Why we should develop neurotechnology. The brief history of neurotech.

The next technological revolution. The brief history of neurotech: the origin of data reading, visualization, and brain stimulation…

In all scientific and technological revolutions, several basic parameters undergo significant modification, the first of which is the quality of processing, analysis, and speed of information transmission between human-human and, subsequently, human-machine. Thus, the creation of the first trains and rail system significantly reduced the time of movement of people, and the introduction of electricity allowed to create machines that automated production, thus, the manufacturer’s productivity was increased, namely production — essentially processing information. What about the days of information technologies? The methods of collecting, processing and storing data have dramatically changed, which has transformed our ability to track real-time changes that are taking place in the world, which has made it possible for us to make quick decisions in relevant industries. Each generation of the Internet has implemented new communication capabilities, but the further improvement of wireless technologies will not have a relatively significant effect: if society is viewed as an information system that includes the people and computers they use, interact with each other and the environment, then the systems’ improvement should occur not only by increasing the elements and the relationships between them but also by increasing the capacities of these elements, in particular humans. All past technological revolutions have implemented technical capabilities that complemented and expanded the ability of a person outside his body in the constant presence of a mediator element. Yes, a modern computer can be considered an extension of our cognitive organs, but the transmission occurs through several mediators, such as hands and keyboards — in this case, the speed of information transmission from person to computer is much lower than that of information in the human nervous system. While artificially created machines are increasing their computing power, the nature of human-machine interaction remains conservative, all of which impose restrictions on human development.

The graph below shows the backlog of communication between a computer to human and human to a computer by more than 3 times, so the potential for growth of various interfaces is significant.

The next technological revolution should solve the problem of human communication between computing devices.

Due to modern neurotechnology, the development of “human-machine” interfaces and improvement of the cognitive abilities of the person is possible. Therefore, the rapid development of this industry and the potential to increase the communication capabilities of human-human, human-machine systems and the achievement of the information technology threshold of the current stage of scientific and technological progress make us believe that the next technological revolution will be based on neurotechnology [1]. In our day’s different areas of social science, such economy, implemented principles of neuroscience in their methodology, looking brain processes in deciding on finance operations.

In the foregoing analysis, we have focused on the fundamental capabilities and perspectives of neurotechnology, but it should be understood that very different processes have influenced the beginning of the development of this industry, which, incidentally, are still powerful drivers. It is about diagnosing and treating a variety of neurodegenerative diseases, which are currently one of the main causes of deterioration in the quality of life of a person. According to some reports, the total cost (direct and indirect) of maintaining mental health in the world can rise from $ 2.5 trillion in 2010 to $ 6.05 trillion in 2030 [2]. Thus, in 2017, the Wait But Why blog stated that Neuralink was beginning to develop a device for the treatment of serious brain diseases, but in the long run, the company is interested in developing full-fledged human-machine interfaces [3, 4]. Kernel company is interested at the same topic, it develops interfaces, helping researchers to understand better disorders such as Alzheimer’s, Parkinson’s, depression and anxiety [5]. Similar strategies are followed by many modern neurotechnology startups that use medical implementation of their own technologies as a staging area for the development of human-machine interfaces.

Currently, magnetic resonance imaging is the standard and is used in many research and medical practices. The MR-image method allows to obtain 3D morphological and functional information at the millimetre and submillimeter levels. Because a human’s body is made of water to a great extent that contains hydrogen atoms, studying their magnetic properties can provide a lot of useful information about the condition of a tissue or organ. A hydrogen atom consists of a single proton that contains its own magnetic moment. This magnetic field is influenced by the application of the magnetic field, the surrounding gradient fields, and the radio frequency pulses, which are actually these factors, are used to find out in which tissue the proton is localized, but how? In the strong magnetic field, most of the protons are in the direction of this field, but some of them are in opposition, after the action of radiofrequency pulse, the protons change their orientation and emit their own radio frequency pulse, which is captured by numerous scanners, and then return to the previous position and process is repeated again.

The concept of MRI was developed by Paul Lauterbourg, сhemistry professor, in 1971, as he applied a three-way magnetic field gradient and reverse projection technique to produce nuclear magnetic resonance imaging (MRI). After that, in 1973, he published in the “Nature” magazine the article named “Image Formation by Induced Local Interactions: Examples of Employing Nuclear Magnetic Resonance” [6]. It is important to decrypt a received radio signal correctly. The mathematical algorithms for image processing were refined by Peter Mansfield, and that allowed him to scan topologically important areas of the brain and track its activity. The first tomographs had weak sources of the magnetic field, their magnetic induction was 0.005 T and it did not allow to create high-quality images. Modern devices contain powerful electromagnets, magnetic induction of which averages 1–3 T, and even up to 9 T in some cases. Besides those, permanent magnets (0.7 T) are used. Considering these capacities, superconducting magnets, that work in liquid helium, are used too.

From the 1990s, functional MRI, a technique that was made by Seiji Ogawa, began to develop. This technique is based on the different saturation of the tissue with oxygen, depending on its activity, so, the more activated is the tissue, the greater is the blood flow to that tissue and its oxygen consumption. Thanks to the work of Linus Pauling and Charles Correll, it became possible to open this type of MRI. Researchers in 1936 demonstrated that oxygen-enriched blood with Hb (haemoglobin) is weakly repelled by a magnetic field, while oxygen-depleted blood with dHb (deoxyhemoglobin) is attracted by a magnetic field. The fMRI technique has made it possible to map associative connections between different brain regions, including discovering new ones [7]. This has led to the origin of various related industries that have incorporated brain imaging technologies into their own methods, such as neural management and neuromarketing.

