{"title":"Accurate Predictions Facilitate Robust Memory Encoding Independently From Stimulus Probability.","authors":"Jiawen Huang, Eleanor Furness, Yifang Liu, Morell-Jovan Kenmoe, Ronak Elias, Hannah Tongxin Zeng, Christopher Baldassano","doi":"10.1162/opmi.a.14","DOIUrl":null,"url":null,"abstract":"<p><p>We can use prior knowledge of temporal structure to make predictions about how an event will unfold, and this schematic knowledge has been shown to impact the way that event memories are encoded and later reconstructed. Existing paradigms for studying prediction, however, are largely unable to separate effects of prediction accuracy from effects of stimulus probability: likely outcomes are assumed to be predicted, while unlikely outcomes are assumed to cause prediction errors. Here we use a novel approach in which we can independently manipulate prediction success and stimulus probability, by using real-time eye-tracking when viewing moves in a board game. The moves can be consistent or inconsistent with a participant's predictions (assessed via fixation patterns) and can be also be likely or unlikely to be played by a strategic player. By decorrelating these two measures, we found that both probability and prediction accuracy boost memory through two separate mechanisms, leading to different eye-movement strategies at retrieval. Accurate prediction improved encoding precision, allowing participants to directly retrieve these moves without the use of schematic knowledge. Probable moves, on the other hand, led to improved memory through a retrieval-time strategy in which schematic knowledge was used to generate candidate moves for recognition. These results shed new light on the specific role of predictions in enhancing event memories, and provide a more realistic paradigm for studying schemas, learning, and decision making.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"9 ","pages":"940-958"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373454/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Mind","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1162/opmi.a.14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
We can use prior knowledge of temporal structure to make predictions about how an event will unfold, and this schematic knowledge has been shown to impact the way that event memories are encoded and later reconstructed. Existing paradigms for studying prediction, however, are largely unable to separate effects of prediction accuracy from effects of stimulus probability: likely outcomes are assumed to be predicted, while unlikely outcomes are assumed to cause prediction errors. Here we use a novel approach in which we can independently manipulate prediction success and stimulus probability, by using real-time eye-tracking when viewing moves in a board game. The moves can be consistent or inconsistent with a participant's predictions (assessed via fixation patterns) and can be also be likely or unlikely to be played by a strategic player. By decorrelating these two measures, we found that both probability and prediction accuracy boost memory through two separate mechanisms, leading to different eye-movement strategies at retrieval. Accurate prediction improved encoding precision, allowing participants to directly retrieve these moves without the use of schematic knowledge. Probable moves, on the other hand, led to improved memory through a retrieval-time strategy in which schematic knowledge was used to generate candidate moves for recognition. These results shed new light on the specific role of predictions in enhancing event memories, and provide a more realistic paradigm for studying schemas, learning, and decision making.