubMed

    Palaniyappan, L; Doege, K; Mallikarjun, P; Liddle, E; Francis-Liddle, P

    2012-01-01

    Schizophrenia is characterised by both electrophysiological abnormalities and consistent changes in the structure of cortical grey matter. But the relationship between these two observations is largely unknown. Structural changes reported in schizophrenia include reduced grey matter volume, thickness and surface area in several cortical regions, but most frequently in the insula and anterior cingulate cortex. These two regions together constitute an intrinsic brain circuit known as the "Salience Network", which has a key role in stimulus processing. During stimulus processing tasks, evoked activity is noted using electroencephalography (EEG). Phase resetting of ongoing oscillations contributes to this evoked activity. Neuronal oscillations play a crucial role in cerebral recruitment during cognitive tasks, and influencing the oscillatory phase can modulate cortical excitability and the transition between various cognitive states. At a network level, such a transition or switch is thought to be enabled by the Salience Network. In this study, we investigated the relationship between the cortical thickness in the Salience Network (measured using MRI) and the degree of phase resetting observed during an oddball task (measured using EEG) in 18 medicated male patients in a clinically stable phase of schizophrenia and 20 age and gender matched healthy controls. We obtained a measure of partial phase resetting after a stimulus is presented, and a second measure representing mean evoked activity, using the methods proposed by Martinez-Montes. Using MRI analysis, we have firstly shown that there is a significant loss of cortical thickness of regions that constitute the Salience Network in patients with schizophrenia. EEG analysis revealed that in healthy controls, the expected relationship between phase resetting and evoked electrical activity is observed, but in patients with schizophrenia the theta phase resetting is a weak predictor of the activity evoked by attending to

  14. Pore network microarchitecture influences human cortical bone elasticity during growth and aging.

    PubMed

    Bala, Yohann; Lefèvre, Emmanuelle; Roux, Jean-Paul; Baron, Cécile; Lasaygues, Philippe; Pithioux, Martine; Kaftandjian, Valérie; Follet, Hélène

    2016-10-01

    Cortical porosity is a major determinant of bone strength. Haversian and Volkmann׳s canals are׳seen' as pores in 2D cross-section but fashion a dynamic network of interconnected channels in 3D, a quantifiable footprint of intracortical remodeling. Given the changes in bone remodeling across life, we hypothesized that the 3D microarchitecture of the cortical pore network influences its stiffness during growth and ageing. Cubes of cortical bone of 2 mm side-length were harvested in the distal 1/3 of the fibula in 13 growing children (mean age±SD: 13±4 yrs) and 16 adults (age: 75±13 yrs). The cubes were imaged using desktop micro-CT (8.14µm isotropic voxel size). Pores were segmented as a solid to assess pore volume fraction, number, diameter, separation, connectivity and structure model index. Elastic coefficients were derived from measurements of ultrasonic bulk compression and shear wave velocities and apparent mass density. The pore volume fraction did not significantly differ between children and adults but originates from different microarchitectural patterns. Compared to children, adults had 42% (p=0.033) higher pore number that were more connected (Connective Density: +205%, p=0.001) with a 18% (p=0.007) lower pore separation. After accounting for the contribution of pore volume fraction, axial elasticity in traction-compression mode was significantly correlated with better connectivity in growing children and with pore separation among adults. The changes in intracortical remodeling across life alter the distribution, size and connectedness of the channels from which cortical void fraction originates. These alterations in pore network microarchitecture participate in changes in compressive and shear mechanical behavior, partly in a porosity-independent manner. The assessment of pore volume fraction (i.e., porosity) provides only a limited understanding of the role of cortical void volume fraction in its mechanical properties. PMID:27389322

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

    PubMed

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

    2008-06-01

    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

  16. 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

  17. 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

  18. The plasticity of the mirror system: How reward learning modulates cortical motor simulation of others

    PubMed Central

    Trilla Gros, Irene; Panasiti, Maria Serena; Chakrabarti, Bhismadev

    2015-01-01

    Cortical motor simulation supports the understanding of others' actions and intentions. This mechanism is thought to rely on the mirror neuron system (MNS), a brain network that is active both during action execution and observation. Indirect evidence suggests that (alpha/beta) mu suppression, an electroencephalographic (EEG) index of MNS activity, is modulated by reward. In this study we aimed to test the plasticity of the MNS by directly investigating the link between (alpha/beta) mu suppression and reward. 40 individuals from a general population sample took part in an evaluative conditioning experiment, where different neutral faces were associated with high or low reward values. In the test phase, EEG was recorded while participants viewed videoclips of happy expressions made by the conditioned faces. Alpha/beta mu suppression (identified using event-related desynchronisation of specific independent components) in response to rewarding faces was found to be greater than for non-rewarding faces. This result provides a mechanistic insight into the plasticity of the MNS and, more generally, into the role of reward in modulating physiological responses linked to empathy. PMID:25744871

  19. Covert neurofeedback without awareness shapes cortical network spontaneous connectivity

    PubMed Central

    Grossman, Shany; Friedman, Doron; Malach, Rafael

    2016-01-01

    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. PMID:27071084

  20. 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. PMID:20060111

  1. 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.

  2. Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks.

    PubMed

    Wang, Tao; Wang, Kangcheng; Qu, Hang; Zhou, Jingjing; Li, Qi; Deng, Zhou; Du, Xue; Lv, Fajin; Ren, Gaoping; Guo, Jing; Qiu, Jiang; Xie, Peng

    2016-01-01

    Major depressive disorder is associated with abnormal anatomical and functional connectivity, yet alterations in whole cortical thickness topology remain unknown. Here, we examined cortical thickness in medication-free adult depression patients (n = 76) and matched healthy controls (n = 116). Inter-regional correlation was performed to construct brain networks. By applying graph theory analysis, global (i.e., small-worldness) and regional (centrality) topology was compared between major depressive disorder patients and healthy controls. We found that in depression patients, topological organization of the cortical thickness network shifted towards randomness, and lower small-worldness was driven by a decreased clustering coefficient. Consistently, altered nodal centrality was identified in the isthmus of the cingulate cortex, insula, supra-marginal gyrus, middle temporal gyrus and inferior parietal gyrus, all of which are components within the default mode, salience and central executive networks. Disrupted nodes anchored in the default mode and executive networks were associated with depression severity. The brain systems involved sustain core symptoms in depression and implicate a structural basis for depression. Our results highlight the possibility that developmental and genetic factors are crucial to understand the neuropathology of depression. PMID:27302485

  3. Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks

    PubMed Central

    Wang, Tao; Wang, Kangcheng; Qu, Hang; Zhou, Jingjing; Li, Qi; Deng, Zhou; Du, Xue; Lv, Fajin; Ren, Gaoping; Guo, Jing; Qiu, Jiang; Xie, Peng

    2016-01-01

    Major depressive disorder is associated with abnormal anatomical and functional connectivity, yet alterations in whole cortical thickness topology remain unknown. Here, we examined cortical thickness in medication-free adult depression patients (n = 76) and matched healthy controls (n = 116). Inter-regional correlation was performed to construct brain networks. By applying graph theory analysis, global (i.e., small-worldness) and regional (centrality) topology was compared between major depressive disorder patients and healthy controls. We found that in depression patients, topological organization of the cortical thickness network shifted towards randomness, and lower small-worldness was driven by a decreased clustering coefficient. Consistently, altered nodal centrality was identified in the isthmus of the cingulate cortex, insula, supra-marginal gyrus, middle temporal gyrus and inferior parietal gyrus, all of which are components within the default mode, salience and central executive networks. Disrupted nodes anchored in the default mode and executive networks were associated with depression severity. The brain systems involved sustain core symptoms in depression and implicate a structural basis for depression. Our results highlight the possibility that developmental and genetic factors are crucial to understand the neuropathology of depression. PMID:27302485

  4. Connectivity Analysis Reveals a Cortical Network for Eye Gaze Perception

    PubMed Central

    Passamonti, Luca; Rowe, James; Engell, Andrew D.; Calder, Andrew J.

    2010-01-01

    Haxby et al. (Haxby JV, Hoffman EA, Gobbini MI. 2000. The distributed human neural system for face perception. Trends Cogn Sci. 4:223–233.) proposed that eye gaze processing results from an interaction between a “core” face-specific system involved in visual analysis and an “extended” system involved in spatial attention, more generally. However, the full gaze perception network has remained poorly specified. In the context of a functional magnetic resonance imaging study, we used psychophysiological interactions (PPIs) to identify brain regions that showed differential connectivity (correlation) with core face perception structures (posterior superior temporal sulcus [pSTS] and fusiform gyrus [FG]) when viewing gaze shifts relative to control eye movements (opening/closing the eyes). The PPIs identified altered connectivity between the pSTS and MT/V5, intraparietal sulcus, frontal eye fields, superior temporal gyrus (STG), supramarginal gyrus, and middle frontal gyrus (MFG). The FG showed altered connectivity with the same areas of the STG and MFG, demonstrating the contribution of both dorsal and ventral core face areas to gaze perception. We propose that this network provides an interactive system that alerts us to seen changes in other agents’ gaze direction, makes us aware of their altered focus of spatial attention, and prepares a corresponding shift in our own attention. PMID:20016001

  5. Connectivity analysis reveals a cortical network for eye gaze perception.

    PubMed

    Nummenmaa, Lauri; Passamonti, Luca; Rowe, James; Engell, Andrew D; Calder, Andrew J

    2010-08-01

    Haxby et al. (Haxby JV, Hoffman EA, Gobbini MI. 2000. The distributed human neural system for face perception. Trends Cogn Sci. 4:223-233.) proposed that eye gaze processing results from an interaction between a "core" face-specific system involved in visual analysis and an "extended" system involved in spatial attention, more generally. However, the full gaze perception network has remained poorly specified. In the context of a functional magnetic resonance imaging study, we used psychophysiological interactions (PPIs) to identify brain regions that showed differential connectivity (correlation) with core face perception structures (posterior superior temporal sulcus [pSTS] and fusiform gyrus [FG]) when viewing gaze shifts relative to control eye movements (opening/closing the eyes). The PPIs identified altered connectivity between the pSTS and MT/V5, intraparietal sulcus, frontal eye fields, superior temporal gyrus (STG), supramarginal gyrus, and middle frontal gyrus (MFG). The FG showed altered connectivity with the same areas of the STG and MFG, demonstrating the contribution of both dorsal and ventral core face areas to gaze perception. We propose that this network provides an interactive system that alerts us to seen changes in other agents' gaze direction, makes us aware of their altered focus of spatial attention, and prepares a corresponding shift in our own attention.

  6. Emergence of Small-World and Limitations to Its Maximization in a Macaque Cerebral Cortical Network

    NASA Astrophysics Data System (ADS)

    Zhao, Qing-Bai; Liao, Meng-Jie; Chen, Qi-Cai

    2011-06-01

    We study both the emergence of small-world topology in a macaque cerebral cortical network and the limitations to maximization of small-worldness. The results show that the maximization of neural complexity leads to a small-world topology, but it also limits the maximization of small-worldness. It is suggested that the modular organization that corresponds to different functions may be a limitation. Additionally, the need for strong resilience against attacks may be another limitation.

  7. 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. PMID:25595993

  8. 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.

  9. Prefrontal Cortical Opioids and Dysregulated Motivation: A Network Hypothesis.

    PubMed

    Baldo, Brian A

    2016-06-01

    Loss of inhibitory control over appetitively motivated behavior occurs in multiple psychiatric disorders, including drug abuse, behavioral addictions, and eating disorders with binge features. In this opinion article, novel actions of μ-opioid peptides in the prefrontal cortex (PFC) that could contribute to inhibitory control deficits will be discussed. Evidence has accrued to suggest that excessive intra-PFC μ-opioid receptor (μ-OR) signaling alters the PFC response to excitatory drive, resulting in supernormal and incoherent recruitment of multiple PFC output pathways. Affected pathways include functionally opposed PFC→hypothalamus 'appetitive driver' and PFC→striatum 'appetitive limiter' projections. This network perturbation engenders disorganized, impulsive appetitive responses. Evidence supporting this hypothesis from human imaging and animal studies will be discussed, and combinatorial drug treatments targeting μ-ORs and specific PFC subcortical targets will be explored. PMID:27233653

  10. Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.

    PubMed

    Bennett, Maxwell R; Farnell, Les; Gibson, William G; Lagopoulos, Jim

    2015-01-01

    Measurements of blood oxygenation level dependent (BOLD) signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular) connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular) connections.

  11. Increased cortical thickness in a frontoparietal network in social anxiety disorder.

    PubMed

    Brühl, Annette Beatrix; Hänggi, Jürgen; Baur, Volker; Rufer, Michael; Delsignore, Aba; Weidt, Steffi; Jäncke, Lutz; Herwig, Uwe

    2014-07-01

    Social anxiety disorder (SAD) is the second leading anxiety disorder. On the functional neurobiological level, specific brain regions involved in the processing of anxiety-laden stimuli and in emotion regulation have been shown to be hyperactive and hyper-responsive in SAD such as amygdala, insula and orbito- and prefrontal cortex. On the level of brain structure, prior studies on anatomical differences in SAD resulted in mixed and partially contradictory findings. Based on previous functional and anatomical models of SAD, this study examined cortical thickness in structural magnetic resonance imaging data of 46 patients with SAD without comorbidities (except for depressed episode in one patient) compared with 46 matched healthy controls in a region of interest-analysis and in whole-brain. In a theory-driven ROI-analysis, cortical thickness was increased in SAD in left insula, right anterior cingulate and right temporal pole. Furthermore, the whole-brain analysis revealed increased thickness in right dorsolateral prefrontal and right parietal cortex. This study detected no regions of decreased cortical thickness or brain volume in SAD. From the perspective of brain networks, these findings are in line with prior functional differences in salience networks and frontoparietal networks associated with executive-controlling and attentional functions.

  12. Instantaneous stimulus paradigm: cortical network and dynamics of figure-ground organization

    NASA Astrophysics Data System (ADS)

    Likova, Lora T.; Tyler, Christopher W.

    2007-02-01

    To reveal the cortical network underlying figure/ground perception and to understand its neural dynamics, we developed a novel paradigm that creates distinct and prolonged percepts of spatial structures by instantaneous refreshes in random dot fields. Three different forms of spatial configuration were generated by: (i) updating the whole stimulus field, (ii) updating the ground region only (negative-figure), and (iii) updating the figure and ground regions in brief temporal asynchrony. FMRI responses were measured throughout the brain. As expected, activation by the homogenous whole-field update was focused onto the posterior part of the brain, but distinct networks extending beyond the occipital lobe into the parietal and frontal cortex were activated by the figure/ground and by the negativefigure configurations. The instantaneous stimulus paradigm generated a wide variety of BOLD waveforms and corresponding neural response estimates throughout the network. Such expressly different responses evoked by differential stimulation of the identical cortical regions assure that the differences could be securely attributed to the neural dynamics, not to spatial variations in the HRF. The activation pattern for figure/ground implies a widely distributed neural architecture, distinct from the control conditions. Even where activations are partially overlapping, an integrated analysis of the BOLD response properties will enable the functional specificity of the cortical areas to be distinguished.

  13. 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

  14. 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

  15. 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. PMID:25420745

  16. 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.

  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 Predictive Network Model of Cerebral Cortical Connectivity Based on a Distance Rule

    PubMed Central

    Ercsey-Ravasz, Mária; Markov, Nikola T.; Lamy, Camille; Van Essen, David C.; Knoblauch, Kenneth; Toroczkai, Zoltán; Kennedy, Henry

    2014-01-01

    SUMMARY Recent advances in neuroscience have engendered interest in large-scale brain networks. Using a consistent database of corticocortical connectivity, generated from hemisphere-wide, retrograde tracing experiments in the macaque, we analyzed interareal weights and distances to reveal an important organizational principle of brain connectivity. Using appropriate graph theoretical measures, we show that although very dense (66%), the interareal network has strong structural specificity. Connection weights exhibit a heavy-tailed lognormal distribution spanning five orders of magnitude and conform to a distance rule reflecting exponential decay with interareal separation. A single-parameter random graph model based on this rule predicts numerous features of the cortical network: (1) the existence of a network core and the distribution of cliques, (2) global and local binary properties, (3) global and local weight-based communication efficiencies modeled as network conductance, and (4) overall wire-length minimization. These findings underscore the importance of distance and weight-based heterogeneity in cortical architecture and processing. PMID:24094111

  19. Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.

    PubMed

    Fang, Peng; Zeng, Ling-Li; Shen, Hui; Wang, Lubin; Li, Baojuan; Liu, Li; Hu, Dewen

    2012-01-01

    Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the alterations in connectivity of whole-brain anatomical networks in those suffering from major depression by using machine learning approaches. Brain anatomical networks were extracted from diffusion magnetic resonance images obtained from both 22 first-episode, treatment-naive adults with major depressive disorder and 26 matched healthy controls. Using machine learning approaches, we differentiated depressed patients from healthy controls based on their whole-brain anatomical connectivity patterns and identified the most discriminating features that represent between-group differences. Classification results showed that 91.7% (patients=86.4%, controls=96.2%; permutation test, p<0.0001) of subjects were correctly classified via leave-one-out cross-validation. Moreover, the strengths of all the most discriminating connections were increased in depressed patients relative to the controls, and these connections were primarily located within the cortical-limbic network, especially the frontal-limbic network. These results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease. PMID:23049910

  20. 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. PMID:27228954

  1. 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.

  2. Simulator of Space Communication Networks

    NASA Technical Reports Server (NTRS)

    Clare, Loren; Jennings, Esther; Gao, Jay; Segui, John; Kwong, Winston

    2005-01-01

    Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) is a suite of software tools that simulates the behaviors of communication networks to be used in space exploration, and predict the performance of established and emerging space communication protocols and services. MACHETE consists of four general software systems: (1) a system for kinematic modeling of planetary and spacecraft motions; (2) a system for characterizing the engineering impact on the bandwidth and reliability of deep-space and in-situ communication links; (3) a system for generating traffic loads and modeling of protocol behaviors and state machines; and (4) a system of user-interface for performance metric visualizations. The kinematic-modeling system makes it possible to characterize space link connectivity effects, including occultations and signal losses arising from dynamic slant-range changes and antenna radiation patterns. The link-engineering system also accounts for antenna radiation patterns and other phenomena, including modulations, data rates, coding, noise, and multipath fading. The protocol system utilizes information from the kinematic-modeling and link-engineering systems to simulate operational scenarios of space missions and evaluate overall network performance. In addition, a Communications Effect Server (CES) interface for MACHETE has been developed to facilitate hybrid simulation of space communication networks with actual flight/ground software/hardware embedded in the overall system.

  3. Structural insights into aberrant cortical morphometry and network organization in psychogenic erectile dysfunction.

    PubMed

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

    2015-11-01

    Functional neuroimaging studies have revealed abnormal brain dynamics of male sexual arousal (SA) in psychogenic erectile dysfunction (pED). However, the neuroanatomical correlates of pED are still unclear. In this work, we obtained cortical thickness (CTh) measurements from structural magnetic resonance images of 40 pED patients and 39 healthy control subjects. Abnormalities in CTh related to pED were explored using a scale space search based brain morphometric analysis. Organizations of brain structural covariance networks were analyzed as well. Compared with healthy men, pED patients showed significantly decreased CTh in widespread cortical regions, most of which were previously reported to show abnormal dynamics of male SA in pED, such as the medial prefrontal, orbitofrontal, cingulate, inferotemporal, and insular cortices. CTh reductions in these areas were found to be significantly correlated with male sexual functioning degradation. Moreover, pED patients showed decreased interregional CTh correlations from the right lateral orbitofrontal cortex to the right supramarginal gyrus and the left angular cortex, implying disassociations between the cognitive, motivational, and inhibitory networks of male SA in pED. This work provides structural insights on the complex phenomenon of psychogenic sexual dysfunction in men, and suggests a specific vulnerability factor, possibly as an extra "organic" factor, that may play an important role in pED.

  4. 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

    2011-01-01

    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.

  5. 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.

  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. A GPU-accelerated cortical neural network model for visually guided robot navigation.

    PubMed

    Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L

    2015-12-01

    Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls. PMID:26494281

  8. A GPU-accelerated cortical neural network model for visually guided robot navigation.

    PubMed

    Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L

    2015-12-01

    Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls.

  9. Disrupted cortical network as a vulnerability marker for obsessive-compulsive disorder.

    PubMed

    Peng, Ziwen; Shi, Feng; Shi, Changzheng; Yang, Qiong; Chan, Raymond C K; Shen, Dinggang

    2014-09-01

    Morphological alterations of brain structure are generally assumed to be involved in the pathophysiology of obsessive–compulsive disorder (OCD). Yet, little is known about the morphological connectivity properties of structural brain networks in OCD or about the heritability of those morphological connectivity properties. To better understand these properties, we conducted a study that defined three different groups: OCD group with 30 subjects, siblings group with 19 subjects, and matched controls group with 30 subjects. A structural brain network was constructed using 68 cortical regions of each subject within their respective group (i.e., one brain network for each group). Both small-worldness and modularity were measured to reflect the morphological connectivity properties of each constructed structural brain network. When compared to the matched controls, the structural brain networks of patients with OCD indeed exhibited atypical small-worldness and modularity. Specifically, small-worldness showed decreased local efficiency, and modularity showed reduced intra-connectivity in Module III (default mode network) and increased interconnectivity between Module I (executive function) and Module II (cognitive control/spatial). Intriguingly, the structured brain networks of the unaffected siblings showed similar small-worldness and modularity as OCD patients. Based on the atypical structural brain networks observed in OCD patients and their unaffected siblings, abnormal small-worldness and modularity may indicate a candidate endophenotype for OCD.

  10. 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

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

    PubMed

    van Wijngaarden, Joeri B G; Zucca, Riccardo; Finnigan, Simon; Verschure, Paul F M J

    2016-08-01

    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

  13. Differences in human cortical gene expression match the temporal properties of large-scale functional networks.

    PubMed

    Cioli, Claudia; Abdi, Hervé; Beaton, Derek; Burnod, Yves; Mesmoudi, Salma

    2014-01-01

    We explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas). Previous work suggests that functional cortical networks (resting state and task based) are organized as two large networks (differentiated by their preferred information processing mode) shaped like two rings. The first ring--Visual-Sensorimotor-Auditory (VSA)--comprises visual, auditory, somatosensory, and motor cortices that process real time world interactions. The second ring--Parieto-Temporo-Frontal (PTF)--comprises parietal, temporal, and frontal regions with networks dedicated to cognitive functions, emotions, biological needs, and internally driven rhythms. We found--with correspondence analysis--that the patterns of expression of the 938 genes most differentially expressed across the cortex organized the cortex into two sets of regions that match the two rings. We confirmed this result using discriminant correspondence analysis by showing that the genetic profiles of cortical regions can reliably predict to what ring these regions belong. We found that several of the proteins--coded by genes that most differentiate the rings--were involved in neuronal information processing such as ionic channels and neurotransmitter release. The systematic study of families of genes revealed specific proteins within families preferentially expressed in each ring. The results showed strong congruence between the preferential expression of subsets of genes, temporal properties of the proteins they code, and the preferred processing modes of the rings. Ionic channels and release-related proteins more expressed in the VSA ring favor temporal precision of fast evoked neural transmission (Sodium channels SCNA1, SCNB1 potassium channel KCNA1, calcium channel CACNA2D2, Synaptotagmin SYT2, Complexin CPLX1, Synaptobrevin VAMP1). Conversely, genes expressed in the PTF ring favor slower, sustained, or rhythmic activation (Sodium channels SCNA3

  14. Differences in Human Cortical Gene Expression Match the Temporal Properties of Large-Scale Functional Networks

    PubMed Central

    Cioli, Claudia; Abdi, Hervé; Beaton, Derek; Burnod, Yves; Mesmoudi, Salma

    2014-01-01

    We explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas). Previous work suggests that functional cortical networks (resting state and task based) are organized as two large networks (differentiated by their preferred information processing mode) shaped like two rings. The first ring–Visual-Sensorimotor-Auditory (VSA)–comprises visual, auditory, somatosensory, and motor cortices that process real time world interactions. The second ring–Parieto-Temporo-Frontal (PTF)–comprises parietal, temporal, and frontal regions with networks dedicated to cognitive functions, emotions, biological needs, and internally driven rhythms. We found–with correspondence analysis–that the patterns of expression of the 938 genes most differentially expressed across the cortex organized the cortex into two sets of regions that match the two rings. We confirmed this result using discriminant correspondence analysis by showing that the genetic profiles of cortical regions can reliably predict to what ring these regions belong. We found that several of the proteins–coded by genes that most differentiate the rings–were involved in neuronal information processing such as ionic channels and neurotransmitter release. The systematic study of families of genes revealed specific proteins within families preferentially expressed in each ring. The results showed strong congruence between the preferential expression of subsets of genes, temporal properties of the proteins they code, and the preferred processing modes of the rings. Ionic channels and release-related proteins more expressed in the VSA ring favor temporal precision of fast evoked neural transmission (Sodium channels SCNA1, SCNB1 potassium channel KCNA1, calcium channel CACNA2D2, Synaptotagmin SYT2, Complexin CPLX1, Synaptobrevin VAMP1). Conversely, genes expressed in the PTF ring favor slower, sustained, or rhythmic activation (Sodium

  15. Differential motor and prefrontal cerebello-cortical network development: Evidence from multimodal neuroimaging.

    PubMed

    Bernard, Jessica A; Orr, Joseph M; Mittal, Vijay A

    2016-01-01

    While our understanding of cerebellar structural development through adolescence and young adulthood has expanded, we still lack knowledge of the developmental patterns of cerebellar networks during this critical portion of the lifespan. Volume in lateral posterior cerebellar regions associated with cognition and the prefrontal cortex develops more slowly, reaching their peak volume in adulthood, particularly as compared to motor Lobule V. We predicted that resting state functional connectivity of the lateral posterior regions would show a similar pattern of development during adolescence and young adulthood. That is, we expected to see changes over time in Crus I and Crus II connectivity with the cortex, but no changes in Lobule V connectivity. Additionally, we were interested in how structural connectivity changes in cerebello-thalamo-cortical white matter are related to changes in functional connectivity. A sample of 23 individuals between 12 and 21years old underwent neuroimaging scans at baseline and 12months later. Functional networks of Crus I and Crus II showed significant connectivity decreases over 12months, though there were no differences in Lobule V. Furthermore, these functional connectivity changes were correlated with increases in white matter structural integrity in the corresponding cerebello-thalamo-cortical white matter tract. We suggest that these functional network changes are due to both later pruning in the prefrontal cortex as well as further development of the white matter tracts linking these brain regions.

