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Results for “functional network connectivity”

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At least 793 records · Page 44Linked to original sources

PubMed1996

High-frequency oscillations in the output networks of the hippocampal-entorhinal axis of the freely behaving rat.

Population bursts of the CA3 network, which occur during eating, drinking, awake immobility, and slow-wave sleep, produce a large field excitatory postsynaptic potential throughout stratum radiatum of the CA1 field (sharp wave). The CA3 burst sets into motion a short-lived, dynamic interaction between CA1 pyramidal cells and interneurons, the product of which is a 200 Hz oscillatory field potential (ripple) and phase-related discharge of the CA1 network. Although many CA1 pyramidal neurons discharge during the time (50-100 msec) of each sharp wave, each wave of a ripple (approximately 5 msec) reflects the synchronization of more discrete subsets of CA1 neurons. When we used multi-site recordings in freely behaving rats, we observed ripples throughout the longitudinal extent (approximately 4-5 mm) of the dorsal CA1 region that were coherent for multiple cycles of each ripple. High-frequency ripples were also observed throughout the hippocampal-entorhinal output pathway that were concurrent but less coherent on a cycle-by-cycle basis. Single and multiunit neuronal activity was phase-related to local ripples throughout the hippocampal-entorhinal output pathway. Entorhinal ripples occurred 5-30 msec after the CA1 ripples and were related to the occurrence of an entorhinal sharp wave. Thus, during each hippocampal sharp wave, there is powerful synchronization among the neuronal networks that connect the hippocampus to the neocortex. We suggest that this population interaction (1) biologically constrains theoretical models of hippocampal function and dysfunction and (2) has the capacity to support an "off-line" memory consolidation process.

Animals↗

PubMed2004

Simulated apoptosis/neurogenesis regulates learning and memory capabilities of adaptive neural networks.

Characterization of neuronal death and neurogenesis in the adult brain of birds, humans, and other mammals raises the possibility that neuronal turnover represents a special form of neuroplasticity associated with stress responses, cognition, and the pathophysiology and treatment of psychiatric disorders. Multilayer neural network models capable of learning alphabetic character representations via incremental synaptic connection strength changes were used to assess additional learning and memory effects incurred by simulation of coordinated apoptotic and neurogenic events in the middle layer. Using a consistent incremental learning capability across all neurons and experimental conditions, increasing the number of middle layer neurons undergoing turnover increased network learning capacity for new information, and increased forgetting of old information. Simulations also showed that specific patterns of neural turnover based on individual neuronal connection characteristics, or the temporal-spatial pattern of neurons chosen for turnover during new learning impacts new learning performance. These simulations predict that apoptotic and neurogenic events could act together to produce specific learning and memory effects beyond those provided by ongoing mechanisms of connection plasticity in neuronal populations. Regulation of rates as well as patterns of neuronal turnover may serve an important function in tuning the informatic properties of plastic networks according to novel informational demands. Analogous regulation in the hippocampus may provide for adaptive cognitive and emotional responses to novel and stressful contexts, or operate suboptimally as a basis for psychiatric disorders. The implications of these elementary simulations for future biological and neural modeling research on apoptosis and neurogenesis are discussed.

Animals↗

PubMed2006

Parenting stress of mothers and fathers of young children with cognitive delays in Vietnam.

BACKGROUND: This research examined the effects of child and family variables on stress experienced by mothers and fathers of young children with cognitive delays in Vietnam. METHODS: The mothers (n = 106) and fathers (n = 93) whose children (age range = 3-6 years) were identified as having cognitive delays participated in the interview survey. The survey consisted of a set of the standardized questionnaires that were translated into Vietnamese and assessed for the content validity in the Vietnamese context. RESULTS: Mothers experienced more stress than fathers. Path analyses were conducted for mothers and fathers separately. Mothers with female children, those with children of lower intellectual functioning, and those whose husbands had health conditions experienced more stress than the other mothers. Fathers with lower economic status and a smaller social support network were more stressed than the other fathers. Both mothers and fathers were more stressed when they experienced stronger stigma, although the effects were not significant when other variables were considered together in path analyses. CONCLUSIONS: The findings revealed traditional gender roles. Mothers were more affected by the child's characteristics and the spouse's functioning; they anticipated future problems related to the child's functioning more than fathers did. Fathers were more affected by concerns about the family's connection to the wider world such as economic issues and the social support network. Longitudinal studies of how social support and stigma affect families would be valuable.

