Making iron man suits a reality. Neuroprosthetics: combating tetraplegia

A world in which people who suffer from tetraplegia can walk again seems out of grasp. Are we talking about creating iron man suits? Yes, but not entirely like those seen in the movies. Although, suits quite similar in prospect in which sensors are placed over paralyzed areas of the body to reestablish coordinated movement with a simple thought are beginning to be crafted. Quite literally, researchers at Case Western Reserve University in Cleveland, Ohio have begun to reestablish the grasp of individuals who have not been able to have control over the coordination of their limbs for years. Through the novel field of neuroprothetics, machine brain interfaces have been utilized to decode motor signals sent to them originating in the cortex via an electrode, which then can process the signals computationally and transmit them as electrical impulses to the sensors placed in the muscles of the limb, generating the desired movement. The research team’s work at Case Western Reserve University assisted Bill Kosechav to reestablish control over his arm muscles after eight years of paralyzation. This case has been able to provide hope to people who suffer from various spinal cord injuries that have left them paralyzed, that they too will be able to control the movements of their limbs once again. With novel machine brain interface technology this goal seems to be more attainable than ever before.

First it is necessary to begin by understanding the process of motor signaling in the body. All movements begin with a thought. These thoughts of movement are projected as electrical signals of the motor cortex. How do our thoughts of movement then get to the muscles in which we want to move? Essentially the process of establishing movement of the arm is that we think that we want to move the arm, this movement is coded into a signal which travels via the spinal cord down to the limb of interest, which then has a mechanism for decoding the signal and responding with the corresponding movement. In this way the brain can be thought of as a computational device, a wiring system whose signals can be decoded and manipulated as a piece of machinery. How can these signals be decoded and manipulated to produce the specified movement if the spinal cord is injured? These motor signals are beginning to be rerouted via novel machine brain interface technology that has the ability to decipher them and convert them to electrical pulses, ultimately taking place of the vital role of the spinal cord. When someone suffers paralyzation from say a car accident, their paralyzation stems from their spinal cord being severed. The spinal cord is the mechanism by which motor messages from the brain get delivered to the limbs. In most instances such as Bill Kochevar, the site of his spinal cord injury prevents the transfer of motor signals from his motor cortex to his limbs, therefore leaving his limbs unable to receive the signals directing their movement. A routing system for these motor signals thankfully can be reestablished via the workings of a machine interface and placement of sensors around the desired muscles.

The research team at Case Western Reserve University was able to bridge his motor cortical thoughts to his paralyzed limbs by detouring the spinal cord. They are the first in the world to restore functioning such as this in a person with tetraplegia. His arm, once again became mobile because cortical control was able to be reestablished. Bill has now regained the ability to reach and grasp with the coordinated movement of his shoulder, arm, and hand once again. His thoughts have been decoded by the computer machine interface, and relayed to the sensors in his arm that can reassert that signal and move the arm in the way in which he wanted it to move.

The researchers began by surgically implanting an electrode in the area of Bill Kochevar’s motor cortex that is responsible for crafting signals of hand movement. Bill Kochevar had four months of thought training with the machine interface to ensure that the movement of the virtual hand on the computer matched the signals of motor direction from his brain. Virtual reality training allowed the computer to begin to decipher and recognize which motor signals/ thoughts of motor movement coded for the corresponding hand movements. This training involved Bill Kochevar thinking of moving his arm in a specific way and watching the computer interface decipher these signals of movement and portray them via the movements of a virtual hand on the computer screen. After this baseline training of the machine interface, 36 muscle stimulating electrodes were implanted into his upper and lower arm. His electrical sensors rested on top of his skin and were manipulated at bay by the computer interface.

Seventeen days after the sensors in his arm were implanted, they were connected to the machine interface that would then begin to send them deciphered electrical signals from the motor cortex. The research team stimulated these muscles in his arm for eight hours a week and for eighteen weeks to improve his arm strength, establish a regain of movement, and to reduce fatigue after several years without use. After these additional seventeen days of training of the sensors on his arm, the entire machine interface system could begin working its magic. The entire machine brain interface system begins with the electrode that was inserted in his brain that detects and decodes certain brain signals from the area of the motor cortex in charge of hand and arm movement. These specific signals are sent to the computer interface which receives and then translates the signals into corresponding electrical impulses to the muscle stimulating electrodes in his arms. The electrical impulses can fire in a specific pattern resulting in the original movement/ contraction of those muscles in which was instructed by the motor cortex. In this way, the machine brain interface mechanism can bypass the spinal cord injury and reestablish the connection between Bill’s thoughts and the dictation of the motor movement of his limbs.  At this point in time, Bill still has to utilize a mobile arm support for his shoulder against the forces of gravity as he works to manipulate the movement in his lower arm once again.  This mobile arm support, which coordinates movement of his shoulder muscles up and down is also under cortical control. Bill Kochevar can now slowly but surely feed himself after eight years of not being able to do so. He is also able to grasp and move objects about thanks to this technology. 

