Learning flexible sensori-motor mappings in a complex network

Given the complex structure of the brain, how can synaptic plasticity explain the learning and forgetting of associations when these are continuously changing? We address this question by studying different reinforcement learning rules in a multilayer network in order to reproduce monkey behavior in a visuomotor association task. Our model can only reproduce the learning performance of the monkey if the synaptic modifications depend on the pre- and postsynaptic activity, and if the intrinsic level of stochasticity is low. This favored learning rule is based on reward modulated Hebbian synaptic plasticity and shows the interesting feature that the learning performance does not substantially degrade when adding layers to the network, even for a complex problem.

Quantitative analysis of the native presynaptic cytomatrix by cryoelectron tomography

The presynaptic terminal contains a complex network of filaments whose precise organization and functions are not yet understood. The cryoelectron tomography experiments reported in this study indicate that these structures play a prominent role in synaptic vesicle release. Docked synaptic vesicles did not make membrane to membrane contact with the active zone but were instead linked to it by tethers of different length. Our observations are consistent with an exocytosis model in which vesicles are first anchored by long (>5 nm) tethers that give way to multiple short tethers once vesicles enter the readily releasable pool. The formation of short tethers was inhibited by tetanus toxin, indicating that it depends on soluble N-ethyl-maleimide sensitive fusion protein attachment protein receptor complex assembly. Vesicles were extensively interlinked via a set of connectors that underwent profound rearrangements upon synaptic stimulation and okadaic acid treatment, suggesting a role of these connectors in synaptic vesicle mobilization and neurotransmitter release.

Reticulate eruptions. Part 1: Vascular networks and physiology

Reticulate pattern is one of the most important dermatological signs of a pathological process involving the superficial vascular networks. Vascular malformations, such as cutis marmorata congenita telangiectasia and benign forms of livedo reticularis, and sinister conditions, such as meningococcal meningitis or Sneddon's syndrome, can all present with a reticulate pattern. The clinical presentation and morphology is determined by the nature and extent of the underlying pathology and the involvement of a particular vascular network. This review has been divided into four instalments. In the present paper, we discuss the anatomy and physiology of the complex network of vascular structures that support the function of the skin and subcutis.

Tight junctions in brain barriers during central nervous system inflammation

Homeostasis within the central nervous system (CNS) is a prerequisite to elicit proper neuronal function. The CNS is tightly sealed from the changeable milieu of the blood stream by the blood-brain barrier (BBB) and the blood-cerebrospinal fluid (CSF) barrier (BCSFB). Whereas the BBB is established by specialized endothelial cells of CNS microvessels, the BCSFB is formed by the epithelial cells of the choroid plexus. Both constitute physical barriers by a complex network of tight junctions (TJs) between adjacent cells. During many CNS inflammatory disorders, such as multiple sclerosis, human immunodeficiency virus infection, or Alzheimer's disease, production of pro-inflammatory cytokines, matrix metalloproteases, and reactive oxygen species are responsible for alterations of CNS barriers. Barrier dysfunction can contribute to neurological disorders in a passive way by vascular leakage of blood-borne molecules into the CNS and in an active way by guiding the migration of inflammatory cells into the CNS. Both ways may directly be linked to alterations in molecular composition, function, and dynamics of the TJ proteins. This review summarizes current knowledge on the cellular and molecular aspects of the functional and dysfunctional TJ complexes at the BBB and the BCSFB, with a particular emphasis on CNS inflammation and the role of reactive oxygen species.

Muster, Entwicklungstypen und Persönlichkeit

Studien zu Sozialisationswirkungen sportlicher Aktivitäten auf Facetten der Persönlichkeit (z. B. Selbstkonzept) haben sich bislang in der Regel auf die Analyse isolierter Effekte des Sports konzentriert, ohne weitere Entwicklungskontexte (wie z. B. die Familie) angemessen zu berücksichtigen. Da hierin eine wesentliche Ursache für die unbefriedigende Befundlage gesehen wird, bemüht sich der Beitrag darum, die Rolle des Sports für das Selbstkonzept im komplexen Wirkungsgeflecht verschiedener Entwicklungskontexte herauszuarbeiten. 121 Heranwachsende wurden in einer personorientierten Längsschnittsstudie untersucht und die Daten mit der LICUR-Methode (z. B. Bergman, Magnusson & El-Khouri, 2003) ausgewertet. Die dabei identifizierten Subgruppen unterscheiden sich in allen untersuchten Facetten des Selbstkonzepts bedeutsam, zeigen sowohl zeitstabile als auch dynamische Werteprofile ihrer Entwicklungsfaktoren und folgen überzufällig häufig einzelnen Entwicklungswegen. Aus diesen Befunden werden Konsequenzen für eine ganzheitliche und funktionale Selbstkonzeptförderung durch Sport abgeleitet.

