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Results for “functional network connectivity”

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PubMed2005

Frequency specific changes in regional cerebral blood flow and motor system connectivity following rTMS to the primary motor cortex.

Repetitive transcranial magnetic stimulation (rTMS) to the human primary motor cortex (M1) causes bidirectional changes in corticospinal excitability depending on the stimulation frequency used. We used functional brain imaging to compare the effects of 5 Hz and 1 Hz-rTMS on local and inter-regional connectivity within the motor system. Regional cerebral blood flow (rCBF) was measured as a marker of synaptic activity at rest and during freely selected finger movements. We hypothesized that increased cortical excitability induced by 5 Hz-rTMS over M1 has an opposite effect on the synaptic activity and the connectivity of the motor network from the decreased cortical excitability induced by 1 Hz-rTMS. rTMS at both frequencies induced similar changes in rCBF at the site of stimulation and within areas of the motor network engaged by the task. The two frequencies showed different effects on movement-related coupling between motor areas. Connectivity analyses also indicated a differential effect of 5 and 1 Hz-rTMS on motor network connectivity, suggesting a role for an inferomedial portion of left M1 and left dorsal premotor cortex in maintaining performance. These results suggest that rapid reorganization of the motor system occurs to maintain task performance during periods of altered cortical excitability. This reorganization differs according to the modulation of excitability which is a function of rTMS frequency. This study extends the work of Lee et al. (Lee, L., Siebner, H.R., Rowe, J.B., Rizzo, V. Rothwell, J.C. Frackowiak, R.S. Friston, K.J., 2003. Acute remapping within the motor system induced by low-frequency repetitive transcranial magnetic stimulation. J. Neurosci. 23, 5308-5318.) by providing evidence that the pattern of acute reorganization in the motor network following rTMS depends on the direction of conditioning.

Adult↗

PubMed1979

Central inhibition of an identified mechanosensory interneuron in the crayfish.

Inhibitory input from crayfish mechanoreceptors is mediated polysynaptically to sensory interneurons. An identifiable sensory interneuron, the caudal photoreceptor (CPR), has been used as a model system to characterize inhibitory intermediate cells. A survey of the abdominal connectives, by antidromic stimulation, has identified eleven inhibitory cells, some of which also function as ascending sensory interneurons. These results indicate that lateral interactions within networks of mechanosensory interneurons form an integral part of the information processing mechanisms.

Animals↗

PubMed1986

The relationship between signal response selectivity and the functional structure of complex retinal neural networks.

In this paper we simulate the simultaneous responses of 45 neurones within a hypothetical retina to a variety of spatio-temporal signals. Our results demonstrate how specific convergent and divergent excitatory and inhibitory connections are sufficient to determine signal response selectivity of specific ganglion cells and so delimit the known types of center-surround receptive fields.

Animals↗

PubMed1984

A hierarchical neural network model for associative memory.

A hierarchical neural network model with feedback interconnections, which has the function of associative memory and the ability to recognize patterns, is proposed. The model consists of a hierarchical multi-layered network to which efferent connections are added, so as to make positive feedback loops in pairs with afferent connections. The cell-layer at the initial stage of the network is the input layer which receives the stimulus input and at the same time works as an output layer for associative recall. The deepest layer is the output layer for pattern-recognition. Pattern-recognition is performed hierarchically by integrating information by converging afferent paths in the network. For the purpose of associative recall, the integrated information is again distributed to lower-order cells by diverging efferent paths. These two operations progress simultaneously in the network. If a fragment of a training pattern is presented to the network which has completed its self-organization, the entire pattern will gradually be recalled in the initial layer. If a stimulus consisting of a number of training patterns superposed is presented, one pattern gradually becomes predominant in the recalled output after competition between the patterns, and the others disappear. At about the same time when the recalled pattern reaches a steady state in the initial layer, in the deepest layer of the network, a response is elicited from the cell corresponding to the category of the finally-recalled pattern. Once a steady state has been reached, the response of the network is automatically extinguished by inhibitory signals from a steadiness-detecting cell.(ABSTRACT TRUNCATED AT 250 WORDS)

Association Learning↗

PubMed1993

Network analysis of functional auditory pathways mapped with fluorodeoxyglucose: associative effects of a tone conditioned as a Pavlovian excitor or inhibitor.

