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Results for “functional network connectivity”

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PubMed1987

Transient morphological features of identified ganglion cells in living fetal and neonatal retina.

The function and morphology of retinal ganglion cells in the adult mammalian visual system has been well studied, but little is known about how the adult state is achieved. To address this question, the morphological changes that retinal ganglion cells undergo during development were studied. Ganglion cells were first identified by retrograde labeling with rhodamine latex microspheres deposited in retinorecipient targets in fetal and early postnatal cats. The structure of ganglion cells was then revealed by intracellular injection of Lucifer yellow in living retinas removed and maintained in vitro. As early as 2 weeks before birth, a morphologically diverse assortment of ganglion cells is present, some of which resemble the alpha, beta, and gamma classes found in the adult. However, in contrast to the adult, developing ganglion cells exhibit several transient features, including excessive axonal and dendritic branching and exuberant somatic and dendritic spines. These morphological features indicate that there is a transient network of connectivity that could play an important role in the final determination of retinal ganglion cell form and function.

Animals↗

PubMed1992

Changes in brain functional connectivity in Alzheimer-type and multi-infarct dementia.

Clinical and neuropathological evaluation of elderly subjects with dementia has traditionally concentrated upon the focal distribution of brain disease, ignoring changes in the complex connections that link brain areas and that are crucial for cognition. We examined subjects with the two most common forms of dementia in the elderly (dementia of the Alzheimer type or DAT, and multi-infarct dementia or MID); and used electroencephalographic (EEG) coherence to examine the effects of these illnesses on the functional connections between brain areas. We studied coherence between brain areas known to be linked by two different types of connections: (i) dense narrow bands of long corticocortical fibres; (ii) broad complex networks of corticocortical and corticosubcortical fibres. Areas that were linked by dense narrow bands of long corticocortical fibres showed greatly diminished coherence in subjects with DAT; among MID subjects, this coherence was not significantly affected. Areas that were linked by broad connective networks showed the largest decreases in coherence among MID subjects. These findings are consistent with neuropathological evidence that Alzheimer's disease is a neocortical 'disconnection syndrome' in which there is a loss of structural and functional integrity of long corticocortical tracts. The findings further suggest that the vascular disease of MID most prominently affects broad fibre networks that may be more vulnerable to diffuse subcortical vascular damage. A ratio of coherence from complex corticocortical-corticosubcortical networks divided by coherence from long corticocortical tracts correctly classified 76% of subjects into DAT and MID categories. Overall, these results indicate that EEG coherence detects basic pathophysiological differences between subjects with DAT and MID, and that these differences may be clinically useful.

Aged↗

PubMed2002

The identification of functional modules from the genomic association of genes.

By combining the pairwise interactions between proteins, as predicted by the conserved co-occurrence of their genes in operons, we obtain protein interaction networks. Here we study the properties of such networks to identify functional modules: sets of proteins that together are involved in a biological process. The complete network contains 3,033 orthologous groups of proteins in 38 genomes. It consists of one giant component, containing 1,611 orthologous groups, and of 516 small disjointed clusters that, on average, contain only 2.7 orthologous groups. These small clusters have a homogeneous functional composition and thus represent functional modules in themselves. Analysis of the giant component reveals that it is a scale-free, small-world network with a high degree of local clustering (C = 0.6). It consists of locally highly connected subclusters that are connected to each other by linker proteins. The linker proteins tend to have multiple functions, or are involved in multiple processes and have an above average probability of being essential. By splitting up the giant component at these linker proteins, we identify 265 subclusters that tend to have a homogeneous functional composition. The rare functional inhomogeneities in our subclusters reflect the mixing of different types of (molecular) functions in a single cellular process, exemplified by subclusters containing both metabolic enzymes as well as the transcription factors that regulate them. Comparative genome analysis, thus, allows identification of a level of functional interaction between that of pairwise interactions, and of the complete genome.

Animals↗

PubMed2005

The rewards of music listening: response and physiological connectivity of the mesolimbic system.