Child↗

PubMed1997

Interneuronal cortical connections and intertrial responses in appetitive instrumental learning.

The organization of interneuronal cortical connections in intertrial periods was studied in 4 cats trained to perform the delayed appetitive instrumental response to a visual conditioned stimulus (CS). Crosscorrelationl analysis revealed changes in intra- and intercortical neuronal networks of the visual and motor cortical projection areas. Depending on the form of behavior in the intertrial period, i.e., the presence or absence of the acquired instrumental response, the functional connections of either informational (time delays of less than 30 ms) or motivational (time delays in the range of 60-100 ms) character dominated between the neurons of the motor and visual cortical areas.

Animals↗

PubMed2006

Principles of microRNA regulation of a human cellular signaling network.

MicroRNAs (miRNAs) are endogenous approximately 22-nucleotide RNAs, which suppress gene expression by selectively binding to the 3'-noncoding region of specific messenger RNAs through base-pairing. Given the diversity and abundance of miRNA targets, miRNAs appear to functionally interact with various components of many cellular networks. By analyzing the interactions between miRNAs and a human cellular signaling network, we found that miRNAs predominantly target positive regulatory motifs, highly connected scaffolds and most downstream network components such as signaling transcription factors, but less frequently target negative regulatory motifs, common components of basic cellular machines and most upstream network components such as ligands. In addition, when an adaptor has potential to recruit more downstream components, these components are more frequently targeted by miRNAs. This work uncovers the principles of miRNA regulation of signal transduction networks and implies a potential function of miRNAs for facilitating robust transitions of cellular response to extracellular signals and maintaining cellular homeostasis.

Computational Biology↗

PubMed2003

A persistent cellular change in a single modulatory neuron contributes to associative long-term memory.

Most neuronal models of learning assume that changes in synaptic strength are the main mechanism underlying long-term memory (LTM) formation. However, we show here that a persistent depolarization of membrane potential, a type of cellular change that increases neuronal responsiveness, contributes significantly to a long-lasting associative memory trace. The use of a model invertebrate network with identified neurons and known synaptic connectivity had the advantage that the contribution of this cellular change to memory could be evaluated in a neuron with a known function in the learning circuit. Specifically, we used the well-understood motor circuit underlying molluscan feeding and showed that a key modulatory neuron involved in the initiation of feeding ingestive movements underwent a long-term depolarization following behavioral associative conditioning. This depolarization led to an enhanced single cell and network responsiveness to a previously neutral tactile conditioned stimulus, and the persistence of both matched the time course of behavioral associative memory. The change in the membrane potential of a key modulatory neuron is both sufficient and necessary to initiate a conditioned response in a reduced preparation and underscores its importance for associative LTM.

Animals↗

PubMed2001

[Cellular and molecular mechanisms of memory].

There has been nearly a century of interest in the idea that information is encoded in the brain as specific spatio-temporal patterns of activity in distributed networks and stored as changes in the efficacy of synaptic connections on neurons that are activated during learning. The discovery and detailed report of the phenomenon generally known as long-term potentiation opened a new chapter in the study of synaptic plasticity in the vertebrate brain, and this form of synaptic plasticity has now become the dominant model in the search for the cellular bases of learning and memory. To date, the key events in the cellular and molecular mechanisms underlying synaptic plasticity are starting to be identified. They require the activation of specific receptors and of several molecular cascades to convert extracellular signals into persistent functional changes in neuronal connectivity. Accumulating evidence suggests that the rapid activation of the genetic machinery is a key mechanism underlying the enduring modification of neural networks required for the laying down of memory. The recent developments in the search for the cellular and molecular mechanisms of memory storage are reviewed.

