The Nengo team is glad to announce the release of Nengo 2.1.1.
Nengo is a Python library for building and simulating large-scale neural models for AI and robotics. It can be thought of as a neural compiler, transforming a functional description of a neural model to a network of spiking or non-spiking neurons that can run on multiple backends including GPUs and neuromorphic hardware.
Nengo 2.1.1 changes how the default
LIF neuron model
decides when the spike. It should now be closer to the
behavior of the
LIFRate model, which is used to
determine decoding weights, meaning that the new
is more accurate than the previous model.
However, the previous model is slightly faster,
so we have made it available as
This release also fixes several bugs. To see the full list of changes, head to the Github release page.
To get the new version of Nengo, use
pip install --upgrade nengo