Neuroscience & Economics
Neuroeconomics
• Why?
• How?
• Two examples
Sanfey et. al. on neural basis of rejections in UG
de Quervain et. al. on neural basis of punishment
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Neuroeconomics & Behavioral Economics
• Behavioral economics developed alternative models of economic
behavior.
o Fairness and reciprocity models
o Prospect theory, hyperbolic discounting, learning models.
• These models are black box models. They aim to predict behavior
better but there is no ambition to understand the mind’s internal
processes that generate the behavior.
• Questions
o Are components of behavioral models represented in brain structures?
o Can insights into how the brain works improve economic modeling
o Can those insights discriminate between alternative models?
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Why is Neuroeconomics so fascinating?
• Brain research has made great progress during the past
decade, largely due to noninvasive techniques that allow
observing the brain while it is active.
• Systematic study of the relation between behavior and
brain processes in healthy human subjects is possible.
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Neuroscience may suggest fundamental changes in our
primitive concepts
(e.g. cognition-emotion interactions)
Controlled Processes
serial
effortful
evoked deliberately
good introspective access
Automatic Processes
parallel
reflexive
effortless
no introspective access
Cognitive
Affective
Refinancing your house
Economics deals mainly
with this quadrant
Actor who can truthfully
induce his own emotions
Tennis serve
Jumping when someone
says “boo”!
Table from Camerer, Loewenstein & Prelec, in press, J. Economic Literature
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Why brain details matter I
•
Two twins reveal a distaste for peanuts (example due to P. Romer)
•
Monica has nauseous “taste-aversion” from years ago…
…but knows peanuts are safe
o Automatic affect overrides controlled cognition
•
Claudia loves the smell of roasted nuts…
…but knows she is allergic
o Controlled cognition can override affect
•
Revealed preferences are the same…
… but there are predictable differences:
o Monica’s demand is more price-elastic
o Intertemporal patterns (if Monica eats them once, she will eat more)
o “Cure” for Monica is cognitive therapy & exposure, for Claudia is allergy
treatment
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Why brain details matter II: Automaticity
•
Priming effects (“prime” affects judgment/choice)
o Push-polling
• S Carolina primary ’00: `Would it make a difference to your vote if you knew John McCain had a
child with a black prostitute?’
o “Are you planning to buy a car this year?” raises car sales
o Environmental “cues” trigger drug craving (Laibson QJE 01)
•
•
•
Unconscious racial bias (measured by the implicit association test) correlates
significantly with brain activity in DLPFC suggesting increased attempts to suppress
racial bias cognitively.
Economic behavior is the result of interactions among mechanisms in cells I-IV
Cell I does not necessarily take over for big economic decisions
o
o
o
o
war (“This is the guy that tried to kill my daddy”- Bush Jr.)
bankruptcy (fear)
marriage (lust?)
status quo bias (“automatic”) in asset allocation
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Methods
• “Animal Models” – Many brain areas in humans and animals have
similar structures.
o It‘s possible to “produce” addicted rats.
o Addiction is created in that part of the brain which we share with
other mammals. Tierversuche
o Single cell recording (i.e. measuring the electrical potentials of
single neurons) is possible in non-human primates but not in
healthy humans.
• Psychophysiological measurements (skin conductance, heart rate)
• Brain Imaging (EEG, PET, fMRI)
o Observing the brain “when it works”
• Studying humans with lesions
o Associated deficits provide information about the function of the lesioned brain
area.
• Transcranial Magnetic Stimulation TMS
o Enables a controlled, spatially and temporally limited, stimulation or inhibition of
cortical brain areas.
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Electro-encephalogram (EEG)
• Measures electrical potentials at the
scull
• Very good temporal resolution but bad
spatial resolution.
• Large number of repetitions of the
same situation are necessary.
128 electrode array
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Positron Emission Tomography (PET)
• A radioactive substance is injected into the
blood.
• This substance emits positrons.
• These positrons decay, together with
electrons, into two photons.
