Comparison of Resource-Rational Observer Models of Individual and Ensemble Spatial Perception
Abstract
To better understand the underlying mechanisms of individual and ensemble perception in naturalistic scenes, we compared three bayesian resource-rational models on experimental data (from 27 healthy adults): the ’Individual Encoding Model’ (IEM), a variant of the summation model; the ’Ensemble Encoding Model’ (EEM), related to the automatic averaging model; and the ‘Task Adapted Encoding Model’ (TAEM), a flexible combination of both models that adapts to task demands. In the experiment, participants encoded and reproduced either an individual object position or an ensemble position (group centroid) in a 3D-rendered scene using a computer mouse. In both tasks, we manipulated set size (3, 6, 10 objects) and presentation time (50, 100, 800 ms). The EEM and TAEM generally explained the human behavioral data best. We conclude that, in naturalistic scenes, the choice between individual versus ensemble perception is likely driven by the more compact scene representation of the ensemble model.
Description
The here provided datasets comprises behavioral data collected from 27 participants in a controlled laboratory experiment designed to assess the ability to extract individual and ensemble-level information. Participants completed a single experimental session while seated in a darkened room, viewing stimuli presented on a 25-inch monitor (60 Hz refresh rate, 1920 × 1080 resolution).
Additionally, Bayesian modeling approaches were applied to analyze participant responses, and all scripts required to reproduce these analyses are provided alongside the datasets. The datasets and accompanying materials are distributed as a structured archive, including the processed data, and analysis scripts. A README.md file provides a complete list of contents, software dependencies, and step-by-step instructions for reuse.
