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Results for “functional network connectivity”

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At least 163 records · Page 9Linked to original sources

PubMed2003

Activity-dependent feedforward inhibition modulates synaptic transmission in a spinal locomotor network.

The analysis of synaptic properties in neural networks has focused on the properties of individual synapses. As a result, little is known of how neural assemblies arise from the connectivity and functional properties of different classes of network neurons. I examined synaptic properties in the lamprey locomotor network. Here I show that, in addition to their monosynaptic inputs to motor neurons, a proportion of the excitatory network interneurons (EINs) evoke an activity-dependent disynaptic feedforward inhibitory input. Connections from the excitatory interneurons to small ipsilateral inhibitory interneurons were found that could account for the feedforward inhibition. Both synapses in the disynaptic pathway exhibited activity-dependent facilitation during physiologically relevant spike trains, which could contribute to the delayed, activity-dependent development of the feedforward IPSP. Although it was not as common as the feedforward inhibition, the excitatory interneurons could also evoke feedforward excitatory inputs in motor neurons. EIN inputs to motor neurons usually depress during spike trains. In connections in which a delayed IPSP occurred, blocking the feedforward inhibition in motor neurons or preventing the activation of the disynaptic pathway abolished the depression of the direct EPSP during the spike train and could reveal an underlying facilitation. The feedforward inhibition thus heterosynaptically depressed the direct excitatory input to motor neurons. Activity-dependent heterosynaptic effects acting within network cellular assemblies can thus influence the integration of synaptic inputs in motor neurons. This could help to terminate ipsilateral motor neuron spiking during network activity.

Action Potentials↗

PubMed2006

A novel method for visualizing functional connectivity using principal component analysis.

Functional connectivity is a useful measure of voxel-wise functional magnetic resonance imaging signals that allows for the identification of functionally related brain areas and distributed networks. However, the high dimensionality of functional connectivity makes it difficult to visualize. In most studies, a small percentage of the total functional connectivity is visualized through diagrams that are constructed using individual seed voxels. In the present study describes a new method for visualizing most of the functional connectivity through a single diagram. This method does not rely on seed voxels, but rather employs a reduction of the high-dimensionality of the functional connectivity via a projection onto a three-dimensional color space using principal components analysis. With this new method, most of the information contained in a functional connectivity matrix can be represented through a single color-coded functional connectivity map, thereby facilitating a greater visual appreciation of functional connectivity.

Brain↗

PubMed1998

A model of cortical associative memory based on a horizontal network of connected columns.

An attractor network model of cortical associative memory functions has been constructed and simulated. By replacing the single cell as the functional unit by multiple cells in cortical columns connected by long-range fibers, the model is improved in terms of correspondence with cortical connectivity. The connectivity is improved, since the original dense and symmetric connectivity of a standard recurrent network becomes sparse and asymmetric at the cell-to-cell level. Our simulations show that this kind of network, with model neurons of the Hodgkin-Huxley type arranged in columns, can operate as an associative memory in much the same way as previous models having simpler connectivity. The network shows attractor-like behaviour and performs the standard assembly operations despite differences in the dynamics introduced by the more detailed cell model and network structure. Furthermore, the model has become sufficiently detailed to allow evaluation against electrophysiological and anatomical observations. For instance, cell activities comply with experimental findings and reaction times are within biological and psychological ranges. By introducing a scaling model we demonstrate that a network approaching experimentally reported neuron numbers and synaptic distributions also could work like the model studied here.

Action Potentials↗

PubMedDate not supplied

Cellular, synaptic and network effects of neuromodulation.

All network dynamics emerge from the complex interaction between the intrinsic membrane properties of network neurons and their synaptic connections. Nervous systems contain numerous amines and neuropeptides that function to both modulate the strength of synaptic connections and the intrinsic properties of network neurons. Consequently network dynamics can be tuned and configured in different ways, as a function of the actions of neuromodulators. General principles of the organization of modulatory systems in nervous systems include: (a) many neurons and networks are multiply modulated, (b) there is extensive convergence and divergence in modulator action, and (c) some modulators may be released extrinsically to the modulated circuit, while others may be released by some of the circuit neurons themselves, and act intrinsically. Some of the computational consequences of these features of modulator action are discussed.

