A Morphological Box for Handling Temporal Data in B2C Systems

User interfaces are key properties of Business-to-Consumer (B2C) systems, and Web-based reservation systems are an important class of B2C systems. In this paper we show that these systems use a surprisingly broad spectrum of different approaches to handling temporal data in their Web inter faces. Based on these observations and on a literature analysis we develop a Morphological Box to present the main options for handling temporal data and give examples. The results indicate that the present state of developing and maintaining B2C systems has not been much influenced by modern Web Engi neering concepts and that there is considerable potential for improvement.

Factor analysis of responses to thermal, electrical, and mechanical painful stimuli supports the importance of multi-modal pain assessment

During the last decade, a multi-modal approach has been established in human experimental pain research for assessing pain thresholds and responses to various experimental pain modalities. Studies have concluded that differences in responses to pain stimuli are mainly related to variation between individuals rather than variation in response to different stimulus modalities. In a factor analysis of 272 consecutive volunteers (137 men and 135 women) who underwent tests with different experimental pain modalities, it was determined whether responses to different pain modalities represent distinct individual uncorrelated dimensions of pain perception. Volunteers underwent single painful electrical stimulation, repeated painful electrical stimulation (temporal summation), test for reflex receptive field, pressure pain stimulation, heat pain stimulation, cold pain stimulation, and a cold pressor test (ice water test). Five distinct factors were found representing responses to 5 distinct experimental pain modalities: pressure, heat, cold, electrical stimulation, and reflex-receptive fields. Each of the factors explained approximately 8% to 35% of the observed variance, and the 5 factors cumulatively explained 94% of the variance. The correlation between the 5 factors was near null (median ρ=0.00, range -0.03 to 0.05), with 95% confidence intervals for pairwise correlations between 2 factors excluding any relevant correlation. Results were almost similar for analyses stratified according to gender and age. Responses to different experimental pain modalities represent different specific dimensions and should be assessed in combination in future pharmacological and clinical studies to represent the complexity of nociception and pain experience.

Cognitive binding in schizophrenia: weakened integration of temporal intersensory information

Cognitive functioning is based on binding processes, by which different features and elements of neurocognition are integrated and coordinated. Binding is an essential ingredient of, for instance, Gestalt perception. We have implemented a paradigm of causality perception based on the work of Albert Michotte, in which 2 identical discs move from opposite sides of a monitor, steadily toward, and then past one another. Their coincidence generates an ambiguous percept of either "streaming" or "bouncing," which the subjects (34 schizophrenia spectrum patients and 34 controls with mean age 27.9 y) were instructed to report. The latter perception is a marker of the binding processes underlying perceived causality (type I binding). In addition to this visual task, acoustic stimuli were presented at different times during the task (150 ms before and after visual coincidence), which can modulate perceived causality. This modulation by intersensory and temporally delayed stimuli is viewed as a different type of binding (type II). We show here, using a mixed-effects hierarchical analysis, that type II binding distinguishes schizophrenia spectrum patients from healthy controls, whereas type I binding does not. Type I binding may even be excessive in some patients, especially those with positive symptoms; Type II binding, however, was generally attenuated in patients. The present findings point to ways in which the disconnection (or Gestalt) hypothesis of schizophrenia can be refined, suggesting more specific markers of neurocognitive functioning and potential targets of treatment.

