iiinova — where your digital self keeps evolving

Richard Gao @rdgao.bsky.social · 10/06/2026

it took me so damn long to write this thing that the field actually became real in the 2.5 years hooooly anyway, here's another book: 100% grass-fed human-written down to every single letter, though probably for AI consumption only at this point. www.rdgao.com/blog/2026/06...

rdgao.com

Beyond #NeuroAI, we need #AI4Neuro—and we’re going to suck at it (at first). [Part 3]

The fundamental principle of using AI for science is that it can help us do some things extremely efficiently, but it usually requires an ‘oracle’ or verifier. I’m of the opinion that we simply don’t ...

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Richard Gao @rdgao.bsky.social · 27/04/2026

the holy trinity: beach tapas and ephys reproducibility

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Richard Gao @rdgao.bsky.social · 20/04/2026

holy crap you guys are writing these faster than I can read them. super cool, this was the dream experiment / data for us in 2016, and great to see more nuances parsed out with this resolution of data!!

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Richard Gao @rdgao.bsky.social · 31/03/2026

I'll push your supplements and gifs

Richard Gao @rdgao.bsky.social · 31/03/2026

not yet, not before I get my Stanford affiliation

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Richard Gao @rdgao.bsky.social · 31/03/2026

oh I think I will like this one very much...except I'm giving a seminar on the same day, potentially on the same topic lol

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Richard Gao @rdgao.bsky.social · 22/03/2026

this is literally the most beautiful thing I've ever seen

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Richard Gao @rdgao.bsky.social · 20/03/2026

damn that's a crisp story, very cool

Neuromatch @neuromatch.bsky.social · 18/03/2026

Reposted by Richard Gao

We are building out a new curriculum day for our #ComputationalNeuroscience course focused on time series analysis and #SignalProcessing. We're looking for 5-10 volunteer contributors w #CompNeuro & #DSP experience. This is a #volunteer position. Learn more & apply: neuromatch.io/volunteer/

Real expertise.
Real students.
Real impact.

Volunteer to create Computational Neuroscience course material on time series analysis and signal processing.

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Richard Gao @rdgao.bsky.social · 17/03/2026

And even that Claude did most of the work why do they even pay you

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Reposted by Richard Gao

Mattia Chini @mattiachini.bsky.social · 17/03/2026

New paper out in PLOS Computational Biology! We introduce iSTTC, a robust method to estimate intrinsic neural timescales from single-unit recordings. Congrats to Irina Pochinok for leading the project! Package: github.com/iinnpp/isttc Paper: journals.plos.org/ploscompbiol...

github.com

GitHub - iinnpp/isttc: iSTTC: intrinsic neural timescales estimation

iSTTC: intrinsic neural timescales estimation. Contribute to iinnpp/isttc development by creating an account on GitHub.

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Richard Gao @rdgao.bsky.social · 13/03/2026

Oh cmon guys I’m nice to you both

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If you're interested in contributing to this global summer school and get some teaching-related experience, shoot me a DM or email with what you'd like to help with and roughly how much time you can commit from now to June. I'm at cosyne too so happy to chat there, at the NMA booth or otherwise!

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For this year's Neuromatch Computation Neuroscience course, the Curriculum Team is adding a new Day 🥁🥁🥁 Time series analysis and signal processing! We're looking for 5-10 content contributors with relevant neuro+DSP experience for various tasks: co-Day Lead, video, slides, code tutorials, etc.

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* cue banger entrance music *

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Richard Gao @rdgao.bsky.social · 09/03/2026

get paid to teach and learn about computational neuroscience (and other cool topics), highly recommend. If you're considering it, don't hesitate, just go for it!

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I'd say we hate splitters and root for the lumpers because unifying * p r i n c i p l e s *....but yeah, sadly, data don't lie

Richard Gao @rdgao.bsky.social · 09/03/2026

I've often had very pessimistic answers for this, but I think "new data shows that brain is much more complicated than we originally thought" is actual progress. e.g., cortex is not homogeneous repeats of the same columns, cells are not all the same, it's not just single-neuron tuning curves, etc.

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Richard Gao @rdgao.bsky.social · 03/03/2026

I'd have nothing to talk about on this episode if not for my paper co-authors in the @mackelab.bsky.social, as well as Pedro, Jan-Matthis, and Michael paving the way with SBI.

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Richard Gao @rdgao.bsky.social · 03/03/2026

I'm extremely grateful for Gaute for having me on the show, especially considering the roster of previous guests. All the work from his group advancing our understanding of the LFP has influenced me since day 1 of my PhD. They say never meet your heroes but I think this time it went pretty good.

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Richard Gao @rdgao.bsky.social · 03/03/2026

Once you get past the first 5 minutes of me bumbling around clearly in need of media training, we settle into a nice groove talking about fitting mechanistic models, ML/AI for neuroscience, underconstrainedness vs. degeneracy, and its potential benefits for biology (plus some good chuckles).

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Richard Gao @rdgao.bsky.social · 20/01/2026

dang you're a real fan because that's a solid who-he-play-for

Richard Gao @rdgao.bsky.social · 20/01/2026

I woke up today and the Detroit Pistons are first in the East. what year is this??

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Reposted by Richard Gao

Natalie Schaworonkow @nschawor.bsky.social · 16/01/2026

main goal for this year: find a new job! 🙂 looking for a role with fun & complex technical challenges & within a great community. my main expertise is in signal processing/EEG/MEG, but topic-wise I am quite flexible. science/industry both great! starting mid-year. nschawor.github.io/cv

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Richard Gao @rdgao.bsky.social · 15/01/2026

please only do bird research from now on

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Richard Gao @rdgao.bsky.social · 15/01/2026

get in before the spots run out, otherwise put your money in the betting pool

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we'll take what we can get

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I also had a similar interpretation as you though, that as a first approximation, "pattern-y"=dimensionality, such that spikes destructively interfere. same argument as spatial alignment of neurons and makes sense if one knows LFP, but I like this paper because it lays it out quantitatively

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I think you have a much more nuanced view of spikes and LFPs than the strawhumans in my head Ben

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