How to Make Decisions Under Uncertainty 

This piece, by Onno Berkan, was published on 10/29/24. The original text was published by Nature Neuroscience on 09/05/2007.

This study by Behrens et al. (Oxford) investigated how humans learn from past experiences to make better decisions in changing environments. The research challenges previous beliefs that voluntary decision-making is purely unpredictable, showing instead that our brains actively track and respond to environmental patterns.

The researchers conducted two main experiments where participants played a choice game between blue and green rectangles. This setup was similar to flipping a weighted coin, where only one color could be correct in each trial.

A key finding was that humans naturally adjust their learning rates– how much weight they give to new information– based on how volatile or stable their environment is. When conditions were rapidly changing, participants relied more heavily on recent outcomes, but in stable conditions, they considered longer historical patterns.

Using fMRI brain scanning, the researchers identified the anterior cingulate cortex (ACC) as the key brain region responsible for this adaptive learning. The ACC showed two distinct functional areas: the caudal region activated during decision-making, connecting with motor areas, while the rostral region activated during outcome monitoring, linking with reward-processing areas.

Interestingly, the strength of ACC activity predicted how well participants adjusted their learning rates. This suggests that the ACC acts as a sophisticated monitoring system that helps us determine how much weight to give to new experiences.

The findings have potential implications for understanding psychiatric conditions like obsessive-compulsive disorder, where patients might incorrectly weigh the importance of different information. This research provides valuable insights into how our brains help us make optimal decisions in an uncertain world.

If this research interests you, check out Dr. Payam Piray’s work! He extends Behrens’s research to discern two different types of uncertainty: stochasticity and volatility to create a fascinating model of decision making.

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