Mazviita Chirimuuta

People often said machine-like reflexes and making comparisons with sort of Newtonian decomposition theory.

With the computational framework, you have an actual machine, a digital or analogue computer, which could be compared with brain processes.

I mean, cybernetics is an interesting stage along the way because they were buildings of little devices which had some degree of autonomy made up of computers.

and supposed to be emulating versions of negative and positive feedback as hypothesized to occur in the body.

But yeah, I would say at the core of this research idea is that if what's going on in the body is ultimately a mechanistic process, then by redoing engineering with this non-living system, which is capturing some of the core operating principles of

that we find in biology, then we can use that device as a map, as a resource to then reinterpret what's going on in the biological system.

You saw that with, for example, McCulloch and Pitts in their 1943 sort of landmark paper of interpreting neuronal cells as logic gates

and then saying, yeah, you could build a computer out of neural nets.

This is the origin of neural nets as we know them today.

This is the birth of the idea.

But then using that notion that neurons are

logic gates to then interpret what's going on in physiology.

So what I describe in chapter four of the book is a sort of back and forth thing of making devices which are somewhat inspired by biology and then using those then as the lens through which to review biology again.

And I say that the advantage and the appeal of this process is that it allows you to, or gives you a kind of license to ignore so many things that are happening in the brain and nervous system, which are just not shared with non-living machines.

Like all of the biochemistry, all of the ways that neural tissue

is shaped by vasculature and interacts with the immune system and all of that sort of background stuff that if you're a theoretical computational neuroscience, you can say, I'm only interested in the computational properties of the brain.

I don't need to care about all of that messy biological detail.

So it gives you...

kind of tunnel vision, which a scientist can be fine to have tunnel vision.

You can't take in everything at once all of the time.