Official Braintech Q&A “Why Braintech?”

Brain technology, as a technology that can be safely and ethically accepted by society, can not only treat diseases, but can also help to eliminate inconveniences and enrich our daily lives. Brain tech applications should expand to all areas of society, thereby making a significant contribution to society.

It can be divided into two types of technology: one that uses electricity or magnetism to stimulate the brain, and the other that measures and visualizes brain activity. The principle of the former is similar to that of devices that electrically stimulate the abdominal muscles, and is characterized by the fact that it does not require the user’s volition. On the other hand, there is a risk of inducing epileptic seizures or burns due to brain stimulation. Since the latter is only an observation of brain activity, it is safer and more widely used than the former technology. On the other hand, there are some difficulties, such as the need to manipulate the visualized brain activity at one’s own will, and the strong electromagnetic noise in some operating environments prevents the product from performing its claimed functions.

There are many ways to get involved in Braintech, but the basics require knowledge of “brain” (neuroscience) and “technology” (engineering). There are universities, graduate schools, and research institutes where neuroscience can be studied, such as those listed in the references.
Reference：Places to study neuroscience (undergraduate/departmental/graduate/acceptable research institutions)

When working in medical schools, the main focus is on brain research, such as functional brain analysis, and clinical research and clinical trials of developed BMI devices, and evaluation of the devices on animals and humans. The actual application of BMI requires collaboration between the two.

If the emphasis is on exporting information, areas such as signal processing and machine learning are particularly important. In addition, the basics of neurophysiology should be kept in mind in order to understand the background of the biological information obtained. In addition, when implementing neurofeedback, BMI, etc., it is necessary to learn more extensive neuroscience knowledge, such as the mechanisms of human learning, depending on the respective control target.

BTC believes that support systems that require brain activity will be related to higher cognitive functions. For example, in the case of ALS patients who have completely lost their motor skills, technology that targets the brain as an alternative means of expressing intentions should be essential. On the other hand, prosthetic hands and feet do not necessarily need to be manipulated using brain activity; rather, prosthetic hands and feet that use electromyography from the remaining muscles would be safer and cheaper to use.

There are two types of brain intervention and manipulation methods: non-invasive and invasive.

Noninvasive techniques, such as EEG, optical topography, fMRI, and MEG, do not require special manipulation of the human body to measure brain function.

Invasive techniques require surgical procedures. When used on humans, not everyone can do it. Invasive manipulation of the brain always carries risks such as infection and bleeding, so it is necessary not only to establish a technique to do it safely, but also to provide users with benefits that outweigh the risks.

Magnetoencephalography (MEG) and Magnetic Resonance Imaging (MRI) are representative non-contact brain activity measurement techniques. Unlike electroencephalography (EEG), which measures electrical activity on the surface of the brain, MEG measures brain activity from the magnetic field, making it non-contact.

In recent years, some research teams have also studied “brain activity measurement by pupillary response” and “non-contact EEG measurement electrodes” (Park & Whang, 2018; Chi et al., 2011).

Reference：Infrared Camera-Based Non-contact Measurement of Brain Activity From Pupillary Rhythms

Dry and Noncontact EEG Sensors for Mobile Brain–Computer Interfaces

Based on many past studies, there is no doubt that there are gender differences in brain function and structure. However, there is no scientific basis at this time for such popular discourses as “women have better left-right brain coordination” or “men have a brain structure better suited for calculation. In this sense, we may answer that the gender difference in the brain is small compared to the world’s understanding.
Reference：Part 5: Why and how the “male brain” and “female brain” lies spread

For general analysis methods, you may want to refer to “Introduction to EEG Analysis”. For Matlab, you can use EEGLAB or Fieldtrip, and for Python, you can use Python MNE or brainflow, etc. You may also find tutorials and sample codes from these packages useful. For detailed analysis methods, you may want to refer to similar studies.
Reference：脳波解析入門 EEGLABとSPMを使いこなす

Compared to the more invasive cortical electroencephalography (ECoG), scalp electroencephalography (EEG) has lower spatial resolution, but is easier to measure. It mainly measures neural activity in the cerebral cortex, although the sensitivity and placement of the electrodes may vary, and spatial filters can be used to narrow down the area of interest.

