53 resultados para spatial activity recognition
em Université de Lausanne, Switzerland
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SOUND OBJECTS IN TIME, SPACE AND ACTIONThe term "sound object" describes an auditory experience that is associated with an acoustic event produced by a sound source. At cortical level, sound objects are represented by temporo-spatial activity patterns within distributed neural networks. This investigation concerns temporal, spatial and action aspects as assessed in normal subjects using electrical imaging or measurement of motor activity induced by transcranial magnetic stimulation (TMS).Hearing the same sound again has been shown to facilitate behavioral responses (repetition priming) and to modulate neural activity (repetition suppression). In natural settings the same source is often heard again and again, with variations in spectro-temporal and spatial characteristics. I have investigated how such repeats influence response times in a living vs. non-living categorization task and the associated spatio-temporal patterns of brain activity in humans. Dynamic analysis of distributed source estimations revealed differential sound object representations within the auditory cortex as a function of the temporal history of exposure to these objects. Often heard sounds are coded by a modulation in a bilateral network. Recently heard sounds, independently of the number of previous exposures, are coded by a modulation of a left-sided network.With sound objects which carry spatial information, I have investigated how spatial aspects of the repeats influence neural representations. Dynamics analyses of distributed source estimations revealed an ultra rapid discrimination of sound objects which are characterized by spatial cues. This discrimination involved two temporo-spatially distinct cortical representations, one associated with position-independent and the other with position-linked representations within the auditory ventral/what stream.Action-related sounds were shown to increase the excitability of motoneurons within the primary motor cortex, possibly via an input from the mirror neuron system. The role of motor representations remains unclear. I have investigated repetition priming-induced plasticity of the motor representations of action sounds with the measurement of motor activity induced by TMS pulses applied on the hand motor cortex. TMS delivered to the hand area within the primary motor cortex yielded larger magnetic evoked potentials (MEPs) while the subject was listening to sounds associated with manual than non- manual actions. Repetition suppression was observed at motoneuron level, since during a repeated exposure to the same manual action sound the MEPs were smaller. I discuss these results in terms of specialized neural network involved in sound processing, which is characterized by repetition-induced plasticity.Thus, neural networks which underlie sound object representations are characterized by modulations which keep track of the temporal and spatial history of the sound and, in case of action related sounds, also of the way in which the sound is produced.LES OBJETS SONORES AU TRAVERS DU TEMPS, DE L'ESPACE ET DES ACTIONSLe terme "objet sonore" décrit une expérience auditive associée avec un événement acoustique produit par une source sonore. Au niveau cortical, les objets sonores sont représentés par des patterns d'activités dans des réseaux neuronaux distribués. Ce travail traite les aspects temporels, spatiaux et liés aux actions, évalués à l'aide de l'imagerie électrique ou par des mesures de l'activité motrice induite par stimulation magnétique trans-crânienne (SMT) chez des sujets sains. Entendre le même son de façon répétitive facilite la réponse comportementale (amorçage de répétition) et module l'activité neuronale (suppression liée à la répétition). Dans un cadre naturel, la même source est souvent entendue plusieurs fois, avec des variations spectro-temporelles et de ses caractéristiques spatiales. J'ai étudié la façon dont ces répétitions influencent le temps de réponse lors d'une tâche de catégorisation vivant vs. non-vivant, et les patterns d'activité cérébrale qui lui sont associés. Des analyses dynamiques d'estimations de sources ont révélé des représentations différenciées des objets sonores au niveau du cortex auditif en fonction de l'historique d'exposition à ces objets. Les sons souvent entendus sont codés par des modulations d'un réseau bilatéral. Les sons récemment entendus sont codé par des modulations d'un réseau du côté gauche, indépendamment du nombre d'expositions. Avec des objets sonores véhiculant de l'information spatiale, j'ai étudié la façon dont les aspects spatiaux des sons répétés influencent les représentations neuronales. Des analyses dynamiques d'estimations de sources ont révélé une discrimination ultra rapide des objets sonores caractérisés par des indices spatiaux. Cette discrimination implique deux représentations corticales temporellement et spatialement distinctes, l'une associée à des représentations indépendantes de la position et l'autre à des représentations liées à la position. Ces représentations sont localisées dans la voie auditive ventrale du "quoi".Des sons d'actions augmentent l'excitabilité des motoneurones dans le cortex moteur primaire, possiblement par une afférence du system des neurones miroir. Le rôle des représentations motrices des sons d'actions reste peu clair. J'ai étudié la plasticité des représentations motrices induites par l'amorçage de répétition à l'aide de mesures de potentiels moteurs évoqués (PMEs) induits par des pulsations de SMT sur le cortex moteur de la main. La SMT appliquée sur le cortex moteur primaire de la main produit de plus grands PMEs alors que les sujets écoutent des sons associée à des actions manuelles en comparaison avec des sons d'actions non manuelles. Une suppression liée à la répétition a été observée au niveau des motoneurones, étant donné que lors de l'exposition répétée au son de la même action manuelle les PMEs étaient plus petits. Ces résultats sont discuté en termes de réseaux neuronaux spécialisés impliqués dans le traitement des sons et caractérisés par de la plasticité induite par la répétition. Ainsi, les réseaux neuronaux qui sous-tendent les représentations des objets sonores sont caractérisés par des modulations qui gardent une trace de l'histoire temporelle et spatiale du son ainsi que de la manière dont le son a été produit, en cas de sons d'actions.
