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Results for “functional network connectivity”

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At least 739 records · Page 41Linked to original sources

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↗

PubMed2003

Constraints-based models: regulation of gene expression reduces the steady-state solution space.

Constraints-based models have been effectively used to analyse, interpret, and predict the function of reconstructed genome-scale metabolic models. The first generation of these models used "hard" non-adjustable constraints associated with network connectivity, irreversibility of metabolic reactions, and maximal flux capacities. These constraints restrict the allowable behaviors of a network to a convex mathematical solution space whose edges are extreme pathways that can be used to characterize the optimal performance of a network under a stated performance criterion. The development of a second generation of constraints-based models by incorporating constraints associated with regulation of gene expression was described in a companion paper published in this journal, using flux-balance analysis to generate time courses of growth and by-product secretion using a skeleton representation of core metabolism. The imposition of these additional restrictions prevents the use of a subset of the extreme pathways that are derived from the "hard" constraints, thus reducing the solution space and restricting allowable network functions. Here, we examine the reduction of the solution space due to regulatory constraints using extreme pathway analysis. The imposition of environmental conditions and regulatory mechanisms sharply reduces the number of active extreme pathways. This approach is demonstrated for the skeleton system mentioned above, which has 80 extreme pathways. As regulatory constraints are applied to the system, the number of feasible extreme pathways is reduced to between 26 and 2 extreme pathways, a reduction of between 67.5 and 97.5%. The method developed here provides a way to interpret how regulatory mechanisms are used to constrain network functions and produce a small range of physiologically meaningful behaviors from all allowable network functions.

Animals↗

PubMed2003

Topology and correlations in structured scale-free networks.

We study a recently introduced class of scale-free networks showing a high clustering coefficient and nontrivial connectivity correlations. We find that the connectivity probability distribution strongly depends on the fine details of the model. We solve exactly the case of low average connectivity, providing also exact expressions for the clustering and degree correlation functions. The model also exhibits a lack of small-world properties in the whole parameter range. We discuss the physical properties of these networks in the light of the present detailed analysis.

Journal Article↗

PubMed1996

Frequency-spatial transformation: a proposal for parsimonious intra-cortical communication.

This work examines a neural network model of a cortical module, where neurons are organized on a 2-dimensional sheet and are connected with higher probability to their spatial neighbors. Motivated by recent findings that cortical neurons have a resonant peak in their impedance magnitude function, we present a frequency-spatial transformation scheme that is schematically described as follows: An external input signal, applied to a small input subset of the neurons, spreads along the network. Due to a stochastic component in the dynamics of the neurons, the frequency of the spreading signal decreases as it propagates through the network. Depending on the input signal frequency, different neural assemblies will hence fire at their specific resonance frequency. We show analytically that the resulting frequency-spatial transformation is well-formed; an injective, fixed, mapping is obtained. Extensive numerical simulations demonstrate that a homogeneous, well-formed transformation may also be obtained in neural networks with cortical-like "Mexican-hat" connectivity. We hypothesize that a frequency-spatial transformation may serve as a basis for parsimonious cortical communication.

Cell Communication↗

PubMed2005

Exuberance in the development of cortical networks.

The cerebral cortex is the largest and most intricately connected part of the mammalian brain. Its size and complexity has increased during the course of evolution, allowing improvements in old functions and causing the emergence of new ones, such as language. This has expanded the behavioural and cognitive repertoire of different species and has determined their competitive success. To allow the relatively rapid emergence of large evolutionary changes in a structure of such importance and complexity, the mechanisms by which cortical circuitry develops must be flexible and yet robust against changes that could disrupt the normal functions of the networks.

Animals↗

PubMed2004

Detection of functional modules from protein interaction networks.

