ABSTRACT

Pattern separation is a computational mechanism performed by the hippocampus allowing the reduction of overlap between sensory inputs with similar perceptual features. Our first aim was to develop a new paradigm sensitive to the behavioural consequences of pattern separation (mnemonic discrimination). For this purpose, we constructed morphed face stimuli with parametrically changing levels of similarity. After encoding participants saw studied items and similar lure faces. Perceptual similarity affected false recognition and there was a gradual reduction in discrimination accuracy with the increment of similarity between the stimuli. However, confidence ratings were sensitive to smaller changes (Experiment 1) than the other test type with “old”/“similar”/“new” response options (Experiment 2). Mnemonic discrimination relies strongly on retrieving details of the original stimulus. Therefore, we investigated whether pattern separation can be tuned by retrieval in the form of a discrimination task (Experiment 3). Our findings suggest that repeatedly encountering the stimuli within a two-alternative forced-choice task (in comparison with the repeated presentation of the material) increased both the correct identification and the false recognition of similar stimuli two days after encoding. We conclude that basic computational mechanisms of the hippocampus can be tuned by a task that requires discrimination between studied and new stimuli.

摘要

模式分离是由海马体执行的一种计算机制，允许减少具有相似感知特征的感觉输入之间的重叠。我们的第一个目标是开发一种对模式分离（助记区分）的行为后果敏感的新范式。为此，我们构建了具有参数变化相似度水平的变形面部刺激。编码后，参与者看到了研究项目和类似的诱饵面孔。感知相似度会影响错误识别，并且随着刺激之间相似度的增加，识别准确度逐渐降低。然而，与具有“旧”/“相似”/“新”响应选项（实验 2）的其他测试类型相比，置信等级对较小的变化（实验 1）更敏感。助记符辨别强烈依赖于检索原始刺激的细节。因此，我们研究了模式分离是否可以通过以判别任务的形式进行检索来调整（实验 3）。我们的研究结果表明，在两种可选的强制选择任务中反复遇到刺激（与材料的重复呈现相比）增加了编码两天后对类似刺激的正确识别和错误识别。我们得出结论，海马体的基本计算机制可以通过需要区分研究的刺激和新刺激的任务来调整。我们的研究结果表明，在两种可选的强制选择任务中反复遇到刺激（与材料的重复呈现相比）增加了编码两天后对类似刺激的正确识别和错误识别。我们得出结论，海马体的基本计算机制可以通过需要区分研究的刺激和新刺激的任务来调整。我们的研究结果表明，在两种可选的强制选择任务中反复遇到刺激（与材料的重复呈现相比）增加了编码两天后对类似刺激的正确识别和错误识别。我们得出结论，海马体的基本计算机制可以通过需要区分研究的刺激和新刺激的任务来调整。