Adaptive Attentional Regulation to Emotional Faces in Subclinical Depression

Cognitive models of depression posit a core role for attentional biases, though empirical evidence remains inconsistent, likely due to variations in task demands. This study utilized eye-tracking to assess attentional patterns in individuals with depressive symptoms during a goal-directed visual search task, specifically dissociating early orienting and late disengagement. Seventy-seven participants, classified into high (HD) and low (LD) depressive-symptom groups based on PHQ-9 scores, completed a "face-in-the-crowd" (FITC) task. The set size (4, 8, or 12 faces) was varied to examine the role of perceptual load. The task involved searching for a single emotional target among neutral distractors (assessing early orienting) and searching for a single neutral target among emotional distractors (assessing late disengagement). Contrary to the negativity-bias hypothesis, the HD group demonstrated what might be interpreted as adaptive attentional regulation. During early orienting (8-face condition), the HD group showed reduced total dwell time on happy targets, suggesting accelerated identification. An attentional bias index (sad minus happy dwell time) correlated positively with depression severity. During late disengagement (8-face condition), the HD group exhibited shorter target fixation latency specifically with sad distractors, indicating facilitated disengagement from negative information. The corresponding bias index correlated negatively with depression levels. Under explicit goal-directed demands, individuals with high depressive symptoms displayed facilitated processing of happy faces and accelerated disengagement from sad faces, rather than an enhanced negativity bias. This pattern tentatively suggests a possible adaptive attentional regulatory mechanism in early depression, although the findings were limited to the 8-face condition and no significant group differences emerged at set sizes 4 or 12. Replication is required before firm conclusions can be drawn. The result underscores the critical influence of task demands and highlights the value of early identification and targeted intervention.