![]() Large changes in scenes can go unnoticed when the change occurs during some sort of perceptual disruption, for example an ISI, an eye movement – or an occlusion. Research from the field of change detection suggests that our stored representations lack visual detail. Thus, to evaluate what such a seemingly remarkable memory performance means, a measure of the level of stored detail would be needed. Distractor and target images were rather dissimilar in those studies, possibly allowing participants to rely upon merely storing the basic meaning of an image, in terms of a short verbal description. ![]() However, this remarkable ability to successfully discriminate between targets and distractors did not necessarily mean that a detailed representation of each image was created and stored. Even when 10,000 images were shown, participants were able to decide with an accuracy of 83% which of two images they had seen. For example, after seeing 2560 slides for 10 seconds each participants’ recognition performance, even after several days, was still above 90%. It is a well-established finding that long-term memory for images is extensive and that thousands of items can be stored –. Overall performance was high, indicating a large-capacity, detailed visual long-term memory. After delayed testing, these differences disappeared. Performance was lowest when the distractor image was conceptually and visually similar to the target image, indicating that both factors matter in such a memory task. We analyzed the distribution of errors depending on distractor type. In Experiment 3, testing occurred after a delay of one week. In Experiment 1, participants performed a two-alternative forced choice recognition task and in Experiment 2, a yes/no-recognition task. Memory for a subset of these images was tested subsequently. Participants viewed 219 images with the instruction to memorize them. For each target, four distractors were selected that were (1) conceptually and visually similar, (2) only conceptually similar, (3) only visually similar, or (4) neither conceptually nor visually similar to the target image. This similarity index takes colours and spatial frequencies into account. The important novelty of our approach was that visual similarity was determined using an algorithm instead of being judged subjectively. We examined the role of conceptual and visual similarity in a memory task for natural images.
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