Attentional bias modification with a new paradigm: The effect of the Detection Engagement and Savoring Positivity (DESP) task on eye-tracking of attention.

BACKGROUND AND OBJECTIVES: We tested the effect of a new Attentional Bias Modification (ABM) task - the Detection Engagement and Savoring Positivity (DESP) task - on attentional biases. The DESP is innovative in that it involves a procedure of savoring the positivity of various pictures. METHODS: Participants were randomly assigned to the DESP or to a placebo control condition (experiment 1; n = 38) or a condition controlling for savoring (experiment 2; n = 54) in a pre-post/training experimental design. During one week, the participants completed the DESP or the control task once a day between three and six times. We assessed the effects of the DESP task on various attentional biases (i.e. positive, negative and threat) by computing dwell time from an eye-tracking technology before and after the training, and also one week after the post-training session in experiment 2. RESULTS: In both experiments, the attentional bias toward positive stimuli between the pre- and the post-training increased significantly more in the DESP task condition than in the control conditions. Negative and threat attentional biases were not significantly affected by the experimental manipulations. Experiment 2 revealed that the DESP task - including the savoring instruction - increased significantly more the positive attentional bias than a task excluding this step and that this effect remained significant one week after the post-training session. LIMITATIONS: Our samples were mainly composed of women participants. This prevents generalization of the findings. CONCLUSIONS: The DESP task offers promising perspectives for sustainably improving attention to positive information.

Automatic correction of Ma and Sonka's thinning algorithm using P-simple points.

Ma and Sonka proposed a fully parallel 3D thinning algorithm which does not always preserve topology. We propose an algorithm based on P-simple points which automatically corrects Ma and Sonka's algorithm. As far as we know, our algorithm is the only fully parallel curve thinning algorithm which preserves topology.