Gene Expression Regulation↗

PubMed1995

Differentiation between nodules and end-on vessels using a convolution neural network architecture.

In recent years, many computer-aided diagnosis schemes have been proposed to assist radiologists in detecting lung nodules. The research efforts have been aimed at increasing the sensitivity while decreasing the false-positive detections on digital chest radiographs. Among the problems of reducing the number of false positives, the differentiation between nodules and end-on vessels is one of the most challenging tasks performed by computer. Most investigators have used a conventional two-stage pattern recognition approach, ie, feature extraction followed by feature classification. The performance of this approach depends totally on good feature definition in the feature extraction stage. Unfortunately, suitable feature definition and corresponding extraction implementation algorithms proved to be very difficult to define and specify. A convolution neural network (CNN) architecture, trained by direct connection to the raw image is proposed to tackle the problem. The CNN, which uses locally responsive activation function, is directly and locally connected to the raw image. The performance of the CNN is evaluated in comparison to an expert radiologist. We used the receiver operating characteristics (ROC) method with area under the curve (Az) as the performance index to evaluate all the simulation results. The CNN showed superior performance (Az = 0.99) to the radiologist's (Az = 0.83). The CNN approach can potentially be applied to other applications, such as the differentiation of film defects and microcalcifications in mammography, in which the image features are difficult to define or not known a priori.

Algorithms↗

PubMed2005

High-betweenness proteins in the yeast protein interaction network.

Structural features found in biomolecular networks that are absent in random networks produced by simple algorithms can provide insight into the function and evolution of cell regulatory networks. Here we analyze "betweenness" of network nodes, a graph theoretical centrality measure, in the yeast protein interaction network. Proteins that have high betweenness, but low connectivity (degree), were found to be abundant in the yeast proteome. This finding is not explained by algorithms proposed to explain the scale-free property of protein interaction networks, where low-connectivity proteins also have low betweenness. These data suggest the existence of some modular organization of the network, and that the high-betweenness, low-connectivity proteins may act as important links between these modules. We found that proteins with high betweenness are more likely to be essential and that evolutionary age of proteins is positively correlated with betweenness. By comparing different models of genome evolution that generate scale-free networks, we show that rewiring of interactions via mutation is an important factor in the production of such proteins. The evolutionary and functional significance of these observations are discussed.

Journal Article↗

PubMed2000

Optimal design of connectivity in neural network training.

Many authors consider neural network (NN) supervised training as an optimization process during which the weights are iteratively adjusted in order to minimise an error (cost) function, which represents the difference between the obtained and the aimed output. The error function surface is usually nonconvex, can be highly convoluted, with many plateaux and long narrow troughs, and can encounter many saddle and local minima (LM) points. Because backpropagation (BP), which is widely used method for supervised learning, uses local methods for optimization, it can get stuck in LM. This can make learning very difficult and sometimes its convergence to optimal solution--not possible. In this paper we propose a stochastic method for global optimization (GO), which make use of a uniformly distributed LP tau sequence of points. The developed technique is tested with common benchmark problems and used for neural network supervised learning. The conducted tests show that the proposed method can be successfully used for an optimal supervised training of small size NN.

Neural Networks, Computer↗

PubMed2005

Competition and adaptation in an Internet evolution model.

We model the evolution of the Internet at the autonomous system level as a process of competition for users and adaptation of bandwidth capability. From a weighted network formalism, where both nodes and links are weighted, we find the exponent of the degree distribution as a simple function of the growth rates of the number of autonomous systems and connections in the Internet, both empirically measurable quantities. Our approach also accounts for a high level of clustering as well as degree-degree correlations, both with the same hierarchical structure present in the real Internet. Further, it also highlights the interplay between bandwidth, connectivity, and traffic of the network.

Competitive Behavior↗

PubMed1999

A neural network model of lateralization during letter identification.