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Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) without significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.
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Forest fire sequences can be modelled as a stochastic point process where events are characterized by their spatial locations and occurrence in time. Cluster analysis permits the detection of the space/time pattern distribution of forest fires. These analyses are useful to assist fire-managers in identifying risk areas, implementing preventive measures and conducting strategies for an efficient distribution of the firefighting resources. This paper aims to identify hot spots in forest fire sequences by means of the space-time scan statistics permutation model (STSSP) and a geographical information system (GIS) for data and results visualization. The scan statistical methodology uses a scanning window, which moves across space and time, detecting local excesses of events in specific areas over a certain period of time. Finally, the statistical significance of each cluster is evaluated through Monte Carlo hypothesis testing. The case study is the forest fires registered by the Forest Service in Canton Ticino (Switzerland) from 1969 to 2008. This dataset consists of geo-referenced single events including the location of the ignition points and additional information. The data were aggregated into three sub-periods (considering important preventive legal dispositions) and two main ignition-causes (lightning and anthropogenic causes). Results revealed that forest fire events in Ticino are mainly clustered in the southern region where most of the population is settled. Our analysis uncovered local hot spots arising from extemporaneous arson activities. Results regarding the naturally-caused fires (lightning fires) disclosed two clusters detected in the northern mountainous area.
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The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.
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Abstract : Auditory spatial functions are of crucial importance in everyday life. Determining the origin of sound sources in space plays a key role in a variety of tasks including orientation of attention, disentangling of complex acoustic patterns reaching our ears in noisy environments. Following brain damage, auditory spatial processing can be disrupted, resulting in severe handicaps. Complaints of patients with sound localization deficits include the inability to locate their crying child or being over-loaded by sounds in crowded public places. Yet, the brain bears a large capacity for reorganization following damage and/or learning. This phenomenon is referred as plasticity and is believed to underlie post-lesional functional recovery as well as learning-induced improvement. The aim of this thesis was to investigate the organization and plasticity of different aspects of auditory spatial functions. Overall, we report the outcomes of three studies: In the study entitled "Learning-induced plasticity in auditory spatial representations" (Spierer et al., 2007b), we focused on the neurophysiological and behavioral changes induced by auditory spatial training in healthy subjects. We found that relatively brief auditory spatial discrimination training improves performance and modifies the cortical representation of the trained sound locations, suggesting that cortical auditory representations of space are dynamic and subject to rapid reorganization. In the same study, we tested the generalization and persistence of training effects over time, as these are two determining factors in the development of neurorehabilitative intervention. In "The path to success in auditory spatial discrimination" (Spierer et al., 2007c), we investigated the neurophysiological correlates of successful spatial discrimination and contribute to the modeling of the anatomo-functional organization of auditory spatial processing in healthy subjects. We showed that discrimination accuracy depends on superior temporal plane (STP) activity in response to the first sound of a pair of stimuli. Our data support a model wherein refinement of spatial representations occurs within the STP and that interactions with parietal structures allow for transformations into coordinate frames that are required for higher-order computations including absolute localization of sound sources. In "Extinction of auditory stimuli in hemineglect: space versus ear" (Spierer et al., 2007a), we investigated auditory attentional deficits in brain-damaged patients. This work provides insight into the auditory neglect syndrome and its relation with neglect symptoms within the visual modality. Apart from contributing to a basic understanding of the cortical mechanisms underlying auditory spatial functions, the outcomes of the studies also contribute to develop neurorehabilitation strategies, which are currently being tested in clinical populations.
