Event-related fMRI Contrast When Using Constant Interstimulus

Interval: Theory and Experiment

Peter A. Bandettini & Robert W. Cox

Steve Smith Psychology 670 Oct. 22, 2002

OR…

The Peter Bandettini Event-Related fMRI Cookbook™: Constant ISI Version

• Background Information

• Theory (translated from the original Greek)

• Method of testing the theory

• Analysis

• Applying the Cookbook to our own Research (2 examples)

PART I: Background Information

Optimal Designs

• “Optimal designs are those that yield the largest estimated magnitudes with the best statistical properties while satisfying the behavioral constraints of the experiment” (Ollinger et al., 2001b)– low variance– equal variance across effects– minimum correlation among effects

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Stimulation protocols in fMRI

baseline rest

stimulationhaemodynamic

response function

time courseof activation

Slide ruthlessly stolen from previous lecture

ER vs. Blocked Designs

• Better randomization of task types in a time series

• Allows for selective analysis of response data– particular stimuli– errors (and the accompanying “Oh Shit!” response)

• Easier separation of motion artifacts (you can, in theory, look at particular trials)

Methodological Variables

• Stimulus Duration (SD)

• Interstimulus Interval (ISI)

SD SD SD

ISI ISI

•Altering either SD or ISI alters the response function.

Methodological Variables

• Stimulus Duration (SD)

• Interstimulus Interval (ISI)

SD SD SD

ISI ISI

•Altering either SD or ISI alters the response function.

Different ISI Patterns• Constant

– (relatively) easy to analyze b/c they involve simple binning and averaging.

– Does not require the assumption of linearity

• Randomized (Mike’s presentation)– more time efficient– allow for shorter ISIs

ISI ISI

ISI ISI

Two Critical Questions

• How does the statistical power of ER-fMRI compare to that of blocked designs?

• What is the optimal ISI for a given SD?

Two Critical Questions

• How does the statistical power of ER-fMRI compare to that of blocked designs?

• What is the optimal ISI for a given SD?

• Trade-off: Number of trials per unit time vs. the degree of attenuation of the hemodynamic signal that occurs with close temporal spacing of trials.

Three Components of a Signal:

1) pre-undershoot (approx. 2 sec)

2) signal (approx. 6-9 sec to plateau)

3) post-undershoot (approx. 3 sec)

Signal attenuation or “clipping”:

•If one trial begins before the hemodynamic response function has settled back to baseline, the two functions (trial 1 and 2) will interfere with each other.

A B

Thus...

• The purpose of this paper is to determine the optimal ISI for a given SD in a constant-ISI ER-fMRI design.

PART II: The Theory (or What I Understood of It)

Bandettini’s Goal

• Create a theoretical response function for constant-ISI ER-fMRI based on fancy-schmancy math.

• Compare theoretical response function to experimental data.

The Theory (as I understand it)

• We want to estimate the activation in each voxel.

• The catch: we don’t know the response or the baseline level of activation.

• Use matrix algebra magic to get estimators of response and baseline activation.

The Theory (as I understand it)• If the stimuli are far enough apart (i.e., the

signals of each activation do not overlap), then we can accurately predict a response function.

• If there is overlap, we get more intimidating Greek symbols.

• Thus, we want to find a value that gives us a usable function rather than menacing symbols.

PART III: Method of Testing the Theory

Participants

• 5 people (probably Bandettini’s family)– data from 2 were lost due to motion artifacts.

Two Tasks

•Passive viewing of an 8-Hz red square (presented through goggles)

•Bilateral finger tapping

•Tasks performed simultaneously (hmmm….)

Different ISIs

ISI (sec) SD (sec) # of Cycles

20 20 924 2 1320 2 1616 2 2012 2 2510 2 308 2 366 2 454 2 602 2 90

Separate time series were run for 9 different ER-fMRI ISIs.

One blocked time series was run for comparison.

Image Acquisition

3 x 3 x 7 = 63 mm3

non-isotropic

From last lecture…”In general, larger voxels buy you more SNR, EXCEPT when the activated region does not fill the voxel (partial voluming)”

•Two axial imaging planes (visual and motor cortex)

•Echoplanar imaging

•TR = 1 sec

•TE = 40 msec

•Time series length = 360 images

Hmmm...

• What is gained by having the visual and motor stimulation simultaneous?

• Will this pattern generalize to other areas?

• Simple tasks (necessary, as this is a pilot study). Can we use this cookbook for more complex recipes?

PART IV: Analysis

Image Construction• Based ROI on data from blocked study.

• Created average plots for each time series

• Created a reference function (just a function in which the average function repeats over and over again.

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average

Image Construction Cont’d

• Created a correlation image (this is when you compare the obtained data to the average data)

• Divided this image by the residual time series’ standard deviation for each voxel in order to create a functional contrast-to-noise image

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Task validity: Visual and motor areas were found to be activated by the tasks.

At ISIs of 8 sec or less, the responses are blunted (over-lapping hemodynamic functions.

Ideal ISI: approx. 10-12 sec (similar pattern to blocked)

The “cleanest” response function is found for ISIs of 10 and 12 sec (followed by 8). The rest suck.

ISI-10 and ISI-12 lead to images that are similar to blocked images in resolution.

Blocked vs. Optimal ER

• The experimental contrast per unit time for ISI-12sec is only 35% lower than that of blocked designs.– For ISI-12sec, the stimulus is “on” for 14% of

the time, whereas for blocked, the stimulus is “on” for 50% of the time.

In a simulation, Bandettini’s model produced data very similar to that found in the experiment.

The theoretical model produced a similar pattern, but peaked earlier. (Needs to account for post-activation undershoot.)

PART V: Applying the Logic to Own Our Studies

Sledge Hammer or Whipped Cream?

• Pilot Study - blocked or constant-ISI ER

• Test - depends on the question

• Whipped Cream study - randomized-ISI ER

Before using constant ISIs, ask yourself: What phenomenon are we looking at? What subject population are we using? Will this give us the most bang-for-the-buck?

Constant-ISI event-related fMRI is a useful tool in specific situations.

• What would you use this sort of design to study? Could you apply it to your own research?

• What patient populations should and should not be tested this way?

• The constant-ISI generally shows that the hemodynamic response is slightly nonlinear. Since the randomized ISI design assumes linearity, should we be concerned?

Example 1: Expectation of Pain

Expectation of Pain

• What areas of the brain ‘light up’ during (1) pain and (2) the expectation of pain?

• Pain induced through a balloon that is inflated in one’s esophagus.– Nasal intubation

Three Types of Trials

• Pain trials vs. Pleasure trials vs. No sensation

• Pain = the balloon in the esophagus is inflated to a pre-determined threshold of pain

• Pleasure = a puff of air on the wrist

• No sensation = duh

Details

• SD: 4 sec of conditioned stimulus + 4 sec of pain/pleasure/nothing.

• ISI: 16 sec

• TR = 1 sec

• TE = 40 msec

• (Don’t remember slice #’s, flip angle, etc).

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Results

• Pain activated the anterior cingulate and somatosensory areas.

• The expectation of pain also activated these areas.

Subtle Transition to Mike’s Presentation

• It makes sense to study pain perception/expectation using a constant ISI. – You don’t need many trials– Methodologically difficult to present pain over

and over again without habituation, violence, etc.

Subtle Transition to Mike’s Presentation

• But, what if you’re interested in something like working memory? Or low-level visual perception? Or language processing?

• Is there a way to have shorter ISIs, thus allowing you to maximize your scanner time???