pynacollada 🍍 🥥 🍹

Collaborative platform for high-level analysis with pynapple.

• pynacollada
  • Getting Started
    • Requirements
    • Installation
  • Libraries
    • Neural Ensembles
    • Manifolds
    • EEG processing
    • PETH
    • Brain state scoring
    • Graphics
    • Position tracking

Note See the analysis of the pynapple paper here

Getting Started

Requirements

• Python 3.6+
• pynapple
• scikit-learn
• seaborn

Installation

Directly from the source code:

$ # clone the repository
$ git clone https://github.com/PeyracheLab/pynacollada.git
$ cd pynacollada
$ # Install in editable mode with `-e` or, equivalently, `--editable`
$ pip install -e .

Libraries

	Jupyter notebook / scripts	Description	Contributors
Neural Ensembles	Neuralensemble_tutorial_replay1.ipynb pynacollada_tutorial_replay_short.py	How to use pynapple to compute sleep reactivation, step by step.	Adrien Peyrache
Manifolds	Tutorial_manifold_ring.ipynb	How to project a ring manifold with head-direction neurons.	Guillaume Viejo
EEG processing	Tutorial_ripple_detection.ipynb Tutorial_ripple_detection.py	How to detect ripples in CA1 step by steps.	Guillaume Viejo
PETH	Tutorial_PETH_Ripples.ipynb	How to make a peri-event time histogramm and raster plots around ripples.	Guillaume Viejo
Position tracking	Tutorial_DeepLabCut_Path_Segmentation.ipynb	How to segment the path of a mouse running in a radial-arm maze with position extracted with DeepLabCut.	Dhruv Mehrotra
Waveform processing	load_mean_waveforms.ipynb	How to extract the mean waveforms from a binary file.	Sofia Skromne Carrasco