57 resultados para spatial information processing theories


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To estimate the minimal gene set required to sustain bacterial life in nutritious conditions, we carried out a systematic inactivation of Bacillus subtilis genes. Among approximately 4,100 genes of the organism, only 192 were shown to be indispensable by this or previous work. Another 79 genes were predicted to be essential. The vast majority of essential genes were categorized in relatively few domains of cell metabolism, with about half involved in information processing, one-fifth involved in the synthesis of cell envelope and the determination of cell shape and division, and one-tenth related to cell energetics. Only 4% of essential genes encode unknown functions. Most essential genes are present throughout a wide range of Bacteria, and almost 70% can also be found in Archaea and Eucarya. However, essential genes related to cell envelope, shape, division, and respiration tend to be lost from bacteria with small genomes. Unexpectedly, most genes involved in the Embden-Meyerhof-Parnas pathway are essential. Identification of unknown and unexpected essential genes opens research avenues to better understanding of processes that sustain bacterial life.

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The complexity of the signaling network that underlies astrocyte-synapse interactions may seem discouraging when tackled from a theoretical perspective. Computational modeling is challenged by the fact that many details remain hitherto unknown and conventional approaches to describe synaptic function are unsuitable to explain experimental observations when astrocytic signaling is taken into account. Supported by experimental evidence is the possibility that astrocytes perform genuine information processing by means of their calcium signaling and are players in the physiological setting of the basal tone of synaptic transmission. Here we consider the plausibility of this scenario from a theoretical perspective, focusing on the modulation of synaptic release probability by the astrocyte and its implications on synaptic plasticity. The analysis of the signaling pathways underlying such modulation refines our notion of tripartite synapse and has profound implications on our understanding of brain function.

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Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs.We found widespread correlations between BM and MM, which were almost frequency-independent for all the measures except coherence. The analysis of the behavior of synchronization measures in simulated settings with variable coupling strength, connection probability, and parameter mismatch showed that some of them, including S-estimator, S-Renyi, omega, and coherence, aremore sensitive to linear interdependences,while others, like mutual information and phase locking value, are more responsive to nonlinear effects. Onemust consider these properties together with the fact thatMM are computationally less expensive and, therefore, more efficient for the large-scale data sets than BM while choosing a synchronization measure for EEG analysis.

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We present a method for segmenting white matter tracts from high angular resolution diffusion MR. images by representing the data in a 5 dimensional space of position and orientation. Whereas crossing fiber tracts cannot be separated in 3D position space, they clearly disentangle in 5D position-orientation space. The segmentation is done using a 5D level set method applied to hyper-surfaces evolving in 5D position-orientation space. In this paper we present a methodology for constructing the position-orientation space. We then show how to implement the standard level set method in such a non-Euclidean high dimensional space. The level set theory is basically defined for N-dimensions but there are several practical implementation details to consider, such as mean curvature. Finally, we will show results from a synthetic model and a few preliminary results on real data of a human brain acquired by high angular resolution diffusion MRI.

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How does the multi-sensory nature of stimuli influence information processing? Cognitive systems with limited selective attention can elucidate these processes. Six-year-olds, 11-year-olds and 20-year-olds engaged in a visual search task that required them to detect a pre-defined coloured shape under conditions of low or high visual perceptual load. On each trial, a peripheral distractor that could be either compatible or incompatible with the current target colour was presented either visually, auditorily or audiovisually. Unlike unimodal distractors, audiovisual distractors elicited reliable compatibility effects across the two levels of load in adults and in the older children, but high visual load significantly reduced distraction for all children, especially the youngest participants. This study provides the first demonstration that multi-sensory distraction has powerful effects on selective attention: Adults and older children alike allocate attention to potentially relevant information across multiple senses. However, poorer attentional resources can, paradoxically, shield the youngest children from the deleterious effects of multi-sensory distraction. Furthermore, we highlight how developmental research can enrich the understanding of distinct mechanisms controlling adult selective attention in multi-sensory environments.

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We examined how general intelligence, personality, and emotional intelligence-measured as an ability using the MSCEIT-predicted performance on a selective-attention task requiring participants to ignore distracting emotion information. We used a visual prime in which participants saw a pair of faces depicting emotions; their task was to focus on one of the faces (the target) while ignoring the other (the distractor). Next, participants categorized a string of letters (word or nonword), which was either congruent to the target or the distractor. The speed of response to categorizing the string was recorded. Given the emotional nature of the stimuli and the emotional information processing involved in the task, we were surprised to see that none of the MSCEIT branches predicted performance. However, general intelligence and openness to experience reduced response time.

