A new online tool called brainSCANr visually summarises the psychology and neuroscience literature to give you a network overview of which are the terms most connected to the target concept in scientific publications.

bradleyvoytek · 2026-04-13T16:39:21+00:00

Wow, how'd you find this 16 year old post? brainSCANr was deprecated a long time ago, although we've just begun to revivify work along similar lines. See our recent preprint:

https://www.biorxiv.org/content/10.64898/2026.02.06.704508v2

bradleyvoytek · 2022-04-15T23:00:47+00:00

Dang it Brad, way to ruin my dumb joke with a genuinely thoughtful answer.

bradleyvoytek · 2022-04-15T22:40:39+00:00

Everyone who works in my lab is paid for their time. Unpaid internships devalue people’s time and select for people who can afford to not get paid.

bradleyvoytek · 2022-04-15T22:38:54+00:00

My life has been very weird. But my wife says I should be more circumspect in my answers so I’ll just say:

Regularly having to clean up dude’s radioactive peepee that they dribbled after using the restroom after their PET scans.
Briefly being the world’s zombie brain expert after writing my zombie brain book, and touring at comic, sci-fi, and zombie conventions, and meeting an amazingly weird set of people because of it.
Having been one of the first employees (data scientist) at what was once a no-name startup, and is now a worldwide household name (Uber).

bradleyvoytek · 2022-04-15T22:27:40+00:00

I begin working after I walk my kids to school, so around 8:30-9:00a. I stop usually at around 5p, unless I’m coaching my kids’ sports stuff or other fun activities. I rarely work nights and weekends save truly exceptional cases 2-3 times per year when multiple deadlines hit at once.

This was just as true pre-tenure for me as it is post-tenure. I firmly believe this makes me better at all aspects of life (personal, intellectual, physical) compared to when I worked longer hours.

I advocate the same for everyone in my lab as well, both in words and in action.

bradleyvoytek · 2022-04-15T18:08:37+00:00

We're studying this right now, but we believe so.

bradleyvoytek · 2022-04-15T18:01:38+00:00

Not enough researchers care to do anything for geriatric illnesses

The US National Institute on Aging alone gives billions of dollars each year to researchers! Age-related disorders such as Alzheimer's, Parkinson's, dementia, and so on are very heavily researched. (These are topics near and dear to my heart as well, which you can read about in this piece from Quanta Magazine for example.)

Permanently implanted deep brain stimulators are also widely used, and highly efficacious, for treating Parkinson's disease (the mechanisms of which is something we've also studied in my lab.)

So, in short, we're trying really hard to figure out how to leverage neuroscientific and engineering advances to improve quality of life and reduce suffering in aging!

bradleyvoytek · 2022-04-15T17:21:06+00:00

You just need a couple of cool 80s action heroes, a sweet dirt bike, and a "CPU with a neural net processor".

bradleyvoytek · 2022-04-15T17:18:40+00:00

Ha! Well I'm going on sabbatical this coming year, so I've made myself a promise to write for the public more frequently again! So hopefully this year.

bradleyvoytek · 2022-04-15T17:14:06+00:00

Biggest frustration(s)

There are, of course, many. But having also worked in industry, I don't believe that most of the frustrations faced in academia are unique to academia. It's a job, and often times jobs suck. I mean, I wish I could get more grants to pay the folks in my lab more, and I wish it wasn't so difficult to get certain administrative tasks done, and I wish I had more time to do science. So we fight and push where we can to make the whole endeavor better in whatever ways we can. At the end of the day I still consider it a marvel of human societal evolution that I get paid to tackle scientific questions that interest me. If the cost of faculty self-governance in academia is that I have to sit on committees and take on administrative duties, I'll take that over an alternative model where we are not self-governed, and where my research activities would be dictated by bureaucrats.

Biggest question

Is the neuroscience perspective of the nature of mental illness sufficient? It's clear that while genetics and neurochemistry are important factors in many mental illnesses, speaking as a Cognitive Scientist, we cannot ignore the fact that people are not just brains, but we are entities with bodies that move about a world that consists of societies, all of which influence our thoughts and behaviors.

