May 2021 | ISE Magazine 37

Brain-to-brain communication:

Science ﬁction becomes reality

ISEs’ involvement key to developing technology for workplace, medical uses

By Chang S. Nam, Zachary Traylor and Maria Mackie

38 ISE Magazine | www.iise.org/ISEmagazine

Brain-to-brain communication: Science fiction becomes reality

In the past several decades, the idea of interfacing the

human brain and a computer, once only imagined in

science ﬁction, has materialized via brain-computer

interface (Brain–Computer Interfaces Handbook: Techno-

logical and Theoretical Advances, Chang S. Nam, Anton

Nijholt and Fabien Lotte, 2018).

Always looking for new frontiers, researchers have begun

to turn their attention toward another audacious thought:

Directly extracting and delivering information between

brains, allowing direct brain-to-brain communication.

This new technology, collectively known as brain-to-brain

interface (B2BI), has made us rethink human communica-

tion. Figure 1 illustrates direct bidirectional B2BI commu-

nication system overview.

In general, B2BI combines a neuroimaging method, also

known as BCI, and a neurostimulation method, also known

as computer-brain interface (CBI), to exchange informa-

tion between brains directly in neural code. A BCI (e.g.,

EEG-based motor-imagery BCI) reads a sender’s brain ac-

tivity and then sends it to an interface, e.g., transcranial

magnetic stimulation (TMS) that writes the delivered brain

activity to a receiving brain.

Since its proof of concept by Miguel Pais-Vieira (“A

Brain-To-Brain Interface for Real-Time Sharing of Sen-

sorimotor Information,” Pais-Vieira, Mikhail Lebedev,

Carolina Kunicki, Jing Wang and Miguel A.L. Nicolelis,

2013), B2BI has been demonstrated in both animal models

(“Building an Organic Computing Device with Multiple

Interconnected Brains,” Miguel Pais-Vieira, Gabriela Chi-

uffa, Mikhail Lebedev and Miguel A.L. Nicolelis, 2013;

2015) and humans (“A Direct Brain-

to-Brain Interface in Humans,” Rajesh

P. N. Rao, Andrea Stocco, Matthew

Bryan, Devapratim Sarma, Tiffany M.

Youngquist, Joseph Wu and Chantel

S. Prat, 2014; “Conscious Brain-To-

Brain Communication in Humans Us-

ing Non-Invasive Technologies, Carles

Grau, Romuald Ginhoux, Alejandro

Riera, Thanh Lam Nguyen, Hubert

Chauvat, Michel Berg, Julià L. Amen-

gual, Alvaro Pascual-Leone and Giulio

Rufﬁni, 2014) where same or different

brain regions are invasively or nonin-

vasively recorded and stimulated in

many interesting applications, ranging

from simply transmitting binary infor-

mation (Grau et al., 2014) to creating

biological neural networks (Pais-Vieira

et al., 2015).

However, it is also true that B2BI is

still in its infancy and has a long way to

go before any mainstream adoption. In this article, we re-

view the state-of-the-art work, developments, limitations

and challenges in B2BI research, which is also conducted

in the Brain-Computer Interface and Neuroergonom-

ics Lab at North Carolina State University. In particular,

we point out that industrial and systems engineers need to

be involved in developing and investigating this emerg-

ing neural interfacing technology to make sure we fully

explore and correctly apply its potential (“Brain-to-Brain

Communication Based on Wireless Technologies: Actual

and Future Perspectives,” Dick Carrillo Melgarejo, Renan

Moioli and Pedro Nardelli, 2019).

B2BI, at its logical extremes, could help rehabilitate

stroke victims, enable mind-to-mind communication – a

precursor to what eventually could resemble telepathy –

and help people receive tasks best suited to their brain as

they collaborate with others. B2BI could be used for brain

rehabilitation of musculature control in stroke victims or

brain tumor patients.

