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At least 721 records · Page 40Linked to original sources
PubMed2006

Distinct electrical and chemical connectivity maps in the thalamic reticular nucleus: potential roles in synchronization and sensation.

GABAergic neurons of the thalamic reticular nucleus (nRt) provide thalamocortical relay neurons with feedback inhibition that influences sensory processing and thalamocortical rhythm generation. Mutual interactions between reticular neurons coordinate oscillatory activities developed within the network during normal sleep and in absence epilepsy, but the chemical versus electrical nature of these connections and their functional influence remain controversial. Here, we investigated the incidence and spatial extent of intra-nRt connectivity in vitro in horizontal and coronal thalamic slices from rat. Laser scanning photostimulation activated presynaptic nRt cells during patch-clamp recordings of postsynaptic neurons. Photolysis of caged glutamate evoked GABAergic IPSCs and/or depolarizing events (spikelets, mediated via electrical coupling) in a large proportion of neurons, thus indicating connectivity with presynaptic cell(s). Synaptic inputs were organized along the major axis of the nucleus in the same orientation as, but commonly exceeding the extent of, dendritic arborization of the postsynaptic neuron. In the anteroposterior (horizontal) plane, chemical connectivity had higher incidence (60% of recorded neurons vs 40% in vertical plane) and longer spatial extent, whereas in the dorsoventral (vertical) plane, electrical coupling dominated (47% incidence vs 37% in horizontal plane) and was more widely distributed. These data demonstrate that both electrical and chemical synapses are prominent within nRt and suggest different roles for the two types of connections. We thus propose that, along the vertical plane, electrical connectivity will promote coordinated rhythmic activity of sleep and/or thalamocortical epilepsy, whereas along the horizontal plane, chemical connectivity will oppose widespread thalamocortical synchronization and modulate sensory throughput.

Animals↗
PubMed1989

The blood vascular architecture of the rat thyroid gland: a scanning electron microscope study of corrosion casts.

The blood vascular bed of the rat thyroid gland was reproduced by injection of a methacrylate casting medium and observed with a scanning electron microscope. The rat thyroid gland received the superior and inferior thyroid arteries and emitted the superior and inferior thyroid veins. Anastomosis between the interlobular arteries or between the interlobular veins was frequently observed in the thyroid gland. The arteriovenous anastomosis was rarely observed between the terminal branches of the lobular arteries and veins. The thyroid blood vascular bed was divided into lobular units which consisted of basket-like capillary networks surrounding the thyroid follicles; a small lobular unit consisted of a few networks, whereas a large one of fifty or more networks. Sizes and forms of the networks varied widely in each case. However, the networks in the superficial layers of the lateral parts of the thyroid gland were typically most developed. Regardless of its size and form, each network always received a proper efferent vessel continuous with the lobular vein, though it was sometimes provided with an accessory afferent or efferent vessel. Only occasionally were the adjacent networks fused with each other or connected by transfollicular capillaries. Thus, the present data suggest that each follicular capillary network is a fairly independent functional-unit in the thyroid microcirculation. The capillaries of the network were sinusoidal in nature and sometimes protruded fine projections which indicated the neogenesis of capillaries. The blood vascular bed of the newborn rat thyroid gland was not always differentiated into basket-like capillary networks.

Animals↗
PubMed2000

Corticolimbic interactions associated with performance on a short-term memory task are modified by age.

Aging has been associated with a decline in memory abilities dependent on hippocampal processing. We investigated whether the functional interactions between the hippocampus and related cortical areas were modified by age. Young and old subjects' brain activity was measured using positron emission tomography (PET) while they performed a short-term memory task (delayed visual discrimination) in which they determined which of two successively presented sine-wave gratings had the highest spatial frequency. Behavioral performance was equal for the two groups. Partial least squares (PLS) analysis of PET images identified a hippocampal voxel whose activity was similarly correlated with performance across groups. Using this voxel as a seed, a second PLS analysis identified cortical regions functionally connected to the hippocampus. Quantification of the neural interactions with structural equation modeling suggested that a different hippocampal network supported performance in the elderly. Unlike the neural network engaged by the young, which included prefrontal cortex Brodmann's area (BA) 10, fusiform gyrus, and posterior cingulate gyrus, the network recruited by the old included more anterior areas, i.e., dorsolateral prefrontal cortex (BA 9/46), middle cingulate gyrus, and caudate nucleus. Recruitment of a distinct corticolimbic network for visual memory in the elderly suggests that age-related neurobiological deterioration not only results in focal changes but also in the modification of large-scale network operations.

