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Results for “functional network connectivity”

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PubMed2006

Topological determinants of epileptogenesis in large-scale structural and functional models of the dentate gyrus derived from experimental data.

In temporal lobe epilepsy, changes in synaptic and intrinsic properties occur on a background of altered network architecture resulting from cell loss and axonal sprouting. Although modeling studies using idealized networks indicated the general importance of network topology in epilepsy, it is unknown whether structural changes that actually take place during epileptogenesis result in hyperexcitability. To answer this question, we built a 1:1 scale structural model of the rat dentate gyrus from published in vivo and in vitro cell type-specific connectivity data. This virtual dentate gyrus in control condition displayed globally and locally well connected ("small world") architecture. The average number of synapses between any two neurons in this network of over one million cells was less than three, similar to that measured for the orders of magnitude smaller C. elegans nervous system. To study how network architecture changes during epileptogenesis, long-distance projecting hilar cells were gradually removed in the structural model, causing massive reductions in the number of total connections. However, as long as even a few hilar cells survived, global connectivity in the network was effectively maintained and, as a result of the spatially restricted sprouting of granule cell axons, local connectivity increased. Simulations of activity in a functional dentate network model, consisting of over 50,000 multicompartmental single-cell models of major glutamatergic and GABAergic cell types, revealed that the survival of even a small fraction of hilar cells was enough to sustain networkwide hyperexcitability. These data indicate new roles for fractionally surviving long-distance projecting hilar cells observed in specimens from epilepsy patients.

Animals↗

PubMed2003

Two mitofusin proteins, mammalian homologues of FZO, with distinct functions are both required for mitochondrial fusion.

Mitochondria are dynamic organelles that undergo frequent fission and fusion or branching. Although these morphologic changes are considered crucial for cellular functions, the underlying mechanisms remain elusive, especially in mammalian cells. We characterized two rat mitochondrial outer membrane proteins, Mfn1 and Mfn2, with distinct tissue expressions, that are homologous to Drosophila Fzo, a GTPase involved in mitochondrial fusion. Expression of the GTPase-domain mutant of Mfn2 (Mfn2(K109T)) in HeLa cells induced mitochondrial fragmentation in which Mfn2(K109T) localized at the restricted domains. Immuno-electronmicroscopy revealed that Mfn2(K109T) was concentrated at the contact domains between adjacent mitochondria, suggesting that fusion of the outer membrane was arrested at some intermediate step. Mfn1 expression induced highly connected tubular network structures depending on the functional GTPase domain. The Mfn1-induced tubular networks were suppressed by co-expression with Mfn2. In vivo depletion of either isoform by RNA interference revealed that both are required to maintain normal mitochondrial morphology. The fusion of differentially-labeled mitochondria in HeLa cells subjected to depletion of either Mfn isoform and subsequent cell fusion by hemagglutinating virus of Japan revealed that both proteins have distinct functions in mitochondrial fusion. We conclude that the two Mfn isoforms cooperate in mitochondrial fusion in mammalian cells.

Animals↗

PubMed2003

Necessary and sufficient condition for absolute stability of normal neural networks.

Globally convergent dynamics of a class of neural networks with normal connection matrices is studied by using the Lyapunov function method and spectral analysis of the connection matrices. It is shown that the networks are absolutely stable if and only if all the real parts of the eigenvalues of the connection matrices are nonpositive. This extends an existing result on symmetric neural networks to a larger class including certain asymmetric networks. Further extension of the present result to certain non-normal case leads naturally to a quasi-normal matrix condition, which may be interpreted as a generalization of the so-called principle of detailed balance for the connection weights or the quasi-symmetry condition that was previously proposed in the literature in association with symmetric neural networks. These results are of particular interest in neural optimization and classification problems.

Models, Theoretical↗

PubMed2006

Influence of metabolic network structure and function on enzyme evolution.

