The Influence of Attention, Learning, and Motivation on Visual Search

The Effect of Time Pressure on Visual Search Eye Tracking Metrics in Virtual Reality

“…As previously noted, classical computer-based visual search paradigms are limited by tightly controlled environments and abstract target stimuli that do not accurately represent real-life visual search behavior (Dodd & Flowers, 2012). To bridge the gap between laboratory-based and real-life visual search, we present our environment in VR.…”

How predictability and individual alpha frequency shape memory: insights from an event-related potential investigation

“…The notion that predictions rely on memory representations is grounded in the brain’s ability to extract environmental regularities – a process known as statistical learning (Turk-Browne in Dodd & Flowers, 2012; Siegelman & Frost, 2015). Regularities are abundant in the natural world, such that similar patterns are encountered across time and space (Turk-Browne in Dodd & Flowers, 2012, p. 118).…”

“…There is strong evidence that the brain can learn and encode patterns of this nature into memory (i.e., that it can engage in statistical learning); for example, classic visual statistical learning tasks show successful learning of triplets of shapes (Fiser & Aslin, 2002) and syllables (Saffran et al, 1996), presented in a continuous sequence (for similar research in mice, see Gavornik & Bear, 2014). This learning also appears relatively implicit, with participants judging patterns as more familiar than random shapes despite being unaware of an underlying relationship and having low confidence in their decisions (Turk-Browne in Dodd & Flowers, 2012, p. 123). This proficiency for pattern learning has been shown to facilitate predictive processing, with research demonstrating enhanced prediction of upcoming visual orientations following structured versus random sequences (Baker et al, 2014).…”

“…The notion that predictions rely on memory representations is grounded in the brain’s ability to extract environmental regularities – a process known as statistical learning (Turk-Browne in Dodd & Flowers, 2012; Siegelman & Frost, 2015). Regularities are abundant in the natural world, such that similar patterns are encountered across time and space (Turk-Browne in Dodd & Flowers, 2012, p. 118). There is strong evidence that the brain can learn and encode patterns of this nature into memory (i.e., that it can engage in statistical learning); for example, classic visual statistical learning tasks show successful learning of triplets of shapes (Fiser & Aslin, 2002) and syllables (Saffran et al, 1996), presented in a continuous sequence (for similar research in mice, see Gavornik & Bear, 2014).…”

“…Additionally, studies employing Serial Reaction Time tasks have revealed faster reaction times for spatial locations that were preceded by predictable versus unpredictable sequences (Nissen & Bullemer, 1987, in Schwarb & Schumacher, 2012). As such, a statistical learning mechanism within memory has been proposed, where statistical relationships are encoded as generalized memory traces to enable the anticipation of future states (Bar, 2007; Turk-Browne in Dodd & Flowers, 2012; Sherman & Turk-Browne, 2020). Statistical learning may thus act as a precursor to the formation of a predictive model (Rauss & Born, 2017), such that regularities are learnt and stored as associative traces in memory, which are subsequently retrieved for future use (Bar, 2007).…”