Neuroeconomics: arriving at a consensual definition

Opinions about neuroeconomics vary enormously – to begin with, there is little agreement about what even *counts* as neuroeconomics.

In my historical study of neuroeconomics,  I am confronted to this difficulty right from the first step. Before even analyzing it, what is neuroeconomics, the field that I am studying? There is yet no journal of neuroeconomics which would map and delineate the topic, and there is of course no single parent field from which this sub-field can be traced from.

Mapping neuroeconomics

The Society for Neuroeconomics is a useful rallying point where neuroeconomists can be found, but there is an obvious North American bias. More, an unknown proportion of scientists attending this conference would be reluctant to be labeled neuroeconomists, if I refer to the interviews I conducted there. So?

There is always the possibility to ask “the experts”, as it is customary to do in scientometrics. That is, I would not placate any arbitrary definition of neuroeconomics on the field, but would ask some renowned neuroeconomists what they would consider classic papers in neuroeconomics, or who do they consider to be the leading figures in neuroeconomics, and then start from there.

The problem with this approach is that leading neuroeconomists are truly extremely busy people, so the sample of experts that I could tap from would be very low, and hence surely not representative of all the currents represented in neuroeconomics.

There are many other ways to define a field, all with their particular drawbacks. One is to refer to the indexing of papers performed by Thomson Reuters‘ ISI Web of Knowledge, a database which records and indexes virtually all peer-reviewed journals and their papers on the planet since 1988. If a paper is indexed with the keyword “neuroeconomics”, then it can count as neuroeconomics. Authors who published a certain number of articles indexed with the keyword “neuroeconomics” can be considered to be neuroeconomists. However, this approach is equivalent to delegating the task of defining neuroeconomics to the employees in charge of indexing the papers at Thomson Reuters: given the immensity of their task, probably not the best experts in neuroeconomics.

I am in the process of finding my own (and hopefully, consensual) solution to this arduous problem of mapping a field which has still not a stabilized identity. But from experience, it is an issue where everybody can quickly come up with their preferred procedure. So, what do you think? What would be your procedure to arrive at a definition of *who is a neuroeconomist*, and *what is a paper in neuroeconomics*?

But what exactly is computational neuroeconomics?

Computational neuroeconomics?

Neuroeconomists develop their own jargon, as it is to be expected from a consolidating community of scientists with distinct interests. But denominations, categorical classifications, and basic concepts in neuroeco are very much still in the early stages of their definitions – they have not been “blackboxed” yet.

“Computational neuroeconomics” is one of such terms. I was a bit tired of nodding to my interlocutors when computational neuroeco popped up in interviews, without being sure to understand how different it was from “not computational” neuroeco, or from computational modeling in cognitive neuroscience.

A first possibility was that it could resemble this class of models where connectivity of different brain regions is represented by an analogy with the architecture of a computer.  This is the kind of model used by Peter Dayan and Szabolcs Kali in a paper in 2004, who discussed memory storage and retrieval.

It could have also been the models inspired not by computer hardware, but by softwares: algorithm processes which demonstrate that starting with very simple building blocks and logical rules, an organism could  achieve complex cognitive tasks like letter recognition and other sensory to motor tasks.

But computational neuroeconomics seems in fact to represent an alternative, third possibility.  An entire session was devoted to it in the third day of the annual meeting of the Society for Neuroeconomics. It featured papers which were basically game theory applied to social cognitive problems. The language of game theory provides concepts  to think many useful parameters of behavior: strategies, payoffs, probabilities, types. As I understand it, the task of computational neuroeco is to operationalize those concepts. In the speeches of the session, it was interesting to see how the presenters navigated between mathematical sophistication, and constant references to pragmatic issues in social behavior: what theory of mind emerges from repeated interactions between players, or how risk minimization is accomplished through learning.

Is it a new approach in neuroeconomics? Not really. When one thinks about it, it is “simply” further work in a direction impulsed by Paul Glimcher and his collaborators since the very beginnings of neuroeconomics, when they introduced expected utility and then Bayesian Nash equilibrium in their studies of neurons in the LIP area for monkeys.  In this light, computational neuroeco appears to be at the very core of the new discipline.

