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PubMed1993

Lattice neural network minimization. Application of neural network optimization for locating the global-minimum conformations of proteins.

A way of formulating the protein-folding problem in neural network optimization terms is presented in this paper. This is accomplished by representing the conformation of a protein as an array of the amino acid sequence versus position on a three-dimensional face-centered cubic lattice with an energy function defined in terms of the array variables. The method is called lattice neural network minimization (LNNM). Using the neural network minimization method, the energy function is minimized to locate the global minimum energy for the conformation of the protein. The energy function consisted of site exclusion and bond connectivity penalty terms and a pairwise contact energy potential. The contact energy potential used in the procedure is the united-residue potential of Miyazawa, Jernigan and Covell. The LNNM method found the global minimum for a seven-residue peptide in all of the 15 runs carried out. The time for each run was approximately 30 seconds on one processor of an IBM 3090 computer. For a nine-residue peptide, the global minimum was found in 7 out of 15 runs (47%) in approximately 50 seconds per run. For this peptide, LNNM found the global minimum or the second lowest minimum in 10 of the runs. In the same total CPU times (approximately 750 seconds), a Monte Carlo simulated annealing method found the global minimum or the second lowest minimum in only two runs, demonstrating the superiority of LNNM over the standard Monte Carlo simulated annealing method for this nine-residue peptide. Starting from a uniform array for the protein crambin (46 residues) on the lattice, the energy of the crambin array was minimized and a compact low-energy structure was found in approximately 25 minutes of CPU time. Its energy was much lower than that of the native protein, suggesting that there are inadequacies in the Miyazawa-Jernigan-Covell potential. The LNNM method was applied to the prediction of what was previously called nucleation but more properly called chain-folding initiation sites (CFIS) of a protein. LNNM correctly predicted the CFIS for the two proteins examined, RNase S and T4 lysozyme. The LNNM method was also applied to another chain optimization problem, minimization of the root-mean-square distance error (r.m.s.d.) (a measure similar to r.m.s. deviation) in fitting X-ray structures to a lattice, with good results.

Models, Chemical↗

PubMed2005

Brain activity during emotionally negative pictures in schizophrenia with and without flat affect: an fMRI study.

The aim of this functional magnetic resonance imaging (fMRI) study was to compare regional brain activity in schizophrenia subjects with (FA+) and without (FA-) flat affect during the viewing of emotionally negative pictures. Thirteen FA+ subjects and 11 FA- subjects were scanned while being presented with a series of emotionally negative and neutral pictures. Experientially, the viewing of the negative pictures induced a negative emotional state whose intensity was significantly greater in the FA- group than in the FA+ group. Neurally, the Negative minus Neutral contrast revealed, in the FA- group, significant loci of activation in the midbrain, pons, anterior cingulate cortex, insula, ventrolateral orbitofrontal cortex, anterior temporal pole, amygdala, medial prefrontal cortex, and extrastriate visual cortex. In the FA+ group, this contrast produced significant loci of activation in the midbrain, pons, anterior temporal pole, and extrastriate visual cortex. When the brain activity measured in the FA+ group was subtracted from that measured in the FA- group, only the lingual gyrus was significantly activated. Perhaps in FA+ subjects an amygdaloid malfunction rendered the amygdala unable to correctly evaluate the emotional meaning of the pictures presented, thus preventing effective connectivity linking the amygdala to the brain regions implicated in the physiological and experiential dimensions of emotion. Alternatively, a disturbance of effective connectivity in the neural networks linking the midbrain and the medial prefrontal system may have been responsible for the quasi absence of emotional reaction in FA+ subjects, and the abnormal functioning of the medial prefrontal cortex and anterior cingulate cortex in the FA+ group.

Adult↗

PubMed1991

Structural analysis of neural circuits using the theory of directed graphs.

