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Education and Cognitive Functioning

Education and Cognitive Functioning. Lars Nyberg Umeå University Sweden. Research on Aging at UmU. Cross-faculty environment ” Aging and Living Conditions ” (ALC) One of 10 national ”Linnaeus” centra funded by the Swedish Research Council Three main themes:. The Linnaeus Database.

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Education and Cognitive Functioning

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  1. Education and Cognitive Functioning Lars Nyberg Umeå University Sweden

  2. Research on Aging at UmU • Cross-faculty environment ”Aging and Living Conditions” (ALC) • One of 10 national ”Linnaeus” centra funded by the Swedish Research Council • Three main themes:

  3. The Linnaeus Database

  4. Wave 4 (2003-05) 609 (83%) 50-95 yrs 698 (84%) 50-95 yrs S5: 563 35-95 yrs The Betula Study:A prospective study of aging, memory & health Total of > 4200 participants

  5. Two sessions 1. Health examination - current & past health - demographics - subjective measures - social variables - critical life events - personality - genetics (APOE, COMT) 2. Cognitive testing

  6. N = 1959 • Episodic: significant decline already at age 45 • Semantic memory: significant decline after 55 Rönnlund et al (2005) Psych & Aging Cross-sectional analyses

  7. Practice-adjusted data* • Episodic: significant decline at age 65 • Semantic : significant decline at age 80 * P = D - A Difference (D) = S1T2 – S2T2 = Attrition (A) + Practice (P) A = S1T1 (returnees) – S1T1 (whole group); Longitudinal analyses • Episodic: significant decline at age 80 • Semantic : significant decline at age 85

  8. Comparing longitudinal and cross-sectional data Cross-sectional data ≠ Practice-adjusted longitudinal data Influence of cohort differences in education on cross-sectional data?

  9. EducationSelf-reported # years of formal education

  10. Education-adjusted cross-sectional data Identical pattern as practice-adjusted longitudinal data (significant decline in episodic memory 60-65 yrs)

  11. Intermediate summary Cohort differences in education account for disparity between cross-sectional and longitudinal trajectories across the adult age span -- control removes early onset of episodic decline (35-60) Substantial portion of the age-related variance remained after controlling for education in the 5 oldest cohorts

  12. Variability in cognitive aging Most studies consider group-averaged cognitive changes -- less focus on distribution of individual scores => => Some elderly with a high level of functioning are ”hidden” Inspired by Rowe and Kahn (1987) we used Q-mode factor analysis to identify usual and successful aging on basis of longitudinal change in performance across cognitive and non-cognitive variables (Habib, Nyberg & Nilsson, 2007). --usual vs successful: based on performance levels at two test sessions and change in levels across sessions

  13. Sample composition Middle age = 50-65 at T1; 55-70 at T2

  14. Measures

  15. Results 25 / 403 successful (6.2%) 55 / 663 successful (8.3%)

  16. Variables defining usual vs.successful aging

  17. 352 of the 608 usual elderly at T1 were re-tested at T2 Of these 352, 345 (98%) were again classified as usual -- 7 (2%) were classified as successful (”positive reversal”) • Predictors of success over time: • Successful-Successful (N=18) vs Successful-Usual (N=33) • no difference on cognitive measures • one difference on non-cognitive measures; education • (12.1 vs 9.6 years) Longitudinal analysis 51 of the 55 successful elderly at T1 were re-tested at T2 Of these 51, 18 (35%) were again classified as successful

  18. Participants from the Betula Study (selected from population of 1000 ss at T1) ’Memory’ defined by 3 episodic tests • 2002-03: MRI/fMRI-session • fMRI – categorization task (abs/conc) • - left PFC activity for young adults (Wagner et al. 2000, Cer Cortex) • Hippocampus volume • Diffusion Tensor Imaging (DTI) Neural correlates of success over time (Persson et al., 2006, Cerebral Cortex) • Stable & Decline groups well matched (N=20/20): • Age: 68.2 / 68.2 • MMSE: 28.25 / 28.35 • Female/male: 13/7 / 13/7 • Education: 10.1 / 10.7

  19. Hippocampal volume Anterior white matter integrity Group differences: brain structure

  20. Overall analysis (N=40) revealed bilateral frontal activity Both groups showed typical left PFC activity Atypical right frontal activity driven by declining elderly -- compensatory response? Functional changesCategorization vs Rest

  21. Fostering positive reversals: Cognitive training ”Spontaneous” positive reversals rare (2%) => directed training Several recent demonstrations that training can improve performance on various executive tasks (e.g. working memory) - transfer / generalization of learning more difficult to show Present study: updating training (Dahlin et al., 2008, Science; Dahlin et al., 2009, Psychology & Aging)

  22. Time L V 3 1 M FMRI I WEEK 1 WEEK 2 WEEK 3 WEEK 4 WEEK 5 FMRI II LM LM n-back n-back Stroop Stroop 4 Always memorize last 4 items Variable list length — 5-15 items Also ”keep track” task Graded training (3 levels; all at level 3 at week 5) Younger (15) and older adults in training group Control group did fMRI I & II Extensive transfer battery outside scanning 18-month maintenance test session Training of updating

  23. Significant long-term maintenance Behavioral findings: criterion task Substantial training effect in both groups

  24. Transfer Semantic memory -letter fluence (FAS) -category fluency Speed -digit symbol Working memory -computation span -digit span (F/B) -n-back (1/2/3) Episodic memory -recall of nouns -paired associates Reasoning -Raven’s Limited transfer effects -no significant transfer for elderly group -significant transfer to 3-back working memory of numbers for young (transfer effect maintained after 18 months)

  25. FMRI findings: young adults Pre-training -- fronto-parietal activity for all 3 tasks -- striatal activity for LM & 3-back Training-related changes --no common fronto-parietal changes --overlapping increase in striatum for LM & 3-back (No significant training-related fMRI changes on Stroop)

  26. FMRI findings: older adults • Pronounced fronto-parietal activity during LM prior to training • No significant striatal activation during LM prior to training • Training-related striatal increase for LM (cf., younger adults) • No training-related increase for 3-back Variability within older group – those who showed transfer displayed striatal activation

  27. Summary • Substantial and durable training effects in both groups • Weak transfer effects • More narrow view on process-region overlap • No support that a task-general fronto-parietal system mediates transfer • Support that transfer rests on shared process (updating) and related striatal brain system

  28. Concluding points • Education – substantial influence on ”cognitive profile” across the adult life span • Strong impact on slope for younger cohorts • Education also explains some of the heterogeneity among older adults • Neural changes additional factor • Hippocampus & striatum; ant. WM changes • Functional compensation? • Next step: Imaging at Betula T5 • Brain x education interactions?

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