BACKGROUND: Most studies of molecular evolution are focused on individual genes and proteins. However, understanding the design principles and evolutionary properties of molecular networks requires a system-wide perspective. In the present work we connect molecular evolution on the gene level with system properties of a cellular metabolic network. In contrast to protein interaction networks, where several previous studies investigated the molecular evolution of proteins, metabolic networks have a relatively well-defined global function. The ability to consider fluxes in a metabolic network allows us to relate the functional role of each enzyme in a network to its rate of evolution. RESULTS: Our results, based on the yeast metabolic network, demonstrate that important evolutionary processes, such as the fixation of single nucleotide mutations, gene duplications, and gene deletions, are influenced by the structure and function of the network. Specifically, central and highly connected enzymes evolve more slowly than less connected enzymes. Also, enzymes carrying high metabolic fluxes under natural biological conditions experience higher evolutionary constraints. Genes encoding enzymes with high connectivity and high metabolic flux have higher chances to retain duplicates in evolution. In contrast to protein interaction networks, highly connected enzymes are no more likely to be essential compared to less connected enzymes. CONCLUSION: The presented analysis of evolutionary constraints, gene duplication, and essentiality demonstrates that the structure and function of a metabolic network shapes the evolution of its enzymes. Our results underscore the need for systems-based approaches in studies of molecular evolution.

Amino Acid Substitution↗

PubMed2001

Multimodal characterisation of cortical areas by multivariate analyses of receptor binding and connectivity data.

Cortical areas are regarded as fundamental structural and functional units within the information processing networks of the brain. Their properties have been described extensively by cyto-, myelo- and chemoarchitectonics, cortical and extracortical connectivity patterns, receptive field mapping, activation properties, lesion effects, and other structural and functional characteristics. Systematic integrative approaches aiming at multimodal characterisations of cortical areas or at the delineation of global features of the cortical network, however, are still scarce and usually limited to a single data modality, such as cytoarchitectonical or tract tracing data. Here we describe a methodological framework for the systematic evaluation, comparison and integration of different data modalities from the brain and demonstrate its practical application and significance in the analysis of receptor binding and connectivity data within the motor and visual cortices of macaque monkeys. The framework builds on algorithmic methods to convert data between different cortical parcellation schemes, as well as on statistical techniques for the exploration of multivariate data sets comprising data of different types and scales. Thereby, we establish a relationship between intrinsic area properties as expressed by quantitative receptor binding, and extrinsic inter-area communication, which relies on anatomical connectivity. Our analyses provide preliminary evidence for a good correspondence of these two data types in the motor cortex, and their partial discrepancy in the visual cortex, raising hypotheses about the different organisational aspects highlighted by receptors and connectivity. The methodological framework presented here is flexible enough to accommodate a wide range of further data modalities, and is specific enough to permit novel insights and predictions concerning brain organisation. Thus, this approach promises to be very useful in the endeavour to characterise multimodal structure-function relationships in the brain.

Animals↗

PubMed2006

Magnetoencephalographic evaluation of resting-state functional connectivity in Alzheimer's disease.

Statistical interdependencies between magnetoencephalographic signals recorded over different brain regions may reflect the functional connectivity of the resting-state networks. We investigated topographic characteristics of disturbed resting-state networks in Alzheimer's disease patients in different frequency bands. Whole-head 151-channel MEG was recorded in 18 Alzheimer patients (mean age 72.1 years, SD 5.6; 11 males) and 18 healthy controls (mean age 69.1 years, SD 6.8; 7 males) during a no-task eyes-closed resting state. Pair-wise interdependencies of MEG signals were computed in six frequency bands (delta, theta, alpha1, alpha2, beta and gamma) with the synchronization likelihood (a nonlinear measure) and coherence and grouped into long distance (intra- and interhemispheric) and short distance interactions. In the alpha1 and beta band, Alzheimer patients showed a loss of long distance intrahemispheric interactions, with a focus on left fronto-temporal/parietal connections. Functional connectivity was increased in Alzheimer patients locally in the theta band (centro-parietal regions) and the beta and gamma band (occipito-parietal regions). In the Alzheimer group, positive correlations were found between alpha1, alpha2 and beta band synchronization likelihood and MMSE score. Resting-state functional connectivity in Alzheimer's disease is characterized by specific changes of long and short distance interactions in the theta, alpha1, beta and gamma bands. These changes may reflect loss of anatomical connections and/or reduced central cholinergic activity and could underlie part of the cognitive impairment.

