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Part I - Cognitive Development

Published online by Cambridge University Press:  11 May 2017

Nancy Budwig
Clark University, Massachusetts
Elliot Turiel
University of California, Berkeley
Philip David Zelazo
University of Minnesota
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Publisher: Cambridge University Press
Print publication year: 2017

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Anderson, J. R. (1993). Rules of the mind. Hillsdale, NJ: Lawrence Erlbaum.Google ScholarPubMed
Baetu, I., & Shultz, T. R. (2010). Development of prototype abstraction and exemplar memorization. In Ohlsson, S. & Catrambone, R. (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 814819). Austin, TX: Cognitive Science Society.Google Scholar
Baluja, S., & Fahlman, S. E. (1994). Reducing network depth in the cascade-correlation learning architecture. Pittsburgh, PA: School of Computer Science, Carnegie Mellon University.CrossRefGoogle Scholar
Berthiaume, V. G., Shultz, T. R., & Onishi, K. H. (2013). A constructivist connectionist model of developmental transitions on false-belief tasks. Cognition, 126(3), 441458.CrossRefGoogle Scholar
Buckingham, D., & Shultz, T. R. (1996). Computational power and realistic cognitive development Proceedings of the 18th Annual Conference of the Cognitive Science Society (pp. 507511). Mahwah, NJ: Erlbaum.Google Scholar
Buckingham, D., & Shultz, T. R. (2000). The developmental course of distance, time, and velocity concepts: A generative connectionist model. Journal of Cognition and Development, 1, 305345.CrossRefGoogle Scholar
Dandurand, F., & Shultz, T. R. (2014). A comprehensive model of development on the balance-scale task. Cognitive Systems Research, 31 –32, 125. doi: Scholar
Egri, L., & Shultz, T. R. (2006). A compositional neural-network solution to prime-number testing. In Sun, R. & Miyake, N. (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 12631268). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Fahlman, S. E., & Lebiere, C. (1990). The cascade-correlation learning architecture. In Touretzky, D. S. (Ed.), Advances in neural information processing systems 2 (pp. 524532). Los Altos, CA: Morgan Kaufmann.Google Scholar
Fodor, J. (1980). On the impossibility of learning “more powerful” structures. In Piattelli-Palmarini, M. (Ed.), The debate between Jean Piaget and Noam Chomsky (pp. 142152). London: Routledge & Kegan Paul.Google Scholar
Gerken, L. A., Balcomb, F. K., & Minton, J. L. (2011). Infants avoid “labouring in vain” by attending more to learnable than unlearnable linguistic patterns. Developmental Science, 14(5), 972979.CrossRefGoogle ScholarPubMed
Griffiths, T. L., Kemp, C., & Tenenbaum, J. B. (2008). Bayesian models of cognition. In Sun, R. (Ed.), The Cambridge handbook of computational psychology (pp. 59100). Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Hinton, G. E., Osindero, S., & Teh, Y. (2006). A fast learning algorithm for deep belief nets. Neural Computation, 18, 15271554.CrossRefGoogle ScholarPubMed
Jamrozik, A., & Shultz, T. R. (2007). Learning the structure of a mathematical group. In McNamara, D. & Trafton, G. (Eds.), Proceedings of the 29th Annual Conference of the Cognitive Science Society (pp. 11151120). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Kidd, C., Piantadosi, S. T., & Aslin, R. N. (2010). The Goldilocks Effect: Infants’ preference for stimuli that are neither too predictable nor too surprising. In Ohlsson, S. & Catrambone, R. (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 24762481). Austin, TX: Cognitive Science Society.Google Scholar
Kidd, C., Piantadosi, S. T., & Aslin, R. N. (2012). The Goldilocks Effect: Human infants allocate attention to visual sequences that are neither too simple nor too complex. PLoS ONE, 7(5), e36399. doi: 10.1371/journal.pone.0036399CrossRefGoogle ScholarPubMed
Lany, J., Gómez, R. L., & Gerken, L. (2007). The role of prior experience in language acquisition. Cognitive Science, 31, 481507.CrossRefGoogle ScholarPubMed
Mareschal, D., & Shultz, T. R. (1999). Development of children’s seriation: A connectionist approach. Connection Science, 11, 149186.CrossRefGoogle Scholar
Piaget, J., Inhelder, B., & Szeminska, A. (1999). The child’s conception of geometry. Abingdon, UK: Routledge.Google Scholar
Quartz, S. R. (2003). Learning and brain development: A neural constructivist perspective. In Quinlan, P. T. (Ed.), Connectionist models of development: developmental processes in real and artificial neural networks (pp. 279309). New York: Psychology Press.Google Scholar
Schlimm, D., & Shultz, T. R. (2009). Learning the structure of abstract groups. In Taatgen, N. A. & Rijn, H. v. (Eds.), Proceedings of the 31st annual conference of the Cognitive Science Society (pp. 29502955). Austin, TX: Cognitive Science Society.Google Scholar
Shultz, T. R. (1998). A computational analysis of conservation. Developmental Science, 1, 103126.CrossRefGoogle Scholar
Shultz, T. R. (2001). Assessing generalization in connectionist and rule-based models under the learning constraint. Proceedings of the 23rd annual conference of the Cognitive Science Society (pp. 922927). Mahwah, NJ: Erlbaum.Google Scholar
Shultz, T. R. (2003). Computational developmental psychology. Cambridge, MA: MIT Press.Google Scholar
Shultz, T. R. (2006). Constructive learning in the modeling of psychological development. In Munakata, Y. & Johnson, M. H. (Eds.), Processes of change in brain and cognitive development: Attention and performance XXI. (pp. 6186). Oxford, UK: Oxford University Press.Google Scholar
Shultz, T. R. (2011). Computational modeling of infant concept learning: The developmental shift from features to correlations. In Oakes, L. M., Cashon, C. H., Casasola, M., & Rakison, D. H. (Eds.), Infant perception and cognition: Recent advances, emerging theories, and future directions (pp. 125152). New York: Oxford University Press.Google Scholar
Shultz, T. R., & Bale, A. C. (2001). Neural network simulation of infant familiarization to artificial sentences: Rule-like behavior without explicit rules and variables. Infancy, 2, 501536.CrossRefGoogle Scholar
Shultz, T. R., & Bale, A. C. (2006). Neural networks discover a near-identity relation to distinguish simple syntactic forms. Minds and Machines, 16, 107139.CrossRefGoogle Scholar
Shultz, T. R., Berthiaume, V. G., & Dandurand, F. (2010). Bootstrapping syntax from morpho-phonology Proceedings of the Ninth IEEE International Conference on Development and Learning (pp. 5257). Ann Arbor, MI: IEEE.Google Scholar
Shultz, T. R., Buckingham, D., & Oshima-Takane, Y. (1994). A connectionist model of the learning of personal pronouns in English. In Hanson, S. J., Petsche, T., Kearns, M., & Rivest, R. L. (Eds.), Computational learning theory and natural learning systems, Vol. 2: Intersection between theory and experiment (pp. 347362). Cambridge, MA: MIT Press.Google Scholar
Shultz, T. R., & Cohen, L. B. (2004). Modeling age differences in infant category learning. Infancy, 5, 153171.CrossRefGoogle Scholar
Shultz, T. R., & Doty, E. (2014). Knowing when to quit on unlearnable problems: another step towards autonomous learning. Computational Models of Cognitive Processes (pp. 211221). London: World Scientific.CrossRefGoogle Scholar
Shultz, T. R., Doty, E., & Dandurand, F. (2012). Knowing when to abandon unproductive learning. In Miyake, N., Peebles, D., & Cooper, R. P. (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 23272332). Austin, TX: Cognitive Science Society.Google Scholar
Shultz, T. R., & Fahlman, S. E. (2010). Cascade-correlation. In Sammut, C. & Webb, G. I. (Eds.), Encyclopedia of Machine Learning, Part 4/C (pp. 139147). Heidelberg, Germany: Springer-Verlag.Google Scholar
Shultz, T. R., & Gerken, L. A. (2005). A model of infant learning of word stress. Proceedings of the 27th Annual Conference of the Cognitive Science Society (pp. 20152020). Mahwah, NJ: Erlbaum.Google Scholar
Shultz, T. R., Mysore, S. P., & Quartz, S. R. (2007). Why let networks grow? In Mareschal, D., Sirois, S., Westermann, G., & Johnson, M. H. (Eds.), Neuroconstructivism: Perspectives and prospects (Vol. 2, pp. 6598). Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
Shultz, T. R. & Rivest, F. (2001). Knowledge-based cascade-correlation: Using knowledge to speed learning. Connection Science, 13, 130.CrossRefGoogle Scholar
Shultz, T. R., Rivest, F., Egri, L., Thivierge, J.-P., & Dandurand, F. (2007). Could knowledge-based neural learning be useful in developmental robotics? The case of KBCC. International Journal of Humanoid Robotics, 4, 245279.CrossRefGoogle Scholar
Shultz, T. R., Thivierge, J. P., & Laurin, K. (2008). Acquisition of concepts with characteristic and defining features. In Love, B. C., McRae, K., & Sloutsky, V. M. (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 531536). Austin, TX: Cognitive Science Society.Google Scholar
Shultz, T. R., & Vogel, A. (2004). A connectionist model of the development of transitivity. Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 12431248). Mahwah, NJ: Erlbaum.Google Scholar
Sirois, S., & Shultz, T. R. (1998). Neural network modeling of developmental effects in discrimination shifts. Journal of Experimental Child Psychology, 71, 235274.CrossRefGoogle ScholarPubMed
Sirois, S., & Shultz, T. R. (2006). Preschoolers out of adults: Discriminative learning with a cognitive load. Quarterly Journal of Experimental Psychology, 59, 13571377.CrossRefGoogle ScholarPubMed
Spencer, J. P., Austin, A., & Schutte, A. R. (2012). Contributions of dynamic systems theory to cognitive development. Cognitive Development, 27, 401418.CrossRefGoogle ScholarPubMed
Wilkening, F. (1981). Integrating velocity, time, and distance information: a developmental study. Cognitive Psychology, 13, 231247.CrossRefGoogle ScholarPubMed
Aboud, F. E. (1988). Children and prejudice. Oxford: Basil Blackwell.Google ScholarPubMed
Aboud, F. E. (2008). A social-cognitive developmental theory of prejudice. In Quintana, S. M. & McKown, C. (Eds.) Handbook of race, racism, and the developing child (pp. 5571). New Jersey: John Wiley & Sons.Google Scholar
Aboud, F. E. (2013). What are they thinking? The mystery of young children’s thoughts on race. In Banaji, M. R. & Gelman, S. A. (Eds.), Navigating the social world: What infants, children, and other species can teach us (pp. 332335). New York: Oxford University Press.CrossRefGoogle Scholar
Aboud, F. E., Tredoux, C., Tropp, L. R., Brown, C. S., Niens, U., & Noor, N. M. (2012). Interventions to reduce prejudice and enhance inclusion and respect for ethnic differences in early childhood: A systematic review. Developmental Review, 32, 307336. doi: 10.1016/j.dr.2012.05.001CrossRefGoogle Scholar
Allport, G. W. (1954). The nature of prejudice. New York: Basic Books.Google Scholar
Anzures, G., Kelly, D. J., Pascalis, O., Quinn, P. C., Slater, A. M., de Viviés, X., & Lee, K. (2014). Own- and other-race face identity recognition in children: The effects of pose and feature composition. Developmental Psychology, 50, 469481.CrossRefGoogle ScholarPubMed
Anzures, G., Pascalis, O., Quinn, P. C., Slater, A. M., & Lee, K. (2011). Minimizing skin color differences does not eliminate the own-race recognition advantage in infants. Infancy, 16, 640654. PMCID: PMC3203025CrossRefGoogle Scholar
Anzures, G., Quinn, P. C., Pascalis, O., Slater, A. M., & Lee, K. (2013a). Development of own-race biases. Visual Cognition, 21, 1165.CrossRefGoogle Scholar
Anzures, G., Quinn, P. C., Pascalis, O., Slater, A. M., Tanaka, J. W., & Lee, K. (2013b). Developmental origins of the other-race effect. Current Directions in Psychological Science, 22, 173178.CrossRefGoogle ScholarPubMed
Bahrick, L. E., & Lickliter, R. (2000). Intersensory redundancy guides attentional selectivity and perceptual learning in infancy. Developmental Psychology, 36, 190201.CrossRefGoogle ScholarPubMed
Balas, B., & Quinn, P. C. (2015, March). Simulating classification of face race by infants: Similarities and differences between model and infant looking performance. Paper presented at the Meeting of the Society for Research in Child Development, Philadelphia, PA.Google Scholar
Banaji, M. R., & Greenwald, A. G. (2013). Blindspot: Hidden biases of good people. New York: Delacorte Press.Google Scholar
Bar-Haim, Y., Ziv, T., Lamy, D., & Hodes, R. M. (2006). Nature and nurture in own-race face processing. Psychological Science, 17, 159163.CrossRefGoogle ScholarPubMed
Baron, A. S., & Banaji, M. R. (2006). The development of implicit attitudes evidence of race evaluations from ages 6 and 10 and adulthood. Psychological Science, 17, 5358. doi: 10.1111/j.1467–9280.2005.01664.xCrossRefGoogle ScholarPubMed
Bigler, R. S. (2013). Understanding and reducing social stereotyping and prejudice among children. In Banaji, M. R. & Gelman, S. A. (Eds.), Navigating the social world: What infants, children, and other species can teach us (pp. 327331). New York: Oxford University Press.CrossRefGoogle Scholar
Bigler, R. S., & Liben, L. S. (2007). Developmental intergroup theory explaining and reducing children’s social stereotyping and prejudice. Current Directions in Psychological Science, 16, 162166. doi: 10.1111/j.1467-8721.2007.00496.xCrossRefGoogle Scholar
