The automatic processing of information was investigated, varying valence (positive vs. negative) and relevance (other-relevant traits [ORT] vs. possessor-relevant traits [PRTj; G. Peeters, 1983) of stimuli. ORTs denote unconditionally positive or negative consequences for persons in the social environment of the holder of the trait (e.g., honest, brutal) whereas PRTs denote unconditionally positive or negative consequences for the trait holder (e.g., happy, depressive). In 2 experiments using the Stroop paradigm, larger interference effects were found for ORTs than PRTs. This is due to the behavior-relatedness of ORTs. In a go/no-go lexical decision task (Experiment 3), participants either had to withdraw their finger from a pressed key (i.e., "avoid") or had to press a key (i.e., "approach") if a word was presented. Responses to negative ORTs were relatively faster in the withdraw condition, whereas positive ORTs were relatively faster in the press condition.

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Animal experiments have shown that the nociceptive reflex can be used as an indicator of central temporal integration in the nociceptive system. The aim of the present study on humans was to investigate whether the nociceptive reflex, evoked by repetitive strong electrical sural nerve stimuli, increased when summation was reported by the volunteers. The reflexes were recorded from the biceps femoris and rectus femoris muscles in eight volunteers following a series of stimulations at 0.1, 1, 2, and 3 Hz. Each series consisted of five consecutive stimuli. Using 0.1- and 1-Hz stimulation, the reflex was not facilitated in the course of the five consecutive stimuli. Following 2- and 3-Hz stimulation, the reflex size (root mean square amplitude) increased significantly during the course of the fifth stimulus. This reflex facilitation was followed by a significant increase (summation) in the pain magnitude when compared with 1- and 0.1-Hz stimulation. Furthermore, the threshold for psychophysical summation could be determined. This threshold (stimulus intensity) decreased when the stimulus frequency (1-5 Hz) of the five consecutive stimuli was increased. The nociceptive reflex and the psychophysical summation threshold might be used to clarify and quantify aspects of temporal summation within the human nociceptive system.

Ketamine is a noncompetitive N-methyl-D-aspartate (NMDA) receptor channel blocker known to inhibit "wind-up" and hence central hyperexcitability of dorsal horn neurons. We sought to assess the effect of ketamine on single and repeated nociceptive stimuli. A placebo-controlled, human (12 volunteers) experimental study was conducted in which several psychophysical (pain detection and tolerance thresholds, magnitude ratings) and electrophysiologic (withdrawal reflex) techniques were used 1) to investigate whether a ketamine (0.5 mg/kg) bolus followed by a 20-min infusion (9 micrograms.kg-1.min-1) inhibits central temporal summation to repeated nociceptive electrical stimuli, and 2) to assess quantitatively the hypoalgesic potency using several experimental nociceptive stimuli (argon laser, pressure, electrical). Facilitation of the withdrawal reflex to and pain rating of repeated electrical stimuli (five pulses at 2 Hz) were inhibited by ketamine. Reflex and pain rating to a single stimulus did not change. The pressure pain detection and tolerance thresholds were increased significantly by ketamine, whereas the laser heat pain and tolerance thresholds remained stable compared with placebo. The stimulus response function showed that ketamine reduced the responses to the highest electrical stimulus intensities (1.4, 1.6, and 1.8 times the reflex threshold). We conclude that ketamine inhibits central temporal summation in humans and has a marked hypoalgesic effect on high intensity nociceptive stimuli.

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Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data cannot be analyzed by fully automatic methods but require the involvement of the human analyst's expertise. For a comprehensive analysis, the data need to be considered from two complementary perspectives: (1) as spatial distributions (situations) changing over time and (2) as profiles of local temporal variation distributed over space. In order to support the visual analysis of spatiotemporal data, we suggest a framework based on the "Self-Organizing Map" (SOM) method combined with a set of interactive visual tools supporting both analytic perspectives. SOM can be considered as a combination of clustering and dimensionality reduction. In the first perspective, SOM is applied to the spatial situations at different time moments or intervals. In the other perspective, SOM is applied to the local temporal evolution profiles. The integrated visual analytics environment includes interactive coordinated displays enabling various transformations of spatiotemporal data and post-processing of SOM results. The SOM matrix display offers an overview of the groupings of data objects and their two-dimensional arrangement by similarity. This view is linked to a cartographic map display, a time series graph, and a periodic pattern view. The linkage of these views supports the analysis of SOM results in both the spatial and temporal contexts. The variable SOM grid coloring serves as an instrument for linking the SOM with the corresponding items in the other displays. The framework has been validated on a large dataset with real city traffic data, where expected spatiotemporal patterns have been successfully uncovered. We also describe the use of the framework for discovery of previously unknown patterns in 41-years time series of 7 crime rate attributes in the states of the USA.

This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractMovement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic information science, database technology, and data mining.We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks.Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake.3