The Brain-Machine Connection: Humans and Computers in the 21st Century
A bull is charging at full speed, riveted in its fury, straight at you. Rather than running for your life, you calmly flip a switch on a remote control you’re holding. Immediately, the bull halts its furious charge and awkwardly trots away. This sort of mind control is not science fiction – it was an actual experiment performed by one of the earliest practitioners of brain implants – José Delgado, a neurophysiologist at Yale University from 1946 to 1974.
Trained in the venerable tradition of neuroanatomists, José Delgado was a physiologist who primarily studied the neural anatomies of animals. After reading about how Nobel Prize-winning neurologist Walter Hess was able to induce various emotions through electrical stimulation, Delgado chose to further explore this concept. Over the next thirty years, he constructed increasingly sophisticated devices that would deliver measured electrical pulses to specific targets in the brain. For example, one of his innovations was a device known as a stimoceiver, a pacemaker-like device that could electrically stimulate a certain area of the brain when triggered by a remote electrical receiver. The device provided Delgado unprecedented control of an animal’s movement and emotional state. In his mind, the final purpose of these devices was to be able to control mental illnesses, such as schizophrenia or depression, by stimulating various parts of the brain, a less invasive and destructive alternative to a then-popular surgical procedure known as a lobotomy. Using this device, he dramatically demonstrated his control of behavior by stopping a charging bull just a few feet away.
Delgado’s findings were profound in many ways. One of his most important inventions was a special stimoceiver that tracked patterns in a specific region of the brain and responded when certain patterns arose. His first use of this design was on a chimpanzee’s amygdala. When the amygdala produced a pattern known as a spindle, the stimoceiver automatically stimulated the central gray region of its brain, inducing an unpleasant nausea. The result was a dramatic reduction in the frequency that these spindles appeared. Although it seemed cruel to the hapless chimp, Delgado believed that this device could halt or reverse diseases such as epilepsy. Unfortunately, because much of his work was in the 1970’s and was ahead of its time, the experiments caused a firestorm of ethical outrage at what the public considered an Orwellian mechanization of the human will. Delgado exited the American neurological research field and immigrated to Spain, while his stimoceivers faded into the footnotes of science.
From Fiction to Cure
But what seemed like a bizarre story from the annals of research was just the first step in a variety of increasingly sophisticated ways to link mind and machine. In the 1980’s, several teams at different universities developed tools to record and stimulate different parts of the brain. For example, Apostolos Georgopoulos at Johns Hopkins University inserted single electrodes into different parts of the motor region of a macaque monkey’s brain, recording how various neurons responded to different directions its arm moved. In the intervening decades, scientists have advanced and refined this ability, allowing them unprecedented control over certain manipulatable areas of the brain.
One of the direct clinical applications of Delgado’s work, deep-brain stimulation is a recently FDA-approved approach towards treating Parkinson’s disease and depression. A long electrode is surgically inserted into a targeted region of the brain, such as the basal ganglia in Parkinson’s, where a pulse generator steadily sends bursts of electricity to stimulate that region. It is now known that the electrical pulses from deep brain stimulation stimulate certain neurons to secrete compounds that suppress the symptoms associated with a disease such as Parkinson’s. They act as pacemakers, regulating the chemical balance of the brain without resorting to drugs. Although not a cure, they serve to significantly reduce symptoms and improve the quality of life for the patient. Delgado’s dream of using his stimoceivers to cure disease has finally been realized.
Towards a Man-Machine Meld
A more profound and intensive area of research for neuroscientists has been the development of brain-computer interfaces (BCI). Conceptually, a brain-computer interface is a system where a computer can directly receive and interpret information from a subject’s brain, seamlessly bridging the gap between man and machine. The technology to enable this futuristic advance has been the work of countless laboratories and millions of dollars in funding.
The first step in constructing a BCI is to create a physical interface between the neurons of the brain and the copper of the computer. Three main approaches have been taken, which vary in the amount of physical penetration into the brain.
