A recent study from researchers at the University of Michigan suggests that the behaviors of the brain and stock markets during times of crisis are governed by similar principles, drawing on concepts from physics. This research was published in the journal Proceedings of the National Academy of Sciences.
Led by Dr. UnCheol Lee from the Department of Anesthesiology, the team began their investigation after observing varying recovery times among patients under anesthesia. Dr. Lee noted, “Anesthetic drugs can be considered as introducing a controlled crisis in the brain, interrupting the brain”s network to induce unconsciousness.” This led him to ponder if the brain”s recovery from anesthesia shares similarities with a country”s recovery from an economic downturn, such as a stock market crash.
Despite their apparent differences, both the brain and financial markets are intricate systems that operate under a delicate balance termed criticality. At this state, they are most effective and adaptable. When this balance is disrupted, both systems can rapidly enter a crisis phase, losing their advantageous properties. In physics, these shifts are classified as phase transitions, which can occur suddenly or gradually.
The researchers discovered that both first-order and second-order transitions are evident in the brain during the process of anesthesia and in financial markets during economic collapses. They developed a computational model to determine whether specific networks were classified as first-order or second-order transitions at their breaking points. Networks exhibiting first-order transitions, characterized by their explosive nature and vulnerability to disturbances, were found to be more prone to rapid collapse and slower recovery post-crisis.
Dr. Lee elaborated on their methodology, stating, “With the model, we moderated the phase transition type and generated time series data, analyzed the data, and tried to identify signal characteristics of first- and second-order transitions. We found that a network of a first-order transition exhibits larger variance of network synchronizations.”
By applying their model to the financial sector, the researchers examined the 2007-2009 Subprime Mortgage Crisis and EEG recordings from patients undergoing anesthesia. They observed that stock markets closer to a first-order transition experienced quicker declines and slower recoveries. Countries with a higher likelihood of first-order transitions often corresponded with emerging markets that had lower gross domestic product per capita.
In analyzing EEG data from anesthesia patients, the team found a correlation between the brain”s proximity to first-order transitions and the speed of loss and recovery of consciousness. This predictive capability about network collapse could have significant implications, including enhancing anesthesia safety tailored to individual brain characteristics and devising strategies to better manage transitions in financial markets or even climate change.
Dr. George Mashour, a senior author of the study and founder of the U-M Center for Consciousness, praised Dr. Lee”s innovative work, stating, “Leveraging network science to understand the common dynamics of the brain and other complex systems has been a longstanding goal of our Center.”
The findings reveal not only the interconnectedness of seemingly disparate systems but also the potential for applying these insights across various fields, including healthcare and economics.
