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Understanding the structure of cognitive noise
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Zhu , Jian-Qiao , León-Villagrá, Pablo, Chater, Nick and Sanborn, Adam N. (2022) Understanding the structure of cognitive noise. PLoS Computational Biology, 18 (8). e1010312. doi:10.1371/journal.pcbi.1010312
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Official URL: https://doi.org/10.1371/journal.pcbi.1010312
Abstract
Human cognition is fundamentally noisy. While routinely regarded as a nuisance in experimental investigation, the few studies investigating properties of cognitive noise have found surprising structure. A first line of research has shown that inter-response-time distributions are heavy-tailed. That is, response times between subsequent trials usually change only a small amount, but with occasional large changes. A second, separate, line of research has found that participants’ estimates and response times both exhibit long-range autocorrelations (i.e., 1/f noise). Thus, each judgment and response time not only depends on its immediate predecessor but also on many previous responses. These two lines of research use different tasks and have distinct theoretical explanations: models that account for heavy-tailed response times do not predict 1/f autocorrelations and vice versa. Here, we find that 1/f noise and heavy-tailed response distributions co-occur in both types of tasks. We also show that a statistical sampling algorithm, developed to deal with patchy environments, generates both heavy-tailed distributions and 1/f noise, suggesting that cognitive noise may be a functional adaptation to dealing with a complex world.
| Item Type: | Journal Article | ||||||
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| Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > QP Physiology |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Psychology Faculty of Social Sciences > Warwick Business School |
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| Library of Congress Subject Headings (LCSH): | Cognition, Decision making, Human behavior | ||||||
| Journal or Publication Title: | PLoS Computational Biology | ||||||
| Publisher: | Public Library of Science | ||||||
| ISSN: | 1553-7358 | ||||||
| Official Date: | 17 August 2022 | ||||||
| Dates: |
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| Volume: | 18 | ||||||
| Number: | 8 | ||||||
| Article Number: | e1010312 | ||||||
| DOI: | 10.1371/journal.pcbi.1010312 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access |
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