Experimental Design John VanMeter, Ph.D. Center for Functional and Molecular Imaging

1. Experimental Design • John VanMeter, Ph.D. • Center for Functional and Molecular Imaging • Georgetown University Medical Center

2. Development of an fMRI Experiment

3. Independent and Dependent Variables • Independent variables are the parameters that are controlled by the experimenter • Dependent variables are the data measured by the experiment • One or more independent variables is manipulated in an experiment the effect of which will be measured by the dependent variables • In most fMRI studies the dependent variable is the change in BOLD fMRI signal

4. Types of Conditions • Two basic types of conditions are used in fMRI: • Experimental condition is the condition or task of interest • Control condition is the task that is subtracted from the experimental condition • Recall that BOLD contrast is non-quantitative

5. Possible Control Conditions for a Face Processing Study

6. Confounding Factors • Control condition should in general match the experimental condition as much as possible • Confounding factor is any parameter that varies with the independent variable • Selection of a good control condition is important to getting meaningful results

7. Alcohol Example • Suppose one found that there was a decrease in fMRI activation for a motor task when subjects drank alcohol as opposed to water • Possible conclusion is that alcohol reduces neuronal activity • However, should consider other possibilities such as whether the effect of alcohol caused these subject to perform the motor task at the wrong times or less frequently

8. Subtraction Method • Basic analysis is based on comparing fMRI signal between two conditions • Assumption is that cognitive process of interest is the only difference between the two conditions Petersen, et al., 1988

9. Pure Insertion Assumption • Insertion of a single cognitive process does not affect any other processes • Interactions between two cognitive processes would invalidate subtraction analysis • Violation of Pure Insertion would mean results uninterruptible

10. Example of Failure of Pure Insertion Assumption • Comparison of semantic and letter judgment tasks using three different modalities: mouse, vocal, and covert (silent/mental) • Interaction between modality and task in left inferior prefrontal cortex • Cannot distinguish whether change due to modality or task Jennings, et al., 1997

11. Analysis and Pure Insertion Assumption • Subtraction analysis assumes pure insertion holds - baseline/control task does not engage any other processes • Example • Subtraction of word naming from verb generation • Word naming does not require semantic processes • What if this control condition automatically engages these processes anyway

12. Main Design Models • Common Baseline • Parallel Comparisons • Tailored Baselines • Hierarchical • Parametric • Selective Attention • Adaptation

13. Common Baseline • Comparison of two experimental conditions to same control • Ex A > Ctrl • Ex B > Ctrl • Detects areas common to both conditions • Assumes both experimental conditions have similar psychometric properties (ie, task difficulty, equivalent degree of activation across subjects)

14. Parallel Comparisons • Compare both experimental tasks to each other (seeing vs hearing words) • Ex A > Ex B • Ex B > Ex A • Compliments Common Baseline • Assumes similar psychometric properties in both A and B

15. Tailored Baseline • Use different control tasks unique to each experimental condition • Ex A > Ctrl A • Ex B > Ctrl B • Example: • visual display of words vs. false font text • hearing words vs.reverse speech • Assumes each control task equally removes modality specifics • Assumes similar psychometric properties for all conditions - unlikely in most cases • Good idea to include a common baseline

16. Sensory Motor Semantic Hierarchical Subtraction • Three or more task conditions that progressively include additional factors • Ex A > Rest • Ex B > Ex A • Ex C > Ex B • Example: • Ex A = see words, no response • Ex B = repeat words verbally • Ex C = generate verb associated with word • Pure Insertion must hold at all levels

17. Parametric • Increasing level of difficulty or intensity of task • Variation along a single dimension • A > A > A > A • Example - working memory load • Useful for determining function in addition to “where” • Assumes Pure Modulation - • Different levels produce quantitative differences in level of engagement • Must be able to define magnitude of differences across levels

18. Variation of Rate of Extension and Flexion of Wrist Step function – fixed increase in activity irrespective of tapping rate Linear function – linear increase in activity with tapping rate VanMeter, et al., 1995

19. Differential Response Premotor Primary Motor (M1)

20. Selective Attention • Present same stimuli in all conditions but instruct subject to attend to different features • A B C • A B C • A B C • Can be done implicitly or explicitly • Assumes cognitive process is modified by what is attended to • Assumes variables of interest are modulated by selective attention • Assumes passive processing of unattended features does not include cognitive processes of attended feature

21. Selective Attention: Visual Processing • Corbetta, et al. presented squares, circles, and triangles that changed in color and moved • On each trial all three parameters were varied • By instructing subjects to attend to different features able to identify areas that respond uniquely to shape, color, and motion