  16. Differential motor and prefrontal cerebello-cortical network development: Evidence from multimodal neuroimaging.

    PubMed

    Bernard, Jessica A; Orr, Joseph M; Mittal, Vijay A

    2016-01-01

    While our understanding of cerebellar structural development through adolescence and young adulthood has expanded, we still lack knowledge of the developmental patterns of cerebellar networks during this critical portion of the lifespan. Volume in lateral posterior cerebellar regions associated with cognition and the prefrontal cortex develops more slowly, reaching their peak volume in adulthood, particularly as compared to motor Lobule V. We predicted that resting state functional connectivity of the lateral posterior regions would show a similar pattern of development during adolescence and young adulthood. That is, we expected to see changes over time in Crus I and Crus II connectivity with the cortex, but no changes in Lobule V connectivity. Additionally, we were interested in how structural connectivity changes in cerebello-thalamo-cortical white matter are related to changes in functional connectivity. A sample of 23 individuals between 12 and 21years old underwent neuroimaging scans at baseline and 12months later. Functional networks of Crus I and Crus II showed significant connectivity decreases over 12months, though there were no differences in Lobule V. Furthermore, these functional connectivity changes were correlated with increases in white matter structural integrity in the corresponding cerebello-thalamo-cortical white matter tract. We suggest that these functional network changes are due to both later pruning in the prefrontal cortex as well as further development of the white matter tracts linking these brain regions. PMID:26391125

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

    PubMed

    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

  18. 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

  19. Trace Replay and Network Simulation Tool

    SciTech Connect

    Acun, Bilge; Jain, Nikhil; Bhatele, Abhinav

    2015-03-23

    TraceR is a trace reply tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performances and understanding network behavior by simulating messaging in High Performance Computing applications on interconnection networks.

  20. 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…

  1. Circular representation of human cortical networks for subject and population-level connectomic visualization.

    PubMed

    Irimia, Andrei; Chambers, Micah C; Torgerson, Carinna M; Van Horn, John D

    2012-04-01

    Cortical network architecture has predominantly been investigated visually using graph theory representations. In the context of human connectomics, such representations are not however always satisfactory because canonical methods for vertex-edge relationship representation do not always offer optimal insight regarding functional and structural neural connectivity. This article introduces an innovative framework for the depiction of human connectomics by employing a circular visualization method which is highly suitable to the exploration of central nervous system architecture. This type of representation, which we name a 'connectogram', has the capability of classifying neuroconnectivity relationships intuitively and elegantly. A multimodal protocol for MRI/DTI neuroimaging data acquisition is here combined with automatic image segmentation to (1) extract cortical and non-cortical anatomical structures, (2) calculate associated volumetrics and morphometrics, and (3) determine patient-specific connectivity profiles to generate subject-level and population-level connectograms. The scalability of our approach is demonstrated for a population of 50 adults. Two essential advantages of the connectogram are (1) the enormous potential for mapping and analyzing the human connectome, and (2) the unconstrained ability to expand and extend this analysis framework to the investigation of clinical populations and animal models.

  2. Hierarchical organization of macaque and cat cortical sensory systems explored with a novel network processor.

    PubMed Central

    Hilgetag, C C; O'Neill, M A; Young, M P

    2000-01-01

    Neuroanatomists have described a large number of connections between the various structures of monkey and cat cortical sensory systems. Because of the complexity of the connection data, analysis is required to unravel what principles of organization they imply. To date, analysis of laminar origin and termination connection data to reveal hierarchical relationships between the cortical areas has been the most widely acknowledged approach. We programmed a network processor that searches for optimal hierarchical orderings of cortical areas given known hierarchical constraints and rules for their interpretation. For all cortical systems and all cost functions, the processor found a multitude of equally low-cost hierarchies. Laminar hierarchical constraints that are presently available in the anatomical literature were therefore insufficient to constrain a unique ordering for any of the sensory systems we analysed. Hierarchical orderings of the monkey visual system that have been widely reported, but which were derived by hand, were not among the optimal orderings. All the cortical systems we studied displayed a significant degree of hierarchical organization, and the anatomical constraints from the monkey visual and somato-motor systems were satisfied with very few constraint violations in the optimal hierarchies. The visual and somato-motor systems in that animal were therefore surprisingly strictly hierarchical. Most inconsistencies between the constraints and the hierarchical relationships in the optimal structures for the visual system were related to connections of area FST (fundus of superior temporal sulcus). We found that the hierarchical solutions could be further improved by assuming that FST consists of two areas, which differ in the nature of their projections. Indeed, we found that perfect hierarchical arrangements of the primate visual system, without any violation of anatomical constraints, could be obtained under two reasonable conditions, namely the

  3. Development of Distributed Generic Simulator (GenSim) through Invention of Simulated Network (simNetwork)

    NASA Astrophysics Data System (ADS)

    Koo, Cheol-Hea; Lee, Hoon-Hee; Cheon, Yee-Jin

    2011-09-01

    A simulated network protocol provides the capability of distributed simulation to a generic simulator. Through this, full coverage of management of data and service handling among separated simulators is achieved. The distributed simulation environment is much more conducive to handling simulation load balancing and hazard treatment than a standalone computer. According to the simulated network protocol, one simulator takes on the role of server and the other simulators take on the role of client, and client is controlled by server. The purpose of the simulated network protocol is to seamlessly connect multiple simulator instances into a single simulation environment. This paper presents the development of a simulated network (simNetwork) that provides the capability of distributed simulation to a generic simulator (GenSim), which is a software simulator of satellites that has been developed by the Korea Aerospace Research Institute since 2010, to use as a flight software! validation bench for future satellite development.

  4. 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

  5. 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.

  6. 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

  7. A topological study of repetitive co-activation networks in in vitro cortical assemblies.

    PubMed

    Pirino, Virginia; Riccomagno, Eva; Martinoia, Sergio; Massobrio, Paolo

    2015-02-01

    To address the issue of extracting useful information from large data-set of large scale networks of neurons, we propose an algorithm that involves both algebraic-statistical and topological tools. We investigate the electrical behavior of in vitro cortical assemblies both during spontaneous and stimulus-evoked activity coupled to Micro-Electrode Arrays (MEAs). Our goal is to identify core sub-networks of repetitive and synchronous patterns of activity and to characterize them. The analysis is performed at different resolution levels using a clustering algorithm that reduces the network dimensionality. To better visualize the results, we provide a graphical representation of the detected sub-networks and characterize them with a topological invariant, i.e. the sequence of Betti numbers computed on the associated simplicial complexes. The results show that the extracted sub-populations of neurons have a more heterogeneous firing rate with respect to the entire network. Furthermore, the comparison of spontaneous and stimulus-evoked behavior reveals similarities in the identified clusters of neurons, indicating that in both conditions similar activation patterns drive the global network activity. PMID:25559130

  8. Statistical Analysis of Tract-Tracing Experiments Demonstrates a Dense, Complex Cortical Network in the Mouse

    PubMed Central

    Ypma, Rolf J. F.; Bullmore, Edward T.

    2016-01-01

    Anatomical tract tracing methods are the gold standard for estimating the weight of axonal connectivity between a pair of pre-defined brain regions. Large studies, comprising hundreds of experiments, have become feasible by automated methods. However, this comes at the cost of positive-mean noise making it difficult to detect weak connections, which are of particular interest as recent high resolution tract-tracing studies of the macaque have identified many more weak connections, adding up to greater connection density of cortical networks, than previously recognized. We propose a statistical framework that estimates connectivity weights and credibility intervals from multiple tract-tracing experiments. We model the observed signal as a log-normal distribution generated by a combination of tracer fluorescence and positive-mean noise, also accounting for injections into multiple regions. Using anterograde viral tract-tracing data provided by the Allen Institute for Brain Sciences, we estimate the connection density of the mouse intra-hemispheric cortical network to be 73% (95% credibility interval (CI): 71%, 75%); higher than previous estimates (40%). Inter-hemispheric density was estimated to be 59% (95% CI: 54%, 62%). The weakest estimable connections (about 6 orders of magnitude weaker than the strongest connections) are likely to represent only one or a few axons. These extremely weak connections are topologically more random and longer distance than the strongest connections, which are topologically more clustered and shorter distance (spatially clustered). Weak links do not substantially contribute to the global topology of a weighted brain graph, but incrementally increased topological integration of a binary graph. The topology of weak anatomical connections in the mouse brain, rigorously estimable down to the biological limit of a single axon between cortical areas in these data, suggests that they might confer functional advantages for integrative

  9. Cortical networks for visual reaching: physiological and anatomical organization of frontal and parietal lobe arm regions.

    PubMed

    Johnson, P B; Ferraina, S; Bianchi, L; Caminiti, R

    1996-01-01

    The functional and structural properties of the dorsolateral frontal lobe and posterior parietal proximal arm representations were studied in macaque monkeys. Physiological mapping of primary motor (MI), dorsal premotor (PMd), and posterior parietal (area 5) cortices was performed in behaving monkeys trained in an instructed-delay reaching task. The parietofrontal corticocortical connectivities of these same areas were subsequently examined anatomically by means of retrograde tracing techniques. Signal-, set-, movement-, and position-related directional neuronal activities were distributed nonuniformly within the task-related areas in both frontal and parietal cortices. Within the frontal lobe, moving caudally from PMd to the MI, the activity that signals for the visuo-spatial events leading to target localization decreased, while the activity more directly linked to movement generation increased. Physiological recordings in the superior parietal lobule revealed a gradient-like distribution of functional properties similar to that observed in the frontal lobe. Signal- and set-related activities were encountered more frequently in the intermediate and ventral part of the medial bank of the intraparietal sulcus (IPS), in area MIP. Movement-and position-related activities were distributed more uniformly within the superior parietal lobule (SPL), in both dorsal area 5 and in MIP. Frontal and parietal regions sharing similar functional properties were preferentially connected through their association pathways. As a result of this study, area MIP, and possibly areas MDP and 7m as well, emerge as the parietal nodes by which visual information may be relayed to the frontal lobe arm region. These parietal and frontal areas, along with their association connections, represent a potential cortical network for visual reaching. The architecture of this network is ideal for coding reaching as the result of a combination between visual and somatic information.

  10. Statistical Analysis of Tract-Tracing Experiments Demonstrates a Dense, Complex Cortical Network in the Mouse.

    PubMed

    Ypma, Rolf J F; Bullmore, Edward T

    2016-09-01

    Anatomical tract tracing methods are the gold standard for estimating the weight of axonal connectivity between a pair of pre-defined brain regions. Large studies, comprising hundreds of experiments, have become feasible by automated methods. However, this comes at the cost of positive-mean noise making it difficult to detect weak connections, which are of particular interest as recent high resolution tract-tracing studies of the macaque have identified many more weak connections, adding up to greater connection density of cortical networks, than previously recognized. We propose a statistical framework that estimates connectivity weights and credibility intervals from multiple tract-tracing experiments. We model the observed signal as a log-normal distribution generated by a combination of tracer fluorescence and positive-mean noise, also accounting for injections into multiple regions. Using anterograde viral tract-tracing data provided by the Allen Institute for Brain Sciences, we estimate the connection density of the mouse intra-hemispheric cortical network to be 73% (95% credibility interval (CI): 71%, 75%); higher than previous estimates (40%). Inter-hemispheric density was estimated to be 59% (95% CI: 54%, 62%). The weakest estimable connections (about 6 orders of magnitude weaker than the strongest connections) are likely to represent only one or a few axons. These extremely weak connections are topologically more random and longer distance than the strongest connections, which are topologically more clustered and shorter distance (spatially clustered). Weak links do not substantially contribute to the global topology of a weighted brain graph, but incrementally increased topological integration of a binary graph. The topology of weak anatomical connections in the mouse brain, rigorously estimable down to the biological limit of a single axon between cortical areas in these data, suggests that they might confer functional advantages for integrative

  11. Dysfunction of a Cortical Midline Network During Emotional Appraisals in Schizophrenia

    PubMed Central

    Holt, Daphne. J.; Lakshmanan, Balaji; Freudenreich, Oliver; Goff, Donald C.; Rauch, Scott L.; Kuperberg, Gina R.

    2011-01-01

    A cardinal feature of schizophrenia is the poor comprehension, or misinterpretation, of the emotional meaning of social interactions and events, which can sometimes take the form of a persecutory delusion. It has been shown that the comprehension of the emotional meaning of the social world involves a midline paralimbic cortical network. However, the function of this network during emotional appraisals in patients with schizophrenia is not well understood. In this study, hemodynamic responses were measured in 14 patients with schizophrenia and 18 healthy subjects during the evaluation of descriptions of social situations with negative, positive, and neutral affective valence. The healthy and schizophrenia groups displayed opposite patterns of responses to emotional and neutral social situations within the medial prefrontal and posterior cingulate cortices—healthy participants showed greater activity to the emotional compared to the neutral situations, while patients exhibited greater responses to the neutral compared to the emotional situations. Moreover, the magnitude of the response within bilateral cingulate gyri to the neutral social stimuli predicted delusion severity in the patients with schizophrenia. These findings suggest that impaired functioning of cortical midline structures in schizophrenia may underlie faulty interpretations of social events, contributing to delusion formation. PMID:19605517

  12. 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

  13. On visual hallucinations and cortical networks: a trans-diagnostic review.

    PubMed

    Carter, Rowena; Ffytche, Dominic H

    2015-07-01

    Our current clinical approach to visual hallucinations is largely derived from work carried out by Georges de Morsier in the 1930s. Now, almost a century after his influential papers, we have the research tools to further explore the ideas he put forward. In this review, we address de Morsier's proposal that visual hallucinations in all clinical conditions have a similar neurological mechanism by comparing structural imaging studies of susceptibility to visual hallucinations in Parkinson's disease, Alzheimer's disease, Dementia with Lewy bodies and schizophrenia. Systematic review of the literature was undertaken using PubMed searches. A total of 18 studies across conditions were identified reporting grey matter differences between patients with and without visual hallucinations. Grey matter changes were categorised into brain regions relevant to current theories of visual hallucinations. The distribution of cortical atrophy supports de Morsier's premise that visual hallucinations are invariably linked to aberrant activity within visual thalamo-cortical networks. Further work is required to determine by what mechanism these networks become predisposed to spontaneous activation, and whether the frontal lobe and hippocampal changes identified are present in all conditions. The findings have implications for the development of effective treatments for visual hallucinations.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. A cortical attractor network with Martinotti cells driven by facilitating synapses.

    PubMed

    Krishnamurthy, Pradeep; Silberberg, Gilad; Lansner, Anders

    2012-01-01

    The population of pyramidal cells significantly outnumbers the inhibitory interneurons in the neocortex, while at the same time the diversity of interneuron types is much more pronounced. One acknowledged key role of inhibition is to control the rate and patterning of pyramidal cell firing via negative feedback, but most likely the diversity of inhibitory pathways is matched by a corresponding diversity of functional roles. An important distinguishing feature of cortical interneurons is the variability of the short-term plasticity properties of synapses received from pyramidal cells. The Martinotti cell type has recently come under scrutiny due to the distinctly facilitating nature of the synapses they receive from pyramidal cells. This distinguishes these neurons from basket cells and other inhibitory interneurons typically targeted by depressing synapses. A key aspect of the work reported here has been to pinpoint the role of this variability. We first set out to reproduce quantitatively based on in vitro data the di-synaptic inhibitory microcircuit connecting two pyramidal cells via one or a few Martinotti cells. In a second step, we embedded this microcircuit in a previously developed attractor memory network model of neocortical layers 2/3. This model network demonstrated that basket cells with their characteristic depressing synapses are the first to discharge when the network enters an attractor state and that Martinotti cells respond with a delay, thereby shifting the excitation-inhibition balance and acting to terminate the attractor state. A parameter sensitivity analysis suggested that Martinotti cells might, in fact, play a dominant role in setting the attractor dwell time and thus cortical speed of processing, with cellular adaptation and synaptic depression having a less prominent role than previously thought.

  20. 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.

  1. Oscillatory entrainment of the motor cortical network during motor imagery is modulated by the feedback modality.

    PubMed

    Vukelić, Mathias; Gharabaghi, Alireza

    2015-05-01

    Neurofeedback of self-regulated brain activity in circumscribed cortical regions is used as a novel strategy to facilitate functional restoration following stroke. Basic knowledge about its impact on motor system oscillations and functional connectivity is however scarce. Specifically, a direct comparison between different feedback modalities and their neural signatures is missing. We assessed a neurofeedback training intervention of modulating β-activity in circumscribed sensorimotor regions by kinesthetic motor imagery (MI). Right-handed healthy participants received two different feedback modalities contingent to their MI-associated brain activity in a cross-over design: (I) visual feedback with a brain-computer interface (BCI) and (II) proprioceptive feedback with a brain-robot interface (BRI) orthosis attached to the right hand. High-density electroencephalography was used to examine the reactivity of the cortical motor system during the training session of each task by studying both local oscillatory power entrainment and distributed functional connectivity. Both feedback modalities activated a distributed functional connectivity network of coherent oscillations. A significantly higher skill and lower variability of self-controlled sensorimotor β-band modulation could, however, be achieved in the BRI condition. This gain in controlling regional motor oscillations was accompanied by functional coupling of remote β-band and θ-band activity in bilateral fronto-central regions and left parieto-occipital regions, respectively. The functional coupling of coherent θ-band oscillations correlated moreover with the skill of regional β-modulation thus revealing a motor learning related network. Our findings indicate that proprioceptive feedback is more suitable than visual feedback to entrain the motor network architecture during the interplay between motor imagery and feedback processing thus resulting in better volitional control of regional brain activity.

  2. 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.

  3. 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.

  4. 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

  5. Fast oscillations in cortical-striatal networks switch frequency following rewarding events and stimulant drugs

    PubMed Central

    Berke, J.D.

    2009-01-01

    Oscillations may organize communication between components of large-scale brain networks. Although gamma-band oscillations have been repeatedly observed in cortical-basal ganglia circuits, their functional roles are not yet clear. Here I show that, in behaving animals, distinct frequencies of ventral striatal local field potential oscillations show coherence with different cortical inputs. ~50Hz gamma oscillations that normally predominate in awake ventral striatum are coherent with piriform cortex, while ~80-100Hz high-gamma oscillations are consistently coherent with frontal cortex. Within striatum, entrainment to gamma rhythms is selective to fast-spiking interneurons (FSIs), with distinct FSI populations entrained to different gamma frequencies. Administration of the psychomotor stimulant amphetamine or the dopamine agonist apomorphine causes a prolonged decrease in ~50Hz power and increase in ~80-100Hz power. The same frequency switch is observed for shorter epochs spontaneously in awake, undrugged animals, and is consistently provoked for <1s following reward receipt. Individual striatal neurons can participate in these brief high-gamma bursts with, or without, substantial changes in firing rate. Switching between discrete oscillatory states may allow different modes of information processing during decision-making and reinforcement-based learning, and may also be an important systems-level process by which stimulant drugs affect cognition and behavior. PMID:19659455

  6. 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.

  7. Vectorized algorithms for spiking neural network simulation.

    PubMed

    Brette, Romain; Goodman, Dan F M

    2011-06-01

    High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages. PMID:21395437

  8. 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.

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

    PubMed

    Muthalib, Makii; Re, Rebecca; 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.

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

    PubMed

    Muthalib, Makii; Re, Rebecca; 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

  11. 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

  12. Brain changes within the visuo-spatial attentional network in posterior cortical atrophy.

    PubMed

    Cerami, Chiara; Crespi, Chiara; Della Rosa, Pasquale Anthony; Dodich, Alessandra; Marcone, Alessandra; Magnani, Giuseppe; Coppi, Elisabetta; Falini, Andrea; Cappa, Stefano F; Perani, Daniela

    2015-01-01

    Posterior cortical atrophy (PCA) is characterized by basic visual and high order visual-spatial dysfunctions. In this study, we investigated long-distance deafferentation processes within the frontal-parietal-occipital network in ten PCA patients using a MRI-PET combined approach. Objective voxel-based [18F]FDG-PET imaging measured metabolic changes in single patients. Comprehensive investigation of diffusion tensor imaging (DTI) metrics and grey-matter density with voxel-based morphometry were obtained in a subgroup of 6 patients. Fractional anisotropy in the superior longitudinal fasciculus correlated with the PET metabolic changes within the inferior parietal and frontal eye field regions. [18F]FDG-PET analysis showed in each PCA case the typical bilateral hypometabolic pattern, involving posterior temporal, parietal, and occipital cortex, with additional hypometabolic foci in the frontal eye fields. Voxel-based morphometry showed right-sided atrophy in the parieto-occipital cortex, as well as a limited temporal involvement. DTI revealed extensive degeneration of the major anterior-posterior connecting fiber bundles and of commissural frontal lobe tracts. Microstructural measures in the superior longitudinal fasciculus were correlated with the PET metabolic changes within the inferior parietal and frontal eye field regions. Our results confirmed the predominant occipital-temporal and occipital-parietal degeneration in PCA patients. [18F]FDG-PET and DTI-MRI combined approaches revealed neurodegeneration effects well beyond the classical posterior cortical involvement, most likely as a consequence of deafferentation processes within the occipital-parietal-frontal network that could be at the basis of visuo-perceptual, visuo-spatial integration and attention deficits in PCA.