Brain infiltration of leukocytes contributes to the pathophysiology of temporal lobe epilepsy

Clinical and experimental evidence indicates that inflammatory processes contribute to the pathophysiology of epilepsy, but underlying mechanisms remain mostly unknown. Using immunohistochemistry for CD45 (common leukocyte antigen) and CD3 (T-lymphocytes), we show here microglial activation and infiltration of leukocytes in sclerotic tissue from patients with mesial temporal lobe epilepsy (TLE), as well as in a model of TLE (intrahippocampal kainic acid injection), characterized by spontaneous, nonconvulsive focal seizures. Using specific markers of lymphocytes, microglia, macrophages, and neutrophils in kainate-treated mice, we investigated with pharmacological and genetic approaches the contribution of innate and adaptive immunity to kainate-induced inflammation and neurodegeneration. Furthermore, we used EEG analysis in mutant mice lacking specific subsets of lymphocytes to explore the significance of inflammatory processes for epileptogenesis. Blood-brain barrier disruption and neurodegeneration in the kainate-lesioned hippocampus were accompanied by sustained ICAM-1 upregulation, microglial cell activation, and infiltration of CD3(+) T-cells. Moreover, macrophage infiltration was observed, selectively in the dentate gyrus where prominent granule cell dispersion was evident. Unexpectedly, depletion of peripheral macrophages by systemic clodronate liposome administration affected granule cell survival. Neurodegeneration was aggravated in kainate-lesioned mice lacking T- and B-cells (RAG1-knock-out), because of delayed invasion by Gr-1(+) neutrophils. Most strikingly, these mutant mice exhibited early onset of spontaneous recurrent seizures, suggesting a strong impact of immune-mediated responses on network excitability. Together, the concerted action of adaptive and innate immunity triggered locally by intrahippocampal kainate injection contributes seizure-suppressant and neuroprotective effects, shedding new light on neuroimmune interactions in temporal lobe epilepsy.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

Correlation between topographic N400 anomalies and reduced cerebral blood flow in the anterior temporal lobes of patients with dementia

In Alzheimer's disease (AD) patients, episodic memory impairments are apparent, yet semantic memory difficulties are also observed. While the episodic pathology has been thoroughly studied, the neurophysiological mechanisms of the semantic impairments remain obscure. Semantic dementia (SD) is characterized by isolated semantic memory deficits. The present study aimed to find an early marker of mild AD and SD by employing a semantic priming paradigm during electroencephalogram recordings. Event-related potentials (ERP) of early (P1, N1) and late (N400) word processing stages were obtained to measure semantic memory functions. Separately, baseline cerebral blood flow (CBF) was acquired with arterial spin labeling. Thus, the analysis focused on linear regressions of CBF with ERP topographical similarity indices in order to find the brain structures that showed altered baseline functionality associated with deviant ERPs. All participant groups showed semantic priming in their reaction times. Furthermore, decreased CBF in the temporal lobes was associated with abnormal N400 topography. No significant CBF clusters were found for the early ERPs. Taken together, the neurophysiological results suggested that the automatic spread of activation during semantic word processing was preserved in mild dementia, while controlled access to the words was impaired. These findings suggested that N400-topography alterations might be a potential marker for the detection of early dementia. Such a marker could be beneficial for differential diagnosis due to its low cost and non-invasive application as well as its relationship with semantic memory dysfunctions that are closely associated to the cortical deterioration in regions crucial for semantic word processing.

Differences between RNA and DNA due to RNA editing in temporal lobe epilepsy

To investigate whether alterations in RNA editing (an enzymatic base-specific change to the RNA sequence during primary transcript formation from DNA) of neurotransmitter receptor genes and of transmembrane ion channel genes play a role in human temporal lobe epilepsy (TLE), this exploratory study analyzed 14 known cerebral editing sites in RNA extracted from the brain tissue of 41 patients who underwent surgery for mesial TLE, 23 with hippocampal sclerosis (MTLE+HS). Because intraoperatively sampled RNA cannot be obtained from healthy controls and the best feasible control is identically sampled RNA from patients with a clinically shorter history of epilepsy, the primary aim of the study was to assess the correlation between epilepsy duration and RNA editing in the homogenous group of MTLE+HS. At the functionally relevant I/V site of the voltage-gated potassium channel Kv1.1, an inverse correlation of RNA editing was found with epilepsy duration (r=-0.52, p=0.01) but not with patient age at surgery, suggesting a specific association with either the epileptic process itself or its antiepileptic medication history. No significant correlations were found between RNA editing and clinical parameters at other sites within glutamate receptor or serotonin 2C receptor gene transcripts. An "all-or-none" (≥95% or ≤5%) editing pattern at most or all sites was discovered in 2 patients. As a secondary part of the study, RNA editing was also analyzed as in the previous literature where up to now, few single editing sites were compared with differently obtained RNA from inhomogenous patient groups and autopsies, and by measuring editing changes in our mouse model. The present screening study is first to identify an editing site correlating with a clinical parameter, and to also provide an estimate of the possible effect size at other sites, which is a prerequisite for power analysis needed in planning future studies.

