1. NIA Neuroeconomics Workshop Scott Huettel, Duke University Neuroimaging the Aging Brain: Methodological Insights from Cognitive Neuroscience

2. NIA Neuroeconomics Workshop Scott Huettel, Duke University Major Themes: Methodology and Function How do neuroimaging methods change when studying elderly adults? Are there general principles underlying functional changes in the elderly brain, and how can those principles be addressed using neuroimaging?

3. NIA Neuroeconomics Workshop Scott Huettel, Duke University I. Methodological Changes

4. NIA Neuroeconomics Workshop Scott Huettel, Duke University Overview of Methodological Changes in Neuroimaging Functional MRI (fMRI) MRI Volumetrics Diffusion Tensor Imaging (DTI) Task Logistics

5. NIA Neuroeconomics Workshop Scott Huettel, Duke University Overview of Methods in Cognitive Neuroscience Neuronal activity vs. Metabolism Key idea: distinguish changes in our measure from changes in function.

6. NIA Neuroeconomics Workshop Scott Huettel, Duke University Neuronal Activity: Signaling and Integration Local field potentials (LFPs) reflect the summed activity of many neurons

7. NIA Neuroeconomics Workshop Scott Huettel, Duke University The fMRI Blood-Oxygenation-Level-Dependent (BOLD) Response Increased neuronal activity results in increased MR (T 2 *) signal BASELINE ACTIVE

8. NIA Neuroeconomics Workshop Scott Huettel, Duke University Neuronal origins of the fMRI Hemodynamic Response The fMRI BOLD response is predicted by dendritic activity (LFPs) Adapted from Logothetis et al. (2002)

9. NIA Neuroeconomics Workshop Scott Huettel, Duke University Age-Related Changes in Cerebrovascular System Structural changes that may have functional consequences Thickening of vessel walls Hypertension Venous occlusions Changes in capillary structure Reduced blood flow Reduced oxygen consumption (CMRO 2 ) Fang (1976)

10. NIA Neuroeconomics Workshop Scott Huettel, Duke University Do these Structural Changes Influence the fMRI BOLD Signal? Time since stimulus onset (sec) 012 BOLD Signal Change ~1% Huettel et al. (2001)

11. NIA Neuroeconomics Workshop Scott Huettel, Duke University Do these Structural Changes Influence the fMRI BOLD Signal? Probably not… No… and Yes Huettel et al. (2001) BOLD Amplitude BOLD Refractory Effects BOLD Signal-Noise Ratio Y E Y E Y E Y1 E1 Y2 E2 Two of three studies report that BOLD amplitude is similar in young (Y) and elderly (E) adults. Two studies report that the BOLD signal has similar refractory properties (i.e., to multiple events in rapid succession) in young and elderly adults. Two studies report that the BOLD signal has reduced signal-noise ratio (SNR) in elderly adults. D’Esposito et al. (1999) Buckner et al. (2000) Y1 E1 Y2 E2 YEE/Y

12. NIA Neuroeconomics Workshop Scott Huettel, Duke University How does Increased Noise affect fMRI Analyses? Simulations show clear effects on spatial extent Huettel et al., 2001 SNR = 0.10 SNR = 0.15 SNR = 0.25 SNR = 1.00 SNR = 0.52 (Young) SNR = 0.35 (Old) Number of Trials Averaged Number of Supra-threshold Voxels Age-related differences in how much of the brain is activated may reflect differences in SNR, not cognition.

13. NIA Neuroeconomics Workshop Scott Huettel, Duke University Conclusions: Aging and BOLD fMRI Effects not in principle, but for practice FMRI is a hemodynamic measure Aging causes cardiovascular changes BOLD response form unchanged with age BOLD response SNR decreased with age Problematic for between-group comparisons Suggestion: Group by Condition testing

14. NIA Neuroeconomics Workshop Scott Huettel, Duke University Structural Changes in the Elderly Brain: Gray Matter Different brain regions exhibit different patterns of lifespan change Data from Raz et al. (2004); figure from Hedden & Gabrieli (2004) These effects are attributable primarily to loss of synaptic density (secondarily, to cell death). Image courtesy Gregory McCarthy

15. NIA Neuroeconomics Workshop Scott Huettel, Duke University Structural Changes in the Elderly Brain: White Matter Measurement using diffusion tensor imaging (DTI) Fractional Anisotropy (FA) FA ~ 0 FA ~ 1

16. NIA Neuroeconomics Workshop Scott Huettel, Duke University White Matter Maps: Diffusion Tensor Maps Diffusion tends to be less anisotropic in elderly adults OlderYounger

17. NIA Neuroeconomics Workshop Scott Huettel, Duke University DTI: White-Matter Changes with Aging Reduced Fractional Anisotropy Genu Region of Interest FA Older Younger.20.30.40.50.60.70.80 SFGPCF PVFFGALCSpleniumPAR Key fiber tracts in the human brain Data from Madden et al. (2004) White matter integrity, assessed in central voxels, decreases in the elderly

18. NIA Neuroeconomics Workshop Scott Huettel, Duke University DTI: White-Matter Changes with Aging Reduced Fractional Anisotropy Data from Madden et al. (2004) Different white matter tracts mediate performance in young and elderly.

