an overview of neuroeconomics
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Trial 1 T. 3.5. 3. 2.5. 2. 1.5. 1. 0.5. 0. An Overview of Neuroeconomics. Dante Monique Pirouz Doctoral Student Psychology and Capital Markets Workshop December 13, 2006. Some Neuroecon Humor…. What is Neuroeconomics?. - PowerPoint PPT PresentationTRANSCRIPT
An Overview of Neuroeconomics
Dante Monique PirouzDoctoral Student
Psychology and Capital Markets WorkshopDecember 13, 2006
Trial 1 T
0
0.5
1
1.5
2
2.5
3
3.5
Some Neuroecon Humor…
What is Neuroeconomics?• Studies how the brain interacts with
the environment to produce economic behavior
• Integrates economics, psychology, neuroscience, and cognitive science – Financial decision making– Game theory strategy– Influence of emotion, biases, etc.– Social dynamics on economic behavior– Developmental similarities and differences – Addictive consumption– Influence of cues such as advertising, brands,
etc.
Development of Neuroeconomics
• Experimental Economics– Uses lab experiments to test
economic models
• Behavioral Economics– Combines economics and
psychology
• Behavioral Finance– Combines finance and psychology
Development of Neuroeconomics
• Cognitive Neuroscience– Seeks to understand the neural
mechanisms underlying higher brain function• Language, learning, memory, attention,
emotion, decision making, perception
Why Combine Economics with Neuroscience?
• Neoclassical economists ask “Given rational people, how do models behave?”– Rational choice theory, expected utility
theory
• Psychologists ask “Why do people behave the way they do?”– Prospect theory
• Looking into the “black box”– At the neuronal and biochemical level – To understand what makes people happy,
risk seeking or averse, trusting or trustworthy and what drives preference and choice
Neuroscience Methods– Animal studies– Human studies– Lesion studies– Single and multiunit recordings– Measuring hormone levels, pupil
dilation, galvanic skin response– Stimulation
• Transcranial magnetic stimulation (TMS)
– Imaging of brain activity
Occipital Lobe
Frontal Lobe
Parietal Lobe
Temporal Lobe
Main Brain Regions
Pons
Spinal Cord
Cerebellum
Amygdala
Thalamus
Hypothalamus
Hippocampal
FormationCorpusCallosu
m
Cingulate Gyrus
Striatum
Limbic System
Brain Imaging Techniques
Methodology What is imaged? How?
Electroencephalography (EEG)
Changes in electrical brain current
Electrodes placed on scalp measure electrical brain waves
Computed (Axial) Tomography Scan (CT or CAT)
X-ray images of the brain
Multiple images (tomograms) are taken by rotating X-ray tubes. Does not image function
Positron Emission Tomography (PET)
Emissions from radioactive chemicals in the blood
Radioactive isotopes injected into the blood are detected like X-rays
Magnetoencephalography (MEG)
Changes in electrical brain current
Similar to EEG but magnetic brain waves are measured instead of electrical waves
Functional Magnetic Resonance Imaging (fMRI)
Blood flow; oxyhemoglobin to deoxyhemoglobin ratio
Relies on magnetic properties of blood. Shows brain function spatially and temporally
EEG
CT/CAT
PET
MEG
Functional Magnetic Resonance Imaging (fMRI)
• Uses strong magnetic fields to create images of biological tissue– Measures hemodynamic
signals related to neural activity
• Blood Oxygenation Level Dependent (BOLD) contrast
• MR signal of blood is dependent on level of oxygenation
• Changes in deoxyhemoglobin
• Blood flow in the brain implies function– Studies have shown regional
brain activity when exposed to cues (Huettel et al. 2004)
Source: UC Irvine Center for Functional Onco-Imaging
Why is fMRI so exciting?
• Non-invasive• Better temporal
resolution• Good and
improving spatial resolution
• Can be used in conjunction with other methods (Savoy 2005)
Source: MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging Visiting Fellowship Program in fMRI, 2005
Caveats of fMRI
• Interpreting the results– Direct vs. indirect measure of brain activity– Inferring behavior
• Experimental design• Statistical methods
– Learning the procedure and statistical methods
• Cost• Comfort/safety/cooperation of the
subject
The Neural Basis of Financial Risk Taking
• Kuhnen & Knutson, Neuron, 2005– Is individual investor deviation from
optimal behavior due to emotion?• Brain imaging evidence that anticipation
of gain vs. loss activate different regions– Nucleus accumbens (NAcc) of ventral striatum
=gains– Anterior insula = loss
– Examined whether anticipatory neural activity could predict optimal and suboptimal choices in financial choices• Event related fMRI with 1.5T scanner• 19 subjects (experts and non-experts)
Stimuli• Behavioral Investment Allocation Task (BIAS)
– 20 blocks 10 trials each– Randomly assigned one stock to be bad and other good
Results• NAcc and MPFC activation related to
anticipation of risk-seeking choices• Insula activation related to anticipation of
risk-averse choices
Investment Behavior and the Negative Side of Emotion
• Shiv, Loewenstein, Bechara, Damasio, & Damasio, 2005, Psychological Science– Do emotions cause poor investment
decisions?• Compared subjects with stable focal brain
lesions disabling emotional regions with control patients with no impairment
• 19 normal subjects, 15 lesion patients with damage in emotional regions, 7 lesion controls with damage in non-emotion related regions
• Endowed with $20 play money (exchange for gift certificate)
Investment Game• Participants told they would
making several rounds of investment decisions– Choose between 2 options: invest
or don’t invest• If invest, give $1 to researcher; if not,
keep $1
– Researcher will flip coin • If heads, then lose $1• If tails, then get $2.50• Rational choice: Always invest!!