  13. 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

  14. Brain changes within the visuo-spatial attentional network in posterior cortical atrophy.

    PubMed

    Cerami, Chiara; Crespi, Chiara; Della Rosa, Pasquale Anthony; Dodich, Alessandra; Marcone, Alessandra; Magnani, Giuseppe; Coppi, Elisabetta; Falini, Andrea; Cappa, Stefano F; Perani, Daniela

    2015-01-01

    Posterior cortical atrophy (PCA) is characterized by basic visual and high order visual-spatial dysfunctions. In this study, we investigated long-distance deafferentation processes within the frontal-parietal-occipital network in ten PCA patients using a MRI-PET combined approach. Objective voxel-based [18F]FDG-PET imaging measured metabolic changes in single patients. Comprehensive investigation of diffusion tensor imaging (DTI) metrics and grey-matter density with voxel-based morphometry were obtained in a subgroup of 6 patients. Fractional anisotropy in the superior longitudinal fasciculus correlated with the PET metabolic changes within the inferior parietal and frontal eye field regions. [18F]FDG-PET analysis showed in each PCA case the typical bilateral hypometabolic pattern, involving posterior temporal, parietal, and occipital cortex, with additional hypometabolic foci in the frontal eye fields. Voxel-based morphometry showed right-sided atrophy in the parieto-occipital cortex, as well as a limited temporal involvement. DTI revealed extensive degeneration of the major anterior-posterior connecting fiber bundles and of commissural frontal lobe tracts. Microstructural measures in the superior longitudinal fasciculus were correlated with the PET metabolic changes within the inferior parietal and frontal eye field regions. Our results confirmed the predominant occipital-temporal and occipital-parietal degeneration in PCA patients. [18F]FDG-PET and DTI-MRI combined approaches revealed neurodegeneration effects well beyond the classical posterior cortical involvement, most likely as a consequence of deafferentation processes within the occipital-parietal-frontal network that could be at the basis of visuo-perceptual, visuo-spatial integration and attention deficits in PCA. PMID:25114070

  15. Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

    PubMed Central

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

    2011-01-01

    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. PMID:21625569

  16. A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings.

    PubMed

    Zerouali, Younes; Lina, Jean-Marc; Sekerovic, Zoran; Godbout, Jonathan; Dube, Jonathan; Jolicoeur, Pierre; Carrier, Julie

    2014-01-01

    Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging.

  17. A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

    PubMed Central

    Zerouali, Younes; Lina, Jean-Marc; Sekerovic, Zoran; Godbout, Jonathan; Dube, Jonathan; Jolicoeur, Pierre; Carrier, Julie

    2014-01-01

    Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging. PMID:25389381

  18. Spiking in auditory cortex following thalamic stimulation is dominated by cortical network activity

    PubMed Central

    Krause, Bryan M.; Raz, Aeyal; Uhlrich, Daniel J.; Smith, Philip H.; Banks, Matthew I.

    2014-01-01

    The state of the sensory cortical network can have a profound impact on neural responses and perception. In rodent auditory cortex, sensory responses are reported to occur in the context of network events, similar to brief UP states, that produce “packets” of spikes and are associated with synchronized synaptic input (Bathellier et al., 2012; Hromadka et al., 2013; Luczak et al., 2013). However, traditional models based on data from visual and somatosensory cortex predict that ascending sensory thalamocortical (TC) pathways sequentially activate cells in layers 4 (L4), L2/3, and L5. The relationship between these two spatio-temporal activity patterns is unclear. Here, we used calcium imaging and electrophysiological recordings in murine auditory TC brain slices to investigate the laminar response pattern to stimulation of TC afferents. We show that although monosynaptically driven spiking in response to TC afferents occurs, the vast majority of spikes fired following TC stimulation occurs during brief UP states and outside the context of the L4>L2/3>L5 activation sequence. Specifically, monosynaptic subthreshold TC responses with similar latencies were observed throughout layers 2–6, presumably via synapses onto dendritic processes located in L3 and L4. However, monosynaptic spiking was rare, and occurred primarily in L4 and L5 non-pyramidal cells. By contrast, during brief, TC-induced UP states, spiking was dense and occurred primarily in pyramidal cells. These network events always involved infragranular layers, whereas involvement of supragranular layers was variable. During UP states, spike latencies were comparable between infragranular and supragranular cells. These data are consistent with a model in which activation of auditory cortex, especially supragranular layers, depends on internally generated network events that represent a non-linear amplification process, are initiated by infragranular cells and tightly regulated by feed-forward inhibitory

  19. 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

  20. 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

  1. 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.

  2. Forebrain organization representing baroreceptor gating of somatosensory afferents within the cortical autonomic network.

    PubMed

    Goswami, Ruma; Frances, Maria Fernanda; Steinback, Craig Douglas; Shoemaker, J Kevin

    2012-07-01

    Somatosensory afferents are represented within the cortical autonomic network (CAN). However, the representation of somatosensory afferents, and the consequent cardiovascular effects, may be modified by levels of baroreceptor input. Thus, we examined the cortical regions involved with processing somatosensory inputs during baroreceptor unloading. Neuroimaging sessions (functional magnetic resonance imaging [fMRI]) recorded brain activity during 30 mmHg lower-body negative pressure (LBNP) alone and combined with somatosensory stimulation (LBNP+SS) of the forearm (n = 14). Somatosensory processing was also assessed during increased sympathetic outflow via end-expiratory apnea. Heart rate (HR), blood pressure (BP), cardiac output (Q), and muscle sympathetic nerve activity (MSNA) were recorded during the same protocols in a separate laboratory session. SS alone had no effect on any cardiovascular or MSNA variable at rest. Measures of HR, BP, and Q during LBNP were not different compared with LBNP+SS. The rise in MSNA burst frequency was attenuated during LBNP+SS versus LBNP alone (8 vs. 12 bursts/min, respectively, P < 0.05). SS did not affect the change in MSNA during apnea. Activations within the insula and dorsal anterior cingulate cortex (ACC) observed during LBNP were not seen during LBNP+SS. Anterior insula and ACC activations occurring during apnea were not modified by SS. Thus, the absence of insular and dorsal ACC activity during LBNP+SS along with an attenuation of MSNA burst frequency suggest sympathoinhibitory effects of sensory stimulation during decreased baroreceptor input by a mechanism that includes conjoint insula-dorsal ACC regulation. These findings reveal that the level of baroreceptor input influences the forebrain organization of somatosensory afferents. PMID:22514285

  3. 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.

  4. Structural alteration of the dorsal visual network in DLB patients with visual hallucinations: a cortical thickness MRI study.

    PubMed

    Delli Pizzi, Stefano; Franciotti, Raffaella; Tartaro, Armando; Caulo, Massimo; Thomas, Astrid; Onofrj, Marco; Bonanni, Laura

    2014-01-01

    Visual hallucinations (VH) represent one of the core features in discriminating dementia with Lewy bodies (DLB) from Alzheimer's Disease (AD). Previous studies reported that in DLB patients functional alterations of the parieto-occipital regions were correlated with the presence of VH. The aim of our study was to assess whether morphological changes in specific cortical regions of DLB could be related to the presence and severity of VH. We performed a cortical thickness analysis on magnetic resonance imaging data in a cohort including 18 DLB patients, 15 AD patients and 14 healthy control subjects. Relatively to DLB group, correlation analysis between the cortical thickness and the Neuropsychiatric Inventory (NPI) hallucination item scores was also performed. Cortical thickness was reduced bilaterally in DLB compared to controls in the pericalcarine and lingual gyri, cuneus, precuneus, superior parietal gyrus. Cortical thinning was found bilaterally in AD compared to controls in temporal cortex including the superior and middle temporal gyrus, part of inferior temporal cortex, temporal pole and insula. Inferior parietal and supramarginal gyri were also affected bilaterally in AD as compared to controls. The comparison between DLB and AD evidenced cortical thinning in DLB group in the right posterior regions including superior parietal gyrus, precuneus, cuneus, pericalcarine and lingual gyri. Furthermore, the correlation analysis between cortical thickness and NPI hallucination item scores showed that the structural alteration in the dorsal visual regions including superior parietal gyrus and precuneus closely correlated with the occurrence and severity of VH. We suggest that structural changes in key regions of the dorsal visual network may play a crucial role in the physiopathology of VH in DLB patients.

  5. Framework for Network Co-Simulation

    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 canmore » 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.« less

  6. Variability of spike firing during θ-coupled replay of memories in a simulated attractor network.

    PubMed

    Lundqvist, Mikael; Herman, Pawel; Lansner, Anders

    2012-01-24

    Simulation work has recently shown that attractor networks can reproduce Poisson-like variability of single cell spiking, with coefficient of variation (Cv(2)) around unity, consistent with cortical data. However, the use of local variability (Lv) measures has revealed area- and layer-specific deviations from Poisson-like firing. In order to test these findings in silico we used a biophysically detailed attractor network model. We show that Lv well above 1, specifically found in superficial cortical layers and prefrontal areas, can indeed be reproduced in such networks and is consistent with periodic replay rather than persistent firing. The memory replay at the theta time scale provides a framework for a multi-item memory storage in the model. This article is part of a Special Issue entitled Neural Coding.

  7. 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

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

    PubMed

    Horvát, Szabolcs; Gămănuț, Răzvan; Ercsey-Ravasz, Mária; Magrou, Loïc; Gămănuț, Bianca; Van Essen, David C; Burkhalter, Andreas; Knoblauch, Kenneth; Toroczkai, Zoltán; Kennedy, Henry

    2016-07-01

    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

  9. Simulating Network Retrieval of Arithmetic Facts.

    ERIC Educational Resources Information Center

    Ashcraft, Mark H.

    This report describes a simulation of adults' retrieval of arithmetic facts from a network-based memory representation. The goals of the simulation project are to: demonstrate in specific form the nature of a spreading activation model of mental arithmetic; account for three important reaction time effects observed in laboratory investigations;…

  10. 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.

  11. Polymer networks and gels: Simulation and theory

    NASA Astrophysics Data System (ADS)

    Kenkare, Nirupama Ramamurthy

    1998-12-01

    The purpose of this research is to understand the molecular origins of the dynamic and swelling properties of polymer networks and gels. Our approach has been to apply computer simulations techniques to off-lattice, near-perfect, trifunctional and tetrafunctional network models. The networks are constructed by endlinking freely-jointed, tangent-hard-sphere chains. Equilibrium discontinuous molecular dynamics techniques are employed to simulate the relaxation of large networks of chain lengths ranging from N = 20 to N = 150 at a packing fraction of 0.43. The simulation trajectories are used to calculate the radius of gyration and end-to-end distance of the network chains, the static structure factor of the crosslinks, the mean-squared displacement of the crosslinks and chain inner segments, the intermediate scattering function of the chains and the elastic modulus of the network. The structure and properties of the networks are shown to depend heavily on the manner in which the network is initially constructed. The dynamics of the network crosslinks and chain inner segments are similar to those of melt chains at short times and show evidence of spatial localization at long times. The results from the elastic moduli and long-time crosslink and chain displacement calculations indicate that entanglement constraints act in conjunction with crosslink constraints to reduce crosslink and chain mobility. The presence of entanglements appears to cause the magnitude of the elastic modulus to be larger than the affine/phantom model predictions. The pressure-volume behavior and the chain configurational properties of deformed networks are investigated over a range of packing fractions. The variation of network pressure with density is found to be similar to that of uncrosslinked chain systems of the same chain length, except at low densities where the network pressures become negative due to elastic effects. We derive a simple, mean-field network equation of state in which the

  12. Simulated micro-gravity and cortical inhibition: a study of the hemodynamic-brain interaction.

    PubMed

    Vaitl, D; Gruppe, H; Stark, R; Pössel, P

    1996-01-01

    The present study was carried out to determine the inhibitory cortical processes induced by changes in hemodynamics. Previous experiments in humans conducted in our laboratory have shown that there is a close relationship between posture and delta and theta EEG activity. The most pronounced effects were obtained during the 6 degrees head-down tilt (HDT) position. In space medicine the HDT procedure is very frequently employed to simulate micro-gravity and to determine the neurohormonal counter-regulations evoked by the expansion of central volume. Twenty male subjects spent 23 h in bed in 6 degrees HDT and 23 h in 6 degrees HUT (head-up tilt) positions during which EEG (frontal, central, parietal, occipital), startle responses, and reaction-times were measured every 2 h (from 10:00 h till 20:00 h). The effects of cardiovascular deconditioning (CD) regularly occurring after HDT were assessed by examining orthostatic tolerance and the physical work capacity (bicycle ergometry). As expected, 23 h HDT led to more pronounced CD than HUT. Spectral power analyses of EEG revealed increases in delta and theta frequency hands similar to those found during HDT in previous EEG studies. In addition, subjects responded more slowly (S1-S2 reaction-time task) during HDT as compared with HUT bedrest. The influence of HDT on startle response, however, was not in keeping with the initial hypothesis (i.e. dampening of reflex activity). The EEG data and the sensorimotor performance indicated that the body fluid shift towards the thoracic cavity induced by HDT resulted in signs of cortical inhibition. In addition to neural mechanisms, other processes must be postulated which are closely related to the counter-regulation evoked by the varying body positions.

  13. 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

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

    PubMed

    Lecrux, C; Hamel, E

    2016-10-01

    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'. PMID:27574304

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

    PubMed

    Lecrux, C; Hamel, E

    2016-10-01

    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'.

  16. Snazer: the simulations and networks analyzer

    PubMed Central

    2010-01-01

    Background Networks are widely recognized as key determinants of structure and function in systems that span the biological, physical, and social sciences. They are static pictures of the interactions among the components of complex systems. Often, much effort is required to identify networks as part of particular patterns as well as to visualize and interpret them. From a pure dynamical perspective, simulation represents a relevant way-out. Many simulator tools capitalized on the "noisy" behavior of some systems and used formal models to represent cellular activities as temporal trajectories. Statistical methods have been applied to a fairly large number of replicated trajectories in order to infer knowledge. A tool which both graphically manipulates reactive models and deals with sets of simulation time-course data by aggregation, interpretation and statistical analysis is missing and could add value to simulators. Results We designed and implemented Snazer, the simulations and networks analyzer. Its goal is to aid the processes of visualizing and manipulating reactive models, as well as to share and interpret time-course data produced by stochastic simulators or by any other means. Conclusions Snazer is a solid prototype that integrates biological network and simulation time-course data analysis techniques. PMID:20056001

  17. Endogenous cholinergic tone modulates spontaneous network level neuronal activity in primary cortical cultures grown on multi-electrode arrays

    PubMed Central

    2013-01-01

    Background Cortical cultures grown long-term on multi-electrode arrays (MEAs) are frequently and extensively used as models of cortical networks in studies of neuronal firing activity, neuropharmacology, toxicology and mechanisms underlying synaptic plasticity. However, in contrast to the predominantly asynchronous neuronal firing activity exhibited by intact cortex, electrophysiological activity of mature cortical cultures is dominated by spontaneous epileptiform-like global burst events which hinders their effective use in network-level studies, particularly for neurally-controlled animat (‘artificial animal’) applications. Thus, the identification of culture features that can be exploited to produce neuronal activity more representative of that seen in vivo could increase the utility and relevance of studies that employ these preparations. Acetylcholine has a recognised neuromodulatory role affecting excitability, rhythmicity, plasticity and information flow in vivo although its endogenous production by cortical cultures and subsequent functional influence upon neuronal excitability remains unknown. Results Consequently, using MEA electrophysiological recording supported by immunohistochemical and RT-qPCR methods, we demonstrate for the first time, the presence of intrinsic cholinergic neurons and significant, endogenous cholinergic tone in cortical cultures with a characterisation of the muscarinic and nicotinic components that underlie modulation of spontaneous neuronal activity. We found that tonic muscarinic ACh receptor (mAChR) activation affects global excitability and burst event regularity in a culture age-dependent manner whilst, in contrast, tonic nicotinic ACh receptor (nAChR) activation can modulate burst duration and the proportion of spikes occurring within bursts in a spatio-temporal fashion. Conclusions We suggest that the presence of significant endogenous cholinergic tone in cortical cultures and the comparability of its modulatory effects

  18. Improved dimensionally-reduced visual cortical network using stochastic noise modeling.

    PubMed

    Tao, Louis; Praissman, Jeremy; Sornborger, Andrew T

    2012-04-01

    In this paper, we extend our framework for constructing low-dimensional dynamical system models of large-scale neuronal networks of mammalian primary visual cortex. Our dimensional reduction procedure consists of performing a suitable linear change of variables and then systematically truncating the new set of equations. The extended framework includes modeling the effect of neglected modes as a stochastic process. By parametrizing and including stochasticity in one of two ways we show that we can improve the systems-level characterization of our dimensionally reduced neuronal network model. We examined orientation selectivity maps calculated from the firing rate distribution of large-scale simulations and stochastic dimensionally reduced models and found that by using stochastic processes to model the neglected modes, we were able to better reproduce the mean and variance of firing rates in the original large-scale simulations while still accurately predicting the orientation preference distribution.

  19. Default network connectivity decodes brain states with simulated microgravity.

    PubMed

    Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

    2016-04-01

    With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity.

  20. Default network connectivity decodes brain states with simulated microgravity.

    PubMed

    Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

    2016-04-01

    With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity. PMID:27066149

  1. Electrophysiological potentials reveal cortical mechanisms for mental imagery, mental simulation, and grounded (embodied) cognition.

    PubMed

    Schendan, Haline E; Ganis, Giorgio

    2012-01-01

    Grounded cognition theory proposes that cognition, including meaning, is grounded in sensorimotor processing. The mechanism for grounding cognition is mental simulation, which is a type of mental imagery that re-enacts modal processing. To reveal top-down, cortical mechanisms for mental simulation of shape, event-related potentials were recorded to face and object pictures preceded by mental imagery. Mental imagery of the identical face or object picture (congruous condition) facilitated not only categorical perception (VPP/N170) but also later visual knowledge [N3(00) complex] and linguistic knowledge (N400) for faces more than objects, and strategic semantic analysis (late positive complex) between 200 and 700 ms. The later effects resembled semantic congruity effects with pictures. Mental imagery also facilitated category decisions, as a P3 peaked earlier for congruous than incongruous (other category) pictures, resembling the case when identical pictures repeat immediately. Thus mental imagery mimics semantic congruity and immediate repetition priming processes with pictures. Perception control results showed the opposite for faces and were in the same direction for objects: Perceptual repetition adapts (and so impairs) processing of perceived faces from categorical perception onward, but primes processing of objects during categorical perception, visual knowledge processes, and strategic semantic analysis. For both imagery and perception, differences between faces and objects support domain-specificity and indicate that cognition is grounded in modal processing. Altogether, this direct neural evidence reveals that top-down processes of mental imagery sustain an imagistic representation that mimics perception well enough to prime subsequent perception and cognition. Findings also suggest that automatic mental simulation of the visual shape of faces and objects operates between 200 and 400 ms, and strategic mental simulation operates between 400 and 700

  2. Structure of entangled polymer network from primitive chain network simulations

    NASA Astrophysics Data System (ADS)

    Masubuchi, Yuichi; Uneyama, Takashi; Watanabe, Hiroshi; Ianniruberto, Giovanni; Greco, Francesco; Marrucci, Giuseppe

    2010-04-01

    The primitive chain network (PCN) model successfully employed to simulate the rheology of entangled polymers is here tested versus less coarse-grained (lattice or atomistic) models for what concerns the structure of the network at equilibrium (i.e., in the absence of flow). By network structure, we mean the distributions of some relevant quantities such as subchain length in space or in monomer number. Indeed, lattice and atomistic simulations are obviously more accurate, but are also more difficult to use in nonequilibrium flow situations, especially for long entangled polymers. Conversely, the coarse-grained PCN model that deals more easily with rheology lacks, strictly speaking, a rigorous foundation. It is therefore important to verify whether or not the equilibrium structure of the network predicted by the PCN model is consistent with the results recently obtained by using lattice and atomistic simulations. In this work, we focus on single chain properties of the entangled network. Considering the significant differences in modeling the polymer molecules, the results here obtained appear encouraging, thus providing a more solid foundation to Brownian simulations based on the PCN model. Comparison with the existing theories also proves favorable.

  3. Micro-electrode array recordings reveal reductions in both excitation and inhibition in cultured cortical neuron networks lacking Shank3.

    PubMed

    Lu, C; Chen, Q; Zhou, T; Bozic, D; Fu, Z; Pan, J Q; Feng, G

    2016-02-01

    Numerous risk genes have recently been implicated in susceptibility to autism and schizophrenia. Translating such genetic findings into disease-relevant neurobiological mechanisms is challenging due to the lack of throughput assays that can be used to assess their functions on an appropriate scale. To address this issue, we explored the feasibility of using a micro-electrode array (MEA) as a potentially scalable assay to identify the electrical network phenotypes associated with risk genes. We first characterized local and global network firing in cortical neurons with MEAs, and then developed methods to analyze the alternation between the network active period (NAP) and the network inactive period (NIP), each of which lasts tens of seconds. We then evaluated the electric phenotypes of neurons derived from Shank3 knockout (KO) mice. Cortical neurons cultured on MEAs displayed a rich repertoire of spontaneous firing, and Shank3 deletion led to reduced firing activity. Enhancing excitation with CX546 rescued the deficit in the spike rate in the Shank3 KO network. In addition, the Shank3 KO network produced a shorter NIP, and this altered network firing pattern was normalized by clonazepam, a positive modulator of the GABAA receptor. MEA recordings revealed electric phenotypes that displayed altered excitation and inhibition in the network lacking Shank3. Thus, our study highlights MEAs as an experimental framework for measuring multiple robust neurobiological end points in dynamic networks and as an assay system that could be used to identify electric phenotypes in cultured neuronal networks and to analyze additional risk genes identified in psychiatric genetics. PMID:26598066

  4. 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.

  5. 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.

  6. Improving cosmic string network simulations

    NASA Astrophysics Data System (ADS)

    Hindmarsh, Mark; Rummukainen, Kari; Tenkanen, Tuomas V. I.; Weir, David J.

    2014-08-01

    In real-time lattice simulations of cosmic strings in the Abelian Higgs model, the broken translational invariance introduces lattice artifacts; relativistic strings therefore decelerate and radiate. We introduce two different methods to construct a moving string on the lattice, and study in detail the lattice effects on moving strings. We find that there are two types of lattice artifact: there is an effective maximum speed with which a moving string can be placed on the lattice, and a moving string also slows down, with the deceleration approximately proportional to the exponential of the velocity. To mitigate this, we introduce and study an improved discretization, based on the tree-level Lüscher-Weisz action, which is found to reduce the deceleration by an order of magnitude, and to increase the string speed limit by an amount equivalent to halving the lattice spacing. The improved algorithm is expected to be very useful for 3D simulations of cosmic strings in the early Universe, where one wishes to simulate as large a volume as possible.

  7. Abnormal activation of the motor cortical network in idiopathic scoliosis demonstrated by functional MRI.

    PubMed

    Domenech, Julio; García-Martí, G; Martí-Bonmatí, L; Barrios, C; Tormos, J M; Pascual-Leone, A

    2011-07-01

    The aetiology of idiopathic scoliosis (IS) remains unknown, but there is growing support for the possibility of an underlying neurological disorder. Functional magnetic resonance imaging (fMRI) can characterize the abnormal activation of the sensorimotor brain network in movement disorders and could provide further insights into the neuropathogenesis of IS. Twenty subjects were included in the study; 10 adolescents with IS (mean age of 15.2, 8 girls and 2 boys) and 10 age-matched healthy controls. The average Cobb angle of the primary curve in the IS patients was 35° (range 27°-55°). All participants underwent a block-design fMRI experiment in a 1.5-Tesla MRI scanner to explore cortical activation following a simple motor task. Rest periods alternated with activation periods during which participants were required to open and close their hand at an internally paced rate of approximately 1 Hz. Data were analyzed with Statistical Parametric Mapping (SPM5) including age, sex and laterality as nuisance variables to minimise the presence of bias in the results. Compared to controls, IS patients showed significant increases in blood oxygenation level dependent (BOLD) activity in contralateral supplementary motor area when performing the motor task with either hand. No significant differences were observed when testing between groups in the functional activation in the primary motor cortex, premotor cortex and somatosensory cortex. Additionally, the IS group showed a greater interhemispheric asymmetry index than the control group (0.30 vs. 0.13, p < 0.001). This study demonstrates an abnormal pattern of brain activation in secondary motor areas during movement execution in patients with IS. These findings support the hypothesis that a sensorimotor integration disorder underlies the pathogenesis of IS.