Annual Meeting of the Society for Neuroeconomics – day 1

This is the second annual meeting of the SfN that I attend, and this time I am there to do interviews and publicize an online survey on interdisciplinarity which I designed for neuroeconomists (are you a neuroeconomist? Drop me an email at clevallois@rsm.nl, and I will send you the link to it).

The program is remarkably different from the last year. Much less rat studies, and a lot of papers and posters on social interactions in humans. I am not sure whether it reflects an inflexion in the selection process by the organizing committee, or a new direction in neuroeconomics. A participant at the diner hinted that it merely reflects the changes in priorities laid out by funding agencies.

A few labs are overrepresented – Duke and CalTech; and the usual big names are all around. I could interview Peter Bossaerts, Colin Camerer and Paul Gimcher, and I should continue this series tomorrow.

For this evening, I hesitate between catching up with some sleep and fight the jetlag, or join the conference-sponsored dart-and-pool evening at the pub around the corner. Hm.

Free-rider problem solved through neuroeconomic design

That is big, really big.

The free-rider problem is simple. It describes those situations when a group of individuals would benefit from a common action, but each individual separately would prefer not to make any effort to make this action happen.

Like: as a group, we would like to have an environmental policy to stop global warming, but when asked how much tax I personally would be ready to pay to implement this policy, I refuse to declare that I’d be willing to pay much. Even if the amount that I would pay would be more than compensated by the benefits of an environmental policy! Simply because hey, if the environmental policy is decided by others and payed by others, once implemented it will also benefit me, so why would I bother paying for it? It is much easier to let others pay for it, and then, I’ll benefit from it anyway!

Another free rider

It is the eternal problem of the free rider: “I would like to have the benefits of the collective action, but I would prefer if the costs were payed by my neighbor.” The problem is, of course, that if everybody thinks like that, then everybody states that they would not pay much, and the budget for the collective action is never gathered. That’s too bad, because the collective good would have enhanced everybody’s welfare!

It has huge implications for tax policy, or any issue where a collective action would be required. And the difficulty faced has always been that when you ask people “how much would you be ready to pay for this collective good”, they tend to understate what they are really willing to pay – always hoping that the collective good will be build anyhow – but payed by their neighbors.

What if we could “read” in people’s mind what they would really like to pay for a collective good? This would allow to know how much people would each be ready to pay for the collective action. The collective action would then be undertaken, only if its benefits would be superior to the sum of the payments that each individual declared to be ready to make.

This is the experiment conducted by a team of CalTech neuroeconomists, just published in Science. They gathered groups of subjects, and scanned their brain while they stated the amount they were willing to pay for a given collective investment.

To be precise, this what not a simple lie-detector mechanism: the accuracy of the scan to detect the “honesty” of your choice was just 56%. But it is enough to act as a threat to participants: they will be punished with heavy taxes if they are found to be willing to pay very little for an investment which will repay them much. It acts as an incentive for participants to reveal their true preference each time they are asked about a potential collective investment!

Ian Krajbich, lead author of the study

The results of this “Neurally Informed Mechanism” as they call it are astounding: the total welfare achieved by this experiment is 93% of the ideal case, which means that free-riding has almost completely disappeared! This is a remarkable result, given that traditional experimental settings do not score better than 23%.

So, the free-rider problem, or the problem of collective action finally solved? Neuroeconomics made an interesting step in this direction. Huge!

The study raises some questions though. For example, the procedure followed shows that the participants were convinced with lengthy, technical arguments that the “not free-riding” strategy was the most advantageous one.  Those arguments were true, and the experimenters deduce that if the participants did not free-ride, it is because they understood it was in their best interest. But one can also object that they did not free-ride simply because they had been brain-washed about not free-riding: they simply trusted the experimenter and played in the fashion that was strongly suggested. If that is the case, then the 93% result is not so amazing.

This doubt is even greater when one wonders about the actual role played by the fMRI scan: crucial or not? At 56% of free-riding detection, just above fifty-fifty, one doubts whether the participants refused to free-ride because the threat of the scan detection made it the best strategy to play, or simply because they were impressed by this big machine and the intense strategical training they received from the researchers (see the supplement online material of the article, esp. the section “strategy” on pp. 42-45, which shows how much the participants were lectured about NOT free-riding. )

More about it? Antonio Rangel, an economist in the CalTech team reports on the Science article in an interviewed by James Hugues, from the Institute for Ethics and Emerging Technologies. Click here for the interview.