The purpose of this study was to examine how opposite learned associative properties of the same auditory stimulus are represented by the pattern of network interactions between auditory system structures. [14C(U)]2-fluoro-2-deoxyglucose (FDG) autoradiography was used to compare mean auditory system activity and interregional correlations resulting from the presentation of a tone trained as either a Pavlovian conditioned excitor or inhibitor. Rats were trained with reinforced trials of the conditioned excitor (A+) intermixed with non-reinforced trials of a tone-light compound (AX-). For the Conditioned Excitor group, the tone was the excitor (A+), while for the Conditioned Inhibitor group the tone was the inhibitor (X-). After conditioning, both groups were injected with FDG and presented with the same tone. Structural equation models, constructed from the anatomical connections between auditory regions and their interregional correlations in FDG uptake, were used to calculate path coefficients representing the network interactions. The opposite associative significance of the tone was reflected as functional changes in the interactions between parallel auditory pathways. Direct covariance effects through lemniscal pathways from the ventral cochlear nucleus were similar in absolute magnitude but differed in sign between the Excitor and Inhibitor network models. Extra-auditory influences on the dorsal cochlear nucleus were greater for the tone-inhibitor, reflecting possible interactions of this nucleus with extra-auditory regions. The different associative effects of the tone suggest that central auditory pathways can code not only the physical qualities, but also the associative significance of auditory stimuli. These findings demonstrate that neural network interactions differentiate the associative effects of tones in the brain. It is proposed that associative learning is a distributed property of neural networks and that such a property can be understood by considering the interactions between component parts of the network.

Acoustic Stimulation↗

PubMed2004

Functional connectivity of the prefrontal cortex and the amygdala in posttraumatic stress disorder.

BACKGROUND: Persistent, intrusive re-experiencing in posttraumatic stress disorder (PTSD) is commonly construed as a failure of cingulate inhibition (i.e., extinction) over a hyperresponsive amygdala, based primarily on animal research of fear conditioning and the finding of cingulate hypoperfusion in PTSD. METHODS: We examined functional connectivity in patients with PTSD and healthy trauma survivors during repeated symptom provocation using H(2)O(15) positron emission tomography. RESULTS: Memory retrieval networks (right prefrontal cortex, hippocampus, and visual cortex) were common to both groups. Networks supporting autonomic and emotional control and preparatory motor action (amygdala, anterior cingulate, subcallosal gyrus, and premotor cortex) differed between the two groups and became progressively disparate with successive presentations of the traumatic script. Patterns of effective connectivity demonstrated the predominance of direct influences of the amygdala on visual cortex, subcallosal gyrus, and anterior cingulate in PTSD but not in control subjects. There was little evidence for failure of inhibition of cingulate or subcallosal cortex over the amygdala. CONCLUSIONS: These patterns might represent excessive influences of the amygdala over regions involved in autonomic, and higher-order visual memory processing in PTSD. The present data suggest that inferences of direct correspondence between animal studies and pathophysiology of PTSD should be made with caution.

Adult↗

PubMed2026

Spiramycin fermentation residue-derived biochar regulates soil nutrient cycling, microbial communities, and antibiotic resistance gene dynamics.

Spiramycin fermentation residues (SFR) are hazardous wastes enriched with residual antibiotics, yet they can serve as potential feedstocks for resource recovery after appropriate treatment. In this study, SFR-derived biochar (SFR-BC) was produced by pyrolysis and applied to agricultural soil to evaluate its effects on soil properties, microbial communities, potential pathogenic bacteria, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs). A 60-day soil incubation experiment was conducted with one control and three SFR-BC application rates of 0.5%, 1.0%, and 2.0%. SFR-BC improved soil physicochemical properties, nutrient status, enzyme activities, and microbial alpha diversity. Metagenomic analysis showed that SFR-BC altered the abundance of functional genes associated with carbon and nitrogen cycling, indicating shifts in microbial functional potential. SFR-BC also changed bacterial co-occurrence patterns, with the high-dose treatment showing a more complex and highly connected network structure during incubation. In addition, high-dose SFR-BC reduced several potential pathogenic bacteria, including major plant pathogenic taxa. SFR-BC decreased soil ARG abundance by 9.38%-33.67% and MGE abundance by 6.49%-27.89% relative to the control, showing a dose-dependent reduction in antibiotic resistance-related genetic elements. Network and PLS-PM analyses further indicated that ARG variation was statistically associated with soil physicochemical properties, microbial diversity, potential bacterial hosts, and MGEs. Overall, these results suggest that SFR-BC can improve short-term soil nutrient status and reduce ARGs, MGEs, and several potential pathogenic taxa under controlled incubation conditions, providing useful evidence for the potential valorization of antibiotic fermentation residues through pyrolysis.

