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Experimental Design for Functional MRI. David Glahn Updated by JLL. General Experimental Design - Neuropsychology -. What is the question? What are appropriate controls? Which imaging modality? Study style?. Experimental Design: Terminology. Variables Independent vs. Dependent

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experimental design for functional mri

Experimental Designfor Functional MRI

David Glahn

Updated by JLL

general experimental design neuropsychology
General Experimental Design- Neuropsychology -
  • What is the question?
  • What are appropriate controls?
  • Which imaging modality?
  • Study style?
experimental design terminology
Experimental Design: Terminology
  • Variables
    • Independent vs. Dependent
    • Categorical vs. Continuous
  • Contrasts
    • Experimental vs. Control
    • Parametric vs. subtractive
  • Comparisons of subjects
    • Between- vs. Within-subjects
  • Confounding factors
  • Randomization, counterbalancing

From Scott Huettel, Duke

donder s method subtraction
Donder’s Method: Subtraction

Example: How long does it take to choose between alternatives? (Mental Chronometry)

  • A random series of A’s and B’s presented and the subject must:
    • Task 1 - Respond whenever event A or B occurs (RT1)
    • Task 2 - Respond only to A not to B (RT2)
    • Task 3 - Respond X to A and Y to B (RT3)

RT = reaction time

  • RT1 = T-detect + T-response
  • RT2 = T-detect + T-discrimination + T-response
  • RT3 = T-detect + T-discrimination + T-choice + T-response
  • T-discrimination = RT2 - RT1
  • T-choice = RT3 - RT2
criticisms of donder
Criticisms of Donder
  • Assumes that adding components does not affect other components (i.e. assumption of pure insertion)
  • One should pick tasks that differ along same dimension (time in our example)
  • Although resting baseline is good to include, it may limit inference

(e.g. Sternberg, 1964)

experimental design for fmri
Experimental Design for fMRI

Must Account for Hemodynamic Response

(HR)

Savoy et al., 1995

linear systems analysis boynton et al 1996
Linear Systems Analysis Boynton et al. 1996
  • The linear transform model of fMRI hypothesizes that responses are proportional to local average neural activity averaged over a period of time.
    • fMRI responses in human primary visual cortex (V1) depend on both stimulus timing (8 Hz) and stimulus contrast (black/white).
    • Responses to long-duration stimuli can be predicted from a hemodynamic response function (HRF) derived from shorter duration stimuli.
    • The noise in the fMRI data is independent of stimulus contrast and stimulus temporal period.
  • Because the linear transform model is consistent with our data, we proceeded to estimate the temporal fMRI response function and the underlying (presumably neural) contrast response function using HRF…
  • Assumption is that HRF is linear and shift-invariant!
linearity of bold response

Sync each differential response to start of trial

Linearity of BOLD response

Dale & Buckner, 1997

Reversing Checkerboard (8 Hz)

One-trial = 1 stimulus

Two-trial – 2 stimuli

Three-trial = 3 stimuli

Stim duration (SD) = 1 s

Inter-stim interval (ISI) = 2 s

Not quite linear but good enough for first order approximations

fmri design types
fMRI Design Types
  • Blocked Designs
  • Event-Related Designs
    • Periodic Single Trial
    • Jittered Single Trial
  • Mixed Designs

- Combination blocked/event-related

what are blocked designs
What are Blocked Designs?
  • Blocked designs segregate different cognitive tasks into distinct time periods (blocks)

Paradigm – pattern or model; detailed plan for the experiment

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

fMRI brain images acquired continuously

loose vs tight block designs
“Loose” vs. “Tight” Block Designs
  • Loose: 1 Task, 1 contrast (with Baseline)
  • Tight: more than 1 Task, multiple contrasts (including baseline)
types of blocked design
Types of Blocked Design
  • Task A vs. Task B (… vs. Task C…)
    • 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 (… vs. Task C…)
    • Example: Squeezing Right Hand vs. Rest
    • Shows you activity associated with task
    • May introduce unwanted results if not matched properly

(example would be if rest acquired with eyes closed but task had eyes open)

slide15

(E - Bad Control Design)

Adapted from Gusnard & Raichle (2001)

a true baseline
A True Baseline?

