"Through the development of the mathematics necessary to understand the facts of neural physiology and the electro-chemistry of the nervous system, which themselves had to be, had to be, traced down to nuclear forces, it first became possible to truly develop psychology. And through the generalization of psychological knowledge from the individual to the group, sociology was also mathematicized." Isaac Asimov, Second Foundation, pg 84
The above quote is taken from the third book in famed science fiction writer Isaac Asimov's Foundation trilogy (later expanded to an immense and all encompassing series until you eventually discover that all of human history for 20,000 years was controlled by a former detective humanoid robot obeying his own special interpretation of Asimov's Laws of Robots, the Zeroth Law. Let's stay on track and only worry about the original trilogy). In it, in one succinct paragraph, is the entire aim of neuroeconomics.
Recently, I attended the Society for Neuroscience's 2011 conference. It is the largest conference dedicated to Neuroscience in the world. Some 31,000+ attended from around the world to present and discuss the most recent findings and the frontiers of neuroscience. The Keynote speech and panel of the event was the Yale economist Robert Shiller's attempt to bridge the gap between neuroscience and economics, followed by a panel discussion involving him, the Caltech neuroeconomist Antonio Rangel (probably the best in the field, or, as my professor described him, "your intellectual daddy"), SfN president Susan Amara, and esteemed Cambridge neuroscientist Wolfram Schultz.
Fortunately, it was forgettable and thousands walked out during the talk. I say fortunately, because it was an absolute disaster and the neuroscientists who remained must have only been further convinced that at best, economists were shoddy scientists, and at worse, idiots and charlatans. The best part of it, in my opinion, was Rangel desperately trying to explain how an economy, made of millions and billions of people each making independent decisions, was orders of magnitude more complex than the human brain and that analyzing human behavior on such large scales was extraordinarily more difficult than it might at first appear. All that the neuroscientists heard was that economists can't do controlled experiments, which, while true, was not the intended take away.
This is immensely unfortunate, because it was a wasted opportunity to make a couple good points. The first good point to be made is the one Isaac Asimov made 60 years ago in the above quote. Once we are able to understand human behavior on a neuroscientific level, we can make models about how individuals make decisions and choices. Once that is done, we can argue against the Von Neumann Morgernstern Utility Theory, the basic underlying theory of all of economics, and replace its axioms with models on human behavior.
These are the four VNM axioms:
Axiom 1 (Completeness)
For any two choices (A and B), either A is preferred to B, B is preferred to A, or there is equal preference.
Axiom 2 (Transitivity)
For any three choices (A, B, and C), if A is preferred to B, and B is preferred to C, A is preferred to C.
Axiom 3 (Continuity)
For any three choices (A, B, and C), where A > B > C and there exists probability p (where p is between 0 and 1), then pC + (1-p)A = B.
Axiom 4 (Independence)
For any three choices (A, B, and C), if A > B, then for any C and p (where p is between 0 and 1),
pA + (1-p)C > pB + (1-p)C.
Now, the trouble is that human behavior has and does violate these axioms. A replacement with models that do work (and there are several outlined in a paper entitled "Does the brain calculate value?" written by Vlaev et al, a copy of which I have on my computer but no link to online) can fundamentally alter several economics models and practically everything on risk aversion.
That list bit is critical. The question can be raised, even if these axioms are violated by individuals, might they not hold across aggregated decisions made by large numbers of people? If so, do we really need to worry about retooling economic models?
The answer is no. Small things, like how individuals consider risk, do not get smoothed over across the aggregate. Instead, risk preferences are constantly shifted by the context in which they're made. This is an oversimplification, but the general result is that where you would usually expect a sort of average risk to be taken by a large group of people, the amount of risk people are willing to take on escalates as they view others taking on increasing amounts of risk. A very small change in the way people think thus has huge macro implications. Models would then need to be altered.
The second good point that should have been made, that could have been made, is what economics bring to neuroscience. It brings a mathematical rigor found outside few disciplines besides higher math, physics, and computer science. It brings a host of statistical and surveying techniques designed for examining hundreds of interlocking, interdependent variables. Finally, it brings a certain humbleness to our model making. Our models will never be perfectly accurate, precise, or computationally efficient, and often times we will find ourselves having to sacrifice one of those virtues for another.
"[A model] is neither complete or correct. Instead, it is merely the best that could be done at the time. Over a dozen generation of men have poured over these equations, worked at them, taken them apart to the last decimal place, and put them together again. They've done more than that. They've watched nearly four hundred years past and against the predictions and equations, they've checked reality, and they have learned." Isaac Asimov, Second Foundation, pg 86
These two quotes outline the two fundamental foundations, the twin axioms, of neuroeconomics. The first, that there is a continuity from physics to economics, and the precision in the latter depends on understanding of the former and all the intervening steps. The second, that are models are always to be improved upon, to be experimented on, and to be tested time and time again.
