Framing the area: An efficient approach for avoiding visual interference and optimising visual search in adolescents

Andersson, U., Lyxell, B. (2007). Working memory deficit in children with mathematical difficulties: A general or specific deficit? Journal of Experimental Child Psychology, 96(3), 197–228. https://doi.org/10.1016/j.jecp.2006.10.001
Google Scholar | Crossref Arnal, L. H., Doelling, K. B., Poeppel, D. (2015). Delta–beta coupled oscillations underlie temporal prediction accuracy. Cerebral Cortex, 25(9), 3077–3085. https://doi.org/10.1093/cercor/bhu103
Google Scholar | Crossref Ayres, P. L. (2001). Systematic mathematical errors and cognitive load. Contemporary Educational Psychology, 26(2), 227–248. https://doi.org/10.1006/ceps.2000.1051
Google Scholar | Crossref Balas, B., Auen, A., Thrash, J., Lammers, S. (2020). Children’s use of local and global visual features for material perception. Journal of Vision, 20(2), Article 10. https://doi.org/10.1167/jov.20.2.10
Google Scholar | Crossref Brascamp, J. W., Blake, R., Kristjánsson, Á. (2011). Deciding where to attend: Priming of pop-out drives target selection. Journal of Experimental Psychology: Human Perception and Performance, 37(6), 1700–1707. https://doi.org/10.1037/a0025636
Google Scholar | Crossref Checa, P., Rueda, M. R. (2011). Behavioral and brain measures of executive attention and school competence in late childhood. Developmental Neuropsychology, 36(8), 1018–1032. https://doi.org/10.1080/87565641.2011.591857
Google Scholar | Crossref Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Academic Press. https://doi.org/10.2307/2290095
Google Scholar | Crossref Desimone, R., Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18(1), 193–222. https://doi.org/10.1146/annurev.ne.18.030195.001205
Google Scholar | Crossref Diamond, A. (2006). The Early Development of Executive Functions. In Bialystok, E., Craik, F. I. M. (Eds.), Lifespan cognition: Mechanisms of change (pp. 70–95). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195169539.003.0006
Google Scholar | Crossref Duncan, J., Humphreys, G. W. (1989). Visual search and stimulus similarity. Psychological Review, 96(3), 433–458. https://doi.org/10.1037/0033-295x.96.3.433
Google Scholar | Crossref Erickson, L. C., Thiessen, E. D., Godwin, K. E., Dickerson, J. P., Fisher, A. V. (2015). Endogenously and exogenously driven selective sustained attention: Contributions to learning in kindergarten children. Journal of Experimental Child Psychology, 138, 126–134. https://doi.org/10.1016/j.jecp.2015.04.011
Google Scholar | Crossref Faul, F., Erdfelder, E., Lang, A. G., Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/bf03193146
Google Scholar | Crossref Fisher, A. V., Godwin, K. E., Seltman, H. (2014). Visual environment, attention allocation, and learning in young children: When too much of a good thing may be bad. Psychological Science, 25(7), 1362–1370. https://doi.org/10.1177/0956797614533801
Google Scholar | SAGE Journals Gathercole, S. E., Alloway, T. P., Willis, C., Adams, A. M. (2006). Working memory in children with reading disabilities. Journal of Experimental Child Psychology, 93(3), 265–281. https://doi.org/10.1016/j.jecp.2005.08.003
Google Scholar | Crossref Gazzaley, A., Clapp, W., Kelley, J., McEvoy, K., Knight, R. T., D’Esposito, M. (2008). Age-related top-down suppression deficit in the early stages of cortical visual memory processing. Proceedings of the National Academy of Sciences, 105(35), 13122–13126. https://doi.org/10.1073/pnas.0806074105
Google Scholar | Crossref Gerlach, C., Poirel, N. (2018). Navon’s classical paradigm concerning local and global processing relates systematically to visual object classification performance. Scientific Reports, 8(1), Article 324. https://doi.org/10.1038/s41598-017-18664-5