  8. Stochastic simulation of karst conduit networks

    NASA Astrophysics Data System (ADS)

    Pardo-Igúzquiza, Eulogio; Dowd, Peter A.; Xu, Chaoshui; Durán-Valsero, Juan José

    2012-01-01

    Karst aquifers have very high spatial heterogeneity. Essentially, they comprise a system of pipes (i.e., the network of conduits) superimposed on rock porosity and on a network of stratigraphic surfaces and fractures. This heterogeneity strongly influences the hydraulic behavior of the karst and it must be reproduced in any realistic numerical model of the karst system that is used as input to flow and transport modeling. However, the directly observed karst conduits are only a small part of the complete karst conduit system and knowledge of the complete conduit geometry and topology remains spatially limited and uncertain. Thus, there is a special interest in the stochastic simulation of networks of conduits that can be combined with fracture and rock porosity models to provide a realistic numerical model of the karst system. Furthermore, the simulated model may be of interest per se and other uses could be envisaged. The purpose of this paper is to present an efficient method for conditional and non-conditional stochastic simulation of karst conduit networks. The method comprises two stages: generation of conduit geometry and generation of topology. The approach adopted is a combination of a resampling method for generating conduit geometries from templates and a modified diffusion-limited aggregation method for generating the network topology. The authors show that the 3D karst conduit networks generated by the proposed method are statistically similar to observed karst conduit networks or to a hypothesized network model. The statistical similarity is in the sense of reproducing the tortuosity index of conduits, the fractal dimension of the network, the direction rose of directions, the Z-histogram and Ripley's K-function of the bifurcation points (which differs from a random allocation of those bifurcation points). The proposed method (1) is very flexible, (2) incorporates any experimental data (conditioning information) and (3) can easily be modified when

  9. 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

  10. 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...

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Roles of nitric oxide in the homeostatic control of the excitation-inhibition balance in rat visual cortical networks.

    PubMed

    Le Roux, N; Amar, M; Moreau, A W; Fossier, P

    2009-10-20

    The level of excitability of cortical neurons depends on the balance between their excitatory and inhibitory inputs (excitation/inhibition [E/I] balance). In the cortex, the E/I balance received by a neuron is dynamically maintained through a coordinated regulation of the strength of these inputs, described in term of homeostatic plasticity. Using a method allowing the determination of the E/I balance in rat cortical layer 5 pyramidal neurons (L5-PNs, the main output stage of the cortex), while keeping the interactions between excitatory and inhibitory networks functional, we examined the effects of high or low frequency of stimulation (HFS or LFS) protocols in layer 4 (in order to mimic thalamo-cortical entries) on the E-I level of the neuronal network. We previously showed that the E/I balance of L5-PNs remains stable due to a dual potentiation or dual depression of E and I after HFS or LFS protocols. Here, using a specific neuronal nitric oxide synthase (nNOS) inhibitor, we show that the related potentiation or depression of E and I (underlying homeostatic plasticity processes) required nNOS activation. We also show that application of an unspecific blocker of nitric oxide synthase (NOS) or a nitric oxide (NO) scavenger induces an increase of the E/I balance suggesting a role for a tonic NO synthesis in the regulation of the network activity. It is concluded that, in the cortex, a phasic NO effect (due to activation of nNOS) is required for the induction of homeostatic plasticity processes whereas a tonic NO signal is involved in the regulation of a set-point value for the E/I balance.

  18. Cortical and subcortical contributions to sequence retrieval: Schematic coding of temporal context in the neocortical recollection network.

    PubMed

    Hsieh, Liang-Tien; Ranganath, Charan

    2015-11-01

    Episodic memory entails the ability to remember what happened when. Although the available evidence indicates that the hippocampus plays a role in structuring serial order information during retrieval of event sequences, information processed in the hippocampus must be conveyed to other cortical and subcortical areas in order to guide behavior. However, the extent to which other brain regions contribute to the temporal organization of episodic memory remains unclear. Here, we examined multivoxel activity pattern changes during retrieval of learned and random object sequences, focusing on a neocortical "core recollection network" that includes the medial prefrontal cortex, retrosplenial cortex, and angular gyrus, as well as on striatal areas including the caudate nucleus and putamen that have been implicated in processing of sequence information. The results demonstrate that regions of the core recollection network carry information about temporal positions within object sequences, irrespective of object information. This schematic coding of temporal information is in contrast to the putamen, which carried information specific to objects in learned sequences, and the caudate, which carried information about objects, irrespective of sequence context. Our results suggest a role for the cortical recollection network in the representation of temporal structure of events during episodic retrieval, and highlight the possible mechanisms by which the striatal areas may contribute to this process. More broadly, the results indicate that temporal sequence retrieval is a useful paradigm for dissecting the contributions of specific brain regions to episodic memory. PMID:26209802

  19. Cortical and subcortical contributions to sequence retrieval: Schematic coding of temporal context in the neocortical recollection network.

    PubMed

    Hsieh, Liang-Tien; Ranganath, Charan

    2015-11-01

    Episodic memory entails the ability to remember what happened when. Although the available evidence indicates that the hippocampus plays a role in structuring serial order information during retrieval of event sequences, information processed in the hippocampus must be conveyed to other cortical and subcortical areas in order to guide behavior. However, the extent to which other brain regions contribute to the temporal organization of episodic memory remains unclear. Here, we examined multivoxel activity pattern changes during retrieval of learned and random object sequences, focusing on a neocortical "core recollection network" that includes the medial prefrontal cortex, retrosplenial cortex, and angular gyrus, as well as on striatal areas including the caudate nucleus and putamen that have been implicated in processing of sequence information. The results demonstrate that regions of the core recollection network carry information about temporal positions within object sequences, irrespective of object information. This schematic coding of temporal information is in contrast to the putamen, which carried information specific to objects in learned sequences, and the caudate, which carried information about objects, irrespective of sequence context. Our results suggest a role for the cortical recollection network in the representation of temporal structure of events during episodic retrieval, and highlight the possible mechanisms by which the striatal areas may contribute to this process. More broadly, the results indicate that temporal sequence retrieval is a useful paradigm for dissecting the contributions of specific brain regions to episodic memory.

  20. Enhanced GABAergic network and receptor function in pediatric cortical dysplasia Type IIB compared with Tuberous Sclerosis Complex.

    PubMed

    Cepeda, Carlos; André, Véronique M; Hauptman, Jason S; Yamazaki, Irene; Huynh, My N; Chang, Julia W; Chen, Jane Y; Fisher, Robin S; Vinters, Harry V; Levine, Michael S; Mathern, Gary W

    2012-01-01

    Tuberous Sclerosis Complex (TSC) and cortical dysplasia Type IIB (CDIIB) share histopathologic features that suggest similar epileptogenic mechanisms. This study compared the morphological and electrophysiological properties of cortical cells in tissue from pediatric TSC (n=20) and CDIIB (n=20) patients using whole-cell patch clamp recordings and biocytin staining. Cell types were normal-appearing and dysmorphic-cytomegalic pyramidal neurons, interneurons, and giant/balloon cells, including intermediate neuronal-glial cells. In the cortical mantle, giant/balloon cells occurred more frequently in TSC than in CDIIB cases, whereas cytomegalic pyramidal neurons were found more frequently in CDIIB. Cell morphology and membrane properties were similar in TSC and CDIIB cases. Except for giant/balloon and intermediate cells, all neuronal cell types fired action potentials and displayed spontaneous postsynaptic currents. However, the frequency of spontaneous glutamatergic postsynaptic currents in normal pyramidal neurons and interneurons was significantly lower in CDIIB compared with TSC cases and the GABAergic activity was higher in all neuronal cell types in CDIIB. Further, acutely dissociated pyramidal neurons displayed higher sensitivity to exogenous application of GABA in CDIIB compared with TSC cases. These results indicate that, in spite of similar histopathologic features and basic cell membrane properties, TSC and CDIIB display differences in the topography of abnormal cells, excitatory and inhibitory synaptic network properties, and GABA(A) receptor sensitivity. These differences support the notion that the mechanisms of epileptogenesis could differ in patients with TSC and CDIIB. Consequently, pharmacologic therapies should take these findings into consideration. PMID:21889982

  1. 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.

  2. Simulation of large systems with neural networks

    SciTech Connect

    Paez, T.L.

    1994-09-01

    Artificial neural networks (ANNs) have been shown capable of simulating the behavior of complex, nonlinear, systems, including structural systems. Under certain circumstances, it is desirable to simulate structures that are analyzed with the finite element method. For example, when we perform a probabilistic analysis with the Monte Carlo method, we usually perform numerous (hundreds or thousands of) repetitions of a response simulation with different input and system parameters to estimate the chance of specific response behaviors. In such applications, efficiency in computation of response is critical, and response simulation with ANNs can be valuable. However, finite element analyses of complex systems involve the use of models with tens or hundreds of thousands of degrees of freedom, and ANNs are practically limited to simulations that involve far fewer variables. This paper develops a technique for reducing the amount of information required to characterize the response of a general structure. We show how the reduced information can be used to train a recurrent ANN. Then the trained ANN can be used to simulate the reduced behavior of the original system, and the reduction transformation can be inverted to provide a simulation of the original system. A numerical example is presented.

  3. Cortical and subcortical contributions to sequence retrieval: schematic coding of temporal context in the neocortical recollection network

    PubMed Central

    Hsieh, Liang-Tien; Ranganath, Charan

    2015-01-01

    Episodic memory entails the ability to remember what happened when. Although the available evidence indicates that the hippocampus plays a role in structuring serial order information during retrieval of event sequences, information processed in the hippocampus must be conveyed to other cortical and subcortical areas in order to guide behavior. However, the extent to which other brain regions contribute to the temporal organization of episodic memory remains unclear. Here, we examined multivoxel activity pattern changes during retrieval of learned and random object sequences, focusing on a neocortical “core recollection network” that includes the medial prefrontal cortex, retrosplenial cortex, and angular gyrus, as well as on striatal areas including the caudate nucleus and putamen that have been implicated in processing of sequence information. The results demonstrate that regions of the core recollection network carry information about temporal positions within object sequences, irrespective of object information. This schematic coding of temporal information is in contrast to the putamen, which carried information specific to objects in learned sequences, and the caudate, which carried information about objects, irrespective of sequence context. Our results suggest a role for the cortical recollection network in the representation of temporal structure of events during episodic retrieval, and highlight the possible mechanisms by which the striatal areas may contribute to this process. More broadly, the results indicate that temporal sequence retrieval is a useful paradigm for dissecting the contributions of specific brain regions to episodic memory. PMID:26209802

  4. Freshly frozen E18 rat cortical cells can generate functional neural networks after standard cryopreservation and thawing procedures.

    PubMed

    Quasthoff, Kim; Ferrea, Stefano; Fleischer, Wiebke; Theiss, Stephan; Schnitzler, Alfons; Dihné, Marcel; Walter, Janine

    2015-05-01

    Primary dissociated brain tissue from rodents is widely used in a variety of different scientific methods to investigate cellular processes in vitro. Often, for this purpose cell cultures need to be generated just on time, requiring extensive animal lab infrastructure. We show here that cryopreservation and thawing of dissociated tissue from rat cerebral cortex at embryonic day 18 is feasible without affecting its ability to form functional neuronal networks in vitro. Vitality of fresh and re-thawed cortical cells was comparable, assessed by CellTiter-Blue-assay, CytoTox-ONE assay, immunocytochemical characterization and in vitro neuronal network activity recordings on microelectrode arrays. These findings suggest that planning and execution of experiments might be considerably facilitated by using cryo-preserved neurons instead of acutely dissociated neural cultures due to fewer logistical issues with regard to animal breeding and pregnancy timed preparations.

  5. 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.

  6. A time and place for language comprehension: mapping the N400 and the P600 to a minimal cortical network

    PubMed Central

    Brouwer, Harm; Hoeks, John C. J.

    2013-01-01

    We propose a new functional-anatomical mapping of the N400 and the P600 to a minimal cortical network for language comprehension. Our work is an example of a recent research strategy in cognitive neuroscience, where researchers attempt to align data regarding the nature and time-course of cognitive processing (from ERPs) with data on the cortical organization underlying it (from fMRI). The success of this “alignment” approach critically depends on the functional interpretation of relevant ERP components. Models of language processing that have been proposed thus far do not agree on these interpretations, and present a variety of complicated functional architectures. We put forward a very basic functional-anatomical mapping based on the recently developed Retrieval-Integration account of language comprehension (Brouwer et al., 2012). In this mapping, the left posterior part of the Middle Temporal Gyrus (BA 21) serves as an epicenter (or hub) in a neurocognitive network for the retrieval of word meaning, the ease of which is reflected in N400 amplitude. The left Inferior Frontal Gyrus (BA 44/45/47), in turn, serves a network epicenter for the integration of this retrieved meaning with the word's preceding context, into a mental representation of what is being communicated; these semantic and pragmatic integrative processes are reflected in P600 amplitude. We propose that our mapping describes the core of the language comprehension network, a view that is parsimonious, has broad empirical coverage, and can serve as the starting point for a more focused investigation into the coupling of brain anatomy and electrophysiology. PMID:24273505

  7. Detecting Allosteric Networks Using Molecular Dynamics Simulation.

    PubMed

    Bowerman, S; Wereszczynski, J

    2016-01-01

    Allosteric networks allow enzymes to transmit information and regulate their catalytic activities over vast distances. In principle, molecular dynamics (MD) simulations can be used to reveal the mechanisms that underlie this phenomenon; in practice, it can be difficult to discern allosteric signals from MD trajectories. Here, we describe how MD simulations can be analyzed to reveal correlated motions and allosteric networks, and provide an example of their use on the coagulation enzyme thrombin. Methods are discussed for calculating residue-pair correlations from atomic fluctuations and mutual information, which can be combined with contact information to identify allosteric networks and to dynamically cluster a system into highly correlated communities. In the case of thrombin, these methods show that binding of the antagonist hirugen significantly alters the enzyme's correlation landscape through a series of pathways between Exosite I and the catalytic core. Results suggest that hirugen binding curtails dynamic diversity and enforces stricter venues of influence, thus reducing the accessibility of thrombin to other molecules. PMID:27497176

  8. 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

  9. Spiking network simulation code for petascale computers

    PubMed Central

    Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M.; Plesser, Hans E.; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

    2014-01-01

    Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today. PMID:25346682

  10. Spiking network simulation code for petascale computers.

    PubMed

    Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M; Plesser, Hans E; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

    2014-01-01

    Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today. PMID:25346682

  11. Spiking network simulation code for petascale computers.

    PubMed

    Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M; Plesser, Hans E; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

    2014-01-01

    Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today.

  12. A cortical network model of cognitive and emotional influences in human decision making.

    PubMed

    Nazir, Azadeh Hassannejad; Liljenström, Hans

    2015-10-01

    Decision making (DM)(2) is a complex process that appears to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) seem to be essential in human decision making, where both emotional and cognitive aspects are taken into account. In this paper, we present a computational network model representing the neural information processing of DM, from perception to behavior. We model the population dynamics of the three neural structures (amygdala, OFC and LPFC), as well as their interaction. In our model, the neurodynamic activity of amygdala and OFC represents the neural correlates of secondary emotion, while the activity of certain neural populations in OFC alone represents the outcome expectancy of different options. The cognitive/rational aspect of DM is associated with LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in DM under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. Simulation results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on CO2 emissions and climate change.

  13. 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.

  14. 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.

  15. Large-scale modeling of epileptic seizures: scaling properties of two parallel neuronal network simulation algorithms.

    PubMed

    Pesce, Lorenzo L; Lee, Hyong C; Hereld, Mark; Visser, Sid; Stevens, Rick L; Wildeman, Albert; van Drongelen, Wim

    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 determined 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. PMID:24416069

  16. Large-scale modeling of epileptic seizures: scaling properties of two parallel neuronal network simulation algorithms.

    PubMed

    Pesce, Lorenzo L; Lee, Hyong C; Hereld, Mark; Visser, Sid; Stevens, Rick L; Wildeman, Albert; van Drongelen, Wim

    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 determined 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.

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

    DOE PAGESBeta

    Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; Visser, Sid; Stevens, Rick L.; Wildeman, Albert; van Drongelen, Wim

    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

  18. The statistics of repeating patterns of cortical activity can be reproduced by a model network of stochastic binary neurons.

    PubMed

    Roxin, Alex; Hakim, Vincent; Brunel, Nicolas

    2008-10-15

    Calcium imaging of the spontaneous activity in cortical slices has revealed repeating spatiotemporal patterns of transitions between so-called down states and up states (Ikegaya et al., 2004). Here we fit a model network of stochastic binary neurons to data from these experiments, and in doing so reproduce the distributions of such patterns. We use two versions of this model: (1) an unconnected network in which neurons are activated as independent Poisson processes; and (2) a network with an interaction matrix, estimated from the data, representing effective interactions between the neurons. The unconnected model (model 1) is sufficient to account for the statistics of repeating patterns in 11 of the 15 datasets studied. Model 2, with interactions between neurons, is required to account for pattern statistics of the remaining four. Three of these four datasets are the ones that contain the largest number of transitions, suggesting that long datasets are in general necessary to render interactions statistically visible. We then study the topology of the matrix of interactions estimated for these four datasets. For three of the four datasets, we find sparse matrices with long-tailed degree distributions and an overrepresentation of certain network motifs. The remaining dataset exhibits a strongly interconnected, spatially localized subgroup of neurons. In all cases, we find that interactions between neurons facilitate the generation of long patterns that do not repeat exactly.

  19. αTubulin 67C and Ncd Are Essential for Establishing a Cortical Microtubular Network and Formation of the Bicoid mRNA Gradient in Drosophila

    PubMed Central

    Cai, Xiaoli; Koul, Aabid; Hayder, Awais; Baumgartner, Stefan

    2014-01-01

    The Bicoid (Bcd) protein gradient in Drosophila serves as a paradigm for gradient formation in textbooks. To explain the generation of the gradient, the ARTS model, which is based on the observation of a bcd mRNA gradient, proposes that the bcd mRNA, localized at the anterior pole at fertilization, migrates along microtubules (MTs) at the cortex to the posterior to form a bcd mRNA gradient which is translated to form a protein gradient. To fulfil the criteria of the ARTS model, an early cortical MT network is thus a prerequisite. We report hitherto undiscovered MT activities in the early embryo important for bcd mRNA transport: (i) an early and omnidirectional MT network exclusively at the anterior cortex of early nuclear cycle embryos showing activity during metaphase and anaphase only, (ii) long MTs up to 50 µm extending into the yolk at blastoderm stage to enable basal-apical transport. The cortical MT network is not anchored to the actin cytoskeleton. The posterior transport of the mRNA via the cortical MT network critically depends on maternally-expressed αTubulin67C and the minus-end motor Ncd. In either mutant, cortical transport of the bcd mRNA does not take place and the mRNA migrates along another yet undisclosed interior MT network, instead. Our data strongly corroborate the ARTS model and explain the occurrence of the bcd mRNA gradient. PMID:25390693

  20. 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

    2016-09-01

    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.

  1. 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

    2016-09-01

    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. PMID:27568515

  2. Passive ankle dorsiflexion by an automated device and the reactivity of the motor cortical network.

    PubMed

    Pittaccio, Simone; Zappasodi, Filippo; Tamburro, Gabriella; Viscuso, Stefano; Marzetti, Laura; Garavaglia, Lorenzo; Tecchio, Franca; Pizzella, Vittorio

    2013-01-01

    Gait impairment is an important consequence of neurological disease. Passive mobilization of the affected lower limbs is often prescribed in order to safeguard tissue properties and prevent circulatory sequelae during paresis. However, passive movement could play a role also in stimulating cortical areas of the brain devoted to the control of the lower limb, so that deafferentation and learned non-use can be contrasted. The purpose of the present work is to investigate cortical involvement during active and passive movements of the ankle joint, in an attempt to gain deeper insight in the similarities between these two conditions. A wearable device to mobilize the ankle joint was implemented utilizing rotary shape memory alloy actuators. The technical characteristics of this actuator make it very compatible with the tight limitations on electromagnetic noise imposed by diagnostic instrumentation. Eleven healthy volunteers took part in the pre-clinical phase of the study. According to the protocol, brain activity was recorded by 165-channel magnetoencephalography (MEG) under three different conditions: rest, active dorsiflexion of the ankle and passive mobilization of the same joint. The acquired data were processed to obtain cortical ERD/ERS (Event Related Desynchronization/ Synchronization) maps, which were then compared. The results of this analysis show that there are similar patterns of activity between active and passive movement, particularly in β band, in the contralateral primary sensorimotor, dorsal premotor and supplementary motor areas. This result, albeit obtained from healthy subjects, might suggest that passive motion provides somatosensory afferences that, to some extent, are processed in a similar manner as for voluntary control. Should this evidence be confirmed by further experiments on neurological patients, it could support the prescription of passive exercise as a surrogate of active workout, at least, so long as patients are paretic.

  3. 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

  4. Quantitative imaging of microvascular blood flow networks in deep cortical layers by 1310 nm µODT

    PubMed Central

    You, Jiang; Zhang, Qiujia; Park, Kicheon; Du, Congwu

    2016-01-01

    There is growing interest in new neuroimage techniques that permit not only high-resolution quantification of cerebral blood flow velocity (CBFv) in capillaries, but also a large field of view to map the CBFv network dynamics. Such image capabilities are of great importance for decoding the functional difference across multiple cortical layers under stimuli. To tackle the limitation of optical penetration depth, we present a new ultrahigh-resolution optical coherence Doppler tomography (µODT) system at 1310 nm and compare it with a prior 800 nm µODT system for mouse brain 3D CBFv imaging. We show that the new 1310 nm µODT allows for dramatically increased depth (~4 times) of quantitative CBFv imaging to 1.4 mm, thus covering the full thickness of the mouse cortex (i.e., layers I–VI). Interestingly, we show that such a unique 3D CBFv imaging capability allows identification of microcirculatory redistribution across different cortical layers resulting from repeated cocaine exposures. PMID:26371919

  5. Nanoindentation testing and finite element simulations of cortical bone allowing for anisotropic elastic and inelastic mechanical response.

    PubMed

    Carnelli, Davide; Lucchini, Riccardo; Ponzoni, Matteo; Contro, Roberto; Vena, Pasquale

    2011-07-01

    Anisotropy is one of the most peculiar aspects of cortical bone mechanical behaviour, and the numerical approach can be successfully used to investigate aspects of bone tissue mechanics that analytical methods solve in approximate way or do not cover. In this work, nanoindentation experimental tests and finite element simulations were employed to investigate the elastic-inelastic anisotropic mechanical properties of cortical bone. The model allows for anisotropic elastic and post-yield behaviour of the tissue. A tension-compression mismatch and direction-dependent yield stresses are allowed for. Indentation experiments along the axial and transverse directions were simulated with the purpose to predict the indentation moduli and hardnesses along multiple orientations. Results showed that the experimental transverse-to-axial ratio of indentation moduli, equal to 0.74, is predicted with a ∼3% discrepancy regardless the post-yield material behaviour; whereas, the transverse-to-axial hardness ratio, equal to 0.86, can be correctly simulated (discrepancy ∼6% w.r.t. the experimental results) only employing an anisotropic post-elastic constitutive model. Further, direct comparison between the experimental and simulated indentation tests evidenced a good agreement in the loading branch of the indentation curves and in the peak loads for a transverse-to-axial yield stress ratio comparable to the experimentally obtained transverse-to-axial hardness ratio. In perspective, the present work results strongly support the coupling between indentation experiments and FEM simulations to get a deeper knowledge of bone tissue mechanical behaviour at the microstructural level. The present model could be used to assess the effect of variations of constitutive parameters due to age, injury, and/or disease on bone mechanical performance in the context of indentation testing. PMID:21570077

  6. 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.

  7. 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

  8. Prediction of the main cortical areas and connections involved in the tactile function of the visual cortex by network analysis.

    PubMed

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

    2006-04-01

    We explored the cortical pathways from the primary somatosensory cortex to the primary visual cortex (V1) by analysing connectional data in the macaque monkey using graph-theoretical tools. Cluster analysis revealed the close relationship of the dorsal visual stream and the sensorimotor cortex. It was shown that prefrontal area 46 and parietal areas VIP and 7a occupy a central position between the different clusters in the visuo-tactile network. Among these structures all the shortest paths from primary somatosensory cortex (3a, 1 and 2) to V1 pass through VIP and then reach V1 via MT, V3 and PO. Comparison of the input and output fields suggested a larger specificity for the 3a/1-VIP-MT/V3-V1 pathways among the alternative routes. A reinforcement learning algorithm was used to evaluate the importance of the aforementioned pathways. The results suggest a higher role for V3 in relaying more direct sensorimotor information to V1. Analysing cliques, which identify areas with the strongest coupling in the network, supported the role of VIP, MT and V3 in visuo-tactile integration. These findings indicate that areas 3a, 1, VIP, MT and V3 play a major role in shaping the tactile information reaching V1 in both sighted and blind subjects. Our observations greatly support the findings of the experimental studies and provide a deeper insight into the network architecture underlying visuo-tactile integration in the primate cerebral cortex.