People who have had strokes or brain tumors removed

often lose some cognitive ability, preventing their brain

from producing certain patterns. Sometimes this is minor,

like forgetting a word, but it can also cut out motor pat-

terns that the brain uses to walk or grip things. B2BI could

be used to help stimulate parts of the brain to send infor-

mation to a stroke patient, who would move an arm or

build strength in the neural pathways as they worked with

their B2BI partner (“Secure Brain-to-Brain Communica-

tion With Edge Computing for Assisting Post-Stroke Par-

alyzed Patients,” Sreeja Rajesh, Varghese Paul, Varun G.

FIGURE 1

A brain-to-brain link

An overview of a direct bidirectional B2BI communication system. An EEG-based motor

imagery BCI system is shown schematically (e.g., motor imagery of the hands codes the

bit value 0 and of the feet codes bit value of 1). A noninvasive neurostimulation technology,

also known as CBI (e.g., TMS), is illustrated, encoding the brain-driven information (e.g.,

the two bit values from the BCI). Communication between brains via the BCI and CBI

systems can be mediated by the internet.

May 2021 | ISE Magazine 39

Menon, Sunil Jacob and P. Vinod,

2020). This partner would send

signals that would help the patient

understand what moving a leg or

arm should feel like and look like in

the brain. Repeated use and neural

stimulation would help the patient

to relearn the motions he or she had

before the stroke. This opens up a

wide range of therapeutic options

for the technology.

There are many possible uses for

B2BI in the medical sector beyond

only beneﬁting research. Speciﬁ-

cally, it offers potential applications

in communication, speciﬁcally in

patients with neurological damage

(“Ethical Issues in Neuroprosthet-

ics,” Walter Glannon, 2016; “Brain-

to-Brain Interfaces: When Reality

Meets Science Fiction,” Nicolelis,

2014). Communication happens

most in spoken or written form,

which may not be possible or easy

to use for stroke patients or patients

of neurodegenerative diseases.

For example, people who have

neurodegenerative diseases slowly

lose the ability to talk and then ﬁnd it hard to type as the

disease progresses. B2BI would allow them to communi-

cate solely through the use of their brain, subverting any

physical disabilities. The person with whom they are com-

municating would receive signals from the sender using a

B2BI. The receiver or caretaker would not need to send any

information back through neural networks to the sender

since the caretaker can communicate by voice. This appli-

cation of B2BI would only need a few improvements, such

as making the technology more portable and speeding up

rates of transmission, to be possible in the near future.

A more general application for B2BI in the future is to

introduce new ways to deal with human factors engineer-

ing. B2BIs could be used for measuring fatigue, for tim-

ing breaks or for creating a more synchronous workforce.

There have already been tests conducted where partici-

pants doing a task are given harder or easier tasks based on

their cognitive states (“Increasing Human Performance by

Sharing Cognitive Load Using Brain-To-Brain Interface,

Vladimir A. Maksimenko, Alexander E. Hramov, Nikita

S. Frolov, Annika Lüttjohann, Vladimir O. Nedaivozov,

Vadim V. Grubov, Anastasia E. Runnova, Vladimir V. Ma-

karov, Jürgen Kurths and Alexander N. Pisarchik, 2018).

Electrical activity from two users’ brains as they performed

the task allowed a computer, through B2BI, to assign the

pair the task that would add the least fatigue to the group.

This cannot be done as effectively without a constant

monitoring system as the feedback from the brain gives

more direct feedback about the fatigue. The study included

a pair of operators in which the more skilled operator got

harder tasks and the less skilled operator got easier tasks.

This would allow better timing for breaks as individuals

would fatigue closer to the same rate. It would also allow

the computer to monitor their fatigue levels for speciﬁc

constrained tasks to ensure the best break times are identi-

ﬁed and used. This could drastically improve the amount

of time spent on breaks as they could be put in place when

needed by the most workers for the time they need to re-

cover or by allowing individualized breaks based on cogni-

tive stress.