There is also a separate technique associated with MRI — magnetic resonance spectroscopy, which allows you to study certain specialized areas, exploring their metabolic processes. The main advantages of MRI are the safety of the technology and the excellent picture quality of the morphological structures of organs and tissues, however, there are limitations in resolution, since the very phenomenon of nuclear magnetism is weak by its nature.

Another visualization that allows the metabolism to be investigated is positron emission tomography, which is based on the fixation of gamma rays that we receive from the annihilation of a positron with an electron. How it works: a radiopharm substance is injected into the body (an analogue of metabolism substances, which are being investigated); during the decay of the radioisotope, a positron is formed, it undergoes annihilation, which results in the fixation of high-energy photons (gamma-rays), which penetrate the human body very easily, and special scanners are able to capture these photons and convert the detection signal into an electrical signal, and that finally creates a multidimensional image.

The concept of this type of tomography was developed by David E. Kuhl, Luke Chapman and Roy Edwards in the late 1950s [8]. Later, their work was used to design several devices at the University of Pennsylvania. Equally important were efforts of Gordon Brownell, Charles Burnham and their coworkers at Massachusetts General Hospital, who made the first demonstration of annihilation radiation for medical imaging. In 1961, James Robertson and his associates have built the first single-plane PET (positron emission tomography) scanner at the Brookhaven National Laboratory. And in 1975 this technique was refined by M. Pogossian, M. Phelps, E. Hoffman and others at the Washington University School of Medicine [9]. Today, the use of PET makes it possible to detail the study of various mental processes at the level of specific substances, and it has its advantages, compared with fMRI, which is able to record only the total activity of the brain. But researches are limited to short-term tasks, because, in addition to the rapid decay of radioisotopes, usage of radioactive substances involves some actual risk [10].

Nevertheless, the first technology that was used to investigate the general state of the brain is electroencephalography.

The beginning of the study of electrical processes in the brain was laid by D. Raymond in 1849, who showed that brain, like nerve and muscle, has electrogenic properties. The beginning of a full-fledged electroencephalographic study was encharged by Ukrainian psychologist V. Pravdich-Neminsky, who published in 1913 the first-ever electroencephalogram, recorded from a dog’s brain. In his research, he used a string galvanometer.

And the first human EEG record was obtained by German psychiatrist Hans Berger in 1928. He also suggested the recording of the brain bio currents to be called “electroencephalogram”. Berger’s work, as well as the method of encephalography, was widely recognized only after May 1934, when Adrian and Metthews first convincingly demonstrated the “Berger’s rhythm” at the Cambridge Physiological Society meeting. Nowadays, EEG is widely used in clinical practice, and numerous neurotech startups use this technology to create human-machine interfaces (Emotiv), sleep control devices (Dream), and human thoughts fixing (AlterEgo).

However, the history of brain stimulation has more than 100 years of history, although rapid development began after the development of imaging technologies. For the first time in 1986, Jacques Arsene d’Arsonval applied a magnetic field to humans, inducing visual sensations [11]. And in 1902, A. Pollaksek and B. Birr patented in Vienna a method of treating “depression and neuroses” with an electromagnetic device. A new period of magnetic stimulation research began in 1985 when A. Barker et al. (UK) for the first time experimentally demonstrated the ability of muscle contraction caused by non-invasive effects on the central nervous system of an alternating magnetic field [12]. In 2018, the FDA device from Brainsway Ltd was approved as a method of treatment for adult patients with obsessive-compulsive disorder in whom the pharmacological treatment of the disease exacerbation of antidepressants in adequate doses had no proper effect.

Another area of ​​stimulation is micropolarization, which is based on the action of low-voltage direct current on certain areas of the brain with the help of small electrodes. In the 1960s, a study by D.D. Albert has shown that stimulation can affect brain function by altering the excitability of the cortex, so the interest in this type of stimulation was gained [13]. It is worth noting that the method was primarily designed to assist patients with post-stroke conditions, but further studies have shown a positive effect on the cognitive abilities of healthy people. Only in 2015 did the British National Institute for Health and Care Excellence (NICE) justify the use of tDCS (transcranial direct current stimulation) as a safe and effective method for the treatment of depression, although more research was needed at that time. With regard to research, their number has increased significantly over the last 5 years; according to a search on PubMed, 9600 papers were published, which is more than half of the total number of publications (16494). No tDCS-based devices have been approved by the FDA at this time. However, another electrical stimulation device, the NeuroSigma Monarch external Trigeminal Nerve Stimulation (eTNS) system, which uses low-level electrical impulses has been authorized by the FDA for marketing promotion [14].

The company was approved in 2019. A device is used for the treatment of hyperactivity disorder and attention deficit disorder (ADHD) in patients aged 7 to 12 years who don’t take medicines. The device is only available by prescription and is intended for home usage under the supervision of a caregiver during periods of sleep.

Written by Ihor Stepanov

Edited and translated by Oleksandra Melnykova, Yuliia Nazarenko and Oleksandra Naumenko


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  2. Bowman, Diana M., et al. “The Neurotechnology and Society Interface: Responsible Innovation in an International Context.” Journal of Responsible Innovation, vol. 5, no. 1, 2018, pp. 1–12., doi:10.1080/23299460.2018.1433928.
  3. Urban, Tim, and Tim Urban →. “Neuralink and the Brain’s Magical Future.” Wait But Why, 21 Jan. 2020, waitbutwhy.com/2017/04/neuralink.ht
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