hnn-core 0.2 released!

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

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We welcome your bug reports, feature requests, critiques and contributions on our Github page.

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