course-content
Kilosort
course-content | Kilosort | |
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14 | 2 | |
2,591 | 402 | |
0.9% | 5.2% | |
7.9 | 9.6 | |
2 months ago | 7 days ago | |
Jupyter Notebook | Python | |
Creative Commons Attribution 4.0 | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
course-content
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Can a CS student get a phd In Neuroscience?
Yes. And if you want to get a jump start on what a computational neuroscience PhD might look like, check out our materials at https://compneuro.neuromatch.io. Like a PhD in a box... and all free to use/explore!
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Ask HN: How to get back into AI?
The neuromatch computational neuroscience course also seems quite interesting, though maybe less of practical use.
https://compneuro.neuromatch.io/
Recent research like "Relating transformers to models and neural representations of the hippocampal formation" might make it more relevant though (https://arxiv.org/abs/2112.04035v2)
quote from the abstract of that paper:
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Looking for neuro-related research ideas for a masters in mathematics
check out the curated datasets and project outlines for Neuromatch Academy's computational neuroscience course for some inspiration! https://compneuro.neuromatch.io
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How can I become a strong candidate for a comp. neuroscience MS/Ph.D. program?
One possible thing I saw is taking https://compneuro.neuromatch.io/ courses, Although I'm not sure of the effect it adds to my CV.
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AskScience AMA Series: We are seven leading scientists specializing in the intersection of machine learning and neuroscience, and we're working to democratize science education online. Ask Us Anything about computational neuroscience or science education!
https://github.com/NeuromatchAcademy/course-content https://github.com/NeuromatchAcademy/course-content-dl
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We are Konrad Kording, Megan Peters, Brad Wyble, Dan Goodman, Gunnar Blohm, and Sean Escola, and we're a group of scientists who started a major, international online summer school aiming to democratize science education and make it accessible to all. Ask Us Anything!
If you'd like to learn more about it, you can check out last year's Comp Neuro course contents here, last year's Deep Learning course contents here, read the paper we wrote about the original NMA here, read our Nature editorial, or the Lancet article00074-0/fulltext) about us.
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Help with computational modelling
Check out Neuromatch Academy. If you don't have time or inclination to do the summer school this summer, you can simply access all the videos and tutorials for free at https://compneuro.neuromatch.io
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Best sources for someone interested in pursuing computational neuroscience?
https://compneuro.neuromatch.io has all the materials for free, including lecture videos and hands on Google Colab notebook programming exercises. You can also apply to take the course synchronously with a "pod" of 10 other people in a 3-week summer intensive online, with a TA to guide you and group projects to cement your understanding. To apply, check out http://academy.neuromatch.io. Applications open soon and it sounds like you'd be a great fit.
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Some questions on studying computational neuroscience
Yes, Neuromatch Academy. Their whole course is available as a Jupyter Book here
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What psychology papers to read as a computer science researcher looking to break into cognitive science research?
Maybe better than any single book or paper, I would recommend you check out neuromatch academy. There are 2 courses, computational neuroscience and deep learning and everything is free and open source. Play with the code, listen to the lectures, even do a "canned project" if you want experience.
Kilosort
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Is there a whole “layer” of neuroscience that we haven’t uncovered yet?
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.
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Clustering Neurons
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.
What are some alternatives?
stats305c - STATS305C: Applied Statistics III (Spring, 2023)
snntorch - Deep and online learning with spiking neural networks in Python
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
brainflow - BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
fooof - Parameterizing neural power spectra into periodic & aperiodic components.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
brainstorm3 - Brainstorm software: MEG, EEG, fNIRS, ECoG, sEEG and electrophysiology
Neuro-Breakout - Play breakout using the Myo Armband by Thalmic labs using python.
Homer3 - MATLAB application for fNIRS data processing and visualization
course-content-dl - NMA deep learning course
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)