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Results for “functional network connectivity”

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PubMed2000

Respiratory rhythm generation in neonatal and adult mammals: the hybrid pacemaker-network model.

We review a new unified model of respiratory rhythm generation - the hybrid pacemaker-network model. This model represents a comprehensive synthesis of cellular and network mechanisms that can theoretically account for rhythm generation in different functional states, from the most reduced states in the neonatal nervous system in vitro to the intact adult system in vivo. The model incorporates a critical neuronal kernel consisting of a network of excitatory neurons with state-dependent, oscillatory bursting or pacemaker properties. This kernel, located in the pre-Bötzinger complex of the ventrolateral medulla, provides a rudimentary pacemaker network mechanism for generating an inspiratory rhythm, revealed predominately in functionally reduced states in vitro. In vivo the kernel is embedded in a larger network that interacts with the kernel via inhibitory synaptic connections that provide the dynamic control required for the evolution of the complete pattern of inspiratory and expiratory network activity. The resulting hybrid of cellular pacemaker and network properties functionally endows the system with multiple mechanisms of rhythm generation. New biophysically realistic mathematical models of the hybrid pacemaker-network have been developed that illustrate these concepts and provide a computational framework for investigating interactions of cellular and network processes that must be analyzed to understand rhythm generation.

Animals↗

PubMed2006

An effective structure learning method for constructing gene networks.

MOTIVATION: Bayesian network methods have shown promise in gene regulatory network reconstruction because of their capability of capturing causal relationships between genes and handling data with noises found in biological experiments. The problem of learning network structures, however, is NP hard. Consequently, heuristic methods such as hill climbing are used for structure learning. For networks of a moderate size, hill climbing methods are not computationally efficient. Furthermore, relatively low accuracy of the learned structures may be observed. The purpose of this article is to present a novel structure learning method for gene network discovery. RESULTS: In this paper, we present a novel structure learning method to reconstruct the underlying gene networks from the observational gene expression data. Unlike hill climbing approaches, the proposed method first constructs an undirected network based on mutual information between two nodes and then splits the structure into substructures. The directional orientations for the edges that connect two nodes are then obtained by optimizing a scoring function for each substructure. Our method is evaluated using two benchmark network datasets with known structures. The results show that the proposed method can identify networks that are close to the optimal structures. It outperforms hill climbing methods in terms of both computation time and predicted structure accuracy. We also apply the method to gene expression data measured during the yeast cycle and show the effectiveness of the proposed method for network reconstruction.

Algorithms↗

PubMed1997

[Lymph flow and the development of the lymph nodes in human fetuses].

Since its anlage lymph node forms as a functional anastomosis between lymph and blood vessels. They make a complex with intimate anatomotopographic interrelations and their branches--an interconnected system, within which intervascular connective tissue transforms into lymphoid one. Interstitial canals networks may play a role of connecting "bridges" during lymphatic sinuses and blood microvessels unification with lymphoid tissue into a specific functional complex of counterflow system (arteries/veins--lymphatic vessels). On this basis histo- and morphogenesis of lymph node as a part of lymphatic bed occur. Lymph node uneven growth due to their depositing and resorptive function development allows to explain peculiarities of central lymph flow in human embryos.

Abdomen↗

PubMed2000

On imputing function to structure from the behavioural effects of brain lesions.

What is the link, if any, between the patterns of connections in the brain and the behavioural effects of localized brain lesions? We explored this question in four related ways. First, we investigated the distribution of activity decrements that followed simulated damage to elements of the thalamocortical network, using integrative mechanisms that have recently been used to successfully relate connection data to information on the spread of activation, and to account simultaneously for a variety of lesion effects. Second, we examined the consequences of the patterns of decrement seen in the simulation for each type of inference that has been employed to impute function to structure on the basis of the effects of brain lesions. Every variety of conventional inference, including double dissociation, readily misattributed function to structure. Third, we tried to derive a more reliable framework of inference for imputing function to structure, by clarifying concepts of function, and exploring a more formal framework, in which knowledge of connectivity is necessary but insufficient, based on concepts capable of mathematical specification. Fourth, we applied this framework to inferences about function relating to a simple network that reproduces intact, lesioned and paradoxically restored orientating behaviour. Lesion effects could be used to recover detailed and reliable information on which structures contributed to particular functions in this simple network. Finally, we explored how the effects of brain lesions and this formal approach could be used in conjunction with information from multiple neuroscience methodologies to develop a practical and reliable approach to inferring the functional roles of brain structures.

Behavior↗

PubMed1995

A network model of developmental gene hierarchy.

