Sequential Predictive Attention for the Representation of SpiKing Signals

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  • License: GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007 Free Software Foundation, Inc...
  • Author: Nicolas Skatchkovsky
  • Tags Computational neuroscience, Artificial Intelligence, GenAI
  • Requires: Python >=3.9
  • Provides-Extra: scripts
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SPARKS 🎆

This is the official repository for SPARKS: a Sequential Predictive Autoencoder for the Analysis of SpiKing Signals.

SPARKS includes a novel self-attention mechanism using Hebbian learning to generate reliable latent representations from single spike timings. SPARKS trains a variational autoencoder with a novel criterion inspired by predictive coding for temporal coherence.

sparks is implemented in PyTorch and includes demos for a quickstart. It can perform supervised or unsupervised to produce low-dimensional latent embeddings which allows to gain biological insights from neural data.

Make sure to 👀 watch or ⭐️ star this repository to keep updated!

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  • 📄 Preprint:

Coming soon!

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  • SPARKS is an open source software under a GLPv3 license.

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  • License: GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007 Free Software Foundation, Inc...
  • Author: Nicolas Skatchkovsky
  • Tags Computational neuroscience, Artificial Intelligence, GenAI
  • Requires: Python >=3.9
  • Provides-Extra: scripts
Classifiers

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0.1.1

0.1.0

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