  9. 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.

  10. 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

  11. 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.

  12. 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...

  13. Patterns of Cortical Oscillations Organize Neural Activity into Whole-Brain Functional Networks Evident in the fMRI BOLD Signal

    PubMed Central

    Whitman, Jennifer C.; Ward, Lawrence M.; Woodward, Todd S.

    2013-01-01

    Recent findings from electrophysiology and multimodal neuroimaging have elucidated the relationship between patterns of cortical oscillations evident in EEG/MEG and the functional brain networks evident in the BOLD signal. Much of the existing literature emphasized how high-frequency cortical oscillations are thought to coordinate neural activity locally, while low-frequency oscillations play a role in coordinating activity between more distant brain regions. However, the assignment of different frequencies to different spatial scales is an oversimplification. A more informative approach is to explore the arrangements by which these low- and high-frequency oscillations work in concert, coordinating neural activity into whole-brain functional networks. When relating such networks to the BOLD signal, we must consider how the patterns of cortical oscillations change at the same speed as cognitive states, which often last less than a second. Consequently, the slower BOLD signal may often reflect the summed neural activity of several transient network configurations. This temporal mismatch can be circumvented if we use spatial maps to assess correspondence between oscillatory networks and BOLD networks. PMID:23504590

  14. Self-sustained asynchronous irregular states and Up-Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons.

    PubMed

    Destexhe, Alain

    2009-12-01

    Randomly-connected networks of integrate-and-fire (IF) neurons are known to display asynchronous irregular (AI) activity states, which resemble the discharge activity recorded in the cerebral cortex of awake animals. However, it is not clear whether such activity states are specific to simple IF models, or if they also exist in networks where neurons are endowed with complex intrinsic properties similar to electrophysiological measurements. Here, we investigate the occurrence of AI states in networks of nonlinear IF neurons, such as the adaptive exponential IF (Brette-Gerstner-Izhikevich) model. This model can display intrinsic properties such as low-threshold spike (LTS), regular spiking (RS) or fast-spiking (FS). We successively investigate the oscillatory and AI dynamics of thalamic, cortical and thalamocortical networks using such models. AI states can be found in each case, sometimes with surprisingly small network size of the order of a few tens of neurons. We show that the presence of LTS neurons in cortex or in thalamus, explains the robust emergence of AI states for relatively small network sizes. Finally, we investigate the role of spike-frequency adaptation (SFA). In cortical networks with strong SFA in RS cells, the AI state is transient, but when SFA is reduced, AI states can be self-sustained for long times. In thalamocortical networks, AI states are found when the cortex is itself in an AI state, but with strong SFA, the thalamocortical network displays Up and Down state transitions, similar to intracellular recordings during slow-wave sleep or anesthesia. Self-sustained Up and Down states could also be generated by two-layer cortical networks with LTS cells. These models suggest that intrinsic properties such as adaptation and low-threshold bursting activity are crucial for the genesis and control of AI states in thalamocortical networks.

  15. Integrated workflows for spiking neuronal network simulations

    PubMed Central

    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. PMID

  16. 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.

  17. Numeric simulation of plant signaling networks.

    PubMed

    Genoud, T; Trevino Santa Cruz, M B; Métraux, J P

    2001-08-01

    Plants have evolved an intricate signaling apparatus that integrates relevant information and allows an optimal response to environmental conditions. For instance, the coordination of defense responses against pathogens involves sophisticated molecular detection and communication systems. Multiple protection strategies may be deployed differentially by the plant according to the nature of the invading organism. These responses are also influenced by the environment, metabolism, and developmental stage of the plant. Though the cellular signaling processes traditionally have been described as linear sequences of events, it is now evident that they may be represented more accurately as network-like structures. The emerging paradigm can be represented readily with the use of Boolean language. This digital (numeric) formalism allows an accurate qualitative description of the signal transduction processes, and a dynamic representation through computer simulation. Moreover, it provides the required power to process the increasing amount of information emerging from the fields of genomics and proteomics, and from the use of new technologies such as microarray analysis. In this review, we have used the Boolean language to represent and analyze part of the signaling network of disease resistance in Arabidopsis. PMID:11500542

  18. 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...

  19. Simulation of the effects of microtubules in the cortical rotation of amphibian embryos in normal and zero gravity.

    PubMed

    Nouri, Comron; Tuszynski, Jack A; Wiebe, Mark W; Gordon, Richard

    2012-09-01

    This paper reports the results of computer modeling of microtubules that end up in the cortical region of a one-cell amphibian embryo, prior to the first cell division. Microtubules are modeled as initially randomly oriented semi-flexible rods, represented by several lines of point-masses interacting with one another like masses on springs with longitudinal and transverse stiffness. They are also considered to be space-filling rods floating in a viscous fluid (cytoplasm) experiencing drag forces and buoyancy from the fluid under a variable gravity field to test gravitational effects. Their randomly distributed interactions with the surrounding spherical container (the cell membrane) have a statistical nonzero average that creates a torque causing a rotational displacement between the cytoplasm and the rigid cortex. The simulation has been done for zero and normal gravity and it validates the observation that cortical rotation occurs in microgravity as well as on Earth. The speed of rotation depends on gravity, but is still substantial in microgravity.

  20. 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.

  1. 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

  2. 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

  3. 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.

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

    PubMed Central

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

    2015-01-01

    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. PMID:25823864

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

    PubMed

    Suffczynski, Piotr; Crone, Nathan E; Franaszczuk, Piotr J

    2014-12-01

    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

  6. 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…

  7. 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

  8. Distinct cortical networks activated by auditory attention and working memory load.

    PubMed

    Huang, Samantha; Seidman, Larry J; Rossi, Stephanie; Ahveninen, Jyrki

    2013-12-01

    Auditory attention and working memory (WM) allow for selection and maintenance of relevant sound information in our minds, respectively, thus underlying goal-directed functioning in everyday acoustic environments. It is still unclear whether these two closely coupled functions are based on a common neural circuit, or whether they involve genuinely distinct subfunctions with separate neuronal substrates. In a full factorial functional MRI (fMRI) design, we independently manipulated the levels of auditory-verbal WM load and attentional interference using modified Auditory Continuous Performance Tests. Although many frontoparietal regions were jointly activated by increases of WM load and interference, there was a double dissociation between prefrontal cortex (PFC) subareas associated selectively with either auditory attention or WM. Specifically, anterior dorsolateral PFC (DLPFC) and the right anterior insula were selectively activated by increasing WM load, whereas subregions of middle lateral PFC and inferior frontal cortex (IFC) were associated with interference only. Meanwhile, a superadditive interaction between interference and load was detected in left medial superior frontal cortex, suggesting that in this area, activations are not only overlapping, but reflect a common resource pool recruited by increased attentional and WM demands. Indices of WM-specific suppression of anterolateral non-primary auditory cortices (AC) and attention-specific suppression of primary AC were also found, possibly reflecting suppression/interruption of sound-object processing of irrelevant stimuli during continuous task performance. Our results suggest a double dissociation between auditory attention and working memory in subregions of anterior DLPFC vs. middle lateral PFC/IFC in humans, respectively, in the context of substantially overlapping circuits.

  9. Distinct cortical networks activated by auditory attention and working memory load

    PubMed Central

    Huang, Samantha; Seidman, Larry J.; Rossi, Stephanie; Ahveninen, Jyrki

    2013-01-01

    Auditory attention and working memory (WM) allow for selection and maintenance of relevant sound information in our minds, respectively, thus underlying goal-directed functioning in everyday acoustic environments. It is still unclear whether these two closely coupled functions are based on a common neural circuit, or whether they involve genuinely distinct subfunctions with separate neuronal substrates. In a full factorial functional MRI (fMRI) design, we independently manipulated the levels of auditory-verbal WM load and attentional interference using modified Auditory Continuous Performance Tests. Although many frontoparietal regions were jointly activated by increases of WM load and interference, there was a double dissociation between prefrontal cortex (PFC) subareas associated selectively with either auditory attention or WM. Specifically, anterior dorsolateral PFC (DLPFC) and the right anterior insula were selectively activated by increasing WM load, whereas subregions of middle lateral PFC and inferior frontal cortex (IFC) were associated with interference only. Meanwhile, a superadditive interaction between interference and load was detected in left medial superior frontal cortex, suggesting that in this area, activations are not only overlapping, but reflect a common resource pool recruited by increased attentional and WM demands. Indices of WM-specific suppression of anterolateral non-primary auditory cortices (AC) and attention-specific suppression of primary AC were also found, possibly reflecting suppression/interruption of sound-object processing of irrelevant stimuli during continuous task performance. Our results suggest a double dissociation between auditory attention and working memory in subregions of anterior DLPFC vs. middle lateral PFC/IFC in humans, respectively, in the context of substantially overlapping circuits. PMID:23921102

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

    NASA Astrophysics Data System (ADS)

    Ascenzi, Maria-Grazia; Kawas, Neal P.; Lutz, Andre; 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.

  11. 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

  12. The role of axonal delay in the synchronization of networks of coupled cortical oscillators.

    PubMed

    Crook, S M; Ermentrout, G B; Vanier, M C; Bower, J M

    1997-04-01

    Coupled oscillator models use a single phase variable to approximate the voltage oscillation of each neuron during repetitive firing where the behavior of the model depends on the connectivity and the interaction function chosen to describe the coupling. We introduce a network model consisting of a continuum of these oscillators that includes the effects of spatially decaying coupling and axonal delay. We derive equations for determining the stability of solutions and analyze the network behavior for two different interaction functions. The first is a sine function, and the second is derived from a compartmental model of a pyramidal cell. In both cases, the system of coupled neural oscillators can undergo a bifurcation from synchronous oscillations to waves. The change in qualitative behavior is due to the axonal delay, which causes distant connections to encourage a phase shift between cells. We suggest that this mechanism could contribute to the behavior observed in several neurobiological systems.

  13. 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

  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. 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.

  16. Research and Simulation on Application of the Mobile IP Network

    NASA Astrophysics Data System (ADS)

    Yibing, Deng; Wei, Hu; Minghui, Li; Feng, Gao; Junyi, Shen

    The paper analysed the mobile node, home agent, and foreign agent of mobile IP network firstly, some key technique, such as mobile IP network basical principle, protocol work principle, agent discovery, registration, and IP packet transmission, were discussed. Then a network simulation model was designed, validating the characteristic of mobile IP network, and some advantages, which were brought by mobile network, were testified. Finally, the conclusion is gained: mobile IP network could realize the expectation of consumer that they can communicate with others anywhere.

  17. Simulation of Soil Macropore Networks Using Multi-Point Geostatistics

    NASA Astrophysics Data System (ADS)

    Luo, L.; Lin, H.; Singha, K.

    2006-12-01

    Two-point correlation functions have been used to quantitatively evaluate the spatial variability of soil structure but cannot characterize its specific geometry. Multi-point (MP) geostatistics can be used to consider both spatial correlation and the specific shape of objects. The algorithm, SNESIM, developed by Strebelle (2002) was used to simulate complex geological patterns, reflecting different scales of variability and types of heterogeneity. Soil macropores, especially earthworm burrows and root channels, are critical to preferential flow and transport in soils. Accurate simulation of soil macropore network can allow us better simulate soil hydraulic properties and address scaling issues of structured soils. However, little work has been done to simulate soil macropore network using MP geostatistics. 3D soil macropore network of an agricultural soil in Pennsylvania, Hagerstown silt loam, was extracted from the spatially exhaustive data collected with Micro Computing Tomography. 3D training image was scanned by 3D template to obtain the 3D patterns. Permeability of the simulated macropore network was calculated using Lattice-Boltzmann method. SNESIM was able to simulate different types of macropores, the earthworm burrows and inter-aggregate pores. However, SNESIM requires that training images must have a stationary character, which may limit its ability to simulate soil macropore network. SNESIM is still very computationally consuming for the 3D structure simulation. While computationally expensive, MP geostatistics has great potential for simulating 3D soil macropore network, which is useful to understand and predict the hydraulic behavior of structured soils.

  18. 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.

  19. 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.

  20. Menstrual cycle effects on selective attention and its underlying cortical networks.

    PubMed

    Thimm, M; Weis, S; Hausmann, M; Sturm, W

    2014-01-31

    It was the aim of the present study to investigate menstrual cycle effects on selective attention and its underlying functional cerebral networks. Twenty-one healthy, right-handed, normally cycling women were investigated by means of functional magnetic resonance imaging using a go/no-go paradigm during the menstrual, follicular and luteal phase. On the behavioral level there was a significant interaction between visual half field and cycle phase with reaction times to right-sided compared to left-sided stimuli being faster in the menstrual compared to the follicular phase. These results might argue for a more pronounced functional cerebral asymmetry toward the left hemisphere in selective attention during the menstrual phase with low estradiol and progesterone levels. Functional imaging, however, did not reveal clear-cut menstrual phase-related changes in activation pattern in parallel to these behavioral findings. A functional connectivity analysis identified differences between the menstrual and the luteal phase: During the menstrual phase, left inferior parietal cortex showed a stronger negative correlation with the right middle frontal gyrus while the left medial frontal cortex showed a stronger negative correlation with the left middle frontal gyrus. These results can serve as further evidence of a modulatory effect of steroid hormones on networks of lateralized cognitive functions not only by interhemispheric inhibition but also by affecting intrahemispheric functional connectivity.

  1. Aberrant development and plasticity of excitatory visual cortical networks in the absence of cpg15.

    PubMed

    Picard, Nathalie; Leslie, Jennifer H; Trowbridge, Sara K; Subramanian, Jaichandar; Nedivi, Elly; Fagiolini, Michela

    2014-03-01

    During development, experience plays a crucial role in sculpting neuronal connections. Patterned neural activity guides formation of functional neural circuits through the selective stabilization of some synapses and the pruning of others. Activity-regulated factors are fundamental to this process, but their roles in synapse stabilization and maturation is still poorly understood. CPG15, encoded by the activity-regulated gene candidate plasticity gene 15, is a small, glycosylphosphatidylinositol (GPI)-linked, extracellular protein that promotes synapse stabilization. Here we show that global knock-out of cpg15 results in abnormal postnatal development of the excitatory network in visual cortex and an associated disruption in development of visual receptive field properties. In addition, whereas repeated stimulation induced potentiation and depression in wild-type mice, the depression was slower in cpg15 knock-out mice, suggesting impairment in short-term depression-like mechanisms. These findings establish the requirement for cpg15 in activity-dependent development of the visual system and demonstrate the importance of timely excitatory network development for normal visual function. PMID:24599452

  2. Aberrant Development and Plasticity of Excitatory Visual Cortical Networks in the Absence of cpg15

    PubMed Central

    Picard, Nathalie; Leslie, Jennifer H.; Trowbridge, Sara K.; Subramanian, Jaichandar; Nedivi, Elly

    2014-01-01

    During development, experience plays a crucial role in sculpting neuronal connections. Patterned neural activity guides formation of functional neural circuits through the selective stabilization of some synapses and the pruning of others. Activity-regulated factors are fundamental to this process, but their roles in synapse stabilization and maturation is still poorly understood. CPG15, encoded by the activity-regulated gene candidate plasticity gene 15, is a small, glycosylphosphatidylinositol (GPI)-linked, extracellular protein that promotes synapse stabilization. Here we show that global knock-out of cpg15 results in abnormal postnatal development of the excitatory network in visual cortex and an associated disruption in development of visual receptive field properties. In addition, whereas repeated stimulation induced potentiation and depression in wild-type mice, the depression was slower in cpg15 knock-out mice, suggesting impairment in short-term depression-like mechanisms. These findings establish the requirement for cpg15 in activity-dependent development of the visual system and demonstrate the importance of timely excitatory network development for normal visual function. PMID:24599452

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

    PubMed

    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 synchronized

  4. Cortical network differences in the sighted versus early blind for recognition of human-produced action sounds

    PubMed Central

    Lewis, James W.; Frum, Chris; Brefczynski-Lewis, Julie A.; Talkington, William J.; Walker, Nathan A.; Rapuano, Kristina M.; Kovach, Amanda L.

    2012-01-01

    Both sighted and blind individuals can readily interpret meaning behind everyday real-world sounds. In sighted listeners, we previously reported that regions along the bilateral posterior superior temporal sulci (pSTS) and middle temporal gyri (pMTG) are preferentially activated when presented with recognizable action sounds. These regions have generally been hypothesized to represent primary loci for complex motion processing, including visual biological motion processing and audio-visual integration. However, it remained unclear whether, or to what degree, life-long visual experience might impact functions related to hearing perception or memory of sound-source actions. Using functional magnetic resonance imaging (fMRI), we compared brain regions activated in congenitally blind versus sighted listeners in response to hearing a wide range of recognizable human-produced action sounds (excluding vocalizations) versus unrecognized, backward-played versions of those sounds. Here we show that recognized human action sounds commonly evoked activity in both groups along most of the left pSTS/pMTG complex, though with relatively greater activity in the right pSTS/pMTG by the blind group. These results indicate that portions of the postero-lateral temporal cortices contain domain-specific hubs for biological and/or complex motion processing independent of sensory-modality experience. Contrasting the two groups, the sighted listeners preferentially activated bilateral parietal plus medial and lateral frontal networks, while the blind listeners preferentially activated left anterior insula plus bilateral anterior calcarine and medial occipital regions, including what would otherwise have been visual-related cortex. These global-level network differences suggest that blind and sighted listeners may preferentially use different memory retrieval strategies when attempting to recognize action sounds. PMID:21305666

  5. 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

  6. 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

  7. 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.

  8. Stimulus-induced reversal of information flow through a cortical network for animacy perception.

    PubMed

    Shultz, Sarah; van den Honert, Rebecca N; Engell, Andrew D; McCarthy, Gregory

    2015-01-01

    Decades of research have demonstrated that a region of the right fusiform gyrus (FG) and right posterior superior temporal sulcus (pSTS) responds preferentially to static faces and biological motion, respectively. Despite this view, both regions activate in response to both stimulus categories and to a range of other stimuli, such as goal-directed actions, suggesting that these regions respond to characteristics of animate agents more generally. Here we propose a neural model for animacy detection composed of processing streams that are initially differentially sensitive to cues signaling animacy, but that ultimately act in concert to support reasoning about animate agents. We use dynamic causal modeling, a measure of effective connectivity, to demonstrate that the directional flow of information between the FG and pSTS is initially dependent on the characteristics of the animate agent presented, a key prediction of our proposed network for animacy detection. PMID:24625785

  9. 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.

  10. 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.

  11. Cortical neuron activation induced by electromagnetic stimulation: a quantitative analysis via modelling and simulation.

    PubMed

    Wu, Tiecheng; Fan, Jie; Lee, Kim Seng; Li, Xiaoping

    2016-02-01

    Previous simulation works concerned with the mechanism of non-invasive neuromodulation has isolated many of the factors that can influence stimulation potency, but an inclusive account of the interplay between these factors on realistic neurons is still lacking. To give a comprehensive investigation on the stimulation-evoked neuronal activation, we developed a simulation scheme which incorporates highly detailed physiological and morphological properties of pyramidal cells. The model was implemented on a multitude of neurons; their thresholds and corresponding activation points with respect to various field directions and pulse waveforms were recorded. The results showed that the simulated thresholds had a minor anisotropy and reached minimum when the field direction was parallel to the dendritic-somatic axis; the layer 5 pyramidal cells always had lower thresholds but substantial variances were also observed within layers; reducing pulse length could magnify the threshold values as well as the variance; tortuosity and arborization of axonal segments could obstruct action potential initiation. The dependence of the initiation sites on both the orientation and the duration of the stimulus implies that the cellular excitability might represent the result of the competition between various firing-capable axonal components, each with a unique susceptibility determined by the local geometry. Moreover, the measurements obtained in simulation intimately resemble recordings in physiological and clinical studies, which seems to suggest that, with minimum simplification of the neuron model, the cable theory-based simulation approach can have sufficient verisimilitude to give quantitatively accurate evaluation of cell activities in response to the externally applied field. PMID:26719168

  12. 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.

  13. 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.

  14. Stimulus-induced visual cortical networks are recapitulated by spontaneous local and interareal synchronization

    PubMed Central

    Lewis, Christopher M.; Fries, Pascal

    2016-01-01

    Intrinsic covariation of brain activity has been studied across many levels of brain organization. Between visual areas, neuronal activity covaries primarily among portions with similar retinotopic selectivity. We hypothesized that spontaneous interareal coactivation is subserved by neuronal synchronization. We performed simultaneous high-density electrocorticographic recordings across the dorsal aspect of several visual areas in one hemisphere in each of two awake monkeys to investigate spatial patterns of local and interareal synchronization. We show that stimulation-induced patterns of interareal coactivation were reactivated in the absence of stimulation for the visual quadrant covered. Reactivation occurred through both interareal cofluctuation of local activity and interareal phase synchronization. Furthermore, the trial-by-trial covariance of the induced responses recapitulated the pattern of interareal coupling observed during stimulation, i.e., the signal correlation. Reactivation-related synchronization showed distinct peaks in the theta, alpha, and gamma frequency bands. During passive states, this rhythmic reactivation was augmented by specific patterns of arrhythmic correspondence. These results suggest that networks of intrinsic covariation observed at multiple levels and with several recording techniques are related to synchronization and that behavioral state may affect the structure of intrinsic dynamics. PMID:26787906

  15. Neuropathological and neuromorphometric abnormalities in bipolar disorder: view from the medial prefrontal cortical network.

    PubMed

    Savitz, Jonathan B; Price, Joseph L; Drevets, Wayne C

    2014-05-01

    The question of whether BD is primarily a developmental disorder or a progressive, neurodegenerative disorder remains unresolved. Here, we review the morphometric postmortem and neuroimaging literature relevant to the neuropathology of bipolar disorder (BD). We focus on the medial prefrontal cortex (mPFC) network, a key system in the regulation of emotional, behavioral, endocrine, and innate immunological responses to stress. We draw four main conclusions: the mPFC is characterized by (1) a decrease in volume, (2) reductions in neuronal size, and/or changes in neuronal density, (3) reductions in glial cell density, and (4) changes in gene expression. These data suggest the presence of dendritic atrophy of neurons and the loss of oligodendroglial cells in BD, although some data additionally suggest a reduction in the cell counts of specific subpopulations of GABAergic interneurons. Based on the weight of the postmortem and neuroimaging literature discussed herein, we favor a complex hypothesis that BD primarily constitutes a developmental disorder, but that additional, progressive, histopathological processes also are associated with recurrent or chronic illness. Conceivably BD may be best conceptualized as a progressive neurodevelopmental disorder.

  16. Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

    PubMed Central

    Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime

    2015-01-01

    Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611

  17. 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.

  18. 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.

  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. Decreased functional connectivity in dorsolateral prefrontal cortical networks in adult macaques with neonatal hippocampal lesions: Relations to visual working memory deficits.

    PubMed

    Meng, Yuguang; Hu, Xiaoping; Bachevalier, Jocelyne; Zhang, Xiaodong

    2016-10-01

    Neonatal hippocampal lesions in monkeys impairs normal performance on both relational and working memory tasks, suggesting that the early lesions have impacted the normal development of prefrontal-hippocampal functional interactions necessary for normal performance on these tasks. Given that working memory processes engage distributed neuronal networks associated with the prefrontal cortex, it is critical to explore the integrity of distributed neural networks of dorsolateral prefrontal cortex (dlPFC) following neonatal hippocampal lesions in monkeys. We used resting-state functional MRI to assess functional connectivity of dlPFC networks in monkeys with neonatal neurotoxic hippocampal lesion (Neo-Hibo, n=4) and sham-operated control animals (Neo-C, n=4). Significant differences in the patterns of dlPFC functional networks were found between Groups Neo-Hibo and Neo-C. The within-group maps and the between-group comparisons yielded a highly coherent picture showing altered interactions of core regions of the working memory network (medial prefrontal cortex and posterior parietal cortex) as well as the dorsal (fundus of superior temporal area and superior temporal cortex) and ventral (V4 and infero-temporal cortex) visual processing areas in animals with Neo-Hibo lesions. Correlations between functional connectivity changes and working memory impairment in the same animals were found only between the dlPFC and visual cortical areas (V4 and infero-temporal cortex). Thus, the impact of the neonatal hippocampal lesions extends to multiple cortical areas interconnected with the dlPFC.

