Unseen food images capture the attention of hungry viewers: Evidence from event-related potentials

Effect of texture preference on food texture perception: Exploring the role of matching food texture and preference

This study aimed to investigate the influence of smooth texture preference on smoothness perception. An online questionnaire (Study 1, n = 464) and a sensory evaluation test (Study 2, n = 65) were administered to Japanese elderly participants (65-74 years), with common Japanese confectionery (Daifuku) as test foods. Through the online questionnaire, four distinct texture preference groups were formed based on the factors of preference for smoothness and firmness of the inner bean paste layer. Analysis of the food preference scale for imbalanced diet (FPSID) revealed that smooth-texture likers were more likely to be picky eaters than firm-texture likers. Furthermore, high (HiSm) and low smoothness preference groups (LoSm) were selected for the food sensory evaluation test to compare perceived textures (smoothness and firmness). Only the HiSm group exhibited a positive association between perceived smoothness and overall texture liking, perceiving smoothness significantly more intense than the LoSm group in situations where overall texture liking was high. This finding indicates that smooth texture preference does not act independently but rather interacts with food texture matching to affect perception. Our findings suggest that when food texture aligns with individuals' preferences, it elicits hedonic emotions and dynamically enhances food texture perception. This preference-involved perceptual process may contribute to the development of more explicit texture preferences.

It does not need two: Assessing physiological linkage from videos across the valence dimension

The phenomenon of physiological linkage describes similar fluctuations of two individuals' physiology, for example, the cardiac inter-beat interval (IBI). Physiological linkage is a well-documented occurrence in research settings of interacting dyads but the literature on non-interacting dyads, that is, someone watching a video of another person, is sparse. The current study investigated whether physiological linkage, based on IBI, occurs from watching videos where strangers report about personal (neutral, positive, negative non-traumatic, and negative traumatic) experiences. Videos were produced with six individuals and then presented to observers (N = 26). Time-frequency-domain cross-wavelet analyses supplemented by threshold-free cluster enhancement (TFCE; to account for multiple testing) showed significant physiological linkage between the IBI of observers and persons in the videos for 16 out of the 21 tested videos. Although significant physiological linkage also emerged for neutral videos and positive, negative valence videos led to such associations more reliably. This study shows that physiological linkage can be investigated in highly controlled conditions based on video stimuli paving the path for experimental manipulation in future research. Furthermore, due to the provision of information on time and frequency, the use of cross-wavelet analysis is encouraged to learn more about factors modulating physiological linkage. The current study presents the next step toward identifying psychophysiological causal and modulating factors of physiological linkage.

Neuroscientific Evidence for Processing Without Awareness

The extent to which we are affected by perceptual input of which we are unaware is widely debated. By measuring neural responses to sensory stimulation, neuroscientific data could complement behavioral results with valuable evidence. Here we review neuroscientific findings of processing of high-level information, as well as interactions with attention and memory. Although the results are mixed, we find initial support for processing object categories and words, possibly to the semantic level, as well as emotional expressions. Robust neural evidence for face individuation and integration of sentences or scenes is lacking. Attention affects the processing of stimuli that are not consciously perceived, and such stimuli may exogenously but not endogenously capture attention when relevant, and be maintained in memory over time. Sources of inconsistency in the literature include variability in control for awareness as well as individual differences, calling for future studies that adopt stricter measures of awareness and probe multiple processes within subjects.

A systematic and meta-analytic review on the neural correlates of viewing high- and low-calorie foods among normal-weight adults

In the context of current-day online shopping, people select foods based on pictures and using their visual systems. Although there are some reviews of previous neuroimaging studies on appetitive behaviors, the findings on neural activation in response to pictures of high- and low-calorie foods seem inconsistent. This study aims to systematically review, integrate, and meta-analyze neuroimaging evidence of viewing high- and low-calorie foods. There were 25 samples from 24 studies, totalizing 489 normal-weight participants (311 female, 160 male, and 18 of unknown sex). We conducted a systematic review and Activation Likelihood Estimation (ALE) meta-analysis on viewing high-calorie foods (versus non-foods), low-calorie foods (versus non-foods), and high- versus low-calorie foods. In systematic review, several brain regions were shown to be activated when viewing high- or low-calorie foods (versus non-foods) and viewing high- versus low-calorie foods, including the prefrontal cortex, orbitofrontal cortex, amygdala, insula, ventral striatum, hippocampus, superior parietal lobe, and fusiform gyrus. However, the ALE meta-analysis showed that the left orbitofrontal cortex, left amygdala, insula, superior parietal lobe, and fusiform gyrus were activated when viewing high-calorie foods (versus non-foods); the left fusiform gyrus was activated when viewing low-calorie foods (versus non-foods); and no cluster was activated when viewing high- versus low-calorie foods. Our research suggests an appetitive brain network that includes visual perception and attentional processing, sensory input integration, subjective reward value encoding, decision-making, and top-down cognitive control. Future studies should control for the effects of methodological and physiological variables when examining the neural correlates of viewing high- and low-calorie foods.