Is the human brain a biological computer?

Is the human brain a biological computer?

March 14-20, 2022 is Brain Awareness Week, an annual global campaign to generate public support for brain science. Brain Awareness Week was founded by the Dana Alliance for Brain Initiatives (DABI) and the European Dana Alliance for the Brain (EDAB). The goal of this initiative is to get people excited about solving the many mysteries of the human brain. One of these unsolved mysteries is how our brain, the main electrical organ of the human body, actually manages its electrical activity and how it does this job with such remarkable efficiency.

Electrically, the brain remains largely a black box. We send electrical signals and we receive electrical signals, but exactly what this all means is open to much interpretation and intense controversy. But if we just look at the energy consumption of the brain, we have to conclude that the human brain is very “green”. The adult human brain operates continuously, whether awake or asleep, with only about 12 watts of power. For comparison, a typical desktop computer consumes about 175 watts and a laptop about 60 watts. And the energy source of the brain is renewable; it is the solar energy stored in food. If the human brain was a computer, it would be the greenest computer on Earth.

The basis of brain greenness is its ultra-high computational efficiency; that is, it can generate an enormous amount of computational output for the very little power it consumes. Studies have shown that the brain has a higher computing power efficiency than electronic computers by orders of magnitude. This has led to efforts to attempt to design computer architectures to better mimic the brain. The idea is that if computer circuitry were to become more like a brain, the power requirements of computers would drop dramatically, resulting in practical benefits such as smaller batteries and longer charging times.

How did the brain’s high computational efficiency come about? As I explain in my book, Spark: the life of electricity and the electricity of life, some claim it was the result of evolutionary pressures that favored individuals with the highest neurological efficiencies. Some evolutionary biologists have even argued that evolution in higher animals has been largely driven by natural selection for neurological efficiency at the level of the neuron. Thus, by mimicking the nervous systems of higher organisms in our electronic computer design, we could exploit design strategies that have already withstood millions of years of natural verification. But aside from the practical applications of brain science to computers, attempts to develop computer electronics that emulate the circuitry of the brain may lead to a better understanding of the actual workings of the brain itself, at its most fundamental level.

Yet this vision of the brain as a super green computer is not without criticism. Some argue that there are serious limits to what we can learn about the brain just by equating its components with computer components. They say that true insight into the electrical nature of the brain can only be gained by studying the electrical activity of the brain as a whole. They argue that reducing the brain to the status of a computer is a great injustice to the brain and ultimately fails to gain true insight, because such an approach cannot see the forest instead of the trees. They therefore advocate for large-scale complementary approaches, arguing that such approaches are essential to understanding the functioning of the brain in its entirety.

Some brain scientists are even more hostile to the metaphor of the brain as a computer. They say the metaphor has long lost its usefulness and now holds us back. Holds us back because the model of the brain as a computer ignores what is called emergent properties— properties which emerge as a system operates and which cannot be predicted solely from the study of its components. They argue that the things we most want to know about brain function, such as the mechanism of consciousness and the nature of sleep, are emergent properties, and therefore inaccessible to us as long as we keep trying to understand the brain. in terms of corresponding computer components. This group of neuroscientists generally believe that insight into the brain will be gained by behavioral studies, not by comparison with computers.

This critique of the brain-as-computer model has been around for a long time. As early as 1951, neuroscientist Karl Lashley decried the use of any machine-based metaphor for the brain. Lashley said:

Descartes was impressed by the hydraulic figures in the royal gardens and developed a hydraulic theory of brain action. We have since had telephone theories, electric field theories, and now theories based on calculating machines…. We are more likely to discover how the brain works by studying the brain itself and the phenomenon of behavior than by indulging in wild physical analogies.

It’s a common sentiment among modern haters of the computer metaphor of the brain. In particular, they believe that the emphasis on studying the brain’s interaction with the senses, as do the majority of studies of the brain, ignores the true marvel of the brain: its control of behavior. It is the processing and translation of sensory information into appropriate behaviors that they believe is the key to understanding how the brain actually works. Unfortunately, we know little about how the brain controls body behaviors, and they say we’ll never get there by studying the details of things like eye-brain visual circuitry. According to them, we can never understand why, when the eyes see flames, the nose smells of smoke and the ears hear an alarm, then the legs pull the body out of the building as quickly as possible. When we understand this, we will understand how the brain actually works.

Nobody knows how many annual weeks of brain awareness will pass before we finally resolve the controversy between the brain and the computer. But that doesn’t matter. What matters is that people become aware of the many questions that brain science addresses and that they are enthusiastic enough about brain research to support and fund it. Hopefully, this research will eventually lead to cures for the many different brain diseases that cause so much human suffering. The American Brain Foundation estimates that one in 6 people worldwide suffer from a brain-related disorder, and there is little hope of relieving people of these diseases without a better understanding of the underlying mechanisms by which a brain actually works. We may not be able to answer all the questions about the brain, but we can certainly become aware of the most important questions to ask.

Timothy J. Jorgensen is Professor of Radiation Medicine and Director of the Graduate Program in Health Physics at Georgetown University. He is the author of the award-winning book Strange Glimmer: The History of Radiation (Princeton). He lives in Rockville, Maryland. Twitter @Tim_Jorgensen