Doris Tsao

I am deeply excited to share that I will be joining @AsteraInstitute to start a new effort to understand how the brain generates consciousness and intelligence.

The Lin Lab is hiring! We're seeking motivated postdocs for projects on voltage imaging and optogenetics in the brain. If you're excited about using new methods to undersatand and correct brain diseases, working together with other neuroscience labs at Stanford, drop us a line!

One thing great stories share is that they work on multiple levels. This is definitely that: mars, purple paint, and how to become a better scientist 🤩

@alfairhall Love your list! I will add: Liping Wang discovering that messy mixed selectivity of single neurons in PFC can be understood as beautiful geometric subspaces for working memory.

In systems neuroscience, this is simply not the case. Paradigms are challenged and updated all the time.

The conclusion that the brain is not OFF during anesthesia is very important, and adds to what we already know about preserved activity of autonomic feedback circuits during anesthesia. Neural processing can be very complex without being conscious. Whatever produces consciousness must be a very specific property of brain dynamics.

Those heat maps show the difference vs baseline. Most striking, the fold-change in beta-gamma band power, which many have associated with ket's antidepressant mechanism, are virtually identical with and without anesthesia. The brain is not "off" during anesthesia.

Lots of folks seemed PRETTY sure that giving ketamine during general anesthesia to "block the trip" was pointless, anesthesia silences the brain and ketamine won't work. We checked. Just out in @JAMAPsych. Below: frequency heatmaps over the course of 40 min, + and - anesthesia:

Thank you, Stan! Inspired by our recent dinner conversation, I just did some vibe coding :) So, the big problem with answering your question is the limited number of reactivated neurons per session (dream: redo with Neuropixels). k neurons can span at most a k-dimensional feature subspace. So for each session, Claude picked the neurons that were both axis-tuned AND reactivated during imagery (1–7 per session, 43 in total across all sessions), computed each neuron's preferred axis (50D vector, from viewing responses to all 500 stimuli), stacked them, and did SVD to find an orthonormal basis for the k-dimensional subspace those axes span, ordered from most to least collectively represented (Axis 1 = the direction in 50D feature space onto which the k neurons' preferred axes collectively project most strongly, with subsequent axes being orthogonal directions of decreasing collective projection). Note that these axes differ across sessions since they depend on which specific neurons were recorded that day. It then learned a linear decoder W from the viewing responses of just those k neurons across all 500 stimuli, using leave-one-out cross-validation. This same W was then applied to: the viewing responses of those same k neurons for only the stimuli shown during imagery (row 2) and the imagery responses of those same k neurons (row 3). Critically, rows 2 and 3 use only 1–7 neurons per session, so the decoded subspace is severely limited. The fact that significant decoding is nevertheless observed across multiple axes in imagery (row 3) is therefore a conservative estimate of how well the visual code is reinstated. Long story short: to the extent we can test with the available neurons, imagery signal appears present across all axes, not just the dominant ones! And in fact axis 1 is surprisingly weak. [Top row shows viewing decoded from all 43 reactivated neurons pooled across sessions (500 stimuli, LOO)] I am trusting Claude did all this correctly :)

@doristsao @dileeplearning @WadiaVarun @UeliRutishauser Congratulations for a fantastic study! Are all object axes equally present in imagery, or can you see if higher-level, more abstract ones are somehow privileged ?

This is the strongest ephys evidence so far for a generative model in the brain that I know of. Congratulations @WadiaVarun! Wonderful collaboration with @UeliRutishauser on science that could only be done in humans. And please check out Fig. 5FG. This is new since biorxiv and really surprised me: the mean response to imagery and viewing is actually the same & there are many cells that respond only during imagery--challenging the idea that signal strength is what distinguishes reality from imagination.

Just a reminder of @AsteraInstitute's open essay competition about identifying and overcoming scientific bottlenecks. Deadline for entries is May 1!

Great to see this on X. This is something I created during my PhD time 20 years ago.

@ChongxiLai Thank you, Chongxi!

Imagination is one of the brain’s most remarkable capabilities. With such a rich human single-neuron dataset when asking them to imagine, this paper looks like a must-read! Congrats the entire author team, with a special nod to @doristsao

@BIONIC_Lab @CarnegieMellon Can I join from zoom?

Next Wednesday, April 15, 1–2PM ET I'm giving a seminar at @CarnegieMellon on why BCIs fail, and why the answer isn't what most people think.

I will be giving the Martin Meyerson Faculty Research Lecture tomorrow 4/8 at 4 pm at UC Berkeley. This is a public lecture open to all. Revised title is: "Representing the visual world: from faces to consciousness" facultylectures.berkeley.edu

The brain uses 20% of your body's energy with 2% of its mass. Implant an electrode, and you sever the blood vessels delivering that energy. Nearby neurons don't die. They go silent. They're rationing fuel.

@maxhodak_ @KordingLab Yes, I loved that line from your talk for making stark that there would be no value without consciousness.

@KordingLab @doristsao yeah i think she was paraphrasing my comments at 2:00 from this talk youtu.be/DI6Hu-DhQwE?t=…

What do you all think? "You cannot align a system to human values without fundamentally understanding how those values are implemented." -James Fickel et al. "The existence of experience is the universe's sole source of value." -Max Hodak

Because: 1) I believe in the power of understanding in general, 2) I think evolution is still smarter than us, and humans are the one system whose values we know are aligned to human values, 3) the bits and pieces I've seen about AI alignment through mech interp (e.g., alignment.anthropic.com/2026/psm/) are fascinating but don't inspire confidence in our ability to control...the take home message I get is that we need raise LLMs like good children and then hope and pray that they will end up with mostly good personas. A deep understanding of how value is generated in the human brain will not only help AI alignment, but also education of human children, which is not exactly yet a science either.

@doristsao Why do you think that we need to know how human values are implemented to align to them?

"You cannot align a system to human values without fundamentally understanding how those values are implemented." -James Fickel et al. "The existence of experience is the universe's sole source of value." -Max Hodak If the above statements are true (and I think they are), it's critical to understand how experience, i.e., consciousness, is implemented.

We show face patches implement the following code through recurrent dynamics: Detect face If (face found) Discriminate face else Continue to detect face IMHO, our paper conclusively resolves a debate that has raged since I was a graduate student, about whether face patches are specialized for processing faces or not. It turns out domain-general folks were right early on, domain-specific folks were right later in the response. So proud of @Yuelin_Shi and the entire team!

@YifeiBNU1 Yes, please stay tuned for opportunities at Astera Neuro! We are just getting started

@doristsao Will there be summer internship opportunities for PhD students? very exciting research area!

Come be my colleague! Apply to the Astera Fellows program! You will get a great salary AND very generous resources to start your own independent research program. A core area of interest is neuroscience & AI. Please RT