在小数量和大数量处理之间有明显的序列依赖
Yue Huang1,2,3, Haokun Li1,2,3,4, Shiming Qiu1,2,3
1School of Psychology, Central China Normal University (CCNU), Wuhan, 430079, China.
Psychological research
|December 31, 2024
概括
在数量处理中,序列依赖效应 (SDE) 在分类和估计之间有所不同. 分类显示不对称的SDE,而估计显示对称的SDE,这表明数字感知有不同的潜在机制.
科学领域:
- 认知心理学 认知心理学
- 神经科学是一个神经科学.
- 视觉感知 视觉感知 视觉感知
背景情况:
- 序列依赖效应 (SDE) 将当前感知偏向于最近的刺激,可能有助于视觉稳定.
- 目前尚不清楚单一的SDE机制是否支持在分类 (小数) 和估计 (大数) 两方面进行数量处理.
研究的目的:
- 调查分类和估计是否表现出不同的SDE模式和潜在机制.
- 为了确定SDE机制是否在支持不同数量范围的数值处理方面有所不同.
主要方法:
- 在分类和估计范围内对数量刺激的实验操纵.
- 在两个数值范围内分析串行依赖效应 (SDE) 模式 (对称与不对称).
- 在分类和估计之间比较SDE特征,包括处理精度.
主要成果:
- 分类证明了一个不对称的SDE,只有当当前大小小小于前一个时才会发生.
- 估计显示了一个对称的SDE,当当前大小小小于或大于前一个时存在.
- 仅在亚型化中观察到具有加工精度降低的新型SDE.
结论:
- 亚分化和估计依赖于不同的SDE机制,可能是由于不同的感知和后感知过程.
- 这些发现表明,时间歇斯底里解释了subitizing的不对称SDE,而估计涉及感知和后感知因素.
- 数字处理中的连续性和稳定性可以分离,突出显示SDE在动态感知中的多面性质.
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