Regulation of androgen biosynthesis - A short review and preliminary results from the hyperandrogenic starvation NCI-H295R cell model

Regulation of androgen production is poorly understood. Adrenarche is the physiologic event in mid-childhood when the adrenal zona reticularis starts to produce androgens through specific expression of genes for enzymes and cofactors necessary for androgen synthesis. Similarly, expression and activities of same genes and products are deregulated in hyperandrogenic disorders such as the polycystic ovary syndrome (PCOS). Numerous studies revealed involvement of several signaling pathways stimulated through G-protein coupled receptors or growth factors transmitting their effects through cAMP- or non-cAMP-dependent signaling. Overall a complex network regulates androgen synthesis targeting involved genes and proteins at the transcriptional and post-translational levels. Newest players in the field are the DENND1A gene identified in PCOS patients and the MAPK14 which is the kinase phosphorylating CYP17 for enhanced lyase activity. Next generation sequencing studies of PCOS patients and transcriptome analysis of androgen producing tissues or cell models provide newer tools to identify modulators of androgen synthesis.

Using the contribution matrix to evaluate complex study limitations in a network meta-analysis: a case study of bipolar maintenance pharmacotherapy review.

BACKGROUND Limitations in the primary studies constitute one important factor to be considered in the grading of recommendations assessment, development, and evaluation (GRADE) system of rating quality of evidence. However, in the network meta-analysis (NMA), such evaluation poses a special challenge because each network estimate receives different amounts of contributions from various studies via direct as well as indirect routes and because some biases have directions whose repercussion in the network can be complicated. FINDINGS In this report we use the NMA of maintenance pharmacotherapy of bipolar disorder (17 interventions, 33 studies) and demonstrate how to quantitatively evaluate the impact of study limitations using netweight, a STATA command for NMA. For each network estimate, the percentage of contributions from direct comparisons at high, moderate or low risk of bias were quantified, respectively. This method has proven flexible enough to accommodate complex biases with direction, such as the one due to the enrichment design seen in some trials of bipolar maintenance pharmacotherapy. CONCLUSIONS Using netweight, therefore, we can evaluate in a transparent and quantitative manner how study limitations of individual studies in the NMA impact on the quality of evidence of each network estimate, even when such limitations have clear directions.

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.

Recurrent antitopographic inhibition mediates competitive stimulus selection in an attention network

Topographically organized neurons represent multiple stimuli within complex visual scenes and compete for subsequent processing in higher visual centers. The underlying neural mechanisms of this process have long been elusive. We investigate an experimentally constrained model of a midbrain structure: the optic tectum and the reciprocally connected nucleus isthmi. We show that a recurrent antitopographic inhibition mediates the competitive stimulus selection between distant sensory inputs in this visual pathway. This recurrent antitopographic inhibition is fundamentally different from surround inhibition in that it projects on all locations of its input layer, except to the locus from which it receives input. At a larger scale, the model shows how a focal top-down input from a forebrain region, the arcopallial gaze field, biases the competitive stimulus selection via the combined activation of a local excitation and the recurrent antitopographic inhibition. Our findings reveal circuit mechanisms of competitive stimulus selection and should motivate a search for anatomical implementations of these mechanisms in a range of vertebrate attentional systems.

Predicting asthma control and exacerbations: chronic asthma as a complex dynamic model

PURPOSE OF REVIEW: Predicting asthma episodes is notoriously difficult but has potentially significant consequences for the individual, as well as for healthcare services. The purpose of this review is to describe recent insights into the prediction of acute asthma episodes in relation to classical clinical, functional or inflammatory variables, as well as present a new concept for evaluating asthma as a dynamically regulated homeokinetic system. RECENT FINDINGS: Risk prediction for asthma episodes or relapse has been attempted using clinical scoring systems, considerations of environmental factors and lung function, as well as inflammatory and immunological markers in induced sputum or exhaled air, and these are summarized here. We have recently proposed that newer mathematical methods derived from statistical physics may be used to understand the complexity of asthma as a homeokinetic, dynamic system consisting of a network comprising multiple components, and also to assess the risk for future asthma episodes based on fluctuation analysis of long time series of lung function. SUMMARY: Apart from the classical analysis of risk factor and functional parameters, this new approach may be used to assess asthma control and treatment effects in the individual as well as in future research trials.