  1. Cortical dynamics revisited.

    PubMed

    Singer, Wolf

    2013-12-01

    Recent discoveries on the organisation of the cortical connectome together with novel data on the dynamics of neuronal interactions require an extension of classical concepts on information processing in the cerebral cortex. These new insights justify considering the brain as a complex, self-organised system with nonlinear dynamics in which principles of distributed, parallel processing coexist with serial operations within highly interconnected networks. The observed dynamics suggest that cortical networks are capable of providing an extremely high-dimensional state space in which a large amount of evolutionary and ontogenetically acquired information can coexist and be accessible to rapid parallel search.

  2. Simulated evolution of signal transduction networks.

    PubMed

    Mobashir, Mohammad; Schraven, Burkhart; Beyer, Tilo

    2012-01-01

    Signal transduction is the process of routing information inside cells when receiving stimuli from their environment that modulate the behavior and function. In such biological processes, the receptors, after receiving the corresponding signals, activate a number of biomolecules which eventually transduce the signal to the nucleus. The main objective of our work is to develop a theoretical approach which will help to better understand the behavior of signal transduction networks due to changes in kinetic parameters and network topology. By using an evolutionary algorithm, we designed a mathematical model which performs basic signaling tasks similar to the signaling process of living cells. We use a simple dynamical model of signaling networks of interacting proteins and their complexes. We study the evolution of signaling networks described by mass-action kinetics. The fitness of the networks is determined by the number of signals detected out of a series of signals with varying strength. The mutations include changes in the reaction rate and network topology. We found that stronger interactions and addition of new nodes lead to improved evolved responses. The strength of the signal does not play any role in determining the response type. This model will help to understand the dynamic behavior of the proteins involved in signaling pathways. It will also help to understand the robustness of the kinetics of the output response upon changes in the rate of reactions and the topology of the network.

  3. Simulation studies of learning in an informon network.

    PubMed

    Uttley, A M

    1976-01-30

    A single informon reproduces classical conditioning to compound stimuli under a wide range of conditions during reinforcement and non-reinforcement; it also reproduces simple operant conditioning. A network of 210 informons with 8400 simultaneouslly varying pathways has been simulated; it can learn to recognize handprinted numerals. The networks studied must be more richly interconnected before they can reproduce more detailed behaviour of animals.

  4. Simulation of a National Computer Network in a Gaming Environment

    ERIC Educational Resources Information Center

    Segal, Ronald; O'Neal, Beverly

    1978-01-01

    A national computer services network simulation model was used in a 3-day gaming exercise involving 16 institutional teams who made decisions about their likely long-term network participation. Participants were able to react to others' decisions and actions, and to critical overriding political, economical, and organizational issues. (CMV)

  5. Neural network simulations of the nervous system.

    PubMed

    van Leeuwen, J L

    1990-01-01

    Present knowledge of brain mechanisms is mainly based on anatomical and physiological studies. Such studies are however insufficient to understand the information processing of the brain. The present new focus on neural network studies is the most likely candidate to fill this gap. The present paper reviews some of the history and current status of neural network studies. It signals some of the essential problems for which answers have to be found before substantial progress in the field can be made. PMID:2245130

  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. 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)

  8. Simulation studies of a wide area health care network.

    PubMed Central

    McDaniel, J. G.

    1994-01-01

    There is an increasing number of efforts to install wide area health care networks. Some of these networks are being built to support several applications over a wide user base consisting primarily of medical practices, hospitals, pharmacies, medical laboratories, payors, and suppliers. Although on-line, multi-media telecommunication is desirable for some purposes such as cardiac monitoring, store-and-forward messaging is adequate for many common, high-volume applications. Laboratory test results and payment claims, for example, can be distributed using electronic messaging networks. Several network prototypes have been constructed to determine the technical problems and to assess the effectiveness of electronic messaging in wide area health care networks. Our project, Health Link, developed prototype software that was able to use the public switched telephone network to exchange messages automatically, reliably and securely. The network could be configured to accommodate the many different traffic patterns and cost constraints of its users. Discrete event simulations were performed on several network models. Canonical star and mesh networks, that were composed of nodes operating at steady state under equal loads, were modeled. Both topologies were found to support the throughput of a generic wide area health care network. The mean message delivery time of the mesh network was found to be less than that of the star network. Further simulations were conducted for a realistic large-scale health care network consisting of 1,553 doctors, 26 hospitals, four medical labs, one provincial lab and one insurer. Two network topologies were investigated: one using predominantly peer-to-peer communication, the other using client-server communication.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:7949966

  9. PyNN: A Common Interface for Neuronal Network Simulators.

    PubMed

    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.

  10. PyNN: A Common Interface for Neuronal Network Simulators.

    PubMed

    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. Effectiveness of Simulation in a Hybrid and Online Networking Course.

    ERIC Educational Resources Information Center

    Cameron, Brian H.

    2003-01-01

    Reports on a study that compares the performance of students enrolled in two sections of a Web-based computer networking course: one utilizing a simulation package and the second utilizing a static, graphical software package. Analysis shows statistically significant improvements in performance in the simulation group compared to the…

  12. 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.

  13. Evaluation of Network-Based Minimally Invasive VR Surgery Simulator.

    PubMed

    Tagawa, Kazuyoshi; Tanaka, Hiromi T; Kurumi, Yoshimasa; Komori, Masaru; Morikawa, Shigehiro

    2016-01-01

    In this paper, we report a result of an experiment of a field trial of our network-based minimally invasive surgery simulator. In our previous paper, we proposed a network-based visuohaptic surgery training system for laparoscopic surgery. In addition, we proposed a volume-based haptic communication approach, which allows participants at remote sites on the network to simultaneously interact with the same target object in virtual environments presented by multi-level computer performance systems, by only exchanging a small set of manipulation parameters for the target object and additional packet for synchronization of status of binary tree and deformation of shared volume model. We implemented the approach into our network-based surgery simulator, and field trial of the simulator at three locations was performed. PMID:27046613

  14. 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.

  15. Electrical Conductivity in Transparent Silver Nanowire Networks: Simulations and Experiments

    NASA Astrophysics Data System (ADS)

    Sherrott, Michelle; Mutiso, Rose; Rathmell, Aaron; Wiley, Benjamin; Winey, Karen

    2012-02-01

    We model and experimentally measure the electrical conductivity of two-dimensional networks containing finite, conductive cylinders with aspect ratio ranging from 33 to 333. We have previously used our simulations to explore the effects of cylinder orientation and aspect ratio in three-dimensional composites, and now extend the simulation to consider two-dimensional silver nanowire networks. Preliminary results suggest that increasing the aspect ratio and area fraction of these rods significantly decreases the sheet resistance of the film. For all simulated aspect ratios, this sheet resistance approaches a constant value for high area fractions of rods. This implies that regardless of aspect ratio, there is a limiting minimum sheet resistance that is characteristic of the properties of the nanowires. Experimental data from silver nanowire networks will be incorporated into the simulations to define the contact resistance and corroborate experimentally measured sheet resistances of transparent thin films.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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. PMID:23507378

  2. 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

  3. Disrupted ERK signaling during cortical development leads to abnormal progenitor proliferation, neuronal and network excitability and behavior, modeling human neuro-cardio-facial-cutaneous and related syndromes.

    PubMed

    Pucilowska, Joanna; Puzerey, Pavel A; Karlo, J Colleen; Galán, Roberto F; Landreth, Gary E

    2012-06-20

    Genetic disorders arising from copy number variations in the ERK (extracellular signal-regulated kinase) MAP (mitogen-activated protein) kinases or mutations in their upstream regulators that result in neuro-cardio-facial-cutaneous syndromes are associated with developmental abnormalities, cognitive deficits, and autism. We developed murine models of these disorders by deleting the ERKs at the beginning of neurogenesis and report disrupted cortical progenitor generation and proliferation, which leads to altered cytoarchitecture of the postnatal brain in a gene-dose-dependent manner. We show that these changes are due to ERK-dependent dysregulation of cyclin D1 and p27(Kip1), resulting in cell cycle elongation, favoring neurogenic over self-renewing divisions. The precocious neurogenesis causes premature progenitor pool depletion, altering the number and distribution of pyramidal neurons. Importantly, loss of ERK2 alters the intrinsic excitability of cortical neurons and contributes to perturbations in global network activity. These changes are associated with elevated anxiety and impaired working and hippocampal-dependent memory in these mice. This study provides a novel mechanistic insight into the basis of cortical malformation which may provide a potential link to cognitive deficits in individuals with altered ERK activity.

  4. 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...

  5. Optically Connected Multiprocessors For Simulating Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Ghosh, Joydeep; Hwang, Kai

    1988-05-01

    This paper investigates the architectural requirements in simulating large neural networks using a highly parallel multiprocessor with distributed memory and optical interconnects. First, we model the structure of a neural network and the functional behavior of individual cells. These models are used to estimate the volume of messages that need to be exchanged among physical processors to simulate the weighted connections of the neural network. The distributed processor/memory organization is tailored to an electronic implementation for greater versatility and flexibility. Optical interconnects are used to satisfy the interprocessor communication bandwidth demands. The hybrid implementation attempts to balance the processing, memory and bandwidth demands in simulating asynchronous, value-passing models for cooperative parallel computation with self-learning capabilities.

  6. 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

  7. 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.

  8. Stochastic Simulation of Biomolecular Networks in Dynamic Environments

    PubMed Central

    Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G.

    2016-01-01

    Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. PMID:27248512

  9. Synthesis of recurrent neural networks for dynamical system simulation.

    PubMed

    Trischler, Adam P; D'Eleuterio, Gabriele M T

    2016-08-01

    We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamical system using backpropagation, then recast it as a recurrent network that replicates the original system's dynamics. After detailing this algorithm and its relation to earlier approaches, we present numerical examples that demonstrate its capabilities. One of the distinguishing features of our approach is that both the original dynamical systems and the recurrent networks that simulate them operate in continuous time.

  10. Decreased functional connectivity in dorsolateral prefrontal cortical networks in adult macaques with neonatal hippocampal lesions: Relations to visual working memory deficits.

    PubMed

    Meng, Yuguang; Hu, Xiaoping; Bachevalier, Jocelyne; Zhang, Xiaodong

    2016-10-01

    Neonatal hippocampal lesions in monkeys impairs normal performance on both relational and working memory tasks, suggesting that the early lesions have impacted the normal development of prefrontal-hippocampal functional interactions necessary for normal performance on these tasks. Given that working memory processes engage distributed neuronal networks associated with the prefrontal cortex, it is critical to explore the integrity of distributed neural networks of dorsolateral prefrontal cortex (dlPFC) following neonatal hippocampal lesions in monkeys. We used resting-state functional MRI to assess functional connectivity of dlPFC networks in monkeys with neonatal neurotoxic hippocampal lesion (Neo-Hibo, n=4) and sham-operated control animals (Neo-C, n=4). Significant differences in the patterns of dlPFC functional networks were found between Groups Neo-Hibo and Neo-C. The within-group maps and the between-group comparisons yielded a highly coherent picture showing altered interactions of core regions of the working memory network (medial prefrontal cortex and posterior parietal cortex) as well as the dorsal (fundus of superior temporal area and superior temporal cortex) and ventral (V4 and infero-temporal cortex) visual processing areas in animals with Neo-Hibo lesions. Correlations between functional connectivity changes and working memory impairment in the same animals were found only between the dlPFC and visual cortical areas (V4 and infero-temporal cortex). Thus, the impact of the neonatal hippocampal lesions extends to multiple cortical areas interconnected with the dlPFC. PMID:27063864

  11. 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.

  12. 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. PMID:25695269

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Task- and stimulus-related cortical networks in language production: Exploring similarity of MEG- and fMRI-derived functional connectivity.

    PubMed

    Liljeström, Mia; Stevenson, Claire; Kujala, Jan; Salmelin, Riitta

    2015-10-15

    account when assessing the correspondence between MEG and fMRI networks. Task-driven network hubs, evident in both MEG and fMRI, were found in cortical regions previously associated with language processing, including the posterior temporal cortex and the inferior frontal cortex. Network hubs related to stimulus-driven modulations, however, were found in regions related to object recognition and visual processing, including the lateral occipital cortex. Overall, the results depict a shift in network structure when moving from a task dependent modulation to a stimulus dependent modulation, revealing a reorganization of large-scale functional connectivity during task performance.

  18. Top-Down Feedback in an HMAX-Like Cortical Model of Object Perception Based on Hierarchical Bayesian Networks and Belief Propagation

    PubMed Central

    Dura-Bernal, Salvador; Wennekers, Thomas; Denham, Susan L.

    2012-01-01

    Hierarchical generative models, such as Bayesian networks, and belief propagation have been shown to provide a theoretical framework that can account for perceptual processes, including feedforward recognition and feedback modulation. The framework explains both psychophysical and physiological experimental data and maps well onto the hierarchical distributed cortical anatomy. However, the complexity required to model cortical processes makes inference, even using approximate methods, very computationally expensive. Thus, existing object perception models based on this approach are typically limited to tree-structured networks with no loops, use small toy examples or fail to account for certain perceptual aspects such as invariance to transformations or feedback reconstruction. In this study we develop a Bayesian network with an architecture similar to that of HMAX, a biologically-inspired hierarchical model of object recognition, and use loopy belief propagation to approximate the model operations (selectivity and invariance). Crucially, the resulting Bayesian network extends the functionality of HMAX by including top-down recursive feedback. Thus, the proposed model not only achieves successful feedforward recognition invariant to noise, occlusions, and changes in position and size, but is also able to reproduce modulatory effects such as illusory contour completion and attention. Our novel and rigorous methodology covers key aspects such as learning using a layerwise greedy algorithm, combining feedback information from multiple parents and reducing the number of operations required. Overall, this work extends an established model of object recognition to include high-level feedback modulation, based on state-of-the-art probabilistic approaches. The methodology employed, consistent with evidence from the visual cortex, can be potentially generalized to build models of hierarchical perceptual organization that include top-down and bottom-up interactions, for

  19. 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…

  20. 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.

  1. 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.

  2. 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...

  3. Experimental simulation of quantum graphs by microwave networks.

    PubMed

    Hul, Oleh; Bauch, Szymon; Pakoński, Prot; Savytskyy, Nazar; Zyczkowski, Karol; Sirko, Leszek

    2004-05-01

    We present the results of experimental and theoretical study of irregular, tetrahedral microwave networks consisting of coaxial cables (annular waveguides) connected by T joints. The spectra of the networks were measured in the frequency range 0.0001-16 GHz in order to obtain their statistical properties such as the integrated nearest neighbor spacing distribution and the spectral rigidity Delta(3) (L). The comparison of our experimental and theoretical results shows that microwave networks can simulate quantum graphs with time reversal symmetry. In particular, we use the spectra of the microwave networks to study the periodic orbits of the simulated quantum graphs. We also present experimental study of directional microwave networks consisting of coaxial cables and Faraday isolators for which the time reversal symmetry is broken. In this case our experimental results indicate that spectral statistics of directional microwave networks deviate from predictions of Gaussian orthogonal ensembles in random matrix theory approaching, especially for small eigenfrequency spacing s, results for Gaussian unitary ensembles. Experimental results are supported by the theoretical analysis of directional graphs.

  4. Improved Element Production Networks for Type Ia Supernova Simulations

    NASA Astrophysics Data System (ADS)

    Chupryna, Viktor; Budiardja, Reuben; Guidry, Mike

    2004-11-01

    The cosmological implications of Type Ia supernovae depend crucially on their assumed standardizable candle properties. Therefore it is highly desirable to understand the detailed mechanism of the Ia supernova explosion from a fundamental point of view. There is some consensus that Type Ia supernovae result when a white dwarf in a binary star system is driven to the Chandrasekhar limit by accretion from a companion star, with the resulting instability triggering a thermonuclear runaway that burns most of the white dwarf to iron and nickel. However, the details of this mechanism are very poorly understood. The energy released in the supernovae comes primarily from the element and energy production network that powers the thermonuclear flash, but in most simulations of Ia explosions this network and its coupling to the hydrodynamics are treated only in an approximate fashion. In this presentation we shall discuss our current efforts to incorporate an improved description of energy generation networks coupled to hydrodynamics in Type Ia supernova simulations.

  5. SIMULATING BIOCHEMICAL SIGNALING NETWORKS IN COMPLEX MOVING GEOMETRIES.

    PubMed

    Strychalski, Wanda; Adalsteinsson, David; Elston, Timothy C

    2010-01-01

    Signaling networks regulate cellular responses to environmental stimuli through cascades of protein interactions. External signals can trigger cells to polarize and move in a specific direction. During migration, spatially localized activity of proteins is maintained. To investigate the effects of morphological changes on intracellular signaling, we developed a numerical scheme consisting of a cut cell finite volume spatial discretization coupled with level set methods to simulate the resulting advection-reaction-diffusion system. We then apply the method to several biochemical reaction networks in changing geometries. We found that a Turing instability can develop exclusively by cell deformations that maintain constant area. For a Turing system with a geometry-dependent single or double peak solution, simulations in a dynamically changing geometry suggest that a single peak solution is the only stable one, independent of the oscillation frequency. The method is also applied to a model of a signaling network in a migrating fibroblast. PMID:24086102

  6. 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.

  7. The Network Modification (NeMo) Tool: Elucidating the Effect of White Matter Integrity Changes on Cortical and Subcortical Structural Connectivity

    PubMed Central

    Maruta, Jun; Relkin, Norman; Raj, Ashish

    2013-01-01

    Abstract Accurate prediction of brain dysfunction caused by disease or injury requires the quantification of resultant neural connectivity changes compared with the normal state. There are many methods with which to assess anatomical changes in structural or diffusion magnetic resonance imaging, but most overlook the topology of white matter (WM) connections that make up the healthy brain network. Here, a new neuroimaging software pipeline called the Network Modification (NeMo) Tool is presented that associates alterations in WM integrity with expected changes in neural connectivity between gray matter regions. The NeMo Tool uses a large reference set of healthy tractograms to assess implied network changes arising from a particular pattern of WM alteration on a region- and network-wise level. In this way, WM integrity changes can be extrapolated to the cortices and deep brain nuclei, enabling assessment of functional and cognitive alterations. Unlike current techniques that assess network dysfunction, the NeMo tool does not require tractography in pathological brains for which the algorithms may be unreliable or diffusion data are unavailable. The versatility of the NeMo Tool is demonstrated by applying it to data from patients with Alzheimer's disease, fronto-temporal dementia, normal pressure hydrocephalus, and mild traumatic brain injury. This tool fills a gap in the quantitative neuroimaging field by enabling an investigation of morphological and functional implications of changes in structural WM integrity. PMID:23855491

  8. Molecular Simulations of Actomyosin Network Self-Assembly and Remodeling

    NASA Astrophysics Data System (ADS)

    Komianos, James; Popov, Konstantin; Papoian, Garegin; Papoian Lab Team

    Actomyosin networks are an integral part of the cytoskeleton of eukaryotic cells and play an essential role in determining cellular shape and movement. Actomyosin network growth and remodeling in vivo is based on a large number of chemical and mechanical processes, which are mutually coupled and spatially and temporally resolved. To investigate the fundamental principles behind the self-organization of these networks, we have developed a detailed mechanochemical, stochastic model of actin filament growth dynamics, at a single-molecule resolution, where the nonlinear mechanical rigidity of filaments and their corresponding deformations under internally and externally generated forces are taken into account. Our work sheds light on the interplay between the chemical and mechanical processes governing the cytoskeletal dynamics, and also highlights the importance of diffusional and active transport phenomena. Our simulations reveal how different actomyosin micro-architectures emerge in response to varying the network composition. Support from NSF Grant CHE-1363081.

  9. Brian: a simulator for spiking neural networks in python.

    PubMed

    Goodman, Dan; Brette, Romain

    2008-01-01

    "Brian" is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience. PMID:19115011

  10. 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.

  11. 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.

  12. 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.

  13. Computer Simulations of Bottle Brushes: From Melts to Soft Networks

    DOE PAGESBeta

    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 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

  14. 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.

  15. Real-time hierarchically distributed processing network interaction simulation

    NASA Technical Reports Server (NTRS)

    Zimmerman, W. F.; Wu, C.

    1987-01-01

    The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

  16. Estimation of Thalamocortical and Intracortical Network Models from Joint Thalamic Single-Electrode and Cortical Laminar-Electrode Recordings in the Rat Barrel System

    PubMed Central

    Blomquist, Patrick; Devor, Anna; Indahl, Ulf G.; Ulbert, Istvan; Einevoll, Gaute T.; Dale, Anders M.

    2009-01-01

    A new method is presented for extraction of population firing-rate models for both thalamocortical and intracortical signal transfer based on stimulus-evoked data from simultaneous thalamic single-electrode and cortical recordings using linear (laminar) multielectrodes in the rat barrel system. Time-dependent population firing rates for granular (layer 4), supragranular (layer 2/3), and infragranular (layer 5) populations in a barrel column and the thalamic population in the homologous barreloid are extracted from the high-frequency portion (multi-unit activity; MUA) of the recorded extracellular signals. These extracted firing rates are in turn used to identify population firing-rate models formulated as integral equations with exponentially decaying coupling kernels, allowing for straightforward transformation to the more common firing-rate formulation in terms of differential equations. Optimal model structures and model parameters are identified by minimizing the deviation between model firing rates and the experimentally extracted population firing rates. For the thalamocortical transfer, the experimental data favor a model with fast feedforward excitation from thalamus to the layer-4 laminar population combined with a slower inhibitory process due to feedforward and/or recurrent connections and mixed linear-parabolic activation functions. The extracted firing rates of the various cortical laminar populations are found to exhibit strong temporal correlations for the present experimental paradigm, and simple feedforward population firing-rate models combined with linear or mixed linear-parabolic activation function are found to provide excellent fits to the data. The identified thalamocortical and intracortical network models are thus found to be qualitatively very different. While the thalamocortical circuit is optimally stimulated by rapid changes in the thalamic firing rate, the intracortical circuits are low-pass and respond most strongly to slowly varying

  17. 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.

  18. 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

  19. 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). PMID:14761255

  20. Code generation: a strategy for neural network simulators.

    PubMed

    Goodman, Dan F M

    2010-10-01

    We demonstrate a technique for the design of neural network simulation software, runtime code generation. This technique can be used to give the user complete flexibility in specifying the mathematical model for their simulation in a high level way, along with the speed of code written in a low level language such as C+ +. It can also be used to write code only once but target different hardware platforms, including inexpensive high performance graphics processing units (GPUs). Code generation can be naturally combined with computer algebra systems to provide further simplification and optimisation of the generated code. The technique is quite general and could be applied to any simulation package. We demonstrate it with the 'Brian' simulator ( http://www.briansimulator.org ).

  1. 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.

  2. 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.

  3. 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.

  4. Simulating Geomagnetically Induced Currents in the Irish Power Network

    NASA Astrophysics Data System (ADS)

    Jones, A. G.; Blake, S. P.; Gallagher, P.; McCauley, J.; Hogg, C.; Beggan, C.; Thomson, A. W. P.; Kelly, G.; Walsh, S.

    2014-12-01

    Geomagnetic storms are known to cause geomagnetically induced currents (GICs) which can damage or destroy transformers on power grids. Previous studies have examined the vulnerability of power networks in countries such as the UK, New Zealand, Canada and South Africa. Here we describe the application of a British Geological Survey (BGS) thin-sheet conductivity model to compute the geo-electric field from the variation of the magnetic field, in order to better quantify the risk of space weather to Ireland's power network. This was achieved using DIAS magnetotelluric data from across Ireland. As part of a near-real-time warning package for Eirgrid (who oversee Ireland's transmission network), severe storm events such as the Halloween 2003 storm and the corresponding GIC flows at transformers are simulated.

