A plea for interdisciplinarity (Hayek's quote)

he who is only an economist cannot be a good economist. Much more than in the natural sciences, it is true in the social sciences that there is hardly a concrete problem which can be adequately answered on the basis of a single special discipline.

-- Hayek, 1967

p. 267 in Studies in Philosophy, Politics and Economics, pp.251–269. Chicago: University of Chicago Press.

Social Cognition: A Special Issue of Science

The new edition of Science if devoted to Social Cognition. It

(...) explores the adaptive advantages of group life and the accompanying development of social skills. News articles examine clues from our primate cousins about the evolution of sophisticated social behavior and explorations of human behavior made possible by computer-generated realities. Review articles dissect the human capacity for prospection and the links between sociality and brain evolution and fitness. And related podcast segments highlight research on the social abilities of children and chimps and the value of virtual worlds to studies of social science

Four papers you don't want to miss:

• Dunbar, R. I. M. and Susanne Shultz. 2007. “Evolution in the Social Brain.” Science 317(5843):1344-1347.
• Herrmann, Esther, Josep Call, Maria Victoria Hernandez-Lloreda, Brian Hare, and Michael Tomasello. 2007. “Humans Have Evolved Specialized Skills of Social Cognition: The Cultural Intelligence Hypothesis.” Science 317(5843):1360-1366.
• Silk, Joan B. 2007. “Social Components of Fitness in Primate Groups.” Science 317(5843):1347-1351.
• Wood, Justin N., David D. Glynn, Brenda C. Phillips, and Marc D. Hauser. 2007. “The Perception of Rational, Goal-Directed Action in Nonhuman Primates.” Science 317(5843):1402-1405.

Moreover, in the same edition, psychologists Dan Gilbert and Tim Wilson presents a theory of prospection, the anticipation of future events (a subject important for decision-making research:

All animals can predict the hedonic consequences of events they've experienced before. But humans can predict the hedonic consequences of events they've never experienced by simulating those events in their minds. Scientists are beginning to understand how the brain simulates future events, how it uses those simulations to predict an event's hedonic consequences, and why these predictions so often go awry.

• Gilbert, D. T., & Wilson, T. D. (2007). Prospection: Experiencing the Future. Science, 317(5843), 1351-1354.

A basic mode of behavior: a review of reinforcement learning, from a computational and biological point of view.

The Journal Frontiers of Interdisciplinary Research in the Life Sciences (HFSP Publishing) made its first issue freely available online. The Journal specializes in "innovative interdisciplinary research at the interface between biology and the physical sciences." An excellent paper (complete, clear, exhaustive) by Kenji Doya presents a state-of-the-art review of reinforcement learning, both as a computational theory (the procedures) and a biological mechanism (neural activity). Exactly what the title announces: Reinforcement learning: Computational theory and biological mechanisms. The paper covers research in neuroscience, AI, computer science, robotics, neuroeconomics, psychology. See this nice schema of reinforcement learning in the brain:

(From the paper:) A schematic model of implementation of reinforcement learning in the cortico-basal ganglia circuit (Doya, 1999, 2000). Based on the state representation in the cortex, the striatum learns state and action value functions. The state value coding striatal neurons project to dopamine neurons, which sends the TD signal back to the striatum. The outputs of action value coding striatal neurons channel through the pallidum and the thalamus, where stochastic action selection may be realized

This stuff is exactly what a theory of natural rationality (and economics tout court): plausible, tractable, and real computational mechanism grounded in neurobiology. As Selten once said, speaking of reinforcement learning:

a theory of bounded rationality cannot avoid this basic mode of behavior (Selten, 2001, p. 16)

References

• Kenji, D. (2007). Reinforcement learning: Computational theory and biological mechanisms. HFSP Journal, 1(1), 30-40.
• Selten, R. (2001). What is bounded rationality ? . In G. Gigerenzer & R. Selten (Eds.), Bounded Rationality: The Adaptive Toolbox (pp. 13-36). MIT Press: Cambridge, MA.
  

The selective impairment of prosocial sentiments and the moral brain

Philosophers often describes the history of philosophy as a dispute between Plato (read: idealism/rationalism) and Aristotle (read:materialism/empiricism). It is of course extremely reductionist since many conceptual and empirical issues where not addressed in Ancient Greece, but there is a non-trivial interpretation of the history of thought according to which controversies often involves these two positions. In moral philosophy and moral psychology, however, the big figures are Hume and Kant. Is morality based on passions (Hume) or reasons (Kant)? This is another simplification, but again it frames the debate. In the last issue of Trends in Cognitive Science(TICS), three papers discusses the reason/emotions debate but provides more acute models.

Recently (see this previous post), Koenig and other collaborators (2007b) explored the consequences of ventromedial prefrontal cortex (VMPC) lesions in moral reasoning and showed that they tend to rely a little more on a 'utilitarian' scheme (cost/benefit), and less on a deontological scheme (moral do's and don'ts ), thus suggesting that emotions are involved in moral deontological judgement. These patients, however, were also more emotional in the Ultimatum game, and rejected more offers than normal subjects. So are they emotional or not? In the first TICS paper, Moll and de Oliveira-Souza review the Koenig et al. (2007a) experiment and argue that neither somatic markers nor dual-process theory explains these findings. They propose that a selective impairment of prosocial sentiments explains why the same patient are both less emotional in moral dilemma but more emotional in economic bargaining. These patients can feel less compassion but still feel anger. In a second paper, Greene (author of the research on the trolley problems, see his homepage) challenge this interpretation and put forward his dual-process view (reason-emotion interaction). Moll and de Oliveira-Souza reply in the third paper. As you can see, there is still a debate between Kant and Hume, but cognitive neuroscience provides new tools for both sides of the debates, and maybe even a blurring of these opposites.


