Our decisions are shaped by optimistic and pessimistic neurons

Imagine navigating the intricate pathways of your mind, deciphering the signals that shape your decisions. Whether it’s choosing where to eat or making a life-changing move, your brain is constantly balancing risk and reward.

The complex puzzle of how the brain navigates these choices continues to inspire extensive research and remarkable discoveries.

Navigating reward-based decisions

Recently, a team of researchers from Harvard Medical School made a compelling discovery. The study connected machine-learning concepts to mouse experiments to explore deeper into the brain circuitry that governs reward-based decisions.

The experts identified two distinct groups of neurons in the brains of mice. One group aids in learning about outcomes that are above-average, while another associates with below-average results.

Together, these neurons grant the brain the capacity to assess the entire spectrum of potential rewards linked with a decision.

Jan Drugowitsch is the co-senior author of the study and an associate professor of neurobiology at the Blavatnik Institute at Harvard Medical School.

“Our results suggest that mice – and by extension, other mammals – seem to be representing more fine-grained details about risk and reward than we thought before,” explained Professor Drugowitsch.

A new approach to risk and reward

Neuroscience has long explored how past experiences influence future decisions. Yet, as Professor Drugowitsch pointed out, traditional theories often fall short in capturing the intricate patterns and subtle complexities of real-world behavior.

For instance, choosing between familiar good food at a known restaurant or testing a new place with a mix of good and not-so-good dishes is a choice that goes beyond mere averages. Existing theories fail to account for such risk-seeking or safe-playing behavior.

A new theory of decision-making borne out of machine learning research has begun to address these gaps. The new algorithm learns from the entire distribution of outcomes rather than just focusing on averages.

This approach significantly enhances performance, as observed in Atari video games and several other tasks involving multiple potential outcomes for each decision.

“They basically asked what happens if rather than just learning average rewards for certain actions, the algorithm learns the whole distribution, and they found it improved performance significantly,” explained Professor Drugowitsch.

Decisions and potential rewards

In the latest study, Drugowitsch collaborated with Naoshige Uchida, a professor of molecular and cellular biology at Harvard University. The goal was to gain a better understanding of how the potential risks and rewards of a decision are weighed in the brain.

The experts devised experiments with mice to unravel how the decision-making process unfolds within the ventral striatum – a region of the brain that stores data about potential rewards linked with a decision.

“We used high-density probes (neuropixels) to record striatal activity from mice performing a classical conditioning task in which reward mean, reward variance and stimulus identity were independently manipulated,” explained the researchers.

The team trained mice to associate different odors with varying extents of rewards, effectively teaching mice about the range of potential outcomes for each decision.

The researchers then observed the mice’s licking behavior (an indication of their anticipation for better rewards) alongside recordings of neural activity in the ventral striatum.

The neurons that make decisions

The results were remarkable. The experts identified two distinct groups of neurons that were guiding decisions made by the mice.

When the researchers silenced “optimistic” neurons, mice acted as if they anticipated lesser rewards. Conversely, when “pessimistic” neurons were silenced, the mice behaved as if they expected a more valuable treat.

Professor Drugowitsch compared this to “having an optimist and a pessimist in your brain, both giving you advice on what to do next.“

Continuing the exploration of these intriguing findings will provide insights into how the brain makes decisions in situations of greater uncertainty.

“These two groups of brain cells work together to form a representation of the full distribution of potential rewards for a decision,” explained Drugowitsch.

He believes that these insights could help us understand why people with conditions like depression or addiction struggle with assessing risks in decisions.

The full study was published in the journal Nature.

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