Issues in Experimental Design

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Transcript Issues in Experimental Design

Issues in
Experimental Design
fMRI Graduate Course
October 26, 2005
Terminology
• Independent vs. Dependent variables
• Categorical vs. Continuous variables
• Between- vs. Within-subjects
manipulations
• Experimental vs. Control conditions
• Confounding factors
• Randomization, counterbalancing
• Parametric vs. subtractive designs
What is fMRI Experimental Design?
• Controlling the timing and quality of cognitive
operations (IVs) to influence resulting brain
processes (DVs)
• What can we control?
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Experimental comparisons (what is to be measured?)
Stimulus properties (what is presented?)
Stimulus timing (when is it presented?)
Subject instructions (what do subjects do with it?)
Goals of Experimental Design
• To maximize the ability to test hypotheses
• To facilitate generation of new hypotheses
What types of hypotheses are possible for fMRI data?
Epiphenomena?
Detection vs. Estimation
• Detection: What is active?
• Estimation: How does activity change over
time?
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Detection
• Detection power defined by SNR
SNR = aM/
M = hemodynamic changes (unit)
a = measured amplitude
 = noise standard deviation
• Depends greatly on hemodynamic
response shape
Estimation
• Ability to determine the shape of fMRI response
• Accurate estimation relies on minimization of
variance in estimate of HDR at each time point
• Efficiency of estimation is generally independent
of HDR form
Optimal Experimental Design
• Maximizing both Detection and Estimation
– Maximal variance in stimulus timing
(increases estimation)
– Maximal variance in measured signal
(increases detection)
• Limitations
– Refractory effects
– Signal saturation
fMRI Design Types
1) Blocked Designs
2) Event-Related Designs
a) Periodic Single Trial
b) Jittered Single Trial
c) Staggered or Interleaved Single Trial
3) Mixed Designs
a) Combination blocked/event-related
b) Variable stimulus probability
1. Blocked Designs
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
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
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 allow for more transitions
– Task-related variability increases (relative to non-task) with increasing
numbers of transitions
• 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
What baseline should you choose?
• Task A vs. Task B
– 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
– Example: Squeezing Right Hand vs. Rest
– Shows you activity associated with task
– May introduce unwanted results
Adapted from Gusnard & Raichle (2001)
Adapted from Gusnard & Raichle (2001)
From Shulman et al., 1997 (PET data)
From Binder et al., 1999
From Huettel et al., 2004
(Baseline > Target Detection)
From Huettel et al., 2001 (Change Detection)
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
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Emotional processes
Gathering/evaluation about the world around you
Awareness (of self)
Online monitoring of sensory information
Daydreaming
Power in Blocked Designs
1. Summation of responses results in large
variance
Single, unit amplitude HDR,
convolved by 1, 2, 4 ,8, 12,
or 16 events (1s apart).
HDR Estimation: Blocked Designs
Power in Blocked Designs
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Simulation of single run with either 2 or 10 blocks.
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2. Transitions between blocks
Power in Blocked Designs
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Addition of linear drift within run.
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2. Transitions between blocks
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Addition of noise (SNR = 0.67)
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Power in Blocked Designs
2. Transitions between blocks
Deeper concept…
We want the changes evoked by the task to
be at different parts of the frequency
spectrum than non-task-evoked changes.
Limitations of Blocked Designs
• Very sensitive to signal drift
– Sensitive to head motion, especially when only a few
blocks are used.
• Poor choice of baseline may preclude
meaningful conclusions
• Many tasks cannot be conducted repeatedly
• Difficult to estimate the HDR
2. Event-Related Designs
What are Event-Related Designs?
• Event-related designs associate brain
processes with discrete events, which may
occur at any point in the scanning session.
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
Word-stem completion task. Blocked design: 30s on/off.
Event-related design: 15s ISI.
Buckner et al., (1996)
Buckner et al., (1996)
McCarthy et al., (1997)
McCarthy et al., (1997)
Dale and Buckner (1997)
2a. Periodic Single Trial Designs
• Stimulus events presented infrequently
with long interstimulus intervals
500 ms
500 ms
18 s
500 ms
18 s
500 ms
18 s
Trial Spacing Effects: Periodic Designs
20sec
12sec
8sec
4sec
ISI:
Interstimulus
Interval
SD:
Stimulus
Duration
From Bandettini
and Cox, 2000
2b. Jittered Single Trial Designs
• Varying the timing of trials within a run
• Varying the timing of events within a trial
Effects of Jittering on Stimulus Variance
From Hopfinger et al., 2000
Effects of ISI on Power
Birn et al, 2002
2c. Staggered Single Trial
• By presenting stimuli at different timings, relative
to a TR, you can achieve sub-TR resolution
• Significant cost in number of trials presented
– Resulting loss in experimental power
• Very sensitive to scanner drift and other sources
of variability
• Also called Interleaved Stimulus Presentation
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Two of the phases are
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But, one has a change in one trial
(e.g., head motion)
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Post-Hoc Sorting of Trials
Data from old/new episodic
memory test.
From Konishi, et al., 2000
Limitations of Event-Related Designs
• Differential effects of interstimulus interval
– Long intervals do not optimally increase
stimulus variance
– Short intervals may result in refractory effects
• Detection ability dependent on form of HDR
• Length of “event” may not be known
3. Mixed Designs
3a. Combination Blocked/Event
• Both blocked and event-related design aspects
are used (for different purposes)
– Blocked design is used to evaluate state-dependent
effects
– Event-related design is used to evaluate item-related
effects
• Analyses are conducted largely independently
between the two measures
– Cognitive processes are assumed to be independent
Mixed Blocked/Event-related Design
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Target-related Activity (Phasic)
Blocked-related Activity (Tonic)
Task-Initiation Activity (Tonic)
Task-Offset Activity (Tonic)
…
3b. Variable Stimulus Probability
• Stimulus probability is varied in a blocked
fashion
– Appears similar to the combination design
• Mixed design used to maximize experimental
power for single design
• Assumes that processes of interest do not vary
as a function of stimulus timing
– Cognitive processing
– Refractory effects
Random and Semi-Random Designs
From Liu et al., 2001
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