– EV of investing is higher than not investing
Results• Lesion patients with
emotional neural damage make more advantageous investment decisions than normal subjects– Target patients
invested consistently across rounds; controls/normal subjects increasingly declined to invest
The Neurobiology of Trust• Zak, Kurzban & Matzner, Annals of
New York Academy of Science, 2004– Do hormones, such as oxytocin,
regulate trust behavior?•Oxytocin
– Neuropeptide involved in social recognition and bonding
•Trust game– Subjects arranged into DM1-DM2 dyads– DM1 asked to split $10– Decision will determine how much they earn
•28 mL of blood drawn after each decision
•2 conditions: Intention and random draw
Trust Game
• At node A, the investor has the option of either path• Moving left ends the game with the outcomes: $0 to
player 1 and $10 to player 2• Moving right allows trustee to move (after
investment is increased)• Trustee can choose either path at node B• Once trustee moves the game ends and payoffs are
distributed (McCabe 2003a)
A: Investor
B: Trustee
$0$10
$15$15
$0$30
Results
• Oxytocin (OT) levels were higher (2x) with an intentional trust signal from DM1s in DM2s than in random draw condition
• Also, behavior changed with an intentional trust signal– DM2s returned 53% of the money they received vs.
18% in the random draw condition
Oxytocin Increases Trust in Humans
• Kosfeld, Heinrichs, Zak, Fishbacher & Fehr, 2005, Nature– 194 subjects
• Conducted in Switzerland
• Subjects received OT via nasal spray or placebo
• 4 rounds with randomly assigned partners
– Trust game• 2 conditions: Trust and
risk (random trustee decision)
Results• OT increased trusting behavior
in investor • OT did not increase trustworthy
behavior in trustee• Trustee behavior dominated by
principle of reciprocity: OT had no effect
• OT also modulates neural networks to enhance trusting behavior
Neuronal Substrates for Choice Under Ambiguity, Risk, Gains,
and Losses• Smith, Dickhaut, McCabe, Pardo,
Management Science, 2002– Positron Emission Tomography (PET)– 9 subjects– Initial endowment $190 cash– Presented with Ellsberg Paradigm
• Asked to indicate from which of 2 containers containing 90 red, blue and yellow marbles they wanted draw a marble ‘
• 4 task conditions– Risk gains– Risk losses– Ambiguity gains– Ambiguity losses
Task
Results
Results• Activation of ventromedial and
dorsomedial network only with gain – loss difference in the risky gambles– Not activated in ambiguous gambles
(Row A)– Tied to amygdala and hypothalamus– Dorsomedial system more involved with
loss
• Study shows that belief (ambiguity vs. risk) interacts with payoff structure (gain vs. loss) to affect brain activity during choice
Criticisms
• Theory?• Preference for existing models• Press coverage• Consumer concern• Commercial ventures
Resources & Labs• Center for the Study of Neuroeconomi
cs– George Mason: Kevin McCabe & Vernon
Smith
• Stanford Neuroeconomics Lab– Stanford: Antonio Rangel
• Human Neuroimaging Lab– Baylor: Read Montague
• Center for Neuroeconomics Studies– Claremont: Paul Zak
• The Camerer Lab– Caltech: Colin Camerer
• Society for Neuroeconomics• Neural Systems of Social Behavior Co
nference
Other Key Researchers• Antoine Bechara - USC• Baba Shiv – Stanford• George Loewenstein – Carnegie
Mellon• Antonio Damasio – USC• John Dickhaut – University of
Minnesota • Camelia Kuhnen – Northwestern• Paul Glimcher - NYU
Recommended Reading• “Neuroeconomics: How Neuroscience Can
Inform Economics.” – Colin F. Camerer, George Loewenstein, and
Drazen Prelec, 2005, Journal of Economic Literature 43(1): 9.
• “Behavioral Economics: Past, Present, Future” – Colin F. Camerer and George Loewenstein,
2002– In Advances in Behavioral Economics
• Functional Magnetic Resonance Imaging – Scott A. Huettel, Allen W. Song, and Gregory
McCarthy, 2004• The Secret Life of the Brain, PBS