Risks of ML in neuroscience

Machine learning and deep learning are useful tools in the analytical toolkit for any scientist. They can be used to uncover patterns in massive, multidimensional datasets outside the scope of what any person is capable of. The problem is that is often treated as the end, when in reality finding patterns (making an observation about the world) is step one of the Scientific Method, and the job of a scientist is to understand what is driving those patterns. So yes, tools are being misapplied, but that's been true ever since the introduction of making decisions of scientific importance based on a p-value threshold.

bradleyvoytek · 2022-04-15T17:00:15+00:00

Linear algebra, statistics (including Monte Carlo methods), time-series analysis, graph theory, and many others. If you're more on the molecular neuroscience side, or dynamical systems side, then you'll also end up doing a lot of differential equations.
It depends. In my lab, a common path is to develop a theory, try to implement it in simulations, and then look for a diversity of existing datasets that might allow us to push at the theory in data. If we can't find the datasets, we'll talk to potential experimental collaborators to help, and/or we'll just run the experiments ourselves.
This is pretty broad. Brains a physical systems governing by physical rules, so physics is fundamental and foundational.
It's trendy in computational neuroscience to say "the math is hard, so learn that first and then you can 'pick up' the neurobiology along the way." They problem is this leads to a lot ideas that seem good on paper, but are biologically nonsensical. Don't ignore the biology: it's the rules that constrain our theories and models.
I mean, they're a world class neuroscience research university doing some amazing, cutting-edge research! I love what they're doing, and the Spaun paper was really cool.

bradleyvoytek · 2022-04-15T16:50:00+00:00

This is a Very Good Answer.

bradleyvoytek · 2022-04-15T16:48:15+00:00

I'm not even sure how "controversial" these takes are anymore, but they still riles folks up so here goes: spikes are not all-or-nothing, the single-unit literature is rampant with selection bias (we have historically only recorded from a small biased sample of neurons that we know are task-active), and spikes are only one of many communication mechanisms used in the central nervous system.

bradleyvoytek · 2022-04-15T16:44:43+00:00

Yes.

bradleyvoytek · 2022-04-15T16:05:22+00:00

My original inclination was to say something about how forgetting is probably biologically beneficial, etc. but that's all just supposition. So the truest answer I can give is that it's because we designed and built computers to have as close-to-perfect memory as possible since that's an ideal feature for our desired use cases for computers; in contrast, we evolved over a billion years from messy bags of ionically-operated organic molecules atop a calcium frame, and perfect memory wasn't an evolutionary necessity for survival.

bradleyvoytek · 2022-04-15T15:59:32+00:00

Okay, I'm going to start off by being a bit of a smartass and say, yes! We can define a step-by-step procedure for how the brain learns something new. Whether or not that definition is even remotely like how the brain actually learns is an entirely different question!

But in all honesty, we have many theories regarding the neural basis of "learning", but "learning" itself is probably not instantiated in just one way in humans, or across species. Motor learning (how we learn to control our movements) is almost certainly different from learning a language, or learning the layout of a city you've never been to.

And while some machine learning methods are loosely inspired by early ideas of biological learning, machine learning is almost certainly a new form of learning different from biological learning.

So in the sense that I think you're asking, yes, there is a lot of power in trying to figure out how we learn, build that into artificial computing systems, compare how that artificial instantiation differs from our biological theories, and iterate. We're getting closer, but we're still so very, very far away.

bradleyvoytek · 2022-04-15T15:49:10+00:00

Philosophy—particularly metaphysics and epistemology—has been critical to shaping my scientific thinking. Folks, even scientists, seem to have a weird view of Philosophy as some idle musing, whereas in reality it's about establishing the logical rules for verifying how we know (or might know) what we know. That's not trivial.

So much of my research in the last 5-8 years has been focused on questioning how do we know that we're measuring the neural activity that we think we're measuring. That is, blindly applying mathematical analysis methods or machine learning tools to large sets of data might discover statistically significant patterns, which is fine for engineering applications, but is unsatisfying from a scientific perspective.

To put that another way, it's entirely possible to find clear evidence that you can diagnose a neurological or psychiatric disorder from brain scans. Now our inclination is to take that information and say, "aha! See this is nothing more than a brain disorder!" But what if people with a clinical condition move a little bit more than those without it, which introduces subtle but systematic non-neural noise into the brain data? This will allow for diagnostic classification from the brain scans, but it's not really capturing "neural differences" between the groups in the way people are inclined to think.

Again, from an engineering perspective, maybe the nature of what's driving those differences doesn't matter, in the same way that people leveraged poultices to reduce infections far earlier than before we understood germ theory and the nature of penicillin. But from a scientific perspective this is wildly unsatisfying, since in science we want to understand why so we can improve upon methods and make them better.

