Brain Responses to Emotional Faces in Natural Settings: A Wireless Mobile EEG Recording Study

open access articleThe detection of a human face in a visual field and correct reading of emotional expression of faces are important elements in everyday social interactions, decision making and emotional responses. Although brain correlates of face processing have been established in previous fMRI and electroencephalography (EEG)/MEG studies, little is known about how the brain representation of faces and emotional expressions of faces in freely moving humans. The present study aimed to detect brain electrical potentials that occur during the viewing of human faces in natural settings. 64-channel wireless EEG and eye-tracking data were recorded in 19 participants while they moved in a mock art gallery and stopped at times to evaluate pictures hung on the walls. Positive, negative and neutral valence pictures of objects and human faces were displayed. The time instants in which pictures first occurred in the visual field were identified in eye-tracking data and used to reconstruct the triggers in continuous EEG data after synchronizing the time axes of the EEG and eye-tracking device. EEG data showed a clear face-related event-related potential (ERP) in the latency interval ranging from 165 to 210 ms (N170); this component was not seen whilst participants were viewing non-living objects. The face ERP component was stronger during viewing disgusted compared to neutral faces. Source dipole analysis revealed an equivalent current dipole in the right fusiform gyrus (BA37) accounting for N170 potential. Our study demonstrates for the first time the possibility of recording brain responses to human faces and emotional expressions in natural settings. This finding opens new possibilities for clinical, developmental, social, forensic, or marketing research in which information about face processing is of importance

Tracking Economic Value of Products in Natural Settings: A Wireless EEG Study

Economic decision making refers to the process of individuals translating their preference into subjective value (SV). Little is known about the dynamics of the neural processes that underpin this form of value-based decision making and no studies have investigated these processes outside of controlled laboratory settings. The current study investigated the spatio-temporal dynamics that accompany economic valuation of products using mobile electroencephalography (EEG) and eye tracking techniques. Participants viewed and rated images of household products in a gallery setting while EEG and eye tracking data were collected wirelessly. A Becker-DeGroot-Marschak (BDM) auction task was subsequently used to quantify the individual’s willingness to pay (WTP) for each product. WTP was used to classify products into low, low medium, high medium and high economic value conditions. Eye movement related potentials (EMRP) were examined, and independent component analysis (ICA) was used to separate sources of activity from grand averaged EEG data. Four independent components (ICs) of EMRPs were modulated by WTP (i.e., SV) in the latency range of 150–250 ms. Of the four value-sensitive ICs, one IC displayed enhanced amplitude for all value conditions excluding low value, and another IC presented enhanced amplitude for low value products only. The remaining two value-sensitive ICs resolved inter-mediate levels of SV. Our study quantified, for the first time, the neural processes involved in economic value based decisions in a natural setting. Results suggest that multiple spatio-temporal brain activation patterns mediate the attention and aversion of products which could reflect an early valuation system. The EMRP parietal P200 component could reflect an attention allocation mechanism that separates the lowest-value products (IC7) from products of all other value (IC4), suggesting that low-value items are categorized early on as being aversive. While none of the ICs showed linear amplitude changes that parallel SV’s of products, results suggest that a combination of multiple components may sub-serve a fine-grained resolution of the SV of products