This documentation is for the development version (0.14.dev0) - switch to Stable

Community-driven software for processing time-resolved neural signals including electroencephalography (EEG) and magnetoencephalography (MEG), offering comprehensive data analysis tools for Windows, OSX, and Linux:

  • Preprocessing and denoising
  • Source estimation
  • Time–frequency analysis
  • Statistical testing
  • Functional connectivity
  • Machine learning
  • Visualization of sensor- and source-space data
  • And much more

From raw data to source estimates in about 20 lines of code (try it in an experimental online demo!):

>>> import mne  
>>> raw ='raw.fif')  # load data  
>>>['bads'] = ['MEG 2443', 'EEG 053']  # mark bad channels  
>>> raw.filter(l_freq=None, h_freq=40.0)  # low-pass filter  
>>> events = mne.find_events(raw, 'STI014')  # extract events and epoch data 
>>> epochs = mne.Epochs(raw, events, event_id=1, tmin=-0.2, tmax=0.5,  
>>>                     reject=dict(grad=4000e-13, mag=4e-12, eog=150e-6))  
>>> evoked = epochs.average()  # compute evoked  
>>> evoked.plot()  # butterfly plot the evoked data 
>>> cov = mne.compute_covariance(epochs, tmax=0, method='shrunk')  
>>> fwd = mne.read_forward_solution(fwd_fname, surf_ori=True)  
>>> inv = mne.minimum_norm.make_inverse_operator(  
>>>, fwd, cov, loose=0.2)  # compute inverse operator 
>>> stc = mne.minimum_norm.apply_inverse(  
>>>     evoked, inv, lambda2=1. / 9., method='dSPM')  # apply it 
>>> stc_fs = stc.morph('fsaverage')  # morph to fsaverage 
>>> stc_fs.plot()  # plot source data on fsaverage's brain 

Direct financial support for MNE has been provided by the United States:

  • NIH National Institute of Biomedical Imaging and Bioengineering 5R01EB009048 and P41EB015896 (Center for Functional Neuroimaging Technologies)
  • NSF awards 0958669 and 1042134.
  • NCRR P41RR14075-06 (Center for Functional Neuroimaging Technologies)
  • NIH 1R01EB009048-01, R01EB006385-A101, 1R01HD40712-A1, 1R01NS44319-01, 2R01NS37462-05
  • Department of Energy Award Number DE-FG02-99ER62764 (The MIND Institute)
  • Amazon Web Services - Research Grant issued to Denis A. Engemann

And France:

  • IDEX Paris-Saclay, ANR-11-IDEX-0003-02, via the Center for Data Science.
  • European Research Council Starting Grant ERC-YStG-263584 and ERC-YStG-676943
  • French National Research Agency ANR-14-NEUC-0002-01.

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