1
|
Geyer T, Zinchenko A, Seitz W, Balik M, Müller HJ, Conci M. Mission impossible? Spatial context relearning following a target relocation event depends on cue predictiveness. Psychon Bull Rev 2024; 31:148-155. [PMID: 37434045 PMCID: PMC10867038 DOI: 10.3758/s13423-023-02328-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/02/2023] [Indexed: 07/13/2023]
Abstract
Visual search for a target is faster when the spatial layout of distractors is repeatedly encountered, illustrating that statistical learning of contextual invariances facilitates attentional guidance (contextual cueing; Chun & Jiang, 1998, Cognitive Psychology, 36, 28-71). While contextual learning is usually relatively efficient, relocating the target to an unexpected location (within an otherwise unchanged search layout) typically abolishes contextual cueing and the benefits deriving from invariant contexts recover only slowly with extensive training (Zellin et al., 2014, Psychonomic Bulletin & Review, 21(4), 1073-1079). However, a recent study by Peterson et al. (2022, Attention, Perception, & Psychophysics, 84(2), 474-489) in fact reported rather strong adaptation of spatial contextual memories following target position changes, thus contrasting with prior work. Peterson et al. argued that previous studies may have been underpowered to detect a reliable recovery of contextual cueing after the change. However, their experiments also used a specific display design that frequently presented the targets at the same locations, which might reduce the predictability of the contextual cues thereby facilitating its flexible relearning (irrespective of statistical power). The current study was a (high-powered) replication of Peterson et al., taking into account both statistical power and target overlap in context-memory adaptation. We found reliable contextual cueing for the initial target location irrespective of whether the targets shared their location across multiple displays, or not. However, contextual adaptation following a target relocation event occurred only when target locations were shared. This suggests that cue predictability modulates contextual adaptation, over and above a possible (yet negligible) influence of statistical power.
Collapse
Affiliation(s)
- Thomas Geyer
- Department of Psychology, Ludwig Maximilian University of Munich, Leopoldstraße 13, 80802, Munich, Germany
- Munich Center of Neurosciences-Brain & Mind, Munich, Germany
- NICUM-NeuroImaging Core Unit Munich, Munich, Germany
| | - Artyom Zinchenko
- Department of Psychology, Ludwig Maximilian University of Munich, Leopoldstraße 13, 80802, Munich, Germany.
| | - Werner Seitz
- Department of Psychology, Ludwig Maximilian University of Munich, Leopoldstraße 13, 80802, Munich, Germany
| | - Merve Balik
- Department of Psychology, Ludwig Maximilian University of Munich, Leopoldstraße 13, 80802, Munich, Germany
| | - Hermann J Müller
- Department of Psychology, Ludwig Maximilian University of Munich, Leopoldstraße 13, 80802, Munich, Germany
- Munich Center of Neurosciences-Brain & Mind, Munich, Germany
| | - Markus Conci
- Department of Psychology, Ludwig Maximilian University of Munich, Leopoldstraße 13, 80802, Munich, Germany
- Munich Center of Neurosciences-Brain & Mind, Munich, Germany
| |
Collapse
|
2
|
Yang X, Yang B, Tang C, Mo X, Hu B. Visual Attention Quality Research for Social Media Applications: A Case Study on Photo Sharing Applications. INTERNATIONAL JOURNAL OF HUMAN–COMPUTER INTERACTION 2023:1-14. [DOI: 10.1080/10447318.2023.2201556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 03/03/2023] [Accepted: 04/03/2023] [Indexed: 09/01/2023]
Affiliation(s)
- Xian Yang
- School of Art and Design, Guangdong University of Technology, Guangzhou, China
| | - Bin Yang
- School of Art and Design, Guangdong University of Technology, Guangzhou, China
| | - Chaolan Tang
- School of Art and Design, Guangdong University of Technology, Guangzhou, China
| | - Xiaohong Mo
- School of Art and Design, Guangdong University of Technology, Guangzhou, China
| | - Bin Hu
- Faculty of Humanities and Arts, Macau University of Science and Technology, Macao, China
| |
Collapse
|