Department of Psychology, University of Warwick, Coventry, United Kingdom.
Warwick Business School, University of Warwick, Coventry, United Kingdom.
PLoS Comput Biol. 2022 Aug 17;18(8):e1010312. doi: 10.1371/journal.pcbi.1010312. eCollection 2022 Aug.
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.
人类认知从根本上说是不稳定的。虽然在实验研究中通常被视为一种干扰，但少数研究认知噪声特性的研究发现了令人惊讶的结构。第一个研究方向表明，反应时分布是重尾的。也就是说，后续试验之间的反应时间通常只变化很小量，但偶尔会有很大的变化。第二个独立的研究方向发现，参与者的估计和反应时间都表现出长程自相关（即 1/f 噪声）。因此，每个判断和反应时间不仅取决于其直接前一个，还取决于许多以前的反应。这两条研究线使用不同的任务，并有不同的理论解释：解释重尾反应时间的模型不预测 1/f 自相关，反之亦然。在这里，我们发现 1/f 噪声和重尾反应分布同时出现在这两种类型的任务中。我们还表明，一种为处理不连续环境而开发的统计抽样算法会产生重尾分布和 1/f 噪声，这表明认知噪声可能是一种适应处理复杂世界的功能适应。
