Neuroscience as intuition

A reflection 1.5 years after my first blog post

Hello, I’m back after a semester off from blogging! I have a plan for upcoming ✨science✨ posts, but in the meantime, my buddy Luckey invited me to submit to the Unlocked series. I’m using it as an opportunity to write a personal reflection I’ve been putting off for a while.

A friend’s attempt to summarize my research.

I wrote my first blog post during my transition from computer science to neuroscience in my PhD. At the time, neuroscience felt religious to me, and I struggled to understand how neuroscientists often have such immutable convictions in the face of so much conflicting yet reputable evidence¹.

Even in computational neuroscience, which appeared more concrete to me than experimental neuroscience, no one really agrees on anything. Unlike machine learning models, it is far less clear what it means for a model of the brain to be “useful”². Should the goal be to fit to recorded neural data? Even if a model predicted spikes with perfectly, would we understood the brain any better? On the other hand, if we had a principled model that did not fit data as well, would that be useful? One could go around in circles forever arguing like this.

Further contributing to my confusion was the fact that I had not yet mapped out the literature and history of the field for myself. I didn’t know what was obvious or accepted, even from my lab’s point of view. I certainly wasn’t ready to form my own beliefs, and as a result, didn’t have a good idea of the research questions I was interested in. I wrote the first blog post with the naive hope that verbalizing my lack of clarity about the field would help me make more sense of everything.

1.5 years later, I am only slightly less naive and only making a little more sense. The biggest change is simply that I have spent much more time reading, talking, writing, and thinking about the brain. Just like practicing an instrument, playing a sport, or learning a language, I feel myself starting to develop proficiency in this new skill of… neuroscience? Let me explain what I mean.

In the past, questions during presentations or even meetings would often send me into a panic. They didn’t have to be particularly hard questions, just ones I hadn’t yet thought too much about. Attempting to answer involved straining through complex logic, or tortuously sifting through figures and equations in my head. I could not understand how people were able to answer hard questions on the fly, or look at a plot and immediately understand what was going on. It was like they were fluent in a language, and all I could do was string together broken phrases. Was I just too stupid to be doing this?³

Through a slow and agonizing process of pushing my research forward and preparing for my qualifying exam, I managed to start orienting myself. I won’t go through the gory details, but I treated it like how I used to practice violin, or prepare for coding interviews in college. I’m sure everyone’s process is different. But as a result, I’ve started to feel the freedom of moving through a new world, truly like developing fluency in a language. I am more comfortable thinking on my feet, as if concepts are flowing around me, and I just need to grab what’s already there. I don’t have to think so hard all the time.

In other words, I have started forming my intuitions about neuroscience, or at least the subfield I’m focusing on now. For example, someone may ask a confusing question about my project, and I can immediately understand their underlying misconception. Or someone brings up an idea, and a simulation I could run with my model will pop into my head. These are things I couldn’t do before, at least not immediately, through reasoning alone.

A lot of this might seem obvious, and I feel a bit silly writing some of this down. But the reason this feels so profound for me is that I have never experienced this in an academic setting. In undergrad and before grad school, I kept hopping around different disciplines and labs to figure out what I wanted to do. I realized that finally, now at the end of my 4th year, this is the longest I’ve ever spent in one field. I am maybe starting to become an expert in something, for the first time?

I can start to see now that after decades of being in a field, a scientist’s intuition might look a lot like what I called religion, from the outside. Their intuition lets them feel that this problem is a good problem, that this approach is the right one. Even if there is evidence that seems to contradict it. Intuition stems from deep understanding, honed from decades of training. Although it may have started there, it goes beyond rational, quantitative scientific thinking.

In Mathematica, David Bessis argues that contrary to popular belief, mathematical ability is not an intrinsic gift certain people are born with. Rather, it is about developing intuitions in your own way, driven by the desire to understand. Although we’re traditionally taught that math is symbols on a page, that’s just one way to communicate intuition. You could also think about math in terms of of something we all have strong intuitions for, such as the physical world. Terence Tao famously rolled on the floor to think about a problem:

Early in his career, he struggled with a problem that involved waves rotating on top of one another. He wanted to come up with a moving coordinate system that would make things easier to see, something like a virtual Steadi­cam. So he lay down on the floor and rolled back and forth, trying to see it in his mind’s eye. ‘‘My aunt caught me doing this,’’ Tao told me, laughing, ‘‘and I couldn’t explain what I was doing.’’ (NYT)⁴

There is something very profound about human intuition, and scientists clearly rely on it to guide them. What would science look like without intuition? Unfortunately, understanding intuition itself is a hard problem, certainly harder than next-token prediction (does AI have intuition?). Regardless, it’s part of what makes us human, and more interesting and beautiful than a reasoning machine could ever be.

Let me connect this back to my original point. Similar to religion, intuition is separable from logic and reasoning. Perhaps someone’s intuition is so strong that no evidence they’ve seen so far can convince them otherwise. But ideally, unlike in religion, we learn something when we’re proven wrong. It deepens our understanding, and we modify the intuition accordingly. When someone’s intuition is correct, it may lead to discoveries that would have taken orders of magnitude longer through reasoning.

So for now, I guess I’d revise my opinion from neuroscience as religion to the less extreme neuroscience as intuition⁵. Through my own attempts to grow as a scientist and seeing others’ processes, I’m realizing how important intuition is in science, and how I might go about developing my own. Maybe these convictions that I see in neuroscientists aren’t as bizarre as they initially seemed. Maybe I will be there too, one day (for better or worse).

This is still just the beginning for me, of course. I still don’t feel comfortable calling myself a neuroscientist (maybe I never will) or a vision scientist (my department, technically), but I’m also definitely not a computer scientist. Whatever I may be, my focus now is not to form beliefs, but to hone my intuition. I guess, until I find a better reframing by the next reflection post.

1. One concrete example is the fundamental debate between using artificial versus natural stimuli to characterize the visual system. I think we are trending toward natural(istic) stimuli as a field, but there are still well-respected scientists on either side!

2. I suspect this statement could get me in trouble with ML people 🫣, but that’s another conversation.

3. I don’t know, jury’s really still out on this one.

4. He wrote about it more here.

5. More cynically, you could also call it neuroscience as vibes. But everyone’s into vibes these days, so maybe there’s no problem with that.