Publications by authors named "Benjamin A McDunn"

Numerous studies have shown that more visual features can be stored in visual short-term memory (VSTM) when they are encoded from fewer objects (Luck & Vogel, 1997, Nature, 390, 279-281; Olson & Jiang, 2002, Perception & Psychophysics, 64[7], 1055-1067). This finding has been consistent for simple objects with one surface and one boundary contour, but very few experiments have shown a clear performance benefit when features are organized as multipart objects versus spatially dispersed single-feature objects. Some researchers have suggested multipart object integration is not mandatory because of the potential ambiguity of the display (Balaban & Luria, 2015, Cortex, 26(5), 2093-2104; Luria & Vogel, 2014, Journal of Cognitive Neuroscience, 26[8], 1819-1828).

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Individuals consistently remember seeing wider-angle versions of previously viewed scenes than actually existed. The multi-source model of boundary extension (BE) suggests many sources of information contribute to this visual memory error. Color diagnosticity is known to affect object recognition with poorer recognition for atypically versus typically colored objects.

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Studies have shown that people consistently remember seeing more of a studied scene than was physically present (e.g., Intraub & Richardson Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 179-187, 1989).

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Boundary extension (BE) is a remarkably consistent visual memory error in which participants remember seeing a more wide-angle image of a scene than was actually viewed (Intraub & Richardson, Journal of Experimental Psychology: Learning, Memory, and Cognition 15:179-187, 1989). Multiple stimulus factors are thought to contribute to the occurrence of BE, including object recognition, conceptual knowledge of scenes, and amodal perception at the view boundaries (Intraub, Wiley Interdisciplinary Reviews: Cognitive Science 3:117-127, 2012). In the present study, we used abstract scenes instead of images of the real world, in order to remove expectations based on semantic associations with objects and the schematic context of the view.

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