Point Process Methodology for On-line Spatio-temporal Disease Surveillance

The AEGISS (Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics) project aims to use spatio-temporal statistical methods to identify anomalies in the space-time distribution of non-specific, gastrointestinal infections in the UK, using the Southampton area in southern England as a test-case. In this paper, we use the AEGISS project to illustrate how spatio-temporal point process methodology can be used in the development of a rapid-response, spatial surveillance system. Current surveillance of gastroenteric disease in the UK relies on general practitioners reporting cases of suspected food-poisoning through a statutory notification scheme, voluntary laboratory reports of the isolation of gastrointestinal pathogens and standard reports of general outbreaks of infectious intestinal disease by public health and environmental health authorities. However, most statutory notifications are made only after a laboratory reports the isolation of a gastrointestinal pathogen. As a result, detection is delayed and the ability to react to an emerging outbreak is reduced. For more detailed discussion, see Diggle et al. (2003). A new and potentially valuable source of data on the incidence of non-specific gastro-enteric infections in the UK is NHS Direct, a 24-hour phone-in clinical advice service. NHS Direct data are less likely than reports by general practitioners to suffer from spatially and temporally localized inconsistencies in reporting rates. Also, reporting delays by patients are likely to be reduced, as no appointments are needed. Against this, NHS Direct data sacrifice specificity. Each call to NHS Direct is classified only according to the general pattern of reported symptoms (Cooper et al, 2003). The current paper focuses on the use of spatio-temporal statistical analysis for early detection of unexplained variation in the spatio-temporal incidence of non-specific gastroenteric symptoms, as reported to NHS Direct. Section 2 describes our statistical formulation of this problem, the nature of the available data and our approach to predictive inference. Section 3 describes the stochastic model. Section 4 gives the results of fitting the model to NHS Direct data. Section 5 shows how the model is used for spatio-temporal prediction. The paper concludes with a short discussion.

Sex Differences in Semantic Processing: Event-Related Brain Potentials Distinguish between Lower and Higher Order Semantic Analysis during Word Reading

Behavioral studies suggest that women and men differ in the strategic elaboration of verbally encoded information especially in the absence of external task demand. However, measuring such covert processing requires other than behavioral data. The present study used event-related potentials to compare sexes in lower and higher order semantic processing during the passive reading of semantically related and unrelated word pairs. Women and men showed the same early context effect in the P1-N1 transition period. This finding indicates that the initial lexical-semantic access is similar in men and women. In contrast, sexes differed in higher order semantic processing. Women showed an earlier and longer lasting context effect in the N400 accompanied by larger signal strength in temporal networks similarly recruited by men and women. The results suggest that women spontaneously conduct a deeper semantic analysis. This leads to faster processing of related words in the active neural networks as reflected in a shorter stability of the N400 map in women. Taken together, the findings demonstrate that there is a selective sex difference in the controlled semantic analysis during passive word reading that is not reflected in different functional organization but in the depth of processing.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

ESTIMATING TEMPORAL ASSOCIATIONS IN ELECTROCORTICOGRAPHIC (ECoG) TIME SERIES WITH FIRST ORDER PRUNING

Granger causality (GC) is a statistical technique used to estimate temporal associations in multivariate time series. Many applications and extensions of GC have been proposed since its formulation by Granger in 1969. Here we control for potentially mediating or confounding associations between time series in the context of event-related electrocorticographic (ECoG) time series. A pruning approach to remove spurious connections and simultaneously reduce the required number of estimations to fit the effective connectivity graph is proposed. Additionally, we consider the potential of adjusted GC applied to independent components as a method to explore temporal relationships between underlying source signals. Both approaches overcome limitations encountered when estimating many parameters in multivariate time-series data, an increasingly common predicament in today's brain mapping studies.

