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Efficient neural decoding of self-location with a deep recurrent network

Ardi Tampuu | Tambet Matiisen | H. Freyja Ólafsdóttir | Caswell Barry | Raul Vicente

Binder

Published paper: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006822#abstract0

Official repo: https://github.com/NeuroCSUT/RatGPS

Jupyter-book: https://notebook-factory.github.io/NeuralDecoding_book/intro


Reproduce author scripts:

Binder : Contains source code for Figures 1 and 3
Binder : Contains source code for Figures 2 and 4
Binder : Contains source code for Figures 5 and 6


Reproduce Jupyter-book figures:

Binder : Accurate decoding of position with a RNN
Binder : Comparison of RNN and Bayesian decoders
Binder : Spatial decoding across animals in 2D and 1D environments
Binder : Analysis of the errors in function of location and neural activity for rat R2192
Binder : Results of knockout analysis
Binder : Gradient analysis, Sensitivity decreases with activity




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A Jupyter book that contains figures for the Neural Decoding research paper (original code is written in Python2).

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