1. Basics of Experimental Design for fMRI: Block Designs
Jody Culham
Brain and Mind Institute
Department of Psychology
University of Western Ontario
Basics of Experimental Design for fMRI: Block Designs
Last Update: February 4, 2013
Last Course: Psychology 9223, W2013, Western University

2. 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. Toys Are Not Enough “Expensive equipment doesn’t merit a lousy study.”
-- Louis Sokoloff

6. Localization for Localization’s Sake
Danckert et al., 2004, Neuropsychologia
Clinical Research
presurgical planning
understanding functional reorganization
Basic Research
implicating well-established areas in cognitive tasks

7. Danger Zone: Reverse Inference
“[Mitt Romney’s] still photos prompted a significant amount of activity in the amygdala, indicating voter anxiety…”
Iacoboni et al., 2007, New York Times Op-Ed, This is Your Brain on Politics

8. Danger Zone: Reverse Inference
“The Romney amygdala activation might indicate anxiety, or any number of other feelings that are associated with the amygdala -- anger, happiness or even sexual excitement”
Martha Farah, Neuroethics and Law Blog

9. Why You Shouldn’t Use fMRI
It’s the most expensive approach
If you’re interested in behavior, study behavior
EEG/ERP/MEG have better temporal resolution
TMS and neuropsychology speak more directly to causality
fMRI activation may be epiphenomonal
neurophysiology/eCoG give more direct access to neural processing
Epiphenomena
Huettel et al. fMRI

10. Behaviorism (circa 1950s)
Black
Box
Stimulus
Response

11. Cognitive Science (circa 1980s)
Attention
Recognition
Stimulus
Perception
Response
Memory
Decision Making
Too many empty
boxes?

12. Early fMRI (1990s)
“Blobology”

13. The Future of fMRI? Networks Map of semantic space derived from fMRI
Gallant Lab

14. What Can fMRI Add?
explicit testing of models derived from other approaches
inform and constrain theories of cognition
whole brain coverage that can constrain or direct data from other approaches (neurophysiology, ERPs, ECoG)
investigation of neural mechanisms of elaborated human functions (language, math, tool use)
correlations between brain and behavior
help to understand clinical disorders or development
look at coding and connections between brain regions

15. What have we learned about the face area?
The face area is activated:
when faces are perceived or imagined
 correlation between brain and behavior
for stimuli at the fovea
 cues to brain organization
by circular patterns
 cues/constraints for modelling
in certain areas of the monkey brain
 cues to brain evolution
for other categories of objects that subjects have extensive experience with
 debate regarding nature/nurture
to some degree by other categories of objects
 debate regarding distributed vs. modular coding in the brain
The fusiform face area may be impaired:
in some but not all patients who have problems recognizing faces
in people with autism
 understanding of brain disorders

16. Finding the Right Experiment

17. So you want to do an fMRI study?
Typical cost of performing an fMRI experiment:
$500/hour!!!
Average cost of performing a thought experiment:
Your Salary
CONCLUSION: Unless you are Bill Gates, a thought experiment is much more efficient!

18. 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, more cheaply or better 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.” -- Jody’s former supervisor, Jane Raymond
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?  “A year of research can save you an hour on PubMed!”

19. 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
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
mixed metaphor: “never sacrifice the meat & potatoes to get the gravy” (“never sacrifice the hot chocolate to get the whipped cream” doesn’t have quite the same punch)

20. Testing Patients fMRI is the art of the barely possible
neuropsychology is the art of the barely possible
combining fMRI and neuropsychology can be very valuable
BUT it’s (art of the barely possible)2
If you want to test a paradigm in patients or special groups (either single cases or group studies), I recommend developing a robust paradigm in control subjects first
It’s generally a bad idea to use patients for pilot testing

21. Understanding Subtraction Logic

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

23. 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

24. Subtraction Logic Detect Stimulus Press Button Discriminate Color T2 -=
Discriminate Color

25. Subtraction Logic Detect Stimulus Discriminate Color Choose Button
Press
Button T3 -
Detect
Stimulus
Press
Button
Discriminate Color T2 =
Choose
Button

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

27. 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 McDonnell-Pew Summer Institute

28. 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

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

30. fMRI Subtraction - =

31. 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

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

33. 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

34. 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

35. 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
+ …
“Our task activated the
occipito-temporo-parieto-fronto-subcortical network”
Another name for this is “the brain”!

36. What are people doing during “rest”?
What are people really doing during rest?
Daydreaming, thinking
“Gawd this is boring. I wonder how long I’ve been in here. I went at 2:00. It must be about 3:30 now…”
Remembering, imagining
“I gotta remember to pick up a carton of milk on the way home”
Attending to bodily sensations
“I really have to pee!”, “My back hurts”, “Get me outta here!”
Getting drowsy
“Zzzzzz… I only closed my eyes for a second… really!”

37. 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

38. Default Mode Network
Fox and Raichle, 2007, Nat. Rev. Neurosci.
red/yellow = areas that tend to be activated during tasks
task > resting baseline
blue/green = areas that tend to be deactivated during tasks
task < resting baseline

39. Interpreting Activations vs. Deactivations
A “rest” baseline is needed to discriminate between these two possibilities
fMRI ACTIVATION
(% BSC)
Rest
baseline
Stimulus/Task
Onset
TIME
More activation for blue than yellow
More deactivation for yellow than blue
If negative betas don’t make sense for your theory and you included a rest baseline, you can eliminate them with a conjunction analysis
+ yellow
- blue
AND
+ yellow
AND
+ blue

40. 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

41. Choosing a Block Design

42. Parameters for Neuroimaging
You decide:
number of slices
slice orientation
slice thickness
in-plane resolution (field of view and matrix size)
volume acquisition time (usually = TR)
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)
TR, TE, flip angle, etc.