Although the neural underpinnings of music cognition have been widely studied in the last 5 years, relatively little is known about the neuroscience underlying emotional reactions that music induces in listeners. Many people spend a significant amount of time listening to music, and its emotional power is assumed but not well understood. Here, we use functional and effective connectivity analyses to show for the first time that listening to music strongly modulates activity in a network of mesolimbic structures involved in reward processing including the nucleus accumbens (NAc) and the ventral tegmental area (VTA), as well as the hypothalamus and insula, which are thought to be involved in regulating autonomic and physiological responses to rewarding and emotional stimuli. Responses in the NAc and the VTA were strongly correlated pointing to an association between dopamine release and NAc response to music. Responses in the NAc and the hypothalamus were also strongly correlated across subjects, suggesting a mechanism by which listening to pleasant music evokes physiological reactions. Effective connectivity confirmed these findings, and showed significant VTA-mediated interaction of the NAc with the hypothalamus, insula, and orbitofrontal cortex. The enhanced functional and effective connectivity between brain regions mediating reward, autonomic, and cognitive processing provides insight into understanding why listening to music is one of the most rewarding and pleasurable human experiences.

Acoustic Stimulation↗

PubMed1990

Pattern-recognition by an artificial network derived from biologic neuronal systems.

A novel artificial neural network, derived from neurobiological observations, is described and examples of its performance are presented. This DYnamically STable Associative Learning (DYSTAL) network associatively learns both correlations and anticorrelations, and can be configured to classify or restore patterns with only a change in the number of output units. DYSTAL exhibits some particularly desirable properties: computational effort scales linearly with the number of connections, i.e., it is O(N) in complexity; performance of the network is stable with respect to network parameters over wide ranges of their values and over the size of the input field; storage of a very large number of patterns is possible; patterns need not be orthogonal; network connections are not restricted to multi-layer feed-forward or any other specific structure; and, for a known set of deterministic input patterns, the network weights can be computed, a priori, in closed form. The network has been associatively trained to perform the XOR function as well as other classification tasks. The network has also been trained to restore patterns obscured by binary or analog noise. Neither global nor local feedback connections are required during learning; hence the network is particularly suitable for hardware (VLSI) implementation.

Animals↗

PubMed2004

Behavior of susceptible-infected-susceptible epidemics on heterogeneous networks with saturation.

We investigate saturation effects in susceptible-infected-susceptible models of the spread of epidemics in heterogeneous populations. The structure of interactions in the population is represented by networks with connectivity distribution P(k), including scale-free (SF) networks with power law distributions P(k) approximately k(-gamma). Considering cases where the transmission of infection between nodes depends on their connectivity, we introduce a saturation function C(k) which reduces the infection transmission rate lambda across an edge going from a node with high connectivity k. A mean-field approximation with the neglect of degree-degree correlation then leads to a finite threshold lambda(c) >0 for SF networks with 2<gamma</=3. We also find, in this approximation, the fraction of infected individuals among those with degree k for lambda close to lambda(c). We investigate via computer simulation the contact process on a heterogeneous regular lattice and compare the results with those obtained from mean-field theory with and without neglect of degree-degree correlations.

Journal Article↗

PubMed2003

Crossover behavior in a communication network.

We address the problem of message transfer in a communication network. The network consists of nodes and links, with the nodes lying on a two-dimensional lattice. Each node has connections with its nearest neighbors, whereas some special nodes, which are designated as hubs, have connections to all the sites within a certain area of influence. The degree distribution for this network is bimodal in nature and has finite variance. The distribution of travel times between two sites situated at a fixed distance on this lattice shows fat-fractal behavior as a function of hub density. If extra assortative connections are now introduced between the hubs so that each hub is connected to two or three other hubs, the distribution crosses over to power-law behavior. Crossover behavior is also seen if end-to-end short cuts are introduced between hubs whose areas of influence overlap, but this is much milder in nature. In yet another information transmission process, namely, the spread of infection on the network with assortative connections, we again observed crossover behavior of another type, viz., from one power law to another for the threshold values of disease transmission probability. Our results are relevant for the understanding of the role of network topology in information spread processes.

Journal Article↗

PubMed2004

Recurrent biological neural networks: the weak and noisy limit.

A perturbative method is developed for calculating the effects of recurrent synaptic interactions between neurons embedded in a network. A series expansion is constructed that converges for networks with noisy membrane potential and weak synaptic connectivity. The terms of the series can be interpreted as loops of interactions between neurons, so the technique is called a loop expansion. A diagrammatic method is introduced that allows for construction of analytic expressions for the parameter dependencies of the spike-probability function and correlation functions. An analytic expression is obtained to predict the effect of the surrounding network on a neuron during an intracellular current injection. The analytic results are compared with simulations to test the range of their validity and significant effects of the the recurrent connections in network are accurately predicted by the loop expansion.