Animals↗

PubMed1996

Visual potentiation of vestibular responses in lamprey reticulospinal neurons.

The lamprey normally swims with the dorsal side up. Illumination of one eye shifts the set-point of the vestibular roll control system, however, so that the animal swims with a roll tilt towards the source of light (the dorsal light response). A tilted orientation is often maintained for up to 1 min after the stimulation. In present study, the basis for this behaviour was investigated at the neuronal level. The middle rhombencephalic reticular nucleus (MRRN) is considered a main nucleus for the control of roll orientation in lampreys. Practically all MRRN neurons receive vestibular and visual input and project to the spinal cord. Earlier extracellular experiments had shown that optic nerve stimulation potentiates the response to vestibular stimulation in the ipsilateral MRRN. This most likely represents a neural correlate of the dorsal light response. Experiments were carried out in vitro on the isolated brainstem of the silver lamprey (Ichthyomyzon unicuspis). MRRN cells were recorded intracellularly, and the overall activity of descending systems was monitored with bilateral extracellular electrodes. The responses to 10 Hz optic nerve stimulation and 1 Hz vestibular nerve stimulation, and the influence of optic nerve stimulation on the vestibular responses, were investigated. In most preparations, optic nerve stimulation excited practically all ipsilateral MRRN cells. After stimulation, the cell was typically depolarized and showed an increased level of synaptic noise for up to 80 s. In contralateral MRRN neurons, optic nerve stimulation usually evoked hyperpolarization or no response. Vestibular nerve stimulation evoked compound excitatory postsynaptic potentials (EPSPs) or spikes in approximately 90% of the cells, both ipsilaterally and contralaterally. A smaller subpopulation of MRRN cells (approximately 10%) received vestibular inhibition. In 26 of 48 recorded MRRN cells, the response to vestibular stimulation was potentiated after ipsilateral optic nerve stimulation. The potentiation was seen in cells receiving either excitatory or inhibitory vestibular input as an increase in EPSP amplitude/spiking (85%) and a decrease in inhibitory postsynaptic potential amplitude (15%) respectively. In most cases the vestibular responses did not return to control levels during the testing period (10-30 min), and thus the visual stimulation most likely induced long-lasting changes in the functional connectivity of the role control network, in addition to the short-lasting afteractivity. In four of the 11 cells recorded contralateral to the stimulated optic nerve, a depression of the vestibular response could be seen. In potentiated cells, single vestibular pulses often evoked longer episodes of large synaptic noise and sometimes spiking. In the latter case, the action potentials appeared with highly variable latency after each stimulation pulse. This indicates that an important mechanism underlying the potentiation may be a long-lasting increase in excitability in a pool of unidentified interneurons located either upstream of the MRRN cells, relaying vestibular and visual inputs, or downstream, providing positive feedback.

Animals↗

PubMed1986

[Comparative neurobiology of the organization of gaze-stabilizing reflex systems in vertebrates].

During locomotion gaze is stabilized against passive head movements by compensatory eye movements. The efficacy and the neuronal organization of optokinetic and vestibular reflexes of different vertebrate species is compared. Besides many similarities between species a number of differences can be found as well. Increase in the efficacy of compensatory reflexes is not correlated with an increase in the efficacy of basic neuronal circuits but with the appearance of functionally new connections and of new network properties. This increasingly higher complexity allows to maintain gaze stability at increasingly higher speeds of locomotion or to suppress these reflexes during visual pursuit of a moving object.

Animals↗

PubMed1982

Electrolytic entorhinal lesions cause seizures.

