an overview of neuroeconomics

An Overview of Neuroeconomics

Dante Monique PirouzDoctoral Student

Psychology and Capital Markets WorkshopDecember 13, 2006

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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