Transcript Document

Experimental Design
John VanMeter, Ph.D.
Center for Functional and Molecular Imaging
Georgetown University Medical Center
Development of an fMRI
Experiment
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
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 nonquantitative
Possible Control Conditions for a
Face Processing Study
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
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
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
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
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
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
Main Design Models
• Common Baseline
• Parallel Comparisons
• Tailored Baselines
• Hierarchical
• Parametric
• Selective Attention
• Adaptation
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)
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
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
Hierarchical Subtraction
• Three or more task conditions that
progressively include additional factors
– Ex A > Rest
– Ex B > Ex A
– Ex C > Ex B
Sensory
Motor
Semantic
• 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
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
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
Differential Response
Premotor
Primary Motor (M1)
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
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
Trial 1
Trial 2
Trial 3
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
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
Adaptation
Selectivity
for B Stimuli
Invariance
between A & B
Stimuli
Adaptation in Visual
Cortex
Rebound Index = (% signal change per condition) /
(% signal change for identical stimuli)
Altmann et al., 2003
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
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)
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
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
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
Superposition and Block
Design Indifference to HRF
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
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
Comparison of Block and
ER Designs - Detection
ER Designs - Estimation
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
Overlap - Rapid ER
• Difference in degree of activity due to
reduced number of events as run length
was kept constant
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
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
Semirandom Design
• Slight reduction in detection power
• But major increase in estimation
efficiency
Mixed Designs
• Uses a blockdesign
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
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
Mixed Design Example Alzheimer Study
Remembered Trials > Forgotten Trials
in the Encoding run
VanMeter, et al. in preparation
Activations and
Deactivations
• Deactivation decrease in
hemodynamic
response in
task condition
relative to
control
condition
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
Questions to Ask When
Designing an Experiment
Good Practices of fMRI
Experimental Design
• Evoke the cognitive or other process of
interest
• Collect as much (fMRI) data as possible
• Collect data on as many subjects as possible
• Choose stimulus and timing to create maximal
change in cognitive process of interest
• Time stimuli presentation of different
conditions to minimize overlap in signal
– Use software to optimize design efficiency for ER
designs
• Get measure of subject behavior in the
scanner (ideally related to task)
Put Thought into
Experimental Design
• Avoid simple comparison of two
conditions with minimal thought of what
cognitive processes are being compared
– Discussion section of these types of papers
come up with a post-hoc “just so story” as
to the meaning of results
• Ideally want to test some model
• Have hypotheses that can be confirmed
or repudiated
Example of Misuse of fMRI:
“This is Your Brain on Politics”
NY Times Op-Ed
• Iacoboni, et al. wrote an Op-Ed piece (Nov.
2007) on an experiment designed “to watch
the brains of a group of swing voters as they
responded to the leading presidential
candidates”
• Never published results in any journal
• Experimental design consisted of showing 20
subjects (1/2 male & 1/2 female) still photos
and videos of speeches from candidates
running for presidency at the time
• Compared brain activity with response to
questionnaires outside scanner
Clinton’s Results
• Voters who had
unfavorable opinions
about Sen. Clinton had
strong activation of ACC
• Therefore “an emotional
center of the brain that is
aroused when a person
feels compelled to act in
two different ways but
must choose one. It
looked as if they were
battling unacknowledged
impulses to like Mrs.
Clinton.”
Male vs Female Response
to Clinton and Giuliani
•
•
•
“Men show little interest in Mrs.
Clinton initially but after watching
her video they react positively.
Women respond to her strongly
at first, but their interest wanes
after they watch her video.”
“With Mr. Giuliani, the reactions
are reversed. Men respond
strongly to his initial still photos,
but this fades after they see his
video. Women grow more
engaged after watching his
video.”
“For men, Mrs. Clinton is a
pleasant surprise. For women,
Mr. Giuliani has unexpected
appeal.”
Obama and McCain
• “Barack Obama and John McCain have work to do.
The scans taken while subjects viewed the first set of
photos and the videos of Mr. McCain and Mr. Obama
indicated a notable lack of any powerful reactions,
positive or negative.”