Neuroeconomics at Caltech in 2008 – a video presentation

A nice summary with Colin Camerer, Ralph Adolphs, etc.

Thanks to Investing Pinoy for the link.

Phineas Gage: the Picture

Like any other science, neuroscience has its founding myths, historical anecdotes, legendary figures… Phineas Gage is one of the most famous.

He was a railroad worker who, on September 13, 1848, was victim of a dynamite explosion which sent a long metal pole through his left chick, eye orbit, brain, and got out the top of his head. Much of the medial region of his prefrontal cortex was just suddenly wiped out… and Phineas Gage survived.

This made him a living experiment in the role of the brain in higher cognitive functions. The myths has it that his basic cognitive skills were undamaged, but that his social behavior shifted dramatically – Phineas became much more irritable and aggressive.

Since then, Phineas Gage is an obliged fixture for undergrad textbooks in cognitive neuroscience (like in Gazzaniga et al. textbook, on p. 600).  Until a few days ago, you were most likely to be presented to Phineas in the following guise:

Phineas Gage's crane

The amazing event is that a daguerreotype of him has just been identified, and that is the buzz of summer ‘09 in the community of neuroscientists! The daguerreotype was in a collection for years, but the owners thought it was the portrait of a whale hunter. So please join me in greeting Phineas Gage. Note the metal pole in his hand: yes, it is the one which pierced his crane.

Phineas Phage

The precursors to neuroeconomics

Sin suits me - Roy Booth, 1935

Writing the title of this post, I feel like I indulge in a delicious sin. Indeed, if there is one taboo in today’s respectable history of science, it is certainly the search for precursors, originators, “first scientist to come up with a theory”, etc. That might sound strange to you, but there are good reasons for that taboo. One of them is that the search for precursors tends to reify ideas, a bit as if ideas were objects that were invented and patented once and for all (whereas one realizes soon that they keep changing in meaning, hence there is no historical origin to a “single idea”). Another reason is that by playing the game of “who got this idea first” seriously, you would almost invariably end up with Aristotle or Adam Smith if you are an economist, and that is boring.

Anyway, I find it fun to transgress those very serious codes, and ask: who got first the idea for neuroeconomics?

Passions with Reason (Frank, 1988)

I just finished reading Robert Frank’s Passions within Reason, a book he published in 1988. This book could be said to be the first in neuroeconomics (Roman trumpet victory sounds in the background). Robert Frank is an economist who, as far as I can tell, is now also writing a lot in the press (NYT column, etc.), and has become an intellectual figure, like a minor Paul Krugman maybe.

So, why is Passions within Reason our winner? This book makes a perfect transition between two periods of the relationship between economics and biology. The period when Darwinian evolution was the hot topic (up to the eighties), and the period we live in now where the brain is the explanation for everything biological in economics. Yes, the two topics are clearly distinct. Before the nineties, you hardly find a discussion in economics about the neurocognitive dimension of economic behavior. Conversely, in today’s neuroeconomics the discussion of the evolutionary dimension of economic behavior is tucked away in a few pages of books in neuroeconomics (just check Gazzaniga’s textbook on Cognitive Neuroscience, or the textbook in neuroeconomics by Glimcher and al., both from 2008).

And between those two periods, you have Frank’s book, which meshes the two: evolutionary explanations à la Jack Hirshleifer / Robert Trivers / Edward Wilson, and a speculative discussion of the decision-making system where “pure rationality” and “emotions” are both inputs in the brain systems which ultimately account for the behavior of the individual.

Robert H. Frank

A real precursor then, “prescient” that the brain was the next big thing, and “unjustly ignored” until now, as it befits to a genuine pioneer. Frank just lacked an essential piece of technology to become the Adam Smith of neuroeconomics: the fMRI brain scans (note: precursors always lack something, if they had everything they would be “new Adam Smithes”). The fMRI  began to be used in social science precisely in the late 80s, and neuroeconomics as we know it today appeared with it.

