The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases

This chapter presents fuzzy cognitive maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. The corresponding Web KnowARR framework incorporates findings from fuzzy logic. To this end, a first emphasis is particularly on the Web KnowARR framework along with a stakeholder management use case to illustrate the framework’s usefulness as a second focal point. This management form is to help projects to acceptance and assertiveness where claims for company decisions are actively involved in the management process. Stakeholder maps visually (re-) present these claims. On one hand, they resort to non-public content and on the other they resort to content that is available to the public (mostly on the Web). The Semantic Web offers opportunities not only to present public content descriptively but also to show relationships. The proposed framework can serve as the basis for the public content of stakeholder maps.

An image-based method to automatically propagate bony landmarks: application to computational spine biomechanics.

In attempts to elucidate the underlying mechanisms of spinal injuries and spinal deformities, several experimental and numerical studies have been conducted to understand the biomechanical behavior of the spine. However, numerical biomechanical studies suffer from uncertainties associated with hard- and soft-tissue anatomies. Currently, these parameters are identified manually on each mesh model prior to simulations. The determination of soft connective tissues on finite element meshes can be a tedious procedure, which limits the number of models used in the numerical studies to a few instances. In order to address these limitations, an image-based method for automatic morphing of soft connective tissues has been proposed. Results showed that the proposed method is capable to accurately determine the spatial locations of predetermined bony landmarks. The present method can be used to automatically generate patient-specific models, which may be helpful in designing studies involving a large number of instances and to understand the mechanical behavior of biomechanical structures across a given population.

Optogenetics: opsins and optical interfaces in neuroscience.

Optogenetics is defined as the integration of optics and genetics to control well-defined events within specified cells of living tissue. In this introduction, we focus on the basic techniques necessary for employing microbial opsins as optogenetic tools in mammalian brains. We provide a guide for the fundamentals of optogenetic application-selecting an opsin, implementing expression of opsins based on the neuroscientific experimental requirements, and adapting the corresponding optical hardware for delivery of light into mammalian brains.

Application of a computational model for complex fluvial ecosystems: The population dynamics of zebra mussel Dreissena polymorpha as a case study

The potential and adaptive flexibility of population dynamic P-systems (PDP) to study population dynamics suggests that they may be suitable for modelling complex fluvial ecosystems, characterized by a composition of dynamic habitats with many variables that interact simultaneously. Using as a model a reservoir occupied by the zebra mussel Dreissena polymorpha, we designed a computational model based on P systems to study the population dynamics of larvae, in order to evaluate management actions to control or eradicate this invasive species. The population dynamics of this species was simulated under different scenarios ranging from the absence of water flow change to a weekly variation with different flow rates, to the actual hydrodynamic situation of an intermediate flow rate. Our results show that PDP models can be very useful tools to model complex, partially desynchronized, processes that work in parallel. This allows the study of complex hydroecological processes such as the one presented, where reproductive cycles, temperature and water dynamics are involved in the desynchronization of the population dynamics both, within areas and among them. The results obtained may be useful in the management of other reservoirs with similar hydrodynamic situations in which the presence of this invasive species has been documented.

Review of recent results using computational fluid dynamics simulations in patients receiving mechanical assist devices for end-stage heart failure

Many end-stage heart failure patients are not eligible to undergo heart transplantation due to organ shortage, and even those under consideration for transplantation might suffer long waiting periods. A better understanding of the hemodynamic impact of left ventricular assist devices (LVAD) on the cardiovascular system is therefore of great interest. Computational fluid dynamics (CFD) simulations give the opportunity to study the hemodynamics in this patient population using clinical imaging data such as computed tomographic angiography. This article reviews a recent study series involving patients with pulsatile and constant-flow LVAD devices in which CFD simulations were used to qualitatively and quantitatively assess blood flow dynamics in the thoracic aorta, demonstrating its potential to enhance the information available from medical imaging.