Adult↗
PubMed2026

Childhood Trauma and Frontoparietal Network Connectivity During Working Memory Task Performance in Individuals With Schizophrenia and Healthy Participants.

Schizophrenia is associated with altered frontoparietal connectivity, which supports higher-order cognition, including working memory. Childhood trauma has been linked to altered functional connectivity and reduced cognitive performance in individuals with schizophrenia and controls. Prior evidence suggests that trauma-related default mode dysconnectivity mediates the association between trauma and cognition. We hypothesised that childhood trauma would be associated with altered frontoparietal connectivity during a working memory task and that such connectivity changes would mediate the relationship between trauma and working memory. Childhood trauma, working memory and fMRI data were collected from individuals with schizophrenia or schizoaffective disorder (n = 38) and controls (n = 128). fMRI data were preprocessed in CONN, and seed-based connectivity analyses were performed for four frontoparietal seeds (bilateral dorsolateral prefrontal and posterior parietal cortices). Connectivity was contrasted across (a) diagnosis and (b) trauma severity. Moderated mediation analyses tested the associations between trauma, connectivity and working memory, with diagnosis as a moderator. Across all participants, higher physical neglect severity predicted poorer working memory performance. Stronger inverse connectivity between left dorsolateral prefrontal and frontal medial cortices predicted better working memory performance. As expected, patients showed widespread frontoparietal dysconnectivity relative to controls, but no differences in frontoparietal connectivity were observed across trauma severity groups. Frontoparietal connectivity did not mediate the association between trauma and working memory, although diagnosis moderated both the trauma-connectivity and connectivity-cognition associations. We conclude that, unlike previous evidence suggesting a mediating role for the default mode network, frontoparietal connectivity did not mediate the trauma-cognition association, possibly suggesting the unique significance of default mode network dysconnectivity in linking trauma to cognition in psychosis.

Humans↗
PubMed2002

Modeling DNA sequence-based cis-regulatory gene networks.

Gene network analysis requires computationally based models which represent the functional architecture of regulatory interactions, and which provide directly testable predictions. The type of model that is useful is constrained by the particular features of developmentally active cis-regulatory systems. These systems function by processing diverse regulatory inputs, generating novel regulatory outputs. A computational model which explicitly accommodates this basic concept was developed earlier for the cis-regulatory system of the endo16 gene of the sea urchin. This model represents the genetically mandated logic functions that the system executes, but also shows how time-varying kinetic inputs are processed in different circumstances into particular kinetic outputs. The same basic design features can be utilized to construct models that connect the large number of cis-regulatory elements constituting developmental gene networks. The ultimate aim of the network models discussed here is to represent the regulatory relationships among the genomic control systems of the genes in the network, and to state their functional meaning. The target site sequences of the cis-regulatory elements of these genes constitute the physical basis of the network architecture. Useful models for developmental regulatory networks must represent the genetic logic by which the system operates, but must also be capable of explaining the real time dynamics of cis-regulatory response as kinetic input and output data become available. Most importantly, however, such models must display in a direct and transparent manner fundamental network design features such as intra- and intercellular feedback circuitry; the sources of parallel inputs into each cis-regulatory element; gene battery organization; and use of repressive spatial inputs in specification and boundary formation. Successful network models lead to direct tests of key architectural features by targeted cis-regulatory analysis.

DNA↗
PubMed2006

Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN) models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array) with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes) are explicitly disfavored in one network module (G2), relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of MBF sites in G1 class genes.

Artificial Intelligence↗
PubMed2005

Bioinformatic methods for integrating whole-genome expression results into cellular networks.

