Category-specific attention for animals reflects ancestral priorities, not expertise

Abstract

Visual attention mechanisms are known to select information to process based on current goals, personal relevance, and lowerlevel features. Here we present evidence that human visual attention also includes a high-level category-specialized system that monitors animals in an ongoing manner. Exposed to alternations between complex natural scenes and duplicates with a single change (a change-detection paradigm), subjects are substantially faster and more accurate at detecting changes in animals relative to changes in all tested categories of inanimate objects, even vehicles, which they have been trained for years to monitor for sudden life-or-death changes in trajectory. This animate monitoring bias could not be accounted for by differences in lower-level visual characteristics, how interesting the target objects were, experience, or expertise, implicating mechanisms that evolved to direct attention differentially to objects by virtue of their membership in ancestrally important categories, regardless of their current utility.animacy ͉ category specificity ͉ domain specificity ͉ evolutionary psychology ͉ visual attention V isual attention is an umbrella term for the set of operations that select some portions of a scene, rather than others, for more extensive processing. These operations evolved because some categories of information in the visual environment were likely to be more important or time-sensitive than others for activities that contributed to an organism's survival or reproduction. The selection criteria that direct visual attention can be categorized by their origin: (i) goal-derived: criteria activated volitionally in response to a transient internally represented goal; (ii) ancestrally derived: criteria so generally useful for a species, generation after generation, that natural selection favored mechanisms that cause them to develop in a species-typical manner; and (iii) expertise-derived: criteria extracted during ontogeny by evolved mechanisms specialized for detecting which perceptual cues predict information that enhances task performance.These three types of criteria may also interact; for example, differential experience or temporary goals could calibrate or elaborate ancestrally derived criteria built into the attentional architecture.The ways in which human attention can be affected by goals and expertise have been extensively investigated. Indeed, humans are zoologically unique in the extent to which we evolved to engage in behavior tailored to achieve situation-specific goals as a regular part of our subsistence and sociality (1, 2). Among our foraging ancestors, improvising solutions in response to the distinctive features of situations would have benefited from the existence of goal-driven voluntary attentional mechanisms. As predicted by such a view, otherwise arbitrary but task-relevant objects command more attention than task-irrelevant ones (3), and expertise in a task domain shifts attention to more tasksignificant objects (4), features (5), and locations (6).In contrast, attentio...

Intuitively detecting what is hidden within a visual mask: Familiar–novel discrimination and threat detection for unidentified stimuli

“…The latter pattern is consistent with Mermillod et al (2010), in that there was something special about living threats: Living threats were more identifiable than living nonthreats, but nonliving threats were not more identifiable than nonliving nonthreats. However, the finding that participants identified more nonliving than living stimuli seems to contrast with the findings of New et al (2007), who found that when living things changed, the changes were detected better in a change-detection paradigm than when nonliving things changed. One contributing factor to the difference in our pattern of identification results might be that identifying a stimulus through noise is different from detecting a change.…”

“…This threat advantage to processing was limited to living (i.e., animate) threats; it was not found with nonliving (i.e., inanimate) threats. This finding may relate to other findings on adaptive cognitive processes, such as evidence that attentional cognitive-processing advantages are associated with animate objects (i.e., animals) relative to inanimate objects, and that this advantage may reflect "ancestral priorities" (New, Cosmides, & Tooby, 2007). More recently, animacy has been shown to influence memory, such that animate stimuli are remembered better than inanimate stimuli (VanArsdall, Nairne, Pandeirada, & Blunt, in press).…”

Infants' knowledge of their own species

“…plants, artefacts), and thus require more frequent and constant monitoring [7]. The animate monitoring hypothesis proposes that the human attention system evolved to differentially monitor animals/humans versus other objects: animals and humans should recruit more spontaneous attention.…”

“…The animate monitoring hypothesis proposes that the human attention system evolved to differentially monitor animals/humans versus other objects: animals and humans should recruit more spontaneous attention. To test this hypothesis, New et al [7] used a change-detection paradigm, in which adults were exposed to alternations between complex natural scenes and duplicates with a single change. Adults were substantially faster and more accurate at detecting changes in animals and people relative to changes in other familiar objects (e.g.…”

Testing location memory for threatening and nonthreatening stimuli : implications for evolutionary psychological theorizing.

“…The ancestral stimuli hypothesis is that the locations of all ancestral stimuli, whether threatening or not, should be detected faster and remembered better than the locations of modern stimuli. This hypothesis has received some support in the attention literature, with certain studies showing very rapid detection of animals (Cosmides & Tooby, 2013;Drewes, Trommershäuser, & Gegenfurtner, 2011;New, Cosmides, & Tooby, 2007;Lipp et al, 2004).…”