The influence of selective attention to specific emotions on the processing of faces as revealed by event-related brain potentials

You're Beautiful When You Smile: Event-Related Brain Potential (ERP) Evidence of Early Opposite-Gender Bias in Happy Faces

Studies of social cognition have shown gender differences regarding human face processing. One interesting finding is the enhanced processing of opposite-gender faces at different time stages, as revealed by event-related brain potentials. Crucially, from an evolutionary perspective, such a bias might interact with the emotional expression of the face. To investigate this, 100 participants (50 female, 50 male) completed an expression-detection task while their EEG was recorded. In three blocks, fearful, happy and neutral faces (female and male) were randomly presented, with participants instructed to respond to only one predefined target expression level in each block. Using linear mixed models, we observed both faster reaction times as well as larger P1 and late positive potential (LPP) amplitudes for women compared to men, supporting a generally greater female interest in faces. Highly interestingly, the analysis revealed an opposite-gender bias at P1 for happy target faces. This suggests that participants' attentional templates may include more opposite-gender facial features when selectively attending to happy faces. While N170 was influenced by neither the face nor the participant gender, LPP was modulated by the face gender and specific combinations of the target status, face gender and expression, which is interpreted in the context of gender-emotion stereotypes. Future research should further investigate this expression and attention dependency of early opposite-gender biases.

Evaluating the effectiveness of artifact correction and rejection in event-related potential research

Eyeblinks and other large artifacts can create two major problems in event-related potential (ERP) research, namely confounds and increased noise. Here, we developed a method for assessing the effectiveness of artifact correction and rejection methods in minimizing these two problems. We then used this method to assess a common artifact minimization approach, in which independent component analysis (ICA) is used to correct ocular artifacts, and artifact rejection is used to reject trials with extreme values resulting from other sources (e.g., movement artifacts). This approach was applied to data from five common ERP components (P3b, N400, N170, mismatch negativity, and error-related negativity). Four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency) were examined for each component. We found that eyeblinks differed systematically across experimental conditions for several of the components. We also found that artifact correction was reasonably effective at minimizing these confounds, although it did not usually eliminate them completely. In addition, we found that the rejection of trials with extreme voltage values was effective at reducing noise, with the benefits of eliminating these trials outweighing the reduced number of trials available for averaging. For researchers who are analyzing similar ERP components and participant populations, this combination of artifact correction and rejection approaches should minimize artifact-related confounds and lead to improved data quality. Researchers who are analyzing other components or participant populations can use the method developed in this study to determine which artifact minimization approaches are effective in their data.

Evaluating the effectiveness of artifact correction and rejection in event-related potential research

Eyeblinks and other large artifacts can create two major problems in event-related potential (ERP) research, namely confounds and increased noise. Here, we developed a method for assessing the effectiveness of artifact correction and rejection methods at minimizing these two problems. We then used this method to assess a common artifact minimization approach, in which independent component analysis (ICA) is used to correct ocular artifacts, and artifact rejection is used to reject trials with extreme values resulting from other sources (e.g., movement artifacts). This approach was applied to data from five common ERP components (P3b, N400, N170, mismatch negativity, and error-related negativity). Four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency) were examined for each component. We found that eyeblinks differed systematically across experimental conditions for several of the components. We also found that artifact correction was reasonably effective at minimizing these confounds, although it did not usually eliminate them completely. In addition, we found that the rejection of trials with extreme voltage values was effective at reducing noise, with the benefits of eliminating these trials outweighing the reduced number of trials available for averaging. For researchers who are analyzing similar ERP components and participant populations, this combination of artifact correction and rejection approaches should minimize artifact-related confounds and lead to improved data quality. Researchers who are analyzing other components or participant populations can use the method developed in this study to determine which artifact minimization approaches are effective in their data.

Mass-univariate analysis of scalp ERPs reveals large effects of gaze fixation location during face processing that only weakly interact with face emotional expression

Decoding others' facial expressions is critical for social functioning. To clarify the neural correlates of expression perception depending on where we look on the face, three combined gaze-contingent ERP experiments were analyzed using robust mass-univariate statistics. Regardless of task, fixation location impacted face processing from 50 to 350 ms, maximally around 120 ms, reflecting retinotopic mapping around C2 and P1 components. Fixation location also impacted majorly the N170-P2 interval while weak effects were seen at the face-sensitive N170 peak. Results question the widespread assumption that faces are processed holistically into an indecomposable perceptual whole around the N170. Rather, face processing is a complex and view-dependent process that continues well beyond the N170. Expression and fixation location interacted weakly during the P1-N170 interval, supporting a role for the mouth and left eye in fearful and happy expression decoding. Expression effects were weakest at the N170 peak but strongest around P2, especially for fear, reflecting task-independent affective processing. Results suggest N170 reflects a transition between processes rather than the maximum of a holistic face processing stage. Focus on this peak should be replaced by data-driven analyses of the epoch using robust statistics to fully unravel the early visual processing of faces and their affective content.

Of ugly gains and happy losses: An event-related potential study of interactions of the intrinsic and acquired valence of emotional pictures

During the last decades, event-related potential research on the processing of intrinsic and acquired valence has made great progress, but the two dimensions rarely varied simultaneously. Only that way, however, can we investigate whether the acquisition of extrinsic valence varies with intrinsic valence and whether intrinsic and acquired valence share the same brain mechanisms. Forty-five participants performed associative learning of gains and losses, using pictures varying on intrinsic valence (positive, negative) and outcome (90 % gain, 50 %/50 %, 90 % loss). 64-channel EEG was recorded. During acquisition, one picture from each valence/outcome combination was repeatedly presented, followed by abstract outcome information (+10 ct, -10 ct) at the predefined probability. In the test phase, participants pressed buttons to earn the real gains and avoid the real losses associated with the pictures. Here, effects of outcome and/or its congruence with intrinsic valence were observed for RT, error rate, frontal theta power, posterior P2, P300, and LPP. Moreover, outcome systematically affected post-test valence and arousal ratings. During acquisition, a contingency effect (90 % > 50 %) on amplitude of a frontal negative slow wave accompanied the progress of learning, independently of outcome, valence, and congruence. The relative absence of outcome effects during acquisition suggests "cold" semantic rather than genuinely affective processing of gains and losses. However, with real gains and losses in the test phase, "hot" affective processing took place, and outcome and its congruence with intrinsic valence influenced behavior and neural processing. Finally, the data suggest both shared and distinct brain mechanisms of intrinsic and acquired valence.