19. NIA Neuroeconomics Workshop Scott Huettel, Duke University Logistical Changes Differences in experimental procedures Reduced tolerance for time in scanner Time  Power  Elderly adults, in our experience, generally tolerate sessions of 60-75 minutes – with substantial individual variation. Younger adults tolerate sessions of 75-90 minutes. Head motion is more extensive in the elderly. Young Elderly

20. NIA Neuroeconomics Workshop Scott Huettel, Duke University Logistical Changes Differences in experimental procedures Reduced tolerance for time in scanner Reduced sensory abilities

21. NIA Neuroeconomics Workshop Scott Huettel, Duke University Logistical Changes Differences in experimental procedures Reduced tolerance for time in scanner Reduced sensory abilities Reduced performance on many tasks NST = nonsingleton target ; ST = singleton target Excerpts from Madden et al. (2004a, 2004b, 2006)

22. NIA Neuroeconomics Workshop Scott Huettel, Duke University Logistical Changes Differences in experimental procedures Reduced tolerance for time in scanner Reduced sensory abilities Reduced performance on many tasks Biased sample selection

23. NIA Neuroeconomics Workshop Scott Huettel, Duke University The “Super Elderly” Performance, on many scales, approximates or exceeds the young Excerpts from Madden et al. (2004a, 2004b) Is the typical elderly adult someone who is college-educated, has no significant health problems, is taking only minimal medication, and has a vocabulary (etc.) similar to a Duke undergraduate?

24. NIA Neuroeconomics Workshop Scott Huettel, Duke University Logistical Changes Differences in experimental procedures for elderly subjects Reduced tolerance for time in scanner Reduced sensory abilities Reduced performance on many tasks Biased sample selection Different motivation for participating Excerpt from Hertwig & Ortmann (2001) ? ?

25. NIA Neuroeconomics Workshop Scott Huettel, Duke University II. Functional Changes

26. NIA Neuroeconomics Workshop Scott Huettel, Duke University Overview of Functional Changes Memory Control processes Emotion and affect Reward evaluation Theme I: Selective and Non-selective deficits Theme II: Functional compensation ?

27. NIA Neuroeconomics Workshop Scott Huettel, Duke University Selective Deficits: Memory Aging has greater effects on recollection (hippocampally mediated) Cabeza et al., 2006 Elderly: Attenuation of recollection-based activation in hippocampus. Elderly: Enhancement of familiarity-based activation in rhinal cortex.

28. NIA Neuroeconomics Workshop Scott Huettel, Duke University Non-Selective Deficits: Emotion Similar regions, but less extensive activation, in the elderly Wright et al., 2006 < Tessitore et al., 2005

29. NIA Neuroeconomics Workshop Scott Huettel, Duke University Compensation: Memory Elderly adults recruit additional regions to maintain performance Cabeza et al., 2002a In a memory retrieval task, elderly adults who perform similarly to young adults (Old-High) show increased activation in left PFC, compared to elderly adults with impaired performance.

30. NIA Neuroeconomics Workshop Scott Huettel, Duke University Compensation: Memory (and other) Frontal compensation is a robust phenomenon Cabeza, 2002; Cabeza et al., 2004 The reductions in asymmetry are found both when hemispheric specialization is based on process (e.g., memory retrieval / encoding) and when based on stimulus domain (e.g., verbal / spatial working memory).

31. NIA Neuroeconomics Workshop Scott Huettel, Duke University Compensation: Attention Increased frontal activation in elderly adults under divided attention Madden et al., 1997 Divided minus Central Younger Adults Older Adults F S W H M D B T G N Z L T R J Q T Y

32. NIA Neuroeconomics Workshop Scott Huettel, Duke University Compensation: Executive Control Elderly adults recruit additional, non-prefrontal regions Madden et al., 2004 Posano et al., 2005 Younger adults: Prefrontal Cortex Elderly adults: Thalamus/BG Elderly adults: Parietal Cortex

33. NIA Neuroeconomics Workshop Scott Huettel, Duke University Compensation: Methodological Caveats fMRI provides information about what’s active, not what’s not active Cabeza, 2002

34. NIA Neuroeconomics Workshop Scott Huettel, Duke University Selective Deficits, Compensation: Reward systems? Almost nothing known… hence, this meeting.

35. NIA Neuroeconomics Workshop Scott Huettel, Duke University Acknowledgments Faculty collaborators, discussed projects David Madden Roberto Cabeza Len White Gregory McCarthy External support NIMH (Huettel) NINDS (McCarthy) NIA (Madden, Cabeza) neuroeconomics.duke.edu Current Laboratory Members Alexandru Avram J. Neil Bearden Jacqui Detwiler Erin Douglas Wilko Schultz-Mahlendorf Mark Sutherland Dharol Tankersley Bethany Weber Recommended Readings: Cabeza, Nyberg, & Park (2005). Cognitive Neuroscience of Aging. Oxford Univ. Press Hedden & Gabrieli (2004). Nature Reviews Neuroscience D’Esposito, Deouell, & Gazzaley (2003). Nature Reviews Neuroscience All uncredited figures from: Huettel, Song, & McCarthy (2004). Functional Magnetic Resonance Imaging