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MIDA

Hello, I’m

HArtMuT

the Head ARTifact Model Using Tripoles

About Me

You have artifacts in your EEG data!

Eye and muscle artifacts are present in almost all M/EEG data sets. Removing them is important for further analysis like source localization.
However, correctly localizing and identifying these components relies on head models that so far only take brain sources into account.
Therefore, I was created: the Head Artifact Model using Tripoles (HArtMuT).

EEG signal origin

Cortex
30
%
Muscles
68
%
Eyes
2
%

(in an example dataset of 2132 extracted independant components (ICs) of in total 19 moving subjects)
I can handle that!

I'm a physiologically motivated volume conduction head model with cortical dipole sources enhanced by symmetric dipoles for the eyes and tripoles for face and neck muscles.
I can model eye and muscle contributions to M/EEG, localize and distinguish brain from non-brain sources, and outperform standard head models (like that of EEGLAB).
I was developed at Technische Universität Berlin (TU Berlin) in a joint work of the neurotechnology group and the department of Biological Psychology and Neuroergonomics.
There was the strong need to create me, when the Mobile Brain / Body Imaging (MOBI) Lab was built.
People are allowed to freely move around during experiments, but the recorded EEG signals are then heavily polluted by artifacts.

Integration into neuroscience pipelines

Current status: OpenMEEG, FieldTrip toolbox.

My performance in source Localization error
fig7a