Release date: 2017-06-27
If what technology is closest to science fiction today, it must be a brain-computer interface.
Brain-computer interface research has achieved conscious typing (average input of 39 letters in 1 minute), and also achieves mind control, such as human control of mouse behavior, allowing it to complete complex tasks. It also realized part of the upload of consciousness, and even made people doubt whether the will is free.
The future is even expected to achieve partial loss of perception and then gain, such as vision; it can also transform non-human perception into human perception, which is actually very anti-sky, such as the ability to perceive ultrasound (like getting from bats) This ability is the same), such as sensing the magnetic field, etc., just like having super power!
As a new way of control and communication, the brain-computer interface can also be applied to the broader field of brain-computer fusion. It is the so-called fusion of silicon-based organisms and carbon-based organisms to create a super-human, and let the brain further extend naturally.
The development of brain-computer interface has put forward new requirements for the fields of brain electricity, brain cognition, brain rehabilitation, signal processing, pattern recognition, chip technology, computing technology, etc., and people will greatly deepen the structure and function of the brain. Awareness.
With the continuous improvement of technology and the efforts of multidisciplinary integration, the brain-computer interface will gradually be applied to reality for the benefit of mankind.
Silicon Valley Live (service number: guigumitanv) combined with Harvard University Brain Science Center scientists and industry experts and scholars to jointly create the first long-term analysis of brain-computer interface industry in China and the United States, deep deconstructing the technical route of brain-computer interface field, depicting the commercialization trend of brain-computer interface And the subject map, foresight has never been seen before.
Brain machine interface definition
First of all, what is the brain machine interface?
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Brain-Computer Interface (BCI): It is a direct connection between human or animal brain (or culture of brain cells) and external devices.
In this definition,
"Brain" means the brain or nervous system of organic life forms, not just "mind" (abstract mind).
"Machine" means any device that is processed or calculated in the form of a simple circuit to a silicon chip to an external device and a Wheelchair.
"Interface" = "Intermediary for information exchange".
The definition of "brain machine interface" = "brain" + machine "+" interface".
That is, a connection path for information exchange created between a human or animal brain (or a culture of brain cells) and an external device.
The brain-computer interface is a multi-disciplinary field, and the core disciplines include cognitive science, neuroengineering, and neuroscience.
Brain-computer interface technology knowledge: implementation steps and analysis
The basic implementation steps of the brain-computer interface can be divided into four steps: acquisition signal >> information decoding processing >> re-encoding >> feedback.
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1. Information collection
The division of the brain-computer interface is generally based on the information collection method, and is usually divided into invasive, semi-invasive, and non-invasive (out-of-brain).
Invasive: This type of brain-computer interface is usually implanted directly into the gray matter of the brain, so the quality of the acquired neural signals is relatively high. However, its shortcomings are easy to trigger immune response and callus (ç–¤), which leads to the decline or even disappearance of signal quality.
The invasive acquired signal is a direct neural signal.
Partially invasive: the interface is usually implanted into the cranial cavity, but outside the gray matter, its spatial resolution is not as good as the invasive brain-computer interface, but better than non-invasive. Another advantage is the small chance of eliciting an immune response and callus, primarily based on cortical electroencephalography (ECoG) for information analysis.
Non-invasive: It does not enter the brain and is easy to wear on the human body like a hat. However, due to the attenuation of the signal on the skull and the dispersion and blurring effect on the electromagnetic waves emitted by the neurons, the resolution of the recorded signal is not high and it is difficult to determine. The discharge of the signaled brain region or associated individual neurons.
A typical system has an electroencephalogram (EGG), which is one of the main information analysis techniques for potential non-invasive brain-computer interfaces. This is mainly due to the good time resolution, ease of use, and portability of the technology. And relatively low prices.
(EEG equipment picture source: )
However, one problem with EEG technology is its sensitivity to noise; another practical obstacle to using EEG as a brain-computer interface is that the user has to do a lot of training before working.
2. Information analysis
Once enough information has been collected, the signal is decoded and re-encoded to handle the interference. There are many interferences in the process of collecting EEG signals, such as power frequency interference, eye movement artifacts, and other electromagnetic interferences in the environment.
The analysis model is the key to the information decoding process. According to different acquisition methods, there are generally EEG, cortical electroencephalography (ECoG) and other models to assist analysis.
Signal processing, analysis and feature extraction methods include denoising filtering, P300 signal analysis, wavelet analysis + singular value decomposition.
3. Recoding
Encoding the analyzed information, how to encode depends on what you want to do. For example, if the control robot picks up the coffee cup to drink coffee for itself, it needs to encode the motion signal of the robot arm, and accurately control the movement trajectory and power control of the object in the complex three-dimensional environment is very complicated.
But the coding format can also be varied, which is why the brain-computer interface can be combined with almost any engineering science. The most complex situations include output to other organisms, such as mice, to control how they behave.
