966 resultados para High-level languages


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In the scenario of social bookmarking, a user browsing the Web bookmarks web pages and assigns free-text labels (i.e., tags) to them according to their personal preferences. In this technical report, we approach one of the practical aspects when it comes to represent users' interests from their tagging activity, namely the categorization of tags into high-level categories of interest. The reason is that the representation of user profiles on the basis of the myriad of tags available on the Web is certainly unfeasible from various practical perspectives; mainly concerning the unavailability of data to reliably, accurately measure interests across such fine-grained categorisation, and, should the data be available, its overwhelming computational intractability. Motivated by this, our study presents the results of a categorization process whereby a collection of tags posted at Delicious #http://delicious.com# are classified into 200 subcategories of interest.

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- The lower member of the Alwa Formation (Lower Olenekian), found within the Ba'id Exotic in the Oman Mountains (Sultanate of Oman), consists of ammonoid-bearing, pelagic limestones that were deposited on an isolated, drowned carbonate platform on the Neotethyan Gondwana margin. The strata contain a variety of unusual carbonate textures and features, including thrombolites, Frutexites-bearing microbialites that contain synsedimentary cements, matrix-free breccias surrounded by isopachous calcite cement, and fissures and cavities filled with large botryoidal cements. Thrombolites are found throughout the study interval, and occur as 0.5-1.0 m thick lenses or beds that contain laterally laterally-linked stromatactis cavities. The Frutexites-bearing microbialites occur less frequently, and also form lenses or beds, up to 30 cm thick; the microbialites may be laminated, and often developed on hardgrounds. In addition, the Frutexites-bearing microbialites also contain synsedimentary calcite cement crusts and botryoids (typically <1 cm thick) that harbour layers or pockets of what appear to be bacterial sheaths and coccoids, and are indicative of biologically mediated precipitation of the cement bodies. Slumping following lithification led to fracturing of the limestone and the precipitation of large, botryoidal aragonite cements in fissures that cut across the primary fabric. Environmental conditions, specifically palaeoxygenation and the degree of calcium carbonate supersaturation, likely controlled whether the thrombolites (high level of calcium carbonate supersaturation associated with vertical mixing of water masses and dysoxic conditions) or Frutexites-bearing microbialites (low level of calcium carbonate supersaturation associated with anoxic conditions and deposition below a stable chemocline) formed. The results of this study point to continued environmental stress in the region during the Early Triassic that likely contributed to the uneven recovery from the Permian-Triassic mass extinction.