A new approach to analysis of structural properties of biological neural circuits is proposed based on their representation in the form of abstract structures called directed graphs. To exemplify this methodology, structural properties of a biological neural network and randomly wired circuits (RC) were compared. The analyzed biological circuit (BC) represented a sample of 39 neural nuclei which are responsible for the control of the cardiovascular function in higher vertebrates. Initially, direct connections of both circuits were stored in a square matrix format. Then, standard algorithms derived from the theory of directed graphs were applied to analyze the pathways of the circuits according to their length (in number of synapses), degree of connectedness, and structural strength. Thus, the BC was characterized by the presence of short, reciprocal, and unidirectional pathways which presented a high degree of heterogeneity in their strengths. This heterogeneity was mainly due to the existence of a small cluster of reciprocally connected neural nuclei in the circuit that have access, through short pathways, to most of the network. On the other hand, RCs were characterized by the presence of long and mainly reciprocal pathways which showed lower and absolute homogeneous strengths. Through this study the proposed methodology was demonstrated to be a simple and efficient way to store, analyze, and compare basic neuroanatomical information.

Animals↗

PubMed2006

Correlated fragile site expression allows the identification of candidate fragile genes involved in immunity and associated with carcinogenesis.

BACKGROUND: Common fragile sites (cfs) are specific regions in the human genome that are particularly prone to genomic instability under conditions of replicative stress. Several investigations support the view that common fragile sites play a role in carcinogenesis. We discuss a genome-wide approach based on graph theory and Gene Ontology vocabulary for the functional characterization of common fragile sites and for the identification of genes that contribute to tumour cell biology. RESULTS: Common fragile sites were assembled in a network based on a simple measure of correlation among common fragile site patterns of expression. By applying robust measurements to capture in quantitative terms the non triviality of the network, we identified several topological features clearly indicating departure from the Erdos-Renyi random graph model. The most important outcome was the presence of an unexpected large connected component far below the percolation threshold. Most of the best characterized common fragile sites belonged to this connected component. By filtering this connected component with Gene Ontology, statistically significant shared functional features were detected. Common fragile sites were found to be enriched for genes associated to the immune response and to mechanisms involved in tumour progression such as extracellular space remodeling and angiogenesis. Moreover we showed how the internal organization of the graph in communities and even in very simple subgraphs can be a starting point for the identification of new factors of instability at common fragile sites. CONCLUSION: We developed a computational method addressing the fundamental issue of studying the functional content of common fragile sites. Our analysis integrated two different approaches. First, data on common fragile site expression were analyzed in a complex networks framework. Second, outcomes of the network statistical description served as sources for the functional annotation of genes at common fragile sites by means of the Gene Ontology vocabulary. Our results support the hypothesis that fragile sites serve a function; we propose that fragility is linked to a coordinated regulation of fragile genes expression.

Cells, Cultured↗

PubMed2003

Nanotube-vesicle networks with functionalized membranes and interiors.

We describe nanotube-vesicle networks with reconstituted membrane protein from cells and with interior activity defined by an injection of microparticles or molecular probes. The functionality of a membrane protein after reconstitution was verified by single-channel ion conductance measurements in excised inside-out patches from the vesicle membranes. The distribution of protein, determined by fluorescence detection, in the network membrane was homogeneous and could diffuse via a nanotube connecting two vesicles. We also show how injecting small unilamellar protein-containing vesicles can differentiate the contents of individual containers in a network. The combination of membrane activity and interior activity was demonstrated by ionophore-assisted accumulation, and internal Calcium Green-mediated detection, of Ca2+ within a single network container. This system can model a variety of biological functions and complex biological multicompartment structures and might serve as a platform for constructing complex sensor and computational devices.

Biomimetic Materials↗

PubMed2004

Distraction modulates connectivity of the cingulo-frontal cortex and the midbrain during pain--an fMRI analysis.

Neuroimaging studies with positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have delineated a human pain network in vivo. Despite the recognition of cerebral structures engaged in pain transmission, the cerebral mechanisms involved in pain modulation are still not well understood. Here, we investigated healthy volunteers using fMRI during experimental heat pain and distraction induced by a visual incongruent color-word Stroop task. A factorial design permitted categorical and covariation analysis of four conditions, namely innocuous and noxious heat; with and without distraction. Pain without distraction evoked an activation pattern similar to that observed in previous neuroimaging pain studies. Distraction was associated with a significant reduction of the visual analogue scale (VAS) ratings for pain intensity and unpleasantness and a reduction of pain-related activation in multiple brain areas, particularly in the so-called 'medial pain system'. Distraction significantly increased the activation of the cingulo-frontal cortex including the orbitofrontal and perigenual anterior cingulate cortex (ACC), as well as the periaquaeductal gray (PAG) and the posterior thalamus. Covariation analysis revealed functional interaction between these structures during pain stimulation and distraction, but not during pain stimulation per se. According to our results, the cingulo-frontal cortex may exert top-down influences on the PAG and posterior thalamus to gate pain modulation during distraction.

