182 research outputs found

    Aortic dissection associated with cogans's syndrome: deleterious loss of vascular structural integrity is associated with GM-CSF overstimulation in macrophages and smooth muscle cells

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    <p>Abstract</p> <p>Background</p> <p>Cogan's syndrome is a rare disorder of unknown origin characterized by inflammatory ocular disease and vestibuloauditory symptoms. Systemic vasculitis is found in about 10% of cases.</p> <p>Case presentation</p> <p>A 46-year-old female with Cogans's syndrome and a history of arterial hypertension presented with severe chest pain caused by an aneurysm of the ascending aorta with a dissection membrane located a few centimeters distal from the aortic root. After surgery, histopathological analysis revealed that vascular matrix integrity and expression of the major matrix molecules was characterized by elastolysis and collagenolysis and thus a dramatic loss of structural integrity. Remarkably, exceeding matrix deterioration was associated with massively increased levels of granulocyte macrophage colony stimulating factor (GM-CSF).</p> <p>Conclusion</p> <p>Our data suggest that the persistently increased secretion of the inflammatory mediator GM-CSF by resident inflammatory cells but also by SMC may be the trigger of aortic wall structural deterioration.</p

    Statistical Analyses Support Power Law Distributions Found in Neuronal Avalanches

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    The size distribution of neuronal avalanches in cortical networks has been reported to follow a power law distribution with exponent close to −1.5, which is a reflection of long-range spatial correlations in spontaneous neuronal activity. However, identifying power law scaling in empirical data can be difficult and sometimes controversial. In the present study, we tested the power law hypothesis for neuronal avalanches by using more stringent statistical analyses. In particular, we performed the following steps: (i) analysis of finite-size scaling to identify scale-free dynamics in neuronal avalanches, (ii) model parameter estimation to determine the specific exponent of the power law, and (iii) comparison of the power law to alternative model distributions. Consistent with critical state dynamics, avalanche size distributions exhibited robust scaling behavior in which the maximum avalanche size was limited only by the spatial extent of sampling (“finite size” effect). This scale-free dynamics suggests the power law as a model for the distribution of avalanche sizes. Using both the Kolmogorov-Smirnov statistic and a maximum likelihood approach, we found the slope to be close to −1.5, which is in line with previous reports. Finally, the power law model for neuronal avalanches was compared to the exponential and to various heavy-tail distributions based on the Kolmogorov-Smirnov distance and by using a log-likelihood ratio test. Both the power law distribution without and with exponential cut-off provided significantly better fits to the cluster size distributions in neuronal avalanches than the exponential, the lognormal and the gamma distribution. In summary, our findings strongly support the power law scaling in neuronal avalanches, providing further evidence for critical state dynamics in superficial layers of cortex

    Angiogenic Factors Stimulate Growth of Adult Neural Stem Cells

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    The ability to grow a uniform cell type from the adult central nervous system (CNS) is valuable for developing cell therapies and new strategies for drug discovery. The adult mammalian brain is a source of neural stem cells (NSC) found in both neurogenic and non-neurogenic zones but difficulties in culturing these hinders their use as research tools.Here we show that NSCs can be efficiently grown in adherent cell cultures when angiogenic signals are included in the medium. These signals include both anti-angiogenic factors (the soluble form of the Notch receptor ligand, Dll4) and pro-angiogenic factors (the Tie-2 receptor ligand, Angiopoietin 2). These treatments support the self renewal state of cultured NSCs and expression of the transcription factor Hes3, which also identifies the cancer stem cell population in human tumors. In an organotypic slice model, angiogenic factors maintain vascular structure and increase the density of dopamine neuron processes.We demonstrate new properties of adult NSCs and a method to generate efficient adult NSC cultures from various central nervous system areas. These findings will help establish cellular models relevant to cancer and regeneration

    Dragon-kings: mechanisms, statistical methods and empirical evidence

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    This introductory article presents the special Discussion and Debate volume "From black swans to dragon-kings, is there life beyond power laws?" published in Eur. Phys. J. Special Topics in May 2012. We summarize and put in perspective the contributions into three main themes: (i) mechanisms for dragon-kings, (ii) detection of dragon-kings and statistical tests and (iii) empirical evidence in a large variety of natural and social systems. Overall, we are pleased to witness significant advances both in the introduction and clarification of underlying mechanisms and in the development of novel efficient tests that demonstrate clear evidence for the presence of dragon-kings in many systems. However, this positive view should be balanced by the fact that this remains a very delicate and difficult field, if only due to the scarcity of data as well as the extraordinary important implications with respect to hazard assessment, risk control and predictability.Comment: 20 page

