解码数字语义的时间动态:早期的枢纽激活和序列处理在空间数字关联中的关键作用
Zhiwei Zhang1, Qingqing Chen1, Chengtao Wang1
1School of Psychology, Guizhou Normal University, Guiyang, China.
Cognition
|July 9, 2025
概括
空间-数值关联 (SNA) 与顺序工作记忆相关,而不仅仅是数量. 枢机数语义在顺序语义之前被处理,挑战了传统的观点.
科学领域:
- 认知神经科学 认知神经科学
- 心理学 心理学 心理学
- 神经科学是一个神经科学.
背景情况:
- 数字认知是人类文化和技术的基础.
- 数字的空间认知和空间-数值关联 (SNAs) 并未完全被理解.
- 了解SNA对于学习和环境相互作用至关重要.
研究的目的:
- 检查SNA中的语义处理机制,重点关注枢纽语义和顺序语义的时间动态.
- 调查SNAs的起源,挑战他们仅仅来自空间量的观点.
- 探索枢机和顺序语义处理之间的时间分离.
主要方法:
- 双重选择的去/不去模式.
- 事件相关潜力 (ERP) 技术.
- 多变量模式分析 (MVPA) 用于语义处理的时间分析.
主要成果:
- 在一个实验中观察到响应代码的空间-数值关联 (SNARC) 效应,而顺序位置效应是一致的.
- MVPA揭示,核心语义比顺序语义 (180-200 ms) 处理得更早 (112 ms).
- SNAs与顺序语义有更强烈的关联,这表明它起源于顺序工作记忆.
结论:
- SNA可能主要来源于工作记忆中的顺序信息,而不是数值量的空间分布.
- 枢机和顺序语义处理表现出时间分离.
- 这项研究为数字认知和SNAs的复杂性和多样性提供了新的视角.
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