Electrodermal activity as an index of food neophobia outside the lab

IntroductionUnderstanding how food neophobia affects food experience may help to shift toward sustainable diets. Previous research suggests that individuals with higher food neophobia are more aroused and attentive when observing food-related stimuli. The present study examined whether electrodermal activity (EDA), as index of arousal, relates to food neophobia outside the lab when exposed to a single piece of food.MethodsThe EDA of 153 participants was analyzed as part of a larger experiment conducted at a festival. Participants completed the 10-item Food Neophobia Scale. Subsequently, they saw three lids covering three foods: a hotdog labeled as “meat”, a hotdog labeled as “100% plant-based”, and tofu labeled as “100% plant-based”. Participants lifted the lids consecutively and the area-under-the-curve (AUC) of the skin conductance response (SCR) was captured between 20 s before and 20 s after each food reveal.ResultsWe found a significant positive correlation between food neophobia and AUC of SCR during presentation of the first and second hotdog and a trend for tofu. These correlations remained significant even when only including the SCR data prior to the food reveal (i.e., an anticipatory response).DiscussionThe association between food neophobia and EDA indicates that food neophobic individuals are more aroused upon the presentation of food. We show for the first time that the anticipation of being presented with food already increased arousal for food neophobic individuals. These findings also indicate that EDA can be meaningfully determined using wearables outside the lab, in a relatively uncontrolled setting for single-trial analysis

A method to assess the clinical significance of unclassified variants in the BRCA1 and BRCA2 genes based on cancer family history

Introduction Unclassified variants (UVs) in the BRCA1/BRCA2 genes are a frequent problem in counseling breast cancer and/or ovarian cancer families. Information about cancer family history is usually available, but has rarely been used to evaluate UVs. The aim of the present study was to identify which is the best combination of clinical parameters that can predict whether a UV is deleterious, to be used for the classification of UVs. Methods We developed logistic regression models with the best combination of clinical features that distinguished a positive control of BRCA pathogenic variants (115 families) from a negative control population of BRCA variants initially classified as UVs and later considered neutral (38 families). Results The models included a combination of BRCAPRO scores, Myriad scores, number of ovarian cancers in the family, the age at diagnosis, and the number of persons with ovarian tumors and/ or breast tumors. The areas under the receiver operating characteristic curves were respectively 0.935 and 0.836 for the BRCA1 and BRCA2 models. For each model, the minimum receiver operating characteristic distance (respectively 90% and 78% specificity for BRCA1 and BRCA2) was chosen as the cutoff value to predict which UVs are deleterious from a study population of 12 UVs, present in 59 Dutch families. The p. S1655F, p. R1699W, and p. R1699Q variants in BRCA1 and the p. Y2660D, p. R2784Q, and p. R3052W variants in BRCA2 are classified as deleterious according to our models. The predictions of the p. L246V variant in BRCA1 and of the p. Y42C, p. E462G, p. R2888C, and p. R3052Q variants in BRCA2 are in agreement with published information of them being neutral. The p. R2784W variant in BRCA2 remains uncertain. Conclusions The present study shows that these developed models are useful to classify UVs in clinical genetic practic

Improved Color Mapping Methods for Multiband Nighttime Image Fusion

Previously, we presented two color mapping methods for the application of daytime colors to fused nighttime (e.g., intensified and longwave infrared or thermal (LWIR)) imagery. These mappings not only impart a natural daylight color appearance to multiband nighttime images but also enhance their contrast and the visibility of otherwise obscured details. As a result, it has been shown that these colorizing methods lead to an increased ease of interpretation, better discrimination and identification of materials, faster reaction times and ultimately improved situational awareness. A crucial step in the proposed coloring process is the choice of a suitable color mapping scheme. When both daytime color images and multiband sensor images of the same scene are available, the color mapping can be derived from matching image samples (i.e., by relating color values to sensor output signal intensities in a sample-based approach). When no exact matching reference images are available, the color transformation can be derived from the first-order statistical properties of the reference image and the multiband sensor image. In the current study, we investigated new color fusion schemes that combine the advantages of both methods (i.e., the efficiency and color constancy of the sample-based method with the ability of the statistical method to use the image of a different but somewhat similar scene as a reference image), using the correspondence between multiband sensor values and daytime colors (sample-based method) in a smooth transformation (statistical method). We designed and evaluated three new fusion schemes that focus on (i) a closer match with the daytime luminances; (ii) an improved saliency of hot targets; and (iii) an improved discriminability of materials. We performed both qualitative and quantitative analyses to assess the weak and strong points of all methods

Pooling speed information in complex tasks: Estimation of average speed and detection of nonplanarity