    Emergent complex neural dynamics

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    A large repertoire of spatiotemporal activity patterns in the brain is the basis for adaptive behaviour. Understanding the mechanism by which the brain's hundred billion neurons and hundred trillion synapses manage to produce such a range of cortical configurations in a flexible manner remains a fundamental problem in neuroscience. One plausible solution is the involvement of universal mechanisms of emergent complex phenomena evident in dynamical systems poised near a critical point of a second-order phase transition. We review recent theoretical and empirical results supporting the notion that the brain is naturally poised near criticality, as well as its implications for better understanding of the brain

    Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

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    Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded as separate file

    Coherence Potentials Encode Simple Human Sensorimotor Behavior

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    Recent work has shown that large amplitude negative periods in the local field potential (nLFPs) are able to spread in saltatory manner across large distances in the cortex without distortion in their temporal structure forming ‘coherence potentials’. Here we analysed subdural electrocorticographic (ECoG) signals recorded at 59 sites in the sensorimotor cortex in the left hemisphere of a human subject performing a simple visuomotor task (fist clenching and foot dorsiflexion) to understand how coherence potentials arising in the recordings relate to sensorimotor behavior. In all behaviors we found a particular coherence potential (i.e. a cascade of a particular nLFP wave pattern) arose consistently across all trials with temporal specificity. During contrateral fist clenching, but not the foot dorsiflexion or ipsilateral fist clenching, the coherence potential most frequently originated in the hand representation area in the somatosensory cortex during the anticipation and planning periods of the trial, moving to other regions during the actual motor behavior. While these ‘expert’ sites participated more consistently, other sites participated only a small fraction of the time. Furthermore, the timing of the coherence potential at the hand representation area after onset of the cue predicted the timing of motor behavior. We present the hypothesis that coherence potentials encode information relevant for behavior and are generated by the ‘expert’ sites that subsequently broadcast to other sites as a means of ‘sharing knowledge’

    A Model of Ischemia-Induced Neuroblast Activation in the Adult Subventricular Zone

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    We have developed a rat brain organotypic culture model, in which tissue slices contain cortex-subventricular zone-striatum regions, to model neuroblast activity in response to in vitro ischemia. Neuroblast activation has been described in terms of two main parameters, proliferation and migration from the subventricular zone into the injured cortex. We observed distinct phases of neuroblast activation as is known to occur after in vivo ischemia. Thus, immediately after oxygen/glucose deprivation (6–24 hours), neuroblasts reduce their proliferative and migratory activity, whereas, at longer time points after the insult (2 to 5 days), they start to proliferate and migrate into the damaged cortex. Antagonism of ionotropic receptors for extracellular ATP during and after the insult unmasks an early activation of neuroblasts in the subventricular zone, which responded with a rapid and intense migration of neuroblasts into the damaged cortex (within 24 hours). The process is further enhanced by elevating the production of the chemoattractant SDf-1α and may also be boosted by blocking the activation of microglia. This organotypic model which we have developed is an excellent in vitro system to study neurogenesis after ischemia and other neurodegenerative diseases. Its application has revealed a SOS response to oxygen/glucose deprivation, which is inhibited by unfavorable conditions due to the ischemic environment. Finally, experimental quantifications have allowed us to elaborate a mathematical model to describe neuroblast activation and to develop a computer simulation which should have promising applications for the screening of drug candidates for novel therapies of ischemia-related pathologies

    Zwanzig-Mori projection operators and EEG dynamics: deriving a simple equation of motion

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    We present a macroscopic theory of electroencephalogram (EEG) dynamics based on the laws of motion that govern atomic and molecular motion. The theory is an application of Zwanzig-Mori projection operators. The result is a simple equation of motion that has the form of a generalized Langevin equation (GLE), which requires knowledge only of macroscopic properties. The macroscopic properties can be extracted from experimental data by one of two possible variational principles. These variational principles are our principal contribution to the formalism. Potential applications are discussed, including applications to the theory of critical phenomena in the brain, Granger causality and Kalman filters

    The Virtual Teacher (VT) Paradigm: Learning New Patterns of Interpersonal Coordination Using the Human Dynamic Clamp

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    The Virtual Teacher paradigm, a version of the Human Dynamic Clamp (HDC), is introduced into studies of learning patterns of inter-personal coordination. Combining mathematical modeling and experimentation, we investigate how the HDC may be used as a Virtual Teacher (VT) to help humans co-produce and internalize new inter-personal coordination pattern(s). Human learners produced rhythmic finger movements whilst observing a computer-driven avatar, animated by dynamic equations stemming from the well-established Haken-Kelso-Bunz (1985) and Schöner-Kelso (1988) models of coordination. We demonstrate that the VT is successful in shifting the pattern co-produced by the VT-human system toward any value (Experiment 1) and that the VT can help humans learn unstable relative phasing patterns (Experiment 2). Using transfer entropy, we find that information flow from one partner to the other increases when VT-human coordination loses stability. This suggests that variable joint performance may actually facilitate interaction, and in the long run learning. VT appears to be a promising tool for exploring basic learning processes involved in social interaction, unraveling the dynamics of information flow between interacting partners, and providing possible rehabilitation opportunities
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