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Neuroimaging studies analyzing neurophysiological signals are typically based on comparing averages of peri-stimulus epochs across experimental conditions. This approach can however be problematic in the case of high-level cognitive tasks, where response variability across trials is expected to be high and in cases where subjects cannot be considered part of a group. The main goal of this thesis has been to address this issue by developing a novel approach for analyzing electroencephalography (EEG) responses at the single-trial level. This approach takes advantage of the spatial distribution of the electric field on the scalp (topography) and exploits repetitions across trials for quantifying the degree of discrimination between experimental conditions through a classification scheme. In the first part of this thesis, I developed and validated this new method (Tzovara et al., 2012a,b). Its general applicability was demonstrated with three separate datasets, two in the visual modality and one in the auditory. This development allowed then to target two new lines of research, one in basic and one in clinical neuroscience, which represent the second and third part of this thesis respectively. For the second part of this thesis (Tzovara et al., 2012c), I employed the developed method for assessing the timing of exploratory decision-making. Using single-trial topographic EEG activity during presentation of a choice's payoff, I could predict the subjects' subsequent decisions. This prediction was due to a topographic difference which appeared on average at ~516ms after the presentation of payoff and was subject-specific. These results exploit for the first time the temporal correlates of individual subjects' decisions and additionally show that the underlying neural generators start differentiating their responses already ~880ms before the button press. Finally, in the third part of this project, I focused on a clinical study with the goal of assessing the degree of intact neural functions in comatose patients. Auditory EEG responses were assessed through a classical mismatch negativity paradigm, during the very early phase of coma, which is currently under-investigated. By taking advantage of the decoding method developed in the first part of the thesis, I could quantify the degree of auditory discrimination at the single patient level (Tzovara et al., in press). Our results showed for the first time that even patients who do not survive the coma can discriminate sounds at the neural level, during the first hours after coma onset. Importantly, an improvement in auditory discrimination during the first 48hours of coma was predictive of awakening and survival, with 100% positive predictive value. - L'analyse des signaux électrophysiologiques en neuroimagerie se base typiquement sur la comparaison des réponses neurophysiologiques à différentes conditions expérimentales qui sont moyennées après plusieurs répétitions d'une tâche. Pourtant, cette approche peut être problématique dans le cas des fonctions cognitives de haut niveau, où la variabilité des réponses entre les essais peut être très élevéeou dans le cas où des sujets individuels ne peuvent pas être considérés comme partie d'un groupe. Le but principal de cette thèse est d'investiguer cette problématique en développant une nouvelle approche pour l'analyse des réponses d'électroencephalographie (EEG) au niveau de chaque essai. Cette approche se base sur la modélisation de la distribution du champ électrique sur le crâne (topographie) et profite des répétitions parmi les essais afin de quantifier, à l'aide d'un schéma de classification, le degré de discrimination entre des conditions expérimentales. Dans la première partie de cette thèse, j'ai développé et validé cette nouvelle méthode (Tzovara et al., 2012a,b). Son applicabilité générale a été démontrée avec trois ensembles de données, deux dans le domaine visuel et un dans l'auditif. Ce développement a permis de cibler deux nouvelles lignes de recherche, la première dans le domaine des neurosciences cognitives et l'autre dans le domaine des neurosciences cliniques, représentant respectivement la deuxième et troisième partie de ce projet. En particulier, pour la partie cognitive, j'ai appliqué cette méthode pour évaluer l'information temporelle de la prise des décisions (Tzovara et al., 2012c). En se basant sur l'activité topographique de l'EEG au niveau de chaque essai pendant la présentation de la récompense liée à un choix, on a pu prédire les décisions suivantes des sujets (en termes d'exploration/exploitation). Cette prédiction s'appuie sur une différence topographique qui apparaît en moyenne ~516ms après la présentation de la récompense. Ces résultats exploitent pour la première fois, les corrélés temporels des décisions au niveau de chaque sujet séparément et montrent que les générateurs neuronaux de ces décisions commencent à différentier leurs réponses déjà depuis ~880ms avant que les sujets appuient sur le bouton. Finalement, pour la dernière partie de ce projet, je me suis focalisée sur une étude Clinique afin d'évaluer le degré des fonctions neuronales intactes chez les patients comateux. Des réponses EEG auditives ont été examinées avec un paradigme classique de mismatch negativity, pendant la phase précoce du coma qui est actuellement sous-investiguée. En utilisant la méthode de décodage développée dans la première partie de la thèse, j'ai pu quantifier le degré de discrimination auditive au niveau de chaque patient (Tzovara et al., in press). Nos résultats montrent pour la première fois que même des patients comateux qui ne vont pas survivre peuvent discriminer des sons au niveau neuronal, lors de la phase aigue du coma. De plus, une amélioration dans la discrimination auditive pendant les premières 48heures du coma a été observée seulement chez des patients qui se sont réveillés par la suite (100% de valeur prédictive pour un réveil).

