Srividya Pattisapu

I have just arrived at @cosynemeeting.bsky.social ! During my flight, as I thought about opening remarks (and had a glass of wine), I got to reflect on why I love neuroscience. Maybe other folks are doing the same and would like to read or add, so I thought I'd do something unusual and share!

my local park is full of hundreds of snow sculptures and someone has been adding museum labels

Super fun workshop, and very warm organisers at #FlatironCCN! Time for my umpteenth code revamp (totally worth it!)

@elife.bsky.social ftw!!

How do we make sense of scientific literature that is growing explosively to the point where no-one could read all the relevant papers, and is contaminated with fraudulent and LLM-generated papers? I think that science isn't currently equipped to deal with this, and we need to. #science #metascience

Yes, this! I used em-dashes all the time and they made me so happy. They break a sentence in ways that commas just cannot do—aesthetically speaking—and now I worry that someone will think I used an LLM to write this post too. Ugh. LLMs use it because, well, they are trained on human data, right??

This paper has now been published in PRX Life! journals.aps.org/prxlife/abst...

In this work I developed a scaling theory for spiking neural populations using a renormalization group approach -- the 1st, to my knowledge, applied to models of spiking neurons. See the thread for a brief summary.

Jane Goodall, primatologist and friend to chimpanzees, dies at 91 She used her global fame to draw attention to the plight of dwindling chimpanzee populations and, more broadly, to the perils of environmental destruction.

Legendary primatologist Jane Goodall has died at 91:
www.washingtonpost.com/obituaries/2...

Two flagship papers from the International Brain Laboratory, now out in ‪@Nature.com‬:
🧠 Brain-wide map of neural activity during complex behaviour: doi.org/10.1038/s41586-025-09235-0
🧠 Brain-wide representations of prior information in mouse decision-making: doi.org/10.1038/s41586-025-09226-1 +

Deeply chilling.
"At some level, AI does seem to separate good things from bad. It just doesn’t seem to have a preference."

This "Everything, Everywhere, All at Once" simultaneously excites and terrifies me. Further evidence that we need to relegate the 'brain region = specialised function' philosophy to the status of an artefact from the times when we were only able to record from one brain region at a time.

😂😭

But, well, there's nothing else I'd rather do. : )

Sometimes after lab meets (my PI and lab mates have math/physics backgrounds), I call it a success if I managed to recognise all the symbols in the equations; forget understanding them.

I can't tell you how strongly I empathise with what you feel. I went to med school, and then somehow decided that comp neuro PhD is the logical next step.

GitHub - Julie-Fabre/bombcell: Automated quality control, curation and neuron classification of spike-sorted electrophysiology data Automated quality control, curation and neuron classification of spike-sorted electrophysiology data - Julie-Fabre/bombcell

🚀 We are excited to share that bombcell is now available in Python! 🐍 Automatically sort your units into good/MUA/noise/non-somatic using quality metrics and interpretable & adjustable classification thresholds.
pip install and play around with our toy dataset:
🔗 github.com/Julie-Fabre/...

This podcast was very interesting, but I think I have a dissatisfaction with the concept of representation in neuroscience that goes behind what they discussed in the podcast. I'd be interested to hear thoughts on whether this is interesting, wrong, obvious, etc. 🧵

Contrary to popular belief, what is important in science is as much its spirit as its product: it is as much the openmindedness, the primacy of criticism, the submission to the unforeseen, however upsetting, as the result, however new that may be. – Francois Jacob
www.nature.com/articles/s41...

Why the 21st-century neuroscientist needs to be neuroethically engaged Technological advances in decoding brain activity and in growing human brain cells raise new ethical issues. Here is a framework to help researchers navigate them.

In the latest essay in our human neurotechnology series, neuroethicist Karen Rommelfanger outlines practical questions that can help researchers recognize when to seek out ethical expertise.

www.thetransmitter.org/human-neurot...

These boxes are not moving. A mind-bending optical illusion by Japanese artist Jagarikin.

The Genomic Code: the genome instantiates a generative model of the organism How does the genome encode the form of the organism? What is the nature of this genomic code? Inspired by recent work in machine learning and neuroscience, we propose that the genome encodes a generat...

The Genomic Code: the genome instantiates a generative model of the organism www.cell.com/trends/genet... - really delighted to see this in print in @cp-trendsgenetics.bsky.social! 😊

4/? The method requires different trials to be of the same sizes though. Time warping is a common way to tackle this, but what do people do if their data has, for example, oscillation locked activity? Trimming does not align the task events, even if it preserves the oscillation structure.

3/? This paper, from what I understand, can help with this, by giving an interpretable look at the components themselves and not just the reconstructed data. But from what I undertand, TCA also serves a similar purpose. Why isn't it more popularly used?

2/? Sometimes the interesting aspect of data is not in the component with the highest variance explained (usually motor variability dominates, and cognitive variability, for eg, is in the smaller variance components) and there is no principled way to pick the components interesting for your task.

1/? It always left me uncomfortable that we smush the time and trial axis of the neuron*time*trial data tensor into one for some analyses. We thought this paper offered an elegant, interpretable (and perhaps more importantly, easy to execute!) way to overcome this.

Dimensionality reduction beyond neural subspaces with slice tensor component analysis - Nature Neuroscience Neural activity does not always lie in a low-dimensional subspace. The authors extend this classic view to show that task-relevant information is distributed across multiple covariability classes and ...

We discussed this elegant methods paper by Arthur Pellegrino, @heikestein.bsky.social , and Alex Cayco-Gajic in our lab's journal club last week. Everybody really liked it, and we already have some data on which we are excited to try out sliceTCA. Some thoughts 🧵:
www.nature.com/articles/s41...

Building AI simulations of the human brain In which Wu Tsai Neuro faculty scholar Dan Yamins explores how foundation models of the human brain could

In a recent podcast @dyamins.bsky.social argues: "We want to be able to use the model of the digital brain as a neurobiomedical discovery and diagnostic design platform." neuroscience.stanford.edu/news/buildin... - That view is popular and I believe that there is a fundamental logical error. Thread

Our award-winning news team is seeking an enthusiastic science reporting intern to join our lively newsroom in New York City. For more information or to apply, please visit: simonsfoundation.wd1.myworkdayjobs.com/en-US/simons...

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It's kinda obvious. #AGIComics has already figured out which brain region is the most important. 😇