Comparison of morphological and rheological conditions between conventional and eversion carotid endarterectomy using computational fluid dynamics - a pilot study

PURPOSE To compare postoperative morphological and rheological conditions after eversion carotid endarterectomy versus conventional carotid endarterectomy using computational fluid dynamics. BASIC METHODS Hemodynamic metrics (velocity, wall shear stress, time-averaged wall shear stress and temporal gradient wall shear stress) in the carotid arteries were simulated in one patient after conventional carotid endarterectomy and one patient after eversion carotid endarterectomy by computational fluid dynamics analysis based on patient specific data. PRINCIPAL FINDINGS Systolic peak of the eversion carotid endarterectomy model showed a gradually decreased pressure along the stream path, the conventional carotid endarterectomy model revealed high pressure (about 180 Pa) at the carotid bulb. Regions of low wall shear stress in the conventional carotid endarterectomy model were much larger than that in the eversion carotid endarterectomy model and with lower time-averaged wall shear stress values (conventional carotid endarterectomy: 0.03-5.46 Pa vs. eversion carotid endarterectomy: 0.12-5.22 Pa). CONCLUSIONS Computational fluid dynamics after conventional carotid endarterectomy and eversion carotid endarterectomy disclosed differences in hemodynamic patterns. Larger studies are necessary to assess whether these differences are consistent and might explain different rates of restenosis in both techniques.

The Neuroscience of Visual Hallucinations

Each year, some two million people in the United Kingdom experience visual hallucinations. Infrequent, fleeting visual hallucinations, often around sleep, are a usual feature of life. In contrast, consistent, frequent, persistent hallucinations during waking are strongly associated with clinical disorders; in particular delirium, eye disease, psychosis, and dementia. Research interest in these disorders has driven a rapid expansion in investigatory techniques, new evidence, and explanatory models. In parallel, a move to generative models of normal visual function has resolved the theoretical tension between veridical and hallucinatory perceptions. From initial fragmented areas of investigation, the field has become increasingly coherent over the last decade. Controversies and gaps remain, but for the first time the shapes of possible unifying models are becoming clear, along with the techniques for testing these. This book provides a comprehensive survey of the neuroscience of visual hallucinations and the clinical techniques for testing these. It brings together the very latest evidence from cognitive neuropsychology, neuroimaging, neuropathology, and neuropharmacology, placing this within current models of visual perception. Leading researchers from a range of clinical and basic science areas describe visual hallucinations in their historical and scientific context, combining introductory information with up-to-date discoveries. They discuss results from the main investigatory techniques applied in a range of clinical disorders. The final section outlines future research directions investigating the potential for new understandings of veridical and hallucinatory perceptions, and for treatments of problematic hallucinations. Fully comprehensive, this is an essential reference for clinicians in the fields of the psychology and psychiatry of hallucinations, as well as for researchers in departments, research institutes and libraries. It has strong foundations in neuroscience, cognitive science, optometry, psychiatry, psychology, clinical medicine, and philosophy. With its lucid explanation and many illustrations, it is a clear resource for educators and advanced undergraduate and graduate students.

BDNF Val66Met polymorphism influence on striatal blood-level-dependent response to monetary feedback depends on valence and agency

Animal work implicates the brain-derived neurotrophic factor (BDNF) in function of the ventral striatum (VS), a region known for its role in processing valenced feedback. Recent evidence in humans shows that BDNF Val66Met polymorphism modulates VS activity in anticipation of monetary feedback. However, it remains unclear whether the polymorphism impacts the processing of self-attributed feedback differently from feedback attributed to an external agent. In this study, we emphasize the importance of the feedback attribution because agency is central to computational accounts of the striatum and cognitive accounts of valence processing. We used functional magnetic resonance imaging and a task, in which financial gains/losses are either attributable to performance (self-attributed, SA) or chance (externally-attributed, EA) to ask whether BDNF Val66Met polymorphism predicts VS activity. We found that BDNF Val66Met polymorphism influenced how feedback valence and agency information were combined in the VS and in the right inferior frontal junction (IFJ). Specifically, Met carriers' VS response to valenced feedback depended on agency information, while Val/Val carriers' VS response did not. This context-specific modulation of valence effectively amplified VS responses to SA losses in Met carriers. The IFJ response to SA losses also differentiated Val/Val from Met carriers. These results may point to a reduced allocation of attention and altered motivational salience to SA losses in Val/Val compared to Met carriers. Implications for major depressive disorder are discussed.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.