One approach is a direct descendent of Delgado’s and Georgopoulos’ wire insertions: using an invasive field of pins called Utah arrays to cleanly capture the signals of hundreds of neurons at once. These arrays, which lie snugly against individual neurons, can capture the changing electrical signals with unprecedented fidelity, making it one of the least error-prone techniques currently available. Researchers in Japan used one of these arrays on a monkey, allowing it to remotely control a robotic arm. However, the quality of the extracted signal is not enough to compensate for the complications associated with open-brain surgery as well as the tissue damage from the pin insertions. Thus, although technology is unceasingly refining and improving the design of these arrays, they are currently relegated to experimentation on rats and monkeys.
At the same time, an alternative approach has been researched in parallel. Known as electroencephalography (EEG), this technology takes a fundamentally different approach from invasive electrode arrays. By applying very sensitive electrodes on the scalp, faint electrical residues emanating from neurons near the surface of the brain could be skimmed off and recorded. By observing large-scale fluctuations in the location and intensity of distinctive parts of the brain, the observed signal could be used by machines. Currently, noninvasive EEG-based devices are used by quadriplegics and individuals suffering from locked-in syndrome, a disease characterized by the complete inability to elicit movement in any part of the body, to communicate through a computer. BCIs act as a detour around the damage and offer these patients the ability to interact with the outside world. This system interprets EEG signals to help the patient input letters in a computer, allowing them to communicate with others.
Finally, recent research has offered yet more methods of signal acquisition that have yet been commercialized. One is a compromise between the tissue-damaging but high-fidelity recordings from electrode arrays and the noninvasive but noisy EEG. Known as electrocorticography (ECoG), this sensor system functions as a plate of EEG-like noninvasive sensors that sits atop the surface of the brain. By sitting much closer to the brain, it offers much higher-fidelity signals than EEG, but without the damage created from the sharp pins of the electrode array. Even as these techniques are commercialized, new and more advanced techniques are being developed that offer higher resolution, better signal fidelity, and larger recording field. For example, Eugenio Culurciello, Associate Professor of Electrical Engineering, and Vincent Pieribone, Associate Professor of Physiology and Neurobiology, developed a system called NeuroView, a novel approach for very fast and noninvasive optical recording of neurons in experimental animals that use fluorescent neurons to track activity. His approach will allow for recording of neurons over a hundred times faster than EEG and on the spatial resolution of individual neurons to rival an electrode array.
The Robotic Man: “Construct Thyself”
Brain-computer interfaces may already seem futuristic enough, but advances in neural prosthetics seem positively alien. Several leading laboratories have successfully grafted robotic devices onto the brains of animals, allowing the animals to control the robot using only their thoughts. Construction of such a device calls for state of the art technology in signal acquisition and processing – but one man’s fiction is another man’s job. In 2009, a team of scientists at Johns Hopkins University, with the support of the Defense Advanced Research Projects Agency (DARPA), successfully constructed the world’s first neural-integrated prosthetic arm designed for human amputees. Integrating the most advanced technology in electrode arrays and data processing, the “million-dollar arm” could move individual fingers and wrists, a huge improvement over current wrist-only prostheses. Unlike any previous device, the prosthetic arm uses residual nerve signals from an amputee’s upper arm as well as direct signals from the amputee’s brain, using a new technology known as data fusion to accurately determine the intent of the amputee. The technology involved millions of dollars of research funding and tapped into advances in biotechnology, material science, mathematics, neuroanatomy, and computer science. The construction of such a device is the culmination of much research understanding the structure and function of the brain. As human curiosity penetrates the murky complexity that is the brain, the ability to interface man and machine will increase, ushering in an era where, as Delgado puts it, we will be able to “construct thyself.”
About the Author
HENRY ZHENG is a sophomore prospective Molecular Biophysics and Biochemistry major in Pierson College. He currently works in a computational neuroscience lab on calcium modeling in the visual system.
The author would like to thank former Yale Professor José Delgado for pioneering the field of using brain electrical stimulations for mind control and current Yale Professor Eugenio Culurciello for continuing similar research interests and for his help with this article.
Zheng, Henry. “Multisensor Data Fusion for Prosthetic Control.” Information Fusion, Proc. 11th Int. Conf. July 2008. 1852-1859.