Computers are all around us, even within your head

As the title says, computers are all around us, on your desktop, laptop, on your phone, on your television screen, and even in some light bulbs. However, these are all silicon-based computers, and there is a highly efficient and powerful computer not yet mentioned, and it helps you read this article, learn new things, daydream, and solve math problems; this computer is your brain. The brain is a highly efficient computational organ that takes input from the environment, through its senses, and outputs a response, such as moving your eyes, arm, and hand to catch a thrown ball. It performs calculations and is the reason you can think, read, and solve math problems using just a pencil and paper. By the end of this article, you will have learned how powerful the brain is, how it works similarly, but more efficiently than a computer, and how limited artificial intelligence is by comparison.

To understand the similarities between a computer and a brain, you must first understand how a computer and a brain, in a general sense, work. We will start by discussing how a computer works and then transition to how a brain and the nervous system work.

The computers we use today are general-purpose computers that were envisioned in the early 20^th century by Alan Turing, a brilliant mathematician and the father of computer science (read for more information about Alan Turing: https://en.wikipedia.org/wiki/Alan_Turing). Our computers work using software to manipulate the hardware of a computer to output what is desired. Essentially, what is happening is that software is switching transistors on or off as needed to produce the computations. The transistors can only be in the on position or the off position, the same way a light bulb can either be on or off.  Computer scientists use the number 1 to denote the on position of a transistor, and 0 as the off position. These are computer bits, and by using a series of 1s and 0s, a computer can answer the question of what 1+1 equals or what (4*3+2)/5 equals. This is essentially how a computer works, by flipping a transistor on or off, a 1 to a 0.

A neuron is the basic computational unit of the nervous system. Neurons, or nerve cells, are the cell types that both relay information from the environment to the spinal cord and the brain and perform calculations on those environmental inputs. (The spinal cord and brain comprise the central nervous system.) Before I can explain how the brain is similar to a computer, I must discuss a bit about a neuron’s anatomy. As can be seen in the picture above, a neuron has an axon, dendrites, and a cell body. The cell body is where all the usual cellular functions occur, such as DNA replication and protein production. The dendrites and the axon are where the fun stuff happens. A neuron’s dendrites are where it receives input from its environment; it is analogous to the neuron’s ears. A neuron’s axon is where it relays information; it is like its mouth. Within our nervous system and especially our brain, neurons “talk” to one another through this axon-to-dendrite connection.

There are two main classes of neurons: excitatory neurons and inhibitory neurons. Excitatory neurons enhance the ability of the neuron it “communicates” with to “communicate” with another neuron. Inhibitory neurons do the opposite; they diminish the connected neuron’s ability to “communicate.” These two classes of neurons are highly important to the computational ability of the brain.

Finally, we have come to the last thing you will need to understand before we can compare the brain to a computer: the action potential. An action potential is what leads to the release of a neurotransmitter from an axon terminal, like the words “spoken” by the neuron. This is how the neurons “communicate,” through these action potentials. Here is the thing about action potentials: they are either sent through the axon or not; there is no in-between. This is wild because a neuron’s axon can be over a meter long, which means the action potential will have to transmit over that length of distance without changing. Biology is amazing! Because the action potential is either on or off, it works the same as a computer bit, and this is where we get into some similarities and differences between the brain and a computer.

The math that allows 1s and 0s to lead modern computation will not be discussed here, but if you are curious, you can read about Boolean mathematics here: https://www.geeksforgeeks.org/boolean-algebra/. Essentially, a series of 1s and 0s, or computer bits, can generate anything we can think of, and is basically how our brain works. Our brain, thanks to the action potential of its neurons, has neurons that either transmit neurotransmitters or do not, a 1 or a 0, but its computation is more complicated by the different classes of neurons discussed above.

As discussed above, an excitatory neuron makes it easier for a neuron it is “talking” with to fire its own action potential, while an inhibitory neuron inhibits the secondary neuron’s firing. This means our brain can do computations not possible by the typical computer bit. Our neurons integrate signals from all the neurons they are connected to through their dendritic tree around the cell body, both excitatory signals and inhibitory signals. If a neuron gets enough excitatory signals to overcome the inhibitory signals it receives, it will fire its own signal. (Disclaimer: This is a simplification of the process of releasing a neurotransmitter.) This means that not only is a neuron something that fires an action potential or doesn’t, but it also computes within the neuronal cell body. Oh, and there's more. this is only a generalized neuron; there are, by some estimates, over one thousand different neuron types in the brain. That is a lot of computing power!

Which leads me to thinking about artificial intelligence (AI). AI has taken over the headlines in the news media, on social media, and even has been seen in some toasters. Many AI models rely on the artificial neural network (ANN), a way to emulate how the visual cortex works using computer bits. These AI models are inefficient, needing thousands of pictures of a cat to differentiate it from a picture of a dog or a lawn mower, requiring a GPU to train the ANN, and a lot of electricity to keep the computer cool enough to train the AI model. This is why AI companies are now looking to build or control nuclear power plants to supply all the electricity needed to train and store their AI models.

In contrast, the brain uses 20 watts of power to allow us to interact with the world. The brain is an extremely efficient computational organ, and one that cannot only identify a cat from a dog but can create giant buildings or microscopic violins. It can wonder about the mysteries of the universe, watch YouTube, and cook some rice all at the same time. In our search for the perfect AI and daily use of computational devices, we have forgotten, or never learned about, the wonders of the computer sitting above our shoulders, contained within a cradle of bone, the brain. I hope that I have inspired you to “look” at your brain in a new light, to see it as the wonderful, efficient, and awe-inspiring organ that it is, and to use your brain to improve society.

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(All images in this post were from Wikipedia Commons)