The EEG mainly observes periodic neural activity called alpha (8-13 Hz) and beta (14-30 Hz) waves, and the amplitude modulation and waveform of such periodic activity can be used to detect arousal level, motor attempts, and conditions such as epileptic seizures. Other brain responses to internal and external stimuli are called event-related potentials (ERPs), which are used as a means of communicating willpower in amyotrophic lateral sclerosis (ALS) and other diseases.

In scalp EEG, which is recorded through tissues such as the scalp and skull, the EEG measured with a single electrode is a collection of a wide range of activity, and EEG is a measurement method with low spatial resolution. Therefore, increasing the number of electrodes spatially limits the accuracy.

Although EEG recording devices inevitably cannot completely eliminate artifacts and noise, if they are included and reproducible, there should be no problem for scientific and commercial use. The important thing is to include artifacts and noise and then utilize the parts that are reproducible.

Because of the functional localization of the brain, it is necessary to measure EEG from the scalp close to the brain region of interest in order to obtain the desired brain activity. However, since scalp EEG records potential changes as a collection of brain activity over a wide range, some allowance can be made for the location of electrodes, although individual differences may affect the results.

There have been a number of studies in which neurofeedback has been used to regulate neural activity limited to specific regions. A representative study was reported in 2016 that showed that it is possible to control activity in the ventral tegmental area, a small area less than a few millimeters in size that is part of the reward system (Maclnnes et al., 2016, Neuron). Furthermore, this study reported that activity in other regions functionally connected to the ventral tegmental area also rises and falls with training.

In invasive brain device implantation, the surgical robot being developed by Neuralink is touted to automate the implantation process. However, the invasive electrode implantation procedure requires many procedures, from skin incision to bone opening, dural incision, hemostatic operation, implantation, suturing of the incision, etc., and it is not clear whether all of these procedures can be automated. Automation is expected to continue, especially in areas such as high-precision implant manipulation, which is difficult for humans to perform.

Deep Brain Stimulation (DBS) is a typical “brain control technology” that is already being used overseas to treat obsessive-compulsive disorder and other disorders. At present, this type of surgical treatment for psychiatric disorders is not practiced in Japan due to ethical issues, but if its safety is sufficiently established overseas, there is a possibility that it may be introduced in Japan in the future. One technical challenge is that, at present, the system is not personalized for each patient. Recently, however, it was reported that stimulating the brain according to the neural activity of depressed patients improved their depressive symptoms (Scangos et al., Nature Medicine, 2021). It is highly likely that such custom-made techniques will advance in the future. Ethical considerations are essential, and I think it is necessary at the very least now to conduct sufficient studies and to have guidelines and other guidelines in place.

As for BMI, there is a study called closed loop BMI, in which brain activity in the motor cortex is measured and decoded for equipment operation, while sensory feedback is provided to the sensory cortex through electrical stimulation and other means. I think it is necessary to separate sensory and motor cortices. I think that most of the studies that measure both are conducted as basic brain research rather than BMI.

Even if only the brain moves, if the inputs and outputs to the brain are the same, there will not be much change, but if one of the inputs or outputs is impaired, there will be changes in the brain as well. There have been research reports that when the brain is not used due to immobility of the body, the brain area of that body part becomes narrower, and if rehabilitation or BMI allows connection to motor function, the related brain area will become wider.

In terms of treatment, there is currently no fundamental cure, but drugs to slow the progression of the disease, symptomatic treatment to control symptoms and anxiety, and rehabilitation to prevent muscle weakness. life-supportive technologies to improve QOL include interfaces that are appropriate to the level of progression, such as Devices to support communication and encourage social participation are being developed.
Reference：Amyotrophic Lateral Sclerosis Treatment Guidelines 2013｜Neurological Society of Japan Treatment Guidelines

There are a great many types of risks, including many minor ones, but many of those commonly cited in implantation surgery also apply to this BMI for implantation. The most important risk to consider is infection associated with the implantation. In particular, it is important to note that ALS patients have difficulty in communicating, making it difficult to confirm their complaints, which is different from healthy people.

Since the application of optogenetics requires genetic modification and physical implantation such as optical fibers and LEDs, it is unlikely to be applied to healthy individuals in the near future.

On the other hand, a study was published in 2021 that applied optogenetics to humans for the first time and restored vision to patients with retinitis pigmentosa (Sahel et al., 2021).

In the future, there may be no possibility that optogenetics will be applied to healthy people.
Reference：Partial recovery of visual function in a blind patient after optogenetic therapy

As an example, the technology to convert neural activity data of the brain into speech, language, video, and motor commands is called neural decoding. There are various types of neural decoding algorithms, but decoding using deep learning is expected to be one of the most versatile and accurate AI applications.

