A Window of Opportunity for Cognitive Training in Adolescence

Psychological Science

Volumn 27, Issue 12, 2016, Pages 1620-1631

  Knoll, Lisa J ^a   Fuhrmann, Delia ^a   Sakhardande, Ashok L ^a   Stamp, Fabian ^a   Speekenbrink, Maarten ^b   Blakemore, Sarah Jayne ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

adolescence; cognitive development; cognitive training; education; learning; plasticity; sensitive periods

Indexed keywords

ADOLESCENT; CHILD; COGNITION; EDUCATION; FACIAL RECOGNITION; FEMALE; HUMAN; LEARNING; MALE; PHYSIOLOGY; THINKING; YOUNG ADULT;

ADOLESCENT; CHILD; COGNITION; EDUCATION; FACIAL RECOGNITION; FEMALE; HUMANS; LEARNING; MALE; THINKING; YOUNG ADULT;

EID: 85006142681     PISSN: 09567976     EISSN: 14679280     Source Type: Journal    
DOI: 10.1177/0956797616671327     Document Type: Article

References (41)

1. Bates D. J., Maechler M., Bolker B., (2014). lme4: Linear-mixed effects models using S4 classes (Version 1.1-7) [Software]. Retrieved from http://CRAN.R-project.org/package=lme4
2. Bergman-Nutley S., Klingberg T., (2014). Effect of working memory training on working memory, arithmetic and following instructions. Psychological Research, 78, 869–877. doi:10.1007/s00426-014-0614-0
3. Blakemore S.-J., Robbins T. W., (2012). Decision-making in the adolescent brain. Nature Neuroscience, 15, 1184–1191.
4. Carey S., Diamond R., Woods B., (1980). Development of face recognition: A maturational component? Developmental Psychology, 16, 257–269. doi:10.1037/0012-1649.16.4.257
5. Chuderski A., (2014). The relational integration task explains fluid reasoning above and beyond other working memory tasks. Memory & Cognition, 42, 448–463. doi:10.3758/s13421-013-0366-x
6. Cohen Kadosh K. (2011). Differing processing abilities for specific face properties in mid-childhood and adulthood. Frontiers in Psychology, 2, Article 400. doi:10.3389/fpsyg.2011.00400
7. Cohen Kadosh K., Johnson M. H., Dick F., Cohen Kadosh R., Blakemore S.-J. (2013). Effects of age, task performance, and structural brain development on face processing. Cerebral Cortex, 23, 1630–1642. doi:10.1093/cercor/bhs150
8. Crone E. A., Wendelken C., Donohue S., van Leijenhorst L., Bunge S. A., (2006). Neurocognitive development of the ability to manipulate information in working memory. Proceedings of the National Academy of Sciences, USA, 103, 9315–9320. doi:10.1073/pnas.0510088103
9. Dehaene S., Piazza M., Pinel P., Cohen L., (2003). Three parietal circuits for number processing. Cognitive Neuropsychology, 20, 487–506. doi:10.1080/02643290244000239
10. DeWind N. K., Brannon E. M., (2012). Malleability of the approximate number system: Effects of feedback and training. Frontiers in Human Neuroscience, 6, Article 68. doi:10.3389/fnhum.2012.00068
11. Dolzycka D., Herzmann G., Sommer W., Wilhelm O., (2014). Can training enhance face cognition abilities in middle-aged adults? PLoS ONE, 9(3), Article e90249. doi:10.1371/journal.pone.0090249
12. Duchaine B., Nakayama K., (2006). The Cambridge Face Memory Test: Results for neurologically intact individuals and an investigation of its validity using inverted faces stimuli and prosopagnosic participants. Neuropsychologia, 44, 576–585. doi:10.1016/j.neuropsychologia.2005.07.001
13. Dumontheil I., (2014). Development of abstract thinking during childhood and adolescence: The role of rostrolateral prefrontal cortex. Developmental Cognitive Neuroscience, 10, 1–20. doi:10.1016/j.dcn.2014.07.009
14. Dumontheil I., Houlton R., Christoff K., Blakemore S.-J., (2010). Development of relational reasoning during adolescence. Developmental Science, 13(6), 15–24. doi:10.1111/j​.1467-7687.2010.01014.x
15. Dumontheil I., Klingberg T., (2012). Brain activity during a visuospatial working memory task predicts arithmetical performance 2 years later. Cerebral Cortex, 22, 1078–1085. doi:10.1093/cercor/bhr175
16. Ferster C. R., Skinner B. F., (1957). Schedules of reinforcement. Englewood Cliffs, NJ: Prentice-Hall.
17. Fuhrmann D., Knoll L. J., Blakemore S.-J., (2015). Adolescence as a sensitive period of brain development. Trends in Cognitive Sciences, 10, 558–566. doi:10.1016/j​.tics.2015.07.008
18. Giedd J. N., Rapoport J. L., (2010). Structural MRI of pediatric brain development: What have we learned and where are we going? Neuron, 67, 728–734. doi:10.1016/j.neuron​.2010.08.040
