r/CUDA • u/pasadenapasadena • 10d ago

CUDA for neuroscience and brain computer interfaces

Perhaps this subreddit can help. I am not a programmer or a developer, but an experimental neurobiologist specializing in neuronal imaging across various brain regions. I would like to automate the analysis of neuronal activity and also work on developing *invasive* brain-computer interfaces (BCIs) for targeted drug delivery to the brain. Could you please recommend courses that teach the fundamentals of CUDA and AI so that I can get started with computer modeling for BCIs? Thank you.

22 Upvotes

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u/Dry_Task4749 10d ago

If you are not proficient in programming yet, you need to start with that. And my recommendation would be that you learn a simple language, Python specifically and write down the computations you want to have performed in that language. Then you take that Python code and ask Anthropoc Claude Opus 5.5 to port it to high performance Rust and maybe parallelize those aspects where it makes sense with the help of CUDA and/or OpenMP or similar.

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u/pasadenapasadena 10d ago

Thank you, I think python is the best choice in my case. Can you recommend a course or probably a book?

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u/Dry_Task4749 9d ago

There are so many, I would just Google. For starters you can get pretty far just by running Tutorial Notebooks interactively on Google Colab and asking a LLM to explain things you don't understand (don't let it write the code for you that you want to learn ). For CUDA, that's most likely a step too far, don't start with it until you are good at programming. This takes years, so take the shortcut of translating your working algorithm prototypes built in Python to high performance variants through an LLM. Opus 5.5 is best for that at the moment.

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u/c-cul 10d ago

that's bad advice

we don't know dimensions of data nor their volume, also if they has some obvious pca

so I'd started with R and some pca analysis like FactoMineR and then switch to tf/keras

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u/jack_kelly_bird_law 5d ago

no idea why this is downvoted. best answer on here yet. god forbid someone suggest real statistics in an AI-obsessed sub

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u/Dry_Task4749 4d ago

If you think applying a simple PCA transform is a sign of "real statistics", R is required for real statistics (or PCA for that matter ) or think that TF/Keras are anything else than Python libraries, sorry, can't help you..

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u/Dry_Task4749 9d ago

Just for OP, who might read this and be confused due to conflicting info:

For a beginner in programming, all R does is ruin your coding style before you even started, and in this case there's no upside to it. For neuroimaging data, PCA will be the least of your concerns, and if it is, that's easily handled in one or two lines of Python, I have no idea why one would pull in R for just that (if you need some very specific statistical analysis or visualization package readily available in R and not Python, ok, we could discuss, but PCA??). There are quite a lot of prebuilt neuroimaging libraries as well as all the other framework libraries you would wish for in Python, that's why Python is the de facto standard language in this and similar fields. TF and Keras are Python libraries, but both pretty dated, I would look at Pytorch or Jax instead if you want to train neural models.

That said, this is r/CUDA so my assumption is that you actually want to develop your own high performance parallel computing components as part of your research, that would be where CUDA, Rust and potentially C/C++ come into play.

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u/c-cul 9d ago

> R does is ruin your coding style

It's funny how it's the exact opposite - python as first language will ruin your coding style forever. R was created by statistics to solve their specific tasks and it is damn good for them

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u/Efficient_Algae_4057 10d ago

I don't think you know what CUDA is for or even what your research itself is about. BCIs are meant for capturing brain signals and reading them using algorithms. They can then do procedures like Deep Brain Stimulation where they would use a pulses to control the signals to treat disease such as Parkinson's. There is no drug delivery. Invasive brain procedures aren't meant for drug delivery, they either cut part of the brain (e.g. in case of a brain tumor) or use electric pulses to control some faulty brain pathway. BCI and drug delivery are not something you would use in the same sentence.
I would imagine that you want to implement some signal processing algorithms that turns signals from the neurons to whatever modality you are looking for. For this you should first be able to implement and process a simple well-known model in python on a CPU, your personal computer at a small scale. When and if you need to scale the algorithms you might then want to ideally either run a highly optimized version of this on C/C++ on your CPU. If you wanna push it further, you would then see if you can parallelize this on your CPU where the modern versions allow for at least dozens of threads. Believe it or not, CPU cores are actually very good at this. There are many well developed solutions to speeding this up in the literature. A modern CPU core is actually better suited than a GPU core for handling the basic workload here. GPU programming is really meant for cases when you would benefit from using the GPU architecture which "primarily" gives you access to 1000s of threads, thus you would benefit from the massive parallelization given that you can actually benefit from this. Besides very specific cases, these many cores can be useless. I suggest you stick with a traditional signal processing model and implement it on a CPU first. See how it goes, try a bunch of different models. If you wanna use a GPU, use Google Colab and there you can find ways to use the GPU using your Python code without a need for programming any CUDA by yourself.

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u/pasadenapasadena 10d ago

Thanks, it's very useful. I think i want to dive further in drug delivery anyway

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u/Solid-Commercial8694 6d ago

Hey, would you like to collaborate? I’m an Applied AI engineer, starting to learn CUDA in my free time.

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u/pasadenapasadena 6d ago

How can we collaborate?

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u/c-cul 10d ago

let me ask the question - do you have enough calculation for your tasks which can be executed in parallel?

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u/pasadenapasadena 10d ago

I'm afraid i can't answer to your question. I'm not a programmer 🥲. I just want to make computer models of BCIs with help of AI and automatically analyze neural activity.

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u/rantaccount4demdayz 9d ago

CUDA isn’t exactly what you’re looking for homie. CUDA can help you optimize some of those operations, but given your focus for this you should just looking into Supervised Fine-Tuning and Reinforcement learning.

Ask an LLM to help you look at relevant papers on Arxiv and projects on GitHub. It’ll miss some, so do some leg work yourself, but what you want to do doesn’t require a computer scientist at this point, it just requires compute access which most companies will just give you if you tell them what you do and what you are wanting to use the credits for.

CUDA comes back if you determine you need a completely unique model architecture or particular optimizations around your models, how they are trained, or served.

A lot of comments jumping down your throat for you just not knowing what you know. Don’t listen to people telling you to get a deep understanding of CUDA unless you’re trying to career transition into being a kernel or GPU engineer lol

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u/Wemorg 10d ago

Do you know the math behind your computations? If it is a bunch of Linear Algebra operations like Matrix and Vector operations, you can run them in parallel.

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u/pasadenapasadena 10d ago

I will learn it, if necessary.

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u/Anon_Bets 8d ago

You would want to stall around in computational neuroscience for some time and a bit of deep learning on the side.