1. Neuroimaging Methods
Scott Huettel
Brain Imaging and Analysis Center
All uncredited figures are from Huettel, Song, & McCarthy
Department of Psychiatry (2004). Functional Magnetic Resonance Imaging.
Duke University This presentation, save for credited figures from other
sources, is copyrighted by Scott Huettel (2006).
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3. 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
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5. 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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6. 1. Electroencephalography
(EEG)
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7. From Cognition to Neuron
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8. Electrophysiological Recording
Electrode Array
(e.g., n = 64)
Amplifier Bank
Brain
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9. EEG recordings
by Hans Berger
(c. 1925-1935)
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10. + VOLTAGE -
Event-Related Potentials (ERPs)
TIME
TIME (ms) (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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11. 2. Magnetoencephalography
(MEG)
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12. Magnetoencephalography (MEG)
Courtesy 4D Neuroimaging from Woldorff et al. (1999)
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13. 3. Transcranial Magnetic Stimulation
(TMS)
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14. Transcranial Magnetic Stimulation (TMS)
TMS allows transient* and safe* disruption of local neuronal activity, in effect
creating reversible lesions.
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15. 4. Positron Emission Tomography
(PET)
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16. PET Scanning: Principles
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17. Positron Emission Tomography
Cyclotron Radio-isotope (FDG)
http://www.med-ed.virginia.edu/courses/rad/PETCT/Emission.html
Image from Utah Center for Advanced Imaging Research
Image Scanner
http://www.idac.tohoku.ac.jp/dep/nmr/pet1.jpg
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18. 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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19. 5. Structural MRI
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20. MRI Scanning Hardware
“Imaging”
(Weak Gradient “Magnetic”
Magnetic Fields) (Strong Static Magnetic Field)
“Resonance”
(Radiofrequency Energy)
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21. Structural MRI
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22. 6. Functional MRI (fMRI)
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23. Fact #1: Energy is supplied to the
brain via the vascular system
Hemoglobin
Glucose
(Oxygen)
Glucose image from NYU Library of 3-D Molecular Structures
From Duvernoy et al., 1982
Hemoglobin image from Pittsburgh Supercomputing Center
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24. Fact #2: More hemoglobin is supplied than needed,
causing a decrease in deoxygenated hemoglobin.
From Mandeville et al., 1999
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25. Fact #3: Deoxygenated hemoglobin reduces
some forms (T2*) of MR signal.
Baseline
Blood-Oxygenation-Level
Dependent Contrast
(BOLD Contrast)
Task
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26. From Cognition to Neuron to fMRI
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27. 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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28. Neuroimaging of Decision Preferences
1. Uncertainty: Risk vs. Ambiguity
2. Probability: High vs. Low
3. 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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29. Dissociable Systems for Risk and Ambiguity
Risky - Certain
Parietal Cortex Ambiguity Preference Risk Preference
Risky - Risky
Ambiguity preference (1-α) Risk preference (β)
Ambiguity Preference Risk Preference
Prefrontal cortex
Ambiguity preference (1-α) Risk preference (β)
Huettel et al. (2006) Neuron
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30. Probability
Probability
of Error
Preuschoff, Boessarts, & Quartz (2006) Neuron
Huettel et al. (2005) J Neuroscience
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31. Safe vs. Risky Choice
Insula activation predicts safe choice.
Nucleus accumbens activation predicts
risky choice.
Kuhnen & Knutson (2005) Neuron
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32. 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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33. Acknowledgments
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
neuroeconomics.duke.edu
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