Current research programs
For publications, please scroll down.
Learning from learners
Adapting infant learning strategies may be important for slowing cognitive decline in older adults. In particular, there are six aspects in the environment and within infants and children that help these young learners learn so efficiently: Open-minded, input-driven learning (learning new patterns, new skills, exploring outside of one’s comfort zone); Individualized scaffolding (consistent access to teachers and mentors who guide learning); Growth mindset (belief that abilities are developed with effort); Forgiving environment (allowed to make mistakes and even fail); Serious commitment to learning (learn to master essential skills rather than hobbies, persevere despite setbacks); Learning multiple skills simultaneously (such as developing language, motor, visual, and social skills).
- Wu, Rebok, & Lin (2017)
- Leanos et al. (2018)
- Wu & Rebok (in press)
- Wu & Strickland-Hughes (2019)
- Leanos et al. (2019)
- Nguyen et al. (2020)
The benefits and costs of knowledge
By young adulthood, we have acquired valuable knowledge that lets us be efficient in the real world (such as shopping at a grocery store and finding what you want). One example of how knowledge is useful is that young adults can find one object (such as carrots) very quickly (by 200 milliseconds). Young adults can even search for a whole category such as “any healthy food” by 200 milliseconds. However, the cost of knowledge is that previous knowledge can be distracting in situations when they are not as relevant. For example, the letter “R” will distract you when searching for the letter “A” because you know that they are both letters. Our studies show that these costs seem to emerge from increased knowledge. This line of research investigates what the benefits and costs of knowledge are for young adults, and how they deal with them as “peak performers” in the lifespan. Future research will extend this work to aging adults who may not deal as well with the costs of knowledge. These studies use neural (EEG) and behavioral responses (reaction time and accuracy).
- Wu, Scerif et al. (2013)
- Nako, Wu, & Eimer (2014)
- Nako, Wu, Smith, & Eimer (2014)
- Wu, Nako et al. (2015) [press release] [print media]
- Wu, Pruitt et al. (2016) [press release] [print media]
- Wu, Pruitt, Zinszer, & Cheung (2017)
- Wu & Zhao (2017)
- Wu et al. (2018a)
- Wu et al. (2018b)
- Bayet et al. (2018)
- van Bergen et al. (2019)
Learning what to learn
Infants have relatively little knowledge compared to adults. The upside to this is that infants are capable of learning many things that are difficult for adults (such as language). The downside is that infants have difficulty choosing what to learn when confronted with a lot of information. This problem is typically solved in adults by knowledge – our previous knowledge tells us what is relevant or not relevant to learn. To solve this problem during infancy, this line of research has found that infants start using people to choose what objects to learn about by 8 months of age. This skill is important to develop because people are powerful tools to help infant learners figure out what is relevant to learn. Without this shortcut, learners may take longer paths to relevant information or even divergent paths to irrelevant information. For these studies, we use eye-trackers to measure where and for how long infants look to determine what they learn.
- Wu, R., Qian, T., & Aslin, R. N. (2019). No evidence that abstract structure learning disrupts novel-event learning in 8- to 11-month-olds. Frontiers in Psychology, 10, 498.
- Wu, R. (2019). Learning what to learn across the lifespan: From objects to real-world skills. Current Directions in Psychological Science, 28(4) 392-397.
- van Bergen, G., Flecken, M., & Wu, R. (2019). Rapid target selection of object categories based on verbs: Implications for language-categorization interactions. Psychophysiology, 56(9), e13395.
- Wu, R., & Strickland-Hughes, C. (2019). Adaptation for growth as a common goal throughout the lifespan: Why and how. Psychology of Learning and Motivation, 71, 387-414.