Adult↗

PubMed1998

Complex microstructures of sensory cortical connections.

The neocortex has a distinctive laminar and modular organization. Although important questions remain regarding structure and function at this level of organization, recent studies are addressing a finer scale of synaptic and network microstructure. New findings concerning network properties are rapidly emerging from approaches in which dual or triple intracellular recordings in vitro are combined with analyses of cell and synaptic morphology, as well as from experiments designed to label multiple cell populations.

Animals↗

PubMed2004

The repulsive guidance molecule RGMa is involved in the formation of afferent connections in the dentate gyrus.

In the developing dentate gyrus, afferent fiber projections terminate in distinct laminas. This relies on an accurately regulated spatiotemporal network of guidance molecules. Here, we have analyzed the functional role of the glycosylphosphatidylinositol (GPI)-anchored repulsive guidance molecule RGMa. In situ hybridization in embryonic and postnatal brain showed expression of RGMa in the cornu ammonis and hilus of the hippocampus. In the dentate gyrus, RGM immunostaining was confined to the inner molecular layer, whereas the outer molecular layers targeted by entorhinal fibers remained free. To test the repulsive capacity of RGMa, different setups were used: the stripe and explant outgrowth assays with recombinant RGMa, and entorhino-hippocampal cocultures incubated either with a neutralizing RGMa antibody (Ab) or with the GPI anchor-digesting drug phosphatidylinositol-specific phospholipase C. Entorhinal axons were clearly repelled by RGMa in the stripe and outgrowth assays. After disrupting the RGMa function, the specific laminar termination pattern in entorhino-hippocampal cocultures was lost, and entorhinal axons entered inappropriate hippocampal areas. Our data indicate an important role of RGMa for the layer-specific termination of the perforant pathway as a repulsive signal that compels entorhinal fibers to stay in their correct target zone.

Afferent Pathways↗

PubMed2006

Optical mapping of spatiotemporal emergence of functional synaptic connections in the embryonic chick olfactory pathway.

In order to understand the functional maturation of the CNS, it is essential to first describe the functional maturation of sensory processing. We have approached this topic by following the ontogenetic patterning of neural circuit formation related to cranial and spinal sensory input using voltage-sensitive dye imaging. In previous studies, we have described the functional maturation of synapses in brainstem/midbrain neural circuits. Here, we elucidate the functional maturation of forebrain circuits by investigating neural networks related to the olfactory nerve (N. I) of chicken embryo. In the isolated N. I-olfactory bulb-forebrain preparation, application of electrical stimulation to N. I elicited excitatory postsynaptic potential (EPSP)-related slow optical signals in the olfactory bulb. The slow signal was mainly mediated by glutamate, and was easily fatigued with repetitive stimuli because of the immaturity of synapses in the embryonic CNS. Ontogenetically, the slow signal was detected from the 6-day embryonic stage, suggesting that functional synaptic connections between N. I and olfactory bulb emerge around this stage. In addition, from the 8-day embryonic stage, another response area was discriminated within the forebrain, which corresponded to the higher-ordered nucleus of the olfactory pathway. In comparison with our previous studies concerning the functional development of other cranial nerve-related sensory nuclei in the embryonic brainstem and midbrain, these results suggest that the olfactory pathway is functionally generated in the early stages of development when neural networks related to other visceral and somatic sensory inputs are also in the process of developing.

Aging↗

PubMed1998

Visuomotor transformations: early cortical mechanisms of reaching.

Recent studies of visually guided reaching in monkeys support the hypothesis that the visuomotor transformations underlying arm movements to spatial targets involve a parallel mechanism that simultaneously engages functionally related frontal and parietal areas linked by reciprocal cortico-cortical connections. The neurons in these areas possess similar combinations of response properties. The multimodal combinatorial properties of these neurons and the gradient architecture of the parietofrontal network emerge as a potential substrate to link the different sensory and motor signals that arise during reaching behavior into common hybrid reference frames. This convergent combinatorial process is evident at early stages of visual information processing in the occipito-parietal cortex, suggesting the existence of re-entrant motor influences on cortical areas once believed to have only visual functions.

