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A Python library for creating and simulating large-scale brain models

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Nengo: Large-scale brain modelling in Python

An illustration of the three principles of the NEF

Installation

Nengo depends on NumPy, and we recommend that you install NumPy before installing Nengo. If you're not sure how to do this, we recommend using Anaconda.

To install Nengo:

pip install nengo

If you have difficulty installing Nengo or NumPy, please read the more detailed Nengo installation instructions first.

If you'd like to install Nengo from source, please read the developer installation instructions.

Nengo is tested to work on Python 2.7 and 3.4+.

Examples

Here are six of many examples showing how Nengo enables the creation and simulation of large-scale neural models in few lines of code.

  1. 100 LIF neurons representing a sine wave
  2. Computing the square across a neural connection
  3. Controlled oscillatory dynamics with a recurrent connection
  4. Learning a communication channel with the PES rule
  5. Simple question answering with the Semantic Pointer Architecture
  6. A summary of the principles underlying all of these examples

Documentation

Usage and API documentation can be found at https://www.nengo.ai/nengo/.

To build the documentation yourself, run the following command:

python setup.py build_sphinx

This requires Pandoc to be installed, as well as the packages in requirements-test.txt and requirements-docs.txt. For more details, see the Developer Guide.

Development

Information for current or prospective developers can be found at https://www.nengo.ai/developers.html.

Getting Help

Questions relating to Nengo, whether it's use or it's development, should be asked on the Nengo forum at https://forum.nengo.ai.

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A Python library for creating and simulating large-scale brain models

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