[Kabar-indonesia] 2 of 2: New Yorker: Money On The Brain: What Neuroeconomics Tells Us

[Joyo at aol.com]

-2 of 2-

The New Yorker Magazine 
What neuroeconomics tells us about money and the
brain... continues...

Some neuroeconomic "findings" aren't exactly
discoveries, of course. In the fourth century B.C.,
Plato described reason as a charioteer attempting to
steer the twin horses of passion and spirit. More
recently, Freud wrote about the contest between the
ego and the id. "What is new," Jonathan Cohen wrote in
the fall, 2005, issue of the Journal of Economic
Perspectives, "is that researchers now have the tools
to begin to identify and characterize these systems at
the level of their physical implementation in the
human brain. Neuroscience gives detailed access to the
mechanisms that underlie behavior and thus may allow
scientists to answer questions that cannot be answered
easily, or at all, by observing behavior alone."

Many traditional economists are unimpressed by this
argument. In a recent paper, "The Case for Mindless
Economics," Faruk Gul and Wolfgang Pesendorfer, two
Princeton economists, wrote, "Neuroscience evidence
cannot refute economic models because the latter make
no assumptions and draw no conclusions about the
physiology of the brain." Gul and Pesendorfer have a
point: neuroeconomics doesn't tell us whether the
neo-Keynesian or the neoclassical model of inflation
is correct. But it can provide indirect evidence to
reinforce certain theories and discredit others. About
ten years ago, David Laibson published a paper on
"hyperbolic discounting," which suggested that people
treat immediate rewards differently from the way they
treat delayed rewards, preferring the former in a
manner that simple rational-choice models can't
explain. Now the results of the Amazon voucher
experiment have provided a possible explanation for
the behavior that Laibson identified: immediate and
delayed rewards stimulate different parts of the
brain. "The practical implications of the experiment
come from obtaining a better understanding of the
human taste for instant gratification," Laibson said.
"If we can understand that, we will be in a much
better position to design policies that mitigate what
can be self-defeating behavior."

The biggest challenge facing neuroeconomics comes not
from its opponents in the economics profession but
from its supposed allies in neuroscience. Many
neuroscientists now consider MRI data to be
uninformative. Neural activity occurs in milliseconds,
on a scale of perhaps 0.1 millimetres. A typical MRI
machine, which measures neural firing indirectly, by
tracking blood flow, takes a picture every couple of
seconds and isn't able to detect anything less than
three millimetres long. Because of these limitations,
neuroscientists prefer to track the firing of single
neurons by inserting tiny electrodes into the brain.
Unfortunately, this is an invasive procedure, and its
experimental use has generally been restricted to
laboratory animals.

There is also a more fundamental objection to
neuroeconomics and the Platonic view of
decision-making. "There is no evidence that hidden
inside the brain are two fully independent systems,
one rational and one irrational," Paul W. Glimcher, a
neuroscientist who is the director of N.Y.U.'s Center
for Neuroeconomics, and two of his colleagues, Michael
C. Dorris and Hannah M. Bayer, wrote in a recent
paper. "There is, for example, no evidence that there
is an emotional system, per se, and a rational system,
per se, for decision making at the neurobiological
level."

In place of the reason-versus-passion model, Glimcher
and his colleagues have adopted a view of
decision-making that, paradoxically, bears a striking
resemblance to orthodox economics. In one experiment,
Glimcher and a colleague trained thirsty monkeys to
direct their eyes to one of two illuminated targets,
which earned them differing chances of getting juice
rewards—a fifty-per-cent chance of getting a full cup
of juice for looking right, say, versus a
seventy-per-cent chance of getting half a cup of juice
for looking left. The game was repeated many times,
with the probabilities changing periodically.

The monkeys' task was to consume as much juice as
possible, and they proved very adept at it. Before
long, they were dividing their time between the
illuminated targets in a way that roughly maximized
their payoffs. When the odds favored looking right,
they looked right; when the odds favored looking left,
they looked left. Glimcher also used electrodes to
track neural firing in part of the posterior parietal
cortex, an area that is thought to organize signals
transmitted by the retina. He discovered that the
firing rate was closely related to the rewards the
monkeys were likely to receive. "Specifically," he and
his colleagues reported, "the firing rate of a neuron
associated with a leftward movement was a linear
function of the probability that the leftward movement
would yield the juice reward."