A network model of development governing the whole temporal and spatial hierarchy of early embryogenesis and pattern formation in Drosophila is introduced. The network is related to a neural network model, with its units being developmental genes mostly connected by the genes' DNA-binding products. The developmental network's agreement with predictions regarding architecture and function of the neural network provides adequate grounds for an analogy between the two. The model is tested through computer simulations--predictions compare favorably with experimental observations. The model not only incorporates a program of control at gene level, but also makes a direct connection with current molecular studies throughout the whole hierarchy of the early embryogenesis of Drosophila.

Animals↗

PubMed2005

Modulation of effective connectivity by cognitive demand in phonological verbal fluency.

Verbal fluency is a classic neuropsychological measure of language production. Phonological verbal fluency involves the generation of words beginning with a specified letter, and its functional neuroanatomy is comprised of a distributed network of regions which is modulated by cognitive load. In order to investigate the functional relationship of these regions, the effective connectivity was analyzed with covariance structural equation modeling under conditions of varying cognitive load. Significant path coefficients were evident between the anterior cingulate, left middle frontal gyrus, and precuneus. The left middle frontal gyrus showed a facilitory projection to the precuneus which had a suppressive influence on anterior cingulate activation. With increasing cognitive demand, the left middle frontal projection to the precuneus became suppressive, and the path coefficient from the precuneus to the anterior cingulate showed a marked diminution in strength. The path analysis suggests that the lead-in process for letter verbal fluency may primarily involve an orthographic visual strategy. The marked changes in path coefficients with the increased cognitive load may reflect the greater demands placed on executive function. The significant changes in path coefficient values with increased cognitive demand indicate the importance of accounting for task difficulty not only in the interpretation of brain activation maps but also for effective connectivity measurements.

Adult↗

PubMed2003

Global exponential stability of hybrid bidirectional associative memory neural networks with discrete delays.

In this paper, the dynamical characteristics of hybrid bidirectional associative memory neural networks with constant transmission delays are investigated. Without assuming symmetry of synaptic connection weights and monotonicity and differentiability of activation functions, Halanay-type inequalities (which are different from the approach of constructing Lyapunov functionals) are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Our results are less conservative and restrictive than previously known results.

Algorithms↗

PubMed2004

Clustered organization of cortical connectivity.

Long-range corticocortical connectivity in mammalian brains possesses an intricate, nonrandom organization. Specifically, projections are arranged in "small-world" networks, forming clusters of cortical areas, which are closely linked among each other, but less frequently with areas in other clusters. In order to delineate the structure of cortical clusters and identify their members, we developed a computational approach based on evolutionary optimization. In different compilations of connectivity data for the cat and macaque monkey brain, the algorithm identified a small number of clusters that broadly agreed with functional cortical subdivisions. We propose a simple spatial growth model for evolving clustered connectivity, and discuss structural and functional implications of the clustered, small-world organization of cortical networks.

Animals↗

PubMedDate not supplied

[Fanconi anemia: genes and function(s) revisited].

Fanconi anemia (FA), a rare inherited disorder, exhibits a complex phenotype including progressive bone marrow failure, congenital malformations and increased risk of cancers, mainly acute myeloid leukaemia. At the cellular level, FA is characterized by hypersensitivity to DNA cross-linking agents and by high frequencies of induced chromosomal aberrations, a property used for diagnosis. FA results from mutations in one of the eleven FANC (FANCA to FANCJ) genes. Nine of them have been identified. In addition, FANCD1 gene has been shown to be identical to BRCA2, one of the two breast cancer susceptibility genes. Seven of the FANC proteins form a complex, which exists in four different forms depending of its subcellular localisation. Four FANC proteins (D1(BRCA2), D2, I and J) are not associated to the complex. The presence of the nuclear form of the FA core complex is necessary for the mono-ubiquitinylation of FANCD2 protein, a modification required for its re-localization to nuclear foci, likely to be sites of DNA repair. A clue towards understanding the molecular function of the FANC genes comes from the recently identified connection of FANC to the BRCA1, ATM, NBS1 and ATR genes. Two of the FANC proteins (A and D2) directly interact with BRCA1, which in turn interacts with the MRE11/RAD50/NBS1 complex, which is one of the key components in the mechanisms involved in the cellular response to DNA double strand breaks (DSB). Moreover, ATM, a protein kinase that plays a central role in the network of DSB signalling, phosphorylates in vitro and in vivo FANCD2 in response to ionising radiations. Moreover, the NBS1 protein and the monoubiquitinated form of FANCD2 seem to act together in response to DNA crosslinking agents. Taken together with the previously reported impaired DSB and DNA interstrand crosslinks repair in FA cells, the connection of FANC genes to the ATM, ATR, NBS1 and BRCA1 links the FANC genes function to the finely orchestrated network involved in the sensing, signalling and repair of DNA replication-blocking lesions.

