Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: BrainNet: A Multi-Person Brain-to-Brain Interface for Direct
  Collaboration Between Brains   We present BrainNet which, to our knowledge, is the first multi-person
non-invasive direct brain-to-brain interface for collaborative problem solving.
The interface combines electroencephalography (EEG) to record brain signals and
transcranial magnetic stimulation (TMS) to deliver information noninvasively to
the brain. The interface allows three human subjects to collaborate and solve a
task using direct brain-to-brain communication. Two of the three subjects are
"Senders" whose brain signals are decoded using real-time EEG data analysis to
extract decisions about whether to rotate a block in a Tetris-like game before
it is dropped to fill a line. The Senders' decisions are transmitted via the
Internet to the brain of a third subject, the "Receiver," who cannot see the
game screen. The decisions are delivered to the Receiver's brain via magnetic
stimulation of the occipital cortex. The Receiver integrates the information
received and makes a decision using an EEG interface about either turning the
block or keeping it in the same position. A second round of the game gives the
Senders one more chance to validate and provide feedback to the Receiver's
action. We evaluated the performance of BrainNet in terms of (1) Group-level
performance during the game; (2) True/False positive rates of subjects'
decisions; (3) Mutual information between subjects. Five groups of three
subjects successfully used BrainNet to perform the Tetris task, with an average
accuracy of 0.813. Furthermore, by varying the information reliability of the
Senders by artificially injecting noise into one Sender's signal, we found that
Receivers are able to learn which Sender is more reliable based solely on the
information transmitted to their brains. Our results raise the possibility of
future brain-to-brain interfaces that enable cooperative problem solving by
humans using a "social network" of connected brains.

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The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
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The categories of this paper are: nucl-ex
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The categories of this paper are: econ
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The categories of this paper are: chao-dyn
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The categories of this paper are: cond-mat
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The categories of this paper are: math-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: math
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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-th
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The categories of this paper are: q-fin
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The categories of this paper are: acc-phys
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The categories of this paper are: quant-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: comp-gas