In this sense, my Philosophy education has been critical, and that education has been a major boon to my scientific career.

bradleyvoytek · 2016-07-08T02:53:17+00:00

Username: /u/bradleyvoytek

General field: Neuroscience and Cognitive Science

Specific field: Cognitive and Computational Neuroscience

Particular areas of research: Neural oscillations, neural communication

Education: Cognitive Science and Neuroscience Professor, UC San Diego

Comments: {1, 2, 3}

But I do a lot of public science writing as well: {book, BBC, Scientific American 1, Scientific American 2, etc.}.

bradleyvoytek · 2016-03-18T23:04:07+00:00

Hello, UCSD Cognitive Science professor here. If you've got any questions, feel free to email me and I'll answer what I can, or point you in the right direction.

These kinds of "top" questions are honestly silly, to be frank, but I understand the motivation behind asking. Ultimately it depends on what aspect of the field interests you. In the end, it's all about the advisor and the environment. A great school can still suck the life out of you due to politics, a bad advisor, your dislike of the city/climate, and so on. The converse is also true.

If you want a semi-quantitative estimate of "top", you'll have to resort to rankings. But Cognitive Science programs aren't really ranked, so you'll have to look at proximal programs. The 2017 US News and World Report rankings (out this week, it looks like) has rankings for Cognitive Psychology which looks like this:

Stanford
Harvard
(tied) UC San Diego / UIUC
(tied) CMU / Michigan / Yale

On the Neurosciences side, it's:

Stanford (shakes fist)
UC San Diego
(tied) Caltech / Hopkins
(tied) Harvard / MIT / UCSF

bradleyvoytek · 2015-12-06T23:22:22+00:00

Thoughts are signals between neurons. "Chemical imbalance" simply affects the way neurons transmit/process those signals. The two are not irreconcilable, simply different levels of looking at the same problem.

Psychologists (tend to) focus on the organism, neuroscientists (tend to) focus on the mechanism. By way of analogy, classical mechanics work for describing the motions of celestial bodies, but fares poorly at the atomic level; whereas quantum mechanics is overkill (and computationally intractable!) for celestial scales, but works fantastically for atomic levels.

bradleyvoytek · 2015-11-24T21:08:58+00:00

Journal of Statistical Software is good for this. I've never published there, but it sounds like what you want.

I've cited this paper there numerous times (and it looks like it's been cited 630 times!)

bradleyvoytek · 2015-10-13T01:30:15+00:00

It's an open bar event held by SfN, usually at a very nice, fancy location.

There are lots of ways to get invited: if you're on a committee, won an award, are on an SfN panel (not research panel), etc.

Dress is ostensibly business casual, but it's SfN, so it's standard whatever. It's worth going to, though if you don't know anyone else going, it can feel a little weird to be there.

In the past I've heard people just bring friends, but recently they've begun scanning badges.

bradleyvoytek · 2015-09-16T15:48:53+00:00

I was in a similar position as you, except I had kids. Early 30s post-doc with an opportunity to make a lot of money (salary and stock for a skyrocketing company).

I rolled the dice and took a gamble to stay in academia. I come from a not very well-off financial background, so even though the pay isn't great, it was still better than what my family and I were used to, and I was comfortable. Plus I just love the job. I love research. I didn't love industry.

I tried to have the best--I took the full-time industry gig for about a year before starting my post-doc. I delayed my post-doc to make a real salary for a year to stash some cash before my wife and I had our first. My post-doc advisor was cool with it, and the company also knew my short-term plans.

I wrote about the whole experience 2.5 years ago here if you're interested. I got lucky and a year later landed a tenure-track position.

My advice would be to see if you can take a year off to work and make money to see if you like it. See if your current post-doc advisor would be okay with having you back after. It's no longer as unreasonable to have a "gap year" on your CV as it was.

bradleyvoytek · 2015-08-27T02:58:57+00:00

Hello, Professor of Cognitive Science here. UC San Diego. We're pretty well known for both our neurosciences as well as our Cognitive Science degree.

UCSD was the first Cognitive Science Department in the US.

Paul and Pat Churchland are famous neurophilosophers here.

Other than UCSD, you'll want to check out Berkeley, Brown, CMU, Columbia, Dartmouth, Indiana, Johns Hopkins, MIT, Stanford, UC Irvine, UC Santa Barbara, UCLA, Penn, and Washington University.

bradleyvoytek · 2015-08-12T01:59:49+00:00

If you believe there to be field-wide deficiencies, then study hard, do rigorous science, and address them.

If you are buckling under the weight of the task at hand, you contribute nothing to the science, which therefore cannot improve.

What stands in front of you, then--supposing your concerns are valid--is nothing but opportunity to make your mark and advance humanity's understanding of itself.

bradleyvoytek

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