19. GIMP Team. (2013). GNU image manipulation program (Version 2.8.8) [Computer software]. Retrieved from http://www.gimp.org
20. Goodwin G. P., Johnson-Laird P. N., (2005). Reasoning about relations. Psychological Review, 112, 468–493. doi:10.1037/0033-295X.112.2.468
21. Gur R. C., Richard J., Calkins M. E., Chiavacci R., Hansen J. A., Bilker W. B.,.. Gur R. E., (2012). Age group and sex differences in performance on a computerized neurocognitive battery in children age 8–21. Neuropsychology, 26, 251–265. doi:10.1037/a0026712
22. Halberda J., Ly R., Wilmer J. B., Naiman D. Q., Germine L., (2012). Number sense across the lifespan as revealed by a massive Internet-based sample. Proceedings of the National Academy of Sciences, USA, 109, 11116–11120. doi:10.1073/pnas.1200196109
23. Heckman J. J., (2006). Skill formation and the economics of investing in disadvantaged children. Science, 312, 1900–1902. doi:10.1126/science.1128898
24. Holmes J., Gathercole S. E., (2014). Taking working memory training from the laboratory into schools. Educational Psychology, 34, 440–450. doi:10.1080/01443410.2013.797338
25. Hothorn T., Bretz F., Westfall P., (2008). Simultaneous inference in general parametric models. Biometrical Journal, 50, 346–363. doi:10.1002/bimj.200810425
26. Houdé O., Rossi S., Lubin A., Joliot M., (2010). Mapping numerical processing, reading, and executive functions in the developing brain: An fMRI meta-analysis of 52 studies including 842 children. Developmental Science, 13, 876–885.
27. Jaeggi S. M., Buschkuehl M., Jonides J., Perrig W. J., (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences, USA, 105, 6829–6833. doi:10.1073/pnas.0801268105
28. Klingberg T., (2010). Training and plasticity of working memory. Trends in Cognitive Sciences, 14, 317–324. doi:10.1016/j.tics.2010.05.002
29. Klingberg T., Fernell E., Olesen P. J., Johnson M., Gustafsson P., Dahlström K.,.. Westerberg H., (2005). Computerized training of working memory in children with ADHD—a randomized, controlled trial. Journal of the American Academy of Child & Adolescent Psychiatry, 44, 177–186. doi:10.1097/00004583-200502000-00010
30. Kuhl P. K., (2004). Early language acquisition: Cracking the speech code. Nature Reviews Neuroscience, 5, 831–843. doi:10.1038/nrn1533
31. Lewis T. L., Maurer D., (2005). Multiple sensitive periods in human visual development: Evidence from visually deprived children. Developmental Psychobiology, 46, 163–183. doi:10.1002/dev.20055
32. Mackey A. P., Hill S. S., Stone S. I., Bunge S. A., (2011). Differential effects of reasoning and speed training in children. Developmental Science, 14, 582–590. doi:10.1111/j​.1467-7687.2010.01005.x
33. Mackey A. P., Whitaker K. J., Bunge S. A., (2012). Experience-dependent plasticity in white matter microstructure: Reasoning training alters structural connectivity. Frontiers in Neuroanatomy, 6, Article 32. doi:10.3389/fnana​.2012.00032
34. Owen A. M., Hampshire A., Grahn J. A., Stenton R., Dajani S., Burns A. S.,.. Ballard C. G., (2010). Putting brain training to the test. Nature, 465, 775–778. doi:10.1038/nature09042
35. Park J., Brannon E. M., (2013). Training the approximate number system improves math proficiency. Psychological Science, 24, 2013–2019. doi:10.1177/0956797613482944
36. Phillips P. J., Moon H., Rizvi S. A., Rauss P. J., (2000). The FERET evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 1090–1104. doi:10.1109/34.879790
37. Raven J. C. (1960). Guide to the standard progressive matrices: Sets A, B, C, D and E. London, England: H. K. Lewis.
38. R Development Core Team. (2013). R: A language and environment for statistical computing (Version 3.02) [Computer software]. Retrieved from https://www.r-project.org/index.html
39. Steinberg L., (2010). Adolescence (9th ed.). New York, NY: McGraw-Hill Higher Education.
40. Tamnes C. K., Østby Y., Fjell A. M., Westlye L. T., Due-Tønnessen P., Walhovd K. B., (2010). Brain maturation in adolescence and young adulthood: Regional age-related changes in cortical thickness and white matter volume and microstructure. Cerebral Cortex, 20, 534–548. doi:10.1093/cercor/bhp118
41. Thorell L. B., Lindqvist S., Bergman Nutley S., Bohlin G., Klingberg T., (2009). Training and transfer effects of executive functions in preschool children. Developmental Science, 12, 106–113. doi:10.1111/j.1467-7687.2008.00745.x