Cameron, L., Rutland, A., Brown, R., & Douch, R. (2006). Changing children’s intergroup attitudes toward refugees: Testing different models of extended contact. Child Development, 77, 12081219. doi: 10.1111/j.1467-8624.2006.00929.xCrossRefGoogle ScholarPubMed
Castelli, L., De Amicis, L., & Sherman, S. J. (2007). The loyal member effect: on the preference for ingroup members who engage in exclusive relations with the ingroup. Developmental Psychology, 43, 13471359. doi: 10.1037/0012-1649.43.6.1347CrossRefGoogle ScholarPubMed
Corriveau, K. H., Fusaro, M., & Harris, P. L. (2009). Going with the flow: Preschoolers prefer nondissenters as informants. Psychological Science, 20, 372377.CrossRefGoogle ScholarPubMed
Cunningham, W. A., Preacher, K. J., & Banaji, M. R. (2001). Implicit attitude measures: Consistency, stability, and convergent validity. Psychological Science, 12, 163170. doi: 10.1111/1467-9280.00328CrossRefGoogle ScholarPubMed
Degner, J., & Dalege, J. (2013). The apple does not fall far from the tree, or does it? A meta-analysis of parent–child similarity in intergroup attitudes. Psychological Bulletin, 139, 12701304. doi: 10.1037/a0031436CrossRefGoogle ScholarPubMed
Devine, P. G. (1989). Stereotypes and prejudice: their automatic and controlled components. Journal of Personality and Social Psychology, 56, 518.CrossRefGoogle Scholar
Dovidio, J. F., Kawakami, K., & Gaertner, S. L. (2002). Implicit and explicit prejudice and interracial interaction. Journal of Personality and Social Psychology, 82, 6268.CrossRefGoogle ScholarPubMed
Dunham, Y., Baron, A. S., & Banaji, M. R. (2006). From American city to Japanese village: A cross-cultural investigation of implicit race attitudes. Child Development, 77, 12681281. doi: 10.1111/j.1467-8624.2006.00933.xCrossRefGoogle ScholarPubMed
Dunham, Y., Baron, A. S., & Banaji, M. R. (2007). Children and social groups: A developmental analysis of implicit consistency in Hispanic Americans. Self and Identity, 6, 238255. doi: 10.1080/15298860601115344CrossRefGoogle Scholar
Dunham, Y., Baron, A. S., & Banaji, M. R. (2008). The development of implicit intergroup cognition. Trends in Cognitive Sciences, 12, 248253. doi: 10.1016/j.tics.2008.04.006CrossRefGoogle ScholarPubMed
Dunham, Y., Baron, A. S., & Carey, S. (2011). Consequences of “minimal” group affiliations in children. Child Development, 82, 793811. doi: 10.1111/j.1467–8624.2011.01577.xCrossRefGoogle ScholarPubMed
Dunham, Y., Chen, E. E., & Banaji, M. R. (2013). Two signatures of implicit intergroup attitudes: Developmental invariance and early enculturation. Psychological Science, 24, 860868. doi: 10.1177/0956797612463081CrossRefGoogle Scholar
Dunham, Y., Newheiser, A., Hoosain, L., Merrill, A., & Olson, K. R. (2014). From a different vantage: Intergroup attitudes among children from low- and intermediate-status racial groups. Social Cognition, 32, 121. doi: 10.1521/soco.2014.32.1.1CrossRefGoogle Scholar
Feddes, A. R., Noack, P., & Rutland, A. (2009). Direct and extended friendship effects on minority and majority children’s interethnic attitudes: A longitudinal study. Child Development, 80, 377390. doi: 10.1111/j.1467-8624.2009.01266.xCrossRefGoogle ScholarPubMed
Feinman, S. (1980). Infant response to race, size, proximity, and movement of strangers. Infant Behavior and Development, 3, 187204. doi: 10.1016/S0163-6383(80)80025-7CrossRefGoogle Scholar
Gaither, S. E., Pauker, K., & Johnson, S. P. (2012). Biracial and monoracial infant own-race face perception: An eye tracking study. Developmental Science, 15, 775782.CrossRefGoogle Scholar
Gawronski, B., & Bodenhausen, G. V. (2006). Associative and propositional processes in evaluation: an integrative review of implicit and explicit attitude change. Psychological Bulletin, 132, 692731.CrossRefGoogle ScholarPubMed
Gergely, G., Egyed, K., & Kiraly, I. (2007). On pedagogy. Developmental Science, 10, 139146.CrossRefGoogle ScholarPubMed
Greenwald, A. G., & Banaji, M. R. (1995). Implicit social cognition: Attitudes, self-esteem, and stereotypes. Journal of Personality and Social Psychology, 102, 427. doi: 10.1037/0033-295X.102.1.4Google Scholar
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of Personality and Social Psychology, 74, 14641480. doi: 10.1037/0022-3514.74.6.1464CrossRefGoogle Scholar
Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the implicit association test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85, 197216. doi: 10.1037/0022-3514.85.2.197CrossRefGoogle ScholarPubMed
Greenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R. (2009). Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity. Journal of Personality and Social Psychology, 97, 1741. doi: 10.1037/a0015575CrossRefGoogle ScholarPubMed
Grossmann, T., Striano, T., & Friederici, A. D. (2006). Crossmodal integration of emotional information from face and voice in the infant brain. Developmental Science, 9, 309315.CrossRefGoogle ScholarPubMed
Hadley, H., Pickron, C. B., & Scott, L. S. (2015). The lasting effects of process-specific versus stimulus-specific learning during infancy. Developmental Science, 18, 842852.CrossRefGoogle ScholarPubMed
Hardin, C. D., & Banaji, M. R. (2013). The nature of implicit prejudice: Implications for personal and public policy. In Shafir, E. (Ed.), The behavioral foundations of public policy (pp. 1331). Princeton, NJ: Princeton University Press.Google Scholar
Hepper, P. (2015). Behavior during the prenatal period: Adaptive for development and survival. Child Development Perspectives, 9, 3843.CrossRefGoogle Scholar
Hetherington, C., Hendrickson, C., & Koenig, M. (2014). Reducing an in-group bias in preschool children: the impact of moral behavior. Developmental Science, 17, 10421049. doi: 10.1111/desc.12192CrossRefGoogle ScholarPubMed
Horowitz, E. L., & Horowitz, R. E. (1938). Development of social attitudes in children. Sociometry, 1, 301338.CrossRefGoogle Scholar
Hugenberg, K., & Bodenhausen, G. V. (2004). Ambiguity in social categorization: The role of prejudice and facial affect in race categorization. Psychological Science, 15, 342345. doi: 10.1111/j.0956-7976.2004.00680.xCrossRefGoogle ScholarPubMed
Kelly, D. J., Liu, S., Ge, L., Quinn, P. C., Slater, A. M., Lee, K., Liu, Q., & Pascalis, O. (2007a). Cross-race preferences for same-race faces extend beyond the African versus Caucasian contrast in 3-month-old infants. Infancy, 11, 8795.CrossRefGoogle ScholarPubMed
Kelly, D. J., Liu, S., Lee, K., Quinn, P. C., Pascalis, O., Slater, A. M., & Ge, L. (2009). Development of the other-race effect in infancy: Evidence towards universality? Journal of Experimental Child Psychology, 17, 105114.CrossRefGoogle Scholar
Kelly, D. J., Quinn, P. C., Slater, A. M., Lee, K., Ge, L., & Pascalis, O. (2007b). The other-race effect develops during infancy. Psychological Science, 18, 10841089.CrossRefGoogle Scholar
Kelly, D. J., Quinn, P. C., Slater, A. M., Lee, K., Gibson, A., Smith, M., Ge, L., & Pascalis, O. (2005). Three-month-olds, but not newborns, prefer own-race faces. Developmental Science, 8, F31F36.CrossRefGoogle Scholar
Killen, M., Margie, N. G., & Sinno, S. (2006). Morality in the context of intergroup relationships. In Killen, M., & Smetana, J. G. (Eds.), Handbook of moral development (pp. 155183). New York: Psychology Press.Google Scholar
Killen, M., Rutland, A., & Ruck, M. D. (2011). Promoting equity, tolerance, and justice in childhood. Social Policy Report, 25, 133.Google Scholar
Kinzler, K. D., Dupoux, E., Spelke, E. S. (2007). The native language of social cognition. Proceedings of the National Academy of Sciences, 104, 1257712580.CrossRefGoogle ScholarPubMed
Kinzler, K. D., & Spelke, E. S. (2011). Do infants show social preferences for people differing in race? Cognition, 119, 19.CrossRefGoogle ScholarPubMed
Kubicek, C., Hillairet de Boisferon, A., Dupierrix, E., Pascalis, O., Loevenbruck, H., & Gervain, J., & Schwarzer, G. (2014). Cross-modal matching of audio-visual German and French fluent speech in infancy. PLoS ONE 9(2):e89275.CrossRefGoogle ScholarPubMed
Kuhl, P. K., Stevens, E., Hayashi, A., Deguchi, T., Kiritani, S., & Iverson, P. (2006). Infants show a facilitation effect for native language phonetic perception between 6 and 12 months. Developmental Science, 9, F13F21.CrossRefGoogle ScholarPubMed
Kuhl, P. K., Williams, K. H., & Lacerda, F. (1992). Linguistic experience alters phonetic perception in infants by 6 months of age. Science, 255, 606608.CrossRefGoogle ScholarPubMed
Lai, C. K., Marini, M., Lehr, S. A., Cerruti, C., Shin, J. E. L., Joy-Gaba, J. A., … & Frazier, R. S. (2014). Reducing implicit racial preferences: I. A comparative investigation of 17 interventions. Journal of Experimental Psychology: General, 143, 17651785. doi: 10.1037/a0036260CrossRefGoogle ScholarPubMed
Lai, C. K., Skinner, A. L., Cooley, E., Murrar, S., Brauer, M., Devos, T., … & Simon, S. (2016). Reducing implicit racial preferences: II. Intervention effectiveness across time. Journal of Experimental Psychology: General, 145, 101116. doi: 10.2139/ssrn.2712520Google Scholar
Lebrecht, S., Pierce, L. J., Tarr, M. J., & Tanaka, J. W. (2009). Perceptual other-race training reduces implicit racial bias. PloS one, 4, e4215. doi: 10.1371/journal.pone.0004215CrossRefGoogle ScholarPubMed
Lee, K., Anzures, G., Quinn, P. C., Pascalis, O., & Slater, A. (2011). Development of face processing expertise. In Calder, A. J., Rhodes, G., Johnson, M. H., & Haxby, J. V. (Eds.), Handbook of face perception (pp.753778). New York: Oxford University Press.Google Scholar
Lee, K., Quinn, P. C., Pascalis, O., & Slater, A. (2013). Development of face processing abilities. In Zelazo, P. D. (Ed.), Oxford handbook of developmental psychology, Vol. 2 (pp. 338370). New York: Oxford University Press.Google Scholar
Liu, S., Quinn, P. C., Wheeler, A., Xiao, N., Ge, L., & Lee, K. (2011). Similarity and difference in the processing of same- and other-race faces as revealed by eye-tracking in 4- to 9-month-olds. Journal of Experimental Child Psychology, 108, 180189. PMCID: PMC3740558CrossRefGoogle ScholarPubMed
Malatesta, C. Z., & Haviland, J. M. (1982). Learning display rules: The socialization of emotion expression in infancy. Child Development, 53, 9911003. doi: 10.1016/j.chc.2013.12.001CrossRefGoogle Scholar
Nesdale, D. (1999). Developmental changes in children’s ethnic preferences and social cognitions. Journal of Applied Developmental Psychology, 20, 501519. doi: 10.1016/S0193-3973(99)00012-X10.1016/j.jesp.2011.08.011CrossRefGoogle Scholar
Newheiser, A. K., & Olson, K. R. (2012). White and Black American children’s implicit intergroup bias. Journal of Experimental Social Psychology, 48, 264270.CrossRefGoogle ScholarPubMed
Olson, K. R., Shutts, K., Kinzler, K. D., & Weisman, K. G. (2012). Children associate racial groups with wealth: Evidence from South Africa. Child Development, 83, 18841899. doi: 10.1111/j.1467-8624.2012.01819.xCrossRefGoogle ScholarPubMed
Pettigrew, T. F., & Tropp, L. R. (2006). A meta-analytic test of intergroup contact theory. Journal of Personality and Social Psychology, 90, 751783.CrossRefGoogle ScholarPubMed
Qian, M. K., Heyman, G. D., Quinn, P. C., Messi, F. A., Fu, G., & Lee, K. (2016). Implicit racial biases in preschool children and adults from Asia and Africa. Child Development, 87, 285296.CrossRefGoogle Scholar
Qian, M., Quinn, P. C., Heyman, G. D., Pascalis, O., Fu, G., & Lee, K. (2017). Perceptual individuation training (but not mere exposure) reduces implicit racial bias in preschool children. Developmental Psychology.
Quinn, P. C., Anzures, G., Lee, K., Pascalis, O., Slater, A., & Tanaka, J. W. (2013). On the developmental origins of differential responding to social category information. In Banaji, M. R. & Gelman, S. A. (Eds.), Navigating the social world: What infants, children, and other species can teach us (pp. 286291). New York: Oxford University Press.CrossRefGoogle Scholar
Quinn, P. C., Lee, K., Pascalis, O., & Tanaka, J. W. (2016). Narrowing in categorical responding to other-race face classes by infants. Developmental Science, 19, 362371.CrossRefGoogle ScholarPubMed
Raabe, T., & Beelmann, A. (2011). Development of ethnic, racial, and national prejudice in childhood and adolescence: A multinational meta-analysis of age differences. Child Development, 82, 17151737. doi: 10.1111/j.1467-8624.2011.01668.xCrossRefGoogle Scholar
Rennels, J. L., & Davis, R. E. (2008). Facial experience during the first year. Infant Behavior & Development, 31, 665678.CrossRefGoogle Scholar
Richeson, J. A., & Shelton, J. N. (2003). When prejudice does not pay: Effects of interracial contact on executive function. Psychological Science, 14, 287290.CrossRefGoogle Scholar
Rutland, A., Killen, M., & Abrams, D. (2010). A new social-cognitive developmental perspective on prejudice: The interplay between morality and group identity. Perspectives on Psychological Science, 5, 279291. doi: 10.1177/1745691610369468CrossRefGoogle Scholar
Setoh, P., Lee, K. J. J., Zhang, L., Qian, M. K., Heyman, G. D., Quinn, P. C., & Lee, K. (under review). Racial categorization predicts implicit racial bias in preschool children.