Consumer-use BrainTech devices currently available in Japan include simple electroencephalographs, which acquire electrical signals by placing electrodes on the forehead, and NIRS (Near Infrared Spectoroscopy) devices. Recently, a domestic manufacturer has developed an earphone-type electroencephalograph, and these devices are expected to become available in the future.

Routine brain activity measurements include earphones/headphones, simple electroencephalographs that acquire signals from the forehead, and NIRS (Near Infrared Spectoroscopy) devices. Many of these devices calculate and display the degree of concentration and relaxation based on brain activity. Brain stimulation methods include headphone-type and forehead-applied weak current stimulators that temporarily increase concentration.

It should be noted that although brain science has accumulated a vast amount of knowledge, there are still only a few applications using it. The reason for this is that brain tech, which manipulates and influences the brain, has always been integrated with ethical issues that question the meaning of human beings themselves. One of the difficulties of brain tech is that it must also answer the question of whether it is ethical to use the technology.

In the short term, the introduction of simple electroencephalographs, etc. can be considered. For example, in an educational setting, a simple electroencephalograph could be used to visualize the degree to which students are concentrating, and to determine what kind of classes help students maintain their concentration. In the workplace, mindfulness can be used to monitor the degree of relaxation using a simple electroencephalograph, which can be useful for stress management in the workplace.

Since neurofeedback facilitates change toward the desired brain state through operant conditioning, it is considered important to be able to visualize one’s brain state in real time and recognize whether one is changing toward the desired state.

One example is the report that neurofeedback training for children with ADHD can improve attention (Doren et al., Eur Child Adolesc Psychiatr 2019). This article is a report of a clinical study that aggregates 10 studies conducted through the scientifically rigorous procedure of randomized controlled trials, so there is some confidence in the evidence. However, it does not necessarily mean that the same effects can be obtained with different subjects. For example, a product that improves attention in children with ADHD may not be effective in improving concentration in healthy children or adults. Often, marketed products claim benefits in general terms (e.g., concentration, memory, etc.), but the reported benefits are often very limited.

Just as it is now common to use smartphones and wearable activity meters to measure daily biometric data (e.g., heart rate) for health management and other purposes, it is highly likely that brain activity measurement will become easier and more useful for health management and other lifestyle support purposes. In addition to brain activity measurement devices for medical and research purposes, consumer-use devices have begun to spread in recent years as a cheaper and easier way to measure brain activity. In addition to measurement devices, analysis technologies for extracting physiologically meaningful information from the obtained data and utilizing it are also developing day by day.

Recently, there are an increasing number of scalp electroencephalographs available on the market, and it is possible to conduct research in the field. However, due to recording accuracy issues, it is not easy to produce excellent research results with scalp EEG, regardless of whether the researcher is in the field or not.

Advances in both hardware and software will undoubtedly increase the quality of the neural activity that can be recorded. The future of medicine and health care is an area with tremendous potential. In addition, as the quality and quantity of the data we can obtain improves, we may find applications that are unimaginable at this point in time.

There is a JIS standard (JIS T 1203) for the signal quality of medical electroencephalographs (telemetry electroencephalographs), but there is no measurement standard for consumer devices as of October 2021. It would be safe to say that the product can be sold if it passes the EMC test, which indicates that it is not affected by electromagnetic waves. There is no standard that guarantees the correctness of the analysis part. Currently, the correctness of measurement and analysis can only be judged indirectly by the presence or absence of papers that report the results of clinical trials conducted on the device or service.

At present, implantable BMI is basically a technology for patients with disabilities, not for healthy individuals. Non-invasive BMI is currently being applied as part of self-management by visualizing brain activity, and its benefits are beginning to be verified.

As one of the applications of BMI, it is expected that the operation of communication devices and smartphones will be possible at the laboratory level in the next few to five years, and from there the application phase will continue to develop in stages for decades to come.

First of all, I think post-stroke sequelae can be mentioned; the number of patients is about 100 times larger than ALS, so the number of patients eligible for medical application of BMI will quickly increase.

In Japan, the Ushiba Laboratory of Keio University’s Faculty of Science and Technology is developing rehabilitation medical devices using brain-machine interface technology. Overseas, the application of neurofeedback to the rehabilitation field is being promoted by Neurolutions, a start-up company from Washington University in St. Louis, and NNRI, a California-based company.

