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What to expect when you are not expecting it: How implicit regularities drive attentional selection

Periodic Reporting for period 3 - LEARNATTEND (What to expect when you are not expecting it: How implicit regularities drive attentional selection)

Berichtszeitraum: 2023-01-01 bis 2024-06-30

Have you ever wondered why we are able to negotiate busy traffic intersections or why we are able to find rather quickly the products we need in a busy supermarket? Our visual system is usually overloaded with massive amounts of information, and still we are able to pick up the right information at the right moment in time. Indeed, we should not and cannot pay attention to all events. Instead, we need to direct attention to those events that have proven to be important in the past and suppress those that were distracting and irrelevant. Experiences moulded through a learning process enable us to extract and adapt to the statistical regularities in the world. This process is often referred to as statistical learning. The current project investigates these learning processes determining on how, when and what information is extracted by the visual system. Through brain imaging we seek to understand how learning taking place in brain and this affects attentional representations within putative priority maps across the visual hierarchy. This type of learning is largely unconscious, unintentional, and implicit; it runs "in the background", both seeking and giving structure to the world around us; making it coherent, predictable and quickly manageable. Even though a lot is known about how statistical learning affects language acquisition, object recognition, motor learning, and decision making, the current project is among the first to focus on its role in attention and selection. Visual perception must be selective, as we are confronted with the massive amount of available sensory input. Statistical learning occurring often beneath the level of awareness provides structure to the environment uncovering the relations between objects in space and time.
Since the beginning of the project (January 2000), we have conducted many behavioral experiments uncovering the boundary conditions of statistical learning and attentional selection. We have focused on (1) the role of awareness during learning (2) the role of working memory during learning (3) whether learning is a truly automatic process (4) the role of statistical learning during reading (5) learning about across trial transitions (6) the extent to which distracting information can be ignored due to learning (6) learning across time and space (7) statistical learning and individual differences. All these projects have resulted in multiple published papers (see website: www.theeuweslab.com). There have been two major review papers: one paper that explains the applied societal relevance of statistical learning in a paper by Theeuwes (2021) in the journal “Cognitive Research: Principles and Implications”, and one paper in which we summarize the results of this project up till now by Theeuwes, Bogaerts & Van Moorselaar 2022 in het high impact journal “Trends in Cognitive Science”
The progress is excellent. Due to Covid-19, up till now, we have mainly focused behavioral studies that could be conducted on-line. This has worked out very well. For the coming period we will focus more on brain imaging, EEG studies and eye tracking, which all require research in the lab. The progress we will make the coming years in this respect will depend on the pandemic and how it will affect access to the laboratory which is needed for these type of studies.
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