Dear all,
We are pleased to announce the release of HNN-core 0.2. HNN-core is a package that is part of the Human Neocortical Neurosolver (HNN) software suite and offers a Pythonic interface for simulating macroscale human MEG and EEG signals from a biophysically-detailed neocortical model. HNN-core is designed to simulate primary electrical current time courses (i.e., current dipoles) that can be compared with source-localized MEG and EEG data.
Examples of use are provided for simulating commonly measured MEG/EEG signals, including event related potentials and low-frequency brain rhythms.These examples closely follow the more detailed tutorials provided for HNN-GUI.
This release includes several exciting new features including the ability to record local field potentials, optimization routines for experimental data and easy modification of connectivity/cell properties.
On Linux and Mac, it is possible to install HNN-core using a single line:
$ pip install --upgrade hnn_core
Follow us on twitter here: https://twitter.com/HNNsolver
We welcome your bug reports, feature requests, critiques and contributions on our Github page.
Best,
HNN-core development team
People who contributed to this release (in alphabetical order)
Alex Rockhill
Blake Caldwell
Christopher Bailey
Dylan Daniels
Kenneth Loi
Mainak Jas
Nick Tolley
Ryan Thorpe
Sarah Pugliese
Stephanie R. Jones