The current reading type of BMI may be difficult to use in cases where the brain function itself is reduced, as in the case of people with dementia or intellectual disabilities. I think that the application to criminals may need to be fully discussed from an ethical rather than a technical standpoint. On the other hand, a stimulated BMI may make it possible to approach addiction to gambling, alcohol, etc.

In October 2021, closed-loop neurofeedback treatment for refractory depression was performed at the University of California, San Francisco, and the results were reported (Scangos et al., 2021, Nature Medicine), In October 2021, the University of California, San Francisco, reported that closed-loop neurofeedback treatment for refractory depression resulted in a significant improvement (Scangos et al., 2021, Nature Medicine). We expect to see more and more such studies in the future.

Mind uploading is the transfer of human consciousness to an external artificial device to achieve a state of being independent of the biological function of the brain. To achieve this, it is necessary to clarify various brain mechanisms that are currently unknown, and it is also necessary to create an artificial device that can implement these mechanisms, which is not possible with current technology.

If this were possible, the concept of the individual would disappear. In addition, as long as the artificial device continues to operate, death will never occur, which means that immortality can be realized. Like the term “singularity,” this is one of the technologies of the future that society believes has the potential to be realized in the future, but we do not know if it will really happen.

The short answer is that it is possible in principle, but difficult with current technology.

To realize a full dive, not only must it be possible to transmit one’s will directly to the BMI device, but sensory feedback from the BMI device must also be realized at the same time. If this can be realized, we will be able to do all kinds of things with a robot in the real world and live in virtual space as in reality.

Currently, reading intentions and sensory feedback are gradually becoming possible, but the amount of information is far from a full dive. It seems difficult to significantly increase the amount of information in this feedback loop by extending existing technology, but there is a possibility that some technological breakthrough could dramatically increase the amount of information. The emergence of completely new measurement principles and information transfer methods is awaited.

In C. elegans, the connectome has been completed, but a complete neural circuit model that reproduces the movement of the nematode has not been achieved. Some argue that even if a complete connectome can be reproduced, the brain cannot be fully reproduced. On the other hand, the connectome is considered very useful as a “tool” for generating hypotheses and constructing experiments, and it is becoming possible to partially reproduce brain functions. As a direction for industrial applications, for example, it may be possible to generate a large amount of pseudo brain activity data for preliminary validation of products and applications on a simulation basis before conducting clinical trials at great cost.

There are currently no clear regulations or rules for consumer EEG devices. Claims of effectiveness of the device must be made in accordance with the Law for Preventing Unjustifiable Premiums and Misleading Representations. If the device is also used for medical purposes, it must be approved as a medical device, and there is a standard (JIS T 1203) for electroencephalographs used for diagnosis. In many cases, consumer-use devices are wireless devices. In such cases, it is necessary to obtain a technical conformity mark that certifies that the device complies with the technical standards set forth in the Radio Law.

When managing biometric data in the cloud, in addition to basic management methods, special attention should be paid to the following two items. In addition to the basic management of biometric data, the following two items require special attention: secure management during communication (measures against eavesdropping, tampering, spoofing, etc.) and secure management of system security (prevention of unauthorized access, data integrity, etc.). Specific measures include “data anonymization, data encryption, selection of cloud providers with high security requirements, setting up authentication and authorization for systems, and implementation of human safety measures.

Since neural activity varies greatly from person to person, it is important to have a “family pharmacist” or “family pharmacy. In the future, the neural activity recording device (and the applications implemented in it) may play the role of a “family doctor” by accumulating a vast amount of data about the person.

Personal information is “information that identifies or can identify a living individual. The revised Personal Information Protection Law of 2009 indicates that personal identification codes also fall under the category of personal information. A personal identification code is a code converted from a feature of a part of the body for electronic computers (e.g., DNA, face, iris, etc.). Therefore, a brain image is a personal identification code and is a form of personal information. Even if the information is processed by Deface, it is still personal information, so it should be handled with care. In addition, the handling of personal information should be reexamined when the Personal Information Protection Law is revised.

I do not think that security is essential for all BMI, but there are some technologies that may be privacy sensitive. For example, technology that allows people to communicate simply by thinking, without words. If what we think is known as it is, it means that what we do not want others to know becomes known, and this requires sufficient ethical consideration and security thinking before practical application.