强记忆形成的神经和认知动力:荟萃分析和 SAM 模型

Hongkeun Kim
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摘要

摘要 后续记忆范式是神经影像学研究编码过程的基本工具。尽管有些研究将记忆的试验与遗忘的试验进行了对比,但其他研究则侧重于强记忆试验与遗忘试验的对比。本研究采用荟萃分析方法将两种对比中观察到的效果并列起来。关于记忆形成的三个不同视角--语义阐释、注意力集中和海马处理--对负责形成强记忆的区域提出了不同的假设。荟萃分析得出的证据支持注意和语义假说,但未能证实海马假说。讨论部分将这些不同的观点整合为一个连贯的观点,最终提出了一个名为 "意义驱动和注意驱动记忆(SAM)"的模型。SAM模型有几个关键假设。首先,该模型建立了试验到试验编码表现的波动与持续注意力的连续变化之间的联系。其次,该模型认为,注意力对知觉和语义加工都有强大的影响,而对海马体加工的影响仍然是温和的。最后,该模型强调了海马体在意义驱动编码中的重要作用,而不是注意力驱动编码。从具体的角度来看,该模型的价值在于促进对当前广泛的荟萃分析结果的整体理解。从更全面的角度来看,该模型引入了一个综合框架,将各种与编码相关的认知和神经过程综合为一个有凝聚力的统一视角。
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Neural and cognitive dynamics leading to the formation of strong memories: A meta-analysis and the SAM model
Abstract The subsequent memory paradigm is a fundamental tool in neuroimaging investigations of encoding processes. Although some studies have contrasted remembered trials with forgotten ones, others have focused on strongly remembered trials versus forgotten ones. This study employed a meta-analytic approach to juxtapose the effects observed in the two types of contrast. Three distinct perspectives on memory formation—semantic elaboration, attentional focus, and hippocampal processing—yield diverse hypotheses about the regions responsible for the formation of strong memories. The meta-analysis yielded evidence supporting the attentional and semantic hypotheses while failing to substantiate the hippocampal hypothesis. The discussion section integrates these varied perspectives into a coherent view, culminating in the proposal of a model called the Significance-driven and Attention-driven Memory (SAM). Several pivotal postulates underpin the SAM model. First, it establishes a link between fluctuations in the trial-to-trial encoding performance and continuous variations in sustained attention. Second, the model contends that attention exerts a potent influence on both perceptual and semantic processing, while its impact on hippocampal processing remains moderate. Lastly, the model accentuates the heightened role of the hippocampus in significance-driven encoding, as opposed to attention-driven encoding. From a specific perspective, the model’s value lies in promoting a holistic understanding of the current extensive meta-analytic results. In a more comprehensive context, the model introduces an integrated framework that synthesizes various encoding-related cognitive and neural processes into a cohesive and unified perspective.
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