4. Feedback
It is also very complicated to get environmental feedback and then act on the brain. Humans perceive the environment through perception and transmit it to the brain for feedback. Perception includes vision, touch, and hearing.
This step of the brain-computer interface is very complicated, and mixed analysis including multi-modality is also difficult, because the process of feedback to the brain may not be compatible.
Important milestones in brain-computer interface history
In 1924, German psychiatrist Hans Berger discovered EEG.
In 1969, the University of Washington School of Medicine used monkeys to conduct EEG biofeedback studies.
In the 1990s, after Nicolelis completed a preliminary study of brainwaves in rats, an experiment was performed in the monkey to extract signals from cortical motor neurons to control the robotic arm.
In 1999, Harvard University's Garrett Stanley attempted to reconstruct neuronal discharge information from the lateral thalamus of the cat to reconstruct visual images.
After 2000, the Donoghue team implemented the rhesus monkey's motion control of the cursor on the computer screen to track visual targets, where the monkeys did not need to move their limbs.
The Theodore Berger team at the University of Southern California in 2009 developed a neural chip that mimics the function of the hippocampus. The team's nerve chip was implanted into the rat brain, making it the first advanced brain function prosthesis.
The 2012 World Cup in Brazil - the machine armor, the amputation disabled in the armor of the machine, with a brain interface and mechanical exoskeleton opened a ball.
In 2014, researchers at the University of Washington conducted direct brain-to-brain communication by transmitting EEG signals over the network.
In December 2016, Bin He and his team at the University of Minnesota in the United States made a major breakthrough, allowing ordinary people to control objects in complex three-dimensional space with only “ideas†without implanting brain electrodes. This includes manipulating the robotic arm to grab, place objects, and control aircraft flight. The research results are expected to help millions of people with disabilities and neurological diseases.
(Bin He and his team's experimental results)
In February 2017, Krisna Shenoyy, a professor of electrical engineering at Stanford University, and Jaimie Henderson, a professor of neurosurgery, published a paper announcing their success in allowing three test subjects to accurately control the cursor of a computer screen with simple imagination. The three paralyzed patients succeeded in imagining the computer. Enter what they want to say on the screen, and one of the patients can enter an average of 39 letters in 1 minute.
Brain-computer interface challenge
Moore's Law of the Brain Machine Interface:
According to the above chart, an average of 7.4 years can be used to calculate the speed of doubling the number of simultaneously recorded neurons. To record 1 million neurons at the same time, it is necessary to record 2100 years, and all neurons in the human brain should be recorded (50~ 10 billion), you have to wait until 2225.
Therefore, how the brain-computer interface solves the bandwidth problem has become a key point in academic research breakthroughs. Neuralink, founded by Elon Musk, is working to accelerate this puzzle.
The brain-computer interface is also a complex interdisciplinary subject. There are two challenges in this interdisciplinary field. One is the engineering challenge and the other is the theoretical challenge.
Theoretical research is trying to solve one or both of these two problems:
1) How to get the right information from the brain?
2) How do I send the right information to the brain?
The first is "from the brain to the machine", capturing the output of the brain - recording what the neurons say.
The second is “from machine to brainâ€, entering information into the brain or otherwise altering the natural flow of the brain – this is stimulating neurons.
At present, there have been some research results from "brain to machine". From "machine to brain", there is almost no clue. Basically, it can be said that it is only black and light.
What does “from the machine to the brain†mean? That is, the perception is reversely encoded into a signal that can be read by the brain. For example, whether you can touch the cat's touch or your imaginary record and reproduce it to you through the machine, it is also a good understanding to help the blind person rebuild the vision.
The brain-to-brain study is much slower than the brain, because the current neuroscience specific method of neural coding is still unknown. The need for machine-to-brain knowledge of neural coding is much greater than from brain to machine. The study of neuroscience in single neurons is gradually becoming clear, but the various magical aspects of the brain cannot be explained at all.
Moreover, the engineering difficulty lies in: a large number of disciplines such as mechanical dynamics, machine learning, neuroscience, cognitive science, information engineering, etc. involved in the brain-computer interface industry, which requires a large number of talents in various industries, and cannot have shortcomings.
In addition, engineering difficulties include cost control and the ability to reduce costs through commercial processes.
Brain machine interface commercialization direction
medical health:
The medical direction is mainly divided into two directions, namely “enhancement†and “recoveryâ€, both of which have extremely ambitious “money scenesâ€, especially the direction of reinforcement. At this stage, the recovery class is the main one because it is easier to implement.
The “enhanced†direction mainly refers to the implantation of chips into the brain to enhance memory and promote the direct connection between the human brain and computing devices. This is called "Human Intelligence (HI)." The shallow level of research is one-way brainstorming, and the deeper level will be two-way. At present, the “strengthening†direction includes Neuralink founded by Musk and Kernel, which has invested 100 million U.S. dollars.