- Leanos, S., Kurum, E., Strickland-Hughes, C., Ditta, A., Nguyen, G., Felix, M., Yum, H., Rebok, G. W., & Wu, R. (2019). The impact of learning multiple real-world skills on cognitive abilities and functional independence in healthy older adults. Journals of Gerontology: Series B Psychological Sciences, gbz084. [NBC coverage]
- Hoemann, K.*, Wu, R.*, LoBue, V.*, Oakes, L.*, Xu, F., & Feldman Barrett, L.* (2020). Developing an understanding of emotion categories: Lessons from objects. Trends in Cognitive Sciences, 24(1), 39-51. (*equal authorship)
- Nguyen, C., Leanos, S., Natsuaki, M., Rebok, G., & Wu, R. (2020). Adaptation for growth via learning new skills as a means to long-term functional independence in older adulthood: Insights from emerging adulthood. The Gerontologist, 60(1), 4-11. [press release]
- Wu, R., & Rebok, G. (2020). Maximizing the impact of cognitive engagement interventions. In A. Thomas & A. Gutchess, Handbook of Cognitive Aging: A Life Course Perspective, pp. 685-700. Cambridge University Press.
- Ditta, A., Strickland-Hughes, C., Cheung, C., & Wu, R. (2020). Exposure to information increases motivation to learn more. Learning and Motivation. Epub ahead of print.
- Bayet, L., Zinszer, B., Pruitt, Z., Aslin, R. N., & Wu, R. (2018). Dynamics of neural representations when searching for human and non-human faces. Scientific Reports, 8, 13277.
- Wu, R., Shimi, A., Solis, M., & Scerif, G. (2018). Learning what to attend to: From the lab to the classroom. Journal of Cognitive Neuroscience, 30(12), 1749-1756.
- Leanos, S., Coons, J., Rebok, G. W., Ozer, D. J., & Wu, R. (2018). Development of the Broad Learning Adult Questionnaire (BLAQ). The International Journal of Aging and Human Development, 88(3), 286-311.
- Wu, R., McGee, B., Rubenstein, M., Pruitt, Z., Cheung, O., & Aslin, R. N. (2018). Emergence of the benefits and costs of grouping for visual search. Psychophysiology, 55(9), e13087.
- Wu, R., McGee, B., Echiverri, C., & Zinszer, B. (2018). Prior knowledge of category size impacts visual search. Psychophysiology, 55(8) e13075.
- Quiñones-Camacho, L., Wu, R., & Davis, E. L. (2018). Motivated attention to fear-related stimuli: Evidence for the enhanced processing of fear in the Late Positive Potential. Motivation and Emotion, 42(2), 299-308.
- Lin, F., Wang, X., Wu, R., Rebok, G., Chapman, B. (2017). Identification of successful cognitive aging in the Alzheimer’s Disease Neuroimaging Initiative Study. Journal of Alzheimer’s Disease, 59(1), 101-111.
- Wu, R., & Zhao, J-Y. (2017). The “item” as a window into how prior knowledge guides visual search. Behavioral and Brain Sciences, 40, e162.
- Wu, R., & Zhao, J. (2017). Prior knowledge of object associations shapes attentional templates and information acquisition. Frontiers in Psychology, 8(843), 1-6.
- Xiao, N. G.*, Wu, R.*, Quinn, P. C., Liu, S., Tummeltshammer, K. S., Kirkham, N. Z., Ge, L., Pascalis, O., & Lee, K. (2017). Infants rely more on social cues from own-race than other-race adults for learning under uncertainty. Child Development, epub ahead of print. (*co-first author)
- Wu, R., Rebok, G. W., & Lin, F. V. (2017). A novel theoretical life course framework for triggering cognitive development across the lifespan. Human Development, 56(6), 342-365. [press release]
- Wu, R., Pruitt, Z., Zinszer, B., & Cheung, O. (2017). Increased experience amplifies the activation of task-irrelevant category representations. Attention, Perception, and Psychophysics, 79(2), 522-532.