Aged↗

PubMed2004

Extending the global workspace theory to emotion: phenomenality without access.

Recent accounts on the global workspace theory suggest that consciousness involves transient formations of functional connections in thalamo-cortico-cortical networks. The level of connectivity in these networks is argued to determine the state of consciousness. Emotions are suggested to play a role in shaping consciousness, but their involvement in the global workspace theory remains elusive. In the present study, the role of emotion in the neural workspace theory of consciousness was scrutinized by investigating, whether unconscious (masked) and conscious (unmasked) display of emotional compared to neutral facial expressions would differentially modulate EEG coherence. EEG coherence was measured by means of computing an average EEG coherence value between the frontal, parietal, and midline scalp sites. Objective awareness checks evidenced that conscious identification of the masked facial expressions was precluded. Analyses revealed reductions in EEG coherence in the lower frequency range for the masked as compared to unmasked neutral facial expressions. Crucially, a decline in EEG coherence was not observed for the emotional facial expressions. In other words, the level of EEG coherence did apparently vary as a function of awareness, but not when emotion was involved. The current finding suggests that EEG coherence is modulated by unconscious emotional processes, which extends common views on the global workspace architecture of consciousness.

Adult↗

PubMed1998

Hints of a functional connection between the neuropeptidergic innervation of arteriovenous anastomoses and the appearance of epithelioid cells in the rabbit ear.

Peripheral blood flow can be regulated by specialized vessel segments, the arteriovenous anastomoses. Their wall consists of a relatively thick layer of smooth muscle cells and so-called epithelioid cells. The epithelioid cell is a specialized myogenic cell phenotype expressing nitric oxide synthase. We studied the innervation of the different segments of arteriovenous anastomoses in the rabbit ear using antisera against neuropeptide Y, tyrosine hydroxylase, calcitonin gene-related peptide and substance P, as well as neuron-specific enolase, calbindin D and neurotubulin. The participation was especially examined of neuropeptidergic innervation and a possible morphological connection to the occurrence of epithelioid cells and a paracrine function. The NADPH diaphorase reaction and alpha-smooth muscle actin immunoelectron microscopy served to distinguish epithelioid cells from smooth muscle cells. Using conventional fluorescence microscopy and confocal laser scanning microscopy, we found the most dense innervation pattern of pan-neuronal markers (neurotubulin, neuron-specific enolase), tyrosine hydroxylase-immunoreactive nerve fibres and neuropeptidergic nerve fibres (neuropeptide Y, calcitonin gene-related peptide, substance P) around the intermediate segment in arteriovenous anastomoses, whereas the venous segment was barely marked. Single nerve fibres penetrated into the medial layer and reached the epithelioid cells. Using immunoelectron microscopy, we found intercellular contacts between epithelioid cells, but not the gap junction protein connexin 43. Here, we report for the first time a correlation of the innervation pattern with epithelioid cell type in arteriovenous anastomoses. Our findings suggest that epithelioid cells of the arteriovenous anastomoses are controlled by a dense network of neuropeptidergic nerve fibres in functional connection to their paracrine role as a nitric oxide producer.

Animals↗

PubMed2004

New approaches for exploring anatomical and functional connectivity in the human brain.

Information processing in the primate brain is based on the complementary principles of modular and distributed information processing. The former emphasizes the specialization of functions within different brain areas. The latter emphasizes the massively parallel nature of brain networks and the fact that function also emerges from the flow of information between brain areas. The localization of function to specific brain areas ("functional segregation") is the commonest approach to investigating function; however, an emerging, complementary approach ("functional integration") describes function in terms of the information flow across networks of areas. Here, we highlight recent advances in neuroimaging methodology that have made it possible to investigate the anatomical architecture of networks in the living human brain with diffusion tensor imaging (DTI). We also highlight recent thinking on the ways in which functional imaging can be used to characterize information transmission across networks in the human brain (functional and effective connectivity).