Google Scholar | Crossref Hanley, M., Khairat, M., Taylor, K., Wilson, R., Cole-Fletcher, R., Riby, D. M. (2017). Classroom displays—Attraction or distraction? Evidence of impact on attention and learning from children with and without autism. Developmental Psychology, 53(7), 1265–1275. https://doi.org/10.1037/dev0000271
Google Scholar | Crossref Kimchi, R., Hadad, B., Behrmann, M., Palmer, S. E. (2005). Microgenesis and ontogenesis of perceptual organization: Evidence from global and local processing of hierarchical patterns. Psychological Science, 16(4), 282–290. https://doi.org/10.1111/j.0956-7976.2005.01529.x
Google Scholar | SAGE Journals Krakowski, C. S., Borst, G., Pineau, A., Houdé, O., Poirel, N. (2015). You can detect the trees as well as the forest when adding the leaves: Evidence from visual search tasks containing three-level hierarchical stimuli. Acta Psychologica, 157, 131–143. https://doi.org/10.1016/j.actpsy.2015.03.001
Google Scholar | Crossref Maljkovic, V., Nakayama, K. E. N. (1996). Priming of pop-out: II. The role of position. Perception & Psychophysics, 58(7), 977–991. https://doi.org/10.3758/bf03206826
Google Scholar | Crossref Melloni, L., van Leeuwen, S., Alink, A., Müller, N. G. (2012). Interaction between bottom-up saliency and top-down control: How saliency maps are created in the human brain. Cerebral Cortex, 22(12), 2943–2952. https://doi.org/10.1093/cercor/bhr384
Google Scholar | Crossref Mevorach, C., Humphreys, G. W., Shalev, L. (2006). Opposite biases in salience-based selection for the left and right posterior parietal cortex. Nature Neuroscience, 9(6), 740–742. https://doi.org/10.1038/nn1709
Google Scholar | Crossref Mevorach, C., Humphreys, G. W., Shalev, L. (2009). Reflexive and preparatory selection and suppression of salient information in the right and left posterior parietal cortex. Journal of Cognitive Neuroscience, 21(6), 1204–1214. https://doi.org/10.1167/8.6.394
Google Scholar | Crossref Moher, J. (2020). Distracting Objects Induce Early Quitting in Visual Search. Psychological Science, 31(1), 31–42. https://doi.org/10.1177/0956797619886809
Google Scholar | SAGE Journals Moisala, M., Salmela, V., Hietajärvi, L., Salo, E., Carlson, S., Salonen, O., Lonka, K., Hakkarainen, K., Salmela-Aro, K., Alho, K. (2016). Media multitasking is associated with distractibility and increased prefrontal activity in adolescents and young adults. NeuroImage, 134, 113–121. https://doi.org/10.1016/j.neuroimage.2016.04.011
Google Scholar | Crossref Nagy, A. L., Sanchez, R. R. (1990). Critical color differences determined with a visual search task. Journal of the Optical Society of America A, 7(7), 1209–1217. https://doi.org/10.1364/josaa.7.001209
Google Scholar | Crossref Navon, D. (1977). Forest before the trees: The precedence of global features in visual perception. Cognitive Psychology, 9, 353–383. https://doi.org/10.1016/0010-0285(77)90012-3
Google Scholar | Crossref Navon, D. (2003). What does a compound letter tell the psychologist’s mind? Acta Psychologica, 114(3), 273–309. https://doi.org/10.1016/j.actpsy.2003.06.002
Google Scholar | Crossref Ophir, E., Nass, C., Wagner, A. D. (2009). Cognitive control in media multitaskers. Proceedings of the National Academy of Sciences, 106(37), 15583–15587. https://doi.org/10.1073/pnas.0903620106
Google Scholar | Crossref Palmer, J., Verghese, P., Pavel, M. (2000). The psychophysics of visual search. Vision Research, 40(10–12), 1227–1268. https://doi.org/10.1016/s0042-6989(99)00244-8
Google Scholar | Crossref Passolunghi, M. C., Siegel, L. S. (2001). Short-term memory, working memory, and inhibitory control in children with difficulties in arithmetic problem solving. Journal of Experimental Child Psychology, 80(1), 44–57. https://doi.org/10.1006/jecp.2000.2626
Google Scholar | Crossref Poirel, N., Krakowski, C. S., Sayah, S., Pineau, A., Houdé, O., Borst, G. (2014). Do you want to see the tree? Ignore the forest. Experimental Psychology, 61(3), 205–214. https://doi.org/10.1027/1618-3169/a000240