• PET detects the brain area where this
decay occurs, i.e., it detects the areas into
which the radiation went.
• Variants:
Glucose with radioactive fluorine.
Water with radioactive oxygen.
“Pet measures blood flow”
•
Advantage: Little repetition of situations of interest is necessary
•
Disadvantage: subjects exposed to radioactivity; bad spatial and temporal resolution.
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fMRI (Functional Magnetic Resonance
Imaging)
•
•
•
•
MRI is based on the principle that protons in a magnetic field align with the
field. If the magnetic field is perturbed the direction of the protons is disturbed.
When the protons are redirected in the magnetic field electromagnetic
radiation is emitted and is detected by the scanner.
Depending on the environment of the protons (high fat or water content) the
signals generated by the redirection of the protons is different.
fMRI uses the fact that hemoglobin (red blood cells) have different magnetic
properties depending on whether there is little or much oxygen in the blood.
Increased neuronal activity in the brain uses up oxygen such that initially the
oxygen level in the activated area fall; later on the fall in oxygen is
overcompensated for when oxygen-rich blood moves to the activated area.
 BOLD-Signal (blood oxygen level dependent signal)
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Temporal resolution of fMRI
• Blood flow has a lagged
response to neural activity.
(Hemodynamic response
function HRF)
• Does still allow relatively
good temporal resolution
because HRF is known.
• Shortest stimuli that have been detected
with fMRI:
• Blamire et al. (1992): 2 sec
• Bandettini (1993): 0.5 sec
• Savoy et al (1995): 34 msec
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Übersicht
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Brain regions that could play an important role in
economic experiments
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The Neural Basis of Responder Behavior in the UG
(A. G. Sanfey, J. K. Rilling, J. A. Aronson, L. E. Nystrom, J. D. Cohen, Sci 13 March ’03)
• Responder’s brain activations are measured by fMRI in a $10 UG.
• A responder faces each of three conditions ten times.
o Offers from a (supposed) human partner
o Random offers from a computer partner
o Money offer (there is no proposer here)
• Research Questions: Which brain areas are more activated when
subjects face…
o fair offers (3-5) relative to unfair offers (1-2).
o the offer of a human proposer relative to a random computer offer.
• Method (very simplified):
o Regression of activity in every voxel (i.e, 3D Pixel) in the brain on the
treatment dummy (i.e., unfair offer dummy, human proposer dummy)
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Details of the Experiment
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Differences in brain activity between unfair and fair offers from a
human proposer (t-Statistic)
dorsolateral
prefrontal cortex.
Bilateral anterior insula and anterior cingulate cortex.
Dorsolateral prefrontal cortex.
Results
• Regions have stronger activations if subjects face unfair human offers
relative to fair human offers (the same regions also show more activation
if the unfair human offer is compared to unfair random offers).
o Bilateral anterior Insula, anterior cingulate Cortex
• Emotion-related region
• Insula also has been associated with negative emotions such as disgust and anger.
• Dorsolateral prefrontal Cortex (DLPFC)
• Cognition-related region
• Associated with control of execution of actions
• Associated with achievement of goals.
• Unfair offers are more likely to be rejected if
insula activation is stronger.
Neurobiology of Trust, Social Preferences and GainLoss Asymmetry – Some Results
o Kosfeld et al. (submitted, 2004): Subjects who receive a dose of the
hormone oxytocin exhibit more trusting but not more trustworthy
behavior. Trust has a neurobiological basis.
o Breiter et al. (Neuron 2001): The same realized outcome (e.g. $0)
activates reward circuits (e.g. NAc) positively if the counterfactual
outcomes are worse (e.g. $-6) and negatively if the counterfactual
outcomes are better (e.g. $10). Brain seems to process outcomes as
gains and losses relative to reference points (counterfactual
outcomes).
o Rilling et al. (Neuron 2002): Mutual cooperation with a human partner
activates reward related neural circuits relative to mutual cooperation with
a computer that provides the same monetary return. Mutual cooperation
with humans is extra rewarding.
