An Introduction to Functional MRI

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Transcript An Introduction to Functional MRI

Experimental Design

FMRI Graduate Course (NBIO 381, PSY 362) Dr. Scott Huettel, Course Director

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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)

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

What types of hypotheses are possible for fMRI data?

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

fMRI Design Types

1) Blocked Designs 2) Event-Related Designs a) Periodic Single Trial b) Jittered Single Trial 3) Mixed Designs - Combination blocked/event-related

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

FMRI – Week 8 – Experimental Design

1. 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 REST Task B REST Task A REST Task B REST

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Adapted from Gusnard & Raichle (2001) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Cerebral Blood Flow Cerebral Metabolic Rate of O 2 Oxygen Extraction Fraction Adapted from Gusnard & Raichle (2001) FMRI – Week 8 – Experimental Design

Any true baseline?

Scott Huettel, Duke University

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”

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Vision.

Default Mode!

Memory.

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Power in Blocked Designs

1. Summation of responses results in large variance

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

HDR Estimation: Blocked Designs

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Deeper concept…

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

2. Event-Related Designs

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

What are Event-Related Designs?

• Event-related designs associate brain processes with discrete events, which may occur at any point in the scanning session.

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

McCarthy et al., (1997) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Trial Spacing Effects: Periodic Designs

20sec 12sec 4sec 8sec

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Why not short, periodic designs?

ISI: Interstimulus Interval SD: Stimulus Duration From Bandettini and Cox, 2000

Scott Huettel, Duke University FMRI – Week 8 – Experimental Design

2b. Jittered Single Trial Designs

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Effects of Jittering on Stimulus Variance

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

How rapidly can we present stimuli?

Dale and Buckner (1997) FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Effects of ISI on Power

FMRI – Week 8 – Experimental Design

Birn et al, 2002

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Efficient Experimental Design

Maximal None

Mean Interval between Stimuli (sec)

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Post-Hoc Sorting of Trials

From Kim and Cabeza, 2007

FMRI – Week 8 – Experimental Design

Using information about fMRI activation at memory

encoding

to predict behavioral performance at memory

retrieval

.

Scott Huettel, Duke University

Limitations of Event-Related Designs

• None, really, at least with design itself.

• 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.)?

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

You can model a block with events…

Blocked (solid) Event-Related (dashed) FMRI – Week 8 – Experimental Design 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

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FMRI – Week 8 – Experimental Design

3. 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.

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

How do we identify efficient designs?

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Issues in Design Efficiency

• Not all random designs are equally efficient!

• Design efficiency is defined in relation to some contrast • Efficiency may interact with predictability & expectation

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University

Iterative (Genetic) Algorithms

Select the most efficient designs A B C A B C A B C

Designs

A B C

Designs

Retest modifications of efficient designs FMRI – Week 8 – Experimental Design Eliminate inefficient designs A B C Scott Huettel, Duke University

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

FMRI – Week 8 – Experimental Design Scott Huettel, Duke University