Nav: Home

How we make complex decisions

May 16, 2019

CAMBRIDGE, MA -- When making a complex decision, we often break the problem down into a series of smaller decisions. For example, when deciding how to treat a patient, a doctor may go through a hierarchy of steps -- choosing a diagnostic test, interpreting the results, and then prescribing a medication.

Making hierarchical decisions is straightforward when the sequence of choices leads to the desired outcome. But when the result is unfavorable, it can be tough to decipher what went wrong. For example, if a patient doesn't improve after treatment, there are many possible reasons why: Maybe the diagnostic test is accurate only 75 percent of the time, or perhaps the medication only works for 50 percent of the patients. To decide what do to next, the doctor must take these probabilities into account.

In a new study, MIT neuroscientists explored how the brain reasons about probable causes of failure after a hierarchy of decisions. They discovered that the brain performs two computations using a distributed network of areas in the frontal cortex. First, the brain computes confidence over the outcome of each decision to figure out the most likely cause of a failure, and second, when it is not easy to discern the cause, the brain makes additional attempts to gain more confidence.

"Creating a hierarchy in one's mind and navigating that hierarchy while reasoning about outcomes is one of the exciting frontiers of cognitive neuroscience," says Mehrdad Jazayeri, the Robert A. Swanson Career Development Professor of Life Sciences, a member of MIT's McGovern Institute for Brain Research, and the senior author of the study.

MIT graduate student Morteza Sarafyzad is the lead author of the paper, which appears in Science on May 16.

Hierarchical reasoning

Previous studies of decision-making in animal models have focused on relatively simple tasks. One line of research has focused on how the brain makes rapid decisions by evaluating momentary evidence. For example, a large body of work has characterized the neural substrates and mechanisms that allow animals to categorize unreliable stimuli on a trial-by-trial basis. Other research has focused on how the brain chooses among multiple options by relying on previous outcomes across multiple trials.

"These have been very fruitful lines of work," Jazayeri says. "However, they really are the tip of the iceberg of what humans do when they make decisions. As soon as you put yourself in any real decision-making situation, be it choosing a partner, choosing a car, deciding whether to take this drug or not, these become really complicated decisions. Oftentimes there are many factors that influence the decision, and those factors can operate at different timescales."

The MIT team devised a behavioral task that allowed them to study how the brain processes information at multiple timescales to make decisions. The basic design was that animals would make one of two eye movements depending on whether the time interval between two flashes of light was shorter or longer than 850 milliseconds.

A twist required the animals to solve the task through hierarchical reasoning: The rule that determined which of the two eye movements had to be made switched covertly after 10 to 28 trials. Therefore, to receive reward, the animals had to choose the correct rule, and then make the correct eye movement depending on the rule and interval. However, because the animals were not instructed about the rule switches, they could not straightforwardly determine whether an error was caused because they chose the wrong rule or because they misjudged the interval.

The researchers used this experimental design to probe the computational principles and neural mechanisms that support hierarchical reasoning. Theory and behavioral experiments in humans suggest that reasoning about the potential causes of errors depends in large part on the brain's ability to measure the degree of confidence in each step of the process. "One of the things that is thought to be critical for hierarchical reasoning is to have some level of confidence about how likely it is that different nodes [of a hierarchy] could have led to the negative outcome," Jazayeri says.

The researchers were able to study the effect of confidence by adjusting the difficulty of the task. In some trials, the interval between the two flashes was much shorter or longer than 850 milliseconds. These trials were relatively easy and afforded a high degree of confidence. In other trials, the animals were less confident in their judgments because the interval was closer to the boundary and difficult to discriminate.

As they had hypothesized, the researchers found that the animals' behavior was influenced by their confidence in their performance. When the interval was easy to judge, the animals were much quicker to switch to the other rule when they found out they were wrong. When the interval was harder to judge, the animals were less confident in their performance and applied the same rule a few more times before switching.

"They know that they're not confident, and they know that if they're not confident, it's not necessarily the case that the rule has changed. They know they might have made a mistake [in their interval judgment]," Jazayeri says.

Decision-making circuit

By recording neural activity in the frontal cortex just after each trial was finished, the researchers were able to identify two regions that are key to hierarchical decision-making. They found that both of these regions, known as the anterior cingulate cortex (ACC) and dorsomedial frontal cortex (DMFC), became active after the animals were informed about an incorrect response. When the researchers analyzed the neural activity in relation to the animals' behavior, it became clear that neurons in both areas signaled the animals' belief about a possible rule switch. Notably, the activity related to animals' belief was "louder" when animals made a mistake after an easy trial, and after consecutive mistakes.