Chromosome Aberrations↗

PubMed1996

[The innervation of the digestive tract: its morphofunctional and neurochemical aspects].

The innervation of the alimentary tract (or enteric nervous system, ENS) represents the third division of the autonomic nervous system and it appears to be unique for its intrinsic ability to mediate reflex activity even when disconnected from the central nervous system. Enteric nerve cells can be classified in subclasses according to combined classic morphological criteria (Dogiel type I, II and III) and electrophysiological properties (type S and AH). A further major feature of the ENS lies in the variety of chemical messengers expressed in its neuronal elements. These substances can act either as neurotransmitters or neuromodulators. A common finding of enteric neurons is to synthetize and store several chemical messengers, a phenomenon known as neurochemical coding. As a consequence, neurotransmission involves the release and action of more than one messenger, an event referred to as plurichemical transmission. Recently, the use of combination of methods (such as immunohistochemical, pharmacological and electrophysiological techniques) has led to the identification of specific functionally distinct categories of enteric neurons. Thus, inhibitory and excitatory motor neurons, interneurons, vasomotor and sensory neurons are now recognized to constitute the complex network of the ENS. These neuronal elements are synaptically connected to form microcircuits which play a pivotal role to control digestive functions, including motility, blood flow, secretion and absorbtion.

Animals↗

PubMed2000

A positron emission tomographic study of auditory localization in the congenitally blind.

We have used positron emission tomography (PET) to measure regional cerebral blood flow (rCBF) in sighted and congenitally blind subjects performing auditory localization tasks. During scanning, the spectral and binaural cues of localized sound were reproduced by a sound system and delivered via headphones. During tasks that required auditory localization both the sighted and blind subjects strongly activated posterior parietal areas. In addition, the blind subjects activated association areas in the right occipital cortex, the foci of which were similar to areas previously identified in visual location and motion detection experiments in sighted subjects. The blind subjects, therefore, demonstrated visual to auditory cross-modal plasticity with auditory localization activating occipital association areas originally intended for dorsal-stream visual processing. To determine the functional connectivity of pre-selected brain regions in primary and non-primary auditory and posterior parietal cortex in the two cohorts, we performed an inter-regional correlation analysis on the rCBF data set. During auditory localization in the blind subjects, rCBF activity in the right posterior parietal cortex was positively correlated with that in the right occipital region, whereas in sighted subjects correlations were generally negative. There were no significant positive occipital correlations in either cohort when reference regions in temporal or left parietal cortex were chosen. This indicates that in congenitally blind subjects the right occipital cortex participates in a functional network for auditory localization and that occipital activity is more likely to arise from connections with posterior parietal cortex.

Adult↗

PubMed2000

Topology of evolving networks: local events and universality

Networks grow and evolve by local events, such as the addition of new nodes and links, or rewiring of links from one node to another. We show that depending on the frequency of these processes two topologically different networks can emerge, the connectivity distribution following either a generalized power law or an exponential. We propose a continuum theory that predicts these two regimes as well as the scaling function and the exponents, in good agreement with numerical results. Finally, we use the obtained predictions to fit the connectivity distribution of the network describing the professional links between movie actors.

Journal Article↗

PubMed1987

Biological macromolecules as gels: functional similarities.

Functional biological macromolecules arising from folding, cross-connection, and solvation of long-chain biopolymers forming three-dimensional networks can be compared to gels. Both involve identical internal competitive forces that are selectively influenced by external conditions and conspire to adjust conformations and modulate functions. In spite of important differences in size, chemical composition, polymer density, and configuration, biological macromolecules indeed manifest some of the essential physical-chemical properties of gels. This result represents presumptive evidence for common underlying mechanisms in functional molecules and gels. Thus, the present and highly perfectible model explains why and how, depending on initial conditions, a system may respond differently to an external parameter and similarly to different parameters. Moreover, the fact that any localized change in one of the competitive forces gives rise to a pressure in the system as a whole provides one explanation for the mechanism of the transmission of information.

Biopolymers↗

PubMed2003

Connections between the anterior inferotemporal cortex (area TE) and CA1 of the hippocampus in monkey.

