Spatial transfer of object-based statistical learning

• Autor(a) principal: Van Moorselaar, Dirk
• Data de Publicação: 2024
• Outros Autores: Theeuwes, Jan
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10400.12/9765
• topic: Attention; Object-based; Attention in learning; Visual search

A large number of recent studies have demonstrated that efcient attentional selection depends to a large extent on the ability to extract regularities present in the environment. Through statistical learning, attentional selection is facilitated by directing attention to locations in space that were relevant in the past while suppressing locations that previously were distracting. The current study shows that we are not only able to learn to prioritize locations in space but also locations within objects independent of space. Participants learned that within a specifc object, particular locations within the object were more likely to contain relevant information than other locations. The current results show that this learned prioritization was bound to the object as the learned bias to prioritize a specifc location within the object stayed in place even when the object moved to a completely diferent location in space. We conclude that in addition to spatial attention prioritization of locations in space, it is also possible to learn to prioritize relevant locations within specifc objects. The current fndings have implications for the inferred spatial priority map of attentional weights as this map cannot be strictly retinotopically organized· · ·