We often reason through analogies. When something is confusing, we can try to tie it back to something we understand better.
Very often, this process it at the heart of scientific understanding. Charles Darwin formed his famous theory of evolution through natural selection by forming an analogy with artificial selection, the process of human intervention to create new breeds of dogs, cats and corn.
However, sometimes this process backfires. An analogy which seems productive ends up giving misleading impressions. The solar-system model of the atom (Bohr model ), in which electrons orbit the nucleus, was such a theory. It predicted that electrons would be constantly accelerating, and thus should emit light continuously until they fell into the nucleus. A better analogy, with wave functions and probabilistic clouds, took root instead.
Given this double-edged sword of analogical reasoning, let’s turn to one about learning itself: is the brain like a muscle?
Measuring the Analogy
Obviously the brain is not literally a muscle. It’s made of neurons and glial cells, not muscle fibers. So on this level, the two can’t possibly be equated. But what about in its function?
Here it really depends on what features you want to compare. Muscles can change and improve, and so can the brain. Muscles seem to experience fatigue with use, and although the brain may turn out to be more complicated, I definitely feel tired after solving math problems all day, and I bet you do too.
However, since two different things can be compared in an unlimited number of ways, the strength of an analogy is never in the analogy itself—it’s what you use it for. And in this case, the analogy saying the brain is like a muscle has had a long history and a very specific implication.
Prior to the early part of the twentieth century, the popular educational dogma was formal discipline theory. This theory reasoned that the brain was possessive of different intellectual capabilities, broadly defined: reasoning, perception, affect, memory, etc.. Each of these, it was assumed, was like a muscle. If you flexed your reasoning faculty with a game of chess, it was assumed, this would help you with reasoning about mathematics, just as flexing your biceps by lifting weights can make you stronger in an arm wrestle.
This analogy led support to the widespread practice of teaching superficially useless subjects, on the idea that the content of education wasn’t what mattered, but its form. If you strained your brain on memorizing Latin, this would improve your memory muscles for all sorts of things later on. Effort, not content, mattered.
So was this analogy correct?
In this case, we know the answer by the work by the psychologist who sought to put it to the test. Edward Thorndike  ran experiments (which have since led to over a century of robust replications) in 1906 that showed, contrary to the muscle analogy, that improving memory or reasoning in one domain did not necessarily benefit those faculties in different ones.
Thorndike, formulated a hypothesis, known as identical elements theory , that said the amount of transfer that would occur from learning one thing to another would be based on the amount of identical sensory or response elements it contains.
This was a valiant first explanation, but researchers now view it as too simplistic. For one, it would seem to prevent analogical reasoning at all (where surface characteristics are different, but deeper structure is the same), the same principle the muscle metaphor rests on. However, psychology was much less developed at the time and cognitive explanations had yet to take root in theories of behavior.
Despite the flawed alternative hypothesis, Thorndike was successful in debunking a popular myth of his time: that teaching students Latin and geometry would exercise the brain’s general-purpose reasoning and memory faculties, and thus make its students excellent reasoners and rememberers for everything else.
A Stubbornly Persistent Myth
Thinking about learning Latin for the sake of building mental muscles is so far from the current educational norm, that it can feel almost quaint. We see ourselves as above falling for such a simplistic error in our own ideas about learning, right?
Yet, it’s exactly a revival of this failed analogy that you see popping up in all sorts of places.
Critical thinking is often touted as the must-teach skill in high-schools and colleges. And while learning logic and syllogisms may be useful in some particular settings, the idea that this exercise trains us to be good thinkers generally was given a thrashing almost a century ago.
Similar are the cries for universal training in programming. While programming is definitely a useful skill (arguably more useful than the pre-calculus directed math we tend to teach) and there are many practical applications for programming, that’s not the only reason offered for it. Programmers have better thinking skills, it has been argued, and that teaching kids to code will help them think logically about the world. The muscle metaphor persists.
Brain-training games premise their entire application on the idea that one can improve cognition like a muscle, training on irrelevant mental tasks to improve brain strength. Some studies (often paid for by the brain training companies themselves) do even suggest that they may work on tests of general reasoning.
But there’s a sneaky trick here: very often the “games” that the brain trainer uses are extremely similar to the tests psychologists use to measure general properties like working memory. But nobody argued that these tests were unlearnable! Even an IQ test is something you could improve on if you studied for it deliberately. The only reason these tests work is because they’re not something people typically study for. If some subset of people practiced them deliberately, we wouldn’t expect them to predict things in a general way.
A final reincarnation of the brain-as-muscle metaphor I’ve seen is that bilingual people have greater creativity, reasoning, memory or something else. Learning new languages, therefore, has the much-sought-after general-purpose learning effects.
While this case is more plausible than the above examples, because learning a language fluently is so extensive, it’s bound to impact your life in many diverse ways. It’s unlikely that any transfer effects from languages to non-linguistic domains will be robust enough to justify the immense cost of learning another language. If you want to learn another language for the purposes of learning another language, great, but the century-long history of failures of transfer in research should give one pause when suggesting it’s an easy fix to improve your intelligence.
Seductive Analogies and the Way Forward
Analogies are potent reasoning tools. They help us map a poorly-understood domain onto something we understand better. When they’re used well, this can be an enormous lever in reasoning, allowing us to think about something more clearly.
However, as the muscle-metaphor shows, analogies to scientific phenomenon can also backfire. Their potency, in this case, can also be their downside, as we get seduced into believing them even after evidence shows that they don’t apply.
Is this the final word on training your brain? Possibly not. It’s very difficult to prove that something is impossible in science. All we can show is that the things we’ve tried already don’t work. It may be the case that this next thing will do the work we need, and improve memory, reasoning, perception or some other cognitive faculty generally.
However, the research seems to suggest that this analogy may simply be wrong. We may not have a general-purpose reasoning ability that, like a bicep, gets improved whenever we use it. Instead, perhaps we have billions of neural circuits that form patterns conducive to solving some problems that can only extend, in a limited fashion to other intellectual tasks.
Or perhaps the circuit analogy is also wrong in some fundamental way, an analogy to computers that turns out to have undiscovered limitations. And when that happens, perhaps people will still insist on talking about the brain-as-circuits, and suggest experiments and techniques based on that analogy, a century after it has been debunked.