Shutts, K., Kinzler, K. D., Katz, R. C., Tredoux, C., & Spelke, E. S. (2011). Race preferences in children: Insights from South Africa. Developmental Science, 14, 12831291. doi: 10.1111/j.1467-7687.2011.01072.xCrossRefGoogle ScholarPubMed
Sugden, N. A., Mohamed-Ali, M. I., & Moulson, M. C. (2014). I spy with my little eye: Typical, daily exposure to faces documented from a first-person infant perspective. Developmental Psychobiology, 56, 249261.CrossRefGoogle Scholar
Vezzali, L., Stathi, S., Giovannini, D., Capozza, D., & Trifiletti, E. (2015). The greatest magic of Harry Potter: Reducing prejudice. Journal of Applied Social Psychology, 45, 105121. doi: 10.1111/jasp.12279CrossRefGoogle Scholar
Werker, J. F., Yeung, H. H., & Yoshida, K. (2012). How do infants become native speech perception experts? Current Directions in Psychological Science, 21, 221226.CrossRefGoogle Scholar
Wheeler, A., Anzures, G., Quinn, P. C., Pascalis, O., Omrin, D. S., & Lee, K. (2011). Caucasian infants scan own- and other-race faces differently. PLoS ONE, 6: e18621.CrossRefGoogle ScholarPubMed
Xiao, N. G., Quinn, P. C., Xiao, W. S., Liu, S., Ge, L., Pascalis, O., & Lee, K. (2017). Older but not younger infants associate own-race faces with positive music and other-race faces with negative music. Developmental Science.
Xiao, N. G., Wu, R., Quinn, P. C., Liu, S., Tummeltshammer, K. S., Kirkham, N. Z., Ge, L., Pascalis, O., & Lee, K. (in press). Infants rely more on gaze cues from own-race than other-race adults for learning under uncertainty. Child Development.
Xiao, W. S., Fu, G., Quinn, P. C., Qin, J., Tanaka, J. W., Pascalis, O., & Lee, K. (2015). Individuation training with other-race faces reduces preschoolers’ implicit racial bias: a link between perceptual and social representation of faces in children. Developmental Science, 18, 655663. doi: 10.1111/desc.12241CrossRefGoogle Scholar
Xiao, W. S., Quinn, P. C., Pascalis, O., & Lee, K. (2014). Own- and other-race face scanning in infants: Implications for perceptual narrowing. Developmental Psychobiology (Special Issue on Perceptual Narrowing), 56, 262273.CrossRefGoogle ScholarPubMed
Agostino, A., Johnson, J., & Pascual-Leone, J. (2010). Executive functions underlying multiplicative reasoning: Problem type matters. Journal of Experimental Child Psychology, 105, 286305. doi: 10.1016/j.jecp.2009.09.006CrossRefGoogle ScholarPubMed
Aron, A. R. (2008). Progress in executive-function research from tasks to functions to regions to networks. Current Directions in Psychological Science, 17, 124129. doi: 10.1111/j.1467-8721.2008.00561.xCrossRefGoogle Scholar
Aron, A. R., Robbins, T. W., & Poldrack, R. A. (2004). Inhibition and the right inferior frontal cortex. Trends in Cognitive Sciences, 8, 170177. doi: 10.1016/j.tics.2004.02.010CrossRefGoogle ScholarPubMed
Booth, J. R., Burman, D. D., Meyer, J. R., Lei, Z., Trommer, B. L., Davenport, N. D., … & Mesulam, M. M. (2003). Neural development of selective attention and response inhibition. NeuroImage, 20, 737751. doi: 10.1016/S1053-8119(03)00404-XCrossRefGoogle ScholarPubMed
Brydges, C. R., Anderson, M., Reid, C. L., & Fox, A. M. (2013). Maturation of cognitive control: delineating response inhibition and interference suppression. PloS one, 8, e69826. doi: 10.1371/journal.pone.0069826CrossRefGoogle ScholarPubMed
Brydges, C. R., Fox, A. M., Reid, C. L., & Anderson, M. (2014). The differentiation of executive functions in middle and late childhood: A longitudinal latent-variable analysis. Intelligence, 47, 3443. doi: 10.1016/j.intell.2014.08.010CrossRefGoogle Scholar
Bunge, S. A., Dudukovic, N. M., Thomason, M. E., & Vaidya, C. J. (2002). Immature frontal lobe contributions to cognitive control in children: evidence from fMRI. Neuron, 33, 301311. doi: 10.1016/S0896-6273(01)00583-9CrossRefGoogle ScholarPubMed
Bunge, S. A., & Zelazo, P. D. (2006). A brain-based account of the development of rule use in childhood. Current Directions in Psychological Science, 15, 118121. doi: 10.1111/j.0963-7214.2006.00419.xCrossRefGoogle Scholar
Casey, B. J., Cohen, J. D., Jezzard, P., Turner, R., Noll, D. C., … & Rapoport, J. L. (1995) Activation of prefrontal cortex in children during a nonspatial working memory task with functional MRI. Neuroimage, 2, 221229. doi: 10.1006/nimg.1995.1029CrossRefGoogle Scholar
Casey, B. J., Davidson, M. C., Hara, Y., Thomas, K. M., Martinez, A., Galvan, A., … & Tottenham, N. (2004). Early development of subcortical regions involved in non‐cued attention switching. Developmental Science, 7, 534542. doi: 10.1111/j.1467-7687.2004.00377.x/fullCrossRefGoogle ScholarPubMed
Ciesielski, K. T., Lesnik, P. G., Savoy, R. L., Grant, E. P., & Ahlfors, S. P. (2006). Developmental neural networks in children performing a Categorical N-Back Task. NeuroImage, 33, 980990. doi: 10.1016/j.neuroimage.2006.07.028CrossRefGoogle ScholarPubMed
Collette, F., Hogge, M., Salmon, E., & Van der Linden, M. (2006). Exploration of the neural substrates of executive functioning by functional neuroimaging. Neuroscience, 139, 209221. doi: 10.1016/j.neuroscience.2005.05.035CrossRefGoogle ScholarPubMed
Collette, F., Van der Linden, M., Laureys, S., Delfiore, G., Degueldre, C., Luxen, A., & Salmon, E. (2005). Exploring the unity and diversity of the neural substrates of executive functioning. Human Brain Mapping, 25, 409423. doi: 10.1002/hbm.20118CrossRefGoogle ScholarPubMed
Cragg, L., & Chevalier, N. (2012). The processes underlying flexibility in childhood. The Quarterly Journal of Experimental Psychology, 65, 209232. Scholar
Crone, E. A., Donohue, S. E., Honomichl, R., Wendelken, C., & Bunge, S. A. (2006). Brain regions mediating flexible rule use during development. The Journal of Neuroscience, 26, 1123911247. doi: 10.1523/JNEUROSCI.2165-06.2006CrossRefGoogle ScholarPubMed
Darki, F., & Klingberg, T. (2015). The role of fronto-parietal and fronto-striatal networks in the development of working memory: A longitudinal study. Cerebral Cortex, 25, 15871595. doi: 10.1093/cercor/bht352CrossRefGoogle ScholarPubMed
Davis, E. P., Bruce, J., Snyder, K., & Nelson, C. A. (2003). The X-trials: Neural correlates of an inhibitory control task in children and adults. Journal of Cognitive Neuroscience, 15, 432443. doi: 10.1162/089892903321593144CrossRefGoogle ScholarPubMed
Diamond, A. (2006). The early development of executive functions. In Bialystok, E. & Craik, F. I. M. (Eds.), Lifespan cognition: Mechanisms of change (pp. 7095). London: Oxford University Press.CrossRefGoogle Scholar
Durston, S., Davidson, M. C., Tottenham, N., Galvan, A., Spicer, J., Fossella, J. A., & Casey, B. J. (2006). A shift from diffuse to focal cortical activity with development. Developmental Science, 9, 120. doi: 10.1111/j.1467-7687.2005.00454.x/fullCrossRefGoogle ScholarPubMed
Durston, S., Thomas, K. M., Yang, Y., Uluğ, A. M., Zimmerman, R. D., & Casey, B. J. (2002). A neural basis for the development of inhibitory control. Developmental Science, 5, F9F16. doi: 10.1111/1467-7687.00235CrossRefGoogle Scholar
Edin, F., Macoveanu, J., Olesen, P., & Tegnér, J. (2007). Stronger synaptic connectivity as a mechanism behind development of working memory-related brain activity during childhood. Journal of Cognitive Neuroscience, 19, 750760. doi: /10.1162/jocn.2007.19.5.750CrossRefGoogle ScholarPubMed
Espinet, S. D., Anderson, J. E., & Zelazo, P. D. (2012). N2 amplitude as a neural marker of executive function in young children: An ERP study of children who switch versus perseverate on the Dimensional Change Card Sort. Developmental Cognitive Neuroscience, 2, S49S58. doi: 10.1016/j.dcn.2011.12.002CrossRefGoogle ScholarPubMed
Espinet, S. D., Anderson, J. E., & Zelazo, P. D. (2013). Reflection training improves executive function in preschool-age children: Behavioral and neural effects. Developmental Cognitive Neuroscience, 4, 315. doi: 10.1016/j.dcn.2012.11.009CrossRefGoogle Scholar
Ezekiel, F., Bosma, R., & Morton, J. B. (2013). Dimensional Change Card Sort performance associated with age-related differences in functional connectivity of lateral prefrontal cortex. Developmental Cognitive Neuroscience, 5, 4050. doi: 10.1016/j.dcn.2012.12.001CrossRefGoogle ScholarPubMed
Friedman, N. P., & Miyake, A. (2004). The relations among inhibition and interference control functions: A latent-variable analysis. Journal of Experimental Psychology: General, 133, 101135. doi: 10.1037/0096-3445.133.1.101CrossRefGoogle ScholarPubMed
Fuhs, M. W., & Day, J. D. (2011). Verbal ability and executive functioning development in preschoolers at head start. Developmental Psychology, 47, 404416. doi: 10.1037/a0021065CrossRefGoogle ScholarPubMed
Garon, N., Bryson, S. E., & Smith, I. M. (2008). Executive function in preschoolers: A review using an integrative framework. Psychological Bulletin, 134, 3160. ScholarPubMed
Hughes, C., Ensor, R., Wilson, A., & Graham, A. (2010). Tracking executive function across the transition to school: A latent variable approach. Developmental Neuropsychology, 35, 2036. doi: 10.1080/87565640903325691CrossRefGoogle ScholarPubMed
Hwang, K., Velanova, K., & Luna, B. (2010). Strengthening of top-down frontal cognitive control networks underlying the development of inhibitory control: A functional magnetic resonance imaging effective connectivity study. Journal of Neuroscience, 30, 1553515545. ScholarPubMed
Johnson, M. H. (2000). Functional brain development in infants: Elements of an interactive specialization framework. Child Development, 71, 7581. doi: 10.1111/1467-8624.00120CrossRefGoogle ScholarPubMed
Johnson, M. H. (2011). Interactive specialization: a domain-general framework for human functional brain development? Developmental Cognitive Neuroscience, 1, 721. doi: 10.1016/j.dcn.2010.07.003CrossRefGoogle ScholarPubMed
Johnstone, S. J., Barry, R. J., & Clarke, A. R. (2007). Behavioural and ERP indices of response inhibition during a Stop-signal task in children with two subtypes of Attention-Deficit Hyperactivity Disorder. International Journal of Psychophysiology, 66, 3747. doi: 10.1016/j.ijpsycho.2007.05.011CrossRefGoogle ScholarPubMed
Jonkman, L. M. (2006). The development of preparation, conflict monitoring and inhibition from early childhood to young adulthood: a Go/NoGo ERP study. Brain Research, 1097, 181193. doi: 10.1016/j.brainres.2006.04.064CrossRefGoogle Scholar
Jonkman, L. M., Sniedt, F. L. F., & Kemner, C. (2007). Source localization of the Nogo-N2: A developmental study. Clinical Neurophysiology, 118, 10691077. doi: 10.1016/j.clinph.2007.01.017CrossRefGoogle ScholarPubMed
Klingberg, T., Forssberg, H., & Westerberg, H. (2002). Increased brain activity in frontal and parietal cortex underlies the development of visuospatial working memory capacity during childhood. Journal of Cognitive Neuroscience, 14, 110. doi: 10.1162/089892902317205276CrossRefGoogle ScholarPubMed
Kraybill, J. H. (2014). A latent factor analysis of preschool executive functions: investigations of antecedents and outcomes (unpublished doctoral dissertation). Virginia Tech, Virgina.Google Scholar
Kwon, H., Reiss, A. L., & Menon, V. (2002). Neural basis of protracted developmental changes in visuo-spatial working memory. Proceedings of the National Academy of Sciences, 99, 1333613341. doi: 10.1073/pnas.162486399CrossRefGoogle ScholarPubMed
Lamm, C., Zelazo, P. D., & Lewis, M. D. (2006). Neural correlates of cognitive control in childhood and adolescence: Disentangling the contributions of age and executive function. Neuropsychologia, 44, 21392148. doi: 10.1016/j.neuropsychologia.2005.10.013CrossRefGoogle ScholarPubMed
Lee, K., Bull, R., & Ho, R. M. H. (2013). Developmental changes in executive functioning. Child Development, 84, 19331953. doi: 10.1111/cdev.12096CrossRefGoogle ScholarPubMed
Lehto, J. E., Juujärvi, P., & Kooistra, L. (2003). Dimensions of executive functioning: Evidence from children. British Journal of Developmental Psychology, 21, 5980. doi: 10.1348/026151003321164627CrossRefGoogle Scholar