Complex cellular processes are modular and are accomplished by the concerted action of functional modules (Ravasz et al., Science 2002;297:1551-1555; Hartwell et al., Nature 1999;402:C47-52). These modules encompass groups of genes or proteins involved in common elementary biological functions. One important and largely unsolved goal of functional genomics is the identification of functional modules from genomewide information, such as transcription profiles or protein interactions. To cope with the ever-increasing volume and complexity of protein interaction data (Bader et al., Nucleic Acids Res 2001;29:242-245; Xenarios et al., Nucleic Acids Res 2002;30:303-305), new automated approaches for pattern discovery in these densely connected interaction networks are required (Ravasz et al., Science 2002;297:1551-1555; Bader and Hogue, Nat Biotechnol 2002;20:991-997; Snel et al., Proc Natl Acad Sci USA 2002;99:5890-5895). In this study, we successfully isolate 1046 functional modules from the known protein interaction network of Saccharomyces cerevisiae involving 8046 individual pair-wise interactions by using an entirely automated and unsupervised graph clustering algorithm. This systems biology approach is able to detect many well-known protein complexes or biological processes, without reference to any additional information. We use an extensive statistical validation procedure to establish the biological significance of the detected modules and explore this complex, hierarchical network of modular interactions from which pathways can be inferred.

Algorithms↗

PubMed2000

Synaptic connectivity in hippocampal neuronal networks cultured on micropatterned surfaces.

Embryonic rat hippocampal neurons were grown on patterned silane surface in order to organize synapse formations in a controlled manner. The surface patterns were composed of trimethoxysilylpropyl-diethylenetriamine (DETA) lines separated by tridecafluoro-1,1,2,2-tetrahydrooctyl-1-dimethylchlorosilane (13F) spaces. Pre- and post-synaptic specializations were identified by immunostaining for synapsin I and microtubule-associated protein-2 (MAP-2). Functional synaptic connections were examined by recording simultaneously from pairs of neurons using the whole-cell configuration of the patch-clamp technique. Spontaneous and evoked synaptic currents were recorded in neurons cultured for 2-14 days. The formation of functional connections was accompanied by the appearance of spontaneous synaptic currents (SSCs), which could be detected after approximately 3 days in culture in the absence of evoked synaptic currents (ESCs). ESCs were detected only after approximately 7 days in culture, mostly in the form of unidirectional synaptic connections. Other forms of synaptic connectivity, such as bidirectional and autaptic connections, were also identified. Both transient GABAergic and glutamatergic signals mediated the transmissions between communicating cells. These results demonstrate the combination of various types of synaptic connections forming simple and complex networks in neurons cultured on line (DETA)-space (13F) patterns. Finally, precisely synchronized SSCs were recorded in neuron pairs cultured on pattern indicating the existence of a fast-acting feedback mechanism mediated by pre-synaptic GABA(A) receptors.

Alkanes↗

PubMed2001

On the stability analysis of delayed neural networks systems.

In this paper, the problems of stability of delayed neural networks are investigated, including the stability of discrete and distributed delayed neural networks. Under the generalization of dropping the Lipschitzian hypotheses for output functions, some stability criteria are obtained by using the Liapunov functional method. We do not assume the symmetry of the connection matrix and we establish that the system admits a unique equilibrium point in which the output functions do not satisfy the Lipschitz conditions and do not require them to be differential or strictly monotonously increasing. These criteria can be used to analyze the dynamics of biological neural systems or to design globally stable artificial neural networks.

Action Potentials↗

PubMed2005

Knowledge-based classification of neuronal fibers in entire brain.

This work presents a framework driven by parcellation of brain gray matter in standard normalized space to classify the neuronal fibers obtained from diffusion tensor imaging (DTI) in entire human brain. Classification of fiber bundles into groups is an important step for the interpretation of DTI data in terms of functional correlates of white matter structures. Connections between anatomically delineated brain regions that are considered to form functional units, such as a short-term memory network, are identified by first clustering fibers based on their terminations in anatomically defined zones of gray matter according to Talairach Atlas, and then refining these groups based on geometric similarity criteria. Fiber groups identified this way can then be interpreted in terms of their functional properties using knowledge of functional neuroanatomy of individual brain regions specified in standard anatomical space, as provided by functional neuroimaging and brain lesion studies.

Algorithms↗

PubMed1992

Controlling domestic life and mental illness: spiritual and aftercare resources used by Dominican New Yorkers.

This research addresses the differential use of spiritual and mental health resources by 15 Dominican migrant women with major psychiatric disorders in Northern Manhattan. Methods included interviews and participant observation with patients, kin, and mental health staff. Structured instruments were used to examine patients' networks and functioning. Folk and popular healing traditions, adopted by some patients and kin through private observances or through a connection with a healer, yielded symbolic supports, companionship for patients, and ways of communicating and coping with distress. Episodes of health-seeking revealed multiple participants competing for control of the patients' lives and illness careers. Consultations with healers offered family members potential mastery over illness and domestic life, with no surrender of centrality, dignity or control in the quest for care.

