Statistical computations underlying the dynamics of memory updating.
Statistical computations underlying the dynamics of memory updating.
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DOI：
10.1371/journal.pcbi.1003939
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发表时间：
2014-11
影响因子：
4.3
通讯作者：
Niv Y
中科院分区：
文献类型：
--
作者：
Gershman SJ;Radulescu A;Norman KA;Niv Y
心理物理学和神经生理学研究表明，记忆不仅仅是我们经验的复制品：记忆的修改或新记忆的形成取决于我们经验的动态结构，特别是世界变化的渐进或突然。我们提出了一个统计理论的记忆形成在动态环境中，基于非参数推广的开关卡尔曼滤波器。我们表明，这一理论可以定性地解释一些心理物理和神经现象，并提出了一个新的视觉记忆实验的结果，旨在直接测试的理论。我们的实验结果表明，人类可以利用环境结构中的时间不连续性来确定何时形成新的记忆痕迹。我们提供的统计学观点提供了一个连贯的解释，说明了新经验整合到旧记忆中的条件，以及形成新记忆的条件，并表明记忆的形成取决于对我们经验的潜在结构的推断。我们什么时候修改旧的记忆，什么时候创造新的？我们认为这个问题可以用统计学来回答：将经验解析成不同的记忆痕迹对应于对环境底层结构的推断。当感觉数据随着时间的推移逐渐变化时，大脑推断出环境已经慢慢演变，并且环境的当前表示（现有记忆痕迹）被更新。相反，突然的变化表明不同结构之间的过渡，导致新记忆的形成。虽然这些想法很自然地从学习的统计模型中产生，但它们尚未在人类记忆领域得到直接测试。在本文中，我们描述了一个模型的统计推断，实例化这些想法，并测试模型，要求人类参与者重建以前看到的视觉对象，因为逐渐或突然改变。这个实验的结果支持了我们关于感觉经验的统计结构如何塑造记忆形成的理论。
Psychophysical and neurophysiological studies have suggested that memory is not simply a carbon copy of our experience: Memories are modified or new memories are formed depending on the dynamic structure of our experience, and specifically, on how gradually or abruptly the world changes. We present a statistical theory of memory formation in a dynamic environment, based on a nonparametric generalization of the switching Kalman filter. We show that this theory can qualitatively account for several psychophysical and neural phenomena, and present results of a new visual memory experiment aimed at testing the theory directly. Our experimental findings suggest that humans can use temporal discontinuities in the structure of the environment to determine when to form new memory traces. The statistical perspective we offer provides a coherent account of the conditions under which new experience is integrated into an old memory versus forming a new memory, and shows that memory formation depends on inferences about the underlying structure of our experience. When do we modify old memories, and when do we create new ones? We suggest that this question can be answered statistically: The parsing of experience into distinct memory traces corresponds to inferences about the underlying structure of the environment. When sensory data change gradually over time, the brain infers that the environment has slowly been evolving, and the current representation of the environment (an existing memory trace) is updated. In contrast, abrupt changes indicate transitions between different structures, leading to the formation of new memories. While these ideas fall naturally out of statistical models of learning, they have not yet been directly tested in the domain of human memory. In this paper, we describe a model of statistical inference that instantiates these ideas, and test the model by asking human participants to reconstruct previously seen visual objects that have since changed gradually or abruptly. The results of this experiment support our theory of how the statistical structure of sensory experiences shapes memory formation.
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