The Utility of Physiological Measures in Assessing the Empathic Skills of Incarcerated Violent Offenders.

Since lack of empathy is an important indicator of violent behaviors, researchers need consistent and valid measures. This study evaluated the practical significance of a potential physiological correlate of empathy compared to a traditional self-report questionnaire in 18 male violent offenders and 21 general population controls. Empathy skills were assessed with the Interpersonal Reactivity Index (IRI) questionnaire. Heart-Rate Variability (HRV) was assessed with an electrocardiogram. The RMSSD (Root Mean Square of the Successive beat-to-beat Differences), an HRV index implicated in social cognition, was calculated. There were no group differences in IRI scores. However, RMSSD was lower in the offender group. Positive correlations between RMSSD and IRI subscales were found for controls only. We conclude that psychometric measures of empathy do not discriminate incarcerated violent offenders, and that the incorporation of psychophysiological measures, such as HRV, could be an avenue for forensic research on empathy to establish translatable evidence-based information

Effects of anxiety on visuospatial pattern discrimination and decision-making processes: what can we learn from brain dynamics ?

Detection and discrimination of visuospatial input involve at least extracting, selecting and encoding relevant information and decision-making processes allowing selecting a response. These two operations are altered, respectively, by attentional mechanisms that change discrimination capacities, and by beliefs concerning the likelihood of uncertain events. Information processing is tuned by the attentional level that acts like a filter on perception, while decision-making processes are weighed by subjective probability of risk. In addition, it has been shown that anxiety could affect the detection of unexpected events through the modification of the level of arousal. Consequently, purpose of this study concerns whether and how decision-making and brain dynamics are affected by anxiety. To investigate these questions, the performance of women with either a high (12) or a low (12) STAI-T (State-Trait Anxiety Inventory, Spielberger, 1983) was examined in a decision-making visuospatial task where subjects have to recognize a target visual pattern from non-target patterns. The target pattern was a schematic image of furniture arranged in such a way as to give the impression of a living room. Non-target patterns were created by either the compression or the dilatation of the distances between objects. Target and non-target patterns were always presented in the same configuration. Preliminary behavioral results show no group difference in reaction time. In addition, visuo-spatial abilities were analyzed trough the signal detection theory for quantifying perceptual decisions in the presence of uncertainty (Green and Swets, 1966). This theory treats detection of a stimulus as a decision-making process determined by the nature of the stimulus and cognitive factors. Astonishingly, no difference in d' (corresponding to the distance between means of the distributions) and c (corresponds to the likelihood ratio) indexes was observed. Comparison of Event-related potentials (ERP) reveals that brain dynamics differ according to anxiety. It shows differences in component latencies, particularly a delay in anxious subjects over posterior electrode sites. However, these differences are compensated during later components by shorter latencies in anxious subjects compared to non-anxious one. These inverted effects seem indicate that the absence of difference in reaction time rely on a compensation of attentional level that tunes cortical activation in anxious subjects, but they have to hammer away to maintain performance

Ontology-Directed Generation of Frameworks For Pervasive Service Development

Pervasive computing applications are tedious to develop because they combine a number of problems ranging from device heterogeneity, to middleware constraints, to lack of programming support. In this paper, we present an approach to integrating the ontological description of a pervasive computing environment into a programming language, namely Java. From this ontological description of a pervasive computing environment, a framework is automatically generated. It provides the developer with dedicated programming support to manage, discover and invoke services. Besides, it performs a number of verifications both at compile and run time, ensuring the robustness of applications. 1