Multi-detector row CT of the small bowel: peak enhancement temporal window--initial experience

PURPOSE: To prospectively determine quantitatively and qualitatively the timing of maximal enhancement of the normal small-bowel wall by using contrast material-enhanced multi-detector row computed tomography (CT). MATERIALS AND METHODS: This HIPAA-compliant study was approved by the institutional review board. After information on radiation risk was given, written informed consent was obtained from 25 participants with no history of small-bowel disease (mean age, 58 years; 19 men) who had undergone single-level dynamic CT. Thirty seconds after the intravenous administration of contrast material, a serial dynamic acquisition, consisting of 10 images obtained 5 seconds apart, was performed. Enhancement measurements were obtained over time from the small-bowel wall and the aorta. Three independent readers qualitatively assessed small-bowel conspicuity. Quantitative and qualitative data were analyzed during the arterial phase, the enteric phase (which represented peak small-bowel mural enhancement), and the venous phase. Statistical analysis included paired Student t test and Wilcoxon signed rank test with Bonferroni correction. A P value less than .05 was used to indicate a significant difference. RESULTS: The mean time to peak enhancement of the small-bowel wall was 49.3 seconds +/- 7.7 (standard deviation) and 13.5 seconds +/- 7.6 after peak aortic enhancement. Enhancement values were highest during the enteric phase (P < .05). Regarding small-bowel conspicuity, images obtained during the enteric phase were most preferred qualitatively; there was a significant difference between the enteric and arterial phases (P < .001) but not between the enteric and venous phases (P = .18). CONCLUSION: At multi-detector row CT, peak mural enhancement of the normal small bowel occurs on average about 50 seconds after intravenous administration of contrast material or 14 seconds after peak aortic enhancement.

BOLD correlates of continuously fluctuating epileptic activity isolated by independent component analysis

Combined EEG/fMRI recordings offer a promising opportunity to detect brain areas with altered BOLD signal during interictal epileptic discharges (IEDs). These areas are likely to represent the irritative zone, which is itself a reflection of the epileptogenic zone. This paper reports on the imaging findings using independent component analysis (ICA) to continuously quantify epileptiform activity in simultaneously acquired EEG and fMRI. Using ICA derived factors coding for the epileptic activity takes into account that epileptic activity is continuously fluctuating with each spike differing in amplitude, duration and maybe topography, including subthreshold epileptic activity besides clear IEDs and may thus increase the sensitivity and statistical power of combined EEG/fMRI in epilepsy. Twenty patients with different types of focal and generalized epilepsy syndromes were investigated. ICA separated epileptiform activity from normal physiological brain activity and artifacts. In 16/20 patients, BOLD correlates of epileptic activity matched the EEG sources, the clinical semiology, and, if present, the structural lesions. In clinically equivocal cases, the BOLD correlates aided to attribute proper diagnosis of the underlying epilepsy syndrome. Furthermore, in one patient with temporal lobe epilepsy, BOLD correlates of rhythmic delta activity could be employed to delineate the affected hippocampus. Compared to BOLD correlates of manually identified IEDs, the sensitivity was improved from 50% (10/20) to 80%. The ICA EEG/fMRI approach is a safe, non-invasive and easily applicable technique, which can be used to identify regions with altered hemodynamic effects related to IEDs as well as intermittent rhythmic discharges in different types of epilepsy.