Google Scholar | Crossref Poirel, N., Mellet, E., Houdé, O., Pineau, A. (2008a). First came the trees, then the forest: Developmental changes during childhood in the processing of visual local-global patterns according to the meaningfulness of the stimuli. Developmental Psychology, 44(1), 245–253. https://doi.org/10.1037/0012-1649.44.1.245
Google Scholar | Crossref Poirel, N., Pineau, A., Mellet, E. (2008b). What does the nature of the stimuli tell us about the Global Precedence Effect? Acta Psychologica, 127(1), 1–11. https://doi.org/10.1016/j.actpsy.2006.12.001
Google Scholar | Crossref Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32(1), 3–25. https://doi.org/10.1080/00335558008248231
Google Scholar | SAGE Journals Posner, M. I. (2016). Orienting of attention: Then and now. Quarterly Journal of Experimental Psychology, 69(10), 1864–1875. https://doi.org/10.1080/17470218.2014.937446
Google Scholar | SAGE Journals Rauschenberger, R., Yantis, S. (2001). Attentional capture by globally defined objects. Perception & Psychophysics, 63(7), 1250–1261. https://doi.org/10.3758/bf03194538
Google Scholar | Crossref Rideout, V. J., Foehr, U. G., Roberts, D. F. (2010). Generation M2: Media in the lives of 8-to 18-year-olds (No. 8010). The Kaiser Family Foundation. http://www.kff.org/entmedia/8010.cfm/
Google Scholar Robinson, C. W., Hawthorn, A. M., Rahman, A. N. (2018). Developmental differences in filtering auditory and visual distractors during visual selective attention. Frontiers in Psychology, 9, Article 2564. https://doi.org/10.3389/fpsyg.2018.02564
Google Scholar | Crossref Samaha, J., Bauer, P., Cimaroli, S., Postle, B. R. (2015). Top-down control of the phase of alpha-band oscillations as a mechanism for temporal prediction. Proceedings of the National Academy of Sciences, 112(27), 8439–8444. https://doi.org/10.1073/pnas.1503686112
Google Scholar | Crossref Treisman, A. M., Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12(1), 97–136. https://doi.org/10.1016/0010-0285(80)90005-5
Google Scholar | Crossref Verghese, P. (2001). Visual search and attention: A signal detection theory approach. Neuron, 31(4), 523–535. https://doi.org/10.1016/s0896-6273(01)00392-0
Google Scholar | Crossref Wei, F. Y. F., Wang, Y. K., Klausner, M. (2012). Rethinking college students’ self-regulation and sustained attention: Does text messaging during class influence cognitive learning? Communication Education, 61(3), 185–204. https://doi.org/10.1080/03634523.2012.672755
Google Scholar | Crossref Wolfe, J. M. (1994). Guided search 2.0 a revised model of visual search. Psychonomic Bulletin & Review, 1(2), 202–238. https://doi.org/10.3758/bf03200774
Google Scholar | Crossref Wolfe, J. M. (1996). Extending guided search: Why guided search needs a preattentive “item map..” In Kramer, A. F., Coles, M. G. H., Logan, G. D. (Eds.), Converging operations in the study of visual selective attention (pp. 247–270). American Psychological Association. https://doi.org/10.1037/10187-008
Google Scholar | Crossref Wolfe, J. M. (2007). Guided search 4.0. In Gray, W. D. (Ed.), Integrated models of cognitive systems (pp. 99–119). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195189193.003.0008
Google Scholar | Crossref Wolfe, J. M., Cave, K. R., Franzel, S. L. (1989). Guided search: An alternative to the feature integration model for visual search. Journal of Experimental Psychology: Human Perception and Performance, 15(3), 419–433. https://doi.org/10.1037/0096-1523.15.3.419
Google Scholar | Crossref Wolfe, J. M., Horowitz, T. S. (2004). What attributes guide the deployment of visual attention and how do they do it? Nature Reviews Neuroscience, 5(6), 495–501. https://doi.org/10.1038/nrn1411
Google Scholar | Crossref Zanto, T. P., Gazzaley, A. (2009). Neural suppression of irrelevant information underlies optimal working memory performance. Journal of Neuroscience, 29(10), 3059–3066. https://doi.org/10.1523/jneurosci.4621-08.2009
Google Scholar | Crossref

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