Different Areas may have different baselines

Cerebral Blood Flow

Cerebral Metabolic Rate of O2

Oxygen Extraction Fraction

Adapted from Gusnard & Raichle (2001)

Depends on what is measured!

power in blocked designs
Power in Blocked Designs
  • Summation of responses results in large signals then plateaus (~10 sec)
  • Response Duration does not plateau and onset does not change

Stimulus duration and interval compared with HRF

ISI = 1 sec

choosing length of blocks
Choosing Length of Blocks
  • Longer block lengths allow for stability of extended responses
    • Hemodynamic response saturates following extended stimulation
      • After about 10s, activation reaches plateau
    • Many tasks require extended intervals
      • Brain processing may differ throughout the task period
  • Shorter block lengths move your signal to higher temporal frequencies
    • Away from low-frequency noise: scanner drift, etc.
    • Not possible in O-15 PET rCBF studies
  • Periodic blocks may result in aliasing of other periodic signals in the data
    • Example: if the person breathes at a regular rate of 12 per min and the blocks are 10s long (6 blocks/min)
    • Could be problem if the aliased signal falls within the range of desired signals

From Scott Huettel, Duke

what are the temporal limits
What are the temporal limits?
  • What is the shortest stimulus duration that fMRI can detect?
    • Blamire et al. (1992) – 2 sec
    • Bandettini (1993): 0.5 sec
    • Savoy et al (1995): 34 msec
  • With enough averaging, anything seems possible.
  • Assume that the shape of the HRF is predictable.
  • Event-related potentials (ERPs) are based on averaging small responses over many trials.
  • Can we do the same thing with fMRI?
assumption of steady state dynamics
Assumption of steady-state dynamics.

For block designs we assume that the BOLD effect remains constant across the epoch of interest.

For PET this assumption is valid given the half-life of the radiotracer used for CBF studies, task designs, and the time period for the image acquisition.

But the BOLD response is much more transient and more importantly may vary according to brain regions and stimulus durations and maybe even stimulus types.

Savoy et al., 1995

limitations of blocked designs
Limitations of Blocked Designs
  • Sensitive to signal drift or MR instability
  • Poor choice of conditions/baseline may preclude meaningful conclusions
  • Many tasks cannot be conducted well repeatedly
non task brain processing
Non-Task Brain Processing
  • In experiments activation can be greater in baseline conditions than in task conditions!
    • Requires different processing for interpretation
  • Suggests the idea of baseline/resting mental processes
    • Gathering/evaluation about the world around you
    • Awareness (of self)
    • Online monitoring of sensory information
    • Daydreaming
    • Neurons that are wired together fire together
  • This collection of resting state brain processes is often called the “Default Mode Network” (DMN)
slide23

Default Mode!

Resting State Networks (RSNs)

Vision.

Frontal Parietal

Damoiseaux 2006 analyzed separate 10-subject resting-state data sets, using Independent Components analysis (ICA).

what are 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.
  • Can detect transient BOLD responses
  • Supports adapting task to response such as changing difficulty based on error rate
why use event related designs
Why use event-related designs?
  • Some experimental tasks are naturally event-related (future stimuli based on response)
  • Allows studying within-trial effects
  • Improves relation to behavioral factors (behavior changes within blocks may be masked)
  • Simple analyses
    • Selective averaging
    • General linear models (GLM)
same event averaging
Same Event Averaging
  • Sorting Into Common Groups
  • Behavior
  • Physiological Measure
  • Outlier Rejection
  • Transient vs. Task level Responses
periodic single trial designs

500 ms

500 ms

500 ms

500 ms

18 s

18 s

18 s

Periodic Single Trial Designs
  • Stimulus events presented infrequently with long inter-stimulus intervals (ISIs)
trial spacing effects periodic designs

ISI = 12sec (15 trials)

ISI = 8sec (~12 trials)

ISI = 4sec (~45 trials)

Trial Spacing Effects: Periodic Designs

ISI = 20sec (9 trials)

