Stanford Neurobiology and Bioengineering Precision molecular design / synbiochem. Also @michaelzlin
Greenberg → Tsien →
Joined July 2022
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Prof. Michael Lin retweeted
I am proud of the clear, logically consistent writing we pore over by hand in the lab. AI still can't quite automate that, at least not yet. The problem is… I don't think logical consistency is valued by humans as much anymore anyway.
The problem of AI for academic writing, and why you don't notice it in your own AI writing:
AI loves to use vague language. It will produce something that’s consistent with what you want it to say. The problem is that it will also be consistent with other interpretations that you didn’t intend. This confuses readers: which interpretation was meant?
But you won’t notice the problem when you proofread your AI’s output. That's because you’re checking whether the output is consistent with what you meant (which it will be), without thinking about how it could be misunderstood (which we're usually unskilled at, due to the curse of knowledge)
Prof. Michael Lin retweeted
Public preview of BioEmu2! @MSFTResearch AI for Science’s new foundation model for biomolecular structure, dynamics and function. Open weights, MIT license.
github.com/microsoft/bioemu2
Movie: BioEmu2-simulated binding of intrinsically disordered peptide PUMA to MCL-1 receptor. 🧵⬇️
BTW the definition of disruptive research here is a paper that is cited out of proportion to the papers it cites, i.e. has a high cited/citing ratio. Just working on technology would do that. When you reference a new tech, there’s usually no need to cite what happened before
Another possibility: postdocs and young PIs develop and train on the latest methods (RNAi, CRISPR, now AI), and these provide finding that can overturn earlier conclusions, so we get large bursts of disruptive work by younger researchers, but these aren't grand paradigm shifts
The study suggests young researchers make more disruptive discoveries, and older ones fewer but more lasting ones.
Perhaps experience, time, and awareness of long-term bottlenecks might be advantages for older researchers to make the more difficult and lasting breakthroughs.
Experienced scientists produce ‘disruptive’ work less often than early-career researchers, but when they do, their innovations are more likely to have a lasting effect
go.nature.com/4sb85DD
Prof. Michael Lin retweeted
I’m so sick of reviewers using ChatGPT to review papers. It’s atrocious having to respond to the same garbage from all 3 reviewers where each comment requests 5 new analyses. Just don’t agree to review papers if it’s too much work 🤷♂️
Even if you used AI to review my paper- at least ensure the asks are genuine and then choose the most pertinent/relevant comments to include in your review? Is that too much work?
I’m sure journal editors recognize that this is a real problem but can’t do much to rectify this issue.
Prof. Michael Lin retweeted
Interesting. If I understood this correctly, TIME once again turns out to be the critical measurement axis that unlocks this mystery.
1/ We discovered something totally unexpected about the neural structure of consciousness that overturns decades of thinking on its biological basis and brings us significantly closer to the recipe for generating conscious awareness.
New preprint: biorxiv.org/content/10.64898… (led by @HesseJanis, with @FrankLanfranchi, @_conor_mcgrory, @Yuelin_Shi, and @EngelTatiana)
Prof. Michael Lin retweeted
Want to get clean calcium signals from tons of deep-brain neurons in freely moving animals?
Check our paper science.org/doi/10.1126/scia… !
We show how correcting GRIN lens aberrations transforms MINI2P performance, revealing sparse HD coding in sensory thalamus!
@ScienceAdvances
Prof. Michael Lin retweeted
Autism cannot be reduced to a simple excitation/inhibition imbalance. Inhibition is not one dial: PV, SST and VIP interneurons regulate different compartments, timescales and network states. A circuit can appear globally “balanced” yet remain computationally disorganized.
Prof. Michael Lin retweeted
In 1952, Alan Hodgkin and Andrew Huxley developed a mathematical model describing how neurons generate electrical impulses.
Using the giant axon of a squid, they studied how sodium (Na⁺) and potassium (K⁺) currents influence the electrical activity of nerve cells.
As luck would have it, my PhD advisor Mike Greenberg happened to be in Barcelona at the same time as me.
Like a science-y version of a Whit Stillman movie, we chatted about engrams and enhancers while dining over tapas and strolling through the city.
I presented ASAP voltage indicators, bioluminescent neurotransmitter reporters, and psCas12f photoswitchable gene editors... not optogenetics as defined by the Nobel committee, but still involving photons and genetic tools.
Many thanks to @IBECBarcelona for the invitation!
Was fun celebrating the recent Nobel with many of the pioneers in optogenetics at Optogen 2026 in beautiful Barcelona — a great place to reunite with old friends.
The conference brought together wide range of approaches, from optical methods to new indicators to clinical trials
Prof. Michael Lin retweeted
Institute Director Kang Shen shares congratulations to Karl Deisseroth for his recent Nobel Prize. Karl shares that he started out with an interest in developmental neuroscience and is excited to see the frontiers of the field today.
Prof. Michael Lin retweeted
Our new paper in @NatureNeuro!
Psilocybin remodels synapses differently in healthy and stressed brains, promoting new connections and limiting stress-induced loss.
We also identify distinct mechanisms for plasticity and hallucination-like behavior. #Zuolab
rdcu.be/LwdavdKQQJwa
Prof. Michael Lin retweeted
Our paper is out in Nature, congrats to Qiyu, An et al!
By stimulating ~20 motor cortex neurons carefully selected based on their activity, we could induce learned population activity and, sometimes, the movement itself, depending on the brain's state.
nature.com/articles/s41586-0…