While this differs from a typical transmission of infor-

mation from one brain to another, there is still a closed

feedback loop connecting multiple subjects’ BCIs, and thus

their brains. Other human optimization that could be done

with B2BI is in synchronizing workers in a group of con-

nected minds. In a factory where multiple people need to

perform the same task at the same time, a sort of hive mind

could allow them to act simultaneously even if they are out

N.C. State lab focused on brain interface,

communications

The Brain-Computer Interface and Neuroergonomics Lab at North Carolina State

University is involved in research concerning brain-computer interface (BCI), a

nonmuscular communication and control system that does not depend on the normal

pathways of peripheral nerves and muscles. BCIs allow users, including those with

severe motor disabilities such as amyotrophic lateral sclerosis (ALS, also known as Lou

Gehrig’s disease), to interact with the world through brain waves.

BCI has recently gained considerable research interest, especially in research involving

disabled persons, and many useful applications have been discovered.

The lab, directed by Chang S. Nam, is involved in research and development of

BCI that includes such projects as brain-computer interfaces, neuroergonomics,

neurorehabilitation, trust in human-robot interaction and human-computer interactions.

Learn more at ise.ncsu.edu/bci.

Chang S. Nam Zachary Traylor Maria Mackie

40 ISE Magazine | www.iise.org/ISEmagazine

Brain-to-brain communication: Science fiction becomes reality

of sight or hearing (Pais-Vieira, et al., 2015). This could

improve the efﬁciency and safety of many different opera-

tions where operators must work in tandem.

Currently B2BI is limited by clunky setups that make

true back-and-forth communication very odd to set up.

There are two different types of setups needed for each

person – one to send information and another to receive

it. However, these must each have a separate region of the

brain to work on because current technology cannot easily

read and write in the same area of the brain. The current

setups to read and write are too bulky and target too much

of the brain’s area to be able to easily set up both sending

and receiving headsets on the same person.

The other main limit is the lack of detail in sending

Forgot your password?

Brain-computer interface could help

Advances in brain-computer interfaces (BCI) in the workplace have led to discussions about the potential practical uses and the

ethical concerns of being able to measure workers’ thoughts. Yet in addition to other potential beneﬁts, the technology could help

many in their day-to-day activities.

One possible application would be assisting with lost or forgotten online passwords. Researchers are experimenting with use

of “passthoughts” as an alternative. The process would allow someone to log on to their devices and platforms by using thoughts

passed through an EEG connection placed in the ear canal like an earbud. Such signals would allow individuals to authenticate

their unique identities via brain waves.

A team of researchers the University of California at Berkeley, led by John Chuang, created such a device with a $100 consumer-

grade EEG headset, then ﬁtted it for the ear. They conducted a study with 12 volunteers performing a series of mental tasks and

found the device could verify their identities 72-80% of the time. Worn as designed on the forehead, the device was accurate

more than 99% of the time.

Chuang then sought to test the device when the wearer’s mental state changed due to mood, stress, fatigue or other factors that

might alter the brain’s electrical signals. He experimented with his teenage son and 10 volunteers and found that after one minute

of exercise, it took up to 60 seconds for brain signals to return to normal.

“Clearly a lot more work needs to be done for this to be effective and useful in the real world,” Chuang told IEEE Spectrum. “But

at least we know this is an area that we can continue to investigate.”

May 2021 | ISE Magazine 41

messages. Currently, participants in B2BI studies get bi-

nary signals sent to them, which they then interpret and to

which they react. For example, a ﬂash of light in a pattern

might mean to click a button and a “no” light means to

wait. If people use morse code or other binary communica-

tion, it can be used to have more complex conversations but

limits the accessibility to simple yes/no actions or similar

applications.

Breakthroughs will come when

the EEG headsets become easier to

wear; neurostimulation technology

advances – such as transductor ar-

rays for focused ultrasonics stimula-

tion (FUS) becoming more com-

mon, cheaper and easier to ﬁt into a

helmet; data transfer rates go up; or

when we can send and receive data

in the brain using one technology

(“Optimizing Computer–Brain In-

terface Parameters for Non-invasive

Brain-to-Brain Interface,” John

LaRocco and Dong-Guk Paeng, 2020). If the technology

can be wireless, it will become more practical for all the

ways discussed earlier (Melgarejo et al., 2019).

