Psychology Department, University of California, San Diego, La Jolla, CA, USA.
Nat Hum Behav. 2023 Oct;7(10):1638-1651. doi: 10.1038/s41562-023-01602-z. Epub 2023 Jul 4.
Ensemble perception is a process by which we summarize complex scenes. Despite the importance of ensemble perception to everyday cognition, there are few computational models that provide a formal account of this process. Here we develop and test a model in which ensemble representations reflect the global sum of activation signals across all individual items. We leverage this set of minimal assumptions to formally connect a model of memory for individual items to ensembles. We compare our ensemble model against a set of alternative models in five experiments. Our approach uses performance on a visual memory task for individual items to generate zero-free-parameter predictions of interindividual and intraindividual differences in performance on an ensemble continuous-report task. Our top-down modelling approach formally unifies models of memory for individual items and ensembles and opens a venue for building and comparing models of distinct memory processes and representations.
整体感知是一种我们对复杂场景进行总结的过程。尽管整体感知对日常认知很重要，但很少有计算模型对此过程提供正式的解释。在这里，我们开发并测试了一个模型，其中整体表示反映了所有单个项目的激活信号的全局总和。我们利用这组最小的假设，将单个项目的记忆模型正式连接到整体中。我们在五个实验中将我们的整体模型与一组替代模型进行了比较。我们的方法使用单个项目的视觉记忆任务的性能，为个体间和个体内差异在整体连续报告任务中的表现生成零参数自由预测。我们的自上而下的建模方法正式统一了单个项目和整体的记忆模型，并为构建和比较不同记忆过程和表示的模型开辟了一个途径。