The entorhinal cortex is a key site of interneuronal communication between a variety of cortical and subcortical areas and hippocampal formation. Lesioning the entorhinal cortex is commonly used in studies of the hippocampal formation, animal behavior and neuronal plasticity. We have found that electrolytic destruction of the entorhinal cortex consistently produces limbic seizure activity in rats. The propensity of lesions in this area for producing seizure activity may facilitate insights into the normal function of this network of neural connections. This unexpected phenomenon represents a potential confounding variable for all researchers using this method for making brain lesions.

Animals↗

PubMed2006

Genomic approach for the understanding of dynamic aspect of chromosome behavior.

Various functions are integrated into a single chromosome molecule. The genomic approach (ChIP-chip) we introduce here is a very powerful tool to study dynamic changes of the structure and function of the chromosome at the level of protein-DNA interaction as precisely as possible without prejudice or bias. This technology opens up the way to understand how local protein-protein or protein-DNA interactions lead to the dynamic changes of chromosome structure and how various chromosomal functions are connected to make a network for the faithful maintenance of the genome.

Base Sequence↗

PubMed2003

Neurons take shape.

To construct the intricate network of connections that supports the functions of an adult nervous system, neurons must form highly elaborate processes, extending in the appropriate direction across long distances to form synapses with their partners. As the nervous system takes shape, the process of neuronal morphogenesis is controlled by a broad repertoire of cellular signals. These extracellular cues and cellular interactions are translated by receptors at the cell surface into physical forces that control the dynamic architecture of the neuron as it explores the surrounding terrain. The interpretation of these cues involves a large set of intracellular proteins, whose functional logic we are just beginning to appreciate. We shall consider the basic mechanics of neuronal morphogenesis and some of the emerging pathways that seem to link the outer and inner worlds of the neuron.

Animals↗

PubMed1982

Dynamic analysis of a rhythmic neural circuit in the leech Hirudo medicinalis.

1. The results of perturbation experiments demonstrate the functional diversity of the interneurons (HN cells) that generate heartbeat in the medicinal leech. 2. HN cells were individually stimulated by single current pulses. The induced activity of HN cells in the first four ganglia (cell pairs HN(1)-HN(4)) reset the rhythm of the interneuron network; induced activity of those in the fifth through seventh ganglia (cell pairs HN(5)-HN(7)) did not. 3. Cells HN(1)-HN(4) can entrain every other interneuron of the network; cells HN(5)-HN(7) cannot. 4. Thus the HN interneuron network includes two distinct subsets: cells HN(1)-HN(4) form the network's timing oscillator; cells HN(5)-HN(7), driven by the timing oscillator, force one of the two coordination states on the heart motor neurons. 5. In general the dynamic behavior of the heart interneuron network was predictable given the web of identified synapses between HN cells. Nevertheless, the unexpected capacity of cells HN(3) and HN(4) to entrain the network shows that there are functional connections still to be found. Burst termination experiments suggest that cells HN(3) and HN(4) inhibit directly the more rostral HN cells. 6. The timing oscillation seems to arise from a balance between the endogenous polarization rhythms of interneurons HN(1)-HN(4) and selective reciprocal inhibition between these same cells.

Animals↗

PubMed2004

Melanin pigmentation in mammalian skin and its hormonal regulation.

Cutaneous melanin pigment plays a critical role in camouflage, mimicry, social communication, and protection against harmful effects of solar radiation. Melanogenesis is under complex regulatory control by multiple agents interacting via pathways activated by receptor-dependent and -independent mechanisms, in hormonal, auto-, para-, or intracrine fashion. Because of the multidirectional nature and heterogeneous character of the melanogenesis modifying agents, its controlling factors are not organized into simple linear sequences, but they interphase instead in a multidimensional network, with extensive functional overlapping with connections arranged both in series and in parallel. The most important positive regulator of melanogenesis is the MC1 receptor with its ligands melanocortins and ACTH, whereas among the negative regulators agouti protein stands out, determining intensity of melanogenesis and also the type of melanin synthesized. Within the context of the skin as a stress organ, melanogenic activity serves as a unique molecular sensor and transducer of noxious signals and as regulator of local homeostasis. In keeping with these multiple roles, melanogenesis is controlled by a highly structured system, active since early embryogenesis and capable of superselective functional regulation that may reach down to the cellular level represented by single melanocytes. Indeed, the significance of melanogenesis extends beyond the mere assignment of a color trait.