To gain insight into how speeds are combined in structure-from-motion, we compared performance for estimating the mean speed and performance for detecting deviations from planarity. The stimuli showed a center dot surrounded by an annulus of dots. In one (plane) condition, the stimuli simulated a rotating plane. In a two alternative forced choice (2AFC) task, the subject had to choose in which of two stimuli the center dot moved in the plane. In another (cloud) condition, the same dot locations and speeds were used but now assigned to different dots. Such a stimulus resembles a translating and rotating cloud of dots. In this case, the subject had to choose the stimulus in which the center dot moved with the mean speed of the surrounding dots. Performance was measured as a function of deformation/slant. Although location and speeds were the same in both conditions, performance was much poorer in the cloud condition. Subsequent experiments and an ideal observer model point to a plausible explanation: in detecting deviations from planarity, the visual system can focus on the most reliable pieces of information (the slower dots, closest to the test dot). Although performance could benefit by taking more dots into account, performance barely improved with an increase in the number of dots. This may reflect a limited processing capacity of the visual system

The TRICLOBS Dynamic Multi-Band Image Data Set for the Development and Evaluation of Image Fusion Methods.

The fusion and enhancement of multiband nighttime imagery for surveillance and navigation has been the subject of extensive research for over two decades. Despite the ongoing efforts in this area there is still only a small number of static multiband test images available for the development and evaluation of new image fusion and enhancement methods. Moreover, dynamic multiband imagery is also currently lacking. To fill this gap we present the TRICLOBS dynamic multi-band image data set containing sixteen registered visual (0.4-0.7μm), near-infrared (NIR, 0.7-1.0μm) and long-wave infrared (LWIR, 8-14μm) motion sequences. They represent different military and civilian surveillance scenarios registered in three different scenes. Scenes include (military and civilian) people that are stationary, walking or running, or carrying various objects. Vehicles, foliage, and buildings or other man-made structures are also included in the scenes. This data set is primarily intended for the development and evaluation of image fusion, enhancement and color mapping algorithms for short-range surveillance applications. The imagery was collected during several field trials with our newly developed TRICLOBS (TRI-band Color Low-light OBServation) all-day all-weather surveillance system. This system registers a scene in the Visual, NIR and LWIR part of the electromagnetic spectrum using three optically aligned sensors (two digital image intensifiers and an uncooled long-wave infrared microbolometer). The three sensor signals are mapped to three individual RGB color channels, digitized, and stored as uncompressed RGB (false) color frames. The TRICLOBS data set enables the development and evaluation of (both static and dynamic) image fusion, enhancement and color mapping algorithms. To allow the development of realistic color remapping procedures, the data set also contains color photographs of each of the three scenes. The color statistics derived from these photographs can be used to define color mappings that give the multi-band imagery a realistic color appearance

Structure from motion: A tolerance analysis

We present a tolerance analysis that is applicable to a large group of stimuli used in structure-frommotion tasks. Human performance in structure-from-motion tasks reflects the fact that the visual system deals with projections of a 3-D world on the retina. A tolerance analysis reveals the relationship between the projections and the 3-D world. Any realistic model of the visual system should incorporate a tolerance analysis as a complete description of the stimulus. By way of example we apply the tolerance analysis to the stimuli used in two widely known experiments in which different properties of structure were tested—that is, perceived nonrigidity (Norman & Todd, 1993) and ordering in depth (Hildreth, Grzywacz, Adelson, & Inada, 1990). The analysis explains qualitatively the results of these experiments, illustrating that the results are to a large extent due to stimulus limitations rather than to mechanistic properties of the visual system. From our analysis it follows that far more sensitive measurements of the optic information are needed to obtain metric structure than affine structure. This research was supported by the Netherlands Organization for Scientific Research. Correspondence should be addressed to M. A. Hogervorst

Toward physiological indices of emotional state driving future ebook interactivity

Ebooks of the future may respond to the emotional experience of the reader. (Neuro-) physiological measures could capture a reader’s emotional state and use this to enhance the reading experience by adding matching sounds or to change the storyline therewith creating a hybrid art form in between literature and gaming. We describe the theoretical foundation of the emotional and creative brain and review the neurophysiological indices that can be used to drive future ebook interactivity in a real life situation. As a case study, we report the neurophysiological measurements of a bestselling author during nine days of writing which can potentially be used later to compare them to those of the readers. In designated calibration blocks, the artist wrote emotional paragraphs for emotional (IAPS) pictures. Analyses showed that we can reliably distinguish writing blocks from resting but we found no reliable differences related to the emotional content of the writing. The study shows that measurements of EEG, heart rate (variability), skin conductance, facial expression and subjective ratings can be done over several hours a day and for several days in a row. In follow-up phases, we will measure 300 readers with a similar setu