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A variational approach for reliably calculating vibrational linear and nonlinear optical properties of molecules with large electrical and/or mechanical anharmonicity is introduced. This approach utilizes a self-consistent solution of the vibrational Schrödinger equation for the complete field-dependent potential-energy surface and, then, adds higher-level vibrational correlation corrections as desired. An initial application is made to static properties for three molecules of widely varying anharmonicity using the lowest-level vibrational correlation treatment (i.e., vibrational Møller-Plesset perturbation theory). Our results indicate when the conventional Bishop-Kirtman perturbation method can be expected to break down and when high-level vibrational correlation methods are likely to be required. Future improvements and extensions are discussed

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In 1875, 7 years prior to the description of the Koch bacillus, Klebs visualized the first Streptococcus pneumoniae in a pleural fluid. Since then, this organism has played a determinant role in biomedical science. From a biological point of view, it was largely implicated in the development of passive and active immunization by serotherapy and vaccination, respectively. Genetic transformation was also first observed in S. pneumoniae, leading to the discovery of DNA. From a clinical point of view, S. pneumoniae is still today a prime cause of otitis media in children and of pneumonia in all age groups, as well as a predominant cause of meningitis and bacteremia. In adults, bacteremia is still entailed with a mortality of over 25%. Although S. pneumoniae remained very sensitive to penicillin for many years, penicillin-resistance has emerged and increased dramatically over the last 15 years. During this period of time, the frequency of penicillin-resistant isolates has increased from &lt; or = 1% to frequencies varying from 20 to 60% in geographic areas as diverse as South Africa, Spain, France, Hungary, Iceland, Alaska, and numerous regions of the United States and South America. In Switzerland, the current frequency of penicillin-resistant pneumococci ranges between 5 and &gt; or = 10%. The increase in penicillin-resistant pneumococci correlates with the intensive use of beta-lactam antibiotics. The mechanism of resistance is not due to bacterial production of penicillinase, but to an alteration of the bacterial target of penicillin, the so-called penicillin-binding proteins. Resistance is subdivided into (i) inter mediate level resistance (minimal inhibitory concentration [MIC] of penicillin of 0.1-1 mg/L) and (ii) high level resistance (MCI &gt; or = 2 mg/L). The clinical significance of intermediate resistance remains poorly defined. On the other hand, highly resistant strains were responsible for numerous therapeutical failures, especially in cases of meningitis. Antibiotics recommended against penicillin-resistant pneumococci include cefotaxime, ceftriaxone, imipenem and in some instances vancomycin. However, penicillin-resistant pneumococci tend to present cross-resistances to all the antibotics of the beta-lactam family and could even become resistant to the last resort drugs mentioned above. Thus, in conclusion, the explosion of resistance to penicillin in pneumococci is a ubiquitous phenomenon which must be fought against by (i) a strict utilization of antibiotics, (ii) the practice of microbiological sampling of infected foci before treatment, (iii) the systematic surveillance of resistance profiles of pneumococci against antibiotics and (iv) the adequate vaccination of populations at risk.

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Human genetics has progressed at an unprecedented pace during the past 10 years. DNA microarrays currently allow screening of the entire human genome with high level of coverage and we are now entering the era of high-throughput sequencing. These remarkable technical advances are influencing the way medical research is conducted and have boosted our understanding of the structure of the human genome as well as of disease biology. In this context, it is crucial for clinicians to understand the main concepts and limitations of modern genetics. This review will describe key concepts in genetics, including the different types of genetic markers in the human genome, review current methods to detect DNA variation, describe major online public databases in genetics, explain key concepts in statistical genetics and finally present commonly used study designs in clinical and epidemiological research. This review will therefore concentrate on human genetic variation analysis.