Charcoal↗

PubMed2003

Learning and inference in the brain.

This article is about how the brain data mines its sensory inputs. There are several architectural principles of functional brain anatomy that have emerged from careful anatomic and physiologic studies over the past century. These principles are considered in the light of representational learning to see if they could have been predicted a priori on the basis of purely theoretical considerations. We first review the organisation of hierarchical sensory cortices, paying special attention to the distinction between forward and backward connections. We then review various approaches to representational learning as special cases of generative models, starting with supervised learning and ending with learning based upon empirical Bayes. The latter predicts many features, such as a hierarchical cortical system, prevalent top-down backward influences and functional asymmetries between forward and backward connections that are seen in the real brain. The key points made in article are: (i). hierarchical generative models enable the learning of empirical priors and eschew prior assumptions about the causes of sensory input that are inherent in non-hierarchical models. These assumptions are necessary for learning schemes based on information theory and efficient or sparse coding, but are not necessary in a hierarchical context. Critically, the anatomical infrastructure that may implement generative models in the brain is hierarchical. Furthermore, learning based on empirical Bayes can proceed in a biologically plausible way. (ii). The second point is that backward connections are essential if the processes generating inputs cannot be inverted, or the inversion cannot be parameterised. Because these processes involve many-to-one mappings, are non-linear and dynamic in nature, they are generally non-invertible. This enforces an explicit parameterisation of generative models (i.e. backward connections) to afford recognition and suggests that forward architectures, on their own, are not sufficient for perception. (iii). Finally, non-linearities in generative models, mediated by backward connections, require these connections to be modulatory, so that representations in higher cortical levels can interact to predict responses in lower levels. This is important in relation to functional asymmetries in forward and backward connections that have been demonstrated empirically.

Bayes Theorem↗

PubMed2006

Measurements and models of cerebral function in the severely injured brain.

We review the emerging applications of functional and structural neuroimaging techniques for the assessment of patients with disorders of consciousness. Measurements of brain function from patients in the vegetative state (VS) and minimally conscious state (MCS) are compared, and a conceptual organization is developed that suggests models of brain mechanisms associated with different functional levels of recovery. We emphasize developing strategies to place complex brain injuries on a more equal footing using global and regional quantification of resting or activated brain activity using functional imaging techniques alongside more detailed structural assessments of neuronal integrity and axonal connectivity now available. Preliminary studies from several investigative groups suggest that some MCS patients may harbor a functional reserve in the form of recruitable cerebral networks. These findings support developing systematic characterizations of the severely injured brain and suggest that some patients may benefit from improved diagnostic assessments.

Brain Injuries↗

PubMed2004

Ising model in scale-free networks: a Monte Carlo simulation.

The Ising model in uncorrelated scale-free networks has been studied by means of Monte Carlo simulations. These networks are characterized by a degree (or connectivity) distribution P (k) approximately k(-gamma). The ferromagnetic-paramagnetic transition temperature has been studied as a function of the parameter gamma. For gamma>3 our results agree with earlier analytical calculations, which found a phase transition at a temperature T(c) (gamma) in the thermodynamic limit. For gamma< or =3, a ferromagnetic-paramagnetic crossover occurs at a size-dependent temperature T(co), and the system is in the ordered ferromagnetic state at any temperature for a system size N--> infinity. For gamma=3 and large enough N, the crossover temperature is found to be T(co) approximately A ln N, with a prefactor A proportional to the mean degree. For 2 N(z), with an exponent z that decreases as gamma increases. This exponent is found to be lower than predicted by earlier calculations.

Journal Article↗

PubMed2006

Iterated maps for annealed Boolean networks.

Boolean networks are used to study the large-scale properties of nonlinear systems and are mainly applied to model genetic regulatory networks. A statistical method called the annealed approximation is commonly used to examine the dynamical properties of randomly generated Boolean networks that are created with selected statistical features. However, in the literature there are several variations of the annealed approximation. These approximations cannot be interchangeably used in all cases due to different background assumptions. In this paper, we present the so-called four-state model, derive the different approximations from this model, and make the differences and connections between these approximations explicit. As an application of the presented results, we study the properties of the Boolean networks that are constructed with random functions, canalizing functions, and regulatory functions found in the biological literature.

