Background. Facial expression recognition depends on how visual information is sampled across the face over time. Static area-of-interest (AOI) measures describe where observers look but provide limited information about the sequential organization of gaze. This study examined how gaze is organized during facial expression recognition and whether this organization remains comparable across two conditions differing in the temporal order of contextual and facial stimuli. Methods. Eye-tracking data were collected from 27 participants performing a facial expression recognition task. Fixations on faces were mapped onto three AOIs: Upper Facial Zone (UFZ), Central Facial Zone (CFZ), and Lower Facial Zone (LFZ). Gaze organization was examined using first- and second-order Markov models, entropy estimates, spatial repositioning measures, and a gaze stability index. Results. Gaze transitions showed a structured, non-random organization centered on the CFZ. In the first-order Markov model, transitions from both the UFZ and LFZ were directed primarily toward the CFZ, and within-zone transitions were also most likely in the CFZ. Entropy was lower for the CFZ than for the upper and lower regions, indicating lower transition uncertainty in the central region. The second-order model showed an influence of recent fixation history while preserving the predominance of the CFZ. Spatial repositioning varied across facial zones in both conditions. However, mixed-effects analyses showed no effect of condition on gaze stability. Conclusions. Facial expression recognition was associated with a pattern of exploration in which the central facial region emerged as the most likely fixation destination, with limited evidence of condition-related differences in gaze organization.

Emotional recognition relies on the integration of multiple affective cues. In everyday contexts, however, facial expressions, vocal prosody, and semantic content may convey incongruent emotional information, generating emotional conflict and increasing cognitive demands. The present study examined how multimodal emotional conflict affects emotion recognition during video viewing, focusing on short videos in which a single actor simultaneously conveyed incongruent emotional cues across facial, vocal, and semantic channels. Forty-seven undergraduate students completed a gaze-based response task in which, after each short video, they provided a single judgment of the overall emotion conveyed by the stimulus. The videos depicted either congruent or incongruent combinations of semantic content, facial expressions, and vocal prosody across six basic emotions and a neutral condition. Data were analyzed using repeated-measures ANOVAs and generalized linear mixed-effects models. Accuracy was consistently higher for congruent than incongruent stimuli across all domains, indicating a robust emotional interference effect. Critically, the magnitude of this effect differed by domain. Semantic content showed the largest performance reduction under incongruence, followed by facial expression and vocal prosody. Mixed-effects models confirmed these effects while accounting for participant- and item-level variability and revealed a significant Congruency × Domain interaction. In a gaze-based response task requiring a single overall emotion judgment, emotional conflict disrupted recognition in a domain-specific manner, with semantic information being particularly vulnerable to multimodal interference.