Institute for Social Neuroscience, Melbourne, VIC, Australia; School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia.
School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia.
Neurosci Biobehav Rev. 2022 Aug;139:104753. doi: 10.1016/j.neubiorev.2022.104753. Epub 2022 Jun 27.
Subitizing is the fast and accurate enumeration of small sets. Whether attention is necessary for subitizing remains controversial considering (1) subitizing is claimed to be "pre-attentive", and (2) existing experimental methods and results are inconsistent. To determine whether manipulations to attention demonstratively affect subitizing, the current study comprises a systematic review and meta-analysis. Results from fourteen studies (22 experiments, 35 comparisons) suggest that changes to attentional demands interferes with enumeration of small sets; leading to slower response times, lower accuracy, and poorer Weber acuity (p < .010; p < .001; p < .001; respectively)-notwithstanding a potential publication bias. A unifying framework is proposed to explain the role of attention in visual enumeration, with progressively greater attentional involvement from estimation to subitizing to counting. Our findings suggest attention is integral for subitizing and highlights the need to emphasise attentional mechanisms into neurocognitive models of numerosity processing. We also discuss the possible role of attention in numerical processing difficulties (e.g., dyscalculia).
心算就是快速准确地对小集合进行计数。考虑到以下两点,心算是否需要注意力仍然存在争议:(1)心算被认为是“非注意的”;(2)现有的实验方法和结果并不一致。为了确定对注意力的操纵是否能明显影响心算,本研究进行了系统综述和荟萃分析。来自 14 项研究(22 个实验,35 个对比)的结果表明,注意力需求的变化会干扰小集合的计数;导致反应时间变慢、准确性降低、韦伯敏锐度变差(p<0.010;p<0.001;p<0.001;分别)-尽管存在潜在的发表偏倚。提出了一个统一的框架来解释注意力在视觉计数中的作用,从估计到心算再到计数,注意力的参与程度逐渐增加。我们的研究结果表明,注意力对于心算至关重要,并强调了需要将注意力机制纳入数量处理的神经认知模型中。我们还讨论了注意力在数字处理困难(例如,计算障碍)中的可能作用。