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Code material for the interactive recitations of the NYU course "Introduction to Neural Engineering"

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IntroNE

Code material for the interactive recitations and homeworks of the NYU course Introduction to Neural Engineering.

These recitations are based on Jupyter notebooks that can be either run locally on your laptop, or executed in an online Binder environment.

Local use

Installation

  • Download and install a Python distribution from https://www.anaconda.com/download/ using the Anaconda installer
  • Open the Anaconda prompt
  • Clone this repository: git clone https://github.com/tjjlemaire/IntroNE.git. To do this you will need to have Git installed on your computer. Alternatively, you can download the repo archive and unzip it (although the Git way is highly advised).
  • Move to the repo folder: cd IntroNE
  • Create a new anaconda environment: conda create -n introne python=3.8
  • Activate the anaconda environment conda activate introne
  • Install the code dependencies: pip install -r requirements.txt
  • You're all set!

Notebook execution

  • Open an anaconda prompt
  • Activate the anaconda environment: conda activate introne
  • Move to this repository
  • Download the latest updates from the online repository: git pull
  • Install the code dependencies: pip install -r requirements.txt
  • Start a jupyter lab session: jupyter lab
  • Open the notebook of interest by double-clicking on it
  • In the upper right corner, make sure that jupyter is running with the right kernel (Python 3.8.12 64-bit ('introne': conda)). If not, click and select the appropriate kernel from the drop-down list.
  • You're all set!

Online use

You can use Binder to access and run the notebooks online without a local installation:

Binder

Recitation 1 (2022.02.03) - the action potential dynamics and the Hodgkin-Huxley model.

Notebook name: tuto_HH.ipynb Binder

Recitation 2 (2022.02.10) - extracellular action potentials and recordings.

Notebook name: tuto_extracellular_recordings.ipynb Binder

Recitation 3 (2022.02.17) - tutorial on spike detection and classification.

Notebook name: tuto_spike_sorting.ipynb Binder

Note: This tutorial uses a significant amount of RAM, hence execution in the Binder environment will be ridiculously slow. It is therefore highly advised to execute the notebook locally.

Recitation 4 (2022.02.24) - tutorial on extracellular electrical stimulation.

Notebook name: tuto_extracellular_stim.ipynb Binder

Note: for Windows users, you will to download and install a NEURON distribution in order to run this notebook on your machine.

Homework 1 (2022.03.07)

Notebook name: homework1.ipynb Binder

Note: for Windows users, you will to download and install a NEURON distribution in order to run this notebook on your machine.

Homework 2 (2022.04.15)

Notebook name: hw2.ipynb Binder

Homework 3 (2022.05.12)

Notebook name: hw3.ipynb Binder

This notebook requires some input data to run. Make sure to follow the assignment instructions for how to download and extract the dataset.

Questions

For any questions, you can contact me by email: [email protected]

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Code material for the interactive recitations of the NYU course "Introduction to Neural Engineering"

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