Extracting a comprehensive overview from the huge amount of information arising from whole-genome analyses is a significant challenge. This review critically surveys the state of the art methods that are used to connect information from functional genomic studies to biological function. Cluster analysis methods for inferring the correlation between genes are discussed, as are the methods for integrating gene expression information with existing information on biological pathways and the methods that combine cluster analysis with biological information to reconstruct novel biological networks.

Cluster Analysis↗
PubMed2003

Coordination of cellular pattern-generating circuits that control limb movements: the sources of stable differences in intersegmental phases.

Neuronal mechanisms in nervous systems that keep intersegmental phase lags the same at different frequencies are not well understood. We investigated biophysical mechanisms that permit local pattern-generating circuits in neighboring segments to maintain stable phase differences. We use a modified version of an existing model of the crayfish swimmeret system that is based on three known coordinating neurons and hypothesized intersegmental synaptic connections. Weakly coupled oscillator theory was used to derive coupling functions that predict phase differences between neurons in neighboring segments. We show how features controlling the size of the lag under simplified network configurations combine to create realistic lags in the full network. Using insights from the coupled oscillator theory analysis, we identify an alternative intersegmental connection pattern producing realistic stable phase differences. We show that the persistence of a stable phase lag to changes in frequency can arise from complementary effects on the network with ascending-only or descending-only intersegmental connections. To corroborate the numerical results, we experimentally constructed phase-response curves (PRCs) for two different coordinating interneurons in the swimmeret system by perturbing the firing of individual interneurons at different points in the cycle of swimmeret movement. These curves provide information about the contribution of individual intersegmental connections to the stable phase lag. We also numerically constructed PRCs for individual connections in the model. Similarities between the experimental and numerical PRCs confirm the plausibility of the network configuration that has been proposed and suggest that the same stabilizing balance present in the model underlies the normal phase-constant behavior of the swimmeret system.

Action Potentials↗
PubMed2002

Trypanin is a cytoskeletal linker protein and is required for cell motility in African trypanosomes.

The cytoskeleton of eukaryotic cells is comprised of a complex network of distinct but interconnected filament systems that function in cell division, cell motility, and subcellular trafficking of proteins and organelles. A gap in our understanding of this dynamic network is the identification of proteins that connect subsets of cytoskeletal structures. We previously discovered a family of cytoskeleton-associated proteins that includes GAS11, a candidate human tumor suppressor upregulated in growth-arrested cells, and trypanin, a component of the flagellar cytoskeleton of African trypanosomes. Although these proteins are intimately associated with the cytoskeleton, their function has yet to be determined. Here we use double-stranded RNA interference to block trypanin expression in Trypanosoma brucei, and demonstrate that this protein is required for directional cell motility. Trypanin(minus sign) mutants have an active flagellum, but are unable to coordinate flagellar beat. As a consequence, they spin and tumble uncontrollably, occasionally moving backward. Immunofluorescence experiments demonstrate that trypanin is located along the flagellum/flagellum attachment zone and electron microscopic analysis revealed that cytoskeletal connections between the flagellar apparatus and subpellicular cytoskeleton are destabilized in trypanin(minus sign) mutants. These results indicate that trypanin functions as a cytoskeletal linker protein and offer insights into the mechanisms of flagellum-based cell motility.

Animals↗
PubMed2006

Metabolome, transcriptome, and bioinformatic cis-element analyses point to HNF-4 as a central regulator of gene expression during enterocyte differentiation.

DNA-binding transcription factors bind to promoters that carry their binding sites. Transcription factors therefore function as nodes in gene regulatory networks. In the present work we used a bioinformatic approach to search for transcription factors that might function as nodes in gene regulatory networks during the differentiation of the small intestinal epithelial cell. In addition we have searched for connections between transcription factors and the villus metabolome. Transcriptome data were generated from mouse small intestinal villus, crypt, and fetal intestinal epithelial cells. Metabolome data were generated from crypt and villus cells. Our results show that genes that are upregulated during fetal to adult and crypt to villus differentiation have an overrepresentation of potential hepatocyte nuclear factor (HNF)-4 binding sites in their promoters. Moreover, metabolome analyses by magic angle spinning (1)H nuclear magnetic resonance spectroscopy showed that the villus epithelial cells contain higher concentrations of lipid carbon chains than the crypt cells. These findings suggest a model where the HNF-4 transcription factor influences the villus metabolome by regulating genes that are involved in lipid metabolism. Our approach also identifies transcription factors of importance for crypt functions such as DNA replication (E2F) and stem cell maintenance (c-Myc).

