1. Basics of Experimental Design for fMRI
fMRI: theory and practice (2012 spring)
Last Update: November 2008

2. Asking the Right Question
Part I
Asking the Right Question

3. “Attending a poster session at a recent meeting, I was reminded of the old adage ‘To the man who has only a hammer, the whole world looks like a nail.’ In this case, however, instead of a hammer we had a magnetic resonance imaging (MRI) machine and instead of nails we had a study. Many of the studies summarized in the posters did not seem to be designed to answer questions about the functioning of the brain; neither did they seem to bear on specific questions about the roles of particular brain regions. Rather, they could best be described as ‘exploratory’. People were asked to engage in some task while the activity in their brains was monitored, and this activity was then interpreted post hoc.”
-- Stephen M. Kosslyn (1999). If neuroimaging is the answer, what is the question? Phil Trans R Soc Lond B, 354,

4. Brains Needed
"...the single most critical piece of equipment is still the researcher's own brain. All the equipment in the world will not help us if we do not know how to use it properly, which requires more than just knowing how to operate it. Aristotle would not necessarily have been more profound had he owned a laptop and known how to program. What is badly needed now, with all these scanners whirring away, is an understanding of exactly what we are observing, and seeing, and measuring, and wondering about."
-- Endel Tulving, interview in Cognitive Neuroscience (2002, Gazzaniga , Ivry & Mangun, Eds., NY: Norton, p. 323)

5. “Expensive equipment doesn’t merit a lousy study.”
-- Louis Sokoloff

6. Localization Localization for localization’s sake has some value
e.g., presurgical planning
However, it is not especially interesting to the cognitive neuroscientist in and of itself
Popularity of brain imaging results suggests people are inherent dualists

7. The Brain Before fMRI (1957)
Polyak, in Savoy, 2001, Acta Psychologica

8. The Brain After fMRI (Incomplete)
reaching and pointing
motor
control
touch
eye
movements
retinotopic visual maps
grasping
executive control
motion
near head
memory
orientation selectivity
motion perception
moving bodies
social cognition
static
bodies
faces
objects
scenes

9. Useful Types of Imaging Studies
Testing of theories and models
Comparing stimuli or tasks within a region
Comparing stimuli or tasks across a network
Examining coding within areas
fMRI adapation
Multi-voxel pattern analysis
Correlations between brain and behavior
Evaluation of the role group differences, experience and even genetics
Comparisons between species
Exploration of specialized human functions
e.g., language, tool use, mathematics
Derivation of general organizational principles

10. So you want to do an fMRI study?
Average cost of performing an fMRI experiment in 2012:
NT$4000/hour!!!
Average cost of performing a thought experiment:
Your Salary
CONCLUSION: Unless you are Bill Gates, a thought experiment is much more efficient!

11. Thought Experiments What do you hope to find?
What would that tell you about the cognitive process involved? 
Would it add anything to what is already known from other techniques? 
Could the same question be asked more easily & cheaply with other techniques?
What would be the alternative outcomes (and/or null hypothesis)? 
Or is there not really any plausible alternative (in which case the experiment may not be worth doing)? 
If the alternative outcome occurred, would the study still be interesting? 
If the alternative outcome is not interesting, is the hoped-for outcome likely enough to justify the attempt? 
What would the “headline” be if it worked? Is it sexy enough to warrant the time, funding and effort?
“Ideas are cheap.”
Good experimenters generate many ideas and ensure that only the fittest survive
What are the possible confounds?
Can you control for those confounds?
Has the experiment already been done?  “An hour on PubMed may save you a year of research!”

12. Three Stages of an Experiment
Sledgehammer Approach
brute force experiment
powerful stimulus
don’t try to control for everything
run a couple of subjects -- see if it looks promising
if it doesn’t look great, tweak the stimulus or task
try to be a subject yourself so you can notice any problems with stimuli or subject strategies
Real Experiment
at some point, you have to stop changing things and collect enough subjects run with the same conditions to publish it
incorporate appropriate control conditions
there is some debate on how many subjects you need
some psychophysical studies test two or three subjects
many studies test 6-10 subjects
random effects analysis requires at least 10 subjects
can run all subjects in one or two days
pro: minimize setup and variability
con: “bad magnet day” means a lot of wasted time
Whipped Cream
after the real experiment works, then think about a “whipped cream” version
going straight to whipped cream is a huge endeavor, especially if you’re new to imaging

