Katkov Mikhail, Romani Sandro, Tsodyks Misha
Department of Neurobiology, The Weizmann Institute of Science, Rehovot 76100, Israel.
Center for Theoretical Neuroscience, Columbia University, New York, New York 10032, USA.
Learn Mem. 2015 Jan 15;22(2):101-8. doi: 10.1101/lm.035238.114. Print 2015 Feb.
Human memory stores vast amounts of information. Yet recalling this information is often challenging when specific cues are lacking. Here we consider an associative model of retrieval where each recalled item triggers the recall of the next item based on the similarity between their long-term neuronal representations. The model predicts that different items stored in memory have different probability to be recalled depending on the size of their representation. Moreover, items with high recall probability tend to be recalled earlier and suppress other items. We performed an analysis of a large data set on free recall and found a highly specific pattern of statistical dependencies predicted by the model, in particular negative correlations between the number of words recalled and their average recall probability. Taken together, experimental and modeling results presented here reveal complex interactions between memory items during recall that severely constrain recall capacity.
人类记忆存储着大量信息。然而，当缺乏特定线索时，回忆这些信息往往具有挑战性。在这里，我们考虑一种关联检索模型，其中每个被回忆起的项目会根据其长期神经元表征之间的相似性触发下一个项目的回忆。该模型预测，存储在记忆中的不同项目被回忆起的概率取决于其表征的大小。此外，具有高回忆概率的项目往往会被更早地回忆起来，并抑制其他项目。我们对一个关于自由回忆的大型数据集进行了分析，发现了该模型预测的高度特定的统计依赖模式，特别是回忆起的单词数量与其平均回忆概率之间的负相关。综上所述，这里呈现的实验和建模结果揭示了回忆过程中记忆项目之间复杂的相互作用，这些相互作用严重限制了回忆能力。