22. Trial 1

23. Trial 2

24. Trial 3

25. Selective Visual Attention Results • Directed attention to specific features elicited selective activation in corresponding form, color, motion centers • Attention to motion -> V5/MT • Attention to color -> V2 • Attention to shape -> V1

26. Adaptation/Repetition Suppression • Repetitive presentation of same stimulus that produces change in level of activity (typically decreased) • Inference is that areas with diminished response are sensitive to stimulus features • Also used to diminish response using one type of stimulus to identify response to a novel stimulus • Pure Modulation Assumption - specific features of stimuli that produce reduction are qualitatively the same

27. Adaptation Selectivity Invariance for B Stimuli between A & B Stimuli

28. Adaptation in Visual Cortex Rebound Index = (% signal change per condition) / (% signal change for identical stimuli) Altmann et al., 2003

29. Main fMRI Designs for Task Presentation • Block Design • Multiple trials of the same condition are presented consecutively • Switch back and forth between blocks of experimental and control conditions • Event Related • Trials are presented separately and in “random” order with respect to experimental and control conditions

30. Reasons for Using Block or Event Related Designs • Block Designs • Better at detecting differences between conditions (detection) • Some experimental factors take time to occur (e.g. vigilance or sustained attention) • Event Related Designs • Better at detecting differences in HRF (estimation) • Some experimental factors are transient or infrequent events by nature (e.g. oddball or n-back tasks)

31. Considerations for Block Designs • Alternating between experimental and control conditions has limitations (e.g. noun vs verb reading) • Generally good idea to include null-task blocks - blocks where subjects do “nothing”; fixation on a cross preferred to “nothing” • Consider including a progression of blocks in which additional factors are added

32. Analysis of Block Designs • Subtraction of two conditions only statistical analysis possible of block designs* • Thus, baseline/ control events equal in importance to experimental condition • Lengths of block types should be equal

33. Block Length and Frequency • Short block lengths presented close together can limit return to baseline of HRF • Longer blocks maximize difference in signal between conditions • Best to use many blocks to minimize noise aliased at frequency of task presentation • Frequency of task should be relatively high to minimize low frequency noise such as scanner drift

34. Superposition and Block Design Indifference to HRF

35. Event Related (ER) Designs • Trials (aka events) are presented briefly in a random order • ISI (interstimulus interval) is the separation between events and is also randomized

36. Analysis of ER Designs • Average fMRI signal across all of the presentations of the same event type beginning from onset time of the event • Similar to ERP (event-related potential) analysis used in analysis of EEG data

37. Comparison of Block and ER Designs - Detection

38. ER Designs - Estimation

39. Principles of ER Designs • Boynton (1996) showed that amplitude and timing of hemodynamic response depends on both intensity and duration of stimulus • Dale and Buckner (1997) showed that it was possible to extract hemodynamic response function of two different events presented only 1-2 seconds apart

40. Overlap - Rapid ER • Difference in degree of activity due to reduced number of events as run length was kept constant

41. Overlap • Overlap of events possible due to “jitter” • Jitter is the randomization of ISI between events • Without jitter the 1-2 sec ISI will become equivalent to block design

42. ER Design Advantages • Flexibility in design • Not every experiment can be turned into block design • Flexibility in analysis as same event type can be treated differently • Trial sorting - choosing events to use in an analysis based on some other parameter such as correctness or reaction time

43. Semirandom Design • Slight reduction in detection power • But major increase in estimation efficiency

44. Mixed Designs • Uses a block-design presentation • Mix • Analysis is done using trial sorting (e.g. examining only trials with correct response) • Within a block presented more than one event type

45. Mixed Design Example - Alzheimer’s Disease • Two separate runs performed • Run1 (Encoding) • single words nouns presented • instructed to identify if animate or inanimate • Run2 (Retrieval) • 8 minutes later present nouns; half old half new • instructed to identify old vs new words • Analysis examined words in Run1 based on whether they were correctly remembered in Run2

46. Mixed Design Example - Alzheimer Study Remembered Trials > Forgotten Trials in the Encoding run VanMeter, et al. in preparation

48. Activations and Deactivations • Deactivation - decrease in hemodynamic response in task condition relative to control condition

49. Good Practices for Experimental Design • Simple methods for reducing confounding factors: • Randomization: randomize the order in which conditions presented • Could also be applied to experimenters; don’t have one person run all subjects from one group and a second person run all subjects from the other group • Counterbalancing: switch the order in which conditions are presented across subjects • Study with subjects assigned to one of two groups; try to ensure equal number of men and women in each group in case there are gender effects • Randomize order of runs across subjects; limits practice and order effects

50. Questions to Ask When Designing an Experiment