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Background: Plasmodium falciparum(P. falciparum) merozoite surfaceprotein 2 (MSP-2) is one of bloodstage proteins that are associated withprotection from malaria. MSP-2 consistsof a highly polymorphic centralrepeat region flanked by a dimorphicregion that defines the two allelicfamilies, 3D7 and FC27; N- and Cterminalregions are conserved domains.Long synthetic peptides (LSP)representing the two allelic familiesof MSP-2 and constant regions arerecognized by sera from donors livingin endemic areas; and specific antibodies(Abs) are associated with protectionand active in antibody dependentcellular inhibition (ADCI) in vitro.However, the fine specificity ofAb response to the two allelic familiesof MSP-2 is unknown. Methods: Peptidesrepresenting dimorphic regionof 3D7 and FC27 families and theirC-terminal (common fragment to thetwo families) termed 3D7-D (88 aa),FC27-D (48 aa) and C (40 aa) respectivelywere synthesized. Overlapping20 mer peptides covering dimorphicand constant regions of two familieswere also synthesized for epitopemapping. Human sera were obtainedfrom donors living in malaria endemicareas. SpecificDand CregionsAbs were purified from single or poolhuman sera. Sera from mice were obtainedafter immunization with thetwo families LSP mixture in three differentadjuvants: alhydrogel (Alum),Glucopyranosyl Lipid Adjuvant-Stableoil-in-water Emulsion (GLA-SE)and Virosome. For ADCI, P. falciparum(strain 3D7) parasite wasmaintained in culture at 0.5% parasitemiaand 4% hematocrit in air tightbox at love oxygen (2%) and 37 ºC.Results: We identified several epitopesfrom the dimorphic and constantregions of both families of MSP-2, inmice and humans (adults and children).In human, most recognizedepitopes were the same in differentendemic regions for each domain ofthe two families of MSP-2. In mice,the differential recognition of epitopewas depending on the strain of mouseand interestingly on the adjuvantused. GLA-SE and alum as adjuvantswere more often associated with therecognition of multiple epitopes thanvirosomes. Epitope-specific Abs recognizednative merozoites of P.falciparum and were active in ADCIto block development of parasite.Conclusion: The delineation of a limitednumber of epitopes could be exploitedto develop MSP-2 vaccinesactive on both allelic families ofMSP-2.
