Huett El
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Association for Consumer Research Scott Huettel, Duke University
Neuroimaging Methods
Scott HuettelBrain Imaging and Analysis CenterDepartment of PsychiatryDuke University
All uncredited figures are from Huettel, Song, & McCarthy (2004). Functional Magnetic Resonance Imaging.
This presentation, save for credited figures from other sources, is copyrighted by Scott Huettel (2006).
Association for Consumer Research Scott Huettel, Duke University
Association for Consumer Research Scott Huettel, Duke University
Methods for Creating Images of (Human) Brain Function
1. Electroencephalography (EEG)2. Magnetoencephalography (MEG)3. Transcranial Magnetic Stimulation (TMS)4. Positron Emission Tomography (PET)5. Structural Magnetic Resonance Imaging (MRI)6. Functional Magnetic Resonance Imaging (fMRI)
7. Examples: Neuroimaging of Choice
Association for Consumer Research Scott Huettel, Duke University
Association for Consumer Research Scott Huettel, Duke University
The Cardinal Principles
Functional neuroimaging comprises methods for mapping information processing within the brain.
All functional neuroimaging is limited by two factors: the physical properties of the recording system and the
physiological constraints of the brain.
Images of brain activity only have meaning when acquired using the correct experimental design and interpreted using
the correct analyses.
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1. Electroencephalography (EEG)
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From Cognition to Neuron
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Electrophysiological Recording
Brain
Amplifier Bank
Electrode Array (e.g., n = 64)
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EEG recordings by Hans Berger (c. 1925-1935)
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Event-Related Potentials (ERPs)
TIME (ms)
+ V
OLT
AG
E -
TIME (in 20ms Intervals)
from Khoe et al. (2004)
Using selective averaging across trials, ERPs have exquisite temporal resolution (but coarse spatial resolution)
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2. Magnetoencephalography (MEG)
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Magnetoencephalography (MEG)
from Woldorff et al. (1999)Courtesy 4D Neuroimaging
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3. Transcranial Magnetic Stimulation (TMS)
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Transcranial Magnetic Stimulation (TMS)
TMS allows transient* and safe* disruption of local neuronal activity, in effect creating reversible lesions.
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4. Positron Emission Tomography (PET)
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PET Scanning: Principles
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http://www.idac.tohoku.ac.jp/dep/nmr/pet1.jpg
Positron Emission Tomography
Image from Utah Center for Advanced Imaging Research
Cyclotron Radio-isotope (FDG)
Image Scanner
http://www.med-ed.virginia.edu/courses/rad/PETCT/Emission.html
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PET: Strengths and Limitations
• Strengths– Uses a simple physiological mechanism– Provides absolute, quantitative data– Allows imaging of anything that can be tagged
• Limitations– Poor temporal resolution (many minutes)– Poor spatial resolution (several centimeters)– Requires injection of radioactive material
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5. Structural MRI
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MRI Scanning Hardware
“Imaging”(Weak Gradient
Magnetic Fields)“Magnetic”(Strong Static Magnetic Field)
“Resonance”(Radiofrequency Energy)
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Structural MRI
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6. Functional MRI (fMRI)
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Fact #1: Energy is supplied to the brain via the vascular system
Glucose image from NYU Library of 3-D Molecular Structures
Glucose
Hemoglobin
Hemoglobin image from Pittsburgh Supercomputing CenterFrom Duvernoy et al., 1982
(Oxygen)
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From Mandeville et al., 1999
Fact #2: More hemoglobin is supplied than needed, causing a decrease in deoxygenated hemoglobin.
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Fact #3: Deoxygenated hemoglobin reduces some forms (T2*) of MR signal.
Baseline
Task
Blood-Oxygenation-Level Dependent Contrast
(BOLD Contrast)
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From Cognition to Neuron to fMRI
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fMRI: Strengths and Limitations
• Strengths– Non-invasive, replicable– Potentially good spatial localization– Common, well-validated technique
• Limitations– Mediocre temporal resolution (seconds)– Complex, highly variable data analyses– Expensive and time-consuming
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Neuroimaging of Decision Preferences
1. Uncertainty: Risk vs. Ambiguity2. Probability: High vs. Low3. Choice: Safe vs. Risky
In all of these cases, there is some derived parameter that is related to the
neuroimaging activation.
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Parietal Cortex
Prefrontal cortex
Huettel et al. (2006) Neuron
Dissociable Systems for Risk and Ambiguity
Risky - Certain
Risky - Risky
Ambiguity Preference
Ambiguity preference (1-α) Risk preference (β)
Risk Preference
Ambiguity Preference Risk Preference
Ambiguity preference (1-α) Risk preference (β)
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Probability
Preuschoff, Boessarts, & Quartz (2006) Neuron
Huettel et al. (2005) J Neuroscience
Probability of Error
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Safe vs. Risky Choice
Insula activation predicts safe choice.
Nucleus accumbens activation predicts risky choice.
Kuhnen & Knutson (2005) Neuron
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Summary
• Neuroimaging techniques create maps of brain function.
• The most common approaches measure neuronal activity (EEG, ERP, MEG) or brain hemodynamics (PET, FMRI).
• The neuroimaging approaches relevant for consumer research involve relating neuroimaging data to economic parameters.
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Acknowledgments
neuroeconomics.duke.edu
Recommended Readings:• Huettel, Song, & McCarthy (2004). Functional Magnetic Resonance Imaging.• Buxton (2002). Introduction to fMRI.• Luck (2005). An Introduction to the ERP Technique.• Purves et al. (2004). Neuroscience, 3rd Edition.
FMRI education colleagues:• Allen Song (Duke University), Gregory McCarthy (Yale University)
Laboratory members:• Bethany Weber, Dharol Tankersley, John Clithero, Luke Vicens, Lily Kinross-
Wright, Parker Goyer, Jason Chen