Gestalt grouping and perceptual averaging to boost memory capacity
It’s very surprising that we are only able to see and remember the details of about 4 objects at a time, because we have a very strong impression that we see everything in the world in front of us in high resolution from moment to moment. The visual system has many “tricks” to accomplish this illusion of detailed perception. One of these is to represent the average properties of sets of similar objects (average size of trees in a forest) instead of wasting the energy it would take to represent each individual object. In this project, we are examining how the visual system uses Gestalt heuristics like grouping by similarity, proximity, connectedness, and common region to define sets of objects to statistically summarize. We are using EEG to record electrical brain activity known to be related to memory capacity while observers try to memorize the sizes of sets of many objects, either grouped by different Gestalt cues or ungrouped. We expect that the EEG data will show that observers are able to remember more objects using less memory resources when the objects are grouped and that observers’ behavioural data will show that they are remembering the objects based on their average set properties instead of their individual sizes.