Lo, Y. H., Liang, W. K., Lee, H. W., Wang, C. H., Tzeng, O. J., Hung, D. L., … & Juan, C. H. (2013). The neural development of response inhibition in 5-and 6-year-old preschoolers: an ERP and EEG study. Developmental Neuropsychology, 38, 301316. doi: 10.1080/87565641.2013.801980CrossRefGoogle ScholarPubMed
Luna, B., & Sweeney, J. A. (2004). The emergence of collaborative brain function: fMRI studies of the development of response inhibition. Annals of the New York Academy of Sciences, 1021, 296309. doi: 10.1196/annals.1308.035CrossRefGoogle ScholarPubMed
Luna, B., Thulborn, K. R., Munoz, D. P., Merriam, E. P., Garver, K. E., Minshew, N. J., … & Sweeney, J. A. (2001). Maturation of widely distributed brain function subserves cognitive development. NeuroImage, 13, 786793. doi: 10.1006/nimg.2000.0743CrossRefGoogle ScholarPubMed
McAuley, T., & White, D. A. (2011). A latent variables examination of processing speed, response inhibition, and working memory during typical development. Journal of Experimental Child Psychology, 108, 453468. doi: 10.1016/j.jecp.2010.08.009CrossRefGoogle ScholarPubMed
Mehnert, J., Akhrif, A., Telkemeyer, S., Rossi, S., Schmitz, C. H., Steinbrink, J., … & Neufang, S. (2013). Developmental changes in brain activation and functional connectivity during response inhibition in the early childhood brain. Brain and Development, 35, 894904. doi: 10.1016/j.braindev.2012.11.006CrossRefGoogle ScholarPubMed
Miller, M. R., Giesbrecht, G. F., Müller, U., McInerney, R. J., & Kerns, K. A. (2012). A latent variable approach to determining the structure of executive function in preschool children. Journal of Cognition and Development, 13, 395423. doi: 10.1080/15248372.2011.585478CrossRefGoogle Scholar
Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 21, 814. doi: 10.1177/0963721411429458CrossRefGoogle ScholarPubMed
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49100. doi: 10.1006/cogp.1999.0734CrossRefGoogle ScholarPubMed
Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., … & Sears, M. R. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences, 108, 26932698.CrossRefGoogle ScholarPubMed
Moriguchi, Y., & Hiraki, K. (2009). Neural origin of cognitive shifting in young children. Proceedings of the National Academy of Sciences, 106, 60176021. doi: 10.1073/pnas.0809747106CrossRefGoogle ScholarPubMed
Moriguchi, Y., & Hiraki, K. (2011). Longitudinal development of prefrontal function during early childhood. Developmental Cognitive Neuroscience, 1, 153162. doi: 10.1016/j.dcn.2010.12.004CrossRefGoogle ScholarPubMed
Morton, J. B., Bosma, R., & Ansari, D. (2009). Age-related changes in brain activation associated with dimensional shifts of attention: An fMRI study. NeuroImage, 46, 249256. doi: 10.1016/j.neuroimage.2009.01.037CrossRefGoogle Scholar
Nagy, Z., Westerberg, H., & Klingberg, T. (2004). Maturation of white matter is associated with the development of cognitive functions during childhood. Journal of Cognitive Neuroscience, 16, 12271233. doi: 10.1162/0898929041920441CrossRefGoogle Scholar
Niendam, T. A., Laird, A. R., Ray, K. L., Dean, Y. M., Glahn, D. C., & Carter, C. S. (2012). Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cognitive, Affective, & Behavioral Neuroscience, 12, 241268. doi: 10.3758/s13415-011-0083-5CrossRefGoogle Scholar
O’Hare, E. D., Lu, L. H., Houston, S. M., Bookheimer, S. Y., & Sowell, E. R. (2008). Neurodevelopmental changes in verbal working memory load-dependency: An fMRI investigation. NeuroImage, 42, 16781685. doi: 10.1016/j.neuroimage.2008.05.057CrossRefGoogle ScholarPubMed
Olesen, P. J., Macoveanu, J., Tegnér, J., & Klingberg, T. (2007). Brain activity related to working memory and distraction in children and adults. Cerebral Cortex, 17, 10471054. doi: 10.1093/cercor/bhl014CrossRefGoogle ScholarPubMed
Olesen, P. J., Nagy, Z., Westerberg, H., & Klingberg, T. (2003). Combined analysis of DTI and fMRI data reveals a joint maturation of white and grey matter in a fronto-parietal network. Cognitive Brain Research, 18, 4857. doi: 10.1016/j.cogbrainres.2003.09.003CrossRefGoogle Scholar
Østby, Y., Tamnes, C. K., Fjell, A. M., & Walhovd, K. B. (2011). Morphometry and connectivity of the fronto-parietal verbal working memory network in development. Neuropsychologia, 49, 38543862. doi: 10.1016/j.neuropsychologia.2011.10.001CrossRefGoogle ScholarPubMed
Rose, S. A., Feldman, J. F., & Jankowski, J. J. (2011). Modeling a cascade of effects: the role of speed and executive functioning in preterm/full-term differences in academic achievement. Developmental Science, 14, 11611175. doi: 10.1111/j.1467-7687.2011.01068.xCrossRefGoogle Scholar
Rubia, K., Smith, A. B., Taylor, E., & Brammer, M. (2007). Linear age-correlated functional development of right inferior fronto-striato-cerebellar networks during response inhibition and anterior cingulate during error-related processes. Human Brain Mapping, 28, 11631177. doi: 10.1002/hbm.20347CrossRefGoogle ScholarPubMed
Rubia, K., Smith, A. B., Woolley, J., Nosarti, C., Heyman, I., Taylor, E., & Brammer, M. (2006). Progressive increase of frontostriatal brain activation from childhood to adulthood during event-related tasks of cognitive control. Human Brain Mapping, 27, 973993. doi: 10.1002/hbm.20237CrossRefGoogle ScholarPubMed
Scherf, K. S., Sweeney, J. A., & Luna, B. (2006). Brain basis of developmental change in visuospatial working memory. Journal of Cognitive Neuroscience, 18, 10451058. doi: 10.1162/jocn.2006.18.7.1045CrossRefGoogle Scholar
Sheridan, M., Kharitonova, M., Martin, R. E., Chatterjee, A., & Gabrieli, J. D. E. (2014). Neural substrates of the development of cognitive control in children ages 5–10 years. Journal of Cognitive Neuroscience, 26(8), 1840–1850. doi: 10.1162/jocn_a_00597CrossRefGoogle Scholar
Shing, Y. L., Lindenberger, U., Diamond, A., Li, S.-C., & Davidson, M. C. (2010). Memory maintenance and inhibitory control differentiate from early childhood to adolescence. Developmental Neuropsychology, 35, 679697. doi: 10.1080/87565641.2010.508546CrossRefGoogle ScholarPubMed
Stuss, D. T., & Alexander, M. (2000). Executive functions and the frontal lobes: A conceptual view. Psychological Research, 63, 289298. doi: 10.1007/s004269900007CrossRefGoogle ScholarPubMed
Tamm, L., Menon, V., & Reiss, A. L. (2002). Maturation of brain function associated with response inhibition. Journal of the American Academy of Child & Adolescent Psychiatry, 41, 12311238. doi: 10.1097/00004583-200210000-00013CrossRefGoogle ScholarPubMed
Usai, M. C., Viterbori, P., & Traverso, L. (2014). Latent structure of executive function in five-and six-year-old children: a longitudinal study. European Journal of Developmental Psychology, 11, 447463. doi: 10.1080/17405629.2013.840578CrossRefGoogle Scholar
Van der Sluis, S., de Jong, P. F., & van der Leij, A. (2007). Executive functioning in children, and its relations with reasoning, reading, and arithmetic. Intelligence, 35, 427449. doi: 10.1016/j.intell.2006.09.001CrossRefGoogle Scholar
Van der Ven, S. H. G., Kroesbergen, E. H., Boom, J., & Leseman, P. P. M. (2011). The development of executive functions and early mathematics: A dynamic relationship. British Journal of Educational Psychology, 82, 100119. doi: 10.1111/j.2044-8279.2011.02035.xCrossRefGoogle Scholar
Velanova, K., Wheeler, M. E., & Luna, B. (2009). The maturation of task set-related activation supports late developmental improvements in inhibitory control. Journal of Neuroscience, 29, 1255812567. doi: 10.1523/JNEUROSCI.1579-09.2009CrossRefGoogle Scholar
Vestergaard, M., Madsen, K. S., Baaré, W. F., Skimminge, A., Ejersbo, L. R., Ramsøy, T. Z., … & Jernigan, T. L. (2011). White matter microstructure in superior longitudinal fasciculus associated with spatial working memory performance in children. Journal of Cognitive Neuroscience, 23, 21352146. doi: 10.1162/jocn.2010.21592CrossRefGoogle ScholarPubMed
Waxer, M., & Morton, J. B. (2011). Multiple processes underlying dimensional change card sort performance: A developmental electrophysiological investigation. Journal of Cognitive Neuroscience, 23, 32673279. doi: 10.1162/jocn_a_00038CrossRefGoogle ScholarPubMed
Wendelken, C., Munakata, Y., Baym, C., Souza, M., & Bunge, S. A. (2012). Flexible rule use: Common neural substrates in children and adults. Developmental Cognitive Neuroscience, 2, 329339. doi: 10.1016/j.dcn.2012.02.001CrossRefGoogle Scholar
Wiebe, S. A., Espy, K. A., & Charak, D. (2008). Using confirmatory factor analysis to understand executive control in preschool children: I. Latent structure. Developmental Psychology, 44, 575587. doi: 10.1037/0012-1649.44.2.575CrossRefGoogle ScholarPubMed
Wiebe, S. A., Sheffield, T., Nelson, J. M., Clark, C. A. C., Chevalier, N., & Espy, K. A. (2011). The structure of executive function in 3-year-olds. Journal of Experimental Child Psychology, 108, 436452. doi: 10.1016/j.jecp.2010.08.008CrossRefGoogle ScholarPubMed
Willoughby, M. T., Blair, C. B., Wirth, R. J., Greenberg, M., & Family Life Project Investigators. (2010). The measurement of executive function at age 3 years: Psychometric properties and criterion validity of a new battery of tasks. Psychological Assessment, 22, 306317. doi: 10.1037/a0018708CrossRefGoogle ScholarPubMed
Willoughby, M. T., Wirth, R. J., Blair, C. B., & Family Life Project Investigators. (2012). Executive function in early childhood: Longitudinal measurement invariance and developmental change. Psychological Assessment, 24, 418431. doi: 10.1037/a0025779CrossRefGoogle ScholarPubMed
Wu, K. K., Chan, S. K., Leung, P. W. L., Liu, W.-S., Leung, F. L. T., & Ng, R. (2011). Components and developmental differences of executive functioning for school-aged children. Developmental Neuropsychology, 36, 319337. doi: 10.1080/87565641.2010.549979CrossRefGoogle ScholarPubMed
Zelazo, P. D., (2006). The Dimensional Change Card Sort (DCCS): A method of assessing executive function in children. Nature Protocols, 1, 297301. doi: 10.1038/nprot.2006.46CrossRefGoogle ScholarPubMed
Zelazo, P. D., Carlson, S. M., & Kesek, A. (2008). The development of executive function in childhood. In Nelson, C. A. & Luciana, M. (Eds.), Handbook of Developmental Cognitive Neuroscience (2nd edn). (pp. 553574). Cambridge, MA: MIT Press.Google Scholar
Zuk, J., Benjamin, C., Kenyon, A., & Gaab, N. (2014). Behavioral and neural correlates of executive functioning in musicians and non-musicians. PLoS ONE, 9, e9986814. doi: 10.1371/journal.pone.0099868CrossRefGoogle ScholarPubMed
Apel, K-O. (1995). Charles Peirce: From pragmatism to pragmaticism. Atlantic Highlands, NJ: Humanities Press.Google Scholar
Arsalidou, M., & Pascual-Leone, J. (2016). Constructivist developmental theory is needed in developmental neuroscience. NPJ Science of Learning, 1, 16016.CrossRefGoogle Scholar
Arsalidou, M., Pascual-Leone, J., & Johnson, J. (2010). Misleading cues improve developmental assessment of attentional capacity: The color matching task. Cognitive Development, 25, 262277.CrossRefGoogle Scholar
Audi, R. (Ed.) (1995). The Cambridge dictionary of philosophy. New York, NY: Cambridge University Press.Google Scholar
Austin, J. H. (2010). The thalamic gateway: How the meditative training of attention evolves toward selfless transformations of attention. In Bruya, B. (Ed.), Effortless attention (pp. 373407). Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Bereiter, C., & Scardamalia, M. (1979). Pascual-Leone’s M construct as a link between cognitive-developmental and psychometric concepts of intelligence. Intelligence, 3, 4163.CrossRefGoogle Scholar
Binet, A., & Simon, T. (1911). A method of measuring the development of intelligence in young children. Lincoln, IL: Courier Company.Google Scholar
Calvo, A. (2004). Detection of latent giftedness by means of mental-capacity testing. Unpublished master’s thesis, York University, Toronto, ON.Google Scholar
Canadian Achievement Tests – Third Edition (CAT-3). (2000). Markham, ON: Canadian Test Centre.
Canadian Cognitive Abilities Test (CCAT). (1998). Toronto, ON: Nelson Education.
