NeuroChaT - Neuron Characterisation Toolbox¶
NeuroChaT (RRID:SCR_018020) is an open-source neuron characterisation toolbox. It is described in our paper on Wellcome Open Research.
Installation¶
To install NeuroChaT from PyPi, run the following
python -m pip install -u neurochat
Alternatively, to develop with NeuroChaT
git clone https://github.com/seankmartin/NeuroChaT
cd NeuroChaT
pip install -e .
Authors¶
Md Nurul Islam, Sean K. Martin, Shane M. O’Mara, and John P. Aggleton.
Contact¶
Feel free to email us, or pop a message into our Gitter channel.
Contributing¶
We are open to contributions and would greatly appreciate any input. Please format your code before submitting a pull request. autopep8 has been run on neurochat. You can run this before contributing by the following:
pip install autopep8
python -m autopep8 -r -i neurochat
Getting started¶
The best ways to get started with NeuroChaT are:
For using the UI, download the executable file for Windows and check out the user manual. For using the Python Code, check out the introductory notebook, and examples on this website and other examples on GitHub. Additionally, Sample hdf5 datasets and results are stored on OSF. We are open to collaborators, questions, etc. so feel free to get in touch!
Contents:
- Neurochat API guide
- Step 1: Install NeuroChaT
- Step 2: Import modules and classes
- Step 3: Instantiate objects
- Step 4: Add paths to the data files
- Step 4a: For HDF5 files
- Step 5: Load spatial and spike data and set the unit number
- Step 6: Instantiate NData object. Add individual data objects to NData object.
- Step 8: Perform analysis of interest
- Step 8a: Analysis of a place cell
- Step 8c: Analysis of spike-train dynamics
- Step 8d: Analysis of rhythmicity of LFP and spike-to-LFP phase relationships
- Step 9: Using the Nhdf class
- Step 10: Use of NeuroChaT class
- Step 11: Use NClust class
- NeuroChaT Examples
- Method Descriptions
- neurochat package
- Development Roadmap
- NeuroChaT Release Notes