(How Neuro-prosthesis reconnects brain and muscles~ The Lancet)

Even though Bill has regained movement of his arm, there are still a number of limitations to this machine brain interface technology. For instance, the number of muscles that can be stimulated from the electrode via the sensors are few and are spatially limited.  This is due to the arduous process of manipulating multiple cortical areas at once and the limiting nature of the placement of the electrical sensors on the skin. Moreover, the decoded signals produce rough and slow movements in the areas in which they stimulate which still makes movement quite debilitating and restricting. Also, quite obviously, the large electrode in the brain requires an invasive surgery to place quite perfectly into the motor cortex and the large computer required as a machine interface is not practical and interferes with day to day activity. Additionally, there is still a reliance on the computer for consistent feedback upon each movement. This leaves the treatment far from ready for use outside the lab.

 Despite these drawbacks of the current state of machine brain interface technology, this achievement of the rehabilitation of Bill Kochevar’s paralyzed limb remains an exciting demonstration of the power of manipulation of the motor signals in the brain. This illuminates the abilities of the motor signals of the brain to be deciphered by a computational device and wired as electrical signals to other areas of the body. The research team of Mr. Jonas and Mr. Kording demonstrate the ways in which the brain can not be directly assessed and manipulated as a computer in, “Could a Neuroscientist Understand a processor?”. They demonstrated a division in neuroscientific research between a computer system and the brain. They highlighted on the ways that they are incohesive and provide no form of further understanding. They did so by applying data analysis methods utilized in neuroscience in attempt to further understand a microprocessor. In the end, the data collected from this engineered model organism via typical neuroscientific methods of analyzation of local field potentials, lesions, etc. were not able to progress their deeper level understanding of the processor.  Dr. Mark Albert went into this even further in a recent talk that he gave to the Loyola University Neuroscience community in which he highlighted the lack of understanding and limitations of current neuroscientific methods. While their claims are very illuminating indeed and do in fact raise many questions for the Neuroscience community and the effectiveness of current research methods, technologies such as the machine brain interface should not be scraped to the curb. Machine brain interface technology has proven to serve as a method by which the computational characteristics/wiring of the brain can be utilized and reconstructed to manipulate the biological wiring of the body successfully. The success of the brain machine interface calls for the identification of areas of the brain that we can be successfully manipulated electronically and those that are unable to be deciphered and replicated as such.

Back to the iron man suit ordeal. As of now, manipulating the rerouting of motor signals to several limbs of the body at once is not possible. However, in the future, when this machine brain interface technology is further developed, as is the case with the improvements seen in any other technological device, there are many areas of improvement that can help reestablish full independence to paralyzed individuals.  For instance, there can be a reduction in the size of the electrode/detector in the brain to the size of a computer chip so that the surgical implantation is not as invasive and that a large cord is not debilitating in its nature. Additionally, this computer chip lying on top of the motor cortex could then signal electronically to a machine interface which is also the size of a computer chip that can be placed into a cellphone so that the interface can be carried around easily. Can we take it further to surgically implant these electrical sensors on the paralyzed limbs under the skin and around those muscles that have suffered from paralyzation so that consumers do not have to wear clothing made up of sensors? That way, paralyzed individuals reroute the motor signals from their cortex to their limbs via a computational and technological interaction between a chip in their motor cortices, the computer chip in their phone, and the sensors on multiple debilitated limbs. These technological manipulations can make the machine brain interface more practical. It will help formally paralyzed individuals regain their independence and movement of their limbs without walking around with a large electrode in their brain and a bulky computer. Forget the iron man suit. We don’t want something so bulky and restricting. Machine brain interface technology gives us a chance to erect a more practical method of regaining strength and motor coordination in paralyzed limbs.

Works Cited

Jonas E, Kording KP (2017) Could a Neuroscientist Understand a Microprocessor? PLoS Comput Biol 13(1): e1005268. doi:10.1371/ journal.pcbi.1005268

"Paralysed man moves arm using power of thought in world first." 29 March 2017. The guardian. Ed. Sarah Boseley. 8 October 2017 <https://www.theguardian.com/science/2017/mar/28/neuroprosthetic-tetraplegic-man-control-hand-with-thought-bill-kochevar>.

The Lancet. "How Neuro-prosthesis reconnects brain and muscles."[Image] The guardian.