Soon, I will examine another candidate for the title of best precursor to neuroeconomics: George Ainslie and his picoeconomics.

And you thought you knew about neuroeconomics ?

Paul Farrell, a long time ago

Reading a column by someone called Paul B. Farrell on Market Watch, a website related to the Wall Street Journal news group, I realized that what neuroeconomics is to me did not correspond to Farrell’s neuroeconomics. At all.

Farrell is mad at neuroeconomists who “promise that if investors, taxpayers and voters simply follow the advice of neuroeconomists, they’ll get rich”. Uh? Later in his column, Farrell gets frantic:

And they [neuroeconomists] are always one step ahead of you and whatever you think you get from their neuroeconomics books. They really are working for Wall Street insiders. What they’re doing is similar to DNA mapping, except the neuroeconomists use MRIs to map your irrational behavioral patterns, then, like a CIA intelligence team secretly monitoring the enemy, their quants develop algorithms that help Wall Street target the little guy with new “financial weapons of mass destruction” that manipulate financial markets.

I don’t know for you, but I don’t follow that too well. As an observer of neuroeconomics, what am I supposed to do with this kind of strange material? I think it educates me on two scores.

First, I have to get used to the rhetoric of online journalism, much more than I am now. Because it really seems that the hysterical tone of this column participates to its dissemination (the blog post I am currently writing is an evidence of it). Hence,  the column by Farrell is not a minor piece of primary material on neuroeconomics. The mere fact that his opinion is shouted is bound to give it some weight. Sad maybe, but the cold and impartial historian of neuroeconomics shall not be moved by that! 

Second, this column is a plea for including “pop neuroeconomics” in the scope of the study of the field. The frontiers are just too blurred, and the exchanges between “academic neuroeconomics” (practised in universities) and pop neuroeconomics (practised in consulting firms and published in self help books) are too significant to ignore. How significant exactly? This column gives a clue of it, but I should be much more precise when I will have read extensively in this literature in “neuroeconomics for brainy traders” and “neurofinance: get rich in three days”. Wish me luck.

The Millionaire Code

Coda: a search on internet turns out this book cover. The vociferations of Farrell against the false promises that neuroeconomics would make to small traders appear in a much better perspective, now!

Much to learn from neuro-finance?

Neuro-finance is now (slowly) making its way onto the economics curriculum, one instance of which is in Ireland, where Dr. Stephen Kinsella, has included a lecture on it, in his lectures on financial economics. This is probably pretty good news for the neuro-scientists out there, but will it bring new insights, or more navel gazing, to a sub-discipline already deeply involved with itself?

Lecture Slide on responses to Intertemporal Choices... Pretty

Either way, it’s cutting edge, and it could provide some answers to the questions and (empirically tested) theories  which Kahneman and Tversky have already provided… Dr. Kinsella offers a very helpful list of extra reading and lecture notes, which discusses the neural responses to decisions about whether to take rewards now or later. It’s admittedly fascinating stuff, but I am not sure if it can add up to explanations of how and why the whole financial markets work, but that is not so much an indictment of neurofinance, but more to do with micro and macroeconomics. At least the brain scans give us something to look at.

The invisible neuroeconomics

Once again, what is neuroeconomics? I would argue that 2 coming symposia organized in The Netherlands are about neuroeconomics. At least two prominent figures in neuroeconomics present talks – Allen Sanfey from the University of Arizona, and Scott Huettel from Duke University. The topic of the symposium is about decisions, reward, punishment, fairness, risk taking, … which are the bread and butter of neuroeconomics.

Yet, “neuroeconomics” is nowhere to be seen in the program. So I would argue that this is brand management in action here: depending on the audience, the place, and the strategic goal pursued in a given communication exercise, the displayed identity is molded with care. Now, the question is: what makes the brand “neuroeconomics” suitable in some circumstances, and undesirable in others? What are the reasons that make of neuroeconomics a brand to promote, or to keep invisible?

Program of the 2 symposia in decision-making (aka neuroeconomics):

• Symposium 1: Decision Making in Goal-Directed Behavior
• Symposium 2: Decisions and Emotions

(20-22 April 2009, Nijmegen, Netherlands)