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The Sweet Taste of Revenge
The Neural Basis of Altruistic Punishment
Dominique J.-F. de Quervain*, Urs Fischbacher*, Valerie Treyer,
Melanie Schellhammer, Ulrich Schnyder Alfred Buck & Ernst Fehr
University of Zurich
Science 305 (2004), 1254-1258
*the first two authors contributed equally
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The neural basis of punishment hypothesis
• Evolutionary models (Boyd et al. 2003) and experimental evidence
(Fehr&Gächter 2002) suggest that altruistic punishment is a key
element in human cooperation.
• Evidence from a host of experiments that many people incur costs to
punish others for unfair behavior and for norm violations.
• Theories of social preferences (Rabin 1993, Fehr& Schmidt 1999)
capture this by assuming a taste for punishment of unfair behavior.
o Subjects are better off (in terms of revealed preference) by
incurring cost to punish others although the costs are not offset by
economic rewards.
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Hypotheses
• Hypothesis 1: The possibility for punishing unfair behavior
activates reward-related neural circuits. (Nucleus
Accumbens, Nucleus Caudate).
• Hypothesis 2: If punishment is costly for the punisher there
is activation in neural circuits (PFC, OFC) that are related
to the integration of separate cognitive operations (weighing
of benefits and costs).
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Striatum and Reward
• Strong evidence from single cell recording in non-human primates that
ventral striatum (nucleus accumbens) and dorsal striatum (caudate
nucleus) are important in processing rewards.
o Schultz et al. etc.
• Strong evidence from neuroimaging studies with humans – using
money as a reward medium – that ventral and dorsal striatum is a key
component of reward circuits.
o Delgado et al. 2004, Knutson et. al. 2000 &2001
• Dorsal striatum seems particularly involved in rewards that accrue as a
result of purposeful behavior.
o Schultz et al., O’Doherty et al 2004.
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The Experimental Design
• Two subjects, A and B, have the opportunity for a social exchange that
benefits both parties.
• However, to complete the exchange, A has to move first while B moves
second, i.e., A has to trust B, and B can cheat A.
• We inform A about B’s action and give A the opportunity to punish B.
• A’s brain is scanned when he is informed about B’s action (i.e., whether
B cheated him or not) and when A deliberates whether, and how much,
he wants to punish B.
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The three stage experiment (baseline
treatment)
• Stage 1:
o Both A and B receive an endowment of 10 MUs (1 MU = CHF 0.1).
o A decides whether to keep or to transfer his endowment to B. In case of a
transfer B receives 4 times A’s endowment (40 MUs), in addition to his
own endowment of 10 MUs.
• Stage 2:
o B has the option to keep all the points he possesses or to give half of his
MUs to A
• If A trusts and B is trustworthy both earn 25.
• If A trusts and B cheats, A has nothing and B has 50.
• Both have 10 if A does not trust and B keeps everything.
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The three stage experiment (baseline
treatment)
• Stage 3:
o Both players receive an additional endowment of 20 Mus
o A has the opportunity to use this money to punish B or to keep the
money.
o Every MU invested into the punishment of B decreases B’s payoff
by 2 MUs.
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The three stage experiment (baseline
treatment)
• Parameters were chosen such that A has a strong incentive to
transfer his endowment (quadrupling of transfer) while B has a
strong incentive to defect (1:2 punishment technology). Pretesting ensured that A’s almost always transfer while the B‘s
cheat in 50 – 60% of the cases.
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The three stage experiment (treatment
conditions)
• Player A sequentially faced 7 different players B.
o In 3 cases B cooperated (transferred half of his MUs).
o In 3 cases B cheated (kept all his MUs).
o In 1 case a random device forced B to “cheat”. A knew that in this case
B’s “decision” was determined by rolling a die.
• We asked pre-test subjects in the role of B whether we can use
their decisions a second time. These decisions were then used in
the PET-experiment as an input.
