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Learning What to Attend To: from the Lab to the Classroom

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Learning What to Attend To: from the Lab to the Classroom Learning What to Attend to: From the Lab to the Classroom Rachel Wu1, Andria Shimi2, Michael Solis1, and Gaia Scerif 3 Abstract ■ Research in adult cognitive neuroscience addresses the bi- the lifespan. In particular, we review the research program that directional relationship between attentional selection and prior we have developed over the last few years, describe the con- knowledge gained from learning and experience. This research straints that we have faced in integrating adult and developmen- area is ready for integration with developmental cognitive tal paradigms, and delineate suggested next steps to inform neuroscience, in particular with educational neuroscience. We educational neuroscience in more applied ways. Our proposed review one aspect of this research area, learning what to attend path of integration transitions from basic to applied research, to, to propose a path of integration from highly controlled while also suggesting that input from education could inform experiments based on developmental and adult cognitive new basic research avenues that may more likely yield out- theories to inform cognitive interventions for learners across comes meaningful for education. ■ INTRODUCTION to adulthood. We highlight the significance of this re- Many basic research areas in adult cognitive neuroscience search question by placing it within the broader field of have the potential to have translational significance and, cognitive neuroscience and summarize our teams’ find- in turn, generate useful avenues for future basic research. ings over the past few years. We present methodological In particular, adult cognitive neuroscience research that limitations and potential solutions when integrating adult dovetails with developmental cognitive neuroscience cognitive neuroscience and developmental psychology research has the potential to inform educational neuro- and provide justifications for translating from the lab to science. The goals of educational neuroscience are three- the classroom. fold: (1) to better understand underlying neural and behavioral learning mechanisms to improve educational outcomes for all learners, (2) to develop markers that SIGNIFICANCE OF LEARNING WHAT TO can identify learners who are struggling or who are at ATTEND TO risk, and (3) to develop evidence-based therapeutic One research area in adult cognitive neuroscience that is practices to address issues in education (see Ansari, underutilized for bridging basic and applied research Coch, & De Smedt, 2011; Szűcs & Goswami, 2007, for addresses the bidirectional relationship between atten- reviews). Educational neuroscience faces not only the tional selection and prior knowledge gained from learn- challenges of moving from the lab to the classroom (e.g., ing and experience. For the past few years, both as a differences between basic research aims and translational team of collaborating researchers and independently, research aims; Onken, Carrol, Shoham, Cuthbert, & Riddle, we have been investigating this topic in adult cognitive 2014; Weisz, Ng, & Bearman, 2014) but also integrating neuroscience using developmental theories, with the between different basic research areas, such as adult aim of future application to education. We have focused cognitive neuroscience and developmental psychology. on one aspect in particular: learning what to attend. This article briefly reviews our research team’s efforts At least 40 years of experimentation have revealed the in the past few years to integrate adult cognitive neuro- process by which observers find what they are looking for science and developmental psychology to inform educa- (i.e., top–down visual search): The to-be-searched item is tional neuroscience. In particular, we have investigated represented as an “attentional template,” which is a how observers learn what to attend to from childhood prioritized working memory representation, and this template is matched against the current input. Top– down visual search studies have shown that attentional 1University of California, Riverside, 2University of Cyprus, 3Univer- templates can contain a single feature (e.g., shape or sity of Oxford color) or an object (e.g., a red square; e.g., Eimer, © 2018 Massachusetts Institute of Technology Journal of Cognitive Neuroscience 30:12, pp. 1749–1756 doi:10.1162/jocn_a_01316 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_01316 by guest on 23 September 2021 2014; Olivers, Peters, Houtkamp, & Roelfsema, 2011; and children, who have to learn what to attend to and Wolfe & Horowitz, 2004; Desimone & Duncan, 1995; what to learn as they acquire knowledge about potential Treisman & Gelade, 1980), and even