Influences of audio-visual environments on feelings of deliciousness during having sweet foods: an electroencephalogram frequency analysis study

Relationships between feeding behaviors and emotions: an electroencephalogram (EEG) frequency analysis study

Feeding behaviors may be easily affected by emotions, both being based on brain activity; however, the relationships between them have not been explicitly defined. In this study, we investigated how emotional environments modulate subjective feelings, brain activity, and feeding behaviors. Electroencephalogram (EEG) recordings were obtained from healthy participants in conditions of virtual comfortable space (CS) and uncomfortable space (UCS) while eating chocolate, and the times required for eating it were measured. We found that the more participants tended to feel comfortable under the CS, the more it took time to eat in the UCS. However, the EEG emergence patterns in the two virtual spaces varied across the individuals. Upon focusing on the theta and low-beta bands, the strength of the mental condition and eating times were found to be guided by these frequency bands. The results determined that the theta and low-beta bands are likely important and relevant waves for feeding behaviors under emotional circumstances, following alterations in mental conditions.

Enhancement of electroencephalogram activity in the theta-band range during unmatched olfactory-taste stimulation

The aim of this study was to investigate how odor stimulation affects taste perception. Electroencephalogram (EEG) signals were measured from the frontal region of the head in normal, healthy subjects, and frequency analyses were performed. Each odor stimulation was delivered while the subject was tasting chocolate, using chocolate paste as the odorant for 'matched odor stimulation,' and garlic paste for 'unmatched odor stimulation.' Differences in EEG signals appeared between the matched and unmatched arms of the study. Comparison of the frequencies of EEGs captured under the condition of unmatched odor stimulation with those captured under the condition of matched odor stimulation showed that the occupancy rate of the theta-frequency band under the condition of unmatched odor stimulation was higher than that under the condition of matched odor stimulation. Interestingly, a negative correlation existed between the occupancy rate of the theta-frequency band and the subjective feeling of chocolate sweetness. The present findings suggest that when humans receive odors that do not match with the foods being consumed, subjective feelings are disturbed and theta-band brain activity is increased while the unmatched information is cross-checked.

Methods for Evaluating Emotions Evoked by Food Experiences: A Literature Review

Besides sensory characteristics of food, food-evoked emotion is a crucial factor in predicting consumer's food preference and therefore in developing new products. Many measures have been developed to assess food-evoked emotions. The aim of this literature review is (i) to give an exhaustive overview of measures used in current research and (ii) to categorize these methods along measurement level (physiological, behavioral, and cognitive) and emotional processing level (unconscious sensory, perceptual/early cognitive, and conscious/decision making) level. This 3 × 3 categorization may help researchers to compile a set of complementary measures (“toolbox”) for their studies. We included 101 peer-reviewed articles that evaluate consumer's emotions and were published between 1997 and 2016, providing us with 59 different measures. More than 60% of these measures are based on self-reported, subjective ratings and questionnaires (cognitive measurement level) and assess the conscious/decision-making level of emotional processing. This multitude of measures and their overrepresentation in a single category hinders the comparison of results across studies and building a complete multi-faceted picture of food-evoked emotions. We recommend (1) to use widely applied, validated measures only, (2) to refrain from using (highly correlated) measures from the same category but use measures from different categories instead, preferably covering all three emotional processing levels, and (3) to acquire and share simultaneously collected physiological, behavioral, and cognitive datasets to improve the predictive power of food choice and other models.