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Experimental Design

Experimental Design. FMRI Graduate Course (NBIO 381, PSY 362) Dr. Scott Huettel, Course Director . Experimental Design: Terminology. Variables Independent vs. Dependent Categorical vs. Continuous Contrasts Experimental vs. Control Parametric vs. subtractive Comparisons of subjects

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Experimental Design

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  1. Experimental Design FMRI Graduate Course (NBIO 381, PSY 362) Dr. Scott Huettel, Course Director FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  2. Experimental Design: Terminology • Variables • Independent vs. Dependent • Categorical vs. Continuous • Contrasts • Experimental vs. Control • Parametric vs. subtractive • Comparisons of subjects • Between- vs. Within-subjects • Confounding factors • Randomization, counterbalancing FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  3. What is fMRI Experimental Design? • Controlling the timing and quality of cognitive operations (IVs) to influence brain activation (DVs) • What can we control? • Stimulus properties (what is presented?) • Stimulus timing (when is it presented?) • Subject instructions (what do subjects do with it?) • What are the goals of experimental design? • To test specific hypotheses (i.e., hypothesis-driven) • To generate new hypotheses (i.e., data-driven) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  4. What types of hypotheses are possible for fMRI data? FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  5. Optimal Experimental Design • Maximizing both Detection and Estimation • Maximal variance in signal (incr. detect.) • Maximal variance in stimulus timing (incr. est.) • Limitations on Optimal Design • Refractory effects • Signal saturation • Subject’s predictability FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  6. fMRI Design Types • Blocked Designs • Event-Related Designs • Periodic Single Trial • Jittered Single Trial • Mixed Designs - Combination blocked/event-related FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  7. 1. Blocked Designs FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  8. What are Blocked Designs? • Blocked designs segregate different cognitive processes into distinct time periods Task A Task B Task A Task B Task A Task B Task A Task B Task A REST Task B REST Task A REST Task B REST FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  9. PET Designs • Measurements done following injection of radioactive bolus • Uses total activity throughout task interval (~30s) • Blocked designs necessary • Task 1 = Injection 1 • Task 2 = Injection 2 FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  10. Choosing Length of Blocks • Longer block lengths allow for stability of extended responses • Hemodynamic response saturates following extended stimulation • After about 10s, activation reaches max • Many tasks require extended intervals • Processing may differ throughout the task period • Shorter block lengths move your signal to higher frequencies • Away from low-frequency noise: scanner drift, etc. • Periodic blocks may result in aliasing of other variance in the data • Example: if the person breathes at a regular rate of 1 breath/5sec, and the blocks occur every 10s FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  11. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  12. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  13. Types of Blocked Design • Task A vs. Task B (… vs. Task C…) • Example: Squeezing Right Hand vs. Left Hand • Allows you to distinguish differential activation between conditions • Does not allow identification of activity common to both tasks • Can control for uninteresting activity • Task A vs. No-task (… vs. Task C…) • Example: Squeezing Right Hand vs. Rest • Shows you activity associated with task • May introduce unwanted results FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  14. Adapted from Gusnard & Raichle (2001) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  15. Any true baseline? Cerebral Blood Flow Cerebral Metabolic Rate of O2 Oxygen Extraction Fraction Adapted from Gusnard & Raichle (2001) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  16. Non-Task Processing • In many experiments, activation is greater in baseline conditions than in task conditions! • Requires interpretations of significant activation • Suggests the idea of baseline/resting mental processes • Gathering/evaluation about the world around you • Awareness (of self) • Online monitoring of sensory information • Daydreaming • This collection of processes is often called the “Default Mode” FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  17. Default Mode! Vision. Memory. Damoiseaux 2006 analyzed separate 10-subject resting-state data sets, using Independent Components analysis. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  18. Power in Blocked Designs • Summation of responses results in large variance FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  19. HDR Estimation: Blocked Designs FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  20. Deeper concept… We want the changes evoked by the task to be at different parts of the frequency spectrum than non-task-evoked changes. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  21. Limitations of Blocked Designs • Very sensitive to signal drift • Poor choice of conditions/baseline may preclude meaningful conclusions • Many tasks cannot be conducted repeatedly • Difficult to estimate the Hemodynamic Response FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  22. 2. Event-Related Designs FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  23. What are Event-Related Designs? • Event-related designs associate brain processes with discrete events, which may occur at any point in the scanning session. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  24. Why use event-related designs? • Some experimental tasks are naturally event-related • Allows studying of trial effects • Improves relation to behavioral factors • Simple analyses • Selective averaging • General linear models FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  25. 2a. Periodic Single Trial Designs • Stimulus events presented infrequently with long interstimulus intervals 500 ms 500 ms 500 ms 500 ms 18 s 18 s 18 s FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  26. McCarthy et al., (1997) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  27. 12sec 8sec 4sec Trial Spacing Effects: Periodic Designs 20sec FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  28. Why not short, periodic designs? ISI: Interstimulus Interval SD: Stimulus Duration From Bandettini and Cox, 2000 FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  29. 2b. Jittered Single Trial Designs • Varying the timing of trials within a run • Varying the timing of events within a trial FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  30. Effects of Jittering on Stimulus Variance FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  31. How rapidly can we present stimuli? Dale and Buckner (1997) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  32. Effects of ISI on Power Birn et al, 2002 FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  33. Efficient Experimental Design Maximal Relative Efficiency None Mean Interval between Stimuli (sec) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  34. Post-Hoc Sorting of Trials Using information about fMRI activation at memory encoding to predict behavioral performance at memory retrieval. From Kim and Cabeza, 2007 FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  35. Limitations of Event-Related Designs • None, really, at least with design itself. • The key issues are: • Can my subjects perform the task as designed? • Are the processes of interest independent from each other (in time, amplitude, etc.)? FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  36. You can model a block with events… Event-related model reaches peak sooner… Blocked (solid) Event-Related (dashed) … and returns to baseline more slowly. In this study, some language-related regions were better modeled by event-related. From Mechelli, et al., 2003 FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  37. 3. Mixed Designs FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  38. 3a. Mixed: Combination Blocked/Event • Both blocked and event-related design aspects are used (for different purposes) • Blocked design: state-dependent effects • Event-related design: item-related effects • Analyses can model these as separate phenomena, if cognitive processes are independent. • “Memory load effects” vs. “Item retrieval effects” • Or, interactions can be modeled. • Effects of memory load on item retrieval activation. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  39. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  40. FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  41. How do we identify efficient designs? FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  42. Issues in Design Efficiency • Not all random designs are equally efficient! • Design efficiency is defined in relation to some contrast • Efficiency may interact with predictability & expectation FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  43. Iterative (Genetic) Algorithms Select the most efficient designs Eliminate inefficient designs A B C A B C Designs A B C Designs A B C Retest modifications of efficient designs A B C FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

  44. Summary of Experiment Design • Main Issues to Consider • What design constraints are induced by my task? • What am I trying to measure? • What sorts of non-task-related variability do I want to avoid? • Rules of thumb • Blocked Designs: • Powerful for detecting activation • Useful for examining state changes • Event-Related Designs: • Powerful for estimating time course of activity • Allows determination of baseline activity • Best for post hoc trial sorting • Mixed Designs • Best combination of detection and estimation • Much more complicated analyses FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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