Statistical learning (SL) refers to the ability to extract statistical regularities from the environment. Many researchersbelieve that SL arises as a consequence of the way that information is stored and accessed in memory (Thiessen, Kronstein,& Hufnagle, 2013). Accordingly, manipulations that influence memory should have similar effects in SL experiments. In thecurrent study, participants were presented with artificial languages that varied along two dimensions known to impact memory:number of distractors in the input and timing of presentation (e.g., spaced vs. massed). Participants’ performance was clearlyinfluenced by these manipulations; for example, the ability to segment a word (e.g., ”dupona”) differed as a function of whetherthere was one frequent competitor (e.g., ”dugalo”) or several less frequent competitors (e.g., ”dugalo,” ”dufalu,” ”dumiso”).Experimental results were compared to two memory-based computational models of SL (PARSER and TRACX). Implicationsof the experimental results and model comparisons will be discussed.

A key feature of attention is that it moves over time, guided both exogenously by changing external circumstances and endogenously by internal cognitive states. However, the endogenous mechanisms guiding the movement of attention in the absence of external cues remain poorly understood. This paper develops and validates a computational model of how internal attentional states, motivated by the Adaptive Gain Theory of the locus coeruleus-norepinephrine (LC-NE) system, can guide the movement of visual attention over time. By fitting our model to young children's gaze data as they perform a visual object tracking task, we investigate developmental changes in higher-order patterns of attending behavior between 3.5-6 years of age, and we hypothesize about how the LC-NE system might mediate these changes.

Experiences of contingent interactions like referential cues (e.g., caregivers pointing to relevant text and pictures) during shared book reading predict better reading and language outcomes (Landry, & Smith, 2007). However, it is unclear whether contingent responsiveness in a digital book could provide similar support for children in the absence of contingent feedback from an adult. The effects on story comprehension using an interactive book with content-related animations that activated contingent on children’s vocalizations were investigated, with a focus on whether the interactive book might be especially useful for children with less developed attentional control. The present study used a within-subject design with data from 69 preschool-aged children. The use of the interactive book exhibited significantly increased comprehension, and was also found to be especially useful for children with less attentional control. Importantly, the associations between attention and comprehension gains were not entirely due to variance shared with verbal ability.

Measuring selective sustained attention (SSA) development in preschool-aged children has been difficult due to challengesin designing age-appropriate measurement paradigms. The TrackIt task, together with eye-tracking and a recently pro-posed Bayesian-model based eye-tracking analysis method, creates opportunity for fine-grained measurement of SSA inyoung children. The current study 1) provides the first rigorous validation of this method by comparing model judgmentswith human video-coding of the data, and 2) further explores potential uses of this method for providing nuanced measuresof SSA. More specifically, we use the analysis method to explore different ways of characterizing SSA based on eye-gazedata obtained during TrackIt with 3- to 6-year old children. We look at patterns of in-trial eye-gazing across age and acrosstime.

The ability to maintain attentive state over a period of time (i.e., Selective Sustained Attention) is important for higher- order cognition but challenging to assess in preschool-age children. The TrackIt task was developed to address this challenge and has been argued to be sensitive to age-related differences in selective sustained attention in 3- to 5-year-old children. However, it remains unclear whether this improvement with age also (or predominantly) reflects improvement in children’s knowledge of different shapes used as stimuli in this task in prior studies. The current study addressed this possibility. Consistent with prior studies, we found clear age-related improvement in performance on TrackIt. However, we did not find evidence that shape knowledge played a role in TrackIt performance for children aged 2 to 5, suggesting that increased knowledge of geometric shapes is not sufficient to explain age-related improvement in performance and helping to validate TrackIt as an assessment of Selective Sustained Attention.

Sustained attention is a dynamic process with rich temporalstructure. Eye-tracking provides a tool for capturing rich tem-poral data relevant to sustained attention, but extracting rele-vant insights from this rich data is nontrivial. This paper stud-ies eye-tracking data collected from children, aged 3-5, per-forming the TrackIt task, a visual object tracking paradigm de-signed for studying sustained attention development in youngchildren. Building on a hidden Markov model paradigm re-cently proposed for analyzing eye-tracking data with TrackIt,we explore characterizations of participant behavior, such ascontinuously maintaining attention on an object and transition-ing attention between objects, that provide richer insights thantask performance alone. In particular, our results suggest thatimprovement in TrackIt performance that accompanies devel-opment in this age range may stem more from improved abilityto return to task after distractions, rather than from improve-ments in ability to continuously maintain attention on the task.