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The three stage experiment
o Between each of the 7 trials there was a break of 10 minutes.
o We scanned all cases in which player B cheated or was forced
to cheat.
o Scanning time was 1 min. A’s were instructed to make a decision
during this time. At the end of the scanning time subjects were
asked whether they punish B and, if so, how much.
o After each punishment condition A answered a questionnaire.
Among other things A was asked whether he experienced a desire
to reward or to punish player B (answers given on a 7-point likert
scale from -3 to +3).
o Each subject received a flat fee of CHF 150 for participation in the
experiment plus the earnings from the interaction with player B.
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The three stage experiment (treatment
conditions)
• From the viewpoint of stage 3 we have 4 treatments of interest in all of
which player B cheated:
o Treatment where B decides himself and punishment is costly for both A and B
(Intentional & Costly, IC). A is hypothesized to experience a desire to punish
cheating and he can in fact punish.
o Treatment where B decides himself and punishment is free for A but costly for B
(Intentional & Free, IF). A is hypothesized to experience a desire to punish
cheating and he can in fact punish – even without a cost.
o Treatment where B decides himself and punishment is only symbolic, i.e., A and B
have no costs of punishing (Intentional & Symbolic; IS). A is also hypothesized to
experience a desire to punish cheating but he cannot punish.
o Treatment where B’s decision is randomly imposed on B; punishment is costly for
both A and B (Non-intentional & Costly, NC). A is to have no or a much less of a
desire to punish B for “non-cooperation” because B is not responsible for his
“action”.
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Hypotheses regarding activation of neural
circuits
•
The following contrasts are hypothesized to show activation of reward related
(N Accumbens, N caudate) neural circuits:
o
o
o
o
o
•
(IC – IS) because no punishment possible in S.
(IF – IS) because no punishment possible in S.
(IC – NC) because no desire to punish in R.
(IF – NC) because no desire to punish in R.
(IC + IF) – (IS + NC) because in IS & NC there is either no possibility or no desire
to punish so that there cannot be any satisfaction from punishing.
The following contrast is hypothesized to show activation of cognition related
(PFC, OFC) neural circuits.
o (IC – IF) because in IC subjects must weigh the costs and benefits of punishing
while in IF there are no costs.
o Related to the Sanfey et al. (2003) hypothesis.
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Rationale behind the treatment conditions
•
A skeptic might argue that whatever is differentially activated in the (IC – IS)
contrast is due to cost of punishing for the punisher.
•
However, if we see the same activation in the (IF – IS) contrast, the activation
cannot be due to this cost.
•
The possibility of many contrasts provides a robustness check. If the same
reward-related circuits are activated in each of the mentioned contrasts we
have a strong result.
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intentional & costly IC
intentional & free IF
intentional & symbolic IS
non-intentional & costly NC
Perceived unfairness
3
Behavioral and Questionnaire Results
2
1
0
-1
-2
Actual payoff reduction imposed on B
-3
40
Desire to punish
35
3
30
2
1
25
20
15
0
10
-1
-2
5
0
-3
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(IC + IF) - (IS + NC)
activates the nucleus caudate
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Differential activation of Nucleus Caudate relative to mean
brain activation (IC + IF) - (IS + NC)
R
2
6
5
4
3
2
1
0
Size of effect at [6, 22, 4]
7
Z value
L
intentional & costly IC
intentional & free IF
intentional & symbolic IS
non-intentional & costly NC
1.5
1
0.5
0
-0.5
-1
-1.5
-2
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Differential activation across contrasts
Table 1. PET results
Contrast
Region (BA)
Coordinates
Z value
x
y
z
Caudate nucleus
6
22
4
5.11*
Thalamus
22
-24
10
4.43*
Thalamus
22
-22
10
4.21
Caudate nucleus
6
22
4
3.55
Thalamus
22
-22
10
4.15
Caudate nucleus
6
24
2
3.70
IF-NC
Caudate nucleus
6
22
4
4.18
IC-NC
Caudate nucleus
6
22
4
4.23
IC-IF
Ventromedial prefrontal /
2
54
-4
4.59
medial orbitofrontal cortex
-4
52
-16
3.35
(IC+IF)-(IS+NC)
IF-IS
IC-IS
The coordinates (x, y, z) locate the maxima of changes in blood flow. * indicate significant activations
at a level < 0.05 corrected, otherwise p<0.001 uncorrected. BA, Brodmann area. I, intentional notransfer; N, non-intentional no-transfer; C, costly punishment; F, free punishment; S, symbolic
punishment.
