.gitignore | ||
bitstream.py | ||
cli.py | ||
config.yaml | ||
data_processing.py | ||
main.py | ||
model.py | ||
README.md | ||
requirements.txt | ||
train.py | ||
utils.py |
Spikey
This repository contains a solution for the Neuralink Compression Challenge. The challenge involves compressing raw electrode recordings from a Neuralink implant. These recordings are taken from the motor cortex of a non-human primate while playing a video game.
Challenge Overview
The Neuralink N1 implant generates approximately 200Mbps of electrode data (1024 electrodes @ 20kHz, 10-bit resolution) and can transmit data wirelessly at about 1Mbps. This means a compression ratio of over 200x is required. The compression must run in real-time (< 1ms) and consume low power (< 10mW, including radio).
Installation
To install the necessary dependencies, create a virtual environment and install the requirements:
python3 -m venv env
source env/bin/activate
pip install -r requirements.txt
Usage
Running the Code
To train the model and compress/decompress WAV files, use the CLI provided:
python cli.py compress --config config.yaml --input_file path/to/input.wav --output_file path/to/output.bin
python cli.py decompress --config config.yaml --input_file path/to/output.bin --output_file path/to/output.wav
Training
Requires Slate, which is not currently publicaly avaible. Install via (requires repo access)
pip install -e git+ssh://git@dominik-roth.eu/dodox/Slate.git#egg=slate
To train the model, run:
python main.py config.yaml Test