The “recovery†direction mainly refers to the corresponding recovery training for diseases such as ADHD, stroke, and epilepsy. The main method adopted is neurofeedback training. This direction has been widely used in some hospitals, clinics, and rehabilitation centers around the world, and many startups are doing wearable devices in this area.
The reason for the lack of "enhancement" is that the first is because the implementation is difficult; the second is because the market has not been fully educated, the thinking paradigm is difficult to change in the short term, and the willingness to pay has not reached the critical value due to insufficient technical ability, but the military field In fact, there have been a lot of applications, and the military has invested a lot of money.
Finally, it is worth adding that "health direction", that is, meditation decompression, there are startups to launch brainwave detection headband to help users enhance meditation effects through real-time audio feedback. In fact, in North America, the market for meditation is very large, and this is a market segment that can definitely be tapped.
VR direction:
At present, the interactive experience of VR/AR needs to be improved. The current solution is to recognize by voice recognition and gestures. However, if you use the brain-computer interface, you can use the idea to control the menu navigation and option control of the VR interface, which greatly enhances. Use experience. At present, the company that is ahead of this is MindMaze, whose total financing has exceeded 100 million US dollars.
Education Technology:
This direction is actually somewhat close to the "recovery" direction in the medical direction. Education technology is a billion-dollar market. At present, Boston startup BrainCo is doing this direction, mainly to detect the students' attention value in real time, so as to help teachers understand the classroom situation and change teaching methods. Market development in this area is currently mainly at the B end.
Smart home :
Smart home is a big imagination space for brain-computer interface and IoT (Internet of Things). In this field, the brain-computer interface plays a role similar to the “remote controlâ€, which helps people to control the switch lights, switch doors, switch curtains, etc., and further control the home service robot.
Global brain-computer interface market size
The brain-computer interface is a new way of input and output, and its application will span several industry fields. The brain-computer interface operating system is also likely to become another large human-computer interaction system after Windows (computer operating system representative), iOS (mobile phone operating system representative), and Alexa (voice operating system representative).
Narrow market size: From the perspective of brain-computer interface equipment (EEG/EMG), the market size will reach 2.5 billion dollars in 5 years.
Market size in a broad sense: From the perspective of several technological fields where the brain-computer interface will be deeply affected, the market size will reach hundreds of billions of dollars in five years, including: ADHD brain-computer interface feedback therapy of 46 billion US dollars, brain detection system 12 billion The US dollar, education technology is 250 billion US dollars, and the game industry is 120 billion US dollars. (The data comes from the third party based on the market size in the past two years and thus the calculation in 5 years)
Imagine that in the future, using the brain-computer interface technology to play "Glory of the King" will be like the idea control plot in "Avatar"?
Factors affecting the commercialization of brain-computer interface
(Source: Allied Market Research)
According to Allied Market Research, in 2014, the biggest factor affecting the development of brain-computer interfaces was the lack of professional knowledge and ethical issues. They also speculate that by 2020, people will be more receptive to this technology, and ethical issues will be reduced, but this will be the danger of conscious information leakage and brain hacking caused by cybersecurity threats. From the point of view of the medical and health industry, as the cure of human terminal illness is realized one by one, neurological diseases will become the biggest problem in the future medical industry, and the incidence of brain disorders has an increasing trend. In addition, government funding, miniaturization of components, and expansion of the game industry will also move in a positive direction.
Investment analysis of brain-computer interface
What happens to the brain-computer interface of private capital:
In 2001, John Donoghue and Brown University research organization jointly established Cyberkinetics to develop brain-interface implantable system BrainGate.
In 2009, the research center of Honda Investment in Japan displayed the results of the brain-computer interface project and opened the door for brain-computer interface from scientific research projects to marketization.
In 2016, Braintree founder Bryan Johnson personally invested $100 million to establish Kernel, a brain-computer interface company, and is currently working on brain-computer interface products that improve human memory.
At the end of 2017, Chen Tianqiao, the chairman of Shanda Group, and his wife donated $150 million to the California Institute of Technology to set up a brain science research center.
In March 2017, Elon Musk announced the investment in the establishment of brain-interface company Neuallink.
In April 2017, Facebook announced the “Imagination Typing†project. Zuckerberg invested a lot of capital and talent to build a brain-computer interface technology team.
Government investment, the “brain plan†of governments:
United States: In 1989, it pioneered a national brain science program and named the last 10 years of this century "the 10 years of the brain." In April 2013, the White House proposed a “brain plan†that is considered to be comparable to the Human Genome Project. It aims to explore the working mechanisms of the human brain, map the whole brain activity, promote neuroscience research, and develop new brain diseases that are currently incurable. therapy. The US government announced that the US BRAIN Initiative has more than $100 million in start-up funds and has been adjusted to plan to invest $4.5 billion over the next 12 years.
