Westebbe Leo, Liang Yibiao, Blaser Erik
Department of Psychology, University of Massachusetts Boston, Boston, MA, USA.
Open Mind (Camb). 2024 Mar 1;8:131-147. doi: 10.1162/opmi_a_00122. eCollection 2024.
It is challenging to quantify the accuracy and precision of scene memory because it is unclear what 'space' scenes occupy (how can we quantify error when misremembering a natural scene?). To address this, we exploited the ecologically valid, metric space in which scenes occur and are represented: routes. In a delayed estimation task, participants briefly saw a target scene drawn from a video of an outdoor 'route loop', then used a continuous report wheel of the route to pinpoint the scene. Accuracy was high and unbiased, indicating there was no net boundary extension/contraction. Interestingly, precision was higher for routes that were self-similar (as characterized by the half-life, in meters, of a route's Multiscale Structural Similarity index), consistent with previous work finding a 'similarity advantage' where memory precision is regulated according to task demands. Overall, scenes were remembered to within a few meters of their actual location.
量化场景记忆的准确性和精确性具有挑战性，因为不清楚场景占据何种“空间”（当错误记忆自然场景时，我们如何量化误差？）。为了解决这个问题，我们利用了场景出现并得以表征的具有生态效度的度量空间：路线。在一个延迟估计任务中，参与者短暂地看到一个从户外“路线循环”视频中选取的目标场景，然后使用路线的连续报告轮来精确指出该场景的位置。准确性很高且无偏差，表明没有净边界扩展/收缩。有趣的是，对于具有自相似性的路线（以路线的多尺度结构相似性指数的半衰期，单位为米来表征），精确性更高，这与之前的研究结果一致，即在根据任务需求调节记忆精确性方面存在“相似性优势”。总体而言，场景的记忆位置与实际位置相差在几米之内。