Learning real-world stimuli in a neural network with spike-driven synaptic dynamics

We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).

Analysis of postprandial lipemia as a Cardiovascular Disease risk factor using genetic and clinical information: an Artificial Neural Network perspective

Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.

Unprecedented Trapping of Difluorooctamolybdate Anions within an α-Polonium Type Coordination Network

New fluorinated hybrid solids [Mo2F2O5(tr2pr)] (1), [Co3(tr2pr)2(MoO4)2F2]·7H2O (2), and [Co3(H2O)2(tr2pr)3(Mo8O26F2)]·3H2O (3) (tr2pr = 1,3-bis(1,2,4-triazol-4-yl)propane) were prepared from the reaction systems consisting of Co(OAc)2/CoF2 and MoO3/(NH4)6Mo7O24, as CoII and MoVI sources, in water (2) or in aqueous HF (1, 3) employing mild hydrothermal conditions. The tr2pr ligand serves as a conformationally flexible tetradentate donor. In complex 1, the octahedrally coordinated Mo atoms are linked in the discrete corner-sharing {Mo2(μ2-O)F2O4N4} unit in which a pair of tr-heterocycles (tr = 1,2,4-triazole) is arranged in cis-positions opposite to “molybdenyl” oxygen atoms. The anti−anti conformation type of tr2pr facilitates the tight zigzag chain packing motif. The crystal structure of the mixed-anion complex salt 2 consists of trinuclear [Co3(μ3-MoO4)2(μ2-F)2] units self-assembling in CoII-undulating chains (Co···Co 3.0709(15) and 3.3596(7) Å), which are cross-linked by tr2pr in layers. In 3, containing condensed oxyfluoromolybdate species, linear centrosymmetric [Co3(μ2-tr)6]6+ SBUs are organized at distances of 10.72−12.45 Å in an α-Po-like network using bitopic tr-linkers. The octahedral {N6} and {N3O3} environments of the central and peripheral cobalt atoms, respectively, are filled by triazole N atoms, water molecules, and coordinating [Mo8O26F2]6− anions. Acting as a tetradentate O-donor, each difluorooctamolybdate anion anchors four [Co3(μ2-tr)6]6+ units through their peripheral Co-sites, which consequently leads to a novel type of a two-nodal 4,10-c net with the Schläfli symbol {32.43.5}{34.420.516.65}. The 2D and 3D coordination networks of 2 and 3, respectively, are characterized by significant overall antiferromagnetic exchange interactions (J/k) between the CoII spin centers on the order of −8 and −4 K. The [Mo8O26F2]6− anion is investigated in detail by quantum chemical calculations.

Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes

Environmental policy and decision-making are characterized by complex interactions between different actors and sectors. As a rule, a stakeholder analysis is performed to understand those involved, but it has been criticized for lacking quality and consistency. This lack is remedied here by a formal social network analysis that investigates collaborative and multi-level governance settings in a rigorous way. We examine the added value of combining both elements. Our case study examines infrastructure planning in the Swiss water sector. Water supply and wastewater infrastructures are planned far into the future, usually on the basis of projections of past boundary conditions. They affect many actors, including the population, and are expensive. In view of increasing future dynamics and climate change, a more participatory and long-term planning approach is required. Our specific aims are to investigate fragmentation in water infrastructure planning, to understand how actors from different decision levels and sectors are represented, and which interests they follow. We conducted 27 semi-structured interviews with local stakeholders, but also cantonal and national actors. The network analysis confirmed our hypothesis of strong fragmentation: we found little collaboration between the water supply and wastewater sector (confirming horizontal fragmentation), and few ties between local, cantonal, and national actors (confirming vertical fragmentation). Infrastructure planning is clearly dominated by engineers and local authorities. Little importance is placed on longer-term strategic objectives and integrated catchment planning, but this was perceived as more important in a second analysis going beyond typical questions of stakeholder analysis. We conclude that linking a stakeholder analysis, comprising rarely asked questions, with a rigorous social network analysis is very fruitful and generates complementary results. This combination gave us deeper insight into the socio-political-engineering world of water infrastructure planning that is of vital importance to our well-being.