Carpenter, P. A., Just, M. A., & Shell, P. (1990). What one intelligence test measures: A theoretical account of the processing in the Raven Progressive Matrices Test. Psychological Review, 97, 404431.CrossRefGoogle ScholarPubMed
Case, R. (1975). Gearing the demands of instruction to the developmental capacities of the learner. Review of Educational Research, 45, 5987.CrossRefGoogle Scholar
Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 215229.CrossRefGoogle Scholar
Cowan, N., Ricker, T. J., Clark, K. M., Hinrichs, G. A., & Glass, B. A. (2014). Knowledge cannot explain the developmental growth of working memory capacity. Developmental Science, 18, 132145.CrossRefGoogle ScholarPubMed
Cunning, S. (2003). The direction-following task: Assessing mental capacity in the linguistic domain. Unpublished doctoral dissertation, York University, Toronto, ON.Google Scholar
Deary, I. J. (2002). g and cognitive elements of information processing: An agnostic view. In Sternberg, R. J. & Grigorenko, E. L. (Eds.), The general factor of intelligence: How general is it? (pp. 151181). Mahwah, NJ: Erlbaum.Google Scholar
Goldstein, K. (2000). The organism. New York, NY: Zone Books. (Original work published 1934).Google ScholarPubMed
Gould, S. J. (1981). The mismeasure of man. New York, NY: Norton.Google Scholar
Greenberg, L., & Pascual-Leone, J. (1995). A dialectical constructivist approach to experiential change. In Neimeyer, R. & Mahoney, M. (Eds.), Constructivism in psychotherapy (pp. 169191). Washington, DC: APA Press.CrossRefGoogle Scholar
Heitz, R. P., Unsworth, N., & Engle, R. W. (2005). Working memory capacity, attentional control, and fluid intelligence. In Wilhelm, O. & Engle, R. W. (Eds.), Handbook of understanding and measuring intelligence (pp. 6178). Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
Howard, S. J., Johnson, J., & Pascual-Leone, J. (2014). Clarifying inhibitory control: Diversity and development of attentional inhibition. Cognitive Development, 31, 121.CrossRefGoogle Scholar
Im-Bolter, N., Johnson, J., Ling, D., & Pascual-Leone, J. (2015). Inhibition: Mental control process or mental resource? Journal of Cognition and Development, 16, 666681.CrossRefGoogle Scholar
Im-Bolter, N., Johnson, J., & Pascual-Leone, J. (2006). Processing limitation in children with specific language impairment: The role of executive function. Child Development, 77, 18221841.CrossRefGoogle Scholar
Johansen, J. D. (1993). Dialogic semiosis: An essay on signs and meaning. Bloomington, IN: Indiana University Press.Google Scholar
Koffka, K. (1963). Principles of gestalt psychology. New York, NY: Harcourt, Brace, & World. (Original work published 1935).Google Scholar
Morra, S. (2008). A test of a neo-Piagetian model of the water-level task. European Journal of Developmental Psychology, 5, 369400.CrossRefGoogle Scholar
Pascual-Leone, J. (1970). A mathematical model for the transition rule in Piaget’s developmental stages. Acta Psychologica, 32, 301345.CrossRefGoogle Scholar
Pascual-Leone, J. (1978). Compounds, confounds, and models in developmental information processing: A reply to Trabasso and Foellinger. Journal of Experimental Child Psychology, 26, 1840.CrossRefGoogle Scholar
Pascual-Leone, J. (1980). Constructive problems for constructive theories: The current relevance of Piaget’s work and a critique of information-processing simulation psychology. In Kluwe, R. & Spada, H. (Eds.), Developmental models of thinking (pp. 263296). New York, NY: Academic Press.Google Scholar
Pascual-Leone, J. (1984). Attention, dialectic, and mental effort: Towards an organismic theory of life stages. In Commons, M. L., Richards, F. A., & Armon, G. (Eds.) Beyond formal operations: Late adolescence and adult cognitive development (pp. 182215). New York, NY: Praeger.Google Scholar
Pascual-Leone, J. (1989). An organismic process model of Witkin’s field-dependence- independence. In Globerson, T. & Zelniker, T. (Eds.), Cognitive style and cognitive development (pp. 3670). Norwood, NJ: Ablex.Google Scholar
Pascual-Leone, J. (1995). Learning and development as dialectical factors in cognitive growth. Human Development, 38, 338348.CrossRefGoogle Scholar
Pascual-Leone, J. (2012). Piaget as a pioneer of dialectical constructivism: Seeking dynamic processes for human science. In Marti, E. & Rodriguez, C. (Eds.), After Piaget. Edison, NJ: Transaction.Google Scholar
Pascual-Leone, J. (2013). Can we model organismic causes of working memory, efficiency and fluid intelligence? A meta-subjective perspective. Intelligence, 41, 738743.CrossRefGoogle Scholar
Pascual-Leone, J. (2014). Dialectics. In Teo, T. (Ed.), Encyclopedia of critical psychology (pp. 421428). New York, NY: SpringerReference.CrossRefGoogle Scholar
Pascual-Leone, J., & Baillargeon, R. (1994). Developmental measurement of mental attention. International Journal of Behavioral Development, 17, 161200.CrossRefGoogle Scholar
Pascual-Leone, J., Escobar, E. M. R., & Johnson, J. (2012). Logic: Development of logical operations. In Hirstein, W. (Ed.), Encyclopedia of human behavior (2nd edn.). New York, NY: Elsevier.Google Scholar
Pascual-Leone, J., & Ijaz, H. (1989). Mental capacity testing as a form of intellectual-developmental assessment. In Samuda, R., Kong, S., Cummins, J., Pascual-Leone, J., & Lewis, J.. Assessment and placement of minority students (pp. 143171). Toronto, ON: Hogrefe International.Google Scholar
Pascual-Leone, J., & Johnson, J. (2004). Affect, self-motivation, and cognitive development: A dialectical constructivist view. In Dai, D. Y. & Sternberg, R. S. (Eds.), Motivation, emotion, and cognition: Integrative perspectives on intellectual functioning and development (pp. 197235). Mahwah, NJ: Erlbaum.Google Scholar
Pascual-Leone, J., & Johnson, J. (2005). A dialectical constructivist view of developmental intelligence. In Wilhelm, O. & Engle, R. (Eds.), Handbook of understanding and measuring intelligence (pp. 177201). Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
Pascual-Leone, J., & Johnson, J. (2011). A developmental theory of mental attention: Its applications to measurement and task analysis (pp. 13–46). In Barrouillet, P. & Gaillard, V. (Eds.), Cognitive development and working memory: A dialogue between neo-Piagetian and cognitive approaches (pp. 1346). New York, NY: Psychology Press.Google Scholar
Pascual-Leone, J., & Johnson, J. (2012, February). Scale invariance in the measurement of mental-attentional capacity. Poster presented at SRCD Themed Meeting: Developmental Methodology, Tampa, FL.Google Scholar
Pascual-Leone, J., Johnson, J., & Agostino, A. (2010). Mental attention, multiplicative structures, and the causal problems of cognitive development. In Ferrari, M. & Vuletic, L. (Eds.), Developmental interplay between mind, brain and education: Essays in honor of Robbie Case (pp. 4982). New York, NY: Springer.Google Scholar
Pascual-Leone, J., Johnson, J., Baskind, S., Dworsky, S., & Severtston, E. (2000). Culture-fair assessment and the processes of mental attention. In Kozulin, A. & Rand, Y. (Eds.), Experience of mediated learning: An impact of Feuerstein’s theory in education and psychology (pp. 191214). New York, NY: Pergamon.Google Scholar
Pascual-Leone, J., Johnson, J., & Calvo, A. (2004, June). Can mental attentional capacity predict the Canadian Cognitive Abilities score of school children? Poster presented at the annual meeting of the Jean Piaget Society, Toronto, ON.Google Scholar
Pascual-Leone, J., & Morra, S. (1991). Horizontality of water level: A neoPiagetian developmental review. Advances in Child Development and Behavior, 23, 231276.CrossRefGoogle Scholar
Pascual-Leone, J., Pascual-Leone, A., & Arsalidou, M. (2015). Neuropsychology still needs to model organismic processes “from within.” Behavioral and Brain Sciences, 38, e83.CrossRefGoogle Scholar
Pascual-Leone, J., & Smith, J. (1969). The encoding and decoding of symbols by children: A new experimental paradigm and a neo-Piagetian model. Journal of Experimental Child Psychology, 8, 328355.CrossRefGoogle Scholar
Pepper, S. C. (1942). World hypotheses: A study of evidence. Berkeley, CA: University of California Press.Google Scholar
Piaget, J. (1983). Piaget’s theory. In Mussen, P. H. (Series Ed.) & Kessen, W. (Vol. Ed.), Handbook of child psychology: Vol. 1. History, theory, and methods (4th edn., pp. 103128). New York, NY: Wiley.Google Scholar
Proctor, R. W., & Reeve, T. G. (Eds.) (1990). Stimulus-response compatibility: An integrated perspective. Amsterdam: North-Holland.Google Scholar
Psillos, S. (2002). Causation and explanation. Montreal, QC: McGill-Queen’s University Press.Google Scholar
Rock, I. (1983). The logic of perception. Cambridge, MA: MIT Press.Google Scholar
Rouse Ball, W. W. (1905). Mathematical recreations and essays (4th edn.). New York, NY: Macmillan.Google Scholar
Shipstead, Z., Lindsey, D. R. B., Marshall, R. L., & Engle, R. W. (2014). The mechanisms of working memory capacity: Primary memory, secondary memory, and attention control. Journal of Memory and Language, 72, 116141.CrossRefGoogle Scholar
Skuy, M., Gewer, A., Osrin, Y., Knunou, D., Fridjhon, P., & Rushton, J. P. (2002). Effects of mediated learning on Raven’s matrices scores of African and non-African university students in South Africa. Intelligence, 30, 221232.CrossRefGoogle Scholar
Spearman, C. E. (1927). The abilities of man, their nature and measurement. New York, NY: MacMillan.Google Scholar
Stöttinger, E., Filipowicz, A., Valadao, D., Culham, J. C., Goodale, M. A., Anderson, B., & Danckert, J. A. (2015). A cortical network that marks the moment when conscious representations are updated. Neuropsychologia, 79, 113122.CrossRefGoogle ScholarPubMed
Unsworth, N., & Engle, R. W. (2005). Working memory capacity and fluid abilities: Examining the correlation between operation span and Raven. Intelligence, 33, 6781.CrossRefGoogle Scholar
Verguts, T., & De Boeck, P. (2002). On the correlation between working memory capacity and performance on intelligence tests. Learning and Individual Differences, 13, 3755.CrossRefGoogle Scholar
Waters, A. C., & Tucker, D. M. (2013). Self-regulation and neural development. In Sokol, B. W., Grouzet, F. M. E., & Muller, U. (Eds.), Self-regulation and autonomy (pp. 279296). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Werner, H., & Kaplan, B. (1984). Symbol formation. Hillsdale, NJ: Erlbaum.Google Scholar
Witkin, H. A., & Goodenough, D. R. (1981). Cognitive styles, essence and origin: Field dependence and field independence. New York, NY: International Universities Press.Google Scholar
Amundson, R. (2005). The changing role of the embryo in evolutionary thought: Roots of evo-devo. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Arthur, W. (2004). Biased embryos and evolution. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Avital, E., & Jablonka, E. (2000). Animal traditions: Behavioral inheritance in evolution. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Badyaev, A. (2009). Evolutionary significance of phenotypic accommodation in novel environments: An empirical test of the Baldwin effect. Philosophical Transactions of the Royal Society B, 364, 11251141.CrossRefGoogle ScholarPubMed
Balakrishnan, C. N., & Sorenson, M. D. (2006). Premating reproductive isolation among sympatric indigobird species and host races. Behavioral Ecology, 17, 473478.CrossRefGoogle Scholar
Barkow, J., Cosmides, L., & Tooby, J. (1992). The adapted mind: Evolutionary psychology and the generation of culture. New York, NY: Oxford University Press.Google Scholar
Bateson, P. P. G., & Gluckman, P. (2011). Plasticity, robustness, development, and evolution. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Bearhop, S., Fiedler, W., Furness, R. W., Votier, S. C., Waldron, S., Newton, J., … & Farnsworth, K. (2005). Assortative mating as a mechanism for rapid evolution of a migratory divide. Science, 310, 502504.CrossRefGoogle ScholarPubMed
Belyaev, D. (1979). Destabilizing selection as a factor in domestication. Journal of Heredity, 70, 301308.CrossRefGoogle ScholarPubMed
Blair, C., & Raver, C. C. (2012). Individual development and evolution: Experiential canalization of self-regulation. Developmental Psychology, 48, 647657.CrossRefGoogle Scholar
Blumberg, M. S. (2005). Basic instinct: The genesis of novel behavior. New York, NY: Thunder’s Mouth Press.Google Scholar
Buss, D. M. (1995). Evolutionary psychology: A new paradigm for psychological science. Psychological Inquiry, 6, 130.CrossRefGoogle Scholar
Casey, M. B, & Karpinski, S. (1999). The development of turning bias is influenced by prenatal visual experience in domestic chicks (Gallus gallus). The Psychological Record, 49, 6774.CrossRefGoogle Scholar
Casey, M. B., & Lickliter, R. (1998). Prenatal visual experience influences the development of turning bias in bobwhite quail chicks (Colinus virginianus). Developmental Psychobiology, 32, 327338.3.0.CO;2-P>CrossRefGoogle Scholar
Clark, M. M., & Galef, B. (1981). Environmental influence on development, behavior, and endocrine morphology of gerbils. Physiology & Behavior, 27, 761765.CrossRefGoogle ScholarPubMed
Confer, J. C., Easton, J. A., Fleischman, D. S., Goetz, C. D., Lewis, D. M. … & Buss, D. M. (2010). Evolutionary psychology: Controversies, questions, prospects, and limitations. American Psychologist, 65, 110126.CrossRefGoogle ScholarPubMed
Dawkins, R. (1975). The selfish gene. New York, NY: Oxford University Press.Google Scholar
de Beer, G. (1940). Embryos and ancestors. Oxford, England: Clarendon Press.Google Scholar
Denenberg, V. H., & Rosenberg, K. M. (1967). Nongenetic transmission of information. Nature, 216, 549550.CrossRefGoogle ScholarPubMed
Denenberg, V. H., & Whimbey, A. E. (1963). Behavior of adult rats is modified by the experiences their mothers had as infants. Science, 142, 11921193.CrossRefGoogle ScholarPubMed
