Minds, Brains and Science

John Searle’s Minds, Brains and Science is a collection of the six Reith Lectures that he gave in 1984 on the relation between our conscious, meaningful, phenomenal experiences and the backdrop of nonconscious, meaningless, objective physical reality against which all of the former inevitably play out. Essentially, the problem is this: We experience things, but everywhere else we look in the universe, we do not see experiences. How do we explain this seemingly trivial fact and make consciousness fit in with everything else we know?

This is inevitably a question that he is unable to provide a clear answer for, but, nonetheless, this was a successful, and worthwhile, work. The lectures were intended for a lay audience, so they are largely non-technical, but as far as I can tell, none of the necessary content was lost. Searle is still able to explicate each of the sub-problems and arguments very well. He manages to minimize caricaturing his opponents while simultaneously keeping the focus on what, he thinks, are the real issues. All the while, he manages to introduce several new ideas. His remarks on the social sciences and the freedom of the will are especially noteworthy.

In its entirety, the read comes down to less than a hundred pages, making it a perfect introduction to the problem at large. At the same time, it retains enough depth to catch the eye of even the most weathered philosopher-scientist—and for that, I give it five out of five stars.

Minds and Computers

In everyday conversation, brains are often equivocated to “computers.” This intellectual laziness, as it were, has led to almost an entire generation of academics asserting that minds are nothing more than programs, run on the machinery of the brain. In this post, I hope to clear up a few confusions and oversights related to this position. I do not claim to be the first to say these things, but I’d like to round up a few of these disconnected views and add my own personal thoughts as they seem useful.

The issue is that to claim that the brain is like something—say, a computer—is to assert that we have any idea as to how the brain really works. This is utterly and completely false. We certainly know a lot about the brain, but most of this is in terms of small, isolated events (action potentials) or very coarsely-grained images (e.g., fMRI), so anyone who claims to have a complete view of how the brain processes, integrates, and distributes information is very misguided, to say the least.

There is certainly a lot more about the brain that we’ve learned since these equivocations were first put forth in the literature. We have learned more about how networks of neurons function coherently to produce meaningful representations. We have learned about oscillations in the brain that help unify otherwise disjoint brain functions (gamma-waves are especially exciting in this regard). We have learned about local field potentials, such as those recorded by EEG, and how they help modulate neighborhoods of neurons. In this sense, the brain is still a kind of information processor, albeit much more complex than we once thought it to be, and this is where the equivocation breaks down.

Computers are designed with distinct functional units that attempt to minimize interference from surrounding units. Neurons, the functional units of the brain, certainly do this to an extent—if they did not, the careful modulation of membrane potentials necessary for coherent communication would be impossible to maintain. They are nevertheless heavily influenced by every single signal and associated field potential that passes through any region of the brain they occupy. Neurons could not function properly in isolation (by function, I mean in a way that is conducive to conscious experience), they require complex interactions among themselves—and with the body they represent—the likes of which we do not see in their silicon counterparts. The most complex relation required is that which is often referred to as “dynamic constancy” in chemical terms. The brain is not a static system. It is constantly changing: in order to understand a single word, much less a sentence, it must alter synaptic connections. Sometimes this involves strengthening a handful due to the accumulation of calcium ions in pre- or post-synaptic terminals*. Other times this involves the generation of entirely new synapses through complex genetic regulatory mechanisms. It is astounding to realize that many everyday actions require synchronous activation and deactivation of entire networks of genes with perfect precision, often several times over. Nonetheless, all of this constant modification leaves, at the end of the day, more or less the same brain that started the day, thus dynamic constancy.

We may one day be able to “create” something that is capable of conscious reflection, and we may even call it a computer when the time comes, but it will not be anything that is recognizably a computer according to today’s standards. Likely, it will incorporate some aspects of biological matter, perhaps some actual living cells will be the only solution. The point of all of this is that minds are not merely computer programs, the distinction between program and hardware is nonexistent. The mind is the brain, and the brain is the mind, and nothing more.

*It is especially exciting to learn that the durations of various synaptic modulating processes correlate almost perfectly with discoveries made quite independently in cognitive psychology. For example, estimates of the durations of mono-synaptic facilitation, which can rely on the accumulation of calcium ions as mentioned above, tend to match up almost perfectly with estimates of the durations of various forms of working memory.