Visual Mismatch Negativity Reflects Enhanced Response to the Deviant: Evidence From Event-Related Potentials and Electroencephalogram Time-Frequency Analysis

Automatic processing of unattended mean emotion: Evidence from visual mismatch responses

The mean emotion from multiple facial expressions can be extracted rapidly and precisely. However, it remains debated whether mean emotion processing is automatic which can occur under no attention. To address this question, we used a passive oddball paradigm and recorded event-related brain potentials when participants discriminated the changes in the central fixation while a set of four faces was presented in the periphery. The face set consisted of one happy and three angry expressions (mean negative) or one angry and three happy expressions (mean positive), and the mean negative and mean positive face sets were shown with a probability of 20% (deviant) and 80% (standard) respectively in the sequence, or the vice versa. The cluster-based permutation analyses showed that the visual mismatch negativity started early at around 92 ms and was also observed in later time windows when the mean emotion was negative, while a mismatch positivity was observed at around 168- 266 ms when the mean emotion was positive. The results suggest that there might be different mechanisms underlying the processing of mean negative and mean positive emotions. More importantly, the brain can detect the changes in the mean emotion automatically, and ensemble coding for multiple facial expressions can occur in an automatic fashion without attention.

Relative saliency affects attentional capture and suppression of color and face singleton distractors: evidence from event-related potential studies

Prior research has yet to fully elucidate the impact of varying relative saliency between target and distractor on attentional capture and suppression, along with their underlying neural mechanisms, especially when social (e.g. face) and perceptual (e.g. color) information interchangeably serve as singleton targets or distractors, competing for attention in a search array. Here, we employed an additional singleton paradigm to investigate the effects of relative saliency on attentional capture (as assessed by N2pc) and suppression (as assessed by PD) of color or face singleton distractors in a visual search task by recording event-related potentials. We found that face singleton distractors with higher relative saliency induced stronger attentional processing. Furthermore, enhancing the physical salience of colors using a bold color ring could enhance attentional processing toward color singleton distractors. Reducing the physical salience of facial stimuli by blurring weakened attentional processing toward face singleton distractors; however, blurring enhanced attentional processing toward color singleton distractors because of the change in relative saliency. In conclusion, the attentional processes of singleton distractors are affected by their relative saliency to singleton targets, with higher relative saliency of singleton distractors resulting in stronger attentional capture and suppression; faces, however, exhibit some specificity in attentional capture and suppression due to high social saliency.

Intelligence and Visual Mismatch Negativity: Is Pre-Attentive Visual Discrimination Related to General Cognitive Ability?

EEG has been used for decades to identify neurocognitive processes related to intelligence. Evidence is accumulating for associations with neural markers of higher-order cognitive processes (e.g., working memory); however, whether associations are specific to complex processes or also relate to earlier processing stages remains unclear. Addressing these issues has implications for improving our understanding of intelligence and its neural correlates. The MMN is an ERP that is elicited when, within a series of frequent standard stimuli, rare deviant stimuli are presented. As stimuli are typically presented outside the focus of attention, the MMN is suggested to capture automatic pre-attentive discrimination processes. However, the MMN and its relation to intelligence has largely only been studied in the auditory domain, thus preventing conclusions about the involvement of automatic discrimination processes in humans' dominant sensory modality-vision. EEG was recorded from 50 healthy participants during a passive visual oddball task that presented simple sequence violations and deviations within a more complex hidden pattern. Signed area amplitudes and fractional area latencies of the visual MMN were calculated with and without Laplacian transformation. Correlations between visual MMN and intelligence (Raven's Advanced Progressive Matrices) were of negligible to small effect sizes, differed critically between measurement approaches, and Bayes Factors provided anecdotal to substantial evidence for the absence of an association. We discuss differences between the auditory and visual MMN, the implications of different measurement approaches, and offer recommendations for further research in this evolving field.