Deng, C., & Rogers, L. J. (2002). Social recognition and approach in the chick: Lateralization and effect of visual experience. Animal Behaviour, 63, 697706.CrossRefGoogle Scholar
Dobzhansky, T. (1937). Genetics and the origin of species, 1st edn. New York, NY: Columbia University Press.Google ScholarPubMed
Duntley, J., & Buss, D. (2008). Evolutionary psychology is a metatheory for psychology. Psychological Inquiry, 19, 3034.CrossRefGoogle Scholar
Feder, J. L., Roethele, J. B., Wlazlo, B., & Berlocher, S. H. (1997). Selective maintenance of allozyme differences among sympatric host races of the apple maggot fly. Proceedings of the National Academy of Sciences, USA, 94, 1141711421.CrossRefGoogle Scholar
Francis, D., Diorio, J., Liu, D., & Meaney, M. J. (1999). Nongenomic transmission across generations of maternal behavior and stress responses in the rat. Science, 286, 11551158.CrossRefGoogle ScholarPubMed
Garstang, W. (1922). The theory of recapitulation: A critical re-statement of the biogenetic law. Journal of the Linnean Society of London, Zoology, 35, 81101.CrossRefGoogle Scholar
Geary, D. C., & Huffman, K. J. (2002). Brain and cognitive evolution: forms of modularity and functions of mind. Psychological Bulletin, 128, 667698.CrossRefGoogle Scholar
Gilbert, S. F., & Epel, D. (2009). Ecological developmental biology. Sunderland, MA: Sinauer.Google ScholarPubMed
Goldschmidt, R. (1940). The material basis of evolution. New Haven, CT: Yale University Press.Google Scholar
Gottlieb, G. (1971). The development of species-identification in birds. Chicago, IL: University of Chicago Press.Google Scholar
Gottlieb, G. (1991). Experiential canalization of behavior development: Theory. Developmental Psychology, 27, 413.CrossRefGoogle Scholar
Gottlieb, G. (1997). Synthesizing nature-nurture: Prenatal roots of instinctive behavior. Mahwah, NJ: Erlbaum.Google Scholar
Gottlieb, G. (2002). Developmental-behavioral initiation of evolutionary change. Psychological Review, 109, 211218.CrossRefGoogle ScholarPubMed
Griffiths, P. E., & Stotz, K. (2013). Genetics and philosophy: An introduction. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Hall, B. K., Pearson, R. D., & Müller, G. B. (2004). Environment, development, and evolution. Cambridge, MA: MIT Press.Google Scholar
Harshaw, C., & Lickliter, R. (2007). Interactive and vicarious acquisition of auditory preferences in Northern bobwhite chicks. Journal of Comparative Psychology, 121, 320331.CrossRefGoogle ScholarPubMed
Harshaw, C., & Lickliter, R. (2011). Biased embryos: Prenatal experience alters the postnatal malleability of auditory preferences in bobwhite quail. Developmental Psychobiology, 53, 291302.CrossRefGoogle Scholar
Harshaw, C., Tourgeman, I., & Lickliter, R. (2008). Stimulus contingency and the malleability of species-typical auditory preferences in Northern bobwhite hatchlings. Developmental Psychobiology, 50, 460472.CrossRefGoogle ScholarPubMed
Huxley, J. (1942). Evolution: The modern synthesis. London, UK: George Allen & Unwin.Google Scholar
Jablonka, E. (2006). Genes as followers in evolution: A post-synthesis synthesis? Biology and Philosophy, 21, 143154.CrossRefGoogle Scholar
Jablonka, E., & Lamb, M. J. (2005). Evolution in four dimensions: Genetic, epigenetic, behavioral, and symbolic variation in the history of life. Cambridge, MA: MIT Press.Google Scholar
Johnston, T. D., & Gottlieb, G. (1990). Neophenogenesis: A developmental theory of phenotypic evolution. Journal of Theoretical Biology, 147, 471495.CrossRefGoogle ScholarPubMed
Johnston, T. D., & Lickliter, R. (2009). A developmental systems theory perspective on psychological change. In Spencer, J. P., Thomas, M., & McClelland, J. M. (Eds.), Toward a unified theory of development: Connectionism and dynamic systems theory re-considered (pp. 285296). New York, NY: Oxford University Press.CrossRefGoogle Scholar
King, J. A. (1968). Species specificity and early experience. In Newton, G. & Levine, S. (Eds.), Early experience and behavior (pp. 4264). Springfield, MA: Thomas.Google Scholar
Kuo, Z. Y. (1967). The dynamics of behavior development: An epigenetic view. New York, NY: Random House.Google Scholar
Laland, K. N., Uller, T., Feldman, M. W., Sterelny, K., Muller, G. B., Moczek, A., …. & Odling-Smee, J. (2015). The extended evolutionary synthesis: Its structure, assumptions, and predictions. Proceeding of the Royal Society, B 282, 114.CrossRefGoogle ScholarPubMed
Ledon-Rettig, C. C., Pfennig, D. W., Chunco, A., & Dworkin, I. (2014). Cryptic genetic variation in natural populations: A predictive framework. Integrated Comparative Biology, 54, 783793.CrossRefGoogle ScholarPubMed
Lerhman, D. S. (1953). A critique of Konrad Lorenz’s theory of instinctive behavior. Quarterly Review of Biology, 28, 337363.CrossRefGoogle Scholar
Lerner, R. M. & Benson, J. B. (2013). Embodiment and epigenesis: Theoretical and methodological issues in understanding the role of biology within the relational developmental system. Advances in Child Development and Behavior, Vol. 44.Google ScholarPubMed
Levine, S. (1956). A further study of infantile handling and adult avoidance learning. Journal of Personality, 25, 7080.CrossRefGoogle ScholarPubMed
Lickliter, R. (2005). Prenatal sensory ecology and experience: Implications for perceptual and behavioral development in precocial birds. Advances in the Study of Behavior, 35, 235274.CrossRefGoogle Scholar
Lickliter, R. (2009). The fallacy of partitioning: Epigenetics’ validation of the organism-environment system. Ecological Psychology, 21, 138146.CrossRefGoogle Scholar
Lickliter, R., & Berry, T. D. (1990). The phylogeny fallacy: Developmental psychology’s misapplication of evolutionary theory. Developmental Review, 10, 348364.CrossRefGoogle Scholar
Lickliter, R. & Harshaw, C. (2010). Canalization and malleability reconsidered: The developmental basis of phenotypic stability and variability. In Hood, K. E., Halpern, C. T., Greenberg, G., & Lerner, R. M. (Eds.), Handbook of developmental science, behavior, and genetics (pp. 491526.). Malden, MA: Wiley-Blackwell.CrossRefGoogle Scholar
Lickliter, R., & Honeycutt, H. (2003). Developmental dynamics: Toward a biologically plausible evolutionary psychology. Psychological Bulletin, 129, 819835.CrossRefGoogle Scholar
Lickliter, R., & Honeycutt, H. (2009). Rethinking epigenesis and evolution in light of developmental science. In Blumberg, M., Freeman, J., & Robinson, S. (Eds.), Oxford handbook of developmental behavioral neuroscience (pp. 3047). New York, NY: Oxford University Press.Google Scholar
Lickliter, R., & Honeycutt, H. (2013). A developmental evolutionary framework for psychology. Review of General Psychology, 17, 11841189.CrossRefGoogle Scholar
Lickliter, R., & Honeycutt, H. (2015). Biology, development, and human systems. In: Overton, W. F. & Molenaar, P. C. M. (Vol. Eds.) Handbook of child psychology and developmental science. Vol. 1: Theory & method (7th edn., pp. 162207). Hoboken, NJ: Wiley.Google Scholar
Lickliter, R., & Ness, J. (1990). Domestication and comparative psychology: Status and strategy. Journal of Comparative Psychology, 104, 211218.CrossRefGoogle Scholar
MacDonald, K., & Herschberger, S. L. (2005). Theoretical issues in the study of evolution and development. In Burgess, R. & MacDonald, K. (Eds.), Evolutionary perspectives on human development (2nd edn., pp. 2172). Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
Malausa, T., Bethend, M. T., Bontemps, A., Bourguet, D., Cornuet, J. M., et al. (2005). Assortative mating in sympatric host races of the European corn borer. Science, 308, 258260.CrossRefGoogle ScholarPubMed
Mameli, M. (2004). Nongenetic selection and nongenetic inheritance. British Journal for the Philosophy of Science, 55, 3571.CrossRefGoogle Scholar
Maynard Smith, J. (1985). Sexual selection, handicaps, and true fitness. Journal of Theoretical Biology, 115, 18.CrossRefGoogle Scholar
Mayr, E. (1942). Systematics and the origins of species. New York, NY: Columbia University Press.Google Scholar
Mayr, E. (1982). The growth of biological thought. Cambridge, MA: Harvard University Press.Google Scholar
Meaney, M. J. (2010). Epigenetics and the biological definition of Gene × Environment interactions. Child Development, 81, 4179.CrossRefGoogle ScholarPubMed
Miller, D. B. (1997). The effects of nonobvious forms of experience on the development of instinctive behavior. In Dent-Reed, C. & Zukow-Goldring, P. (Eds), Evolving explanations of development (pp. 457507). Washington, DC: American Psychological Association.Google Scholar
Minelli, A., & Pradeu, T. (2014). Towards a theory of development. New York, NY: Oxford University Press.CrossRefGoogle Scholar
Moczek, A. (2015). Re-evaluating the environment in developmental evolution. Frontiers in Ecology and Evolution, 3, 18.CrossRefGoogle Scholar
Moczek, A., Sears, K., Stollewerk, A., Wittkopp, P., Diggle, P., Dworkin, I., … & Extavour, C. (2015). The significance and scope of evolutionary developmental biology: A vision for the 21st century. Evolution and Development, 17, 198219.CrossRefGoogle ScholarPubMed
Moore, D. S. (2008). Espousing interactions and fielding reactions: Addressing laypeople’s beliefs about genetic determinism. Philosophical Psychology, 21, 331348.CrossRefGoogle Scholar
Moore, D. S. (2015). The developing genome: An introduction to behavioral epigenetics. New York, NY: Oxford University Press.Google Scholar
Nijhout, H. F. (2003). Development and evolution of adaptive polyphenisms. Evolution & Development, 5, 918.CrossRefGoogle ScholarPubMed
Overton, W. F. (2015). Processes, relations, and relational developmental systems. In Overton, W. F. & Molenaar, P. C. M. (Vol. Eds.) Handbook of child psychology and developmental science. Vol. 1: Theory & method (7th edn., pp. 962). Hoboken, NJ: Wiley.Google Scholar
Overton, W. F., & Molenaar, P. C. M. (2015). Handbook of child psychology and developmental science. Vol. 1: Theory and method. Hoboken, NJ: Wiley.Google Scholar
Oyama, S. (1985). The ontogeny of information: Developmental systems and evolution. New York, NY: Cambridge University Press.Google Scholar
Oyama, S. (1993). Constraints and development. Netherlands Journal of Zoology, 43, 616.CrossRefGoogle Scholar
Pinker, S. (1997). How the mind works. New York, NY: Norton.Google ScholarPubMed
Pinker, S. (2002). The blank slate: The modern denial of human nature. New York, NY: Viking.Google Scholar
Price, E. O. (1999). Behavioral development in animals undergoing domestication. Applied Animal Behavior Science, 65, 245271.CrossRefGoogle Scholar
Price, E. O., & King, J. (1968). Domestication and adaptation. In Hafez, E. S. (Ed.), Adaptation of domestic animals (pp. 3445). Philadelphia, PA: Lea and Febiger.Google Scholar
Provine, W. (1971). The origins of theoretical population genetics. Chicago: University of Chicago Press.Google Scholar
Renner, M. J., & Rosenzweig, M. R. (1987). Enriched and impoverished environments: Effects on brain and behavior. New York, NY: Springer-Verlag.CrossRefGoogle Scholar
Richardson, K. (1998). The origins of human potential: Evolution, development and psychology. London: Routledge.Google Scholar
Robert, J. S. (2004). Embryology, epigenesis, and evolution: Taking development seriously. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Rogers, L. J. (1995). The development of brain and behavior in the chicken. Wallingford, UK: CAB International.Google Scholar
Ronca, A. E., & Alberts, J. R. (1994). Sensory stimuli associated with gestation and parturition evoke cardiac and behavioral responses in fetal rats. Psychobiology, 55, 270282.Google Scholar
Rozenzweig, M. R., & Bennett, E. L. (1972). Cerebral changes in rats exposed individually to an enriched environment. Journal of Comparative and Physiological Psychology, 80, 304313.CrossRefGoogle Scholar
Russell, E. S. (1930). The interpretation of development and heredity. Oxford, England: Clarendon.Google Scholar
Schmalhausen, I. (1949). Factors of evolution: The theory of stabilizing selection. Oxford, England: Blakiston.Google Scholar
Simpson, G. G. (1944). Tempo and mode in evolution. New York, NY: Columbia University Press.Google Scholar
Spear, N. E, & McKenzie, D. L. (1994). Intersensory integration in the infant rat. In Lewkowicz, D. J. & Lickliter, R. (Eds.), The development of intersensory perception: Comparative perspectives (pp. 133161). Hillsdale, NJ: Erlbaum.Google Scholar
Sporns, O. (2011). Networks of the brain. Cambridge, MA: MIT Press.Google Scholar
Stotz, K. (2014). Extended evolutionary psychology: The importance of transgenerational developmental plasticity. Frontiers in Psychology, 5, 114.CrossRefGoogle ScholarPubMed
Urban, J. B., Osgood, N. D., & Mabry, P. L. (2011). Developmental systems science: Exploring the application of systems science methods to developmental science questions. Research in Human Development, 8, 125.CrossRefGoogle Scholar
Waddington, C. H. (1942). The epigenotype. Endeavour, 1, 1820.Google Scholar
Wallace, M. T., & Stein, B. E. (2007). Early experience determines how the senses will interact. Journal of Neurophysiology, 97, 921926.CrossRefGoogle ScholarPubMed
West, M. J., King, A. P., & White, D. J. (2003). The case for developmental ecology. Animal Behaviour, 66, 617622.CrossRefGoogle Scholar
West-Eberhard, M. J. (2003). Developmental plasticity and evolution. New York, NY: Oxford University Press.Google Scholar
Ainsworth, M. D. S., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: A psychology study of the strange situation. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Baier, A. (1986). Trust and antitrust. Ethics, 96(2), 231260. Retrieved from Scholar
Bowlby, J. (1969). Attachment and loss: Vol. 1. Attachment. New York, NY: Basic Books.Google Scholar
Carey, S. (1985). Conceptual change in childhood. Cambridge, MA: MIT Press.Google Scholar
