Cognitive and neural basis of memory for associations and order

关联和顺序记忆的认知和神经基础

• 批准号: RGPIN-2018-04971
• 负责人: Caplan, Jeremy
• 金额: $ 2.91万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=763975
• 关键词: Cognitive; neural; basis; memory; associations

Memory for associations (pairs, such as Notley-Alberta or William-Kate) and memory for order (sequences, such as a phone number) are critical for complex behaviour, from navigation to language to social behaviour. Theories are systematically organized through mathematical models, but these models have also been developed and tested separately for association and order memory. Our aim is to develop a single model that can explain memory behaviour in both standard association and order tasks, but also tasks that combine elements of both. In our approach, with careful design, experiments measuring memory behaviour (accuracy and response time) and brain-activity related to successful encoding can provide powerful tests of models, leading to a deeper and more generalizable unified model of relational memory.Our recent findings show that models must be redesigned. We were the first to ask, when people remember a pair of words, do they remember the association with or without order (was it Christy-Clark or Clark-Christy)? Participants could judge order, even when they did not deliberately study for order. However, order can also be ambiguous, even when the pair of items is remembered. This challenges current models of association: the matrix model (related to Hebb's rule), which learns associations with unambiguous order and convolution-based models, which store associations without order. Second, early models assumed memory of a list (ABCD...) is composed of a "chain" of associations (AB, BC, CD, ...). Pitted against these, "positional-coding" models, which deliberately omit inter-item associations, are now favoured. Our recent findings clearly show that one recall does, in fact, influence the next, overturning a major tenet of positional-coding models and suggesting that associative chaining is a major part of serial-order memory. The next generation of models will need both item-item and item-position associations. Third, we challenged previous arguments that some brain-activity signals in item-memory tasks reflected associative processes. Instead, frontal slow waves and theta rhythms (4-8 cycles/second) rhythms may be specifically critical for association, and perhaps order, memory.We will modify current models of association- and order-memory to accommodate these findings and generate new testable predictions. In parallel, we will conduct behavioural and electroencephalographic experiments to better understand the relationship between memory for associations and memory for order, and to test and guide further model development.Combining mathematical models, behavioural and brain-activity methods, we can better understand memory behaviour at a basic level, potentially identify brain-activity signals that could be targets of memory assessment or enhancement protocols, and guide the development of memories in artificial agents.

联想记忆（配对，如Notley-Alberta或William-Kate）和顺序记忆（序列，如电话号码）对复杂行为至关重要，从导航到语言再到社会行为。理论是通过数学模型系统地组织起来的，但这些模型也被分别开发和测试为关联和顺序记忆。我们的目标是开发一个单一的模型，可以解释记忆行为在标准的协会和秩序的任务，但也有任务，联合收割机元素两者结合。在我们的方法中，通过精心设计，测量记忆行为（准确性和反应时间）和与成功编码相关的大脑活动的实验可以提供强大的模型测试，从而导致更深层次和更普遍的关系记忆统一模型。我们是第一个提出这个问题的人，当人们记住一对单词时，他们是否记得有顺序或没有顺序的联想（是克里斯蒂-克拉克还是克拉克-克里斯蒂）？参与者可以判断秩序，即使他们没有刻意研究秩序。然而，顺序也可能是模糊的，即使是在记住这对项目的情况下。这挑战了当前的关联模型：矩阵模型（与Hebb规则相关），它学习具有明确顺序的关联，以及基于卷积的模型，它存储没有顺序的关联。第二，早期的模型假设记忆是一个列表（ABCD...）由一个关联的“链”组成（AB，BC，CD，.）。与之相对的是“位置编码”模型，它故意忽略了项目间的关联，现在受到青睐。我们最近的研究结果清楚地表明，一次回忆确实会影响下一次回忆，这推翻了位置编码模型的一个主要原则，并表明联想链是序列顺序记忆的一个主要部分。下一代模型将需要物品-物品和物品-位置的关联。第三，我们挑战了以前的论点，即在项目记忆任务中，一些大脑活动信号反映了联想过程。相反，额叶慢波和θ节律（4-8周期/秒）可能对联想记忆和顺序记忆特别重要，我们将修改当前的联想记忆和顺序记忆模型，以适应这些发现，并产生新的可检验的预测。与此同时，我们将进行行为和脑电图实验，以更好地了解联想记忆和顺序记忆之间的关系，并测试和指导进一步的模型开发。结合数学模型，行为和大脑活动方法，我们可以更好地了解基本水平的记忆行为，潜在地识别可能成为记忆评估或增强协议目标的大脑活动信号，引导人工智能体的记忆发展