Animals↗

PubMed1997

Pattern Categorization and Generalization with a Virtual Neuromolecular Architecture.

A multilevel neuromolecular computing architecture has been developed that provides a rich platform for evolutionary learning. The architecture comprises a network of neuron-like modules with internal dynamics modeled by cellular automata. The dynamics are motivated by the hypothesis that molecular processes operative in real neurons (in particular processes connected with second messenger signals and cytoskeleton-membrane interactions) subserve a signal integrating function. The objective is to create a repertoire of special purpose dynamic pattern processors through an evolutionary search algorithm and then to use memory manipulation algorithms to select combinations of processors from the repertoire that are capable of performing coherent pattern recognition/neurocontrol tasks. The system consists of two layers of cytoskeletally controlled (enzymatic) neurons and two layers of memory access neurons (called reference neurons) divided into a collection of functionally comparable subnets. Evolutionary learning can occur at the intraneuronal level through variations in the cytoskeletal structures responsible for the integration of signals in space and time, through variations in the location of elements that represent readin or readout proteins, and through variations in the connectivity of the neurons. The memory manipulation algorithms that orchestrate the repertoire of neuronal processors also use evolutionary search procedures. The network is capable of performing complicated pattern categorization tasks and of doing so in a manner that balances specificity and generalization. Copyright 1996 Elsevier Science Ltd.

Journal Article↗

PubMed2005

Cerebral mechanisms of prosodic sensory integration using low-frequency bands of connected speech.

Even if speech perception has been reported to involve both left and right hemispheres, converging data have posited the existence of a functional asymmetry at the level of secondary auditory cortices. Using fMRI in 12 right-handed French men listening passively to long connected speech stimuli, we addressed the question of neuronal networks involved in the integration of low frequency bands of speech by comparing 1) differences in brain activity in two listening conditions (FN, NF) differing in the integration of pitch modulations (in FN, low frequencies, obtained by a low-pass filter, are addressed to the left ear while the whole acoustic message is simultaneously addressed to the right ear, NF being the reverse position); 2) differences in brain activity induced by high and low degrees of prosodic expression (expressive vs. flat); and 3) effects of the same connected speech stimulus in the two listening conditions. Each stimulus induced a specific cerebral network, the flat one weakening activations which were mainly reduced to the bilateral STG for both listening conditions. In the expressive condition, the specific sensory integration FN results in an increase of the articulatory loop and new recruitments such as right BA6-44, left BA39-40, the left posterior insula and the bilateral BA30. This finding may be accounted for by the existence of temporal windows differing both in length and in acoustic cues decoding, strengthening the "asymmetric sampling in time" hypothesis posited by Poeppel (Speech Commun 2003; 41:245-255). Such an improvement of prosodic integration could find applications in the rehabilitation of some speech disturbances.

Acoustic Stimulation↗

PubMedDate not supplied

Interrelated modification of excitatory and inhibitory connections in the olivocerebellar neural network.

A model of plasticity is proposed for the olivocerebellar neural network in which the efficiency of the synaptic inputs to different neurons changes simultaneously and interdependently. This effect is based on the following functional characteristics of the network: simultaneous arrival of an afferent signal via mossy fibers to input granule cells and output neurons in the deep cerebellar nuclei; synchronous arrival of the signal from the inferior olive, via climbing fibers and their collaterals, at cells in the input and output layers, and to Purkinje cells, and the existence of local excitatory, inhibitory, and disinhibitory feedback circuits. Increases (decreases) in post-tetanic Ca2+ concentrations relative to the level evoked by the preceding stimulation in these cells are accompanied by decreases (increases) in the activity of cGMP-dependent protein kinase G, with increases (decreases) in the activity of protein phosphatase I. As a result, dephosphorylation (phosphorylation) of ionotropic receptors is accompanied by simultaneous depression (potentiation) of the excitatory input to a given neuron and potentiation (depression) of the inhibitory input to the same neuron. The depolarizing signal from the inferior olive affects synapse modification in different layers of the network in such a way that its presence (absence) depresses (potentiates) the signal sent from the output cells of the cerebellum to other structures.