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Introduction: Neuroimaging of the self focused on high-level mechanisms such as language, memory or imagery of the self. Recent evidence suggests that low-level mechanisms of multisensory and sensorimotor integration may play a fundamental role in encoding self-location and the first-person perspective (Blanke and Metzinger, 2009). Neurological patients with out-of body experiences (OBE) suffer from abnormal self-location and the first-person perspective due to a damage in the temporo-parietal junction (Blanke et al., 2004). Although self-location and the first-person perspective can be studied experimentally (Lenggenhager et al., 2009), the neural underpinnings of self-location have yet to be investigated. To investigate the brain network involved in self-location and first-person perspective we used visuo-tactile multisensory conflict, magnetic resonance (MR)-compatible robotics, and fMRI in study 1, and lesion analysis in a sample of 9 patients with OBE due to focal brain damage in study 2. Methods: Twenty-two participants saw a video showing either a person's back or an empty room being stroked (visual stimuli) while the MR-compatible robotic device stroked their back (tactile stimulation). Direction and speed of the seen stroking could either correspond (synchronous) or not (asynchronous) to those of the seen stroking. Each run comprised the four conditions according to a 2x2 factorial design with Object (Body, No-Body) and Synchrony (Synchronous, Asynchronous) as main factors. Self-location was estimated using the mental ball dropping (MBD; Lenggenhager et al., 2009). After the fMRI session participants completed a 6-item adapted from the original questionnaire created by Botvinick and Cohen (1998) and based on questions and data obtained by Lenggenhager et al. (2007, 2009). They were also asked to complete a questionnaire to disclose the perspective they adopted during the illusion. Response times (RTs) for the MBD and fMRI data were analyzed with a 3-way mixed model ANOVA with the in-between factor Perspective (up, down) and the two with-in factors Object (body, no-body) and Stroking (synchronous, asynchronous). Quantitative lesion analysis was performed using MRIcron (Rorden et al., 2007). We compared the distributions of brain lesions confirmed by multimodality imaging (Knowlton, 2004) in patients with OBE with those showing complex visual hallucinations involving people or faces, but without any disturbance of self-location and first person perspective. Nine patients with OBE were investigated. The control group comprised 8 patients. Structural imaging data were available for normalization and co-registration in all the patients. Normalization of each patient's lesion into the common MNI (Montreal Neurological Institute) reference space permitted simple, voxel-wise, algebraic comparisons to be made. Results: Even if in the scanner all participants were lying on their back and were facing upwards, analysis of perspective showed that half of the participants had the impression to be looking down at the virtual human body below them, despite any cues about their body position (Down-group). The other participants had the impression to be looking up at the virtual body above them (Up-group). Analysis of Q3 ("How strong was the feeling that the body you saw was you?") indicated stronger self-identification with the virtual body during the synchronous stroking. RTs in the MBD task confirmed these subjective data (significant 3-way interaction between perspective, object and stroking). fMRI results showed eight cortical regions where the BOLD signal was significantly different during at least one of the conditions resulting from the combination of Object and Stroking, relative to baseline: right and left temporo-parietal junction, right EBA, left middle occipito-temporal gyrus, left postcentral gyrus, right medial parietal lobe, bilateral medial occipital lobe (Fig 1). The activation patterns in right and left temporo-parietal junction and right EBA reflected changes in self-location and perspective as revealed by statistical analysis that was performed on the percentage of BOLD change with respect to the baseline. Statistical lesion overlap comparison (using nonparametric voxel based lesion symptom mapping) with respect to the control group revealed the right temporo-parietal junction, centered at the angular gyrus (Talairach coordinates x = 54, y =-52, z = 26; p>0.05, FDR corrected). Conclusions: The present questionnaire and behavioural results show that - despite the noisy and constraining MR environment) our participants had predictable changes in self-location, self-identification, and first-person perspective when robotic tactile stroking was applied synchronously with the robotic visual stroking. fMRI data in healthy participants and lesion data in patients with abnormal self-location and first-person perspective jointly revealed that the temporo-parietal cortex especially in the right hemisphere encodes these conscious experiences. We argue that temporo-parietal activity reflects the experience of the conscious "I" as embodied and localized within bodily space.