Algorithms↗
PubMed1999

Synaptic cell adhesion proteins and synaptogenesis in the mammalian central nervous system.

Synapses are asymmetric cell-cell contacts, typically formed between the presynaptic axon terminal of a "sending" nerve cell and the postsynaptic dendrite, the soma or - in some cases - the axon of a "receiving" one. The presynaptic axon terminal is specialized for the complex membrane trafficking mechanisms that underlie regulated secretion of neurotransmitter, while the postsynapse is uniquely specialized for signal transduction. Synaptogenesis, the formation of functional synapses, is the final step in the development of the central nervous system. In the mammalian brain it results in the establishment of a neural network, connecting some 10(12) nerve cells with up to 10(15) synapses. In principle, synaptogenesis takes place in two consecutive steps that are most likely mediated by cell adhesion molecules. First, an arriving axonal growth cone identifies its appropriate partner cell, creating an initial contact, and, second, specific axonal and dendritic protein components are recruited to this initial contact site, forming a functional synapse. Three cell adhesion systems have recently been shown to be specifically enriched at synaptic contacts: the cadherin/catenin system, the cadherinlike neuronal receptors, and the beta-neurexin/neuroligin system. Components of all three cell adhesion systems have been localized to synaptic contacts using immunogold electron microscopy but are also present outside of synapses. The present short review discusses the possible role of these synaptic cell adhesion molecules in synaptogenesis.

Animals↗
PubMed1999

Solving the N-bit parity problem using neural networks.

In this letter, a constructive solution to the N-bit parity problem is provided with a neural network that allows direct connections between the input layer and the output layer. The present approach requires no training and adaptation, and thus it warrants the use of the simple threshold activation function for the output and hidden layer neurons. It is previously shown that this choice of activation function and network structure leads to several solutions for the 3-bit parity problem obtained using linear programming. One of the solutions for the 3-bit parity problem is then generalized to obtain a solution for the N-bit parity problem using left floor N/2 right floor hidden layer neurons. It is shown that through the choice of a "staircase" type activation function, the left floor N/2 right floor hidden layer neurons can be further combined into a single hidden layer neuron.

Journal Article↗
PubMed2002

Evolutionary rate in the protein interaction network.

High-throughput screens have begun to reveal the protein interaction network that underpins most cellular functions in the yeast Saccharomyces cerevisiae. How the organization of this network affects the evolution of the proteins that compose it is a fundamental question in molecular evolution. We show that the connectivity of well-conserved proteins in the network is negatively correlated with their rate of evolution. Proteins with more interactors evolve more slowly not because they are more important to the organism, but because a greater proportion of the protein is directly involved in its function. At sites important for interaction between proteins, evolutionary changes may occur largely by coevolution, in which substitutions in one protein result in selection pressure for reciprocal changes in interacting partners. We confirm one predicted outcome of this process-namely, that interacting proteins evolve at similar rates.

Amino Acid Substitution↗
PubMed2026

Amplicon and metagenomic sequencing reveal thifluzamide drive rhizosphere microbial structural shifts and functional adaption.

