@nicolecrust.bsky.social
Mood & Memory researcher with a computational bent. https://www.nicolecrust.com. Science advocate. Prof (UPenn Psych) - on leave as a Simons Pivot Fellow. Author: Elusive Cures. https://press.princeton.edu/books/hardcover/9780691243054/elusive-cures
Oh wow. I know people here have THOUGHTS. Write them up & submit!!
I love that all essays have to be public before entering. This is exactly the type of conversation we need more of. (Also cash prizes + philanthropy is listening)
Now which on my list should I pick 🤔?
astera.org/essay-compet...
I *absolutely love* this take: lean into your uniqueness to be a force that helps prevent the scientific community from settling into a giant local minimum.
After all, nearly everything the brain does is fascinating!
That said, here's the seed I would like to plant for the Cosyne community:
Might there be ways to better maximize the nexus between what you are curious about and what benefits society,
filling in the holes in *foundational* knowledge that most desperately need to be filled?
Everyone at Cosyne can give a first person account of why they study their question, many of which begin with "*I* am curious to understand XXX."
That might lead to the answer: Understanding the brain to understand it is impactful in-and-of-itself. I believe in that too. /4
As always, you-do-you! There are no wrong answers to the question, "What do you study?"
I'm asking a slightly different question: If you answer your question, what will that answer be good for? 😊 /3
just last year, the keywords "emotion", "mood", and "affect" were not on the list (only "fear" and "psychiatric disorder").
If we step back and ask, "What most desperately needs to be figured out by systems neuroscientists?" those are high priorities. Why aren't they here? /2
Ruffling some feathers, it's fascinating to ask: What forces drive this plot?
To what degree is our community targeting important challenges and creating impactful solutions vs caught up in the inertia of curiosity and opportunity?
For instance, ... /1
I tracked every keyword in 22 years of Cosyne abstracts to map how computational neuroscience evolved — from Bayesian brains to neural manifolds to LLMs — and where it's heading next.
Fascinating. Thank you for it.
Well deserved @judithfan.bsky.social!!
OK, I have a US jacket design now. I think it looks rather handsome.
The book is published in the autumn, in both the UK (Little Brown) and US (University of Chicago Press).
Terrific cover. Layers; stories within stories; nuance. "Breaking physics" sounds intriguing.
I'm looking forward to reading it.
Forgot to x-post!
Honored to share this Neuron interview in which I discuss my childhood, getting a PhD, and RNN reverse engineering and its application to brain data. I also talked about my industry/academic life.
authors.elsevier.com/a/1mjFW3BtfH...
Check out our latest research drop! We show BLA dopamine signaling encodes the emotional weight of sensory transitions, but not the associative strength or value of stimuli. These signals dynamically rescale when the learning context changes: "this matters most!" www.biorxiv.org/content/10.1...
Ditto.
Fascinating convergence between this @thetransmitter.bsky.social piece by @lucinauddin.bsky.social and a recent Neuron piece by @sussillodavid.bsky.social. Is this the (interim) future of US academia?
www.cell.com/neuron/fullt... 🤔
Nicole: Don’t argue with people on the internet; don’t argue with people on the internet; don’t argue with people on the internet.
It is a waste of your time and energy.
Nicole: Great advice, thank you! ❤️
That said, what you've pointed to is the way to proceed in brain research: iterate between natural variation in brains (in health and disease), modeling the phenomena of interest & predict the efficacy of interventions.
While one can study such things in a modeling framework, there's always the question: how well does the model capture this slice of reality (like disease causes & resiliance)?
Great Q. The equivalent is impossible/unethical: 1) create brains with different known interdependant properties & study their stability; 2) introduce known disease-causing perturbations to see what factors lead to suseptibility/resilience, 3) repeat each set many times & compute probabilities.
I find work like this inspiring because it reframes the space of possibilities. We can’t do the equivalent of this with brains. What should we do instead to get to similar endpoints? That we can begin to map out (for a fresh perspective).
Also! When I throw the predator/prey (Lotka–Volterra) equation on a talk slide, I question whether 1970s ecology is really a great inspiration. L-V lives on in 2026 Nature papers!
(THIS is how you study a complex dynamical system when you can pull many levers and have near infinite capacity to repeat experiments).
H/T to the @quantamagazine.bsky.social podcast (16 min, worth it!!)
www.quantamagazine.org/podcasts/
Incredible! The ultimate experiment. If we could only do something like this for brains, it would go *so far* toward understanding brain and mental conditions.
www.nature.com/articles/s41...
For sure. Write a book, rip up half of it, write it again. Saying it's "uncomfortable" is a mild way to put it, and, as you say, those re-dos are an important part of the process. It's a great message to send, especially in an era that leans too far toward the praise of "productivity".
I agree & not just b/c of the people-pipeline issue. In this era, a 1-2%ile grant/lab is typically a technical tour de force test of a well developed idea. Novel, transformative ideas score lower upon first reception (reviewers: "Maybe, but ..."). Cutting at 1% eliminates the idea-pipeline too.
And this is how we know you’re deep into nonfiction book writing and all that comes along for the ride, like taking communication literally 😉.
