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BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains.

Linxing Jiang1, Andrea Stocco2,3,4,5, Darby M Losey6,7

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BrainNet is the first non-invasive brain-to-brain interface enabling three people to solve problems collaboratively. This brain-computer interface uses electroencephalography (EEG) and transcranial magnetic stimulation (TMS) for direct brain communication.

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Area of Science:

  • Neuroscience
  • Brain-computer interfaces
  • Human-computer interaction

Background:

  • Direct brain-to-brain communication is an emerging field.
  • Previous interfaces have limitations in non-invasiveness and collaborative tasks.

Purpose of the Study:

  • To introduce BrainNet, the first multi-person non-invasive direct brain-to-brain interface.
  • To enable collaborative problem-solving through direct brain communication.
  • To investigate how individuals integrate information from multiple noisy brain signals.

Main Methods:

  • Utilized electroencephalography (EEG) to record brain signals.
  • Employed transcranial magnetic stimulation (TMS) for non-invasive information delivery.
  • Developed a real-time EEG data analysis pipeline for decision decoding.
  • Designed a collaborative Tetris-like game for task execution.

Main Results:

  • Achieved an average accuracy of 81.25% in collaborative task performance across five groups.
  • Demonstrated that receivers learn to trust more reliable senders based on direct brain signals.
  • Quantified group-level performance, decision accuracy, and inter-subject mutual information.

Conclusions:

  • BrainNet successfully facilitates collaborative problem-solving via direct brain-to-brain communication.
  • The findings suggest future brain-to-brain interfaces can form "social networks" of connected brains.
  • This technology opens new avenues for human cooperation and information integration.