Animals↗

PubMed2005

From anatomic standardization analysis of perfusion SPECT data to perfusion pattern modeling: evidence of functional networks in healthy subjects and temporal lobe epilepsy patients.

RATIONALE AND OBJECTIVES: In the general context of perfusion pattern modeling from single-photon emission computed tomographic (SPECT) data, the purpose of this study is to characterize interindividual functional variability and functional connectivity between anatomic structures in a set of SPECT data acquired from a homogeneous population of subjects. MATERIALS AND METHODS: From volume of interest (VOI)-perfusion measurements performed on anatomically standardized SPECT data, we proposed to use correspondence analysis (CA) and hierarchical clustering (HC) to explore the structure of statistical dependencies among these measurements. The method was applied to study the perfusion pattern in two populations of subjects; namely, SPECT data from 27 healthy subjects and ictal SPECT data from 10 patients with mesio-temporal lobe epilepsy (MTLE). RESULTS: For healthy subjects, anatomic structures showing statistically dependent perfusion patterns were classified into four groups; namely, temporomesial structures, internal structures, posterior structures, and remaining cortex. For patients with MTLE, they were classified as temporomesial structures, surrounding temporal structures, internal structures, and remaining cortex. Anatomic structures of each group showed similar perfusion behavior so that they may be functionally connected and may belong to the same network. Our main result is that the temporal pole and lenticular nucleus seemed to be highly relevant to characterize ictal perfusion in patients with MTLE. This exploratory analysis suggests that a network involving temporal structures, lenticular nucleus, brainstem, and cerebellum seems to be involved during MTLE seizures. CONCLUSION: CA followed by HC is a promising approach to explore brain perfusion patterns from SPECT VOI measurements.

Adult↗

PubMed1997

Activity-dependent wiring of the developing hippocampal neuronal circuit.

In the developing hippocampus, functional excitatory synaptic connections seem to be recruited from a preformed, initially silent synaptic network. This functional synapse induction requires presynaptic action potentials paired with postsynaptic depolarization, thus obeying Hebb's rule of association. During early postnatal development the hippocampus exhibits an endogenous form of patterned neuronal activity that is driven by GABAergic depolarization. We propose that this recurrent activity promotes the input-specific induction of functional synapses in the CA1 region. Thus, activity-dependent synaptic reorganization in the developing hippocampus appears to be dominated by an active recruitment of new synapses rather than an active elimination of redundant connections.

Journal Article↗

PubMed2001

Critical behavior of propagation on small-world networks.

We report numerical evidence that an epidemiclike model, which can be interpreted as the propagation of a rumor, exhibits critical behavior at a finite randomness of the underlying small-world network. The transition occurs between a regime where the rumor "dies" in a small neighborhood of its origin, and a regime where it spreads over a finite fraction of the whole population. Critical exponents are evaluated through finite-size scaling analysis, and the dependence of the critical randomness with the network connectivity is studied. The behavior of this system as a function of the small-network randomness bears noticeable similarities with an epidemiological model reported recently [M. Kuperman and G. Abramson, Phys. Rev. Lett. 86, 2909 (2001)], in spite of substantial differences in the respective dynamical rules.

Biophysical Phenomena↗

PubMed2004

A first-draft human protein-interaction map.

BACKGROUND: Protein-interaction maps are powerful tools for suggesting the cellular functions of genes. Although large-scale protein-interaction maps have been generated for several invertebrate species, projects of a similar scale have not yet been described for any mammal. Because many physical interactions are conserved between species, it should be possible to infer information about human protein interactions (and hence protein function) using model organism protein-interaction datasets. RESULTS: Here we describe a network of over 70,000 predicted physical interactions between around 6,200 human proteins generated using the data from lower eukaryotic protein-interaction maps. The physiological relevance of this network is supported by its ability to preferentially connect human proteins that share the same functional annotations, and we show how the network can be used to successfully predict the functions of human proteins. We find that combining interaction datasets from a single organism (but generated using independent assays) and combining interaction datasets from two organisms (but generated using the same assay) are both very effective ways of further improving the accuracy of protein-interaction maps. CONCLUSIONS: The complete network predicts interactions for a third of human genes, including 448 human disease genes and 1,482 genes of unknown function, and so provides a rich framework for biomedical research.