13. Understanding Subtraction Logic
Part II
Understanding Subtraction Logic

14. Mental Chronometry use reaction times to infer cognitive processes
fundamental tool for behavioral experiments in cognitive science
F. C. Donders
Dutch physiologist

15. Classic Example T1: Simple Reaction Time Detect Stimulus Press Button
Hit button when you see a light
Detect
Stimulus
Press
Button
T2: Discrimination Reaction Time
Hit button when light is green but not red
Detect
Stimulus
Discriminate Color
Press
Button
T3: Choice Reaction Time
Hit left button when light is green and right button when light is red
Detect
Stimulus
Discriminate Color
Choose
Button
Press
Button
Time

16. Subtraction Logic (A + B) - A = B
Detect
Stimulus
Press
Button T1 -
Detect
Stimulus
Press
Button
Discriminate Color T2 =
Discriminate Color

17. Subtraction Logic (A + B) - A = B
Detect
Stimulus
Discriminate Color
Choose
Button
Press
Button T3 -
Detect
Stimulus
Press
Button
Discriminate Color T2 =
Choose
Button

18. Limitations of Subtraction Logic
Assumption of pure insertion
You can insert a component process into a task without disrupting the other components
Widely criticized

19. Top Ten Things Sex and Brain Imaging Have in Common
10. It's not how big the region is, it's what you do with it.
 9. Both involve heavy PETting.
 8. It's important to select regions of interest.
 7. Experts agree that timing is critical.
 6. Both require correction for motion.
 5. Experimentation is everything.
 4. You often can't get access when you need it.
 3. You always hope for multiple activations.
 2. Both make a lot of noise.
 1. Both are better when the assumption of pure insertion is met.
Now you should get this joke!
Source: students in the Dartmouth McPew Summer Institute

20. Subtraction Logic: Brain Imaging Example
Hypothesis (circa early 1990s): Some areas of the brain are specialized for perceiving objects
Simplest design: Compare pictures of objects vs. a control stimulus that is not an object
seeing
pictures
like
seeing
pictures
like
minus
= object perception
Malach et al., 1995, PNAS

21. Objects > Textures Lateral Occipital Complex (LOC)
Malach et al., 1995, PNAS

22. fMRI Subtraction - =

23. Other Differences Is subtraction logic valid here?
What else could differ between objects and textures?
Objects > Textures
object shapes
irregular shapes
familiarity
namability
visual features (e.g., brightness, contrast, etc.)
actability
attention-grabbing

24. Other Subtractions > > > Lateral Occipital Complex
Grill-Spector et al., 1998, Neuron
Visual Cortex (V1)
>
>
Kourtzi & Kanwisher, 2000, J Neurosci
>
Malach et al., 1995, PNAS

25. Dealing with Attentional Confounds
fMRI data seem highly susceptible to the amount of attention drawn to the stimulus or devoted to the task.
How can you ensure that activation is not simply due to an attentional confound?
Add an attentional requirement to all stimuli or tasks.
Example: Add a “one back” task
subject must hit a button whenever a stimulus repeats
the repetition detection is much harder for the scrambled shapes
any activation for the intact shapes cannot be due only to attention
Time
Other common confounds that reviewers love to hate:
eye movements
motor movements

26. Change only one thing between conditions!
As in Donders’ method, in functional imaging studies, two paired conditions should differ by the inclusion/exclusion of a single mental process
How do we control the mental operations that subjects carry out in the scanner?
Manipulate the stimulus
works best for automatic mental processes
Manipulate the task
works best for controlled mental processes
DON’T DO BOTH AT ONCE!!!
Source: Nancy Kanwisher

27. Beware the “Brain Localizer”
Can have multiple comparisons/baselines
Most common baseline = rest
In some fields the baseline may be straightforward
For example, in vision studies, the baseline is often fixation on a point on an otherwise blank screen
Be careful that you don’t try to subtract too much
Reaching – rest
= visual stimulus
+ localization of stimulus
+ arm movement
+ somatosensory feedback
+ response planning
+ …