Action Potentials↗

PubMed2004

Acquired disorders of elastic tissue: Part II. decreased elastic tissue.

Elastic fibers in the extracellular matrix are integral components of dermal connective tissue. The resilience and elasticity required for normal structure and function of the skin are attributable to the network of elastic tissue. Advances in our understanding of elastic tissue physiology provide a foundation for studying the pathogenesis of elastic tissue disorders. Many acquired disorders are nevertheless poorly understood owing to the paucity of reported cases. Several acquired disorders in which loss of dermal elastic tissue produces prominent clinical and histopathologic features have recently been described, including middermal elastolysis, papular elastorrhexis, and pseudoxanthoma-like papillary dermal elastolysis, which must be differentiated from more well-known disorders such as anetoderma, acquired cutis laxa, and acrokeratoelastoidosis. Learning objective At the conclusion of this learning activity, participants should have an understanding of the similarities and differences between acquired disorders of elastic tissue that are characterized by a loss of elastic tissue.

Adolescent↗

PubMed2006

Combining evidence, biomedical literature and statistical dependence: new insights for functional annotation of gene sets.

BACKGROUND: Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). RESULTS: We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). CONCLUSION: The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions.

Algorithms↗

PubMed2003

Computational analyses of high-throughput protein-protein interaction data.

Protein-protein interactions play important roles in nearly all events that take place in a cell. High-throughput experimental techniques enable the study of protein-protein interactions at the proteome scale through systematic identification of physical interactions among all proteins in an organism. High-throughput protein-protein interaction data, with ever-increasing volume, are becoming the foundation for new biological discoveries. A great challenge to bioinformatics is to manage, analyze, and model these data. In this review, we describe several databases that store, query, and visualize protein-protein interaction data. Comparison between experimental techniques shows that each high-throughput technique such as yeast two-hybrid assay or protein complex identification through mass spectrometry has its limitations in detecting certain types of interactions and they are complementary to each other. In silico methods using protein/DNA sequences, domain and structure information to predict protein-protein interaction can expand the scope of experimental data and increase the confidence of certain protein-protein interaction pairs. Protein-protein interaction data correlate with other types of data, including protein function, subcellular location, and gene expression profile. Highly connected proteins are more likely to be essential based on the analyses of the global architecture of large-scale interaction network in yeast. Use of protein-protein interaction networks, preferably in conjunction with other types of data, allows assignment of cellular functions to novel proteins and derivation of new biological pathways. As demonstrated in our study on the yeast signal transduction pathway for amino acid transport, integration of high-throughput data with traditional biology resources can transform the protein-protein interaction data from noisy information into knowledge of cellular mechanisms.

Animals↗

PubMed2005

Self-appraisal decisions evoke dissociated dorsal-ventral aMPFC networks.

The anterior medial prefrontal cortex (aMPFC) is consistently active during personally salient decisions, yet the differential contributory processes of this region along the dorsal-ventral axis are less understood. Using a self-appraisal decision-making task and functional magnetic resonance imaging, we demonstrated task-dependent connectivity of ventral aMPFC with amygdala, insula, and nucleus accumbens, and dorsal aMPFC connectivity with dorsolateral PFC and bilateral hippocampus. These aMPFC networks appear to subserve distinct contributory processes inherent to self-appraisal decisions, specifically a dorsally mediated cognitive and a ventrally mediated affective/self-relevance network.

Adult↗

PubMed1984

Functional anatomy of the perivascular tissue in the adductor canal.

Lower limbs of human adults, males and females, were used for micro- and mesoscopic studies of the collagen-elastic arrangement of the tissue surrounding the femoral vessels on their course along the adductor canal. The vessels' sheaths and lamellae which join them to the canal walls, are formed by strong networks of collagen and elastic fibers, and the perivascular area is filled by thin lamellae of connective tissue, delimiting lobules of adipose tissue. The functional importance of this arrangement to the mechanic protection of the vessels during contraction of the muscles related to the vessels in the adductor canal is discussed.

Connective Tissue↗

PubMed2007

Functional differences between macaque prefrontal cortex and caudate nucleus during eye movements with and without reward.