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Deciding whether two fingerprint marks originate from the same source requires examination and comparison of their features. Many cognitive factors play a major role in such information processing. In this paper we examined the consistency (both between- and within-experts) in the analysis of latent marks, and whether the presence of a 'target' comparison print affects this analysis. Our findings showed that the context of a comparison print affected analysis of the latent mark, possibly influencing allocation of attention, visual search, and threshold for determining a 'signal'. We also found that even without the context of the comparison print there was still a lack of consistency in analysing latent marks. Not only was this reflected by inconsistency between different experts, but the same experts at different times were inconsistent with their own analysis. However, the characterization of these inconsistencies depends on the standard and definition of what constitutes inconsistent. Furthermore, these effects were not uniform; the lack of consistency varied across fingerprints and experts. We propose solutions to mediate variability in the analysis of friction ridge skin.

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Deciding whether two fingerprint marks originate from the same source requires examination and comparison of their features. Many cognitive factors play a major role in such information processing. In this paper we examined the consistency (both between- and within-experts) in the analysis of latent marks, and whether the presence of a 'target' comparison print affects this analysis. Our findings showed that the context of a comparison print affected analysis of the latent mark, possibly influencing allocation of attention, visual search, and threshold for determining a 'signal'. We also found that even without the context of the comparison print there was still a lack of consistency in analysing latent marks. Not only was this reflected by inconsistency between different experts, but the same experts at different times were inconsistent with their own analysis. However, the characterization of these inconsistencies depends on the standard and definition of what constitutes inconsistent. Furthermore, these effects were not uniform; the lack of consistency varied across fingerprints and experts. We propose solutions to mediate variability in the analysis of friction ridge skin.

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Three-dimensional imaging and quantification of myocardial function are essential steps in the evaluation of cardiac disease. We propose a tagged magnetic resonance imaging methodology called zHARP that encodes and automatically tracks myocardial displacement in three dimensions. Unlike other motion encoding techniques, zHARP encodes both in-plane and through-plane motion in a single image plane without affecting the acquisition speed. Postprocessing unravels this encoding in order to directly track the 3-D displacement of every point within the image plane throughout an entire image sequence. Experimental results include a phantom validation experiment, which compares zHARP to phase contrast imaging, and an in vivo study of a normal human volunteer. Results demonstrate that the simultaneous extraction of in-plane and through-plane displacements from tagged images is feasible.

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This study proposes a new concept for upscaling local information on failure surfaces derived from geophysical data, in order to develop the spatial information and quickly estimate the magnitude and intensity of a landslide. A new vision of seismic interpretation on landslides is also demonstrated by taking into account basic geomorphic information with a numeric method based on the Sloping Local Base Level (SLBL). The SLBL is a generalization of the base level defined in geomorphology applied to landslides, and allows the calculation of the potential geometry of the landslide failure surface. This approach was applied to a large scale landslide formed mainly in gypsum and situated in a former glacial valley along the Rhone within the Western European Alps. Previous studies identified the existence of two sliding surfaces that may continue below the level of the valley. In this study. seismic refraction-reflexion surveys were carried out to verify the existence of these failure surfaces. The analysis of the seismic data provides a four-layer model where three velocity layers (<1000 ms(-1), 1500 ms(-1) and 3000 ms(-1)) are interpreted as the mobilized mass at different weathering levels and compaction. The highest velocity layer (>4000 ms(-1)) with a maximum depth of similar to 58 m is interpreted as the stable anhydrite bedrock. Two failure surfaces were interpreted from the seismic surveys: an upper failure and a much deeper one (respectively 25 and 50 m deep). The upper failure surface depth deduced from geophysics is slightly different from the results obtained using the SLBL, and the deeper failure surface depth calculated with the SLBL method is underestimated in comparison with the geophysical interpretations. Optimal results were therefore obtained by including the seismic data in the SLBL calculations according to the geomorphic limits of the landslide (maximal volume of mobilized mass = 7.5 x 10(6) m(3)).

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A. Costanza, K. Weber, S. Gandy, C. Bouras, P. R. Hof, P. Giannakopoulos and A. Canuto (2011) Neuropathology and Applied Neurobiology37, 570-584 Contact sport-related chronic traumatic encephalopathy in the elderly: clinical expression and structural substrates Professional boxers and other contact sport athletes are exposed to repetitive brain trauma that may affect motor functions, cognitive performance, emotional regulation and social awareness. The term of chronic traumatic encephalopathy (CTE) was recently introduced to regroup a wide spectrum of symptoms such as cerebellar, pyramidal and extrapyramidal syndromes, impairments in orientation, memory, language, attention, information processing and frontal executive functions, as well as personality changes and behavioural and psychiatric symptoms. Magnetic resonance imaging usually reveals hippocampal and vermis atrophy, a cavum septum pellucidum, signs of diffuse axonal injury, pituitary gland atrophy, dilated perivascular spaces and periventricular white matter disease. Given the partial overlapping of the clinical expression, epidemiology and pathogenesis of CTE and Alzheimer's disease (AD), as well as the close association between traumatic brain injuries (TBIs) and neurofibrillary tangle formation, a mixed pathology promoted by pathogenetic cascades resulting in either CTE or AD has been postulated. Molecular studies suggested that TBIs increase the neurotoxicity of the TAR DNA-binding protein 43 (TDP-43) that is a key pathological marker of ubiquitin-positive forms of frontotemporal dementia (FTLD-TDP) associated or not with motor neurone disease/amyotrophic lateral sclerosis (ALS). Similar patterns of immunoreactivity for TDP-43 in CTE, FTLD-TDP and ALS as well as epidemiological correlations support the presence of common pathogenetic mechanisms. The present review provides a critical update of the evolution of the concept of CTE with reference to its neuropathological definition together with an in-depth discussion of the differential diagnosis between this entity, AD and frontotemporal dementia.

