On the Same Wavelength: Neural "Fingerprints" Indicate Deep Focus Flow States in Teams

Have you ever been so laser focused on a task—playing a video game, reading an engrossing book, and so on—that when you look up, hours have suddenly gone by? This is commonly referred to as flow state: a state of absorbed concentration and a distorted sense of time. Studies have shown that working in the flow state has a positive impact on happiness and productivity.

A new Caltech-led study examines the phenomenon of "team flow," where individuals work in a flow state with others. Like a fingerprint, the electrical activity of the brain looks different from person to person, including during a flow state (team or solo). By measuring the brainwaves of volunteers as they played a collaborative video game, the researchers discovered that people whose neural patterns or "neural traits" looked similar were able to more easily achieve a team flow state together.

The research is described in a paper appearing in the journal Nature Scientific Reports.

The study was a collaboration between the Caltech laboratory of Shinsuke Shimojo, the Gertrude Baltimore Professor of Experimental Psychology, and the laboratory of Mohammad Shehata at Toyohashi University of Technology in Japan. Shehata is also a visiting associate in biology and biological engineering at Caltech.

"The concept of flow state is very grounded in positive psychology," Shehata says. "It's good for mental health and productivity without leading to burnout. Many people have experienced this 'vibe,' and now we are trying to characterize it with psychophysics and neuroscience."

The research built on a previous study that examined flow state when pairs of participants collaborated to play a video game. The game requires players to press keys with precise timing, as if playing a piece of music, similar to the popular game Guitar Hero. To measure team flow, the participants had to collaborate on the game, each responsible for playing some of the keys. The researchers measured the participants' brain activity using an electroencephalogram (EEG), a noninvasive method using electrodes applied to the head. While the participants were playing the game in a closed room, the researchers would knock on the door. A person in a real flow state would be able to ignore the distractions.

Then, each person's EEG readings for team, solo, and non-flow state were mapped onto a multidimensional space. The team found that the closer two participants' readings were in this space, the more likely they would enter into team flow when working together.

Importantly, a person's EEG reading is different depending on the task at hand. For example, while two participants may be neurally far apart when doing a rhythm game—that is, not in a team flow state—they may be able to flow together well during a different task, such as solving math problem or playing a sport.

"There are huge potential applications for this work," Shehata says. "It can be used to build highly compatible teams with great performance, for example, on long space missions."

Shimojo adds, "Our goal is to continue to work on understanding the neural signatures of the team flow state so that we can ultimately predict from brain activity profiling who would be likely to flow well together in a team."

The paper is titled "A hierarchical trait and state model for decoding dyadic social interactions." Caltech graduate student Qianying Wu is the first author. In addition to Wu, Shehata, and Shimojo, Shigeki Nakauchi of Toyohashi University of Technology is also a co-author. Funding for this research was provided by Japan Society for Promotion of Science and Japan Science and Technology Agency. Wu was also supported by the National Institutes for Mental Health Conte Center at Caltech, the Tianqiao and Chrissy Chen Institute for Neuroscience at Caltech, and the Simons Foundation Autism Research Initiative. Shimojo is an affiliated faculty member with the Tianqiao and Chrissy Chen Institute for Neuroscience at Caltech.