Adult↗

PubMed1993

Rectospinal neurons: cell bodies, pathways, immunocytochemistry and ultrastructure.

A novel class of enteric neurons projecting directly from the rectal wall to the spinal cord, "rectospinal neurons", was investigated in rats by combined retrograde neuronal tracing, immunocytochemistry and electron microscopy. Rectospinal neurons were almost confined to myenteric ganglia of the distal rectum below the pelvic diaphragm and were labeled preferentially by injections into spinal cord segments L6/S1. Injections into more rostral spinal cord segments resulted in hardly any labeled enteric neurons. Dorsal and ventral rhizotomy experiments indicated an almost exclusive projection of rectospinal neurons through dorsal roots L6/S1 to the respective spinal cord segments. Among various peptides immunostained, vasoactive intestinal polypeptide and calcitonin gene-related peptide were selectively found in rectospinal neurons, which were also shown to contain calbindin, neurofilament protein- and peripherin-immunoreactivity. Vasoactive intestinal polypeptide- and calbindin-immunostaining were frequently co-localized in the same perikarya, while calcitonin gene-related peptide-immunoreactive rectospinal neurons probably represented a separate population. Neonatal capsaicin treatment did not significantly reduce the number of rectospinal neurons. Electron microscopy revealed synaptic contacts on the surface of rectospinal neurons. Taken together, these results establish rectospinal neurons as an anatomically and neurochemically distinct class of enteric neurons. Synaptic contacts on rectospinal neurons suggest that these neurons may function as a direct link from the enteric to the central nervous system, thus indicating that connections between these two networks are reciprocal.

Afferent Pathways↗

PubMed2005

Measuring pore connectivity by pulsed field gradient diffusion editing with hydrocarbon gases.

Measurements of time-dependent diffusion are performed on a rock sample saturated first with water, then methane and finally ethane. The gases were selected because their increased diffusivities and relaxation times allow probing greater length scales than water and because of their practical relevance. The nuclear magnetic resonance measurements employed pulse field gradient diffusion editing pulse sequences, allowing analysis of D(t) as a function of relaxation time. Very different D(t) behaviors are observed for different relaxation times, including indications of connected pore networks at moderate relaxation times.

Diffusion↗

PubMed2004

Measuring functional connectivity during distinct stages of a cognitive task.

The inherently multivariate nature of functional brain imaging data affords the unique opportunity to explore how anatomically disparate brain areas interact during cognitive tasks. We introduce a new method for characterizing inter-regional interactions using event-related functional magnetic resonance imaging (fMRI) data. This method's principle advantage over existing analytical techniques is its ability to model the functional connectivity between brain regions during distinct stages of a cognitive task. The method is implemented by using separate covariates to model the activity evoked during each stage of each individual trial in the context of the general linear model (GLM). The resulting parameter estimates (beta values) are sorted according to the stage from which they were derived to form a set of stage-specific beta series. Regions whose beta series are correlated during a given stage are inferred to be functionally interacting during that stage. To validate the assumption that correlated fluctuations in trial-to-trial beta values imply functional connectivity, we applied the method to an event-related fMRI data set in which subjects performed two sequence-tapping tasks. In concordance with previous electrophysiological and fMRI coherence studies, we found that the task requiring greater bimanual coordination induced stronger correlations between motor regions of the two hemispheres. The method was then applied to an event-related fMRI data set in which subjects performed a delayed recognition task. Distinct functional connectivity maps were generated during the component stages of this task, illustrating how important and novel observations of neural networks within the isolated stages of a cognitive task can be obtained.

Adult↗

PubMed2002

Equivariant nonstationary source separation.

Most of source separation methods focus on stationary sources, so higher-order statistics is necessary for successful separation, unless sources are temporally correlated. For nonstationary sources, however, it was shown [Neural Networks 8 (1995) 411] that source separation could be achieved by second-order decorrelation. In this paper, we consider the cost function proposed by Matsuoka et al. [Neural Networks 8 (1995) 411] and derive natural gradient learning algorithms for both fully connected recurrent network and feedforward network. Since our algorithms employ the natural gradient method, they possess the equivariant property and find a steepest descent direction unlike the algorithm [Neural Networks 8 (1995) 411]. We also show that our algorithms are always locally stable, regardless of probability distributions of nonstationary sources.