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It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

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The good news with regard to this (or any) chapter on the future of leadership is that there is one. There was a time when researchers called for a moratorium on new leadership theory and research (e.g., Miner, 1975) citing the uncertain future of the field. Then for a time there was a popular academic perspective that leadership did not really matter when it came to shaping organizational outcomes (Meindl & Ehrlich, 1987; Meindl, Ehrlich, & Dukerich, 1985; Pfeffer, 1977). That perspective was laid to rest by "realists" in the field (Day & Antonakis, 2012a) by means of empirical re-interpretation of the results used to support the position that leadership does not matter (Lieberson & O'Connor, 1972; Salancik & Pfeffer, 1977). Specifically, Day and Lord (1988) showed that when proper methodological concerns were addressed (e.g., controlling for industry and company size effects; incorporating appropriate time lags) that the impact of top-level leadership was considerable - explaining as much as 45% of the variance in measures of organizational performance. Despite some recent pessimistic sentiments about the "curiously unformed" state of leadership research and theory (Hackman & Wageman, 2007), others have argued that the field has continued to evolve and is potentially on the threshold of some significant breakthroughs (Day & Antonakis, 2012a). Leadership scholars have been re-energized by new directions in the field and research efforts have revitalized areas previously abandoned for apparent lack of consistency in findings (e.g., leadership trait theory). Our accumulated knowledge now allows us to explain the nature of leadership including its biological bases and other antecedents, and consequences with some degree of confidence. There are other comprehensive sources that review the extensive theoretical and empirical foundation of leadership (Bass, 2008; Day & Antonakis, 2012b) so that will not be the focus of the present chapter. Instead, we will take a future-oriented perspective in identifying particular areas within the leadership field that we believe offer promising perspectives on the future of leadership. Nonetheless, it is worthwhile as background to first provide an overview of how we see the leadership field changing over the past decade or so. This short chronicle will set the stage for a keener understanding of where the future contributions are likely to emerge. Overall, across nine major schools of leadership - trait, behavioural, contingency, contextual, relational, sceptics, information processing, New Leadership, biological and evolutionary - researchers have seen a resurgence in interest in one area, a high level of activity in at least four other areas, inactivity in three areas, and one that was modestly active in the previous decade but we think holds strong promise for the future (Gardner, Lowe, Moss, Mahoney, & Cogliser, 2010). We will next provide brief overviews of these nine schools and their respective levels of research activity (see Figure 1).

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THE COMBINATION OF ADVANCED NEUROIMAGING TECHNIQUES AND MAJOR DEVELOPMENTS IN COMPLEX NETWORK SCIENCE, HAVE GIVEN BIRTH TO A NEW FRAMEWORK FOR STUDYING THE BRAIN: "connectomics." This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research.

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Formative, also called asymmetric, cell divisions produce daughter cells with different identities. Like other divisions, formative divisions rely first of all on the cell cycle machinery with centrally acting cyclin-dependent kinases (CDKs) and their cyclin partners to control progression through the cell cycle. However, it is still largely obscure how developmental cues are translated at the cellular level to promote asymmetric divisions. Here, we show that formative divisions in the shoot and root of the flowering plant Arabidopsis thaliana are controlled by a common mechanism that relies on the activity level of the Cdk1 homolog CDKA;1, with medium levels being sufficient for symmetric divisions but high levels being required for formative divisions. We reveal that the function of CDKA;1 in asymmetric cell divisions operates through a transcriptional regulation system that is mediated by the Arabidopsis Retinoblastoma homolog RBR1. RBR1 regulates not only cell cycle genes, but also, independent of the cell cycle transcription factor E2F, genes required for formative divisions and cell fate acquisition, thus directly linking cell proliferation with differentiation. This mechanism allows the implementation of spatial information, in the form of high kinase activity, with intracellular gating of developmental decisions.