43. 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)

44. 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)

45. 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

46. 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

47. 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)

48. 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…

49. Convolution of Single Trials
Neuronal Activity
BOLD Signal
Haemodynamic Function
Time
Time
Slide from Matt Brown

50. Block Design: Short Equal Epochs
raw time course
HRF-convolved time course
Time (2 s volumes)
Alternation every 4 sec (2 volumes)
signal amplitude is weakened by HRF because signal doesn’t have enough time to return to baseline
not to far from range of breathing frequency (every 4-10 sec)  could lead to respiratory artifacts
if design is a task manipulation, subject is constantly changing tasks, gets confused

51. Block Design: Short Unequal Epochs
raw time course
HRF-convolved time course
Time (2 s volumes)
4 sec stimuli (2 volumes) with 8 sec (4 volumes) baseline
we’ve gained back most of the HRF-based amplitude loss but the other problems still remain
now we’re spending most of our time sampling the baseline

52. Block Design: Long Epochs
The other extreme…
raw time course
HRF-convolved time course
Time (2 s volumes)
Alternation Every 68 sec (34 volumes)
more noise at low frequencies
linear trend confound
subject will get bored
very few repetitions – hard to do eyeball test of significance

53. Find the “Sweet Spots” 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

54. Block Design: Medium Epochs
raw time course
HRF-convolved time course
Time (2 s volumes)
Every 16 sec (8 volumes)
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

55. Block Design: Other Niceties
truncated too soon
Time (2 s volumes)
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

56. Block Design Sequences: Three Conditions
Suppose you 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 resting fixation as the baseline.
That would allow two subtractions
scrambled - fixation  visual areas
intact - scrambled  object-selective areas
That would also help you discriminate differences in activations from differences in deactivations
Now the options increase.
For simplicity, let’s keep the epoch duration at 16 sec.

57. 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
Problem: If you lose a run (e.g., to head motion), you lose counterbalancing)

58. Block Design: Random Sequence
We could make multiple runs with the order of conditions randomized…
Problem: Randomization can be flukey
Problem: To avoid flukiness, you’d want to have different randomization for different runs and different subjects, but then you’re going to spend ages defining protocols for analysis

59. Block Design: Regular Baseline
We could have a fixation baseline between all stimulus conditions (either with regular or random order)
Benefit: With event-related averaging, this regular baseline design provides nice clear time courses, even for a block design
Problem: You’re spending half of your scan time collecting the condition you care the least about

60. 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

61. 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.

62. 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…

63. EXTRA SLIDES

64. Prepare Well: Subjects
recruit and screen your subjects well in advance
safety screening
best to let them read through and self-screen beforehand so you don’t get any embarrassing situations (e.g., discussions about IUDs, pregnancy)
eye glasses
handedness
make sure your subjects know how to be good subjects
make sure you and the subjects can contact each other in case of problems or delays
if possible, be a subject yourself to see what the pitfalls and strategies might be
remember to bring:
subject fees (and receipt book)
consent and screening forms

65. Prepare Well: Experiments
test all equipment in advance
test software under realistic circumstances (same computer, timing and duration as fMRI experiments)
make sure you know all of the parameters the technician will want (e.g., pulse sequence, timing, slices and orientation)
at RRI, prepare a spreadsheet with mouseclicks and stopwatch times
check the timing as you go, especially at the beginning of an experiment
keep accurate log notes as you go
check with the technician regularly to ensure that your log notes record the same run number as the scanner
attach your timing spreadsheet to the log notes for that subject
write down any problems that arose (e.g., “subject missed second last trial”; “subject drowsy through first ~third of run”)

66. Prepare Well: Postprocessing
move data to secure location as soon as possible
save one backup in the rawest form possible
if advances in reconstruction occur, you will need unprocessed data to use them
save other backups at natural points (e.g., backup and delete 2D data once you’ve made 3D data)
have redundancy
don’t put all backups on the same CD/DVD or you’re toast if one is damaged (CDs aren’t forever like we once thought)
save full projects to one DVD (or HD partition) once you’re done so you can reload an entire project if you need to reanalyze
keep a subject archive …

67. Dealing with Frustration
Murphy's law acts with particular vigour in fMR imaging: 
Number of pieces of equipment required in an fMRI experiment: ~50
Probability of any one piece of equipment working in a session: 95%
Probability of everything working in a session: 0.95^50 = 7.6%
Sign that used to be at the 1.5 T at MGH
Solution for a good imaging session =
$4 million magnet
+ $3 roll of duct tape

68. How NOT to do an imaging experiment
ask a stupid question
e.g., “I wonder what lights up for nose picking vs. rest”
compare poorly-defined conditions that differ in many respects
use a paradigm from another technique (e.g., cognitive psychology) without optimizing any of the timing for fMRI, e.g., 1 minute epochs
be naively optimistic
go straight for the “whipped cream” experiment without starting with a “sledgehammer” experiment
never look at raw data, time courses or individual data, just plunk it all into one big stat model and look at what comes out
publish a long list of activated foci in every possible comparison
don’t use any statistical corrections
write a long discussion on why your task activates the subcortico-occipito-parieto-temporo-frontal network