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When two faces are not better than one: Serial Limited-Capacity Processing with Redundant-Target Faces

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NIAID Data Ecosystem2026-03-12 收录
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Many researchers believe that faces – whether presented alone or as part of an ensemble – are processed automatically. According to this idea: (a) the detection of single- or multiple- faces is resource-free and does not require allocation of attention, and (b) visual search for faces is held in parallel. The current study set to test these hypotheses directly. Participants performed in a redundant target detection task, responding according to the presence or absence of a face (or faces) on the display. We used a rigorous methodology known as the system factorial technology (SFT, Townsend & Nozawa, 1995), which afforded the simultaneous assessment of: (a) architecture (serial vs. parallel), (b) stopping rule (exhaustive vs. self-terminating), and (c) processing capacity (limited, unlimited, or supercapacity). SFT analyses on RT means and RT distributions pointed conclusively to a serial self-terminating architecture with limited-capacity. These findings cast serious doubts on the alleged automaticity of faces.

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2020-10-07
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