The Neuroscience Behind Bad Decisions

From Quanta Magazine:

Humans often make bad decisions. If you like Snickers more than Milky Way, it seems obvious which candy bar you’d pick, given a choice of the two. Traditional economic models follow this logical intuition, suggesting that people assign a value to each choice — say, Snickers: 10, Milky Way: 5 — and select the top scorer. But our decision-making system is subject to glitches.

In one recent experiment, Paul Glimcher, a neuroscientist at New York University, and collaborators asked people to choose among a variety of candy bars, including their favorite — say, a Snickers. If offered a Snickers, a Milky Way and an Almond Joy, participants would always choose the Snickers. But if they were offered 20 candy bars, including a Snickers, the choice became less clear. They would sometimes pick something other than the Snickers, even though it was still their favorite. When Glimcher would remove all the choices except the Snickers and the selected candy, participants would wonder why they hadn’t chosen their favorite.

Economists have spent more than 50 years cataloging irrational choices like these. Nobel Prizes have been earned; millions of copies of Freakonomics have been sold. But economists still aren’t sure why they happen. “There had been a real cottage industry in how to explain them and lots of attempts to make them go away,” said Eric Johnson, a psychologist and co-director of the Center for Decision Sciences at Columbia University. But none of the half-dozen or so explanations are clear winners, he said.

In the last 15 to 20 years, neuroscientists have begun to peer directly into the brain in search of answers. “Knowing something about how information is represented in the brain and the computational principles of the brain helps you understand why people make decisions how they do,” said Angela Yu, a theoretical neuroscientist at the University of California, San Diego.

Glimcher is using both the brain and behavior to try to explain our irrationality. He has combined results from studies like the candy bar experiment with neuroscience data — measurements of electrical activity in the brains of animals as they make decisions — to develop a theory of how we make decisions and why that can lead to mistakes.

Glimcher has been one of the driving forces in the still young field of neuroeconomics. His theory merges far-reaching research in brain activity, neuronal networks, fMRI and human behavior. “He’s famous for arguing that neuroscience and economics should be brought together,” said Nathaniel Daw, a neuroscientist at Princeton University. One of Glimcher’s most important contributions, Daw said, has been figuring out how to quantify abstract notions such as value and study them in the lab.

In a new working paper, Glimcher and his co-authors — Kenway Louie, also of NYU, and Ryan Webb of the University of Toronto — argue that their neuroscience-based model outperforms standard economic theory at explaining how people behave when faced with lots of choices. “The neural model, described in biology and tested in neurons, works well to describe something economists couldn’t explain,” Glimcher said.

At the core of the model lies the brain’s insatiable appetite. The brain is the most metabolically expensive tissue in the body. It consumes 20 percent of our energy despite taking up only 2 to 3 percent of our mass. Because neurons are so energy-hungry, the brain is a battleground where precision and efficiency are opponents. Glimcher argues that the costs of boosting our decision-making precision outweigh the benefits. Thus we’re left to be confounded by the choices of the modern American cereal aisle.

Glimcher’s proposal has attracted interest from both economists and neuroscientists, but not everyone is sold. “I think it’s exciting but at this point remains a hypothesis,” said Camillo Padoa-Schioppa, a neuroscientist at Washington University in St. Louis. Neuroeconomics is still a young field; scientists don’t even agree on what part of the brain makes decisions, let alone how.

So far, Glimcher has shown that his theory works under specific conditions, like those of the candy bar experiment. He aims to expand that range, searching for other Freakonomics-esque mistakes and using them to test his model. “We are aiming for a grand unified theory of choice,” he said.

. . . .

The brain is a power-hungry organ; neurons are constantly sending each other information in the form of electrical pulses, known as spikes or action potentials. Just as with an electrical burst, prepping and firing these signals take a lot of energy.

In the 1960s, scientists proposed that the brain dealt with this challenge by encoding information as efficiently as possible, a model called the efficient coding hypothesis. It predicts that neurons will encode data using the fewest possible spikes, just as communication networks strive to transmit information in the fewest bits.

In the late 1990s and early 2000s, scientists showed that this principle is indeed at work in the visual system. The brain efficiently encodes the visual world by ignoring predictable information and focusing on the surprising stuff. If one part of a wall is yellow, chances are the rest is also yellow, and neurons can gloss over the details of that section. But a giant red splotch on the wall is unexpected, and neurons will pay special attention to it.

Glimcher proposes that the brain’s decision-making machinery works the same way. Imagine a simple decision-making scenario: a monkey choosing between two cups of juice. For simplicity’s sake, assume the monkey’s brain represents each choice with a single neuron. The more attractive the choice is, the faster the neuron fires. The monkey then compares neuron-firing rates to make his selection.

