Models of Explicit and Implicit Memory: Linking Priming, Recognition, and Source Memory

外显记忆和内隐记忆模型：连接启动、识别和源记忆

基本信息

批准号：
ES/N009916/1
负责人：
Christopher Berry
金额：
$ 33.76万
依托单位：
Plymouth University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FN009916%2F1
关键词：
Models Explicit Implicit Memory Linking

项目摘要

Memory comes in many different forms. Understanding how these different forms of memory operate and are enabled in the brain is a crucial goal in psychological and neuroscientific research. A fundamental question is whether there are distinct forms of memory that function independently of other kinds (multiple-systems theory), or whether different forms of memory actually draw upon the same underlying memory (single-system theory). This project will conduct rigorous tests of an existing single-system model by a) applying it to a memory task thought to be challenging for the model to explain -- source memory, and b) comparing its predictions to those of multiple-systems versions of the model in eight new experiments that are designed to discriminate between the models.In previous research, the applicant has found evidence for a single-system model of recognition memory and repetition priming, and this model was preferred to multiple-systems ones. Recognition memory involves being able to determine whether you have encountered something before, for instance, being able to say that you have seen the face of a perpetrator of a crime before. Repetition priming is a more indirect example of memory -- it is typically shown via improvements in performance when a stimulus is re-encountered; for example, when presented with a familiar face that you have seen recently, you will tend to identify it faster than a face that you have not seen for a long time. Recognition memory is a traditional example of explicit (conscious) memory, whereas repetition priming is a traditional example of implicit (unconscious) memory.The new task to be explained by the single-system model is source memory, another explicit memory task, which involves remembering specific information related to a prior encounter. For instance, source memory would be shown if you were able to remember that you saw a particular face at the scene of a crime and not at the supermarket, or if you were able to correctly remember that the colour of the jacket of the perpetrator of a crime was red and not blue. It is important for the single-system model to also explain source memory because many theories propose that the memory used to make source memory decisions is distinct from the kind of memory that drives repetition priming. If the relationship between source memory and repetition priming could be shown to follow the predictions of the single-system model, this would have important implications for these alternative theories, and would be a crucial test of the breadth of single-system views.Multivariate signal detection theory will be drawn upon in extending the model. The main assumption of the single-system model is that priming, recognition, and source are driven by the same memory signal. Specific predictions of the model will be tested experimentally. For example, the model predicts that repetition priming will be positively related to the accuracy of source memory judgments and also the confidence with which these judgments are made. It also predicts that this relationship is modulated by recognition memory. Furthermore, it predicts that experimental variables will tend to affect priming, recognition and source memory similarly, and so would be strongly challenged by experiments in which these measures are differentially affected. Experiments manipulating attention and modality of presentation at encoding will investigate this. The model will be fit to the experimental data and compared with the fit and predictions of multiple-systems models; these will incorporate competing theoretical assumptions to the single-system model and allow for various degrees of independence between the memory signals driving explicit and implicit memory.

记忆有许多不同的形式。了解这些不同形式的记忆如何在大脑中运作和启用是心理和神经科学研究中的关键目标。一个基本的问题是，是否存在独立于其他类型的（多个系统理论）的不同形式的记忆形式，或者是否存在不同形式的记忆形式实际上是在相同的基础记忆（单系统理论）上。该项目将通过a）将其应用于记忆任务，对现有的单一系统模型进行严格的测试，认为对模型的解释很具有挑战性 - 源记忆和b）将其预测与八个新实验中的多个系统版本的预测进行比较，这些新实验旨在在模型之间进行多个模型和重复模型的识别模型，以验证模型的多个模型，并重复了单个模型的识别模型，并重复了单个模型。一个。识别记忆涉及能够确定您以前是否遇到过某些事情，例如，您以前曾见过犯罪者的面孔。重复启动是记忆的一个更间接的示例 - 通常通过重新遇到刺激时的性能改善；例如，当出现您最近见过的熟悉的面孔时，您往往比长期以来从未见过的面孔更快地识别它。识别记忆是显式（有意识）内存的传统示例，而重复启动是隐式（无意识）内存的传统示例。单一系统模型要解释的新任务是源内存，这是另一个明确的内存任务，涉及记住与先前接触有关的特定信息。例如，如果您能够记住您在犯罪现场而不是在超市的现场看到一张特定的面孔，或者您能够正确记住犯罪犯罪者夹克的颜色是红色而不是蓝色的，则将显示出源记忆。对于单一系统模型而言，重要的是也解释源内存，因为许多理论建议用于制定源内存决策的内存与驱动重复启动的那种内存不同。如果可以证明源记忆与重复启动之间的关系遵循单一系统模型的预测，这将对这些替代理论具有重要意义，并且将是对单个系统视图的广度的关键检验。在扩展模型中，将借鉴单个系统视图的广度。单个系统模型的主要假设是启动，识别和源是由相同的内存信号驱动的。该模型的具体预测将进行实验测试。例如，该模型预测重复启动将与源记忆判断的准确性以及对这些判断的信心呈正相关。它还预测这种关系是通过识别记忆来调节的。此外，它预测，实验变量将倾向于同样影响启动，识别和源记忆，因此，这些措施受到差异影响的实验会严重挑战。在编码时操纵注意力和表现方式的实验将调查这一点。该模型将适合实验数据，并将其与多个系统模型的拟合和预测进行比较。这些将对单一系统模型进行竞争的理论假设，并允许在驱动显式和隐式内存的内存信号之间建立各种独立性。