- Wu, R., Pruitt, Z., Runkle, M., Meyer, K., Scerif, G., & Aslin, R. N. (2016). A neural signature of rapid category-based target selection as a function of intra-item perceptual similarity despite inter-item dissimilarity. Attention, Perception, and Psychophysics, 78(3), 749-760. [press release] [print media]
- Wu, R., Nako, R., Band, J., Pizzuto, J., Shadravan, Y., Scerif, G., & Aslin, R. N. (2015). Rapid selection of non-native stimuli despite perceptual narrowing. Journal of Cognitive Neuroscience, 27(11), 2299-2307. [press release] [print media]
- Tummeltshammer, K. A., Wu, R., Sobel, D., & Kirkham, N. Z. (2014). Infants track the reliability of potential informants. Psychological Science, 25(9), 1730-1738.
- Nako, R., Wu, R., & Smith, T. J., & Eimer, M. (2014). Item and category-based attentional control during search for real- world objects: Can you find the pants among the pans? Journal of Experimental Psychology: Human Perception and Performance, 40(4), 1283-1288.
- Papageorgiou, K. A., Smith, T. J., Wu, R., Johnson, M. H., Kirkham, N. Z., & Ronald, A. (2014). Individual differences in infant fixation duration relate to child attention and behavioral control in childhood. Psychological Science, 25(7), 1371-1379.
- Wu, R., Tummeltshammer, K. S., Gliga, T., & Kirkham, N. Z. (2014). Ostensive signals support learning from novel attention cues during infancy. Frontiers in Psychology, 5:251. doi: 10.3389/fpsyg.2014.00251.
- Scerif, G., & Wu, R. (2014). Developmental Disorders. In A.C. Nobre & S. Kastner (Eds.) The Oxford Handbook of Attention. Oxford: OUP.
- Nako, R.*, Wu, R.*, & Eimer, M. (2014). Rapid guidance of visual search by object categories. Journal of Experimental Psychology: Human Perception and Performance, 40(1), 50-60. (* equal authorship)
- Lloyd-Fox, S., Wu, R., Richards, J., Elwell, C., & Johnson, M. H. (2013). Cortical activation to action perception is associated with action production abilities in young infants. Cerebral Cortex. doi: 10.1093/cercor/bht207
- Wu, R., Scerif, G., Aslin, R. N., Smith, T. J., Nako, R., & Eimer, M. (2013). Searching for something familiar or novel: Top-down attentional selection of specific items or object categories. Journal of Cognitive Neuroscience, 25(5), 719-729.
- Wu, R. (2013). Learning from learners. The Psychologist, 26(2), 550-551.
- Yurovsky, D., Hidaka, S., & Wu, R. (2012). Quantitative linking hypotheses for infant eye movements. PLoS One, 7(10), e47419.
- Kirkham, N. Z., Richardson, D. C., Wu, R., & Johnson, S. P. (2012). The importance of ‘what’: Infants use featural information to index events. Journal of Experimental Child Psychology, 113(3), 430-439.
- Karmiloff-Smith, A., Broadbent, H., Farran, E. K., Longhi, E., D’Souza, D., Metcalfe, K., Tassabehji, M., Wu, R., Senju, A., Happe, F., Turnpenny, P., & Sansbury, F. (2012). Social cognition in Williams Syndrome: Insights from partial deletion patients. Frontiers in Developmental Psychology, 3:168. doi: 10.3389/fpsyg.2012.00168
- Morse, A., Hannagan, T., & Wu, R. (2012). Bring on the loop! Commentary on Rohlfing, K. J. & Wrede, B.: What Novel Scientific and Technological Questions Developmental Robotics Bring to HRI? Are we Ready for a Loop? IEEE Transactions on Autonomous Mental Development, 9, 10-11.
