neuroeconomics: the neurobiology of decision-making

Neuroeconomics: The Neurobiology of Decision-Making

Ifat Levy Section of Comparative Medicine

Department of Neurobiology Interdepartmental Neuroscience Program

Yale School of Medicine

Harnessing eHealth and Behavioral Economics for HIV Prevention and Treatment

April 2012

Overview

• Introduction to neuroeconomics

• Decision under uncertainty – Brain and behavior

– Adolescent behavior

– Medical decisions

Neuroscience Psychology Economics

Neuroeconomics

Abstraction

“as if” models Mental states Neuronal architecture


Neuroeconomics

Abstraction

Behavioral Economics

Neuroscience

VISUAL STIMULUS

functional MRI

functional MRI: Blood Oxygenation Level Dependent signals

Changes in oxygen consumption, blood flow and blood volume

Signal from each point in space at each point in time

Neural activity

Change in concentration of deoxyhemoglobin

Change in measured signal

t = 1 t = 2

t = 3 t = 4

t = 5 t = 6

anterior posterior

dorsal

ventral

lateral

anterior posterior

dorsal

ventral

medial

Medial Prefrontal Cortex (MPFC)

Orbitofrontal Cortex (OFC)

Posterior Cingulate Cortex (PCC)

Ventromedial Prefrontal Cortex (vMPFC)

Anterior Cingulate Cortex (ACC)

The cortex

Sub-cortical structures

fMRI signal

• Spatial resolution: ~3x3x3mm3

• Temporal resolution: ~1-2s

• Number of voxels: ~150,000

• Typical signal change: 0.2%-2%

• Typical noise: more than the signal…

Low

Low

High

Low

High

But…

• Intact human brain

• Behaving human

• Whole brain

• Non-invasive


Neuroeconomics

Abstraction

Behavioral Economics Cognitive Neuroscience

New challenge: how do you make sense of such huge

amounts of data??

Neuroeconomics

Behavioral Economics

Cognitive Neuroscience

Economic models as normative theory

Mechanistic constraints of the human brain

Overview





100%

partial relief

50%

full remission

unknown

full remission

certainty risk ambiguity

Most people choose A, implying that B has fewer red than blue chips: red < blue

Most people choose A, implying that B has fewer blue than red chips: blue < red

OR

OR

A

A B

B

Choose one:

Risky Ambiguous

Risky Ambiguous

The Ellsberg paradox: a bag cannot have

fewer red chips and fewer blue chips at the same time

• Risk – probabilities of different outcomes are known

• Ambiguity – probabilities of different outcomes are not known

• Partial ambiguity – partial information

Non-certain outcomes

risk aversion

high probability low reward

low probability high reward

$40

known probability low reward

unknown probability high reward

unknown probability ambiguity aversion

known probability

$110

$0

$0

$110

Value of risk and ambiguity

Risk and ambiguity affect the subjective value of an option

in very different ways

Overview





single system multiple systems

neural representation of value

Research Question

reward punishment

immediate delayed

cognitive

emotional

reward punishment immediate

delayed cognitive

emotional . . .



vs. ambiguity risk ambiguity & risk

x,y,0.5,5

Research Question

Experimental design

Experimental design

OR:

Parametric design

Amount

Probability

Ambiguity level

Winning color

$5 - -

Real bags One trial played for real money

Amount [$]

p (c

hose

ris

ky)

p = 0.75

subject 1

$5

Gain-risk trials

Amount [$]

p (c

hose

ris

ky)

Gain-risk trials

p = 0.75

subject 1

$5

Amount [$]

p = 0.75

subject 1

$5

p (c

hose

ris

ky)

Gain-risk trials

Amount [$]

p (c

hose

ris

ky)

p = 0.75

subject 1

$5

p = 0.50

Gain-risk trials

Amount [$]

p (c

hose

ris

ky)

p = 0.75

subject 1

$5

p = 0.50 p = 0.38

Gain-risk trials

Amount [$]

p (c

hose

ris

ky)

p = 0.75

subject 1

$5

p = 0.50 p = 0.38 p = 0.25

Gain-risk trials

Amount [$]

p (c

hose

ris

ky)

p = 0.75

subject 1

$5

p = 0.50 p = 0.38 p = 0.25 p = 0.13

Gain-risk trials

Amount [$]

p (c

hose

am

bigu

ous)

A = 0.25

subject 1

$5

Gain ambiguity trials

Amount [$]

p (c

hose

am

bigu

ous)

A = 0.25

subject 1

$5

A = 0.50


Amount [$]

p (c

hose

am

bigu

ous)

A = 0.25

subject 1

$5

A = 0.50 A = 0.75


) 2

( A β − amount

V p probability

α risk

preference

· subjective value

ambiguity aversion

ambiguity level

stochastic choice model

Behavioral model MaxMin, Gilboa and Schmeidler 1989

p (c

hose

lott

ery)

