Understanding How the Brain Uses Different Reasoning Strategies for Complex Tasks

The human brain excels at solving intricate problems by breaking them into smaller, more manageable parts. This approach allows us to complete daily activities—like going for coffee—by dividing the process into steps: leaving the office, navigating to the café, and obtaining the drink. If an obstacle, such as a broken elevator, disrupts one step, we can adapt without overhauling the entire plan. Despite behavioral evidence of our skill in handling complex tasks, understanding the precise computational strategies our brain employs has been challenging.

Recent research by MIT scientists has provided valuable insights. They modeled how individuals deploy different decision-making strategies to solve a complex task: predicting the route of a hidden ball traveling through a maze. Since tracking all possible paths simultaneously is impossible for the brain, humans rely on flexible strategies called hierarchical and counterfactual reasoning. The study revealed how people select these strategies depending on the situation.

Professor Mehrdad Jazayeri of MIT explains that humans simplify complex problems by segmenting the maze into parts and solving each with straightforward algorithms. When a problem exceeds their mental capacity, people use heuristics—rules of thumb—that help approximate solutions.

The experiment involved a task where participants predicted the path of a ball in a maze with four possible routes. Hearing cues at two points in the maze, participants had to track the ball's movement without visual confirmation, mimicking real-world decision-making under uncertainty. The study included about 150 volunteers, with their performance modeled against computational predictions based on their timing abilities.

Findings indicated that individuals tend to favor hierarchical reasoning—breaking down the maze into parts—while occasionally switching to counterfactual reasoning, which involves recalling and imagining alternative scenarios. The choice to switch strategies depends on factors like memory reliability and the potential performance loss when using counterfactual reasoning.

The researchers extended their insights by training machine-learning neural networks on the same task. When these models faced simulated cognitive limitations similar to humans, they adopted human-like strategies, suggesting that humans operate rationally within their mental constraints.

Understanding these strategic shifts offers a deeper view of human cognition and could inform future research into brain function during problem-solving. The study underscores that our reasoning is adaptive and bounded by our cognitive resources, with strategy switching happening gradually rather than abruptly.

This research contributes significantly to cognitive science, highlighting the brain's ability to employ simplified heuristics and flexible reasoning tactics when tackling complex problems. Future studies aim to explore the neural mechanisms underlying these strategic shifts, advancing our knowledge of human decision-making processes.

For more details, see the full study in Nature Human Behaviour (June 2025).

Source: https://medicalxpress.com/news/2025-06-brain-deploys-strategies-tackle-mental.html