Real-World Objects Are Represented in Visual Long-Term Memory Both as Unbound Features and as Bound Objects

摘要

Recent research has shown that observers store a vast amount of viewed real-world objects invisual long-term learning with high precision (e.g., Standing, 1973; Vogt and Magnussen, 2007;Brady et al., 2008), even when objects have been processed without any attention and intentionof learning (Kuhbandner et al., 2017). However, one open issue that has attracted considerableattention recently is the nature of the stored visual long-term memory representations. Sinceobjects are higher-level constructs that represent patterns of lower-level features, two contrastingviews have been put forward: objects may be stored in in the form of sets of independent featurerepresentations or in the form of unitary feature-bound object representations (e.g., Brady et al.,2013; van den Honert et al., 2017).