The researchers also found that while these areas showed similar patterns of activity, it was activity in the ACC in particular that predicted when the animal would switch rules, suggesting that ACC plays a central role in switching decision strategies. Indeed, the researchers found that direct manipulation of neural activity in ACC was sufficient to interfere with the animals' rational behavior.

"There exists a distributed circuit in the frontal cortex involving these two areas, and they seem to be hierarchically organized, just like the task would demand," Jazayeri says.
-end-


Massachusetts Institute of Technology

Related Brain Articles:

Human brain size gene triggers bigger brain in monkeys
Dresden and Japanese researchers show that a human-specific gene causes a larger neocortex in the common marmoset, a non-human primate.
Unique insight into development of the human brain: Model of the early embryonic brain
Stem cell researchers from the University of Copenhagen have designed a model of an early embryonic brain.
An optical brain-to-brain interface supports information exchange for locomotion control
Chinese researchers established an optical BtBI that supports rapid information transmission for precise locomotion control, thus providing a proof-of-principle demonstration of fast BtBI for real-time behavioral control.
Transplanting human nerve cells into a mouse brain reveals how they wire into brain circuits
A team of researchers led by Pierre Vanderhaeghen and Vincent Bonin (VIB-KU Leuven, Université libre de Bruxelles and NERF) showed how human nerve cells can develop at their own pace, and form highly precise connections with the surrounding mouse brain cells.
Brain scans reveal how the human brain compensates when one hemisphere is removed
Researchers studying six adults who had one of their brain hemispheres removed during childhood to reduce epileptic seizures found that the remaining half of the brain formed unusually strong connections between different functional brain networks, which potentially help the body to function as if the brain were intact.
Alcohol byproduct contributes to brain chemistry changes in specific brain regions
Study of mouse models provides clear implications for new targets to treat alcohol use disorder and fetal alcohol syndrome.
Scientists predict the areas of the brain to stimulate transitions between different brain states
Using a computer model of the brain, Gustavo Deco, director of the Center for Brain and Cognition, and Josephine Cruzat, a member of his team, together with a group of international collaborators, have developed an innovative method published in Proceedings of the National Academy of Sciences on Sept.
BRAIN Initiative tool may transform how scientists study brain structure and function
Researchers have developed a high-tech support system that can keep a large mammalian brain from rapidly decomposing in the hours after death, enabling study of certain molecular and cellular functions.
Wiring diagram of the brain provides a clearer picture of brain scan data
In a study published today in the journal BRAIN, neuroscientists led by Michael D.
Blue Brain Project releases first-ever digital 3D brain cell atlas
The Blue Brain Cell Atlas is like ''going from hand-drawn maps to Google Earth'' -- providing previously unavailable information on major cell types, numbers and positions in all 737 brain regions.
More Brain News and Brain Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Debbie Millman: Designing Our Lives
From prehistoric cave art to today's social media feeds, to design is to be human. This hour, designer Debbie Millman guides us through a world made and remade–and helps us design our own paths.
Now Playing: Science for the People

#574 State of the Heart
This week we focus on heart disease, heart failure, what blood pressure is and why it's bad when it's high. Host Rachelle Saunders talks with physician, clinical researcher, and writer Haider Warraich about his book "State of the Heart: Exploring the History, Science, and Future of Cardiac Disease" and the ails of our hearts.
Now Playing: Radiolab

Insomnia Line
Coronasomnia is a not-so-surprising side-effect of the global pandemic. More and more of us are having trouble falling asleep. We wanted to find a way to get inside that nighttime world, to see why people are awake and what they are thinking about. So what'd Radiolab decide to do?  Open up the phone lines and talk to you. We created an insomnia hotline and on this week's experimental episode, we stayed up all night, taking hundreds of calls, spilling secrets, and at long last, watching the sunrise peek through.   This episode was produced by Lulu Miller with Rachael Cusick, Tracie Hunte, Tobin Low, Sarah Qari, Molly Webster, Pat Walters, Shima Oliaee, and Jonny Moens. Want more Radiolab in your life? Sign up for our newsletter! We share our latest favorites: articles, tv shows, funny Youtube videos, chocolate chip cookie recipes, and more. Support Radiolab by becoming a member today at Radiolab.org/donate.