Animals↗

PubMed2004

[Neuroprotection in brain ischemia--doubts and hopes].

In ischaemic stroke the two major potential therapeutic strategies are aimed at either improving cerebral blood flow or directly interacting with the cytotoxic cascade--a large body of evidence gained from animal studies is in support of them. In clinical trials direct neuroprotection by blocking the neurotoxic cascade remained ineffective, although there are several clinical trials still in progress. We summarize the experimental data and present the results of clinical trials and also discuss why so many drugs, which were effective in animal studies, failed in human trials. It is emphasized, that 1. in most animal studies the reduction of infarct size, i.e. the amount of saved penumbral tissue, was the outcome measure, whereas neurological function remained unassessed; 2. the recovery of intellectual performance and higher cortical functions are of major importance in the future quality of life in stroke victims; however, it is impossible to examine these parameters appropriately in animal studies; 3. in many clinical trials the patient population was rather heterogenous and low in number, the study protocol was not optimal and the critical analysis of the subacute and chronic phase was lacking or insufficient. We present the major experimental stroke models, discuss their similarities, differences and limitations as compared to the human pathophysiological processes. The pitfalls of extrapolating data from animal studies to clinical practice are also summarized. The complex network of functional and morphological intercellular connections, the long timescale of neurotoxic and reparative events and the lessons learned from clinical trials suggest, that the use of drug combinations (therapeutic cocktails) targeting multiple steps of the neurotoxic cascade would hopefully result in more effective treatment of ischaemic stroke. Strategies to facilitate brain plasticity and regeneration is an additional promising tool to enhance recovery in brain ischaemia.

Animals↗

PubMed2003

Global protein function prediction from protein-protein interaction networks.

Determining protein function is one of the most challenging problems of the post-genomic era. The availability of entire genome sequences and of high-throughput capabilities to determine gene coexpression patterns has shifted the research focus from the study of single proteins or small complexes to that of the entire proteome. In this context, the search for reliable methods for assigning protein function is of primary importance. There are various approaches available for deducing the function of proteins of unknown function using information derived from sequence similarity or clustering patterns of co-regulated genes, phylogenetic profiles, protein-protein interactions (refs. 5-8 and Samanta, M.P. and Liang, S., unpublished data), and protein complexes. Here we propose the assignment of proteins to functional classes on the basis of their network of physical interactions as determined by minimizing the number of protein interactions among different functional categories. Function assignment is proteome-wide and is determined by the global connectivity pattern of the protein network. The approach results in multiple functional assignments, a consequence of the existence of multiple equivalent solutions. We apply the method to analyze the yeast Saccharomyces cerevisiae protein-protein interaction network. The robustness of the approach is tested in a system containing a high percentage of unclassified proteins and also in cases of deletion and insertion of specific protein interactions.

Algorithms↗

PubMed2000

Computational analysis of functional connectivity between areas of primate cerebral cortex.

Recent analyses of association fibre networks in the primate cerebral cortex have revealed a small number of densely intra-connected and hierarchically organized structural systems. Corresponding analyses of data on functional connectivity are required to establish the significance of these structural systems. We therefore built up a relational database by systematically collating published data on the spread of activity after strychnine-induced disinhibition in the macaque cerebral cortex in vivo. After mapping these data to two different parcellation schemes, we used three independent methods of analysis which demonstrate that the cortical network of functional interactions is not homogeneous, but shows a clear segregation into functional assemblies of mutually interacting areas. The assemblies suggest a principal division of the cortex into visual, somatomotor and orbito-temporo-insular systems, while motor and somatosensory areas are inseparably interrelated. These results are largely compatible with corresponding analyses of structural data of mammalian cerebral cortex, and deliver the first functional evidence for 'small-world' architecture of primate cerebral cortex.

