The study investigated the efficiency of detecting angry versus happy facial expressions in a visual search task. Participants searched displays of schematic faces to determine if all faces were the same or if one was different. Four main findings were observed: (1) Detecting the absence of a discrepant face was slower when faces displayed angry or sad/angry expressions compared to happy ones. (2) Detecting a discrepant face was faster when it displayed an angry rather than a happy expression. (3) These patterns were not apparent when faces were inverted or when only the mouth was presented. (4) Search slopes for angry targets were significantly lower than for happy targets, indicating faster and more efficient detection of angry faces. These results suggest that angry facial expressions are detected quickly and efficiently, though not in the traditional "pop-out" sense. The study also explored the evolutionary advantage of rapid threat detection, supported by neurophysiological evidence showing automatic processing of angry expressions. Previous studies showed that angry faces are detected more efficiently than happy ones, but results were inconsistent. The current study used schematic faces to minimize visual confounds and found that angry faces were detected more efficiently than happy or neutral ones. In Experiment 1, angry faces were detected faster in neutral crowds compared to happy faces. In Experiment 2, with longer presentation times, the same pattern was observed. Experiment 3, using inverted faces, showed no difference in detection between angry and happy faces, suggesting that emotional expression, not low-level features, was critical. Experiment 4 confirmed that emotional expression, not just mouth shape, determined detection efficiency. Finally, Experiment 5 tested whether angry faces were processed automatically, finding that search slopes for angry faces were lower, supporting the idea of automatic detection. Overall, the results suggest that angry facial expressions are detected more efficiently than happy ones, indicating a biological predisposition for threat detection.The study investigated the efficiency of detecting angry versus happy facial expressions in a visual search task. Participants searched displays of schematic faces to determine if all faces were the same or if one was different. Four main findings were observed: (1) Detecting the absence of a discrepant face was slower when faces displayed angry or sad/angry expressions compared to happy ones. (2) Detecting a discrepant face was faster when it displayed an angry rather than a happy expression. (3) These patterns were not apparent when faces were inverted or when only the mouth was presented. (4) Search slopes for angry targets were significantly lower than for happy targets, indicating faster and more efficient detection of angry faces. These results suggest that angry facial expressions are detected quickly and efficiently, though not in the traditional "pop-out" sense. The study also explored the evolutionary advantage of rapid threat detection, supported by neurophysiological evidence showing automatic processing of angry expressions. Previous studies showed that angry faces are detected more efficiently than happy ones, but results were inconsistent. The current study used schematic faces to minimize visual confounds and found that angry faces were detected more efficiently than happy or neutral ones. In Experiment 1, angry faces were detected faster in neutral crowds compared to happy faces. In Experiment 2, with longer presentation times, the same pattern was observed. Experiment 3, using inverted faces, showed no difference in detection between angry and happy faces, suggesting that emotional expression, not low-level features, was critical. Experiment 4 confirmed that emotional expression, not just mouth shape, determined detection efficiency. Finally, Experiment 5 tested whether angry faces were processed automatically, finding that search slopes for angry faces were lower, supporting the idea of automatic detection. Overall, the results suggest that angry facial expressions are detected more efficiently than happy ones, indicating a biological predisposition for threat detection.