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MAGE-encoded antigens, which are expressed by tumors of many histological types but not in normal tissues, are suitable candidates for vaccine-based immunotherapy of cancers. Thus far, however, T-cell responses to MAGE antigens have been detected only occasionally in cancer patients. In contrast, by using HLA/peptide fluorescent tetramers, we have observed recently that CD8(+) T cells specific for peptide MAGE-A10(254-262) can be detected frequently in peptide-stimulated peripheral blood mononuclear cells from HLA-A2-expressing melanoma patients and healthy donors. On the basis of these results, antitumoral vaccination trials using peptide MAGE-A10(254-262) have been implemented recently. In the present study, we have characterized MAGE-A10(254-262)-specific CD8(+) T cells in polyclonal cultures and at the clonal level. The results indicate that the repertoire of MAGE-A10(254-262)-specific CD8(+) T cells is diverse both in terms of clonal composition, efficiency of peptide recognition, and tumor-specific lytic activity. Importantly, only CD8(+) T cells able to recognize the antigenic peptide with high efficiency are able to lyse MAGE-A10-expressing tumor cells. Under defined experimental conditions, the tetramer staining intensity exhibited by MAGE-A10(254-262)-specific CD8(+) T cells correlates with efficiency of peptide recognition so that "high" and "low" avidity cells can be separated by FACS. Altogether, the data reported here provide evidence for functional diversity of MAGE-A10(254-262)-specific T cells and will be instrumental for the monitoring of peptide MAGE-A10(254-262)-based clinical trials.
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The proprotein convertases (PCs) are a family of nine mammalian enzymes that play key roles in the maintenance of cell homeostasis by activating or inactivating proteins via limited proteolysis under temporal and spatial control. A wide range of pathogens, including major human pathogenic viruses can hijack cellular PCs for their own purposes. In particular, productive infection with many enveloped viruses critically depends on the processing of their fusion-active viral envelope glycoproteins by cellular PCs. Based on their crucial role in virus-host interaction, PCs can be important determinants for viral pathogenesis and represent promising targets of therapeutic antiviral intervention. In the present review we will cover basic aspects and recent developments of PC-mediated maturation of viral envelope glycoproteins of selected medically important viruses. The molecular mechanisms underlying the recognition of PCs by viral glycoproteins will be described, including recent findings demonstrating differential PC-recognition of viral and cellular substrates. We will further discuss a possible scenario how viruses during co-evolution with their hosts adapted their glycoproteins to modulate the activity of cellular PCs for their own benefit and discuss the consequences for virus-host interaction and pathogenesis. Particular attention will be given to past and current efforts to evaluate cellular PCs as targets for antiviral therapeutic intervention, with emphasis on emerging highly pathogenic viruses for which no efficacious drugs or vaccines are currently available.
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Differences in personality factors between individuals may manifest themselves with different patterns of neural activity while individuals process stimuli with emotional content. We attempted to verify this hypothesis by investigating emotional susceptibility (ES), a specific emotional trait of the human personality defined as the tendency to "experience feelings of discomfort, helplessness, inadequacy and vulnerability" after exposure to stimuli with emotional valence. By administering a questionnaire evaluating the individuals' ES, we selected two groups of participants with high and low ES respectively. Then, we used functional magnetic resonance imaging to investigate differences between the groups in the neural activity involved while they were processing emotional stimuli in an explicit (focusing on the content of the stimuli) or an incidental (focusing on spatial features of the stimuli, irrespectively of their content) way. The results showed a selective difference in brain activity between groups only in the explicit processing of the emotional stimuli: bilateral activity of the anterior insula was present in subjects with high ES but not in subjects with low ES. This difference in neural activity within the anterior insula proved to be purely functional since no brain morphological differences were found between groups, as assessed by a voxel-based morphometry analysis. Although the role of the anterior insula in the processing of contexts perceived as emotionally salient is well established, the present study provides the first evidence of a modulation of the insular activity depending on the individuals' ES trait of personality.
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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.