Databases, Protein↗

PubMed1996

Counting and classifying attractors in high dimensional dynamical systems.

Randomly connected Boolean networks have been used as mathematical models of neural, genetic, and immune systems. A key quantity of such networks is the number of basins of attraction in the state space. The number of basins of attraction changes as a function of the size of the network, its connectivity and its transition rules. In discrete networks, a simple count of the number of attractors does not reveal the combinatorial structure of the attractors. These points are illustrated in a reexamination of dynamics in a class of random Boolean networks considered previously by Kauffman. We also consider comparisons between dynamics in discrete networks and continuous analogues. A continuous analogue of a discrete network may have a different number of attractors for many different reasons. Some attractors in discrete networks may be associated with unstable dynamics, and several different attractors in a discrete network may be associated with a single attractor in the continuous case. Special problems in determining attractors in continuous systems arise when there is aperiodic dynamics associated with quasiperiodicity of deterministic chaos.

Animals↗

PubMed2005

Insights to metabolic network evolution by fusion proteins.

Human fusion proteins consisting of two or more fusion partners of prokaryotic origin exhibit accreted function. Recent studies have elucidated the importance of fusion proteins in complex regulatory networks. The significance of fusion proteins in cellular networks and their evolutionary mechanism is largely unknown. Here, we discuss the association of six fusion proteins with the citric acid cycle. We define possible gene fusion scenarios and show that they produce metabolites with high connectivity for complex networking. Complex networking of metabolites requires proteins with incremental structural architectures and functional capabilities. Such higher order functionality is frequently provided by fusion proteins. Therefore, evolution of fusion proteins capable of producing metabolites with greater connectivity for enhanced cross-talk between pathways is critical for the selection of multiple trajectories in maintaining a stoichiometric balance during regulation. The association of six fusion proteins with the citric acid cycle and their capability to produce metabolites with high connectivity index is intriguing. This suggests that fusion gene products and their evolution have had a key role in the selection of complex multifaceted networks. In addition, we propose that fusion proteins have gained additive biochemical function for a balanced regulation of metabolic networks.

Biological Evolution↗

PubMed1990

Alteration of the humoral immune response against muscle acetylcholine receptor by timed administration of alpha(1----3)dextran.

Previously, we discovered a profound idiotypic connectivity among antibodies involved in the immune responses to alpha(1----3)dextran (Dex) and the acetylcholine receptor (AChR). The present studies were undertaken to assess whether these connections represent functional pathways for regulation. It was found that immunization of mice with Dex prior to challenge with AChR reduced the subsequent response to receptor. The timing of the Dex administration was crucial for this effect with a 6-day delay between Dex and AChR being optimal whereas 0- or 12-day delays proved ineffective. The suppressive effect was specific for Dex, as treatment with the closely related, but idiotypically distinct, alpha(1----6)dextran did not diminish the anti-AChR response. Consistent with functional connections in the AChR-Dex network, an inverse relationship between anti-AChR and anti-Dex antibodies was observed in these studies. Thus, high levels of anti-AChR antibodies were associated with low levels of anti-Dex antibodies and vice versa. A similar relationship was observed for serum antibodies from patients with myasthenia gravis. To investigate the mechanism for the antigen-induced cross-regulation, hybridomas were constructed from spleen cells of mice treated 6 days earlier with Dex. A variety of idiotypes (Id), anti-Id and anti-anti-Id were obtained from this fusion. In addition, sera from day-6 mice were examined for the expression of key anti-Id which might provide regulation in the anti-AChR response. The main feature of these sera was the presence of EB3-7-reactive antibodies which did not bind Dex, and hence were not identical to J558. A monoclonal antibody with similar properties was obtained from the day-6 fusion (DX6) which had additional binding specificity for anti-AChR antibodies. Antibodies induced by Dex immunization appear to participate in the cross-regulation observed here. Understanding the mechanisms involved in this phenomenon will have important implications for network theory and for prediction of immune responsiveness.