To overcome these limits, researchers need to create

partnerships with medical professionals and programmers

for both neurostimulation safety and artiﬁcial intelligence,

respectively, allowing engineers who understand these

systems to work closely with rehabilitation professionals

who may one day use B2BI in the ﬁeld. Future research

and funding may show us the beneﬁts of overcoming

B2BI’s challenges, such as transmitting abstract thought

or emotions, more adaptive two-way links between par-

ticipants and higher data transfer rates (LaRocco & Paeng,

2020; Melgarejo et al., 2019).

Industrial and systems engineers need to be involved in

developing and testing applications of this technology to

make sure we fully explore and correctly apply its poten-

tial (Melgarejo et al., 2019) for these reasons:

• ISEs will beneﬁt from being able to create an even more

efﬁcient and safe workforce with the new tools of behav-

ioral synchronization, communication and rehabilitation

through B2BI.

• ISEs can beneﬁt the ﬁeld of B2BI with their expertise in

design, manufacturing and supply chains as well as opti-

mization. ISEs can design and test slimmer, lighter and

more ergonomic EEG helmets and manufacturing ISEs

can be involved in making these improved helmets.

• ISEs can also be involved in improving the data commu-

nication side of B2BI. When data is collected, it is im-

portant to optimize methods for feature extraction and

classiﬁcation and to assess human performance with the

B2BI.

All of the above are reasons that the ﬁeld of B2BI would

welcome ISEs’ involvement. However, the beneﬁt to hav-

ing ISEs design and test current brain to brain interfaces is

that the future technology will better ﬁt the needs of their

ﬁeld to improve productivity and

satisfaction in the workforce they

support. Industrial and systems en-

gineers who get involved now will

inform the direction that B2BI and

BCI go as the ﬁeld develops.

The study of direct brain-to-

brain interface is slowly fulﬁlling its

potential to make waves in medical

treatment, factory optimization and

ISE as a whole. With the involve-

ment of industrial and systems en-

gineers, we will fully explore and

apply this amazing potential and

overcome the current limitations of the technology. As

B2BI emerges, we need engineers to get involved; the more

that research progresses, the sooner the technology can be

used in supporting the rehabilitation of stroke victims, in

analyzing and optimizing this new way of communicating

and in helping to optimize task assignment based on cogni-

tive states. 

Chang S. Nam is a professor at Edward P. Fitts Industrial and Sys-

tems Engineering, North Carolina State University. He is also an

associated professor of the UNC/NCSU Joint Department of Bio-

medical Engineering, Psychology and UNC-CH Brain Research

Imaging Center. His research interests center around brain-computer

interfaces, social cognitive and affective neuroscience, human-robot

interaction and human-centered explainable artiﬁcial intelligence.

He serves as editor-in-chief of the journal Brain-Computer Inter-

faces. He is an IISE member. Contact him at csnam@ncsu.edu.

Zachary Traylor has a bachelor’s degree in psychology from Loui-

siana State University and a Ph.D. in industrial and systems en-

gineering at North Carolina State University’s Brain-Computer

Interface and Neuroergonomics Lab. He now works on advanc-

ing brain-computer interface applications and developing direct

brain-to-brain interfaces. He is an IISE member. Contact him at

zatraylo@ncsu.edu.

Maria Mackie is pursuing an undergraduate degree in industrial

and systems engineering from North Carolina State University.

She was part of a robotics team in high school and currently men-

tors a middle school FIRST Tech Challenge (FTC) robotics team.

Contact her at mhmackie@ncsu.edu.

Industrial and systems

engineers need to be

involved in developing and

testing applications of this

technology to make sure we

fully explore and correctly

apply its potential.