education and cognitive functioning lars nyberg umeå university sweden
TRANSCRIPT
Research on Aging at UmU
Ageing population Participation
Successful ageing
•Fertility•Mortality•Migration•Biologicalageing
•Work•Leisure•Social relations•Society•Image of ageing
•Health•Cognition•Economy•Network•Care
Interdisciplinaryresearch
Linnaeus database
Conceptualdevelopment
Ageing population Participation
Successful ageing
•Fertility•Mortality•Migration•Biologicalageing
•Work•Leisure•Social relations•Society•Image of ageing
•Health•Cognition•Economy•Network•Care
Interdisciplinaryresearch
Linnaeus database
Conceptualdevelopment
Ageing population Participation
Successful ageing
•Fertility•Mortality•Migration•Biologicalageing
•Work•Leisure•Social relations•Society•Image of ageing
•Health•Cognition•Economy•Network•Care
Interdisciplinaryresearch
Linnaeus database
Conceptualdevelopment
• 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 DatabaseStatistics Swedenregister data
Inpatient and death cause data
VIPVästerbottencounty
BetulaUmeå
Geographical extension
Sweden Sweden Västerbottencounty
Umeå
Number of individuals
Total national population
Total national population
110 000 4200
Time coverage 1960 – 19901990 - 2005
1980s - 2006 1987, 19.. 1988, 19..
Time resolution 5 year (60 -90)Annual (90-05)
Continuous 5 year
Spatial resolution
100 meter squares
Kind of information
Socio-economic
Income
Family (links)
Work
Residence etc.
Hospital care
Death
Death cause
Health indicators
Life style
Living conditions
Socio-economic
Cognitive function
Health
Socio-economic
The Betula Study: A prospective study of aging, memory & health
Sample Wave 1
(1988-90)
Wave 2
(1993-95)
Wave 3
(1998-00)
1 N=1000
35-80 yrs
N=862 (86%)
40-85 yrs
N=730 (85%)
45-90 yrs
2 N=1000
35-80 yrs
N=684 (86%)
50-85 yrs
3 N=1000
40-85 yrs
N=829 (83%)
45-90 yrs
4 N=600
35-90 yrs
Wave 4(2003-05)
609 (83%)50-95 yrs
698 (84%)50-95 yrs
S5: 56335-95 yrs
Total of > 4200 participants
Two sessions
1. Health examination
- current & past health
- demographics
- subjective measures
- social variables
- critical life events
- personality- genetics (APOE, COMT)
2. Cognitive testing
Cross-sectional analyses
• Episodic: significant decline already at age 45• Semantic memory: significant decline after 55
Rönnlund et al (2005) Psych & Aging
N = 1959
Longitudinal analyses
• Episodic: significant decline at age 80• Semantic : significant decline at age 85
Practice-adjusted data*
* P = D - A Difference (D) = S1T2 – S2T2 = Attrition (A) + Practice (P) A = S1T1 (returnees) – S1T1 (whole group);
• Episodic: significant decline at age 65• Semantic : significant decline at age 80
Comparing longitudinal and cross-sectional data
Cross-sectional data ≠ Practice-adjusted longitudinal data
Influence of cohort differences in education on cross-sectional data?
EducationSelf-reported # years of formal education
Education-adjusted cross-sectional data
Identical pattern as practice-adjusted longitudinal data(significant decline in episodic memory 60-65 yrs)
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
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 factoranalysis to identify usual and successful aging on basis oflongitudinal change in performance across cognitive andnon-cognitive variables (Habib, Nyberg & Nilsson, 2007).
--usual vs successful: based on performance levels at two test sessions and change in levels across sessions
Sample composition
Middle age = 50-65 at T1; 55-70 at T2
Measures
Results
55 / 663 successful (8.3%) 25 / 403 successful (6.2%)
Variables defining usual vs.successful aging
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
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)
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
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)
Group differences: brain structure
Hippocampal volume
Anterior white matter integrity
Functional changesCategorization vs Rest
Overall analysis (N=40) revealed bilateral frontal activity
Atypical right frontal activity driven by declining elderly-- compensatory response?
Both groups showedtypical left PFC activity
Fostering positive reversals: Cognitive training
”Spontaneous” positive reversals rare (2%) => directed training
Several recent demonstrations that training can improveperformance 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)
Training of updatingTime
FMRI I WEEK 1 WEEK 2 WEEK 3 WEEK 4 WEEK 5 FMRI IILM LMn-back n-backStroop Stroop
LV
M
31
4
Always memorize last 4 itemsVariable list length — 5-15 itemsAlso ”keep track” taskGraded training (3 levels; all at level 3 at week 5)Younger (15) and older adults in training groupControl group did fMRI I & IIExtensive transfer battery outside scanning18-month maintenance test session
Behavioral findings: criterion task
Substantial training effect in both groups
Significant long-term maintenance
Transfer
Speed-digit symbol
Working memory-computation span-digit span (F/B)-n-back (1/2/3)
Episodic memory-recall of nouns-paired associates
Semantic memory-letter fluence (FAS)-category fluency
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)
FMRI findings: young adultsPre-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)
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
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
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?