Thifluzamide (TF) is a widely used phenyl urea fungicide in rice production; however, its impacts on the structural composition and functional dynamics of the rhizosphere microbiome remain poorly understood. Here, we systematically investigated the effects of TF on the structure, interactions, and functional potential of the rice (Oryza sativa L.) rhizosphere microbiome using integrated amplicon sequencing and metagenomic approaches. TF application significantly altered both bacterial and fungal community composition, bacterial diversity was markedly reduced, whereas fungal diversity increased. With bacterial diversity markedly reduced while fungal diversity increased. Beta-diversity analyses revealed strong treatment-driven community separation, indicating pronounced TF-induced microbial restructuring. Co-occurrence network analysis demonstrated reduced complexity and connectivity in bacterial networks but increased negative co-occurrence patterns within fungal communities, suggesting contrasting stability responses between microbial kingdoms. Metagenomic profiling further revealed substantial functional shifts, including the differential enrichment of KEGG and COG pathways associated with xenobiotic metabolism. Notably, while total ARG abundance remained stable, TF exposure altered the resistome profile by selectively enriching specific classes of antibiotic resistance genes (ARGs), biocide resistance genes (BRGs), and mobile genetic elements (MGEs). Strong positive correlations between MGEs and ARGs highlighted an elevated potential for horizontal gene transfer. Metagenome-assembled genome (MAG) analysis identified specific TF-enriched bacterial taxa, including Methylophilus, Sulfurospirillum, and Azospirillum, which harbored genes involved in pesticide degradation and xenobiotic transformation. Collectively, these findings demonstrate that TF profoundly reshapes the rice rhizosphere microbiome by altering microbial diversity, interaction networks, resistance gene profiles, and functional capacities. This study provides genomic insights into fungicide-microbiome interactions, underscoring the potential ecological implications associated with TF application, while identifying candidate microbial taxa that may contribute to pesticide degradation and rhizosphere microecology resilience.

Rhizosphere↗
PubMed2003

A functions localized neural network with branch gates.

In this paper, a functions localized network with branch gates (FLN-bg) is studied, which consists of a basic network and a branch gate network. The branch gate network is used to determine which intermediate nodes of the basic network should be connected to the output node with a gate coefficient ranging from 0 to 1. This determination will adjust the outputs of the intermediate nodes of the basic network depending on the values of the inputs of the network in order to realize a functions localized network. FLN-bg is applied to function approximation problems and a two-spiral problem. The simulation results show that FLN-bg exhibits better performance than conventional neural networks with comparable complexity.

Animals↗
PubMed2006

Voxel-based diffusion tensor analysis reveals aberrant anterior cingulum integrity in posttraumatic stress disorder due to terrorism.

Recent functional neuroimaging work has suggested that interregional functional connectivity between the anterior cingulate cortex (ACC), other limbic, and prefrontal regions may be involved in the pathophysiology of posttraumatic stress disorder (PTSD). However, less attention has been paid to the white matter network. Voxel-based analysis enables an exploration of morphological or functional changes throughout the entire brain. Here we undertook the first application of this technology to diffusion tensor data in patients with PTSD. Participants were 9 victims of the Tokyo subway sarin attack with PTSD and 16 matched victims of the same traumatic event without PTSD. The voxel-based analysis showed a significant fractional anisotropy increase in the left anterior cingulum, subjacent to the left ACC gray matter where we previously found a volume decrement, in PTSD subjects. Moreover, the severity was positively, but not significantly associated with the fractional anisotropy of the left anterior cingulum in the victims with PTSD, using the region of interest defined in the native space with the inverse normalization technique. The present study demonstrated further evidence of abnormalities of both the ACC, a structure that is pivotally involved in attention, emotional regulation, and fear conditioning, and of subjacent white matter in the pathology of PTSD.

Adult↗
PubMed1990

Functions of the nociceptive primary neurons.

The functions of nociceptive primary neurons are reviewed in brief, with special reference to the polymodal receptor. The polymodal receptor is considered to be a primitive sensory receptor that is not well differentiated and that plays important roles in signaling pain especially from tissues in pathological states, and in causing reflex modulations of a wide variety of bodily functions. This sensory receptor is characterized by the existence of neuropeptides in its neuron. The wide distribution of the central axon branchings of this neuron and the long-lasting effects of the neuropeptides released from the axon terminals provide an "analogue-like" action of the nervous system, which had hitherto been considered to be "digital-like," point-to-point connections in the central neuron network. Neuropeptides released from the peripheral endings of this neuron, on the other hand, play important roles in local regulation of such functions as inflammation, visceral tract motility, trophic effects, immune system functioning and so on. The functions of nociceptive primary neurons are, therefore, not limited to sensory function but should be understood as a component related to the regulation of fundamental functions of the entire organism.

Afferent Pathways↗