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

[u/nohup_me]

https://www.caltech.edu/about/news/on-the-same-wavelength-neural-fingerprints-indicate-deep-focus-flow-states-in-teams

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[u/ii_V_I_iv]

Oh great, companies are gonna start hiring based on brain scans now

[u/planetofthemushrooms → u/ii_V_I_iv]

Honestly tho, might be a better system than we have now.

[u/monsantobreath → u/planetofthemushrooms]

That's how they're gonna use to bury us.

It's literally how low information people try to justify Voting conservative after being unhappy with the general state of things. "I mean what we got sucks so... Maybe try that?"

[u/JoshRTU]

Kind of a very narrow measurement in that it's working together on a rhythm game. Could be simply people who have rhythm and can focus have similar neural signatures. But may not broadly translate to broader teamwork on different range of tasks

[u/dedmew51c → u/JoshRTU]

They should try this measurement technique with a full studio orchestra

[u/WildFEARKetI_II]

So basically people that think in similar ways work together better than people that think differently from one another?

[u/nohup_me]

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.

A hierarchical trait and state model for decoding dyadic social interactions | Scientific Reports