Journal Article↗

PubMed2005

Organization and metabolism of plastids and mitochondria in arbuscular mycorrhizal roots of Medicago truncatula.

Colonization of root cortical cells by arbuscular mycorrhizal fungi leads to marked cytological changes of plastids and mitochondria. Plastids in particular are forming tubular extensions partially connecting individual organelles in a network-like way. These cytological changes correspond to an increased need for plastid and mitochondrial products during establishment and functioning of the symbiosis. The analysis of metabolite and transcript levels in mycorrhizal and nonmycorrhizal roots from Medicago truncatula revealed concomitant changes regarding a number of metabolic pathways. Our results indicate the activation of the mitochondrial tricarboxylic acid cycle and of plastid biosynthetic pathways producing fatty acids, amino acids, and apocarotenoids. These observations provide a general overview of structural and metabolic changes of plastids and mitochondria during colonization of root cortical cells by arbuscular mycorrhizal fungi.

Amino Acids↗

PubMed2004

A feedback model of visual attention.

Feedback connections are a prominent feature of cortical anatomy and are likely to have a significant functional role in neural information processing. We present a neural network model of cortical feedback that successfully simulates neurophysiological data associated with attention. In this domain, our model can be considered a more detailed, and biologically plausible, implementation of the biased competition model of attention. However, our model is more general as it can also explain a variety of other top-down processes in vision, such as figure/ground segmentation and contextual cueing. This model thus suggests that a common mechanism, involving cortical feedback pathways, is responsible for a range of phenomena and provides a unified account of currently disparate areas of research.

Algorithms↗

PubMed2005

A new approach to spatial covariance modeling of functional brain imaging data: ordinal trend analysis.

In neuroimaging studies of human cognitive abilities, brain activation patterns that include regions that are strongly interactive in response to experimental task demands are of particular interest. Among the existing network analyses, partial least squares (PLS; McIntosh, 1999; McIntosh, Bookstein, Haxby, & Grady, 1996) has been highly successful, particularly in identifying group differences in regional functional connectivity, including differences as diverse as those associated with states of awareness and normal aging. However, we address the need for a within-group model that identifies patterns of regional functional connectivity that exhibit sustained activity across graduated changes in task parameters. For example, predictions of sustained connectivity are commonplace in studies of cognition that involve a series of tasks over which task difficulty increases (Baddeley, 2003). We designed ordinal trend analysis (OrT) to identify activation patterns that increase monotonically in their expression as the experimental task parameter increases, while the correlative relationships between brain regions remain constant. Of specific interest are patterns that express positive ordinal trends on a subject-by-subject basis. A unique feature of OrT is that it recovers information about functional connectivity based solely on experimental design variables. In particular, there is no requirement by OrT to provide either a quantitative model of the uncertain relationship between functional brain circuitry and subject variables (e.g., task performance and IQ) or partial information about the regions that are functionally connected. In this letter, we provide a step-by-step recipe of the computations performed in the new OrT analysis, including a description of the inferential statistical methods applied. Second, we describe applications of OrT to an event-related fMRI study of verbal working memory and H(2)15O-PET study of visuo-motor learning. In sum, OrT has potential applications to not only studies of young adults and their cognitive abilities, but also studies of normal aging and neurological and psychiatric disease.

Adult↗

PubMed2006

Remodeling of synaptic structure in sensory cortical areas in vivo.

Although plastic changes are known to occur in developing and adult cortex, it remains unclear whether these changes require remodeling of cortical circuitry whereby synapses are formed and eliminated or whether they rely on changes in the strength of existing synapses. To determine the structural stability of dendritic spines and axon terminals in vivo, we chose two approaches. First, we performed time-lapse two-photon imaging of dendritic spine motility of layer 5 pyramidal neurons in juvenile [postnatal day 28 (P28)] mice in visual, auditory, and somatosensory cortices. We found that there were differences in basal rates of dendritic spine motility of the same neuron type in different cortices, with visual cortex exhibiting the least structural dynamics. Rewiring visual input into the auditory cortex at birth, however, failed to alter dendritic spine motility, suggesting that structural plasticity rates might be intrinsic to the cortical region. Second, we investigated the persistence of both the presynaptic (axon terminals) and postsynaptic (dendritic spine) structures in young adult mice (P40-P61), using chronic in vivo two-photon imaging in different sensory areas. Both terminals and spines were relatively stable, with >80% persisting over a 3 week period in all sensory regions. Axon terminals were more stable than dendritic spines. These data suggest that changes in network function during adult learning and memory might occur through changes in the strength and efficacy of existing synapses as well as some remodeling of connectivity through the loss and gain of synapses.

