1. Methodological issues for scanning geriatric populations Andy James fMRI Journal Club October 12, 2004

2. 1)Participant selection criteria 2)Participants’ ability to perform task 3)Our ability to measure functional data Topics

3. Relevance of Aging Research Data from the US Bureau of the Census, 2000

4. Statistics for Participant Selection Criteria Older Americans 2000: Key Indicators of Well-Being Federal Interagency Forum on Aging-Related Statistics (Forum)

5. Conditions Affecting Participant Selection Criteria Neurological conditions depression strokes / infarcts memory impairment Physical conditions cardiac pacemaker artificial joints dental fixtures aneurysm clips arthritis spine curvature tattoos D’Esposito MD, Deouell L, and Gazzaley A. (2003). Nature Reviews, 4, 1-11

6. Participants’ Ability to Perform Functional Task Performance influenced by: Eyesight Hearing Arthritis Memory Attention and working memory Example: Serial Reaction Time task Participants make motor responses to viewed stimuli Young RT:  (sd) = 323 (17) ms Older RT:  (sd) = 524 (88) ms Howard JH and Howard DV. (1997) Psychology and Aging, 12, 634-656 Introducing a sequence to stimulus location results in decreased RTs (learning). Should paradigm be adjusted to accommodate longer RTs? Is a 100 ms learning gain in RT equivalent across groups? 300-600 ms Rest of trial response Total trial time: 1500 ms 300-600 ms Rest of trial response Total trial time: 1500 ms

7. Ability to compare functional data How do rigid / nonrigid transformations used to convert brains to Talairach or MNI space account for age-related morphology? (i.e. cortical shrinkage, ventricular enlargement) How can we compare sizes/shapes of ROIs across age groups? Head motion: stroke; age: mean 58 (range: 22-78) nonstroke; age: mean 59 (range 25-71) young; age: mean 28 (range 25-38) Seto E, Sela G, McIlroy WE et al.. 2001. Neuroimage, 14, 284-297

8. Functional signal detection Huettel SA, Singerman JD and McCarthy G. (2001). The effects of aging upon the hemodynamic response measured by functional MRI. Neuroimage, 13, 161-175. Claim 1: The hemodynamic response function (HRF) changes with age: CalcarineFusiform

9. Functional signal detection Claim 1: The hemodynamic response function (HRF) changes with age:

10. Functional signal detection Claim 1: The hemodynamic response function (HRF) changes with age: “Nonparametric comparison of relative standard deviation across all epoch time points revealed that elderly subjects had a higher standard deviation than had the young in 15 of 19 time points (p<.01).”

11. Functional signal detection Claim 2: Older participants have greater signal to noise ratios (SNRs) in activated voxels than younger participants Calcarine SD (ROI) Calcarine SD (voxel) Intersubject group variability

12. Functional signal detection Claim 2: Older participants have greater signal to noise ratios (SNRs) in activated voxels than younger participants SNR not due to head motion SNR differences largest when considering only single best voxel from ROI

13. Functional signal detection Claim 2: Older participants have greater SNRs in activated voxels than young Younger participants have significantly more active voxels (p<.001, both ROIs) Difference above is not an artifact from selected t-value (3.5) (note divergence at t=2.5)

14. Conclusions Claim 1: The hemodynamic response function (HRF) changes with age. HRF appears to peak earlier and return to baseline faster for older Results could be skewed by increased variability and a potential outlier in the older adult group D’Esposito (1999) found no age difference for motor cortex. Aizenstein (2003, 2004) and Richter and Richter (2003) found no age difference in when HRFs peaked, but a delayed return to baseline among older adults (~12+ s for older vs ~10 for younger participants) Aizenstein et al., 2004. The BOLD Hemodynamic response to aging. Journal of Cognitive Neuroscience, 16, 789-793.

15. Conclusions Claim 2: SNR decreases with age Older brains exhibit greater HRF variability Older brains are activated to a lesser spatial extent (smaller ROI areas) and to a lesser magnitude (t-value thresholds) SNR improves with the square root of trials performed Possibly due to attenuated return to baseline? (Aizenstein) ~1.5 SNR between groups means 2.25x as many trials for older adults How feasible is this for paradigms? Discussion: Your experiences with geriatric fMRI research.