28. What are people doing during rest?
What are people really doing during rest?
Daydreaming, thinking
Remembering, imagining
Attending to bodily sensations
“I really have to pee!”, “My back hurts”, “Get me outta here!”
Getting drowsy

29. Problems with a Rest Baseline?
For some tasks (e.g., memory studies), rest is a poor, uncontrolled baseline
memory structures (e.g., medial temporal lobes) may be DEactivated in a task compared to rest
To get a non-memory baseline, some memory researchers put a low-memory task in the baseline condition
e.g., hearing numbers and categorizing them as even or odd
Parahippocampal
Cortex
Stark et al., 2001, PNAS

30. Is concurrent behavioral data necessary?
“Ideally, a concurrent, observable and measureable behavioral response, such as a yes or no bar-press response, measuring accuracy or reaction time, should verify task performance.”
-- Mark Cohen & Susan Bookheimer, TINS, 1994
“I wonder whether PET research so far has taken the methods of experimental psychology too seriously. In standard psychology we need to have the subject do some task with an externalizable yes-or-no answer so that we have some reaction times and error rates to analyze – those are our only data. But with neuroimaging you’re looking at the brain directly so you literally don’t need the button press… I wonder whether we can be more clever in figuring out how to get subjects to think certain kinds of thoughts silently, without forcing them to do some arbitrary classification task as well. I suspect that when you have people do some artificial task and look at their brains, the strongest activity you’ll see is in the parts of the brain that are responsible for doing artificial tasks.
-- Steve Pinker, interview in the Journal of Cognitive Neuroscience, 1994
Source: Nancy Kanwisher

31. Part III
Design Decisions

32. Parameters for Neuroimaging
You decide:
number of slices
slice orientation
slice thickness
in-plane resolution (field of view and matrix size)
volume acquisition time
length of a run
number of runs
duration and sequence of epochs within each run
counterbalancing within or between subjects
Your physicist can help you decide:
pulse sequence (e.g., gradient echo vs. spin echo)
k-space sampling (e.g., echo-planar vs. spiral imaging; single- vs. multi-shot)
TR, TE, flip angle, etc.

33. Tradeoffs Number of slices vs. volume acquisition time
“fMRI is like trying to assemble a ship in a bottle – every which way you try to move, you encounter a constraint” -- Mel Goodale
Number of slices vs. volume acquisition time
the more slices you take, the longer you need to acquire them
e.g., 30 slices in 2 sec vs. 45 slices in 3 sec
Number of slices vs. in-plane resolution
the higher your in-plane resolution, the fewer slices you can acquire in a constant volume acquisition time
e.g., in 2 sec, 7 slices at 1.5 x 1.5 mm resolution (128 x 128 matrix) vs. 28 slices at 3 mm x 3 mm resolution (64 x 64 matrix)

34. More Power to Ya! Statistical Power
the probability of rejecting the null hypothesis when it is actually false
“if there’s an effect, how likely are you to find it”?
Effect size
bigger effects, more power
e.g., LO localizer (intact vs. scrambled objects) -- 1 run is usually enough
looking for activation during imagery of objects might require many more runs
Sample size
larger n, more power
more subjects
longer runs
more runs per subject
Signal:Noise Ratio
better SNR, more power
higher magnetic field
multi-channel coils
fewer artifacts (physical noise, physiological noise)

35. Put your conditions in the same run!
As far as possible, put the two conditions you want to compare within the same run.
Why?
subjects get drowsy and bored
magnet may have different amounts of noise from one run to another (e.g., spike)
some stats (e.g., z-normalization) may affect stats differently between runs
Common flawed logic:
Run1: A – baseline
Run2: B – baseline
“A – 0 was significant, B – 0 was not,  Area X is activated by A more than B”
By this logic, there is higher activation for Places than Faces in the data to the left.
Do you agree?
BOLD Activation (%)
Bottom line: If you want to compare A vs. B, compare A vs. B! Simple, eh?
Faces
Places
Error bars = 95% confidence limits

36. Run Duration How long should a run be?
Short enough that the subject can remain comfortable without moving or swallowing
Long enough that you’re not wasting a lot of time restarting the scanner
My ideal is ~6 ± 2 minutes