Clearly, monkeys can't do probability sums. (Many
humans struggle with them!) But Glimcher's experiment
implies that their brains act as if they were solving
a mathematical problem, which is what economists
assume when they depict people as rational agents
trying to maximize their well-being, or "utility."
"What seems to be emerging from these early studies is
a remarkably economic view of the primate brain,"
Glimcher and his colleagues wrote. "The final stages
of decision-making seem to reflect something very much
like a utility calculation."

If Glimcher's results could be demonstrated in human
brains, they might undermine a lot of neuroeconomics,
and many in the field tend to downplay his work.
"Well, monkeys are very interesting, but they are not
nearly as rich in their behavior as humans," George
Loewenstein said to me. "Humans have this very
well-developed prefrontal cortex, which allows us to
look ahead a number of stages, rather than just
behaving in a reflexive fashion. Still, it's wonderful
that we have these controversies. Most of us are
friends, and we debate these issues. I've learned a
lot from talking to Paul."

I was inside the MRI machine for nearly two hours, and
I answered more than two hundred and fifty questions,
which were organized into two blocks. Sokol-Hessner
had instructed me to answer the first set as if each
investment were the only one I would make. He told me
to treat the second set of gambles as a group, as if I
were constructing an investment portfolio. Later, he
explained that he wanted to compare my answers to the
two blocks of questions. Many people become less
loss-averse when they are constructing a portfolio of
investments, presumably because they believe that
losses in one part of their portfolio will be made up
for by gains in others. "Our research has shown that
people can alter their own choice behavior in a
systematic fashion," Sokol-Hessner said. "They can
make themselves less loss-averse. If loss aversion is
mediated by the limbic structures, such as the
amygdala, we would expect a big decrease in activity
in those areas when you become less loss-averse."

The goal of the imaging experiment was to test this
hypothesis. I was only the second person to take part
in the experiment, but Sokol-Hessner told me that I
was an atypical case. Rather than altering my
strategy, I answered all the questions in the same
way. Whenever the risk-free option was worth more than
about five dollars, I accepted it, thinking that I
would have been foolish to turn down a sure thing.
Occasionally, when the risk-free option was zero, or
close to zero, I gambled on the risky option. I'm not
sure why I acted in this way—it wasn't strictly
logical—but it made answering the questions easy, and
it seemed to pay off: by the end of the experiment, I
had won sixty-eight dollars.

My experience illustrated some of the drawbacks of
brain scanning. After about an hour inside the
machine, I was more concerned about getting out than I
was about making a few dollars. (Sokol-Hessner said
that I moved my head around so much that my brain
scans were unusable.) "That's the terrible thing about
MRIs," Sokol-Hessner conceded. "You are in a long
tube, and you might well feel tired or claustrophobic.
There's definitely other stuff going on in there
besides the experiment. We have to be very careful
about how we interpret the evidence."

Economists who have staked their careers on
neuroeconomics are mindful of this advice. "It isn't a
wholesale rejection of the traditional methodology,"
David Laibson said of his field. "It is just a
recognition that decision-making is not always
perfect. People try to do the best they can, but they
sometimes make mistakes. The idea that a single
mechanism maximizes welfare and always gets things
right—that concept is on the rocks. But models that I
call 'cousins' of the rational-actor model will
survive."

The modified theories to which Laibson referred assume
that people have two warring sides: the first
deliberative and forward-looking, the second impulsive
and myopic. Under certain circumstances, the impulsive
side prevails, and people succumb to things like drug
addiction, overeating, and taking wild gambles in the
stock market. For now, the new models await empirical
verification, but neuroeconomists are convinced that
they're onto something. "We are not going to falsify
all of traditional economics," Colin Camerer said.
"But we are going to point to a whole range of
biological variables that traditionally have not been
included in the analysis. In economics, that is a big
change." 
          
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