Neuroeconomics

Question 1

Computational model - Steps

Answer 1

1. Brain computes decision value signal at the time of choice
2. Brain computes experienced utility at the time of consumption
3. Brain compares decision values using a drift-diffusion model
4. Decision values are computed based on each option’s attributes and their respective attractiveness
5. Computation and comparison of decision values are modulated by attention using the original drift-diffusion model + ß to represent attention

Question 2

Brain computes decision value signals at the time of choice

Answer 2

1. Deliberate in DLPFC
2. Hedonic consumption in limbic system
3. OBFC is switchboard
4. Forecasts the hedonic impact of each option

Question 3

Brain computes experienced utility at the time of consumption

Answer 3

1. Experienced v. expected utility

2. Can be influenced by surprise, belief and price

Question 4

Drift-diffusion model

Answer 4

Rt+1 = Rt + ø * {ß*(v(x)-v(y))} + Ɛt

Rt = Relative decision value signal
ø = Constant affecting speed
v(x) and v(y) = Decision value of different options - The bigger the difference the upper/downer the slope goes
Ɛt = Stochastic error term
ß = Attention

Question 5

Decision values are computed based on each option’s attributes and their respective attractiveness

Answer 5

v(x) = Sum of wi*di(x)

The brain takes into account the value of an attribute only to the extent that it can consider it in the construction of decision values

Question 6

Other models

Answer 6

1. Pavlovian system

2. Habitual system

Question 7

So mistakes come from…

Answer 7

1. Stochastic error in choices
2. Errors in computation of decision values
3. Biases in attention

Question 8

Relative evaluations and neuroscience

Answer 8

1. Amygdala activity was correlated with positive or negative value relative to what might have happened
2. OBFC and amygdala activity when making ambiguous gambles - Because scary and emotional