  5. 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

  6. Statistical Comparison of Spike Responses to Natural Stimuli in Monkey Area V1 With Simulated Responses of a Detailed Laminar Network Model for a Patch of V1

    PubMed Central

    Schuch, Klaus; Logothetis, Nikos K.; Maass, Wolfgang

    2011-01-01

    A major goal of computational neuroscience is the creation of computer models for cortical areas whose response to sensory stimuli resembles that of cortical areas in vivo in important aspects. It is seldom considered whether the simulated spiking activity is realistic (in a statistical sense) in response to natural stimuli. Because certain statistical properties of spike responses were suggested to facilitate computations in the cortex, acquiring a realistic firing regimen in cortical network models might be a prerequisite for analyzing their computational functions. We present a characterization and comparison of the statistical response properties of the primary visual cortex (V1) in vivo and in silico in response to natural stimuli. We recorded from multiple electrodes in area V1 of 4 macaque monkeys and developed a large state-of-the-art network model for a 5 × 5-mm patch of V1 composed of 35,000 neurons and 3.9 million synapses that integrates previously published anatomical and physiological details. By quantitative comparison of the model response to the “statistical fingerprint” of responses in vivo, we find that our model for a patch of V1 responds to the same movie in a way which matches the statistical structure of the recorded data surprisingly well. The deviation between the firing regimen of the model and the in vivo data are on the same level as deviations among monkeys and sessions. This suggests that, despite strong simplifications and abstractions of cortical network models, they are nevertheless capable of generating realistic spiking activity. To reach a realistic firing state, it was not only necessary to include both N-methyl-d-aspartate and GABAB synaptic conductances in our model, but also to markedly increase the strength of excitatory synapses onto inhibitory neurons (>2-fold) in comparison to literature values, hinting at the importance to carefully adjust the effect of inhibition for achieving realistic dynamics in current network

  7. Design of a neural network simulator on a transputer array

    NASA Technical Reports Server (NTRS)

    Mcintire, Gary; Villarreal, James; Baffes, Paul; Rua, Monica

    1987-01-01

    A brief summary of neural networks is presented which concentrates on the design constraints imposed. Major design issues are discussed together with analysis methods and the chosen solutions. Although the system will be capable of running on most transputer architectures, it currently is being implemented on a 40-transputer system connected to a toroidal architecture. Predictions show a performance level equivalent to that of a highly optimized simulator running on the SX-2 supercomputer.

  8. Uncemented Total Hip Replacement Stem Loosening after Long Term Compressive Stress Application: A Simulated FEA Study of Cortical Bone Remodeling

    NASA Astrophysics Data System (ADS)

    Jung, Duk-Young; Tsutsumi, Sadami; Nakai, Ryusuke; Ikeuchi, Ken; Sekel, Ron

    The purpose of this study is to predict with the use of FEA, the differing predisposition to cortical bone resorption and subsequent distal migration of an un-cemented femoral hip replacement stem subjected to long term biomechanical high compressive stresses, while varying the load angles, the material properties of the stem, and the stem length. A two-dimensional hip model was constructed to estimate the minimum principle stresses (P3) and migration magnitudes. Bone remodeling at the interface between the bone and the prosthesis was performed by comparison of the local compressive stress to physiological stress values governing bone resorption. With respect to load angles, migrations of the hip prosthesis did not occur with load angles between 63° and 74° load angle in relation to the longitudinal axis of the bony femur, as the compressive stress generated on the cortical bone was under the criteria threshold for bone resorption (-50MPa). In addition, the magnitude of migration (17%decrease) was relatively more sensitive to changes in stem length than those (92%decrease) of changes of material properties. In conclusion, using an FEA model for bone remodeling, based on the high compressive stresses exerted on distal cortical bone, it is possible to estimate migration magnitudes of cementless hip prostheses in the long term. The load angles have been shown to be an important parameter affecting the migration magnitudes and furthermore, it can be demonstrated that the stiffer materials and reduction of stem length can decrease the migration of cementless hip prosthesis in the long term.

  9. Cortical thinning in psychopathy

    PubMed Central

    Ly, Martina; Motzkin, Julian C.; Philippi, Carissa L.; Kirk, Gregory R.; Newman, Joseph P.; Kiehl, Kent A.; Koenigs, Michael

    2013-01-01

    Objective Psychopathy is a personality disorder associated with severely antisocial behavior and a host of cognitive and affective deficits. The neuropathological basis of the disorder has not been clearly established. Cortical thickness is a sensitive measure of brain structure that has been used to identify neurobiological abnormalities in a number of psychiatric disorders. The purpose of this study is to evaluate cortical thickness and corresponding functional connectivity in criminal psychopaths. Method Using T1 MRI data, we computed cortical thickness maps in a sample of adult male prison inmates selected based on psychopathy diagnosis (n=21 psychopathic inmates, n=31 non-psychopathic inmates). Using rest-fMRI data from a subset of these inmates (n=20 psychopathic inmates, n=20 non-psychopathic inmates), we then computed functional connectivity within networks exhibiting significant thinning among psychopaths. Results Relative to non-psychopaths, psychopaths exhibited significantly thinner cortex in a number of regions, including left insula and dorsal anterior cingulate cortex, bilateral precentral gyrus, bilateral anterior temporal cortex, and right inferior frontal gyrus. These neurostructural differences were not due to differences in age, IQ, or substance abuse. Psychopaths also exhibited a corresponding reduction in functional connectivity between left insula and left dorsal anterior cingulate cortex. Conclusions Psychopathy is associated with a distinct pattern of cortical thinning and reduced functional connectivity. PMID:22581200

  10. Impaired gamma-band activity during perceptual organization in adults with autism spectrum disorders: evidence for dysfunctional network activity in frontal-posterior cortices.

    PubMed

    Sun, Limin; Grützner, Christine; Bölte, Sven; Wibral, Michael; Tozman, Tahmine; Schlitt, Sabine; Poustka, Fritz; Singer, Wolf; Freitag, Christine M; Uhlhaas, Peter J

    2012-07-11

    Current theories of the pathophysiology of autism spectrum disorders (ASD) have focused on abnormal temporal coordination of neural activity in cortical circuits as a core impairment of the disorder. In the current study, we examined the possibility that gamma-band activity may be crucially involved in aberrant brain functioning in ASD. Magneto-encephalographic (MEG) data were recorded from 13 adult human participants with ASD and 16 controls during the presentation of Mooney faces. MEG data were analyzed in the 25-150 Hz frequency range and a beamforming approach was used to identify the sources of spectral power. Participants with ASD showed elevated reaction times and reduced detection rates during the perception of upright Mooney faces, while responses to inverted stimuli were in the normal range. Impaired perceptual organization in the ASD group was accompanied by a reduction in both the amplitude and phase locking of gamma-band activity. A beamforming approach identified distinct networks during perceptual organization in controls and participants with ASD. In controls, perceptual organization of Mooney faces involved increased 60-120 Hz activity in a frontoparietal network, while in the ASD group stronger activation was found in visual regions. These findings highlight the contribution of impaired gamma-band activity toward complex visual processing in ASD, suggesting atypical modulation of high-frequency power in frontoposterior networks.

  11. Detection, eye-hand coordination and virtual mobility performance in simulated vision for a cortical visual prosthesis device

    NASA Astrophysics Data System (ADS)

    Srivastava, Nishant R.; Troyk, Philip R.; Dagnelie, Gislin

    2009-06-01

    In order to assess visual performance using a future cortical prosthesis device, the ability of normally sighted and low vision subjects to adapt to a dotted 'phosphene' image was studied. Similar studies have been conduced in the past and adaptation to phosphene maps has been shown but the phosphene maps used have been square or hexagonal in pattern. The phosphene map implemented for this testing is what is expected from a cortical implantation of the arrays of intracortical electrodes, generating multiple phosphenes. The dotted image created depends upon the surgical location of electrodes decided for implantation and the expected cortical response. The subjects under tests were required to perform tasks requiring visual inspection, eye-hand coordination and way finding. The subjects did not have any tactile feedback and the visual information provided was live dotted images captured by a camera on a head-mounted low vision enhancing system and processed through a filter generating images similar to the images we expect the blind persons to perceive. The images were locked to the subject's gaze by means of video-based pupil tracking. In the detection and visual inspection task, the subject scanned a modified checkerboard and counted the number of square white fields on a square checkerboard, in the eye-hand coordination task, the subject placed black checkers on the white fields of the checkerboard, and in the way-finding task, the subjects maneuvered themselves through a virtual maze using a game controller. The accuracy and the time to complete the task were used as the measured outcome. As per the surgical studies by this research group, it might be possible to implant up to 650 electrodes; hence, 650 dots were used to create images and performance studied under 0% dropout (650 dots), 25% dropout (488 dots) and 50% dropout (325 dots) conditions. It was observed that all the subjects under test were able to learn the given tasks and showed improvement in

  12. 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.

  13. Simulation globale et entreprise: Il faut savoir "reseauner" (Global Simulation and Enterprise: Knowing How to Network).

    ERIC Educational Resources Information Center

    Henry, Jean-Baptiste

    1994-01-01

    A simulation exercise consisting of 12 stages corresponding to the life-stages of an enterprise is used as a language-learning technique for business French. The exercise develops both language and networking skills while presenting a creative challenge to students. (MSE)

  14. 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.

  15. Primitive chain network simulations for entangled DNA solutions

    NASA Astrophysics Data System (ADS)

    Masubuchi, Yuichi; Furuichi, Kenji; Horio, Kazushi; Uneyama, Takashi; Watanabe, Hiroshi; Ianniruberto, Giovanni; Greco, Francesco; Marrucci, Giuseppe

    2009-09-01

    Molecular theories for polymer rheology are based on conformational dynamics of the polymeric chain. Hence, measurements directly related to molecular conformations appear more appealing than indirect ones obtained from rheology. In this study, primitive chain network simulations are compared to experimental data of entangled DNA solutions [Teixeira et al., Macromolecules 40, 2461 (2007)]. In addition to rheological comparisons of both linear and nonlinear viscoelasticities, a molecular extension measure obtained by Teixeira et al. through fluorescent microscopy is compared to simulations, in terms of both averages and distributions. The influence of flow on conformational distributions has never been simulated for the case of entangled polymers, and how DNA molecular individualism extends to the entangled regime is not known. The linear viscoelastic response and the viscosity growth curve in the nonlinear regime are found in good agreement with data for various DNA concentrations. Conversely, the molecular extension measure shows significant departures, even under equilibrium conditions. The reason for such discrepancies remains unknown.

  16. A simulation study of TCP performance in ATM networks

    SciTech Connect

    Chien Fang; Chen, Helen; Hutchins, J.

    1994-08-01

    This paper presents a simulation study of TCP performance over congested ATM local area networks. We simulated a variety of schemes for congestion control for ATM LANs, including a simple cell-drop, a credit-based flow control scheme that back-pressures individual VC`s, and two selective cell-drop schemes. Our simulation results for congested ATM LANs show the following: (1) TCP performance is poor under simple cell-drop, (2) the selective cell-drop schemes increase effective link utilization and result in higher TCP throughputs than the simple cell-drop scheme, and (3) the credit-based flow control scheme eliminates cell loss and achieves maximum performance and effective link utilization.

  17. Analysis of an Experimental Cortical Network: ii) Connections of Visual Areas 17 and 18 After Neonatal Injections of Ibotenic Acid

    PubMed Central

    Innocenti, G. M.; Berbel, P.

    1991-01-01

    Lesions of cortical areas 17 and 18 were produced in newborn kittens by local injections of the excitotoxin ibotenic acid. In the adult this results in a microcortex which consists of superficial layers I, II and III, in the absence of granular and infragranular layers. Horseradish peroxidase, alone or wheat germ agglutinin conjugated, was injected in the microcortex or in the contralateral, intact areas 17 and 18. The microcortex maintains several connections characteristic of normal areas 17 and 18 of the cat. It receives afferents from the dLGN, and several visual areas of the ipsilateral and contralateral hemisphere. However, it has lost its projections to dLGN, superior colliculus, and, at least in part, those to contralateral visual areas. Thus some parts of the microcortex receive from, but do not project into, the corpus callosum. In addition, the microcortex maintains afferents from ipsilateral and contralateral auditory areas AI and AII which are normally eliminated in development. PMID:1714302

  18. 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.

  19. 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

  20. Quantum versus simulated annealing in wireless interference network optimization.

    PubMed

    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. Quantum versus simulated annealing in wireless interference network optimization.

    PubMed

    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.

  2. Multifractional analysis and simulation of the global meteorological network

    SciTech Connect

    Tessier, Y.; Lovejoy, S.; Schertzer, D.

    1994-12-01

    Taking the example of the meteorological measuring network, it is shown how the density of stations can be characterized by multifractral analysis techniques are applied (including new ones designed to take into account the spherical geometry) to systematically test the limitsand types of network multiscaling. These techniques start with a network density defined by grids or circles and proceed to systematically degrade their resolution (no a priori scaling assumptions are necessary). The multiscale is found to hold over roughly the range 20 000 to 200 km (limited by the finite number of stations-here about 8000). Special attention is paid to qualitative changes in the scaling behavior occurring at very low and high density regions that the authors argue are associated with multifractural phase transitions. It is argued that the density was produced by a universal multifractal process, and the three corresponding universal multifractal parameters are estimated. The minimum and maximum orders of singularities present in the network are estimated, as well as the minimum- and maximum-order statistical moments that can be reliably estimated. The results are then used to simulate the effects of the finite number of stations on a network with the same statistical properties, and hence to quantitatively show that the observed breaks in the multiscaling can be accounted for by the finiteness. A growing number of geophysical fields have been shown to exhibit multiscaling properties over various ranges, and in this paper it is discussed how the bias introduced by the network clustering can be removed by new `multifractal objective analysis` procedures.

  3. 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

  4. Horizontal integration and cortical dynamics.

    PubMed

    Gilbert, C D

    1992-07-01

    We have discussed several results that lead to a view that cells in the visual system are endowed with dynamic properties, influenced by context, expectation, and long-term modifications of the cortical network. These observations will be important for understanding how neuronal ensembles produce a system that perceives, remembers, and adapts to injury. The advantage to being able to observe changes at early stages in a sensory pathway is that one may be able to understand the way in which neuronal ensembles encode and represent images at the level of their receptive field properties, of cortical topographies, and of the patterns of connections between cells participating in a network.

  5. Adaptive hybrid simulations for multiscale stochastic reaction networks

    SciTech Connect

    Hepp, Benjamin; Gupta, Ankit; Khammash, Mustafa

    2015-01-21

    The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.

  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. Large-Scale, High-Resolution Multielectrode-Array Recording Depicts Functional Network Differences of Cortical and Hippocampal Cultures

    PubMed Central

    Ito, Shinya; Yeh, Fang-Chin; Hiolski, Emma; Rydygier, Przemyslaw; Gunning, Deborah E.; Hottowy, Pawel; Timme, Nicholas; Litke, Alan M.; Beggs, John M.

    2014-01-01

    Understanding the detailed circuitry of functioning neuronal networks is one of the major goals of neuroscience. Recent improvements in neuronal recording techniques have made it possible to record the spiking activity from hundreds of neurons simultaneously with sub-millisecond temporal resolution. Here we used a 512-channel multielectrode array system to record the activity from hundreds of neurons in organotypic cultures of cortico-hippocampal brain slices from mice. To probe the network structure, we employed a wavelet transform of the cross-correlogram to categorize the functional connectivity in different frequency ranges. With this method we directly compare, for the first time, in any preparation, the neuronal network structures of cortex and hippocampus, on the scale of hundreds of neurons, with sub-millisecond time resolution. Among the three frequency ranges that we investigated, the lower two frequency ranges (gamma (30–80 Hz) and beta (12–30 Hz) range) showed similar network structure between cortex and hippocampus, but there were many significant differences between these structures in the high frequency range (100–1000 Hz). The high frequency networks in cortex showed short tailed degree-distributions, shorter decay length of connectivity density, smaller clustering coefficients, and positive assortativity. Our results suggest that our method can characterize frequency dependent differences of network architecture from different brain regions. Crucially, because these differences between brain regions require millisecond temporal scales to be observed and characterized, these results underscore the importance of high temporal resolution recordings for the understanding of functional networks in neuronal systems. PMID:25126851

  8. 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.

  9. 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.

  10. Increased functional connectivity between cortical hand areas and praxis network associated with training-related improvements in non-dominant hand precision drawing.

    PubMed

    Philip, Benjamin A; Frey, Scott H

    2016-07-01

    Chronic forced use of the non-dominant left hand yields substantial improvements in the precision and quality of writing and drawing. These changes may arise from increased access by the non-dominant (right) hemisphere to dominant (left) hemisphere mechanisms specialized for end-point precision control. To evaluate this prediction, 22 healthy right-handed adults underwent resting state functional connectivity (FC) MRI scans before and after 10 days of training on a left hand precision drawing task. 89% of participants significantly improved left hand speed, accuracy, and smoothness. Smoothness gains were specific to the trained left hand and persistent: 6 months after training, 71% of participants exhibited above-baseline movement smoothness. Contrary to expectations, we found no evidence of increased FC between right and left hemisphere hand areas. Instead, training-related improvements in left hand movement smoothness were associated with increased FC between both sensorimotor hand areas and a left-lateralized parieto-prefrontal network implicated in manual praxis. By contrast, skill retention at 6 months was predicted by changes including decreased FC between the representation of the trained left hand and bilateral sensorimotor, parietal, and premotor cortices, possibly reflecting consolidation and a disengagement of early learning processes. These data indicate that modest amounts of training (<200min total) can induce substantial, persistent improvements the precision and quality of non-dominant hand control in healthy adults, supported by strengthened connectivity between bilateral sensorimotor hand areas and a left-lateralized parieto-prefrontal praxis network. PMID:27212059

  11. Task-dependent modulation of functional connectivity between hand motor cortices and neuronal networks underlying language and music: a transcranial magnetic stimulation study in humans.

    PubMed

    Sparing, R; Meister, I G; Wienemann, M; Buelte, D; Staedtgen, M; Boroojerdi, B

    2007-01-01

    Although language functions are, in general, attributed to the left hemisphere, it is still a matter of debate to what extent the cognitive functions underlying the processing of music are lateralized in the human brain. To investigate hemispheric specialization we evaluated the effect of different overt musical and linguistic tasks on the excitability of both left and right hand motor cortices using transcranial magnetic stimulation (TMS). Task-dependent changes of the size of the TMS-elicited motor evoked potentials were recorded in 12 right-handed, musically naive subjects during and after overt speech, singing and humming, i.e. the production of melody without word articulation. The articulation of meaningless syllables served as control condition. We found reciprocal lateralized effects of overt speech and musical tasks on motor cortex excitability. During overt speech, the corticospinal projection of the left (i.e. dominant) hemisphere to the right hand was facilitated. In contrast, excitability of the right motor cortex increased during both overt singing and humming, whereas no effect was observed on the left hemisphere. Although the traditional concept of hemispheric lateralization of music has been challenged by recent neuroimaging studies, our findings demonstrate that right-hemisphere preponderance of music is nevertheless present. We discuss our results in terms of the recent concepts on evolution of language and gesture, which hypothesize that cerebral networks mediating hand movement and those subserving language processing are functionally linked. TMS may constitute a useful tool to further investigate the relationship between cortical representations of motor functions, music and language using comparative approaches.

  12. 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

  13. Runtime Performance and Virtual Network Control Alternatives in VM-Based High-Fidelity Network Simulations

    SciTech Connect

    Yoginath, Srikanth B; Perumalla, Kalyan S; Henz, Brian J

    2012-01-01

    In prior work (Yoginath and Perumalla, 2011; Yoginath, Perumalla and Henz, 2012), the motivation, challenges and issues were articulated in favor of virtual time ordering of Virtual Machines (VMs) in network simulations hosted on multi-core machines. Two major components in the overall virtualization challenge are (1) virtual timeline establishment and scheduling of VMs, and (2) virtualization of inter-VM communication. Here, we extend prior work by presenting scaling results for the first component, with experiment results on up to 128 VMs scheduled in virtual time order on a single 12-core host. We also explore the solution space of design alternatives for the second component, and present performance results from a multi-threaded, multi-queue implementation of inter-VM network control for synchronized execution with VM scheduling, incorporated in our NetWarp simulation system.

  14. 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

  15. 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.

  16. Reduced Topological Efficiency in Cortical-Basal Ganglia Motor Network of Parkinson's Disease: A Resting State fMRI Study

    PubMed Central

    Long, Zhiliang; Wu, Guo-Rong; Hu, Xiaofei; Zhang, Yanling; Wang, Jian

    2014-01-01

    Parkinson's disease (PD) is mainly characterized by dopamine depletion of the cortico-basal ganglia (CBG) motor circuit. Given that dopamine dysfunction could affect functional brain network efficiency, the present study utilized resting-state fMRI (rs-fMRI) and graph theoretical approach to investigate the topological efficiency changes of the CBG motor network in patients with PD during a relatively hypodopaminergic state (12 hours after a last dose of dopamimetic treatment). We found that PD compared with controls had remarkable decreased efficiency in the CBG motor network, with the most pronounced changes observed in rostral supplementary motor area (pre-SMA), caudal SMA (SMA-proper), primary motor cortex (M1), primary somatosensory cortex (S1), thalamus (THA), globus pallidus (GP), and putamen (PUT). Furthermore, reduced efficiency in pre-SMA, M1, THA and GP was significantly correlated with Unified Parkinson's Disease Rating Scale (UPDRS) motor scores in PD patients. Together, our results demonstrate that individuals with PD appear to be less effective at information transfer within the CBG motor pathway, which provides a novel perspective on neurobiological explanation for the motor symptoms in patients. These findings are in line with the pathophysiology of PD, suggesting that network efficiency metrics may be used to identify and track the pathology of PD. PMID:25279557

  17. 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.

  18. Cortical networks for vision and language in dyslexic and normal children of variable socio-economic status.

    PubMed

    Monzalvo, Karla; Fluss, Joel; Billard, Catherine; Dehaene, Stanislas; Dehaene-Lambertz, Ghislaine

    2012-05-15

    In dyslexia, anomalous activations have been described in both left temporo-parietal language cortices and in left ventral visual occipito-temporal cortex. However, the reproducibility, task-dependency, and presence of these brain anomalies in childhood rather than adulthood remain debated. We probed the large-scale organization of ventral visual and spoken language areas in dyslexic children using minimal target-detection tasks that were performed equally well by all groups. In 23 normal and 23 dyslexic 10-year-old children from two different socio-economic status (SES) backgrounds, we compared fMRI activity to visually presented houses, faces, and written strings, and to spoken sentences in the native or in a foreign language. Our results confirm a disorganization of both ventral visual and spoken language areas in dyslexic children. Visually, dyslexic children showed a normal lateral-to-medial mosaic of preferences, as well as normal responses to houses and checkerboards, but a reduced activation to words in the visual word form area (VWFA) and to faces in the right fusiform face area (FFA). Auditorily, dyslexic children exhibited reduced responses to speech in posterior temporal cortex, left insula and supplementary motor area, as well as reduced responses to maternal language in subparts of the planum temporale, left basal language area and VWFA. By correlating these two findings, we identify spoken-language predictors of VWFA activation to written words, which differ for dyslexic and normal readers. Similarities in fMRI deficits in both SES groups emphasize the existence of a core set of brain activation anomalies in dyslexia, regardless of culture, language and SES, without however resolving whether these anomalies are a cause or a consequence of impaired reading.

  19. 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

  20. 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.

  1. Efficient stochastic simulations of complex reaction networks on surfaces.

    PubMed

    Barzel, Baruch; Biham, Ofer

    2007-10-14

    Surfaces serve as highly efficient catalysts for a vast variety of chemical reactions. Typically, such surface reactions involve billions of molecules which diffuse and react over macroscopic areas. Therefore, stochastic fluctuations are negligible and the reaction rates can be evaluated using rate equations, which are based on the mean-field approximation. However, in case that the surface is partitioned into a large number of disconnected microscopic domains, the number of reactants in each domain becomes small and it strongly fluctuates. This is, in fact, the situation in the interstellar medium, where some crucial reactions take place on the surfaces of microscopic dust grains. In this case rate equations fail and the simulation of surface reactions requires stochastic methods such as the master equation. However, in the case of complex reaction networks, the master equation becomes infeasible because the number of equations proliferates exponentially. To solve this problem, we introduce a stochastic method based on moment equations. In this method the number of equations is dramatically reduced to just one equation for each reactive species and one equation for each reaction. Moreover, the equations can be easily constructed using a diagrammatic approach. We demonstrate the method for a set of astrophysically relevant networks of increasing complexity. It is expected to be applicable in many other contexts in which problems that exhibit analogous structure appear, such as surface catalysis in nanoscale systems, aerosol chemistry in stratospheric clouds, and genetic networks in cells.