The causes of cerebral lateralization of cognitive and other functions are currently not well understood. To investigate one aspect of function lateralization, a bihemispheric neural network model for a simple visual identification task was developed that has two parallel interacting paths of information processing. The model is based on commonly accepted concepts concerning neural connectivity, activity dynamics, and synaptic plasticity. A combination of both unsupervised (Hebbian) and supervised (Widrow-Hoff) learning rules is used to train the model to identify a small set of letters presented as input stimuli in the left visual hemifield, in the central position, and in the right visual hemifield. Each visual hemifield projects onto the contralateral hemisphere, and the two hemispheres interact via a simulated corpus callosum. The contribution of each individual hemisphere to the process of input stimuli identification was studied for a variety of underlying asymmetries. The results indicate that multiple asymmetries may cause lateralization. Lateralization occurred toward the side having larger size, higher excitability, or higher learning rate parameters. It appeared more intensively with strong inhibitory callosal connections, supporting the hypothesis that the corpus callosum plays a functionally inhibitory role. The model demonstrates clearly the dependence of lateralization on different hemisphere parameters and suggests that computational models can be useful in better understanding the mechanisms underlying emergence of lateralization.

Adult↗

PubMed1994

The perivascular connective matrix.

The functional properties of the perivascular matrix facilitate the movement, protection and the nutrition of the blood vessels. At the same time the matrix deliniates the vessels to the organs. Different vascular diseases of the vascular system implicate the perivascular matrix consisting of a network of structural and cellular connective tissue components. Impairment of its structural integrity predominantly occurs either from primary or secondary affections. Monospecific antibodies directed against different structural proteins enable detailed histomorphological examinations of the inflammatory tissue reaction in the perivascular space. Since myofibroblasts, fibrocytes, endothelial cells, and macrophages participate in tissue repair mechanisms, in vitro studies on the collagen synthesis may contribute to the understanding of the perivascular tissue reaction according to injury. The present report summarizes perivascular diseases and the in vitro synthesis of procollagen, collagen, and fibronectin of endothelial cells, fibroblasts, smooth muscle cells, and macrophages.

Animals↗

PubMed2004

Changes in functional connectivity of human MT/V5 with visual motion input.

The neural basis of human mental function is characterized by interactions between brain regions. Temporal correlations in MR signals between areas may provide one method for investigating these interactions. This approach was used to examine functional connectivity in the motion processing system of the human brain. Correlations between MT/V5 and other brain regions were examined in a resting state (without visual stimulation) and in an active state produced by viewing moving concentric circles. A network of regions consistent with the known functional anatomy of visual processing was correlated with MT/V5 during rest. When subjects were viewing motion, a more limited network was correlated with MT/V5, suggesting MT/V5 was acting in concert with a smaller network specific to the task.

Brain Mapping↗

PubMed2006

Functional connectivity in human cortical motor system: a cortico-cortical evoked potential study.