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Neuroimaging of the self has focused on high-level mechanisms such as language, memory or imagery of the self and implicated widely distributed brain networks. Yet recent evidence suggests that low-level mechanisms such as multisensory and sensorimotor integration may play a fundamental role in self-related processing. In the present study we used visuotactile multisensory conflict, robotics, virtual reality, and fMRI to study such low-level mechanisms by experimentally inducing changes in self-location. Participants saw a video of a person's back (body) or an empty room (no-body) being stroked while a MR-compatible robotic device stroked their back. The latter tactile input was synchronous or asynchronous with respect to the seen stroking. Self-location was estimated behaviorally confirming previous data that self-location only differed between the two body conditions. fMRI results showed a bilateral activation of the temporo-parietal cortex with a significantly higher BOLD signal increase in the synchronous/body condition with respect to the other conditions. Sensorimotor cortex and extrastriate-body-area were also activated. We argue that temporo-parietal activity reflects the experience of the conscious 'I' as embodied and localized within bodily space, compatible with clinical data in neurological patients with out-of-body experiences.

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Background: Despite the fact that labour market flexibility has resulted in an expansion of precarious employment in industrialized countries, to date there is limited empirical evidence about its health consequences. The Employment Precariousness Scale (EPRES) is a newly developed, theory-based, multidimensional questionnaire specifically devised for epidemiological studies among waged and salaried workers. Objective: To assess acceptability, reliability and construct validity of EPRES in a sample of waged and salaried workers in Spain. Methods: Cross-sectional study, using a sub-sample of 6.968 temporary and permanent workers from a population-based survey carried out in 2004-2005. The survey questionnaire was interviewer administered and included the six EPRES subscales, measures of the psychosocial work environment (COPSOQ ISTAS21), and perceived general and mental health (SF-36). Results: A high response rate to all EPRES items indicated good acceptability; Cronbach’s alpha coefficients, over 0.70 for all subscales and the global score, demonstrated good internal consistency reliability; exploratory factor analysis using principal axis analysis and varimax rotation confirmed the six-subscale structure and the theoretical allocation of all items. Patterns across known groups and correlation coefficients with psychosocial work environment measures and perceived health demonstrated the expected relations, providing evidence of construct validity. Conclusions: Our results provide evidence in support of the psychometric properties of EPRES, which appears to be a promising tool for the measurement of employment precariousness in public health research.

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This paper introduces Collage, a high-level IMS-LD compliant authoring tool that is specialized for CSCL (Computer-Supported Collaborative Learning). Nowadays CSCL is a key trend in elearning since it highlights the importance of social interactions as an essential element of learning. CSCL is an interdisciplinary domain, which demands participatory design techniques that allow teachers to get directly involved in design activities. Developing CSCL designs using LD is a difficult task for teachers since LD is a complex technical specification and modelling collaborative characteristics can be tricky. Collage helps teachers in the process of creating their own potentially effective collaborative Learning Designs by reusing and customizing patterns, according to the requirements of a particular learning situation. These patterns, called Collaborative Learning Flow Patterns (CLFPs), represent best practices that are repetitively used by practitioners when structuring the flow of (collaborative) learning activities. An example of an LD that can be created using Collage is illustrated in the paper. Preliminary evaluation results show that teachers, with experience in CL but without LD knowledge, can successfully design real collaborative learning experiences using Collage.

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In recent years, the large deployment of mobile devices has led to a massiveincrease in the volume of records of where people have been and when they were there.The analysis of these spatio-temporal data can supply high-level human behaviorinformation valuable to urban planners, local authorities, and designer of location-basedservices. In this paper, we describe our approach to collect and analyze the history ofphysical presence of tourists from the digital footprints they publicly disclose on the web.Our work takes place in the Province of Florence in Italy, where the insights on thevisitors’ flows and on the nationalities of the tourists who do not sleep in town has beenlimited to information from survey-based hotel and museums frequentation. In fact, mostlocal authorities in the world must face this dearth of data on tourist dynamics. In thiscase study, we used a corpus of geographically referenced photos taken in the provinceby 4280 photographers over a period of 2 years. Based on the disclosure of the locationof the photos, we design geovisualizations to reveal the tourist concentration and spatiotemporalflows. Our initial results provide insights on the density of tourists, the points ofinterests they visit as well as the most common trajectories they follow.