37. Simple Example Experiment: LO Localizer
Lateral Occipital Complex
responds when subject views objects
Blank
Screen
TIME
Intact
Objects
Scrambled
Objects
(Unit: Volumes)
One volume (12 slices) every 2 seconds for 272 seconds (4 minutes, 32 seconds)
Condition changes every 16 seconds (8 volumes)

38. Options for Block Design Sequences
That design was only one of many possibilities. Let’s consider some of the other options and the pros and cons of each.
Let’s assume we want to have an LO localizer
We need at least two conditions:
but we could consider including a third condition
Let’s assume that in all cases we need 2 sec/volume to cover the range of slices we require
Let’s also assume a total run duration of 136 volumes (x 2 sec = 272 sec = 4 min, 16 sec
We’ll start with 2 condition designs…

39. Physiological Noise Respiration every 4-10 sec (0.3 Hz)
moving chest distorts susceptibility
Cardiac Cycle
every ~1 sec (0.9 Hz)
pulsing motion, blood changes
Solutions
gating
avoiding paradigms at those frequencies
You want your paradigm frequency to be in a “sweet spot” away from the noise

40. Block Design: Medium Epochs
raw time course
HRF-convolved time course
Every 16 sec (8 images)
allows enough time for signal to oscillate fully
not near artifact frequencies
enough repetitions to see cycles by eye
a reasonable time for subjects to keep doing the same thing

41. Block Design: Other Niceties
truncated too soon
If you start and end with a baseline condition, you’re less likely to lose information with linear trend removal and you can use the last epoch in an event related average

42. Block Design Sequences: Three Conditions
Suppose you might want to add a third condition to act as a more neutral baseline
For example, if you wanted to identify visual areas as well as object-selective areas, you could include fixation as the baseline.
That would allow two subtractions
scrambled - fixation  visual areas
intact - scrambled  object-selective areas
Now the options increase.
For simplicity, let’s keep the epoch duration at 16 sec.

43. Block Design: Repeating Sequence
We could just order the epochs in a repeating sequence…
Problem: There might be order effects
Solution: Counterbalance with another order

44. Block Design: Random Sequence
We could make multiple runs with the order of conditions randomized…

45. Block Design: Regular Baseline
We could have a fixation baseline between all stimulus conditions (either with regular or random order)
As we will see when we talk about event-related averaging, this regular baseline design is optimal for getting nice average time courses

46. So What Do We Do?!!!
Any of these designs should work. Some might work better than others depending on your goals.
If you only care about the difference between Intact and Scrambled, you’d be best to go with a 16-sec alternating epochs with only those two conditions
If you are going for three conditions…
putting baselines between all other epochs is great for event-related averaging BUT it means you’re wasting a lot of your statistical power estimating the baseline
regular sequences should include counterbalancing
random sequences can be a lot of work to make protocols

47. But I have 4 conditions to compare!
Here are a couple of options.
A. Orderly progression
Pro: Simple
Con: May be some confounds (e.g., linear trend if you predict green&blue > pink&yellow)
B. Random order in each run
Pro: order effects should average out
Con: pain to make various protocols, no possibility to average all data into one time course, many frequencies involved

48. C. Kanwisher lab clustered design
sets of four main condition epochs separated by baseline epochs
each main condition appears at each location in sequence of four
two counterbalanced orders (1st half of first order same as 2nd half of second order and vice versa) – can even rearrange data from 2nd order to allow averaging with 1st order
Pro: spends most of your n on key conditions, provides more repetitions
Con: not great for event-related averaging because orders are not balanced (e.g., in top order, blue is preceded by the baseline 1X, by green 2X, by yellow 1X and by pink 0X.
As you can imagine, the more conditions you try to shove in a run, the thornier ordering issues are and the fewer n you have for each condition.
My rule of thumb: Never push it beyond 4 main + 1 baseline.

49. But I have 8 conditions to compare!
Just don’t.
In my experience, any block design experiment with more than four conditions becomes unmanageable and incomprehensible
Event-related designs might still be an option… stay tuned…

50. Design Types Block Design Slow ER Design Rapid Counterbalanced
= trial of one type
(e.g., face image)
= null trial
(nothing happens)
Design Types
= trial of another type
(e.g., place image)
Block
Design
Slow ER
Design
Rapid
Counterbalanced
ER Design
Rapid
Jittered ER
Design
Jody
Mixed
Design