Year: 2010
Type: conference-paper
Abstract: When encoding a scene into memory, people store both the overall gist of the scene and detailed information about a few specific objects.Moreover, they use the gist to guide their choice of which specific objects to remember.However, formal models of change detection, like those used to estimate visual working memory capacity, generally assume people represent no higher-order structure about the display and choose which items to encode at random.We present a probabilistic model of change detection that attempts to bridge this gap by formalizing the encoding of both specific items and higherorder information about simple working memory displays.We show that this model successfully predicts change detection performance for individual displays of patterned dots.More generally, we show that it is necessary for the model to encode higher-order structure in order to accurately predict human performance in the change detection task.This work thus confirms and formalizes the role of higher-order structure in visual working memory.
Authors: Timothy F. Brady, Joshua Tenebaum
Institution: Massachusetts Institute of Technology
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2791228886