Monitoring selectively directed auditory attention in groups can be helpful in a range of contexts, such as in education. In real-world settings, selectively directed attention cannot be monitored by relating physiological signals to known event markers. Determining the similarity of physiological responses across individuals in a group (i.e., physiological synchrony - PS) may provide a solution to this problem, as it has been shown reflective of shared attentional engagement toward audiovisual stimuli. This study was aimed at examining whether PS in autonomic and neural measures are suitable markers to recover selectively directed attentional focus and moments of emotional or task-related relevance in a composite auditory stimulus. Electroencephalography (EEG), electrodermal activity (EDA) and cardiac inter-beat interval (IBI) were monitored from participants who heard a composite auditory stimulus, consisting of a narrative audiobook, interspersed with short stimuli. One group of the participants (n = 13) was instructed to attend to the narrative, and the other group (n = 13) was instructed to attend to the short stimuli, that were tones that attending participants needed to keep track of, emotional sounds and a stress test attending participants needed to perform. EEG and EDA signals of participants were more strongly synchronized with those of participants in the same attentional condition than with those of participants in the other attentional condition. No such effect was found in IBI. For a single individual, PS in EEG allowed attribution to the correct attentional group in 85% of the cases, for EDA this was 81% and for IBI accuracy was below chance level. Further analyzing EEG, PS was higher during relevant stimulus presentation than over the entire audiobook. PS across stimulus-attending participants was higher than across book-attending participants during these short stimuli. It is concluded that PS in both autonomic and neural measures can be suitable to recover selectively directed attention, as indicated by the high classification accuracy for EEG and EDA. The results of this study also indicate that PS may be suited for the detection of moments of emotional or task-related relevance, as PS in EEG was higher during relevant stimulus presentation than over the entire experiment. Future research should investigate whether PS in autonomic measures could also be suited for detection of relevant events.

Food-evoked emotions are essential for consumers’ food choice prediction and market success. These food-evoked emotions are predominantly measured by explicit self-reports. Yet in certain situations such as social desirability, explicit measures might not reflect one’s true emotional experience. The additional use of implicit measures can be beneficial. The present study investigated whether social pressure truly changes food experience by means of explicit and implicit measures of food liking. Explicit ratings were EmojiGrid valence and arousal ratings in response to familiar and unfamiliar food images and soups. Implicit measures consisted of frontal alpha asymmetry during pre-selected scenes of a movie about Japanese soy sauce as well as sip size of the soup. Explicit and implicit measures were compared to assess the effect of social pressure on Japanese and Dutch food liking. No differences between the social pressure (n = 19) and control group (n = 23) emerged in any of the measures. Explicit ratings and the implicit measure sip size, but not frontal alpha asymmetry during watching the movie, showed differences between participants with high and low food neophobia. The insensitivity of frontal alpha asymmetry to food neophobia groups could be explained by the movie scenes showing rather familiar foods. BMI grouping similarly showed no effect on frontal alpha asymmetry during watching the movie, but also explicit measures were unaffected. It was concluded that the social pressure intervention itself was not effective in inducing increased liking of Japanese food, since there was no increase in neither reported liking nor ‘true’ liking. Additional ways to induce social pressure, e.g., observation during rating, are advisable if the study was repeated. Furthermore, the use of stronger stimuli to induce approach or avoidance motivation as measured by frontal alpha asymmetry, is recommended. It cannot be concluded whether social pressure truly affects food experience.

Meditation is a contemplative practice that is believed to entail attentional and emotional regulation. One of the biggest challenges in developing personalized, accessible healthcare options with meditation is finding understandable features that signify whether someone is meditating. Specifically, there is no consensus on a feature resulting from the electroencephalogram (EEG) in the current body of literature on meditation. In this thesis, I propose a dynamic systems analysis on EEG data to obtain a dynamic feature capable of distinguishing meditation from an eyes-closed resting baseline. I gathered the EEG data at TNO (Dutch Organisation for Applied Scientific Research) from twenty-two participants during a sixteen-minute loving-kindness meditation and two two-minute baselines. The proposed methodology characterizes temporal and spatial characteristics of the EEG simultaneously by approximating the EEG dynamics with a linear model on short time windows. I assess changes among three features: the frequency and magnitude of the oscillatory dynamics and the corresponding active electrodes. The analysis can identify changes in EEG dynamics for each individual. Across all participants, regions associated with vision and language processing were active throughout the experiment. Notably, attention-related regions were more involved during meditation than rest. Moreover, the results show a shift in active regions throughout the meditation and the baselines for several participants. Moreover, the thesis investigates the sensitivity of the analytical approach to changes in the electrode subset used for the analysis. For each participant, I constructed a subset of electrodes that were most involved in the changing EEG dynamics. The personalized subset was most sensitive to changes between meditation and rest, compared to other subsets based on commercial wearable EEG headsets. Finally, I compare the findings of the dynamic systems approach to a conventional analytical approach, and the participants’ emotional ratings inquired in subjective questionnaires. Unfortunately, from the current data, there appears to be no relationship between the proposed features and the conventional measures or the subjective questionnaires.