- Wu, R., Gopnik, A., Richardson, D. C., & Kirkham, N. Z. (2011). Infants learn about objects from statistics and people. Developmental Psychology, 47(5), 1220-1229. doi: 10.1037/a0024023
- Wu, R., Mareschal, D., & Rakison, D. H. (2011). Attention to multiple cues during spontaneous object labeling. Infancy, 16(5), 545–556. doi: 10.1111/j.1532-7078.2010.00061.x
- Wu, R., & Kirkham, N. Z. (2010). No two cues are alike: Depth of learning during infancy is dependent on what orients attention. Journal of Experimental Child Psychology, 107, 118-136. doi:10.1016/j.jecp.2010.04.014
- Wu, R. (in press). Cross-pollination in cognitive development. In M. H. Bornstein, M. E. Arterberry, K. L. Fingerman, & J. E. Lansford (Eds.) SAGE Encyclopedia of Lifespan Human Development (pp. XXX-XXX). Thousand Oaks, CA: SAGE.
- Wu, R., & Hannagan, T. (in press). Learning. In M. H. Bornstein, M. E. Arterberry, K. L. Fingerman, & J. E. Lansford (Eds.) SAGE Encyclopedia of Lifespan Human Development (pp. XXX-XXX). Thousand Oaks, CA: SAGE.
- Wu, R., & Scerif, G. (in press). Attention. In M. H. Bornstein, M. E. Arterberry, K. L. Fingerman, & J. E. Lansford (Eds.) SAGE Encyclopedia of Lifespan Human Development (pp. XXX-XXX). Thousand Oaks, CA: SAGE.
- Swan, K. A., Wu, R., & Kirkham, N. Z. (2013). 8-month-olds know which face is reliable. In M. Knauff, M Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Berlin, Germany: Cognitive Science Society.
- Wu, R., & Kirkham, N. Z. (2012). Learning (to learn) from spatial attention cues during infancy. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 1161-1166). Sapporo, Japan: Cognitive Science Society.
- Yurovsky, D., Hidaka, S., & Wu, R. (2012). Quantitative Linking Hypotheses for Infant Eye Movements. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society. Sapporo, Japan: Cognitive Science Society.
- Hannagan, T., & Wu, R. (2011). Cued multimodal learning in infancy: A neuro-computational model. In C. Hoelscher, T. F. Shipley, & L. Carlson (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Boston, MA: Cognitive Science Society.
- Yurovsky, D., Wu, R., Yu, C., Kirkham, N. Z., & Smith, L. B. (2011). Model selection for eye movements: assessing the role of attentional cues in infant learning. In E. J. Davelaar (Ed.), Connectionist models of neurocognition and emergent behavior: From theory to applications (pp. 58-75). Singapore: World Scientific.
- Wu, R., Kirkham, N. Z., Swan, K. A., & Gliga, T. (2011). Social signals scaffold learning from novel cues during infancy. In B. Kokinov, A. Karmiloff-Smith, & N. Nersessian (Eds.), Proceedings of the European Conference on Cognitive Science. Sofia, Bulgaria: New Bulgarian University Press. Awarded Best Student Paper Prize.
- Wu, R., Gopnik, A., Richardson, D. C., & Kirkham, N. Z. (2010). Social cues support learning about objects from statistics in infancy. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 1228-1233). Portland, OR: Cognitive Science Society.
Funding agencies and sponsors
Learning to Attend, Attending to Learn: Neurological, Behavioral, and Computational Perspectives
Organizers: Gedeon Deak, Richard Aslin, R. Wu, & Rebecca Nako. UCSD, San Diego, CA (Nov 6-7, 2013)
Gaze, Bias, Learning II: Linking Computation, Neuroscience, and Cognitive Development
Invited speakers: Shinsuke Shimojo, Takashi Omori, Masamichi Sakagami, Jan Lauwereyns, Shohei Hidaka, Hideyuki Takahashi, & R. Wu, Tamagawa University, Tokyo (March 12, 2012)
Gaze, Bias, Learning: Linking Computation, Neuroscience, and Cognitive Development (afternoon workshop)
How to get ahead in academia in 5 countries (morning workshop)
Invited speakers: Jan Lauwereyns, Jochen Triesch, Gaia Scerif, Thomas Hannagan, Eddy Davelaar, & R. Wu, Birkbeck, London (January 23, 2012)