A20

A12

A4

A8

Want to maximize amplitude times number of trials per study

bandettini cox 2000
Bandettini & Cox, 2000
  • The optimal inter-stimulus interval (ISI) for a stimulus duration (SD), was determined.
    • Empirical Observation: For SD=2sec, ISI=12 to 14 sec.
    • Theory Predicts: For SD<=2 sec, the optimal repetition interval (RI=ISI+SD)
    • Theory Predicts: For SD>2sec, RI = 8+(2*SD).
  • The statistical power of ER-fMRI relative to blocked-design was determined
    • Empirical: For SD=2 sec, ER-fMRI was ~35% lower than that of blocked-design
    • Simulations that assumed a linear system demonstrated estimate ~65% reduction in power
    • Difference suggest that the ER-fMRI amplitude is greater than that predicted by a linear shift-invariant system models.
jittered single trial designs
Jittered Single Trial Designs
  • Varying the timing of trials within a run
  • Varying the timing of events within a trial

1 event

2 events

3 events

2 events

Trial 1

Trial 2

Trial 3

Trial 4

effects of jittering on response
Effects of Jittering on Response

Stimulus

Response

Jittering allows us to sample BOLD response in more states

effects of isi on detectability
Effects of ISI on Detectability

Jittered ISI

Detectability

Constant ISI

Max when ½ stims are task state and ½ stims are control state

Estimated

Accuracy of

HRF

Birn et al, 2002

detecting using selective averaging
Detecting Using Selective Averaging

Visual stim duration = 1 s; acquisition 240 sec

Trials subtracted then correlation analysis with predicted response

Large Response

Most samples

Mid Response

More Samples

Low Response

Fewer Samples

Dale and Buckner (1997)

variability of hrf evidence
Variability of HRF: Evidence
  • Aguirre, Zarahn & D’Esposito, 1998
  • HRF shows considerable variability between subjects

different subjects

  • Within subjects, responses are more consistent, although there is still some variability between sessions

same subject, same session

same subject, different session

variability of hrf implications
Variability of HRF: Implications
  • Aguirre, Zarahn & D’Esposito, 1998
  • Generic HRF models (gamma functions) account for 70% of variance
  • Subject-specific models account for 92% of the variance (22% more!)
  • Poor modeling reduces statistical power
  • Less of a problem for block designs than event-related (do you know why?)
  • Biggest problem with delay tasks where an inappropriate estimate of the initial and final components contaminates the delay component
  • Possible solution: model the HRF individually for each subject
  • Possible caveat: HRF may also vary between areas, not just subjects
    • Buckner et al., 1996:
      • noted a delay of 0.5-1 sec between visual and prefrontal regions
      • vasculature difference?
      • processing latency?
    • Bug or feature?
      • Menon & Kim – mental chronometry
post hoc sorting of trials
Post-Hoc Sorting of Trials

True Memory Formation

vs.

False Memory Formation

Using information about fMRI activation at memory encoding to predict behavioral performance at memory retrieval.

From Kim and Cabeza, 2007

limitations of event related designs
Limitations of Event-Related Designs
  • Low power (maybe)
    • Collecting lots of data, many runs
  • The key issues are:
    • Can my subjects perform the task as designed?
    • Are the processes of interest independent from each other (in time, amplitude, etc.)?
mixed combination blocked event
Mixed: Combination Blocked/Event
  • Both blocked and event-related design aspects are used (for different purposes)
    • Blocked design: state-dependent effects
    • Event-related design: item-related effects
  • Analyses can model these as separate phenomena, if cognitive processes are independent.
    • “Memory load effects” vs. “Item retrieval effects”
  • Or, interactions can be modeled.
    • Effects of memory load on item retrieval activation.
you can model a block with events
You can model a block with events…

Event-related model reaches peak sooner…

Blocked (solid)

Event-Related (dashed)

… and returns to baseline more slowly.

In this study, some language-related regions were better modeled by event-related.

From Mechelli, et al., 2003

summary of experiment design
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
what is fmri experimental design
What is fMRI Experimental Design?
  • Controlling the timing and quality of cognitive operations to influence brain activation
  • What can we control?
    • Stimulus properties (what is presented?)
    • Stimulus timing (when is it presented?)
    • Subject instructions (what do subjects do with it?)
  • What are the goals of experimental design?
    • To test specific hypotheses (i.e., hypothesis-driven)
    • To generate new hypotheses (i.e., data-driven)
experimental design for functional mri46

Experimental Designfor Functional MRI

David Glahn

Updated by JLL