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The last ten years of research in the field of innate immunity have been incredibly fertile: the transmembrane Toll-like receptors (TLRs) were discovered as guardians protecting the host against microbial attacks and the emerging pathways characterized in detail. More recently, cytoplasmic sensors were identified, which are capable of detecting not only microbial, but also self molecules. Importantly, while such receptors trigger crucial host responses to microbial insult, over-activity of some of them has been linked to autoinflammatory disorders, hence demonstrating the importance of tightly regulating their actions over time and space. Here, we provide an overview of recent findings covering this area of innate and inflammatory responses that originate from the cytoplasm
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OBJECTIVES: Comparison of doxorubicin uptake, leakage and spatial regional blood flow, and drug distribution was made for antegrade, retrograde, combined antegrade and retrograde isolated lung perfusion, and pulmonary artery infusion by endovascular inflow occlusion (blood flow occlusion), as opposed to intravenous administration in a porcine model. METHODS: White pigs underwent single-pass lung perfusion with doxorubicin (320 mug/mL), labeled 99mTc-microspheres, and Indian ink. Visual assessment of the ink distribution and perfusion scintigraphy of the perfused lung was performed. 99mTc activity and doxorubicin levels were measured by gamma counting and high-performance liquid chromatography on 15 tissue samples from each perfused lung at predetermined localizations. RESULTS: Overall doxorubicin uptake in the perfused lung was significantly higher (P = .001) and the plasma concentration was significantly lower (P < .0001) after all isolated lung perfusion techniques, compared with intravenous administration, without differences between them. Pulmonary artery infusion (blood flow occlusion) showed an equally high doxorubicin uptake in the perfused lung but a higher systemic leakage than surgical isolated lung perfusion (P < .0001). The geometric coefficients of variation of the doxorubicin lung tissue levels were 175%, 279%, 226%, and 151% for antegrade, retrograde, combined antegrade and retrograde isolated lung perfusion, and pulmonary artery infusion by endovascular inflow occlusion (blood flow occlusion), respectively, compared with 51% for intravenous administration (P = .09). 99mTc activity measurements of the samples paralleled the doxorubicin level measurements, indicating a trend to a more heterogeneous spatial regional blood flow and drug distribution after isolated lung perfusion and blood flow occlusion compared with intravenous administration. CONCLUSIONS: Cytostatic lung perfusion results in a high overall doxorubicin uptake, which is, however, heterogeneously distributed within the perfused lung.
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Knockout mice lacking alphalb noradrenergic receptors were tested in behavioural experiments to test a possible effect of the absence of this receptor in reaction to novelty and spatial orientation. Reaction to novelty was tested in two experiments. In the first one the mice' latency to exit the first part of a two compartment set-up was measured. The knockout mice were faster to emerge then their littermate controls. Then they were tested in an open-field, in which new objects were added at the second trial. In the open-field without objects (first trial), the knockout mice showed a greater locomotor activity (path length). Then the same mice showed enhanced exploration of the newly introduced objects, relative to the control. The spatial orientation experiments were done on a homing board and in the water maze. The homing board did not yield a significant difference between the knock-out and the control mice. Both groups showed impaired results when the proximal (olfactory) and distal (visual) cues were disrupted by the rotation of the table. In the water maze however, the alphalb(-/-) mice were unable to solve the task (acquisition and retention), whereas the control mice showed a good acquisition and retention behaviour. The knockout mice' incapacity to learn to reach the submerged platform was not due to an incapacity to swim, as they were as good as their control littermates to reach the platform when it was visible.
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Human electrophysiological studies support a model whereby sensitivity to so-called illusory contour stimuli is first seen within the lateral occipital complex. A challenge to this model posits that the lateral occipital complex is a general site for crude region-based segmentation, based on findings of equivalent hemodynamic activations in the lateral occipital complex to illusory contour and so-called salient region stimuli, a stimulus class that lacks the classic bounding contours of illusory contours. Using high-density electrical mapping of visual evoked potentials, we show that early lateral occipital cortex activity is substantially stronger to illusory contour than to salient region stimuli, whereas later lateral occipital complex activity is stronger to salient region than to illusory contour stimuli. Our results suggest that equivalent hemodynamic activity to illusory contour and salient region stimuli probably reflects temporally integrated responses, a result of the poor temporal resolution of hemodynamic imaging. The temporal precision of visual evoked potentials is critical for establishing viable models of completion processes and visual scene analysis. We propose that crude spatial segmentation analyses, which are insensitive to illusory contours, occur first within dorsal visual regions, not the lateral occipital complex, and that initial illusory contour sensitivity is a function of the lateral occipital complex.