Hi,

We are pleased to announce the new 0.9 release of MNE-python!

This release cycle has been the longest and most extensive in the history of MNE-Python. The new release comes with many new features and usability improvements thanks a consistently growing number of contributors, including last summer’s Google Summer of Code participants.

A few highlights:

- We dramatically improved support for EEG analysis on multiple levels, such as I/O, visualization and statistics

- Support for volume and mixed source spaces including subcortical structures

- Dipole fitting

- RAP-Music inverse solver

- Automated estimation and regularization of M/EEG covariance

- When your events code for different conditions event_id Epochs parameter can be used to tag each event integer to multiple conditions e.g. event_id = {‘Left/Auditory’: 1, ‘Right/Auditory’: 2, ‘Left/Visual: 3, ‘Right/Visual: 4} allows you to extract all visual epochs using epochs[‘Visual’]

- Parsing of SSS processing history from fiff files now available in measurement info

- Additional time-frequency methods such as multi-taper convolution and the Stockwell transform

- Savitzky-Golay method for filtering evoked data

- Extended support for time-generalization and cross-condition generalization decoding

- Support for ECoG and arbitrary data types

For a full list of improvements and API changes, see:

To install the latest release the following command should do the job:

pip install --upgrade --user mne

Note that this version of MNE-Python has an individual DOI and can be cited:

As usual we welcome your bug reports, feature requests, critics and contributions.

Some links:

- https://github.com/mne-tools/mne-python (code + readme on how to install)

- http://martinos.org/mne (full MNE documentation)

- http://martinos.org/mne/auto_examples/index.html (the Python examples)

- http://martinos.org/mne/python_reference.html (Python functions documentation)

- http://mne-tools.github.io/mne-python-intro-slides/ (slides)

- http://martinos.org/mne/python_tutorial.html (anintroduction/tutorial to basic mne-python)

Follow us on Twitter: https://twitter.com/mne_python

Regards,

The MNE-Python maintainer

People who contributed to this release with their number of commits:

   517  Eric Larson

   343  Denis A. Engemann

   305  Alexandre Gramfort

   300  Teon Brooks

   142  Mainak Jas

   119  Jean-Remi King

    77  Alan Leggitt

    75  Marijn van Vliet

    63  Chris Holdgraf

    57  Yousra Bekhti

    49  Mark Wronkiewicz

    44  Christian Brodbeck

    30  Jona Sassenhagen

    29  Hari Bharadwaj

    27  Clément Moutard

    24  Ingoo Lee

    18  Marmaduke Woodman

    16  Martin Luessi

    10  Jaakko Leppakangas

     9  Andrew Dykstra

     9  Daniel Strohmeier

     7  kjs

     6  Dan G. Wakeman

     5  Federico Raimondo

     3  Hafeza Anevar

     3  Christoph Dinh

     3  Basile Pinsard

     2  Martin Billinger

     2  Roan LaPlante

     1  sviter

     1  Manoj Kumar

     1  Matt Tucker

     1  Romain Trachel

     1  mads jensen