Decisions & the Brain. Neuroeconomics CCN Lecture Matteo Colombo 11 February 2010.

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Decisions & the Brain. Neuroeconomics CCN Lecture Matteo Colombo 11 February 2010

Transcript of Decisions & the Brain. Neuroeconomics CCN Lecture Matteo Colombo 11 February 2010.

Decisions & the Brain. Neuroeconomics

CCN LectureMatteo Colombo11 February 2010

Structure of the Lecture

Neuroeconomics. What is it and what’s its aim?

Using economics to do neuroscience Using neuroscience to do economics Public Goods. A Case study. Game Time… “Giving-choice” Motives and Rationality

Neuroeconomics. What is it?

“… an interdisciplinary research program with the goal of building a biological model of decision making in economic environments. Neuroeconomists ask: ‘how does the embodied brain enable the mind (or groups of minds) to make economic decisions?’ ... Neuroeconomics allows us to better understand both the wide range of heterogeneity in human behavior, and the role of institutions as ordered extensions of our minds” Kevin McCabe (Economist)

One Goal Two Perspectives

“The goal of neuroeconomics is an algorithmic description of the human mechanism for choice.” Paul Glimcher (Neuroscientist)

Combines experimental techniques from neuroscience, psychology, and experimental economics (e.g., electrophysiology, FMRI, eye-tracking, behavioural studies) and models from computational neuroscience and economics.

Some Questions of Neuroeconomics

What are the computational processes that the brain uses to make economic decisions?

What is the neural basis of these processes? How (and where) are value and probability

combined in the brain to provide a utility signal? How do emotion and cognition interact to shape

decisions? What are the mechanisms of social decision-

making? ...

Using Economics to do Neuroscience. Why?

(Shizgal & Conover (1996); Shadlen & Newsome (2001);Glimcher (2003))

A unified theoretical framework for understanding human behaviour – behaviour can be interpreted as choosing alternatives with the goal of maximizing utility.

Normativity: Precise Definition of Optimal Performance \ Analytically tractable

Simpler evolutionarily conserved mechanisms might prove to be closer to optimal.

Generation of precise, testable predictions about the system’s behavior.

A benchmark against which to compare actual behavior. Systematic deviations from optimality can generate new insights into underlying mechanisms.

Expected Utility Theory. In a Nutshell

Given some restriction on the preferences of a decision-maker in a risk situation, it exists a function U that represents the preferences of a decision-maker S in a situation of risk or uncertainty, such that if S prefers A to B, then U(A)>U(B) and if S is indifferent to A and B, then U(A) = U(B).

A function of utility u also exists, such that if the outcome x of a prospect is preferred to the outcome y, then u(x) > u(y) or, in the case of indifference, u(x) = u(y).

Given U and u, and given a prospect A which pays x with probability p, and y with probability (1 – p), then:

In general utility is computed as the product of the value and the probability of each potential outcome

Two components: Value and Probability

Neural Basis of Utility Signal

Interaction between value and probability in the computation of utility and the execution of decision-making behavior.

An Example

Neural Bases of EU (Knutson et al 2005)

Shape (circle or square): valence;

Vertical line (left, middle, right):

magnitude

Horizontal line (high, middle, low): probability

Results

The subcortical nucleus accumbens (NAcc) activated proportional to anticipated gain “magnitude”.

The cortical mesial prefrontal cortex (MPFC) activated according to anticipated gain probability.

In sum

For some choice domains (vision, food, sex, safety), evolution has had a long time to sculpt pan-species mechanisms that are crucial for survival.

Mechanisms that implement rational choice (utility-maximization and Bayesian integration of information).

Economic models as tools to test and develop algorithmic models of the neural hardware for choice.

Using the Brain to do Economics

Neoclassical econ models (like SEU) do not provide a satisfactory description of human behavior…

Bounded Rationality & The rise of “Behavioural” Economics.

Human behaviour is not the product of a single process, but rather reflects the interaction of different specialized systems.

Dual Process Models.

Two waysEconomists can use the Brain

I) “Evidence which support the kinds of variables and parameters introduced in behavioral economics.”

II) “Evidence which suggest the influence of “new” variables that are implicit, underweighed, or missing in rational-choice theory.” Colin Camerer

Test and develop alternatives to neoclassical/revealed preference theories

Public Goods. A Case Study

Commodities that can’t be provided without everybody being able to consume them.

Eg: National defense, Clean Air, Public Fireworks, Street Lights, Knowledge, ...

The fact that one person benefits from these things does not diminish their value to other people,

and people can’t be prevented from enjoying the benefits these goods produce.

Public Goods Games. The free rider problem

If people can choose whether or not to buy a ticket when riding on trains, will enough people pay to cover the cost of running the system?

Public goods (PG) games are used to study social dilemmas that arise when the welfare of a group conflicts with the narrow self-interest of each individual group member.

Each player has the private incentive to contribute nothing, and the unique subgame perfect Nash Equilibrium occurs when each subject contributes zero to the group account.

…Game Time

Why paying taxes?

Two Possible Motives Satisfaction from increases in a public good,

such as the provision of basic services to the needy. “Pure Altruism”

Sense of agency associated with the act of voluntary giving. “Warm Glow”

Neural evidence may help clarify the relative importance of pure altruism and warm-glow motives for giving-decisions.

Predictions

A person only gets warm-glow benefits if she makes an active decision to give, while a purely altruistic motive should be satisfied even by passively observing an increase in the public good which is paid for by someone else.

Harbaugh et al (2007)

Upshot Harbaugh et al (2007)

“Consistent with pure altruism, we find that even mandatory, tax-like transfers to a charity elicit neural activity in areas linked to reward processing.”

neural responses to the charity's financial gains predict voluntary giving.

However, consistent with warm glow, neural activity further increases when people make transfers voluntarily.

Both pure altruism and warm-glow motives appear to determine the hedonic consequences of financial transfers to the public good.

In Sum

Evidence supports existence of a purely altruistic motive for charitable giving.

In large societies this motive may lose its force, and could not explain the widespread giving that we observe.

The combination of Pure Altruism and warm-glow known as Impure Altruism may be an appealing alternative model.