Emotion drives attention by automatically capturing it for fear-relevant stimuli, such as snakes or spiders, more quickly than fear-irrelevant ones. Participants searching for fear-relevant targets in fear-irrelevant arrays found them faster, and this was unaffected by target location or number of distractors, suggesting parallel search for fear-relevant targets and serial search for fear-irrelevant ones. Fear-specific individuals showed faster search for their feared objects but not for non-feared ones. Evolutionary relevant threats automatically capture attention, facilitated by emotional provocation. Mammals evolved in unpredictable environments, requiring efficient detection of resources and dangers. Active attention is goal-driven, while passive attention is stimulus-driven. Threat detection relies on passive attention, as seen in James's (1890) description of automatic attention to threats like "wild animals" and "blood." Experimental data support a contrast between voluntary and automatic attention processes. Perceptual processes automatically scan and analyze the environment, distinguishing preattentive (fast, automatic) and postattentive (slow, deliberate) attention. Peripheral threats may interrupt processing, calling for postattentive processing. Evolutionary threats are "tagged" for automatic attention, similar to sudden visual onsets. Peripheral stimuli interact with goal-driven processes, with attention control settings tuning stimulus likelihood based on relevance. Evolutionary threats, like snakes, spiders, and angry faces, are automatically attention-grabbing. Hansen and Hansen (1988) found faster detection of angry faces in crowds, suggesting a "pop-out" effect. However, this was due to unique physical features, not threat. Öhman et al. (2001) confirmed faster detection of angry faces, with psychophysiological responses even when masked. Fear-relevant stimuli, like snakes and spiders, automatically activate fear and capture attention. Öhman's (1993) model suggests automatic evaluation of threat significance. Fear-relevant stimuli are processed automatically, even when masked. Experiments showed faster detection of fear-relevant targets in fear-irrelevant arrays, independent of distractor number. In Experiment 1, participants were faster detecting fear-relevant (snakes/spiders) than fear-irrelevant (flowers/mushrooms) targets. Fear-relevant targets were detected faster in peripheral positions, suggesting automatic detection. Fear-irrelevant targets were detected faster in central positions, requiring more attention. In Experiment 2, fear-relevant targets were detected faster in smaller matrices, with no significant increase in latency with more distractors. Fear-irrelevant targets showed increased latency with more distractors, suggesting serial search. Fear-relevant targets were processed in parallel, while fear-irrelevant targets required serial search. In Experiment 3, fearful participants detected their feared targets faster than non-fearful ones. Fear-relevant targets were detected faster in small matrices, with no significant increase in latency with more distractors. Fear-irrelevantEmotion drives attention by automatically capturing it for fear-relevant stimuli, such as snakes or spiders, more quickly than fear-irrelevant ones. Participants searching for fear-relevant targets in fear-irrelevant arrays found them faster, and this was unaffected by target location or number of distractors, suggesting parallel search for fear-relevant targets and serial search for fear-irrelevant ones. Fear-specific individuals showed faster search for their feared objects but not for non-feared ones. Evolutionary relevant threats automatically capture attention, facilitated by emotional provocation. Mammals evolved in unpredictable environments, requiring efficient detection of resources and dangers. Active attention is goal-driven, while passive attention is stimulus-driven. Threat detection relies on passive attention, as seen in James's (1890) description of automatic attention to threats like "wild animals" and "blood." Experimental data support a contrast between voluntary and automatic attention processes. Perceptual processes automatically scan and analyze the environment, distinguishing preattentive (fast, automatic) and postattentive (slow, deliberate) attention. Peripheral threats may interrupt processing, calling for postattentive processing. Evolutionary threats are "tagged" for automatic attention, similar to sudden visual onsets. Peripheral stimuli interact with goal-driven processes, with attention control settings tuning stimulus likelihood based on relevance. Evolutionary threats, like snakes, spiders, and angry faces, are automatically attention-grabbing. Hansen and Hansen (1988) found faster detection of angry faces in crowds, suggesting a "pop-out" effect. However, this was due to unique physical features, not threat. Öhman et al. (2001) confirmed faster detection of angry faces, with psychophysiological responses even when masked. Fear-relevant stimuli, like snakes and spiders, automatically activate fear and capture attention. Öhman's (1993) model suggests automatic evaluation of threat significance. Fear-relevant stimuli are processed automatically, even when masked. Experiments showed faster detection of fear-relevant targets in fear-irrelevant arrays, independent of distractor number. In Experiment 1, participants were faster detecting fear-relevant (snakes/spiders) than fear-irrelevant (flowers/mushrooms) targets. Fear-relevant targets were detected faster in peripheral positions, suggesting automatic detection. Fear-irrelevant targets were detected faster in central positions, requiring more attention. In Experiment 2, fear-relevant targets were detected faster in smaller matrices, with no significant increase in latency with more distractors. Fear-irrelevant targets showed increased latency with more distractors, suggesting serial search. Fear-relevant targets were processed in parallel, while fear-irrelevant targets required serial search. In Experiment 3, fearful participants detected their feared targets faster than non-fearful ones. Fear-relevant targets were detected faster in small matrices, with no significant increase in latency with more distractors. Fear-irrelevant