Animals↗

PubMed2006

Effects of treatment with the atypical neuroleptic quetiapine on working memory function: a functional MRI follow-up investigation.

BACKGROUND: Working memory as a part of higher-order executive functions is defined by the parallel storage and processing of information. Recent functional fMRI studies have revealed a functional, interregional disintegration of a neuronal network connecting cortical, subcortical and cerebellar regions in schizophrenic patients (SZ). Cognitive impairment in working memory is a core psychopathological correlate of schizophrenic symptoms. Atypical neuroleptics such as quetiapine have shown good efficacy in treating positive and negative symptoms. The presented study evaluated the impact of a neuroleptic steady state treatment with quetiapine on the altered working memory activation patterns in schizophrenia. METHODS: Patients were examined by fMRI at baseline and after 12 weeks of steady state treatment with quetiapine. Matched healthy controls (HC) underwent baseline examination. In the scanner, stimuli were presented in a 2-back and 0-back condition of a working memory (wm) paradigm, whereby a degraded and a non-degraded version were used each time. Additionally, behavioural responses (reaction time to target stimuli and error ratio) were measured. RESULTS: At baseline, healthy controls revealed increased activity in the frontal lobe, especially in regions of the prefrontal cortex. Compared to HC, SZ showed hypoactivation in the right dorsolateral prefrontal cortex (DLPFC) and the ventrolateral prefrontal cortex (VLPFC) bilaterally for the 2-back condition. In the 2-back degraded condition there was a hypoactivation in both, the right DLPFC and the VLPFC. Additionally, patients showed bilaterally decreased activation in the basalganglia in the 2-back and in the right caudatus in the 2-back degraded condition compared to healthy controls. After treatment with quetiapine, patients activations patterns were increased. The pre-post comparison of the 2-back condition revealed a significant increase of activation in the left VLPFC at a significance level of 0.001 (uncorrected). The 2-back degraded condition led to a significant activation pattern in the lingual gyrus and the right precuneus. In both wm conditions, at baseline there were no differences in reaction time but only a worse performance in SZ. After treatment, behavioural measurement of responses, including reaction time and performance, showed slight improvements in SZ, although these did not reach statistical significance. CONCLUSIONS: The neuronal networks underlying working memory are clearly altered in schizophrenia. After 12 weeks of treatment with quetiapine monotherapy, patients showed significant clinical improvement and revealed increased BOLD activity in the VLPFC during a working memory task, although there was no improvement of cognitive performance.

Adult↗

PubMed2004

The functional anatomy of inspection time: an event-related fMRI study.

Twenty healthy young adults underwent functional magnetic resonance imaging (fMRI) of the brain while performing a visual inspection time task. Inspection time is a forced-choice, two-alternative visual backward-masking task in which the subject is briefly shown two parallel vertical lines of markedly different lengths and must decide which is longer. As stimulus duration decreases, performance declines to chance levels. Individual differences in inspection time correlate with higher cognitive functions. An event-related design was used. The hemodynamic (blood oxygenation level-dependent; BOLD) response was computed as both a function of the eight levels of stimulus duration, from 6 ms (where performance is almost at chance) to 150 ms (where performance is nearly perfect), and a function of the behavioral responses. Random effects analysis showed that the difficulty of the visual discrimination was related to bilateral activation in the inferior fronto-opercular cortex, superior/medial frontal gyrus, and anterior cingulate gyrus, and bilateral deactivation in the posterior cingulate gyrus and precuneus. Examination of the time courses of BOLD responses showed that activation was related specifically to the more difficult, briefer stimuli and that deactivation was found across most stimulus levels. Functional connectivity suggested the existence of two networks. One comprised the fronto-opercular area, intrasylvian area, medial frontal gyrus, and the anterior cingulate cortex (ACC), possibly associated with processing of visually degraded percepts. A posterior network of sensory-related and associative regions might subserve processing of a visual discrimination task that has high processing demands and combines several fundamental cognitive domains. fMRI can thus reveal information about the neural correlates of mental events which occur over very short durations.

Adult↗