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If caudate activity reflects satisfaction from
punishment subjects with stronger caudate activation
should punish more
0.08
Question: Does caudate activation cause
punishment or does punishment cause
caudate activation?
Response at [10, 26, -2] in IC
0.06
0.04
0.02
0
-0.02
p < 0.001
-0.04
-0.06
0
2
4
6
8
10
12
14
16
18
20
Amount invested for punishing in IC
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Are subjects with higher caudate activation in the IF
condition willing to pay more for punishing in the IC
condition?
If caudate activation reflects
satisfaction from punishment,
subjects with stronger caudate
activation in IF should be
willing to pay more for
punishment.
0.06
Response at [10, 26, 0] in IF
0.04
0.02
0
-0.02
-0.04
-0.06
0
2
4
6
8
10
12
14
16
18
20
Amount invested for punishing in IC
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Decision-Making & PFC/OFC Activations
• In IC and IS subjects face a decision problem
o IC: Shall I pay money to punish the defector?
o IS: Does it make sense to tell the defector that he is an bad person or that I
dislike what he did?
• In IF and NC subjects face less of a decision problem
o IF: There is a desire to punish and subject can satisfy this desire without
cost. Thus there is no trade off.
o NC: There is no desire to punish, thus no trade off.
• Hypotheses: In IC and IS we predict above average activation of PFC
(BA 10) and OFC (BA 11) whereas in IF and NC we predict below
average activation of these regions.
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Does (IC – IF) activate the PFC/OFC?
L
R
7
6
4
3
Z value
5
2
1
0
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Ventromedial Prefrontal
(BA 10)
IC-IF &
IC-NC are significant;
IS-IF is weakly
significant
Medial OFC (BA 11)
IC-IF
IC-NC
IS-IF
All significant
IC
IF
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IS
NC
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Summary
• Experimental evidence and social preference theories suggest
that many people prefer to punish unfair acts.
• Our study provides support for the view that satisfaction is
associated with the punishment of unfair acts.
• Correlation between caudate activity and punishment in IC, and
between caudate activity in IF and punishment in IC supports
this interpretation.
• More difficult decisions lead to a stronger activation in the
ventromedial PFC (BA 10) and the medial OFC (BA 11).
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Summary
• The activation of BA 10 and BA 11 in (IC-IF) supports our
interpretation of the caudate activation because if punishment of
defectors is not associated with satisfaction there are no
offsetting benefits that need to be weighed against the cost of
punishing.
• Thus, revenge seems to be associated with “a sweet taste”.
• Remark: This suggests that punishment of defectors is better
modeled as a preference phenomenon rather than as a
phenomenon of bounded rationality!!!
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Other Questions and Results
• Is ambiguity aversion better interpreted as a preference phenomenon or
does it reflect bounded rationality?
• Which brain mechanisms are associated with honesty and positive
reciprocity?
• Which brain mechanisms process trust, empathy, fear of punishment.
• Is reputation a belief or a taste? Singer et al. (2004) show that just
seeing the faces of people who previously cooperated as a 2nd mover
in a trust game activates reward related brain regions.
• What is the neural representation of beliefs about facts, beliefs about
other people’s intentions, beliefs about other people’s actions?
• Ultimate aim: Theories that have a sound basis in the insights of
neurobiology and neuroscience.
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