The human brain is a masterful machine that makes decisions based on associations between stimuli in our environment. But did you know that these decisions can also be influenced by indirect associations between seemingly unrelated events? A recent study by the Cellular Mechanisms in Physiological and Pathological Behavior Research Group at the Hospital del Mar Research Institute has shed new light on this process, revealing how a specific scent can alter our mind’s decision-making processes.

The research team, led by PhD student José Antonio González Parra and supervised by Dr. Arnau Busquets, conducted experiments with mice to understand the mechanisms behind indirect associations between different stimuli. They trained the mice to associate two distinct smells – banana and almond – with sweet and salty tastes respectively. Later, a negative stimulus was linked to the smell of banana, causing the mice to reject the sweet taste associated with it.

The researchers used genetic techniques to observe which brain areas were activated throughout this process. They found that the amygdala, a region linked to responses such as fear and anxiety, played a crucial role in encoding and consolidating these associations. Other brain areas also interacted with the amygdala, forming a brain circuit that controls indirect associations between stimuli.

Dr. Busquets explained that if amygdala activity was inhibited while the mice were exposed to the stimuli, they were unable to form these indirect associations. This finding has significant implications for treating mental disorders linked to amygdala activity, such as PTSD and psychosis.

The researchers believe that the brain circuits involved in decision-making processes in humans are similar to those in mice. Therefore, understanding these complex cognitive processes can help us design therapeutic strategies for humans, including brain stimulation or modulation of activity in specific areas.

In conclusion, this study has revealed how a scent can change our mind’s decisions by altering indirect associations between stimuli. By exploring the neural mechanisms behind this process, we may be able to develop innovative treatments for mental disorders that affect millions of people worldwide.

The human brain is incredibly skilled at solving complicated problems. One reason for this is that humans can break down complex tasks into manageable subtasks that are easy to solve one at a time. This strategy helps us handle obstacles easily, as shown by the example of going out for coffee, where we can revise how we get out of the building without changing the other steps.

While there’s a great deal of behavioral evidence demonstrating humans’ skill at these complicated tasks, it’s been difficult to devise experimental scenarios that allow precise characterization of the computational strategies used to solve problems. A new study by MIT researchers has successfully modeled how people deploy different decision-making strategies to solve a complicated task – in this case, predicting how a ball will travel through a maze when the ball is hidden from view.

The human brain cannot perform this task perfectly because it’s impossible to track all possible trajectories in parallel, but the researchers found that people can perform reasonably well by flexibly adopting two strategies known as hierarchical reasoning and counterfactual reasoning. The researchers were also able to determine the circumstances under which people choose each of those strategies.

“Weak humans are capable of doing is breaking down the maze into subsections, and then solving each step using relatively simple algorithms,” says Mehrdad Jazayeri, a professor of brain and cognitive sciences at MIT. “When we don’t have the means to solve a complex problem, we manage by using simpler heuristics that get the job done.”

The researchers recruited about 150 human volunteers to participate in the study and evaluated how accurately they could estimate timespans of several hundred milliseconds. For each participant, the researchers created computational models that could predict the patterns of errors that would be seen for that participant if they were running parallel simulations, using hierarchical reasoning alone, counterfactual reasoning alone, or combinations of the two reasoning strategies.

The researchers compared the subjects’ performance with the models’ predictions and found that for every subject, their performance was most closely associated with a model that used hierarchical reasoning but sometimes switched to counterfactual reasoning. This suggests that instead of tracking all possible paths that the ball could take, people broke up the task into smaller subtasks, picked the direction in which they thought the ball turned at the first junction, and continued to track the ball as it headed for the next turn.

If the timing of the next sound they heard wasn’t compatible with the path they had chosen, they would go back and revise their first prediction – but only some of the time. Switching back to the other side represents a shift to counterfactual reasoning, which requires people to review their memory of the tones that they heard.

The researchers found that people decided whether to go back or not based on how good they believed their memory to be. “People rely on counterfactuals to the degree that it’s helpful,” Jazayeri says. “People who take a big performance loss when they do counterfactuals avoid doing them. But if you’re someone who’s really good at retrieving information from the recent past, you may go back to the other side.”

The research was funded by various organizations, including the Lisa K. Yang ICoN Fellowship, the Friends of the McGovern Institute Student Fellowship, and the National Science Foundation Graduate Research Fellowship.

By slightly varying the amount of memory impairment programmed into the models, the researchers also saw hints that the switching of strategies appears to happen gradually, rather than at a distinct cut-off point. They are now performing further studies to try to determine what is happening in the brain as these shifts in strategy occur.

The article “Brain Drain? More Like Brain Gain: How High-Skilled Emigration Boosts Global Prosperity” challenges the conventional wisdom about the impact of high-skilled emigration on developing countries. A recent study published in Science reveals that this phenomenon can actually boost economic development, human capital, and innovation in migrants’ countries of origin.

The researchers found that access to labor markets in developed countries like the United States encourages people in lower-income countries to invest in education and training. This creates downstream effects that strengthen both home and host countries. The study also discovered that high-skilled migrants often maintain professional ties across borders, facilitating trade, investment, and innovation.

The article highlights a global chain reaction triggered by expanded migration opportunities. When the U.S. increased nursing visa access for Filipinos, enrollment in nursing schools surged, creating nine new nurses in the Philippines for every one who migrated. Similar trends were observed in India, where increased access to H-1B visas led to increased earnings of Indians in the U.S. and raised IT employment in India.

The study’s authors argue that recent changes in U.S. immigration policy risk undercutting both U.S. innovation and global progress. They emphasize that earning a U.S. salary is incredibly lucrative, motivating many people to acquire skills even if they never leave. Some eventually return home and work in their local economy, while others send money back that helps educate children or launch businesses.

The researchers conclude that staying open to global talent strengthens both the U.S. economy and the broader world. They recommend revisiting immigration policies to ensure they promote shared prosperity across borders and encourage people from developing countries to invest in education and training.

In summary, the article suggests that high-skilled emigration can have a positive impact on global prosperity, economic development, and innovation. It highlights the importance of rethinking immigration policies to promote shared benefits for both host and home countries.