References

• Moll, J., & de Oliveira-Souza, R. (2007). Moral judgments, emotions and the utilitarian brain. Trends in Cognitive Sciences, 11(8), 319-321.
• Greene, J. D. (2007). Why are VMPFC patients more utilitarian? A dual-process theory of moral judgment explains. Trends in Cognitive Sciences, 11(8), 322-323.
• Moll, J., & de Oliveira-Souza, R. (2007). Response to Greene: Moral sentiments and reason: friends or foes? Trends in Cognitive Sciences, 11(8), 323-324.
• Koenigs, M., & Tranel, D. (2007a). Irrational Economic Decision-Making after Ventromedial Prefrontal Damage: Evidence from the Ultimatum Game. Journal of Neuroscience, 27(4), 951-956.
• Koenigs, M., Young, L., Adolphs, R., Tranel, D., Cushman, F., Hauser, M., et al. (2007b). Damage to the prefrontal cortex increases utilitarian moral judgements. Nature, 446(7138), 908-911.
  
  
  

On neuroeconomics, its content and its future

I have been contacted by a research group who prepare a report to the Benchmarking Panel of Economics Degrees, to recommend whether Neuroeconomics should be taught as part of Economics degrees at universities across the UK. They had a couple of questions about neuroeconomics, its teaching, its future, etc. My answers are posted here.


What do you feel the teaching of Neuroeconomics gives to its students? (I.e. why would you recommend it to be studied).

• I strongly recommend that any student of economics has a bacground in neuroeconomics.
• Neuroeconomics does what economics should be doing: providing sound models of human valuation before devising more abstract theories.
• It promotes an empirical attitude in economics.
• Neuroeconomics is part of a Trinity: with psychology and classical microeconomics, one has behavioural data, neural activation data and formal models to describe the behavior and the neural activity. A genuine economic science should deals with neurons, peoples and values.

Do you feel the course is challenging to Economics Students? If yes, how so?

• yes, because neuroscience is a highly technical field. Students do not have an empirical background (psychology, neuroscience). Economic departments, however, would benefit from this integration.

Are you pleased with the overall results achieved by your students?

• I taught a course called “Natural Rationality” at the University of Waterloo, and almost half of the content was about neuroeconomics: http://phi673uw.wordpress.com. It triggered many discussions and reflections. So yes, I am pleased with these conceptual “results”.

What potential careers would you feel Neuroeconomics students could succeed in?

• Research in cognitive neuroscience, (not basic neuroscience), experimental economics, microeconomics, sociology, policy-making, Law, politics, psychology, marketing, management.

What potential do you feel Neuroeconomics has for the future of economics in terms of both research and teaching? (I.e. do you feel this will continue to catch on or will the academic world lose interest?)

• Neuroeconomics is not a temporary buzz: it will stay, because it is a complement to behavioural economics. Even if economists lose interest, many researchers from other fields would pursue the project. For the first time in the history of economics, we have – at the same time – formal models of decision-making, cognitive theories of judgment, empirical data on subjects’ real behavior, neural data on brain activation and anatomy, and computational description of neural processes. Economists who take this interdisciplinary turn will revolutionize the discipline. Their students will not discuss axiomatization or existence theorems, but prediction, refutation, correlation, etc. Although it will be hard to keep up to date (there is already many publications), handbooks of neuroeconomics could help research and teaching.

Many sceptics of Neuroeconomics say that the subject only shows where things in the brain happen, and not necessarily why they happen. What would you say to them to convince them otherwise?

• I would first reply that saying that implies discrediting all imaging studies: it is a huge claim. It is always theoretically and practically useful to know what brain resources are involved in an economic task: is it positive/negative emotions, cognition, reward processing, action representation, etc.
• Second, neuroeconomics is not just about imaging: it is also about providing models of neural mechanisms of decision-making, motivation and valuation.
• Third, I would give an example: look at the ultimatum game results. We now from experimental psychology that people make ‘fair’ offer, and reject ‘unfair’ ones. This is compatible with many interpretations (people are irrational, people are influenced by the experimenters, people value fairness). Neuroeconomics (Sanfey et al, 2003) showed that unfair offers trigger negative emotions (anterior insula). Thus it narrows the range of interpretations: people reject unfair offers because they don’t like that. They have preferences for fair offers. The study also showed that other areas are involved: the dorsolateral prefrontal cortex and the anterior cingulated cortex. The first one is involved in cognitve control, the other in emotion modulation. Thus subjects’ choices balance fairness and monetary gain: this processing is not captured by decision theory. Other neural studies also showed that subject enjoy making cooperative moves in prisoner dilemma. Thus subjects value something else than just money. This is important for economics.
  

Many techniques of brain imaging either don’t show enough detail or are potentially damaging to human subjects, or simply cannot be used on humans at all. How do you feel this potential downside of Neuroeconomics will develop, and could it damage the long-term potential for Neuroeconomics to be taught across the board?

• No, because cognitive neuroscience also faces the same problems. Moreover, neuroeconomics also relies on lesion studies, animal models and computational modelling. Again, Handbooks of neuroeconomics could be use as “databases” for research in economics.

Please add any further comments:

• The keyword for the future of economics is interdisciplinarity: neuroscience, psychology, biology, Artificial Intelligence and anthropology are all necessary if we want economics to be the “science which studies human behavior as a relationship between ends and scarce means which have alternative uses” (L. Robbins). Formal models can represent human behavior, but these models ought to be grounded in facts, something these disciplines can afford.