Amount [$] Amount [$]

p = 0.75 p = 0.50 p = 0.38 p = 0.25 p = 0.13 A = 0.25 A = 0.50 A = 0.75

S1: gains

α = 0.55, β = 0.89 α = 0.58, β = -0.03

S2: gains

p = 0.75 p = 0.50 p = 0.38 p = 0.25 p = 0.13 A = 0.25 A = 0.50 A = 0.75

p (c

hose

lott

ery)

Amount [$]

S1: gains

α = 0.55, β = 0.89

Amount [$]

α = 0.58, β = -0.04

S1: losses

Ambi

guity

ave

rsio

n

Risk aversion Risk aversion

Risk aversion Ambiguity aversion

Loss

es

Gains Gains

Losses Gains

αβ VAp ⋅− )2

(

… … time

unde

r am

bigu

ity

unde

r ris

k

subj

ectiv

e va

lue

Subjective value under ambiguity

19 subjects, random effect analysis P<0.002 P<0.0001

R L

ACC / MPFC

caudate posterior cingulate amygdala

Subjective value under risk

19 subjects, random effect analysis P<0.01 P<0.001

R L

ACC / MPFC

caudate posterior cingulate amygdala

PCC amygdala

Unique areas for SV under ambiguity?

ambiguity risk

% s

igna

l cha

nge

% s

igna

l cha

nge

ambiguity risk

No…



vs. ambiguity risk ambiguity & risk

x,y,0.5,5

Research Question

Uncertainty Summary 1

• High variability in risk and ambiguity attitudes across individuals

• Areas in MPFC and striatum represent subjective value under both risk and ambiguity

Can attitudes towards risk and ambiguity explain phenomena like risk-taking in adolescents and overeating in obese

individuals?

Overview





• 200% increase in morbidity and mortality rates in adolescence compared to childhood (Dahl, 2004)

• Adolescents are physically healthier and stronger than both children and adults (Dey et al., 2004)

• Increase mostly attributed to risky behaviors: car accidents, alcohol and substance abuse, violence, eating disorders, unsafe sex (Reyna and Farley, 2006)

• Not due to flawed reasoning capabilities, poor decision-making skills or failure to understand the consequences of their actions (Reyna and Farley, 2006)

Adolescents take risks

Subjects

Age \ Gender

Female Male Total

12-17 17 16 33

21-25 18 16 34

30-50 17 15 32

65-90 18 17 35

Total: 70 64 134

In collaboration with Paul Glimcher

Adolescents vs. adults


• Adolescents are more risk averse, but less ambiguity averse than adults

• Young organisms need to learn about their world

Do people treat risk and ambiguity similarly in different domains?

In collaboration with Terri Fried

Overview





“You were involved in a car accident and as a result suffered traumatic brain injury. You were immediately rushed to the nearest hospital and were informed by the doctor that without immediate treatment you will not survive.”

Gains and losses in medical decisions

Gains: cognitive improvement

Major improvement = Mild cognitive disability: mild memory impairment resulting in forgetting some appointments, forgetting people’s names, needing a list to do food shopping

No effect Slight improvement Moderate improvement Major improvement Recovery

Worst outcome Best outcome

Slight improvement

No effect

recovery

or

Major improvement

No effect

or Slight

improvement

Gains and losses in medical decisions

Losses: headache as an adverse effect

Moderate headache: improves but does not resolve with acetaminophen (Tylenol); requires you to lie down occasionally to relieve pain; occurs a couple of times a week.

Critical headache Severe headache Moderate headache Mild headache Recovery

Worst outcome Best outcome

Mild headache

moderate headache

recovery

or

Mild headache

Severe headache

recovery

or

Decision under risk

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.13 0.25 0.38 0.5 0.75 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.13 0.25 0.38 0.5 0.75

Prop

ortio

n of

lott

ery

choi

ces

Outcome probability Outcome probability

Money Medical N = 29

Positive outcomes Negative outcomes

Decision under ambiguity Pr

opor

tion

of lo

tter

y ch

oice

s

0.75 N = 29

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

gain loss

Money

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

improvement adverse effect

Medical

0 0.50 0.25 Ambiguity level:


• Ambiguity aversion was observed both under gains and under losses when making medical decisions

Summary • Economic models can be used to make sense

of neural data

• High variability across subjects in attitudes towards risk and ambiguity

• Adolescents are more risk averse and less ambiguity averse than adults

• Ambiguity aversion in medical decision-making for both positive and negative outcomes

