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Experimental Design

An Introduction to MRI Physics and Analysis

Michael Jay Schillaci, PhDMonday, March 17th, 2008

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Overview

Design terminology Blocked Designs Event-Related Designs Mixed Designs Summary

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Design Terminology

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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

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What is fMRI Experimental Design?

Controlling the timing and quality of cognitive operations (IVs) to influence brain activation (DVs)

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)

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What types of hypotheses are possible for fMRI data?

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Optimal Experimental Design

Maximizing both Detection and Estimation Maximal variance in signal (incr. detect.) Maximal variance in stimulus timing (incr. est.)

Limitations on Optimal Design Refractory effects Signal saturation Subject’s predictability

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Finding effects Statistics are based on the ratio of explained predictable

versus unexplained variability:

We can improve statistical efficiency by Increasing the task related variance (signal)

Designing Experiments (today’s lecture) Decreasing unrelated variance (noise)

Spatial and temporal processing lectures. Good signal in our fMRI data

Physics lectures

Signal+NoiseNoise

F=SignalNoise

t=

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fMRI Signal

There are two crucial apects of the BOLD effect:The HRF is very sluggish

The is a long delay between brain activity and changes in fMRI images (~5s).

The HRF is additive Doing a task twice causes about twice as much change as

doing it once.

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The BOLD timecourse Visual cortex shows

peak response ~5s after visual stimuli.

Indirect measure

0 6 12 18 24

% Signal Change

2

1

0

Time (seconds)

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Temporal Properties of fMRI Signal

Hemodynamic response function (HRF) is sluggish: peak signal above 5s after activation. We predict the HRF by convolving the neural signal by the HRF. We want to maximize the amount of predictable variability.

Convolved Response

=

Neural Signal HRF

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BOLD effects are additive

Three stimuli presented rapidly result in almost 3 times the signal of a single stimuli (e.g. Dale & Buckner, 1997).

Crucial finding for experimental design. Note there are limits to this additivity effect, but the basic point is

that more stimuli generate more signal (see Birn et al. 2001)

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Blocked Designs

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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 Task BREST REST Task A Task BREST REST

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Comparing predictable HRF Consider 3 paradigms:

1. Fixed ISI: one stimuli every 16 seconds.

– inefficient

2. Fixed ISI: one stimuli every 4 seconds.

– Insanely inefficient: virtually no task-related variability

3. Block design: cluster five stimuli in 8 seconds, pause 12 seconds, repeat.

– Very efficient.– Cluster of events is additive.

Note peak amplitude is x3 the 16s design.

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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 move your signal to higher frequencies Away from low-frequency noise: scanner drift, etc.

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

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Optimal Design Block designs are optimal.

Present trials as rapidly as possible for ~12 sec Summation maximizes additive effect of HRF. Consider experiment:

Three conditions, each condition repeated 14 times (once every 900ms)1. Press left index finger when you see 2. Press right index finger when you see 3. Do nothing when you see

Note huge predictable variability in signal.

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Block designs

While efficient, block designs are often predictable.

May not be experimentally valid. Optimal block length around 12s, followed by

around 12s until condition is repeated.Avoid long blocks:

Reduced signal variability Low frequency signal will be hard to distinguish from low

frequency signals such as drift in MRI signal.

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Block Designs

aka ‘Box Car’, or ‘Epoch’ designs. Different cognitive processes occur in distinct

time periods1. Press left index finger when you see 2. Press right index finger when you see 3. Do nothing when you see

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Block designs good for detection, poor for estimating HDR.

Block design limitations

Detection: which areas are active?

Estimation: what is the timecourse of activity?

-10 0 10 20 30 40

R_Tap L_Tap right left

-0.005

0.000

0.005

0.010

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Block design limitations While block designs offer statistical

power, they are very predictable. E.G. our participants will know they will

press the same finger 14 times in a row.

Many tasks not suitable for block design E.G. Novelty detection, memory, etc. Your can not post-hoc sort data from

block designs, e.g. Konishi, et al., 2000 examine correct rejection vs hits on episodic memory task.

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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

25 Adapted from Gusnard & Raichle (2001)

26 Adapted from Gusnard & Raichle (2001)

Oxygen Extraction Fraction

Cerebral Metabolic Rate of O2

Cerebral Blood Flow

Any true baseline?

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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 Gathering/evaluation about the world around you Awareness (of self) Online monitoring of sensory information Daydreaming

This collection of processes is often called the “Default Mode”

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Default Mode!

Damoiseaux 2006 analyzed separate 10-subject resting-state data sets, using Independent

Components analysis.

Vision.

Memory.

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Power in Blocked Designs

1. Summation of responses results in large variance

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HDR Estimation: Blocked Designs

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Deeper concept…

We want the changes evoked by the task to be at different parts of the frequency spectrum than non-task-evoked changes.

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Limitations of Blocked Designs

Very sensitive to signal drift

Poor choice of conditions/baseline may preclude meaningful conclusions

Many tasks cannot be conducted repeatedly

Difficult to estimate the Hemodynamic Response

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Event-Related Designs

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What are Event-Related Designs? Event-related designs associate brain processes with

discrete events, which may occur at any point in the scanning session.

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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 averagingGeneral linear models

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Event related designs Much less power than block designs.

Simply randomizing trial order of our block design, the typical event related design has one quarter the efficiency. Here, we ran 50 iterations and selected the most efficient event related design.

Still half as efficient as the block design. Note this design is not very random: runs of same condition make it efficient.

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2a. Periodic Single Trial Designs

Stimulus events presented infrequently with long interstimulus intervals

500 ms 500 ms 500 ms 500 ms

18 s 18 s 18 s

38 McCarthy et al., (1997)

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Trial Spacing Effects: Periodic Designs

20sec

8sec 4sec

12sec

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From Bandettini and Cox, 2000

ISI: Interstimulus Interval

SD: Stimulus Duration

Why not short, periodic designs?

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2b. Jittered Single Trial Designs

Varying the timing of trials within a run Varying the timing of events within a trial

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Effects of Jittering on Stimulus Variance

43 Dale and Buckner (1997)

How rapidly can we present stimuli?

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Effects of ISI on Power

Birn et al, 2002

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Mixed Designs

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3a. 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.

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Permuted Blocks

Permuted block designs (Liu, 2004) offer possible some unpredictability…

Permuted Design:

1. Start with a block design

2. Randomly swap stimuli

3. Repeat step to for n iterations

More iterations = less predictable, less power

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Summary

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Blocked (solid)

Event-Related (dashed)

Event-related model reaches peak sooner…

… and returns to baseline more slowly.

In this study, some language-related

regions were better modeled by event-

related.

From Mechelli, et al., 2003

You can model a block with events…

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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