Animals↗

PubMed2006

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae.

BACKGROUND: The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. RESULTS: We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID (http://www.thebiogrid.org) and SGD (http://www.yeastgenome.org/) databases. CONCLUSION: Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks.

Computational Biology↗

PubMed1999

Remote-rendered 3D CT angiography (3DCTA) as an intraoperative aid in cerebrovascular neurosurgery.

OBJECTIVE: To assess the viability and utility of network-based rendering in the treatment of patients with cerebral aneurysms, we implemented an intraoperative rendering system and protocol using both three-dimensional CT angiography (3DCTA) and perspective volume rendering (PVR). MATERIALS AND METHODS: A Silicon Graphics InfiniteReality engine was connected via a Fast Ethernet network to a workstation in the neurosurgical operating room. A protocol was developed to isolate bone and vessels using an appropriate transfer function. Three-dimensional CT angiogram images were volume rendered and transmitted to the workstation using a bandwidth-conserving remote rendering system, and were rotated, cut using clipping planes, and viewed using normal and perspective views. Twelve patients with intracranial aneurysms were examined at surgery using this system. RESULTS: Rendering performance at optimal operating bandwidths (50-60 Mb/s) was excellent, with regeneration of a high-resolution image in less than 1 s. Network performance varied in two cases, slowing image regeneration. Surgeons found the images to be useful as an adjunct to conventional imaging in understanding the morphology of complex aneurysms and their relationship to the skull base. CONCLUSIONS: Intraoperative volume rendering using 3DCTA is achievable over a network, can reduce hardware costs by amortizing hardware among multiple users, and provides useful imaging information during the surgical treatment of cerebral aneurysms. Future operating suites may incorporate network-transmitted three-dimensional images as additional sources of imaging information.

Aged↗

PubMed1997

Polarized expression of HD1: relationship with the cytoskeleton in cultured human colonic carcinoma cells.

Hemidesmosomes (HDs) mediate adhesion of epithelial cells to the extracellular matrix and have morphological associations with intermediate-size filaments (IFs). Hemidesmosomal molecular components including HD1, the two bullous pemphigoid antigens, and the integrin alpha 6 beta 4 have been identified in HDs of stratified and complex epithelium. In this study, we report that HT29-Fu cells, a human colonic tumor cell line, express two hemidesmosomal components (HD1, alpha 6 beta 4) associated in an adhesion structure termed type II HDs. Immunofluorescence studies showed a colocalization of HD1 and alpha 6 beta 4 in basal patches between actin stress fibers. Using cytochalasin B or vinblastine, two drugs which disrupt the cytoskeleton, we demonstrate that the redistribution of HD1 was probably induced by the reorganization of the basal cytokeratin network. We also show that in vitro HD1 binds to polymerized cytokeratin intermediate filaments; this suggests that HD1 in intestinal epithelial cells functions as a linker protein connecting cytokeratin filaments to the basal plasma membrane, probably through the beta 4 subunit of the integrin alpha 6 beta 4.

Actins↗

PubMed1982

Adaptive filter model of the cerebellum.

The Marr-Albus model of the cerebellum has been reformulated with linear system analysis. This adaptive linear filter model of the cerebellum performs a filtering action of a phase lead-lag compensator with learning capability, and will give an account for the phenomena which have been termed "cerebellar compensation". It is postulated that a Golgi cell may act as a phase lag element; for example, as a leaky integrator with time constant about several seconds. Under this assumption, a mossy fiber - granule cell - Golgi cell input network functions as a phase lead-lag compensator. Output signals from Golgi-granule cell systems, namely, parallel fiber signals, are gathered together through variable synaptic connections to form a Purkinje cell output. From a general theory of adaptive linear filters, learning principles for these modifiable connections are derived. By these learning principles, a Purkinje cell output converges to the "desired response" to minimize the mean square error of the performance. In a more general sense, a Purkinje cell acquires a filtering function on the basis of multiple pairs of input signals and corresponding desired output signals. The mode of convergence of the output signal is described when the input signal is sinusoidal.

Animals↗

PubMed2004

Study of CNG/diesel dual fuel engine's emissions by means of RBF neural network.

Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFEmain performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx, emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.

Energy-Generating Resources↗