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几何模型揭示了将体验转化为记忆的行为和神经特征。

Geometric models reveal behavioural and neural signatures of transforming experiences into memories.

机构信息

Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.

Akili Interactive Labs, Boston, MA, USA.

出版信息

Nat Hum Behav. 2021 Jul;5(7):905-919. doi: 10.1038/s41562-021-01051-6. Epub 2021 Feb 11.

Abstract

How do we preserve and distort our ongoing experiences when encoding them into episodic memories? The mental contexts in which we interpret experiences are often person-specific, even when the experiences themselves are shared. Here we develop a geometric framework for mathematically characterizing the subjective conceptual content of dynamic naturalistic experiences. We model experiences and memories as trajectories through word-embedding spaces whose coordinates reflect the universe of thoughts under consideration. Memory encoding can then be modelled as geometrically preserving or distorting the 'shape' of the original experience. We applied our approach to data collected as participants watched and verbally recounted a television episode while undergoing functional neuroimaging. Participants' recountings preserved coarse spatial properties (essential narrative elements) but not fine spatial scale (low-level) details of the episode's trajectory. We also identified networks of brain structures sensitive to these trajectory shapes.

摘要

当我们将持续的体验编码为情景记忆时,我们如何保存和扭曲这些体验?我们解释体验的心理背景通常是特定于个人的,即使体验本身是共享的。在这里,我们开发了一个几何框架,用于从数学上刻画动态自然体验的主观概念内容。我们将体验和记忆建模为通过词嵌入空间的轨迹,其坐标反映了正在考虑的思想的范围。记忆编码可以建模为几何上保留或扭曲原始体验的“形状”。我们将我们的方法应用于参与者在进行功能神经影像学检查的同时观看和口头叙述电视剧集时收集的数据。参与者的叙述保留了粗略的空间属性(基本叙事元素),但没有保留情节轨迹的精细空间尺度(低水平)细节。我们还确定了对这些轨迹形状敏感的大脑结构网络。

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