  2. 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

  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. PMID:25960314

  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. PMID:25921620

  5. Spatio-temporal electrical stimuli shape behavior of an embodied cortical network in a goal-directed learning task

    NASA Astrophysics Data System (ADS)

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

    2008-09-01

    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. Corrections were made to this article on 27 August 2008. Changes were made to affiliation 3, and to figure 2. The corrected electronic version is identical to the print version.

  6. Spatio-temporal electrical stimuli shape behavior of an embodied cortical network in a goal-directed learning task.

    PubMed

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

    2008-09-01

    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.

  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. 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.

  9. 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

  10. Characterizing Brain Cortical Plasticity and Network Dynamics Across the Age-Span in Health and Disease with TMS-EEG and TMS-fMRI

    PubMed Central

    Pascual-Leone, Alvaro; Freitas, Catarina; Oberman, Lindsay; Horvath, Jared C.; Halko, Mark; Eldaief, Mark; Bashir, Shahid; Vernet, Marine; Shafi, Mouhshin; Westover, Brandon; Vahabzadeh-Hagh, Andrew M.; Rotenberg, Alexander

    2012-01-01

    Brain plasticity can be conceptualized as nature’s invention to overcome limitations of the genome and adapt to a rapidly changing environment. As such, plasticity is an intrinsic property of the brain across the life-span. However, mechanisms of plasticity may vary with age. The combination of transcranial magnetic stimulation (TMS) with electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) enables clinicians and researchers to directly study local and network cortical plasticity, in humans in vivo, and characterize their changes across the age-span. Parallel, translational studies in animals can provide mechanistic insights. Here, we argue that, for each individual, the efficiency of neuronal plasticity declines throughout the age-span and may do so more or less prominently depending on variable ‘starting-points’ and different ‘slopes of change’ defined by genetic, biological, and environmental factors. Furthermore, aberrant, excessive, insufficient, or mistimed plasticity may represent the proximal pathogenic cause of neurodevelopmental and neurodegenerative disorders such as autism spectrum disorders or Alzheimer’s disease. PMID:21842407

  11. 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. PMID:20857499

  12. 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.

  13. How the human brain goes virtual: distinct cortical regions of the person-processing network are involved in self-identification with virtual agents.

    PubMed

    Ganesh, Shanti; van Schie, Hein T; de Lange, Floris P; Thompson, Evan; Wigboldus, Daniël H J

    2012-07-01

    Millions of people worldwide engage in online role-playing with their avatar, a virtual agent that represents the self. Previous behavioral studies have indicated that many gamers identify more strongly with their avatar than with their biological self. Through their avatar, gamers develop social networks and learn new social-cognitive skills. The cognitive neurosciences have yet to identify the neural processes that underlie self-identification with these virtual agents. We applied functional neuroimaging to 22 long-term online gamers and 21 nongaming controls, while they rated personality traits of self, avatar, and familiar others. Strikingly, neuroimaging data revealed greater avatar-referential cortical activity in the left inferior parietal lobe, a region associated with self-identification from a third-person perspective. The magnitude of this brain activity correlated positively with the propensity to incorporate external body enhancements into one's bodily identity. Avatar-referencing furthermore recruited greater activity in the rostral anterior cingulate gyrus, suggesting relatively greater emotional self-involvement with one's avatar. Post-scanning behavioral data revealed superior recognition memory for avatar relative to others. Interestingly, memory for avatar positively covaried with play duration. These findings significantly advance our knowledge about the brain's plasticity to self-identify with virtual agents and the human cognitive-affective potential to live and learn in virtual worlds.

  14. 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.

  15. Low and then high frequency oscillations of distinct right cortical networks are progressively enhanced by medium and long term Satyananda Yoga meditation practice

    PubMed Central

    Thomas, John; Jamieson, Graham; Cohen, Marc

    2014-01-01

    Meditation proficiency is related to trait-like (learned) effects on brain function, developed over time. Previous studies show increases in EEG power in lower frequency bands (theta, alpha) in experienced meditators in both meditation states and baseline conditions. Higher gamma band power has been found in advanced Buddhist meditators, yet it is not known if this occurs in Yoga meditation practices. This study used eLORETA to compare differences in cortical source activity underlying scalp EEG from intermediate (mean experience 4 years) and advanced (mean experience 30 years) Australian meditators from the Satyananda Yoga tradition during a body-steadiness meditation, mantra meditation, and non-meditation mental calculation condition. Intermediate Yoga meditators showed greater source activity in low frequencies (particularly theta and alpha1) during mental calculation, body-steadiness and mantra meditation. A similar spatial pattern of significant differences was found in all conditions but the number of significant voxels was double during body-steadiness and mantra meditation than in the non-meditation (calculation) condition. These differences were greatest in right (R) superior frontal and R precentral gyri and extended back to include the R parietal and occipital lobes. Advanced Yoga meditators showed greater activity in high frequencies (beta and especially gamma) in all conditions but greatly expanded during meditation practice. Across all conditions (meditation and non-meditation) differences were greatest in the same regions: R insula, R inferior frontal gyrus and R anterior temporal lobe. Distinct R core networks were identified in alpha1 (8–10 Hz) and gamma (25–42 Hz) bands, respectively. The voxels recruited to these networks greatly expanded during meditation practice to include homologous regions of the left hemisphere. Functional interpretation parallels traditionally described stages of development in Yoga proficiency. PMID:24959124

  16. Negative childhood experiences alter a prefrontal-insular-motor cortical network in healthy adults: A preliminary multimodal rsfMRI-fMRI-MRS-dMRI study

    PubMed Central

    Duncan, Niall W.; Hayes, Dave J.; Wiebking, Christine; Tiret, Brice; Pietruska, Karin; Chen, David Q.; Rainville, Pierre; Marjańska, Malgorzata; Mohammid, Omar; Doyon, Julien; Hodaie, Mojgan; Northoff, Georg

    2016-01-01

    Research in humans and animals has shown that negative childhood experiences (NCE) can have long-term effects on the structure and function of the brain. Alterations have been noted in grey and white matter, in the brain’s resting state, on the glutamatergic system, and on neural and behavioural responses to aversive stimuli. These effects can be linked to psychiatric disorder such as depression and anxiety disorders that are influenced by excessive exposure to early life stressors. The aim of the current study was to investigate the effect of NCEs on these systems. Resting state functional MRI (rsfMRI), aversion task fMRI, glutamate magnetic resonance spectroscopy (MRS), and diffusion magnetic resonance imaging (dMRI) were combined with the Childhood Trauma Questionnaire (CTQ) in healthy subjects to examine the impact of NCEs on the brain. Low CTQ scores, a measure of NCEs, were related to higher resting state glutamate levels and higher resting state entropy in the medial prefrontal cortex (mPFC). CTQ scores, mPFC glutamate and entropy, correlated with neural BOLD responses to the anticipation of aversive stimuli in regions throughout the aversion-related network, with strong correlations between all measures in the motor cortex and left insula. Structural connectivity strength, measured using mean fractional anisotropy, between the mPFC and left insula correlated to aversion-related signal changes in the motor cortex. These findings highlight the impact of NCEs on multiple inter-related brain systems. In particular, they highlight the role of a prefrontal-insular-motor cortical network in the processing and responsivity to aversive stimuli and its potential adaptability by NCEs. PMID:26287448

  17. Low and then high frequency oscillations of distinct right cortical networks are progressively enhanced by medium and long term Satyananda Yoga meditation practice.

    PubMed

    Thomas, John; Jamieson, Graham; Cohen, Marc

    2014-01-01

    Meditation proficiency is related to trait-like (learned) effects on brain function, developed over time. Previous studies show increases in EEG power in lower frequency bands (theta, alpha) in experienced meditators in both meditation states and baseline conditions. Higher gamma band power has been found in advanced Buddhist meditators, yet it is not known if this occurs in Yoga meditation practices. This study used eLORETA to compare differences in cortical source activity underlying scalp EEG from intermediate (mean experience 4 years) and advanced (mean experience 30 years) Australian meditators from the Satyananda Yoga tradition during a body-steadiness meditation, mantra meditation, and non-meditation mental calculation condition. Intermediate Yoga meditators showed greater source activity in low frequencies (particularly theta and alpha1) during mental calculation, body-steadiness and mantra meditation. A similar spatial pattern of significant differences was found in all conditions but the number of significant voxels was double during body-steadiness and mantra meditation than in the non-meditation (calculation) condition. These differences were greatest in right (R) superior frontal and R precentral gyri and extended back to include the R parietal and occipital lobes. Advanced Yoga meditators showed greater activity in high frequencies (beta and especially gamma) in all conditions but greatly expanded during meditation practice. Across all conditions (meditation and non-meditation) differences were greatest in the same regions: R insula, R inferior frontal gyrus and R anterior temporal lobe. Distinct R core networks were identified in alpha1 (8-10 Hz) and gamma (25-42 Hz) bands, respectively. The voxels recruited to these networks greatly expanded during meditation practice to include homologous regions of the left hemisphere. Functional interpretation parallels traditionally described stages of development in Yoga proficiency. PMID:24959124

  18. The Use of Simulation for the Design and Analysis of Thermophotovoltaic Networks

    SciTech Connect

    JE Oppenlander; JL Vell; WS Gaes; DM Siganporia; LR Danielson; MW Dashiell

    2004-07-20

    Simulation has provided valuable quantification of the fundamental behavior of thermophotovoltaic cell networks. The results of simulation studies have supported the design and fabrication of small-scale demonstration networks and are expected to guide assembly of large-scale systems. This paper describes the methodology and software simulator developed to address issues in thermophotovoltaic (TPV) networking, including failure analysis, electrical network design, and nonuniform illumination. Results from simulation studies are given illustrating their application to the design and fabrication of small-scale TPV arrays.

  19. Cortical Memory Mechanisms and Language Origins

    ERIC Educational Resources Information Center

    Aboitiz, Francisco; Garcia, Ricardo R.; Bosman, Conrado; Brunetti, Enzo

    2006-01-01

    We have previously proposed that cortical auditory-vocal networks of the monkey brain can be partly homologized with language networks that participate in the phonological loop. In this paper, we suggest that other linguistic phenomena like semantic and syntactic processing also rely on the activation of transient memory networks, which can be…

  20. Numerical Simulation of Unsteady Blood Flow through Capillary Networks.

    PubMed

    Davis, J M; Pozrikidis, C

    2011-08-01

    A numerical method is implemented for computing unsteady blood flow through a branching capillary network. The evolution of the discharge hematocrit along each capillary segment is computed by integrating in time a one-dimensional convection equation using a finite-difference method. The convection velocity is determined by the local and instantaneous effective capillary blood viscosity, while the tube to discharge hematocrit ratio is deduced from available correlations. Boundary conditions for the discharge hematocrit at divergent bifurcations arise from the partitioning law proposed by Klitzman and Johnson involving a dimensionless exponent, q≥1. When q=1, the cells are partitioned in proportion to the flow rate; as q tends to infinity, the cells are channeled into the branch with the highest flow rate. Simulations are performed for a tree-like, perfectly symmetric or randomly perturbed capillary network with m generations. When the tree involves more than a few generations, a supercritical Hopf bifurcation occurs at a critical value of q, yielding spontaneous self-sustained oscillations in the absence of external forcing. A phase diagram in the m-q plane is presented to establish conditions for unsteady flow, and the effect of various geometrical and physical parameters is examined. For a given network tree order, m, oscillations can be induced for a sufficiently high value of q by increasing the apparent intrinsic viscosity, decreasing the ratio of the vessel diameter from one generation to the next, or by decreasing the diameter of the terminal vessels. With other parameters fixed, oscillations are inhibited by increasing m. The results of the continuum model are in excellent agreement with the predictions of a discrete model where the motion of individual cells is followed from inlet to outlet.

  1. A simulation study of TaMAC protocol using network simulator 2.

    PubMed

    Ullah, Sana; Kwak, Kyung Sup

    2012-10-01

    A Wireless Body Area Network (WBAN) is expected to play a significant role in future healthcare system. It interconnects low-cost and intelligent sensor nodes in, on, or around a human body to serve a variety of medical applications. It can be used to diagnose and treat patients with chronic diseases such as hypertensions, diabetes, and cardiovascular diseases. The lightweight sensor nodes integrated in WBAN require low-power operation, which can be achieved using different optimization techniques. We introduce a Traffic-adaptive MAC protocol (TaMAC) for WBAN that supports dual wakeup mechanisms for normal, emergency, and on-demand traffic. In this letter, the TaMAC protocol is simulated using a well-known Network Simulator 2 (NS-2). The problem of multiple emergency nodes is solved using both wakeup radio and CSMA/CA protocol. The power consumption, delay, and throughput performance are closely compared with beacon-enabled IEEE 802.15.4 MAC protocol using extensive simulations.

  2. 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.

  3. Monitoring Different Phonological Parameters of Sign Language Engages the Same Cortical Language Network but Distinctive Perceptual Ones.

    PubMed

    Cardin, Velia; Orfanidou, Eleni; Kästner, Lena; Rönnberg, Jerker; Woll, Bencie; Capek, Cheryl M; Rudner, Mary

    2016-01-01

    The study of signed languages allows the dissociation of sensorimotor and cognitive neural components of the language signal. Here we investigated the neurocognitive processes underlying the monitoring of two phonological parameters of sign languages: handshape and location. Our goal was to determine if brain regions processing sensorimotor characteristics of different phonological parameters of sign languages were also involved in phonological processing, with their activity being modulated by the linguistic content of manual actions. We conducted an fMRI experiment using manual actions varying in phonological structure and semantics: (1) signs of a familiar sign language (British Sign Language), (2) signs of an unfamiliar sign language (Swedish Sign Language), and (3) invented nonsigns that violate the phonological rules of British Sign Language and Swedish Sign Language or consist of nonoccurring combinations of phonological parameters. Three groups of participants were tested: deaf native signers, deaf nonsigners, and hearing nonsigners. Results show that the linguistic processing of different phonological parameters of sign language is independent of the sensorimotor characteristics of the language signal. Handshape and location were processed by different perceptual and task-related brain networks but recruited the same language areas. The semantic content of the stimuli did not influence this process, but phonological structure did, with nonsigns being associated with longer RTs and stronger activations in an action observation network in all participants and in the supramarginal gyrus exclusively in deaf signers. These results suggest higher processing demands for stimuli that contravene the phonological rules of a signed language, independently of previous knowledge of signed languages. We suggest that the phonological characteristics of a language may arise as a consequence of more efficient neural processing for its perception and production.

  4. Grid cells and cortical representation.

    PubMed

    Moser, Edvard I; Roudi, Yasser; Witter, Menno P; Kentros, Clifford; Bonhoeffer, Tobias; Moser, May-Britt

    2014-07-01

    One of the grand challenges in neuroscience is to comprehend neural computation in the association cortices, the parts of the cortex that have shown the largest expansion and differentiation during mammalian evolution and that are thought to contribute profoundly to the emergence of advanced cognition in humans. In this Review, we use grid cells in the medial entorhinal cortex as a gateway to understand network computation at a stage of cortical processing in which firing patterns are shaped not primarily by incoming sensory signals but to a large extent by the intrinsic properties of the local circuit.

  5. On the Effects on Cortical Spontaneous Activity of the Symmetries of the Network of Pinwheels in Visual Area V1.

    PubMed

    Veltz, Romain; Chossat, Pascal; Faugeras, Olivier

    2015-12-01

    This paper challenges and extends earlier seminal work. We consider the problem of describing mathematically the spontaneous activity of V1 by combining several important experimental observations including (1) the organization of the visual cortex into a spatially periodic network of hypercolumns structured around pinwheels, (2) the difference between short-range and long-range intracortical connections, the first ones being rather isotropic and producing naturally doubly periodic patterns by Turing mechanisms, the second one being patchy, and (3) the fact that the Turing patterns spontaneously produced by the short-range connections and the network of pinwheels have similar periods. By analyzing the PO maps, we are able to classify all possible singular points (the pinwheels) as having symmetries described by a small subset of the wallpaper groups. We then propose a description of the spontaneous activity of V1 using a classical voltage-based neural field model that features isotropic short-range connectivities modulated by non-isotropic long-range connectivities. A key observation is that, with only short-range connections and because the problem has full translational invariance in this case, a spontaneous doubly periodic pattern generates a 2-torus in a suitable functional space which persists as a flow-invariant manifold under small perturbations, for example when turning on the long-range connections. Through a complete analysis of the symmetries of the resulting neural field equation and motivated by a numerical investigation of the bifurcations of their solutions, we conclude that the branches of solutions which are stable over an extended range of parameters are those that correspond to patterns with an hexagonal (or nearly hexagonal) symmetry. The question of which patterns persist when turning on the long-range connections is answered by (1) analyzing the remaining symmetries on the perturbed torus and (2) combining this information with the Poincar

  6. 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.

  7. 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.

  8. 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

  9. 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. PMID:23781198

  10. Broadband macroscopic cortical oscillations emerge from intrinsic neuronal response failures.

    PubMed

    Goldental, Amir; Vardi, Roni; Sardi, Shira; Sabo, Pinhas; Kanter, Ido

    2015-01-01

    Broadband spontaneous macroscopic neural oscillations are rhythmic cortical firing which were extensively examined during the last century, however, their possible origination is still controversial. In this work we show how macroscopic oscillations emerge in solely excitatory random networks and without topological constraints. We experimentally and theoretically show that these oscillations stem from the counterintuitive underlying mechanism-the intrinsic stochastic neuronal response failures (NRFs). These NRFs, which are characterized by short-term memory, lead to cooperation among neurons, resulting in sub- or several- Hertz macroscopic oscillations which coexist with high frequency gamma oscillations. A quantitative interplay between the statistical network properties and the emerging oscillations is supported by simulations of large networks based on single-neuron in-vitro experiments and a Langevin equation describing the network dynamics. Results call for the examination of these oscillations in the presence of inhibition and external drives. PMID:26578893

  11. Broadband macroscopic cortical oscillations emerge from intrinsic neuronal response failures

    PubMed Central

    Goldental, Amir; Vardi, Roni; Sardi, Shira; Sabo, Pinhas; Kanter, Ido

    2015-01-01

    Broadband spontaneous macroscopic neural oscillations are rhythmic cortical firing which were extensively examined during the last century, however, their possible origination is still controversial. In this work we show how macroscopic oscillations emerge in solely excitatory random networks and without topological constraints. We experimentally and theoretically show that these oscillations stem from the counterintuitive underlying mechanism—the intrinsic stochastic neuronal response failures (NRFs). These NRFs, which are characterized by short-term memory, lead to cooperation among neurons, resulting in sub- or several- Hertz macroscopic oscillations which coexist with high frequency gamma oscillations. A quantitative interplay between the statistical network properties and the emerging oscillations is supported by simulations of large networks based on single-neuron in-vitro experiments and a Langevin equation describing the network dynamics. Results call for the examination of these oscillations in the presence of inhibition and external drives. PMID:26578893

  12. 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.…

  13. 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.

  14. Future planning: default network activity couples with frontoparietal control network and reward-processing regions during process and outcome simulations.

    PubMed

    Gerlach, Kathy D; Spreng, R Nathan; Madore, Kevin P; Schacter, Daniel L

    2014-12-01

    We spend much of our daily lives imagining how we can reach future goals and what will happen when we attain them. Despite the prevalence of such goal-directed simulations, neuroimaging studies on planning have mainly focused on executive processes in the frontal lobe. This experiment examined the neural basis of process simulations, during which participants imagined themselves going through steps toward attaining a goal, and outcome simulations, during which participants imagined events they associated with achieving a goal. In the scanner, participants engaged in these simulation tasks and an odd/even control task. We hypothesized that process simulations would recruit default and frontoparietal control network regions, and that outcome simulations, which allow us to anticipate the affective consequences of achieving goals, would recruit default and reward-processing regions. Our analysis of brain activity that covaried with process and outcome simulations confirmed these hypotheses. A functional connectivity analysis with posterior cingulate, dorsolateral prefrontal cortex and anterior inferior parietal lobule seeds showed that their activity was correlated during process simulations and associated with a distributed network of default and frontoparietal control network regions. During outcome simulations, medial prefrontal cortex and amygdala seeds covaried together and formed a functional network with default and reward-processing regions.

  15. 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.

  16. 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. PMID:27557104

  17. 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.

  18. A new approach to blood flow simulation in vascular networks.

    PubMed

    Tamaddon, Houman; Behnia, Mehrdad; Behnia, Masud; Kritharides, Leonard

    2016-01-01

    A proper analysis of blood flow is contingent upon accurate modelling of the branching pattern and vascular geometry of the network of interest. It is challenging to reconstruct the entire vascular network of any organ experimentally, in particular the pulmonary vasculature, because of its very high number of vessels, complexity of the branching pattern and poor accessibility in vivo. The objective of our research is to develop an innovative approach for the reconstruction of the full pulmonary vascular tree from available morphometric data. Our method consists of the use of morphometric data on those parts of the pulmonary vascular tree that are too small to reconstruct by medical imaging methods. This method is a three-step technique that reconstructs the entire pulmonary arterial tree down to the capillary bed. Vessels greater than 2 mm are reconstructed from direct volume and surface analysis using contrast-enhanced computed tomography. Vessels smaller than 2 mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's laws to every vessel bifurcation simultaneously leads to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. In conclusion, the present model provides a morphological foundation for future analysis of blood flow in the pulmonary circulation.

  19. Unified Approach to Modeling and Simulation of Space Communication Networks and Systems

    NASA Technical Reports Server (NTRS)

    Barritt, Brian; Bhasin, Kul; Eddy, Wesley; Matthews, Seth

    2010-01-01

    Network simulator software tools are often used to model the behaviors and interactions of applications, protocols, packets, and data links in terrestrial communication networks. Other software tools that model the physics, orbital dynamics, and RF characteristics of space systems have matured to allow for rapid, detailed analysis of space communication links. However, the absence of a unified toolset that integrates the two modeling approaches has encumbered the systems engineers tasked with the design, architecture, and analysis of complex space communication networks and systems. This paper presents the unified approach and describes the motivation, challenges, and our solution - the customization of the network simulator to integrate with astronautical analysis software tools for high-fidelity end-to-end simulation. Keywords space; communication; systems; networking; simulation; modeling; QualNet; STK; integration; space networks

  20. Effects of Transmitters and Amyloid-Beta Peptide on Calcium Signals in Rat Cortical Astrocytes: Fura-2AM Measurements and Stochastic Model Simulations

    PubMed Central

    Toivari, Eeva; Manninen, Tiina; Nahata, Amit K.; Jalonen, Tuula O.; Linne, Marja-Leena

    2011-01-01

    Background To better understand the complex molecular level interactions seen in the pathogenesis of Alzheimer's disease, the results of the wet-lab and clinical studies can be complemented by mathematical models. Astrocytes are known to become reactive in Alzheimer's disease and their ionic equilibrium can be disturbed by interaction of the released and accumulated transmitters, such as serotonin, and peptides, including amyloid- peptides (A). We have here studied the effects of small amounts of A25–35 fragments on the transmitter-induced calcium signals in astrocytes by Fura-2AM fluorescence measurements and running simulations of the detected calcium signals. Methodology/Principal Findings Intracellular calcium signals were measured in cultured rat cortical astrocytes following additions of serotonin and glutamate, or either of these transmitters together with A25–35. A25–35 increased the number of astrocytes responding to glutamate and exceedingly increased the magnitude of the serotonin-induced calcium signals. In addition to A25–35-induced effects, the contribution of intracellular calcium stores to calcium signaling was tested. When using higher stimulus frequency, the subsequent calcium peaks after the initial peak were of lower amplitude. This may indicate inadequate filling of the intracellular calcium stores between the stimuli. In order to reproduce the experimental findings, a stochastic computational model was introduced. The model takes into account the major mechanisms known to be involved in calcium signaling in astrocytes. Model simulations confirm the principal experimental findings and show the variability typical for experimental measurements. Conclusions/Significance Nanomolar A25–35 alone does not cause persistent change in the basal level of calcium in astrocytes. However, even small amounts of A25–35, together with transmitters, can have substantial synergistic effects on intracellular calcium signals. Computational modeling