The first thing the experimenter does is present the monkey with an easy choice: a teaspoon of yummy juice versus an entire jug. The teaspoon neuron might fire one spike per second while the jug neuron fires 100 spikes per second. In that case, it’s easy to tell the difference between the two options; one neuron sounds like a ticking clock, the other the beating wings of a dragonfly.

The situation gets muddled when the monkey is then offered the choice between a full jug of juice and one that’s nearly full. A neuron might represent that newest offer with 80 spikes per second. It’s much more challenging for the monkey to distinguish between a neuron firing 80 spikes per second and 100 spikes per second. That’s like telling the difference between the dragonfly’s flutter and the hum of a locust.

Glimcher proposes that the brain avoids this problem by recalibrating the scale to best represent the new choice. The neuron representing the almost-full jug — now the worst of the two choices — scales down to a much lower firing rate. Once again it’s easy for the monkey to differentiate between the two choices.

Link to the rest at Quanta Magazine

PG recognized that this article is a bit dated, but he found the topic fascinating. Humanoid robots making complex decisions seem to be a bit more difficult than he would have thought.

5 thoughts on “The Neuroscience Behind Bad Decisions”

  1. People keep trying to force the human mind into the mold of a very complex computer. This just does not work.

    For the example: Presented with those three candy bars, I would pick the Milky Way myself. However, if presented with twenty different ones, it is quite likely that a few of them are ones that I have never tried before – so I’ll pick one of those.

    The other confounding factor with this experiment is that the candy bars are free. People are far more likely to try something new when there is no cost involved if a “bad” choice is made. This is why at CostCo, from where I just returned a while ago, you can hardly get anywhere without a sampler of something or other being offered to you (at least on weekends). That is how, the last time, I started picking up a shelf stable chocolate milk – I wasn’t about to pay $12.99 for a case of the stuff and have the family detest it.

    (This is also why Kindle Unlimited works so well – there is very little cost in trying out an author new to you, as opposed to paying even $3.99 to find out whether you like them or not.)

    • Or $12.99.
      Or even more on print.
      Now that there are cheaper options, discovery of new authors is a lot cheaper. Expecially in genres favored by Indies.

      Cheap discovery is part of the reason why the BAEN monthly bundles are so successful: they’re a mix of established top sellers and newer authors. Who evolve into established authors over time.

      The permafree model evolved to offer a road to building a fanbase and KU exists to monetize discovery and displace permafree.

      Discovery is essential to all authors but usually it *costs* money instead of generating revenue.
      There’s a reason KU is so successful.

  2. Economists have spent more than 50 years cataloging irrational choices like these.

    And for all that time Econ 101 has taught that relative values on an indifference curve change as more goods become available. (Shoes appear on multiple curves.)

    These are not irrational choices. We might just ask why the initial value of 10 assigned to a snickers changed. And don’t worry about the robot. He will pick the Snickers over and over. After gorging on a hundred Snickers, he will immediately pick another because Snickers has a value of 10.

  3. This became real to me after medical issues (all fine now). I expected the predicted “brain fog” during chemo, and I got it. After chemo it persisted for a long time, and I was told “oh, that’s normal”.

    Not until several months later did we figure out that no one (the result of siloed medical experts) had taken into account that the simple basic blood-sugar-reduction medication (for type 2 diabetes) which had not been discontinued during the process was the actual culprit — I’d lost so much weight during chemo, I didn’t need artificial glucose reductions via meds any more. Stop the drug, gain 40 IQ points instantly (or so it seemed).

    This made the whole brain-runs-on-sugar trope very vivid for me. And once you experience the differences and get sensitized to it, it’s hard to un-see it. If I look for it, I can now feel the impact of sugar on my thinking, and when the brain’s not getting enough, I can tell. It’s like sunlight on a plant — don’t get enough, you want to curl up and sleep.

  4. This is an odd experiment; it’s not clear why picking something other than Snickers is a “bad choice” or an “irrational choice.” If you offer me twenty options, why wouldn’t I go with a novelty, or something in a flavor I like but a brand I’ve never seen before?

    I would have thought the experiment would involve something like the marshmallow scenario with the kids who could either eat the marshmallow now, or later when they would be given a second marshmallow if they waited. The kids who ate the marshmallow (or maybe it was candy?) now were initially thought to be irrational.

    Then it turned out the kids were crazy like a fox, because they grew up in homes where waiting until later was the irrational choice, since the candy might not be available later. Or they wouldn’t get the promised extra piece, because circumstances had changed and their mom or dad couldn’t make good on the promise. Humans come with a lot of baggage. What’s bad or maladaptive in one situation becomes the key to survival in another.

    This Snickers experiment just doesn’t do it for me; at least come up with an objectively irrational alternative. Something like, “participants are trying to slim down to fit into particular clothing for a particular occasion. However, they keep selecting the Black Forest cake instead of an apple for dessert. What’s up with that?”


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