Dautenhahn, K. (2004). Socially intelligent agents in human primate culture. In Trappl, R. & Payr, S. (Eds.), Agent culture: Human–agent interaction in a multicultural world (pp. 4571). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Ehrlich, P. R., & Ehrlich, A. H. (2008). The dominant animal: human evolution and the environment. Washington, DC: Island Press.Google Scholar
Erikson, E. H. (1950). Childhood and society. New York, NY: Norton.Google Scholar
Friedman, B., & Kahn, P. H. Jr. (2008). Human values, ethics, and design. In Jacko, J. A. & Sears, A. (Eds.), The human-computer interaction handbook: Fundamentals, evolving technologies, and emerging applications (pp. 12411266). Mahwah, NJ: Lawrence Erlbaum Associates. (Revised and updated chapter from the 2003 edition.)Google Scholar
Friedman, B., Kahn, P. H. Jr., & Borning, A. (2006). Value Sensitive Design and information systems. In Zhang, P. & Galletta, D. (eds.), Human-computer interaction in management information systems: Foundations (pp. 348372). Armonk, New York; London, England: M.E. Sharpe.Google Scholar
Friedman, B., Kahn, P. H. Jr., & Hagman, J. (2003). Hardware companions?: What online AIBO discussion forums reveal about the human-robotic relationship. Proceedings of the Conference on Human Factors in Computing Systems (pp. 273280). New York, NY: Association for Computing Machinery Press.CrossRefGoogle Scholar
Gelman, R. (2003). The essential child: Origins of essentialism in everyday thought. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
Green, A., Huttenrauch, H., & Eklundh, K. S. (2004). Applying the Wizard-of-Oz framework to cooperative service discovery and configuration. In Proceedings of the 13th International Workshop on Robot and Human Interactive Communication (RO-MAN ’04) (pp. 575580). Piscataway, NJ: IEEE.Google Scholar
Helwig, C. C. (1995). Adolescents’ and young adults’ conceptions of civil liberties: Freedom of speech and religion. Child Development, 66, 152166.CrossRefGoogle Scholar
Inagaki, K., & Hatano, G. (2002). Young children’s naïve thinking about the biological world. New York, NY: Psychology Press.Google Scholar
Jipson, J. L., & Gelman, S. A. (2007). Robots and rodents: Children’s inferences about living and nonliving kinds. Child Development, 78(6), 16751688. doi: 10.1111/j.1467-8624.2007.01095.xCrossRefGoogle ScholarPubMed
Kahn, P. H. Jr. (1992). Children’s obligatory and discretionary moral judgments. Child Development, 63(2), 416430.CrossRefGoogle ScholarPubMed
Kahn, P. H. Jr. (2011). Technological nature: Adaptation and the future of human life. Cambridge, MA: MIT Press.Google Scholar
Jr.Kahn, P. H., Freier, N., G., Kanda, T., Ishiguro, H., Ruckert, J. H., Severson, R. L., & Kane, S. K. (2008). Design patterns for sociality in human robot interaction. Proceedings of the 3rd ACM/IEEE International Conference on Human-Robot Interaction 2008 (pp. 271278). New York, NY: Association for Computing Machinery.Google Scholar
Jr.Kahn, P. H., Friedman, B., Perez-Granados, D. R., & Freier, N. G. (2006). Robotic pets in the lives of preschool children. Interaction Studies: Social Behavior and Communication in Biological and Artificial Systems, 7, 405436.CrossRefGoogle Scholar
Kahn, P. H. Jr., Gary, H. E., & Shen, S. (2013). Children’s social relationship with current and near-future robots. Child Development Perspectives, 7, 3237. doi: 10.1111/cdep.12011CrossRefGoogle Scholar
Kahn, P. H. Jr., Gill, B. T., Reichert, A. L., Kanda, T., Ishiguro, H., & Ruckert, J. H. (2010). Validating interaction patterns in HRI. Proceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction (pp.183184). New York, NY: Association for Computing Machinery.Google Scholar
Kahn, P. H. Jr., Kanda, T., Ishiguro, H., Freier, N. G., Severson, R. L., Gill, B. T., … Shen, S. (2012). “Robovie, you’ll have to go into the closet now”: Children’s social and moral relationships with a humanoid robot. Developmental Psychology, 48, 303314. doi: 10.1037/a0027033CrossRefGoogle ScholarPubMed
Kahn, P. H. Jr., Kanda, T., Ishiguro, H., Gill, B. T., Ruckert, J. H., Shen, S., … Severson, R. L. (2012). Do people hold a humanoid robot morally accountable for the harm it causes? Proceedings of the 7th ACM/IEEE International Conference on Human-Robot Interaction, 3340. doi: 10.1145/2157689.2157696
Kahn, P. H. Jr., Kanda, T., Ishiguro, H., Gill, B. T., Shen, S., Gary, H. E., & Ruckert, J. H. (2015). Will people keep the secret of a humanoid robot? – Psychological intimacy in HRI. Proceedings of the 10th ACM/IEEE International Conference on Human-Robot Interaction, (pp. 173180). New York, NY: Association for Computing Machinery.Google Scholar
Kahn, P. H. Jr., Reichert, A. L., Gary, H. E., Kanda, T., Ishiguro, H., Shen, S., … & Gill, B. T. (2011). The new ontological category hypothesis in human-robot interaction. Proceedings of the 6th ACM/IEEE International Conference on Human-Robot Interaction, 159160. doi: 10.1145/1957656.1957710
Kahn, P. H. Jr., Ruckert, J. H., Kanda, T., Ishiguro, H., Reichert, A., Gary, H., and Shen, S. (2010). Psychological intimacy with robots?: Using interaction patterns to uncover depth of relation. Proceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction (pp. 123124). New York, NY: Association for Computing Machinery.Google Scholar
Kahn, P. H. Jr., Severson, R. L., & Ruckert, J. H. (2009). The human relation with nature and technological nature. Current Directions in Psychological Science, 18, 3742.CrossRefGoogle Scholar
Kahn, P. H. Jr., & Turiel, E. (1988). Children’s conceptions of trust in the context of social expectations. Merrill-Palmer Quarterly, 34, 403419.Google Scholar
Keil, F. C. (1989). Concepts, kinds and cognitive development. Cambridge, MA: MIT Press.Google Scholar
Killen, M., & Smetana, J. G. (Eds.) (2006). Handbook of moral development. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Kurzweil, R. (2005). The singularity is near. New York, NY: Viking.Google Scholar
Levy, D. N. (2007). Love + sex with robots: The evolution of human-robot relations. New York, NY: HarperCollins.Google Scholar
MacDorman, K. F., & Ishiguro, H. (2006). The uncanny advantage of using androids in cognitive and social science research. Interaction Studies: Social Behavior and Communication in Biological and Artificial Systems, 7(3), 297337.CrossRefGoogle Scholar
Milgram, S. (1974). Obedience to authority. New York, NY: Harper & Row.Google Scholar
Rawls, J. (1971). A theory of justice. Cambridge: Harvard University Press.Google Scholar
Robins, B., Dautenhahn, K., Boekhorst, R. T., Billard, A. (2004). Robots as assistive technology – Does appearance matter? In Proceedings of the 13th International Workshop on Robot and Human Interactive Communication (RO-MAN ’04) (pp. 277282). Piscataway, NJ: IEEE.Google Scholar
Rotenberg, K. J. (Ed.). (2010). Interpersonal trust during childhood and adolescence. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Rotter, J. B. (1971). Generalized expectancies for interpersonal trust. American Psychologist, 26, 443452.CrossRefGoogle Scholar
Rotter, J. B. (1980). Interpersonal trust, trustworthiness, and gullibility. American Psychologist, 35, 17.CrossRefGoogle Scholar
Severson, R. L., & Carlson, S. M. (2010). Behaving as or behaving as if? Children’s conceptions of personified robots and the emergence of a new ontological category. Neural Networks, 23(8), 10991103.CrossRefGoogle ScholarPubMed
Short, E., Hart, J., Vu, M., & Scassellati, B. (2010). No fair!! An interaction with a cheating robot. Proceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction (pp. 219226). New York, NY: Association for Computing Machinery.Google Scholar
Smetana, J. G., & Braeges, J. (1990). The development of toddlers’ moral and conventional judgments. Merrill-Palmer Quarterly, 36, 329346.Google Scholar
Smetana, J. G., Schlagman, N., & Adams, P. W. (1993). Preschool children’s judgments about hypothetical and actual transgressions. Child Development, 64, 202214.CrossRefGoogle Scholar
Turiel, E. (1983). The development of social knowledge. Cambridge, England: Cambridge University Press.Google Scholar
Turiel, E. (1998). Moral development. In Damon, W. (Ed.), Handbook of child psychology. (5th ed.). Vol. 3: Eisenberg, N. (Ed.), Social, emotional, and personality development (pp. 863932). New York, NY: Wiley.Google Scholar
Wainryb, C. (1995). Reasoning about social conflicts in different cultures: Druze and Jewish children in Israel. Child Development, 66, 390401.CrossRefGoogle Scholar
Alim, H. S., Ibrahim, A., & Pennycook, A. (2008). Global linguistic flows: Hip hop cultures, youth identities, and the politics of language: New York, NY: Routledge.Google Scholar
Ball, A., & Farr, M. (2003). Language varieties, culture and teaching the English language arts. In Flood, J., Lapp, D., Squire, J., & Jensen, J. (Eds.), Handbook of research on teaching the English language arts (2nd edn., pp. 435445). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Bang, M., Medin, D. L., & Altran, S. (2007). Cultural mosaics and mental models of nature. Proceedings of the National Academy of Sciences (104), 1386813874.CrossRefGoogle ScholarPubMed
Belenky, M. F., Clinchy, B. M., Goldberger, N. R., & Tarule, J. M. (1986). The ways of knowing. In Belenky, M. F., Clinchy, B. M., Goldberger, N. R., & Tarule, J. M. (Eds.), Women’s ways of knowing: The development of self, voice, and mind (pp. 23131). New York, NY: Basic Books.Google Scholar
Boykin, A. W., Anderson, A. J., & Yates, J. (1979). Black psychology and the research process: Keeping the baby but throwing out the bath water. New York, NY: Russell Sage Foundation.Google Scholar
Bronfenbrenner, U. (1979). The ecology of human development: Experiment by nature and design. Cambridge, MA: Harvard University Press.Google Scholar
Bruer, J. (1999). In search of brain-based education. Phi Delta Kappan, 80(9), 648657.Google Scholar
Bruner, J. (1990). Acts of meaning. Cambridge, MA: Harvard University Press.Google Scholar
Cacioppo, J. T. (2002). Social neuroscience: Understanding the pieces fosters understanding the whole and vice versa. American Psychologist, 57, 819831.CrossRefGoogle ScholarPubMed
Cacioppo, J. T., Visser, P. S., & Pickett, C. L. (Eds.). (2005). Social neuroscience: People thinking about thinking people. Cambridge, MA: MIT Press.Google Scholar
Carey, S. (1985). Conceptual change in childhood. Cambridge, MA: Bradford Books.Google Scholar
Carlson, S. M., & Meltzoff, A. N. (2008). Bilingual experience and executive functioning in young children. Developmental Science, 11(2), 282298.CrossRefGoogle ScholarPubMed
Cole, M., & Scribner, S. (1974). Culture & thought: A psychological introduction. New York, NY: John Wiley & Sons.Google Scholar
Decety, J., Jackson, P. L., Sommerville, J. A., Chaminade, T., & Meltzoff, A. N. (2004). The neural bases of cooperation and competition: An fMRI investigation. NeuroImage, 23, 744751.CrossRefGoogle Scholar
Dunbar, K., Fugelsang, J., & Stein, C. (2007). Do naïve theories ever go away? Using brain and behavior to understand changes in concepts. In Lovett, M. C & Shah, P (Eds.)Thinking With Data, 193206. New York, NY: Erlbaum.Google Scholar
Dweck, C. S. (2002). Beliefs that make smart people dumb. In Sternberg, R. (Ed.), Why smart people can be so stupid. New Haven: Yale University Press.Google Scholar
Eccles, J. (2005). Subjective task values and the Eccles et al. Model of Achievement related choices. In Elliott, A. & Dweck, C. S. (Eds.), Handbook of competence and motivation. New York, NY: Guilford Press.Google Scholar
Farah, M., Betancourt, L., Shera, D., Savage, J., Giannetta, J., Brodsky, N., … & Hurt, H. (2008). Environmental stimulation, parental nurturance and cognitive development in humans. Developmental Science, 11(5), 793801.CrossRefGoogle ScholarPubMed
Farah, M., Shera, D., Savage, J., Betancourt, L., Giannetta, J., Brodsky, N., … Hurt, H. (2006). Childhood poverty: Specific associations with neuro-cognitive development. Brain Research, 1110(1), 166174.CrossRefGoogle Scholar
Fischer, K. W., & Bidell, T. R. (1998). Dynamic development of psychological structures in action and thought. In Damon, W. & Lerner, R. M. (Eds.), Handbook of child psychology: Theoretical models of human development (5th edn., Vol. 1, pp. 467562). New York, NY: Wiley & Sons.Google Scholar
Fisher, M. T. (2003). Open mics and open minds: Spoken word poetry in African diaspora participatory literacy communities. Harvard Education Review, 73(3), 362389.CrossRefGoogle Scholar
Flavell, J. H., & Miller, P. H. (1998). Social cognition. In Kuhn, D. & Siegler, R. (Eds.), Handbook of child psychology (5th edn., Vol. 2, pp. 851898). New York, NY: Wiley.Google Scholar
Gelman, R. (1990). First principles organize attention to and learning about relevant data: Number and the animate-inanimate distinction as examples. Cognitive Science, 14, 79106.CrossRefGoogle Scholar
Gopnic, A., Meltzoff, A., & Kuhl, P. (1999). The scientist in the crib: What early learning tells us about the mind. New York, NY: Harper Collins.Google Scholar
Gould, S. J. (1981). The mismeasure of man. New York, NY: W.W. Norton.Google Scholar
Graham, S. (1992). “Most of the subjects were white and middle class”: Trends in published research on African Americans in selected APA journals, 1970–1989. American Psychologist, 47(5), 629639CrossRefGoogle Scholar
Grande, S. M. A. (2000). American Indian geographies of identity and power: At the crossroads of Indigena and Mestizaje. Harvard Education Review, 70(4), 467498.CrossRefGoogle Scholar
Gutierrez, K., & Rogoff, B. (2003). Cultural ways of learning: Individual traits or repertoires of practice. Educational Researcher, 32(5), 1925.CrossRefGoogle Scholar
Hackman, D. A., Gallop, R., Evans, G. W., & Farah, M. J. (2015). Socioeconomic status and executive function: Developmental trajectories and mediation. Developmental Science, 18(5), 686702.CrossRefGoogle ScholarPubMed
Heckman, J. J. (2012). An effective strategy for promoting social mobility. Boston Review, 1015510162.