a category or a rule targets and distractors (e.g., Wu, Gopnik, Richardson, & (e.g., Wu & Zhao, 2017; Moores, Laiti, & Chelazzi, 2003). Kirkham, 2011; Wu & Kirkham, 2010). In all top–down search tasks, the participant has to learn It is critical to understand how learning to attend what to attend to (i.e., the target). In one-feature search to relevant stimuli develops, as the development of at- studies, the target (i.e., the feature, such as red objects) tentional processes and their neural correlates undergo is typically easy to determine, especially if an example of significant change from infancy into childhood and adult- the target is provided. In more complex category search hood (see Amso & Scerif, 2015; Power, Fair, Schlaggar, & studies, the target (i.e., the category, such as any letter) Petersen, 2010, for reviews). Correlated but distinguish- may require more time and effort to learn. Classic visual able attentional and executive control networks can be search studies have demonstrated limitations in search identified from early in childhood (e.g., Rueda et al., efficiencies when searching for more than one feature 2004), but their connectivity is characterized by increas- (one feature vs. two or more features in conjunctive ing segregation and differentiation from childhood search) or object (one object vs. two or more objects; into adulthood that supports more efficient attention see Olivers et al., 2011, for a review). Category search (e.g., Fair et al., 2008; Grayson et al., 2014; see Power studies have demonstrated that one way around this et al., 2010, for a review). How do these developing limitation is by grouping objects into one unit (i.e., a skills support the ability to identify what is relevant to category; Nako, Wu, & Eimer, 2014; Wu et al., 2013; the task at hand, that is, the ability to learn to attend? see also Moores et al., 2003). Similarly, grouping fea- Our research program on learning what to attend to tures into one object allows for higher search efficien- has focused on searching for abstract categories. Unlike cies for multiple features within that object (e.g., Wu, perceptual categories (i.e., grouping objects based on Pruitt, Runkle, Scerif, & Aslin, 2016). common perceptual features, such as wheels for cars), A parallel and now equally influential focus of research more general or “abstract” categories are created by has investigated how information held in memory guides grouping objects based on rules, associations, or rela- the orienting of attention: A wealth of evidence points to tions. Importantly, there may be high perceptual dissim- the influence of the contents of memory on attentional ilarity within an abstract category (e.g., the numeral “4” selection. The evidence includes both implicit benefits does not look like the numeral “5”), and there may be of repeated learned contexts on visual search (e.g., re- high perceptual similarity between abstract categories peated spatial arrangement of objects facilitates speed (e.g., the numeral “5” shares features with the letter of target selection, albeit without explicit recollection; “S”). Constructing abstract categories (e.g., letters, num- Chun & Jiang, 1998) and explicit memory of information bers, food, toys) is a critical skill for young children to encoded during visual search of complex or naturalistic master because these categories play a prominent role scenes (such as recalling as precisely as possible a previ- in many facets of everyday cognition. In particular, from ously learned target location in a scene), which are preschool to early school age (i.e., 3–6 years of age), chil- effects that depend on the interplay between fronto- dren have to learn categories important for education parietal and hippocampal circuits (e.g., Patai, Doallo, & (e.g., numbers and letters). Incorrect construction of Nobre, 2012; Stokes, Atherton, Patai, & Nobre, 2012; these new categories, both at the level of the precision of Summerfield, Lepsien, Gitelman, Mesulam, & Nobre, exemplars within each category and at the level of the in- 2006). As a whole, this literature highlights that atten- efficient use or manipulation of these categories, may re- tional processes influence and are influenced by what is sult in poorer academic outcomes and more advanced learned by adult observers. learning that has, at its core, those categories as building Decades of cognitive neuroscience research have blocks. For example, a growing literature emphasizes the focused on the mechanisms and nature of visual atten- importance of symbolic representations of number as the tion for known targets by adults and more recently on foundations for more complex arithmetic (e.g., Bartelet, the interplay between attention and memory in adults. Vaessen, Blomert, & Ansari, 2014; Holloway & Ansari, In a complementary but novel fashion,
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