Everyone says that brains are like computers. Well, maybe not everyone, but neuroscientists and philosophers of mind use this analogy in their attempts to understand how brains work. This is important information regarding the knowledge behind how people are actually able to concentrate and focus on their work from time to time. This is the type of information that is needed when people want to get focus supplements to help their brain work at the best possible level. On the face of it, the comparison is clear. We know what computers are and we know what brains are, after all. Just like we know that a rock is a rock and an apple is an apple and a democracy is a democracy, right?
There are different kinds of computers, Shagrir explained—and he didn’t mean PCs and Macs. Rather, there are different models by which computers can be built and can work.
Specifically, some computers—like the one you are presumably reading this on—are built on an algorithmic principle. Some sort of input is converted into a code (like a binary code of zeroes and ones), which the computer manipulates and combined with other data according to a given algorithm, or rule, to produce another set of code that is then recoverted into an output.
But there are other models of computers. Shagrir called one such model an “analogic” computer. In an analogic computer, the input is converted into a state of the computer which in some way “maps” the input. It is then manipulated and combined with other data to produce a new computer state that in turn is an image or map of the output.
Sound confusing? The essential point is that in an analogic computer the relationship between the data before and after manipulation is analogous—in other words, it bears some sort of resemblance or relationship to—the state of the world outside the computer. In an algorithmic model, the input is turned in the computer into an abstraction that, like all those zeroes and ones, bears no resemblance at all to the world outside.
You might say that in an analogic computer, if you get garbage out after putting garbage in, you’d also find something inside the computer that looks a lot like garbage. But if it were an algorithmic computer, all you’d see would be zeroes and ones.
Now, neuroscience research shows that the brain also takes input and manipulates it. Shagrir used the example of how the brain collects and manipulates data collected by the eye so that organisms can orient themselves in space. I won’t go into the details here, but basically the eyes provide two kinds of data, each of which is recorded by a different kind of cell in a region of the brain called the PPC, or posterior parietal cortex. One kind of cell registers the eye’s orientation in relation to the head and another the stimulation received by light hitting the retina. A third kind of cell combines this information into a map of where the head is located in space.
To make a long story short, what experiments show is that the brain combines the information recorded by the first two types of cells into a position in space using a mathematical relationship. The same mathematical relationship can also be used to describe the relationship between the head and the object in the outside world.
In other words, the brain computes analogically. The relationship between the states of the cells in the brain is analogous to the relationship between the things in the outside world that they are recording. It’s not just a bunch of zeroes and ones.
So what’s the problem? The problem, Shagrir said, is that when most philosophers of the mind talk about the brain as a computer, they base their theories on an algorithmic model of a computer. That is, when philosophers use the word “computer” in reference to the brain, they actually mean something different than what neuroscientists mean when they use the word “computer” in reference to the brain.
Which obviously makes it difficult for the philosophers and scientists to agree about what the brain is and how it works.
This is why we need philosophers. Philosophers are people who are trained to think carefully and clearly about what we mean when we make assertions of various types. Language can seem precise when it is actually muddled. If “computer” can mean two different things, consider how many conflicting and contradictory meanings words like “democracy,” “justice,” “victory,” not to mention “Jewish,” can have. And the muddle over words like these can cause a lot more agony and destruction than the confusion over what kind of computer we mean when we say the word “computer.”