Helms, J. E., Jernigan, M., & Mascher, J. (2005). The meaning of race in psychology and how to change it: A methodological perspective. American Psychologist, 60(1), 2736.CrossRefGoogle Scholar
Hermes, M., Bang, M., & Marin, A. (2012). Designing indigenous language revitalization. Harvard Educational Review, 82(3), 381402.CrossRefGoogle Scholar
Johnston, B. H. (1976). Ojibway heritage. New York, NY: Columbia University Press.Google Scholar
Jones, R. L. (1980). Black psychology (2nd edn.). New York, NY: Harper & Row Publishers.Google Scholar
Kawagley, A. O. (1995). A Yupiaq worldview: A pathway to an ecology and spirit. Prospect Heights, IL: Waveland Press.Google Scholar
Kinloch, V. (2010). Harlem on our minds: Place, race, and the literacies of urban youth. New York, NY: Teachers College PressGoogle Scholar
Kohlberg, L. (1969). Stage and sequence: The cognitive-developmental approach to socialization. In Goslin, D. A. (Ed.), Handbook of socialization theory and research. Chicago: Rand-McNally.Google Scholar
Lawson, G. M., Hook, C. J., Hackman, D. A., Farah, M. J., Griffin, J. A., Freund, L. S., & McCardle, P. (2015). Socioeconomic status and neurocognitive development: Executive function. In Griffin, J, McCardle, P, & Freund, L (Eds) Executive Function in Preschool Children: Integrating Measurement, Neurodevelopment, and Translational Research. Washington, D.C.: American Psychological Association.Google Scholar
Lee, C. D. (1995). A culturally based cognitive apprenticeship: Teaching African American high school students skills in literary interpretation. Reading Research Quarterly, 30(4), 608631.CrossRefGoogle Scholar
Lee, C. D. (2001). Is October Brown Chinese: A cultural modeling activity system for underachieving students. American Educational Research Journal, 38(1), 97142.CrossRefGoogle Scholar
Lee, C. D. (2005). Culture and language: Bi-dialectical issues in literacy. In Anders, P. L. & Flood, J. (Eds.), Culture and language: Bi-dialectical issues in literacy. Newark, DE: International Reading Association.Google Scholar
Lee, C. D. (2007). Culture, literacy and learning: Taking bloom in the midst of the whirlwind. New York, NY: Teachers College Press.Google Scholar
Lee, C. D. (2008). The centrality of culture to the scientific study of learning and development: How an ecological framework in educational research facilitates civic responsibility. Educational Researcher, 37(5), 267279.CrossRefGoogle Scholar
Lee, C. D. (2009). Historical evolution of risk and equity: Interdisciplinary issues and critiques Review of Research in Education, 33, 63100.Google Scholar
Lee, C. D. (2010). Soaring above the clouds, delving the ocean’s depths understanding the ecologies of human learning and the challenge for education science. Educational Researcher, 39(9), 643655.CrossRefGoogle Scholar
Lee, C. D., Spencer, M. B., & Harpalani, V. (2003). Every shut eye ain’t sleep: Studying how people live culturally. Educational Researcher, 32(5), 613.CrossRefGoogle Scholar
Lomawaima, K. T., & McCarty, T. L. (2006). “ To remain an Indian”: Lessons in democracy from a century of Native American education. New York, NY: Teachers College Press.Google Scholar
Majors, Y. (2015). Shop talk. New York, NY: Teachers College Press.Google Scholar
McCarty, T., & Lee, T. (2014). Critical culturally sustaining/revitalizing pedagogy and indigenous education sovereignty. Harvard Educational Review, 84(1), 101124.CrossRefGoogle Scholar
Medin, D. L., Lee, C. D., & Bang, M. (2014). Particular points of view. Scientific American, 311(3), 4445.CrossRefGoogle ScholarPubMed
Meltzoff, A. N., & Decety, J. (2003). What imitation tells us about social cognition: A rapprochement between developmental psychology and cognitive neuroscience. Philosophical Transactions of the Royal Society of London, Biological Sciences, 358, 491500.CrossRefGoogle ScholarPubMed
Meltzoff, A. N., Kuhl, P. K., Movellan, J., & Sejnowski, T. J. (2009). Foundations for a new science of learning. Science, 325(5938), 284288.CrossRefGoogle ScholarPubMed
Meltzoff, A. N., & Moore, M. K. (1977). Imitation of facial and manual gestures by human neonates. Science, 198, 7578.CrossRefGoogle ScholarPubMed
Mintzes, J. J. (1984). Naive theories in biology: Children’s concepts of the human body. School Science and Mathematics, 84(7), 548555.CrossRefGoogle Scholar
Moses, R. P., & Cobb, C. E. (2001). Radical equations: Math literacy and civil rights. Boston: Beacon Press.Google Scholar
Moses, R. P., Kamii, M., Swap, S. M., & Howard, J. (1989). The algebra project: Organizing in the spirit of Ella. Harvard Educational Review, 59(4), 423443.CrossRefGoogle Scholar
Nadel, L., Lane, R., & Ahern, G. L. (Eds.). (2000). The cognitive neuroscience of emotion. New York, NY: Oxford University Press.Google Scholar
Nasir, N. (2000). “Points ain’t everything”: Emergent goals and average and percent understandings in the play of basketball among African American students. Anthropology and Education, 31(1), 283305.CrossRefGoogle Scholar
Nasir, N. (2002). Identity, goals, and learning: Mathematics in cultural practice. In Nasir, N. & Cobb, P. (Eds.), Mathematical thinking and learning: Special issue on diversity, equity and mathematics learning, Vol. 4 (nos. 2 & 3) (pp. 211247).CrossRefGoogle Scholar
Nasir, N. (2005). Individual cognitive structuring and the sociocultural context: Strategy shifts in the game of dominoes. Journal of the Learning Sciences, 14, 534.CrossRefGoogle Scholar
Nasir, N., Rosebery, A. S., Warren, B., & Lee, C. D. (2006). Learning as a cultural process: Achieving equity through diversity. In Sawyer, K. (Ed.), Handbook of the learning sciences. New York, NY: Cambridge University Press.Google Scholar
Nasir, N., & Saxe, G. (2003). Emerging tensions and their management in the lives of minority students. Educational Researcher, 32(5), 1418.CrossRefGoogle Scholar
Nobles, W. (1980). African philosophy: Foundations for black psychology. In Jones, R. L. (Ed.), Black psychology (2nd edn., pp. 2336). New York, NY: Harper & Row.Google Scholar
Noddings, N. (1984). Caring: A feminine approach to ethics and moral education. Berkeley, CA: University of California Press.Google Scholar
OECD. (2010). Pisa 2009 results: Overcoming social background. Equity in learning opportunities and outcomes (Vol. 2). Paris: OECD Publishing.
Paris, D., & Winn, M. T. (2013). Humanizing research: Decolonizing qualitative inquiry with youth and communities. Thousand Oaks, CA: Sage.Google Scholar
Quartz, S. R., & Sejnowski, T. J. (2002). Liars, lovers, and heroes: What the new brain science reveals about how we become who we are. New York, NY: William Morrow.Google Scholar
Rogoff, B. (2003). The cultural nature of human development. New York, NY: Oxford University Press.Google Scholar
Rosebery, A. S., Warren, B., Ballenger, C., & Ogonowski, M. (2005). The generative potential of students’ everyday knowledge in learning science. In Romberg, T., Carpenter, T., & Fae, D. (Eds.), Understanding mathematics and science matters. Mahwah, NJ: Erlbaum.Google Scholar
Rosebery, A. S., Warren, B., & Conant, F. R. (1992). Appropriating scientific discourse: Findings from language minority classrooms. The Journal of Learning Sciences, 2(1), 6194.CrossRefGoogle Scholar
Saxe, G. B. (1988). The mathematics of child street vendors. Child Development, 59, 14151425.CrossRefGoogle Scholar
Saxe, G. B. (1994). Studying cognitive development in sociocultural context: The development of a practice-based approach. Mind, Culture, and Activity, 1(3) 135157.CrossRefGoogle Scholar
Scribner, S., & Cole, M. (1973). Cognitive consequences of formal and informal education. Science, 182(4112), 553559.CrossRefGoogle ScholarPubMed
Sellers, R., Shelton, N., Cooke, D., Chavous, T., Rowley, S. J., & Smith, M. (1998). A multidimensional model of racial identity: Assumptions, findings, and future directions. In Jones, R. (Ed.), African American identity development (pp. 275303). Hampton, VA: Cobb & Henry Publishers.Google Scholar
Silva, C. M., Moses, R. P., Rivers, J., & Johnson, P. (1990). The algebra project: Making middle school mathematics count. Journal of Negro Education, 59(3), 375392.CrossRefGoogle Scholar
Spears, D. (2011). Economic decision-making in poverty depletes behavioral control. The BE Journal of Economic Analysis & Policy, 11(1), 142.Google Scholar
Spencer, M. B. (2006). Phenomenology and ecological systems theory: Development of diverse groups. In Damon, W. & Lerner, R. M. (Eds.), Handbook of child psychology (6th edn., Vol. 1, pp. 829893). New York, NY: Wiley.Google Scholar
Spencer, M. B., Fegley, S., & Dupree, D. (2006). Investigating and linking social conditions of African-American children and adolescents with emotional well-being. Ethnicity and Disease, 16(2), 6367.Google Scholar
Spencer, M. B., Fegley, S., & Harpalani, V. (2003). A theoretical and empirical examination of identity as coping: Linking coping resources to the self processes of African American youth. Journal of Applied Developmental Science, 7(3), 181187.CrossRefGoogle Scholar
Spencer, M. B., Harpalani, V., Cassidy, E., Jacobs, C., Donde, S., & Goss, T. N. (2006). Understanding vulnerability and resilience from a normative development perspective: Implications for racially and ethnically diverse youth. In Chicchetti, D. & Cohen, E. (Eds.), Handbook of developmental psychopathology (Vol. 1). Hoboken, NJ: Wiley.Google Scholar
Steele, C. M., Spencer, S. J., & Aronson, J. (2002). Contending with group image: The psychology of stereotype and social identity threat. Advances in Experimental Social Psychology, 34, 379440.CrossRefGoogle Scholar
Super, C., & Harkness, S. (1986). The developmental niche: A conceptualization at the interface of child and culture. International Journal of Behavioral Development, 9, 545569.CrossRefGoogle Scholar
Taylor, E. V. (2009). The purchasing practice of low-income students: The relationship to mathematical development. The Journal of the Learning Sciences, 18(3), 370415.CrossRefGoogle Scholar
Taylor, E. V. (2013). The mathematics of tithing: A study of religious giving and mathematical development. Mind, Culture, and Activity, 20(2), 132149.CrossRefGoogle Scholar
Valdes, G. (1996). Con respeto: Bridging the distances between culturally diverse families and schools. New York, NY: Teachers College Press.Google Scholar
Varma, S., McCandliss, B., & Schwartz, D. (2008). Scientific and pragmatic challenges for bridging education and neuroscience. Educational Researcher, 37(3), 140152.CrossRefGoogle Scholar
Varma, S., & Schwartz, D. (2008). How should educational neuroscience conceptualise the relation between cognition and brain function? Mathematical reasoning as a network process. Educational Research, 50(2), 149161.CrossRefGoogle Scholar
Warren, B., Ballenger, C., Ogonowski, M., Rosebery, A. S., & Hudicourt-Barnes, J. (2001). Rethinking diversity in learning science: The logic of everyday sense-making. Journal of Research in Science Teaching, 38, 529552.CrossRefGoogle Scholar
Warren, B., & Ogonowski, M. (2001, April). Embodied imagining: A study of adult learning in physics. Paper presented at the American Educational Research Association, Seattle.
Weisner, T. S. (1984). Ecocultural niches of middle childhood: A cross-cultural perspective. In Collins, W. A. (Ed.), Development during middle childhood: The years from six to twelve (pp. 335369). Washington, DC: National Academy of Sciences Press.Google Scholar
Weisner, T. S. (2002). Ecocultural understanding of children’s developmental pathways. Human Development, 174, 275281.CrossRefGoogle Scholar
Whitehead, C. (2010). The culture ready brain. Social Cognitive and Affective Neuroscience, 5, 168179.CrossRefGoogle ScholarPubMed
Wilson, E. O. (1998). Consilience: The unity of knowledge. New York, NY: Knopf.Google Scholar
Zajonc, R. B., & Marcus, H. (1984). Affect and cognition. In Izard, C. E., Kagan, J., & Zajonc, R. B. (Eds.), Emotions, cognition and behavior (pp. 73102). Cambridge, UK: Cambridge University Press.Google Scholar