EU: In 1991, Europe introduced the "European Brain 10 Years" program. In January 2013, the European Commission announced that Human Brain Engineering was selected as “Future Emerging Flagship Technology Project†and established a special research and development program “Human Brain Program (HBP)â€, which will receive 1 billion Euros in the next 10 years (2013 to 2023). Funding. The project brings together more than 400 researchers from different fields.
Japan: In 1996, Japan established a 20-year "Era of Brain Science" program, with an annual investment of 100 billion yen and a total investment of 2 trillion yen. In September 2014, the Ministry of Science and Technology of Japan also announced the chief scientist and organizational model of its “brain planâ€. Japan's "brain plan" focuses on the medical field, mainly using the simian brain as a model to accelerate research on human brain diseases such as senile dementia and schizophrenia. The Japanese government’s budget for the “brain plan†in 2015 was about 6.4 billion yen (about 63.75 million US dollars).
China: "Brain Science and Brain-like Research" has been included in the national major scientific and technological innovation and engineering projects in the "13th Five-Year Plan". At the beginning of this year, the Chinese Academy of Sciences established the Center for Excellence in Brain Science and Intelligent Technology, which includes 80 elite laboratories in 20 institutions. For the "Chinese Brain Project", scientists in various fields have proposed the layout of "one body and two wings": that is, to study the neural principle of brain cognition as the "subject", to develop new methods for the diagnosis and treatment of major brain diseases and the new technology of brain intelligence as "two wings" ". The goal is to achieve international leading results in the forefront of brain science, early diagnosis and intervention of brain diseases, and brain-like intelligent devices in the next 15 years. After a rough estimate, China’s main investment in this area has increased from about 348 million in 2010 to nearly 500 million yuan per year in 2013.
Brain machine interface industry distribution
The world's top 10 most concerned brain-computer interface companies
(names not listed in order)
According to the five dimensions of company technology, team/partnership, development plan, product and financing, the world's top ten most concerned brain-computer interface companies were selected.
Among them, Neuralink and Kernel focus on brain science applications and aim at the direction of human intelligence (HI). The two, together with BrainGate, which focuses on medical health, use invasive technology for EEG signal acquisition, and the remaining seven use non-invasive technology.
Among the non-invasive 7 companies, g·tec and BrainMaster focus on the development of high-precision EEG measurement equipment for clinical and scientific research.
The remaining five in non-invasive models are more oriented towards consumer-grade brain-computer interface products. Among them, NeuroSky, InteraXon (Muse) and Emotiv are mainly engaged in mobile wearable EEG equipment for meditation, games and other needs, these companies often have supporting APP and SDK for users and developers. In Switzerland, MindMaze is committed to combining VR/AR and brain-computer interface into two areas of medical health and games. The Boston-based BrainCo is the first to cut into the field of education, but also involved in the medical and gaming fields.
Among the top 10 most concerned brain-computer interface companies, 7 are from the United States, and the other 3 are from Switzerland, Canada, and Austria. The financing situation and profile are shown in the following figure:
(names not listed in order)
Brain-computer interface scientific research force distribution
According to the output and influence of research results in the field of brain-computer interface in the world's major research institutes, we have selected these 20 research institutes for your reference:
Of course, in addition to these 20 research institutes, there are also mysterious research groups such as DARPA of the US Defense Advanced Research Projects Agency and Building 8 of Facebook, which are engaged in research on brain-computer interfaces.
Brain machine interface subject map
Finally, how can people get started quickly for those who don't want to miss another big enthusiasm after artificial intelligence? Here, we depict the subject map of the brain-computer interface. In this typical interdisciplinary field, science students, engineering students, medical students, and liberal arts students will find their entry points.
Future vision of brain-computer interface
At present, mainstream consumer brain-computer interface research mainly uses non-invasive EEG technology. Although relatively invasive technology is easy to implement, the cost is still high. However, with the influx of talents and capital, non-invasive EEG technology is bound to be miniaturized, portable, wearable and easy to use.
For invasive technology, if the human body's rejection reaction and the transmission of information from the skull will be degraded in the future, the computer will recognize the human mind's thinking in real time. This aspect will help the computer to better understand the characteristics of human brain activity to guide the computer to better imitate the human brain; on the other hand, it can make the computer work better with people.
Of course, standing in Elon Musk's position, he is worried that human beings will be threatened by AI. We need to make the brain-computer interface act as a medium for brain-to-machine connection to ensure that humans can fight against AI in the future. On this whole road of development, topics such as “super-humanâ€, “semi-mechanical†and “consciously uploading human beings for eternal life†that cannot be ignored will become a common issue for all mankind.
Source: Silicon Valley secret probe (micro signal guigudiyixian)
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