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Recently, there has been an increased interest on the neural mechanisms underlying perceptual decision making. However, the effect of neuronal adaptation in this context has not yet been studied. We begin our study by investigating how adaptation can bias perceptual decisions. We considered behavioral data from an experiment on high-level adaptation-related aftereffects in a perceptual decision task with ambiguous stimuli on humans. To understand the driving force behind the perceptual decision process, a biologically inspired cortical network model was used. Two theoretical scenarios arose for explaining the perceptual switch from the category of the adaptor stimulus to the opposite, nonadapted one. One is noise-driven transition due to the probabilistic spike times of neurons and the other is adaptation-driven transition due to afterhyperpolarization currents. With increasing levels of neural adaptation, the system shifts from a noise-driven to an adaptation-driven modus. The behavioral results show that the underlying model is not just a bistable model, as usual in the decision-making modeling literature, but that neuronal adaptation is high and therefore the working point of the model is in the oscillatory regime. Using the same model parameters, we studied the effect of neural adaptation in a perceptual decision-making task where the same ambiguous stimulus was presented with and without a preceding adaptor stimulus. We find that for different levels of sensory evidence favoring one of the two interpretations of the ambiguous stimulus, higher levels of neural adaptation lead to quicker decisions contributing to a speed–accuracy trade off.

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Microsatellite instability (MSI) testing in clinics is becoming increasingly widespread; therefore, there is an urgent need for methodology standardization and the availability of quality control. This study is aimed to assess the interlaboratory reproducibility of MSI testing in archive samples by using a panel of 5 recently introduced, mononucleotide repeats (MNR). The quality control involved 8 European institutions. Participants were supplied with DNA extracted from 15 archive colon carcinoma samples and from the corresponding normal tissues. Every group was asked to assess the MSI status of the samples by using the BAT25, BAT26, NR21, NR24, and NR27 mononucleotide markers. Four institutions repeated the analysis using the NCI reference panel to confirm the results obtained with the MNR markers. The overall concordance among institutions for MSI analyses at single locus level was 97.7% when using the MNR panel and 95.0% with the NCI one. The laboratories obtained a full agreement in scoring the MSI status of each patient sample, both using the mononucleotide and the NCI marker sets. With the NCI marker set, however, concordance was lowered to 85.7% when considering the MSI-Low phenotype. Concordance between the 2 panels in scoring the MSI status of each sample was complete if no discrimination was made between MSI-Stable and MSI-L, whereas it dropped to 76.7% if MSI-L was considered. In conclusion, the use of the MNR panel seems to be a robust approach that yields a very high level of reproducibility. The results obtained with the 5 MNR are diagnostically consistent with those obtained by the use of the NCI markers, except for the MSI-Low phenotype.

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Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that regulate the expression of many genes involved in lipid metabolism. The biological roles of PPARalpha and PPARgamma are relatively well understood, but little is known about the function of PPARbeta. To address this question, and because PPARbeta is expressed to a high level in the developing brain, we used reaggregated brain cell cultures prepared from dissociated fetal rat telencephalon as experimental model. In these primary cultures, the fetal cells initially form random aggregates, which progressively acquire a tissue-specific pattern resembling that of the brain. PPARs are differentially expressed in these aggregates, with PPARbeta being the prevalent isotype. PPARalpha is present at a very low level, and PPARgamma is absent. Cell type-specific expression analyses revealed that PPARbeta is ubiquitous and most abundant in some neurons, whereas PPARalpha is predominantly astrocytic. We chose acyl-CoA synthetases (ACSs) 1, 2, and 3 as potential target genes of PPARbeta and first analyzed their temporal and cell type-specific pattern. This analysis indicated that ACS2 and PPARbeta mRNAs have overlapping expression patterns, thus designating the ACS2 gene as a putative target of PPARbeta. Using a selective PPARbeta activator, we found that the ACS2 gene is transcriptionally regulated by PPARbeta, demonstrating a role for PPARbeta in brain lipid metabolism.

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Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.