In order to understand the complex functional organization of the motor system, it is essential to know the anatomical and functional connectivity among individual motor areas. Clinically, knowledge of these cortico-cortical connections is important to understand the rapid spread of epileptic discharges through the network underlying ictal motor manifestation. In humans, however, knowledge of neuronal in vivo connectivity has been limited. We recently reported a new method, 'cortico-cortical evoked potential (CCEP)', to electrically track the cortico-cortical connections by stimulating a part of the brain through subdural electrodes and recording the cortical evoked potentials that emanate from a distant region of the cortex via neuronal projections. We applied the CCEP methodology to investigate in vivo cortico-cortical connections between the lateral motor cortex [LMCx; sensorimotor (SM) and lateral premotor areas] and the medial motor cortex [MMCx; supplementary motor area proper (SMA), pre-SMA and foot SM]. Seven patients with intractable partial epilepsy were studied. These patients had chronic implantation of subdural electrodes covering part of the lateral and medial frontal areas. As a part of the routine pre-surgical evaluation, comprehensive cortical mapping was performed by electrical stimulation of the subdural electrodes, and the precise localization of the subdural electrodes was defined by MRI co-registration. Single-pulse electrical stimuli were delivered to MMCx (7 patients) and LMCx (4), and CCEPs time-locked to the stimuli were recorded by averaging electrocorticograms from LMCx and MMCx, respectively. Short-latency CCEPs were observed when stimulating MMCx and recording from LMCx (mean latency: 21.6 ms, range: 9-47 ms) and vice versa when stimulating LMCx and recording from MMCx (mean latency: 29.4 ms, range: 11-57 ms). In terms of the location of these stimulus sites and CCEP responses along the rostrocaudal axis, regression analysis revealed a consistent correlation between the sites of stimulation and maximum CCEP for stimulation of both MMCx and LMCx. Functionally, stimulation of the positive motor areas in MMCx elicited CCEPs at the somatotopically homologous regions in LMCx (71%). The same findings were observed in MMCx (82%) upon stimulation of LMCx. In four subjects in whom bi-directional connectivity was investigated by stimulating both MMCx and LMCx, reciprocality was observed in the majority of connections (78-94%). In conclusion, the present study demonstrated a human motor cortico-cortical network connecting (i) anatomically homologous areas of LMCx and MMCx along the rostrocaudal cognitive-motor gradient; and (ii) somatotopically homologous regions in LMCx and MMCx in a reciprocal manner.

Adolescent↗

PubMed2004

Recruitment of periventricular parietal regions in processing cluttered point-light biological motion.

Recent findings point to the existence of a cortical-subcortical parietal network that drives attention-related integration of features and elements. Here we ask whether the functioning of this network might be modulated by early periventricular lesions. To this end, a cohort of adolescents who were born premature with different severity of bilateral periventricular leukomalacia (PVL) and two groups of matched peers (term-born adolescents and former preterms with normal MRI scan) were shown a set of impoverished point-light stimuli. Observers had to detect a point-light walker embedded in an array of distracters mimicking the motion of the target's dots. Patients exhibited higher susceptibility to distortions caused by distracters. In patients only, sensitivity to the point-light figure highly correlates not just with performance on additionally administered feature integration tasks but also on visual attention-demanding IQ tasks. Moreover, the sensitivity index, as well as the values of both IQ factors, decreases with an increase in the volumetric PVL extent in the parieto-occipital region. No relationship was found between these variables and the lesion extent in the frontal or temporal periventricular regions. The data suggest that visual integration and attention in processing cluttered point-light displays are intimately connected. Most importantly, periventricular parieto-occipital regions might be part of a distributed network recruited in deployment of the posterior attentional system. The functioning of this system seems to be vulnerable to bilateral periventricular damage even if it occurs very early in brain development.

Adolescent↗

PubMed1992

[The extracellular matrix and its regulation].

The dermis is a differentiated connective tissue whose mechanical properties originate in a network of polymeric macromolecules associated to a variety of glycoproteins and proteoglycans. Each macromolecule contains specific recognition domains allowing their self-association and binding to other macromolecules and to the cell membrane receptors, through. Cell function is regulated by the transfer of information resulting from contact with the polymeric network, as well as by cytokines and growth factors. The structure of the genes encoding the different macromolecules and their regulation sequences are largely known. Various connective tissue disorders are due to alterations of these genes.

Collagen↗

PubMed2003

Altered effective connectivity in drug free schizophrenic patients.

The present fMRI study aimed to investigate effective connectivity within a cortical-subcortical-cerebellar information processing network in drug free schizophrenic patients while performing a 2-back working memory task. The finding of enhanced thalamo-cortical and cortico-cortical intrahemispheric connectivity could be interpreted as a compensatory increase of neuronal connection strength consistent with a model of cortical inefficiency in schizophrenic patients. Additionally, the result could be integrated into a model of deficient thalamo-cortical filter functions. Conversely, lower interhemispheric connectivity of the frontal and parietal association cortex appears to be the functional correlate of reduced cognitive performance in schizophrenic patients. The study demonstrated the feasibility to model information processing within cognitive networks and provided additional evidence for the concept of cognitive dysmetria in schizophrenia.

Adult↗