The prefrontal cortex and the basal ganglia form mutually connected networks and are thought to play essential roles together in guiding goal-directed behaviors. Yet, these structures seem to have independent pathways to motor outputs as well, suggesting differential contributions to goal-directed behaviors. We hypothesized that the prefrontal cortex guides actions to a direction required by external demands and the basal ganglia guide actions to an internally motivated direction. To test this hypothesis, we used a task in which monkeys were required to make a memory-guided saccade to a direction indicated by a visual cue while only one direction was associated with reward. We observed a functional dissociation between the lateral prefrontal cortex (LPFC), which commonly represented the cue direction, and the caudate nucleus (CD), which commonly represented the reward-associated direction. Furthermore, cue-directed and reward-directed signals were integrated differently in the two areas; when the cue direction and the reward direction were opposite, LPFC neurons maintained tuning to the cue direction, whereas CD neurons lost the tuning. Different types of spatial tuning in the two brain areas may contribute to different types of goal-directed behavior.

Analysis of Variance↗

PubMed2006

Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition.

The recurrent excitatory and inhibitory connections between and within layers of the cerebral cortex are fundamental to the operation of local cortical circuits. Models of cortical function often assume that recurrent excitation and inhibition are balanced, and we recently demonstrated that spontaneous network activity in vitro contains a precise balance of excitation and inhibition; however, the existence of a balance between excitation and inhibition in the intact and spontaneously active cerebral cortex has not been directly tested. We examined this hypothesis in the prefrontal cortex in vivo, during the slow (<1 Hz) oscillation in ketamine-xylazine-anesthetized ferrets. We measured persistent network activity (Up states) with extracellular multiple unit and local field potential recording, while simultaneously recording synaptic currents in nearby cells. We determined the reversal potential and conductance change over time during Up states and found that the body of Up state activity exhibited a steady reversal potential (-37 mV on average) for hundreds of milliseconds, even during substantial (21 nS on average) changes in membrane conductance. Furthermore, we found that both the initial and final segments of the Up state were characterized by significantly more depolarized reversal potentials and concomitant increases in excitatory conductance, compared with the stable middle portions of Up states. This ongoing temporal evolution between excitation and inhibition, which exhibits remarkable proportionality within and across neurons in active local networks, may allow for rapid transitions between relatively stable network states, permitting the modulation of neuronal responsiveness in a behaviorally relevant manner.

Action Potentials↗

PubMed2001

Optimal wiring principle and plateaus in the degree of separation for cortical neurons.

Scaling properties of a cortical network wired in a stochastic manner with a distance-dependent probability of a direct connection are considered. In the infinite network limit, an average degree of separation between neurons displays both universality and criticality. The latter feature manifests itself by appearance of a stairlike structure with numerous plateaus as a function of a connectivity exponent. It is suggested that these plateaus may be advantageous in the cortex design. Wiring principle incorporating minimization of both axonal length and the degree of separation is also discussed. This principle leads naturally to a trade-off between saving axons and saving energy required in the communication.

Axons↗

PubMed1996

A New Family of Multivalued Networks.

This paper introduces a new family of multivalued neural networks. We have interpreted the Hopfield network as encoding the same/different information of elements of binary patterns in the connections and developed a scheme which encodes bigger/smaller information of multivalued patterns in the connections with the aid of signum function. The model can be constructed as an autoassociative memory (multivalued counterpart of Hopfield) or heteroassociative memory (multivalued counterpart of BAM). We have used Lyapunov stability analysis in showing the stability of networks. In simulations the energy surface topography of the model is compared to that of Hopfield. Also, asymptotic stability and basin of attraction of the stored patterns are examined. The proposed model can also be used in solving the optimization problems. Mapping a problem on to the network is relatively easy compared to the Hopfield model because of the multivalued representation. Very good results are obtained in traveling salesperson problem simulations. Copyright 1996 Elsevier Science Ltd.

Journal Article↗

PubMed2001

Functional genomics and the study of development, variation and evolution.

It has rarely been possible to connect the developmental and evolutionary branches of genetics, particularly with regard to the precise changes in the molecular control of development that are responsible for phenotypic variation and evolution. Making such connections will require a high-resolution molecular description of the genetic networks that underlie development and an understanding of their responses to genetic and environmental variation. Functional genomics approaches to development and evolution promise to accelerate the research necessary to accomplish these goals.

Animals↗