Introduction and validation of the Natural Disasters Picture System (NDPS)

Memory modulation: Dominance of negative visual context over neutral verbal memory

Neutral memories can be modulated via intentional memory control paradigms such as directed forgetting. In addition, previous studies have shown that neutral visual memories can be modulated indirectly, via remember and forget instructions towards competing verbal memories. Here we show that direct modulation of neutral verbal memory strength is impaired by negative visual context, and that negative visual context is resistant to indirect memory modulation. Participants were directly instructed to intentionally remember or forget newly encoded neutral verbal information. Importantly, this verbal information was interleaved with embedded negative visual context. Results showed that negative visual context eliminated the well-documented effect of direct instructions to intentionally remember verbal content. Furthermore, negative visual memory was highly persistent, overcoming its sensitivity to indirect modulation shown in previous studies. Finally, these memory effects persisted to the following day. These results demonstrate the dominance of negative visual context over neutral content, highlighting the challenges associated with memory modulation in psychopathologies involving maladaptive processing of negative visual memories.

Environmental risks to humans, the first database of valence and arousal ratings for images of natural hazards

Due to their relevance for the entire society, environmental hazards have largely been investigated in terms of their psychological effects. However, a complete image database comprising different categories of catastrophes has not been proposed yet. We selected 200 photographs of the most frequent natural disasters with the aim to collect the emotional reactions of observers. In particular, 20 stimuli were selected for each of the following 10 categories: earthquake, volcanic activity, lightning, hailstorm, drought, fire, landslide, epidemic, and neutral and positive images as control categories. A sample of 605 participants completed an online survey, in which they were asked to rate either the valence or the arousal of each stimulus, by using a Self-Assessment Manikin. The Environmental Risk to Humans database associates the emotional reactions to these visual stimuli, together with the demographics of the sample (e.g., gender, age, marital status, income, previous experience of natural disasters). The database constitutes a tool to explore human reactions to natural hazards, providing a controlled set of stimuli for different types of catastrophes.

Measurement(s)	valence and arousal
Technology Type(s)	human ratings
Factor Type(s)	natural hazards
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	anthropogenic environment

EEG-Based Estimation on the Reduction of Negative Emotions for Illustrated Surgical Images

Electroencephalogram (EEG) biosignals are widely used to measure human emotional reactions. The recent progress of deep learning-based classification models has improved the accuracy of emotion recognition in EEG signals. We apply a deep learning-based emotion recognition model from EEG biosignals to prove that illustrated surgical images reduce the negative emotional reactions that the photographic surgical images generate. The strong negative emotional reactions caused by surgical images, which show the internal structure of the human body (including blood, flesh, muscle, fatty tissue, and bone) act as an obstacle in explaining the images to patients or communicating with the images with non-professional people. We claim that the negative emotional reactions generated by illustrated surgical images are less severe than those caused by raw surgical images. To demonstrate the difference in emotional reaction, we produce several illustrated surgical images from photographs and measure the emotional reactions they engender using EEG biosignals; a deep learning-based emotion recognition model is applied to extract emotional reactions. Through this experiment, we show that the negative emotional reactions associated with photographic surgical images are much higher than those caused by illustrated versions of identical images. We further execute a self-assessed user survey to prove that the emotions recognized from EEG signals effectively represent user-annotated emotions.