Archive · 26 Dec 2025
Brain Cues Influence Poor Decisions and Risky Behavior
Researchers at the University of Bologna found that some people make poor decisions because they are too focused on cues that signal rewards.
These people, called sign-trackers, are attracted to these cues and have a hard time changing their beliefs, even when the cues lead to bad outcomes.
On the other hand, goal-trackers ignore these cues and go straight for the reward, making better decisions.
The study used eye-tracking and other methods to show how these cues can act like magnets, pulling attention and making it harder to make good choices.
This research can help understand behaviors seen in addiction and compulsive disorders and may lead to new ways to reduce unhealthy behavior.
Researchers at the University of Bologna studied how brain cues influence poor decisions and risky behavior.
Sign-trackers are attracted to reward cues and have difficulty updating their beliefs, leading to poor decisions.
Goal-trackers ignore cues and adapt quickly, making better decisions and avoiding unhealthy behaviors.
The study used eye-tracking, pupillometry, and computational modeling to understand these processes.
The findings could help develop strategies to reduce unhealthy behavior, particularly in addiction and compulsive disorders.
- Who
- Researchers at the University of Bologna led by Giuseppe di Pellegrino
- What
- A study on how brain cues influence poor decisions and risky behavior
- When
- Not specified
- Where
- University of Bologna
- Why
- To understand why some people make consistently poor decisions and to develop strategies to reduce unhealthy behavior
- Researchers
- University of Bologna team led by Giuseppe di Pellegrino
- Study Focus
- Associative learning and maladaptive decision-making
- Decision-Makers Types
- Sign-trackers and goal-trackers
- Sign-Trackers
- Attracted to reward cues, slower to update beliefs
- Goal-Trackers
- Ignore cues, adapt quickly, avoid unhealthy behaviors
- Study Methods
- Eye-tracking, pupillometry, computational modeling
- Potential Applications
- Strategies to reduce unhealthy behavior