Rapid-Presentation Event-Related Design for fMRI - PowerPoint PPT Presentation

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Rapid-Presentation Event-Related Design for fMRI

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Title: Rapid-Presentation Event-Related Design for fMRI


1
Rapid-Presentation Event-Related Design for fMRI
  • Douglas N. Greve

2
Outline
  • What is Event-Related Design?
  • Fixed-Interval Event-Related
  • Rapid-Presentation (Jittered) Event-Related
  • Efficiency and Event Scheduling
  • Mathematical Basis
  • optseq a tool for RPER design
  • (http//surfer.nmr.mgh.harvard.edu/optseq)

3
Dispersion
  • Dispersion is the spreading out of the response
    over time, usually far beyond the end of the
    stimulus
  • How closely can one event follow another?

4
Event-Related fMRI
  • Estimate response from a single event type
  • cf Blocked Design (Habituation, Expectation, Set,
    Power)
  • Randomize Schedule (Order and Timing)
  • Post-Hoc Event Sorting
  • Multimodal Integration (EEG/MEG,Behavioral)
  • Fixed Interval and Rapid Presentation
    (Jittered/Stochastic)

5
Event vs Event Type
  • Three Event Types (yellow, red, green)
  • Number of Events (Repetitions) per Event Type
  • Yellow 2
  • Red 2
  • Green 3
  • Two events belong to the same Event Type if, by
    hypothesis, they have the same response
    (violations are treated as noise).
  • Event Type Condition Trial Type
    Explanatory Variable
  • Event Stimulus Trial

6
Event Schedule
  • Description of which event is presented when

time code duration label 4.0
2 4 yellow 20.0 1
2 red 36.0 1
2 red 52.0 3
6 green
  • Time is the accumulated time since onset of
    scanning run
  • Code unique numeric id
  • Output of optseq

7
Fixed-Interval Event-Related
  • Push trials apart enough to prevent overlap.
  • Interval fixed at minimum is most efficient.
  • Random Sequence (Counter-balanced)
  • Allows Post-Hoc Stimulus Definition
  • Mitigates Habituation, Expectation (?), and Set
  • Inflexible/Inefficient/Boring
  • Good if limited by number of stimuli (not
    scanning time)

8
Rapid-Presentation Event-Related
  • Closely Spaced Trials (Overlap!)
  • Raw signal uninterpretable
  • Random Sequence and Schedule
  • Highly resistant to habituation, set, and
    expectation
  • Jitter Random Inter-Stimulus Interval
    (ISI/SOA)

9
Scheduling and Efficiency
C N10
  • Efficiency is statistical power/SNR/CNR per
    acquisition
  • Efficiency increases with N (number of
    observations)
  • Efficiency decreases with overlap
  • Efficiency increases with differential overlap
  • Choose schedule with optimum efficiency before
    scanning

10
Mathematical Concepts
Forward Model (X design matrix)
Inverse Model
Residual Error
11

Contrast, Contrast Vector (or Matrix), Contrast
Effect Size, COPE (FSL)
t-Ratio
Efficiency
Variance Reduction Factor
12
Where does jitter come from?(Whats a Null
Condition?)
  • Null condition fixation cross or dot
  • By hypothesis, no response to null
  • Insert random amounts of null between task
    conditions
  • Differential ISI Differential Overlap

A

B
A
A
A
A




B
B
B
Time
13
Design Parameters (optseq)
  • TR time between volume acquisition (temporal
    resolution).
  • Ntp number of time points (TRs, frames,
    volumes, )
  • Nc number of event types (conditions)
  • Npc number of events/repetitions of each event
    type (can vary across event types)
  • Tpc duration of each event type (can vary
    across event types)
  • Schedule event onset time and identity
  • Event Response Model FIR Post-Stimulus Delay
    Window (needed for optimization)

14
Time Constraints
Total Scan Time Ntp TR
A
B
C

Null Time
Ta NaTpa
Tc NcTpc
Tb NbTpb
Total Stimulation Time
  • Total Stimulation Time Cannot Exceed Total Scan
    Time
  • How much Null Time is needed? Rule of thumb
    same as any other task condition (or the average
    of the task conditions).

15
Event Response Model (FIR)
  • PSD Post-Stimulus Delay (PSD 0 Stimulus
    Onset)
  • PSDMin Response is zero for PSD lt PSDMin
  • PSDMax Response is zero for PSD gt PSDMax
  • PSD Window should be long enough to capture
    response
  • Response can be anything in between (FIR model)
  • dPSD sets basic temporal resolution for
    schedule
  • DOF Constraint Nbeta nPSDNc lt Ntp

16
Other optseq Parameters/Options
  • Getting help optseq2 --help
  • Search termination criteria nsearch/tsearch
  • Output files (and format)
  • Optimizing over number of repetitions
  • Nuisance variables (polynomial drift terms)
  • Cost Functions
  • First-Order Counter-Balancing Pre-optimization
  • http//surfer.nmr.mgh.harvard.edu/optseq
  • To come contrasts and non-FIR

17
Rapid-Presentation Properties
  • Efficient (not as efficient as blocked)
  • Can distinguish responses despite overlap
  • Highly resistant to habituation, set, and
    expectation
  • Flexible timing (Behavioral, EEG, MEG)
  • Linear overlap assumption
  • Analysis Selective Averaging/Deconvolution
    (GLM)
  • Schedule Optimization Tool (optseq)
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