Animals↗

PubMed2000

Generalized radial basis function networks for classification and novelty detection: self-organization of optimal Bayesian decision.

By adding reverse connections from the output layer to the central layer it is shown how a generalized radial basis functions (GRBF) network can self-organize to form a Bayesian classifier, which is also capable of novelty detection. For this purpose, three stochastic sequential learning rules are introduced from biological considerations which pertain to the centers, the shapes, and the widths of the receptive fields of the neurons and allow ajoint optimization of all network parameters. The rules are shown to generate maximum-likelihood estimates of the class-conditional probability density functions of labeled data in terms of multivariate normal mixtures. Upon combination with a hierarchy of deterministic annealing procedures, which implement a multiple-scale approach, the learning process can avoid the convergence problems hampering conventional expectation-maximization algorithms. Using an example from the field of speech recognition, the stages of the learning process and the capabilities of the self-organizing GRBF classifier are illustrated.

Artificial Intelligence↗

PubMed2001

Networks with trainable amplitude of activation functions.

Network training algorithms have heavily concentrated on the learning of connection weights. Little effort has been made to learn the amplitude of activation functions, which defines the range of values that the function can take. This paper introduces novel algorithms to learn the amplitudes of nonlinear activations in layered networks, without any assumption on their analytical form. Three instances of the algorithms are developed: (i) a common amplitude is shared among all nonlinear units; (ii) each layer has its own amplitude; and (iii) neuron-specific amplitudes are allowed. The algorithms can also be seen as a particular double-step gradient-descent procedure, as gradient-driven adaptive learning rate schemes, or as weight-grouping techniques that are consistent with known scaling laws for regularization with weight decay. As a side effect, a self-pruning mechanism of redundant neurons may emerge. Experimental results on function approximation, classification, and regression tasks, with synthetic and real-world data, validate the approach and show that the algorithms speed up convergence and modify the search path in the weight space, possibly reaching deeper minima that may also improve generalization.

Algorithms↗

PubMed1997

[High-field (3.OT) MR system: advantages in functional analysis].

In order to elucidate the precise mechanisms underlying higher brain function, investigations need to focus not only on functionality of neuronal networks but also the underlying connectivity. Newly developed magnetic resonance (MR) techniques offer revolutional, non-invasive tools for both functionality and connectivity analysis in humans, namely, BOLD (blood oxygen level dependent) functional magnetic resonance imaging (MRI) and three dimensional anisotropy contrast (3DAC) magnetic resonance axonograpy (MRX). The former technique makes use of changes in regional deoxyhemoglobin concentration associated with brain function, while the latter utilizes directional information of apparent diffusivity observed in axonal fibers. In these critically important but highly demanding imaging techniques, high-field (> or = 3.OT) MR systems possess significant advantages over conventional systems.

Axons↗

PubMed2005

Investigating the neural basis for functional and effective connectivity. Application to fMRI.

Viewing cognitive functions as mediated by networks has begun to play a central role in interpreting neuroscientific data, and studies evaluating interregional functional and effective connectivity have become staples of the neuroimaging literature. The neurobiological substrates of functional and effective connectivity are, however, uncertain. We have constructed neurobiologically realistic models for visual and auditory object processing with multiple interconnected brain regions that perform delayed match-to-sample (DMS) tasks. We used these models to investigate how neurobiological parameters affect the interregional functional connectivity between functional magnetic resonance imaging (fMRI) time-series. Variability is included in the models as subject-to-subject differences in the strengths of anatomical connections, scan-to-scan changes in the level of attention, and trial-to-trial interactions with non-specific neurons processing noise stimuli. We find that time-series correlations between integrated synaptic activities between the anterior temporal and the prefrontal cortex were larger during the DMS task than during a control task. These results were less clear when the integrated synaptic activity was haemodynamically convolved to generate simulated fMRI activity. As the strength of the model anatomical connectivity between temporal and frontal cortex was weakened, so too was the strength of the corresponding functional connectivity. These results provide a partial validation for using fMRI functional connectivity to assess brain interregional relations.

Auditory Perception↗