Acknowledgements Collaborators

Paul Glimcher, NYU

Aldo Rustichini, Minnesota U

Agnieszka Tymula, NYU

Amy Roy, Fordham

Terri Fried, Yale

Scott Huettel, Duke

Linda Mayes, Yale

Michael Crowley, Yale

Ashley Gearhardt, Yale

Eric Jackson, Yale

Daniela Schiller, Mount Sinai

Lab

Sarah Abdallah

Jennifer Fanning

Ellen Furlong

Patrick Kenney

Genny Ladiges

Kirk Manson

Helen Pushkarskaya

Lior Rosenberg Belmaker

Lital Ruderman

Sana Samnani

Jeannie Tran

Zhihao Zhang

Funding

NIA, Pepper Center

Sense of incompetence (Heath and Tversky, 1991)

People prefer to bet on events in their field of expertise, even when they judge the probabilities as equal

Comparative ignorance (Fox and Tversky, 1995)

How much will you pay for playing the lottery?

Within subject

>

Between subject

= More recent study: Ambiguity aversion is reduced but not abolished (Chow and Sarin 2001)

Informed opponent (Kuhberger and Perner, 1991)

Subjects chose the ambiguous option more when the person who filled the bag was a partner than when it was an opponent

Experimental design

Real bags!

Risk

Ambiguity

• Subjects were endowed with $125 • Gain and loss trials • Choice between a lottery and a certain amount (±$5) • 3 ambiguity levels: 0.25, 0.5, 0.75 • 5 risk levels: 0.75, 0.5, 0.38, 0.25, 0.13 • 5 outcome levels: ±$5, ±$8, ±$20, ±$50, ±$125 • 320 trials • 1 trial randomly selected and played for real money

Experimental design

) 2

( A β − amount

V p probability

α risk

preference

· subjective value

ambiguity aversion

ambiguity level

stochastic choice model

Behavioral model MaxMin, Gilboa and Schmeidler 1989

Amount [$] Amount [$]

p = 0.75 p = 0.50 p = 0.38 p = 0.25 p = 0.13 A = 0.25 A = 0.50 A = 0.75

S2: gains

α = 0.58, β = -0.03 α = 0.86, β = 0.72

S2: losses p

(cho

se lo

tter

y)

MPFC

ambiguity risk

Subjective value in ambiguity defined regions %

sig

nal c

hang

e

striatum

% s

igna

l cha

nge

ambiguity risk

Subjective value in risk defined regions

ambiguity risk

% s

igna

l cha

nge

striatum

% s

igna

l cha

nge

ambiguity risk

MPFC

• 200% increase in morbidity and mortality rates in adolescence compared to childhood (Dahl, 2004)

• Adolescents are physically healthier and stronger than both children and adults (Dey et al., 2004)

• Increase mostly attributed to risky behaviors: car accidents, alcohol and substance abuse, violence, eating disorders, unsafe sex (Reyna and Farley, 2006)

• Not due to flawed reasoning capabilities, poor decision-making skills or failure to understand the consequences of their actions (Reyna and Farley, 2006)

Adolescents take risks

And in the brain…

• Gray matter maturation processes in PFC and striatum continue into adolescence (Giedd et al., 1996, 1999, 2004)

• Frontal increase in white matter occurs late and extends into adulthood (Fuster, 2002)

• Structural atrophy and decline in dopamine receptors in striatum and PFC in aging (Backman et al., 2000; Volkow et al., 1998)

• Altered striatal activation during gain anticipation in adolescents compared to adults (Ernst et al., 2005; Galvan et al., 2006; Bjork et al., 2004)

• Reduction in activation in striatal areas during loss anticipation in older adults (Samanez-Larkin et al., 2007).

Adolescents vs. adults

Controls

“Cognitive” blocks No effect = The treatment failed. You end up in a vegetative state. Slight improvement = Severe cognitive disability: severe memory impairment resulting in inability to recognize your loved ones. Moderate improvement = Moderate cognitive disability: moderate memory impairment resulting in inability to work and participate in leisure activities such as playing cards or doing crossword puzzles. Major improvement = Mild cognitive disability: mild memory impairment resulting in forgetting some appointments, forgetting people’s names, needing a list to do food shopping. Recovery = return to your initial cognitive ability prior to the accident.

“Headache” blocks

Recovery = successful treatment with no side effects.

Mild headache: responds to acetaminophen (Tylenol); does not interfere with daily activities; occurs a couple of times a week.

Moderate headache: improves but does not resolve with acetaminophen (Tylenol); requires you to lie down occasionally to relieve pain; occurs a couple of times a week.

Severe headache: not responsive to acetaminophen (Tylenol); requires stronger pain medication, which does not fully relieve pain; requires you to lie down frequently to relieve pain; occurs daily.

Critical Headache: Severe headache (as above) accompanied by other symptoms, such as nausea and vomiting.

neuroeconomics: the neurobiology of decision-making

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