brainflow VS Kilosort

The home project I've been working on for 4 years (https://github.com/brainflow-dev/brainflow) has been downloaded 100k times from PyPI. It's a library to work with wearable devices, with primary focus on EEG.

About my current user base, I'd like to highlight we use SimpleBLE at my job, it has been integrated into BrainFlow, it is part of some new tools made by a large industrial automation company (whose name I cannot mention but rhymes with "Good product made by bees") and by a robot researcher in Germany.

BrainFlow provides a uniform SDK to work with biosensors with a primary focus on neurointerfaces. It provides SDK for Python, Java, C#, C++, Matlab, R, Julia and Rust. Core part of BrainFlow is written in C\C++ and all bindings call methods from dynamic library. User API is uniform for all supported devices and allows you to develop device agnostic applications.

I made a mod for Skyrim VR that brings your mental focus level (as determined by a Muse 2 meditation EEG device and the processing of https://brainflow.org) into Skyrim and scales your ingame magic power by your actual mental power. So you now actually need to learn to channel your inner strength if you want to be a successful mage! This is Real Virtual Magic!

I can get the complete EEG reading of four channels plus the gyro sensors and in the future also the heart rate. What I do with it is a different question :D I process the data myself, locally, using the brainflow.org library. So I do create a non-binary value at the moment

Sure! I use brainflow.org to collect the data from the muse and at the moment I just do a super simple spectral analysis and use the average alpha/theta ratio to determine brain power. This will definitely not stay. I am already experimenting with different ratios and I will probably implement a classifier that allows a more sophisticated classification later down the road. I will also augment it with the gyro sensor and the heart rate monitor that is integrated in the Muse. Ultimately, I will make it compatible with the OpenBCI Galea device. Join the discord to stay in touch!

And yet, we are starting to make sense of it all! The experimental tools are really what makes the difference. Lots of recently developed genetic tools (such as optogenetics ) are now allowing us for the first time to activate/inactivate specific neurons and molecular pathways and observe the causal effects . Other genetic methods (like Crispr) allow us to create mutant animals where a specific gene is mutated, so a lot of work is now in rodents, but I expect it to translate to humans in the next decade or so. Another really crazy one are cerebral organoids, where we grow in vitro a simplified human brain from stem cells to study the details of development and the function of different genetic pathways. When it comes to brain function, the ability to record from tens of thousands of neurons simultaneously using new probes like Neuropixels has been a recent game changer. Also, machine learning approaches are now incredibly useful to analyze data, from detecting the individual "spikes" to developing complex models of the brain dynamics to support computation. To give you a concrete example of progress, we can now read a person's mind so he can write words on a screen, pretty much as quickly as if he was typing them on a keyboard.

I'm assuming by clustering neurons, you mean clustering spike data. There are several excellent options that already exist for this purpose, the most notable of which is KiloSort.