Algorithms↗

PubMed2004

Self-referential phase reset based on inferior olive oscillator dynamics.

The olivo-cerebellar network is a key neuronal circuit that provides high-level motor control in the vertebrate CNS. Functionally, its network dynamics is organized around the oscillatory membrane potential properties of inferior olive (IO) neurons and their electrotonic connectivity. Because IO action potentials are generated at the peaks of the quasisinusoidal membrane potential oscillations, their temporal firing properties are defined by the IO rhythmicity. Excitatory inputs to these neurons can produce oscillatory phase shifts without modifying the amplitude or frequency of the oscillations, allowing well defined time-shift modulation of action potential generation. Moreover, the resulting phase is defined only by the amplitude and duration of the reset stimulus and is independent of the original oscillatory phase when the stimulus was delivered. This reset property, henceforth referred to as selfreferential phase reset, results in the generation of organized clusters of electrically coupled cells that oscillate in phase and are controlled by inhibitory feedback loops through the cerebellar nuclei and the cerebellar cortex. These clusters provide a dynamical representation of arbitrary motor intention patterns that are further mapped to the motor execution system. Being supplied with sensory inputs, the olivo-cerebellar network is capable of rearranging the clusters during the process of movement execution. Accordingly, the phase of the IO oscillators can be rapidly reset to a desired phase independently of the history of phase evolution. The goal of this article is to show how this selfreferential phase reset may be implemented into a motor control system by using a biologically based mathematical model.

Action Potentials↗

PubMed1986

From basic network principles to neural architecture: emergence of orientation-selective cells.

This is the second paper in a series of three that explores the emergence of several prominent features of the functional architecture of visual cortex, in a "modular self-adaptive network" containing several layers of cells with parallel feedforward connections whose strengths develop according to a Hebb-type correlation-rewarding rule. In the present paper I show that orientation-selective cells, similar to the "simple" cortical cells of Hubel and Wiesel [Hubel, D. H. & Wiesel, T. N. (1962) J. Physiol. 160, 106-154], emerge in such a network. No orientation preference is specified to the system at any stage, the orientation-selective cell layer emerges even in the absence of environmental input to the system, and none of the basic developmental rules is specific to visual processing.

Adaptation, Physiological↗

PubMed2005

Catecholaminergic innervation of pyramidal neurons in the human temporal cortex.

In the human neocortex, catecholaminergic connections modulate the excitatory inputs of pyramidal neurons and are involved in higher cognitive functions. Catecholaminergic fibers form a dense network in which it is difficult to distinguish whether or not target specificity exists. In order to shed some light on this issue, we set out to quantify the catecholaminergic innervation of pyramidal cells in different layers of the human temporal cortex (II, IIIa, IIIb, V and VI). For this purpose, pyramidal cells were labeled in human cortical tissue by injecting them with Lucifer Yellow, and then performed immunocytochemistry for the rate limiting catecholamine synthesizing enzyme tyrosine hydroxylase (TH) to visualize catecholaminergic fibers in the same sections. Injected cells were reconstructed in three dimensions and appositions were quantified (n = 1503) in serial confocal microscopy images of each injected cell (n = 71). We found TH-immunoreactive appositions (TH-ir) in all the pyramidal cells analyzed, in both the apical and basal dendritic regions. In general, the density of TH-ir apposition was greater in layers II, V and VI than in layers IIIa and IIIb. Furthermore, TH-ir appositions showed a regular distribution in almost all dendritic compartments of the apical and basal dendritic arbors across all layers. Hence, it appears that all pyramidal neurons in the human neocortex receive catecholaminergic afferents in a rather regular pattern, independent of the layer in which they are located. Since pyramidal cells located in different layers are involved in different intrinsic and extrinsic circuits, these results suggest that catecholaminergic afferents may modify the function of a larger variety of circuits than previously thought. Thus, this aspect of human cortical organization is likely to have important implications in cortical function.

Adult↗