使用SAM进行协作内存建模
Willa M Mannering1, Suparna Rajaram2, Richard M Shiffrin3
1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA. manneringwilla@gmail.com.
Memory & cognition
|October 25, 2024
概括
协作抑制,即群体回忆比个人少,通过计算模型来解释. 协同记忆的搜索 (SAM) 模型显示了群体回忆线索如何破坏个人记忆检索.
科学领域:
- 认知心理学 认知心理学
- 计算神经科学是一种神经科学.
- 人类的记忆 人类的记忆
背景情况:
- 人类记忆研究主要使用孤立的个体,忽视了群体动态.
- 协作抑制是协作记忆的一个关键现象,在此过程中,团队在回忆任务中表现低于个人.
- 现有的理论缺乏正式的计算建模指导.
研究的目的:
- 开发一个协作自由回忆的计算框架,使用协同记忆的搜索 (SAM) 模型.
- 测试一个缩放的SAM模型是否可以解释协作抑制.
- 为个人和协作记忆提供统一的理论基础.
主要方法:
- 缩放协同记忆 (SAM) 模型的搜索,以模拟多个代理人协作回忆.
- 实施一个机制,使团队召回作为个人SAM模型的检索线索.
- 分析模型输出以确定协作抑制的出现.
主要成果:
- 规模化的SAM模型自然产生协作抑制.
- 该模型的结果支持"检索中断"假设.
- 该框架成功地在SAM中统一了个人和协作记忆现象.
结论:
- 协同记忆的搜索 (SAM) 模型为人类记忆提供了一个统一的计算理论,包括个人和协作回忆.
- 检索中断假设在计算上得到支持,作为协作抑制的解释.
- 这种框架使得关于组大小,共享知识和虚假记忆动态的未来预测成为可能.
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