@inbook{23ba4d9eee5f4f0e8b88e2db18cf3979,
title = "Past experience and meaning affect object detection: A hierarchical Bayesian approach",
abstract = "For human perceivers, object perception seems immediate and unambiguous. Following the Gestalt reaction against structuralism over 100 years ago, it was long held that serial feedforward processing could account for object perception and that past experience and object meaning played no role because these were assumed to be activated only after objects were detected. We now know that this approach is inadequate: Our systematic investigation of past experience effects has revealed that object perception entails dynamic feedforward and feedback interactions between low- and high-level brain regions. Our research has shown that object semantics (meaning) as well as object shape are activated early in the course of object perception and that semantic activation initiated by a word can facilitate object detection. Finally, we have found that brain regions traditionally thought to be involved in explicit memory play a role in object detection. In this chapter, our work examining how past experience and meaning affects object detection is reviewed and integrated with current research from other laboratories. My goal is for this review to serve as a springboard for research aimed at a deeper understanding of the dynamical interactions involved in object perception.",
keywords = "Alpha suppression, Early visual areas, Familiarity, Figure–ground perception, Hierarchical Bayesian model, Inhibitory competition, Meaning, Object detection, Past experience, Perirhinal cortex, Semantics",
author = "Peterson, {Mary A.}",
note = "Publisher Copyright: {\textcopyright} 2019 Elsevier Inc.",
year = "2019",
doi = "10.1016/bs.plm.2019.03.006",
language = "English (US)",
isbn = "9780128168684",
series = "Psychology of Learning and Motivation - Advances in Research and Theory",
publisher = "Academic Press Inc.",
pages = "223--257",
editor = "Federmeier, {Kara D.} and Beck, {Diane M.}",
booktitle = "Knowledge and Vision",
}