In addition to the trisynaptic perforant pathway from entorhinal cortex to CA1, there are multiple direct parallel pathways between several cortical regions and CA1. These may be supposed to function cooperatively, in conjunction with the perforant pathway; but neither the functional nor anatomical organization of the extended network is well understood. In this report, we further investigate the connections between anterior inferotemporal cortex (area TE) and CA1. Injections of tracer substances demonstrate that part of the dorsal subdivision of TE sends projections to CA1, but does not receive reciprocating projections back. This contrasts with the bi-directional connections between the more ventral subdivision, TEav, and CA1, as reported by previous studies (and corroborated by tracer injections in this report). The corticohippocampal projections from dorsal TE are likely to be unimodal visual. They partially converge in the posterior portion of CA1 with connections from posterior TE and from the inferior parietal lobule, perhaps constituting a network related to visual or visuospatial processes.

Animals↗

PubMed2006

Evolutionary systems biology: links between gene evolution and function.

The recent accumulation of genome-wide data on various facets of gene expression, function and evolution stimulated the emergence of a new field, evolutionary systems biology. Many significant correlations were detected between variables that characterize the functioning of a gene, such as expression level, knockout effect, connectivity of genetic and protein-protein interaction networks, and variables that describe gene evolution, such as sequence evolution rate and propensity for gene loss. The first attempts on multidimensional analysis of genomic data yielded composite variables that describe the 'status' of a gene in the genomic community. However, it remains uncertain whether different functional variables affect gene evolution synergistically or there is a single, dominant factor. The number of translation events, linked to selection for translational robustness, was proposed as a candidate for such a major determinant of protein evolution. These developments show that, although the methodological basis of evolutionary systems biology is not yet fully solidified, this area of research is already starting to yield fundamental biological insights.

Evolution, Molecular↗

PubMed2005

Determination of functional interactions among signalling pathways in Escherichia coli K-12.

Interaction among different signalling pathways has been noted repeatedly. However, no systematic method has been developed to identify and quantify such interactions. Here we reported that network component analysis (NCA) was able to determine interactions among various signalling pathways in Escherichia coli K-12 based on known transcription factor (TF)-promoter connectivity information and microarray data from genetic knockout strains. The TF activities determined from NCA allow the quantitation of functional interactions, barring gross errors in the connectivity and microarray data. By using a robust statistical test, 37 pairs of functional interactions were identified. Eighteen interaction pairs confirmed previous implications, while 19 others represent new predictions. These results demonstrate that the functional interactions among various signalling pathways may be rather significant. With reasonable TF-promoter connectivity, NCA coupled with genetic knockouts and microarray experiments provides a systematic way to elucidate interaction networks. As this approach cannot distinguish between cross-talks and unidentified direct regulation, the results should provide incentives for further experimental testing.

Escherichia coli K12↗

PubMed2004

Hybridized particle swarm algorithm for adaptive structure training of multilayer feed-forward neural network: QSAR studies of bioactivity of organic compounds.

The multilayer feed-forward ANN is an important modeling technique used in QSAR studying. The training of ANN is usually carried out only to optimize the weights of the neural network and without paying attention to the network topology. Some other strategies used to train ANN are, first, to discover an optimum structure of the network, and then to find weights for an already defined structure. These methods tend to converge to local optima, and may also lead to overfitting. In this article, a hybridized particle swarm optimization (PSO) approach was applied to the neural network structure training (HPSONN). The continuous version of PSO was used for the weight training of ANN, and the modified discrete PSO was applied to find appropriate the network architecture. The network structure and connectivity are trained simultaneously. The two versions of PSO can jointly search the global optimal ANN architecture and weights. A new objective function is formulated to determine the appropriate network architecture and optimum value of the weights. The proposed HPSONN algorithm was used to predict carcinogenic potency of aromatic amines and biological activity of a series of distamycin and distamycin-like derivatives. The results were compared to those obtained by PSO and GA training in which the network architecture was kept fixed. The comparison demonstrated that the HPSONN is a useful tool for training ANN, which converges quickly towards the optimal position, and can avoid overfitting in some extent.

Journal Article↗

PubMed1996

The structure and function of hyaluronan: An overview.

Hyaluronan is a major component of synovial tissue and fluid as well as other soft connective tissues. It is a high-Mr polysaccharide which forms entangled networks already at dilute concentrations (< 1 mg/mL) and endows its solutions with unique rheological properties. Physiological functions of hyaluronan (lubrication, water homeostasis, macromolecular filtering, exclusion, etc.) have been ascribed to the properties of these networks. Recently a number of specific interactions between hyaluronan and a group of proteins named hyaladherins have also pointed towards a role of hyaluronan in recognition and the regulation of cellular activities. Many more or less well documented hypotheses have been proposed for the function of hyaluronan in joints, for example, that it should lubricate, protect cartilage surfaces, scavenge free radicals and debris, keep the joint cavities open, form flow barriers in the synovium and prevent capillary growth.

Animals↗