Animals↗

PubMed1996

Immunohistochemical studies on protein gene product 9.5, serotonin and neuropeptides in vallate taste buds and related nerves of the guinea pig.

The occurrence, distribution and innervation of guinea pig vallate papillae were investigated by means of indirect immunofluorescence and immunoperoxidase methods using antibodies against: a neuron-specific protein, protein gene product 9.5 (PGP 9.5); various neuropeptides including calcitonin gene-related peptide (CGRP), substance P (SP), vasoactive intestinal polypeptide (VIP) and galanin; a monoamine, serotonin (5-hydroxytryptamine; 5HT). Numerous PGP 9.5-immunoreactive nerve fibers were found to form plexuses in the lingual epithelium both intragemmally and extragemmally and to comprise dense bundles in the lamina propria just beneath the epithelium. Moderate numbers of PGP 9.5-immunoreactive cells were observed in the taste buds. These cells, typically spindle in shape, extended through the entire thickness of the taste bud. CGRP-immunoreactive nerve fibers were numerous in the subgemmal connective tissue and entered the epithelium to form intragemmal and extragemmal networks. A dense subgemmal SP-immunoreactive network in the vallate papilla can be linked to the presence of taste buds, even though SP-immunoreactive nerve fibers rarely occurred intragemmally. No taste cells immunoreactive for CGRP and for SP were observed. Immunoreactivity for VIP or galanin was not detected in nerve fibers and taste cells. In contrast, some taste cells and a few, fine networks of nerve fibers in the connective tissue were immunoreactive for 5HT; none of the intraepithelial fibers were 5HT-immunoreactive. We suggest that: 1) functionally, 5HT-containing cells and the CGRP-containing nerve fibers may be primarily involved in the neural transmission or its modulation of the taste sensation; and 2) VIP and galanin can be excluded from that group of substances which plays important roles in taste sensation.

Animals↗

PubMed2001

Growth-stimulating pathways in lung cancer: implications for targets of therapy.

Growth-stimulating pathways activated independently of their normal tissue environment are critical to the carcinogenesis and progression of lung cancer. These pathways are comprised of extracellular growth factors; their specific receptors on the cellular membrane; signal transduction cascades in the cytosol; and target molecules, including cytoskeletal proteins, metabolic regulators, and transcription factors in the nucleus. Growth factors can be divided into two groups based on their receptors: G-protein-coupled receptors and receptor tyrosine kinases. Growth factors induce clonal expansion of lung cancer cells by autocrine and/or paracrine mechanisms. Signal transduction cascades form an extremely large and complicated network with cross-talk connections. Ras, phosphatidylinositol-3-OH kinase, and phospholipase C are three key regulators involved in the network. Recent progress in our understanding of the oncoproteins functioning in the pathways has led to the development of novel therapeutic agents. Some of the most exciting results have been obtained with inhibitors of receptor tyrosine kinases. Phase I studies of epidermal growth factor-receptor inhibitors demonstrate objective responses without severe toxicity as single agents in patients with non-small-cell lung cancer refractory to conventional chemotherapy. This new strategy might lead to breakthroughs in the treatment of lung cancer with distant metastases not curable by conventional chemotherapy alone.

Journal Article↗

PubMedDate not supplied

[Changes in synaptic potentials and axonal delays as factors causing epileptic instability of neuronal networks].

Synaptic weights, axonal delays and excitability thresholds are three basic parameters influencing the function of neuronal network as a dynamic system. Changes of the general level of the signal flow, without changes in relation between excitatory and inhibitory connections can cause pathologic oscillations in the network. The conductivity in neuronal nets depends on electrochemical processes and may be influenced by the pH-status, ion concentrations, among other parameters. Also different pathological processes can change it. Even slight changes of axonal delays, as shown above, can cause in certain situations unstable, epileptic oscillations of the net.

Action Potentials↗