[Mne_analysis] blog post on MNE by Clemens Brunner {Disarmed}

[Bharadwaj, Hari M]

If you use samples around each blink event to construct an SSP projector that is orthogonal to the leading eigenvector of  the blink covariance, then the SSP is equivalent to performing a linear-regression based subtraction (with the PCA-component corresponding to the blink as the regressor). As you increase the number of blink events used to compute the blink covariance and the blink projector, the SSP will converge to some set of coefficients. In the same way, as you have longer and longer traces, the linear regression (whether you use the EOG or the PCA component corresponding to the blink) will converge to essentially the same set of coefficients.


So there any reason to think this will be different from SSP?


 Thanks,

Hari


________________________________
From: mne_analysis-bounces at nmr.mgh.harvard.edu <mne_analysis-bounces at nmr.mgh.harvard.edu> on behalf of Denis-Alexander Engemann <denis.engemann at gmail.com>
Sent: Sunday, October 22, 2017 12:35 PM
To: Discussion and support forum for the users of MNE Software
Subject: Re: [Mne_analysis] blog post on MNE by Clemens Brunner

We already chatted a bit on twitter. I'd like to see an example or a simple API for this in MNE. Marjin has worked on this apparently in mne-sandbox.

On Sun, Oct 22, 2017 at 6:33 PM Chris Holdgraf <choldgraf at berkeley.edu<mailto:choldgraf at berkeley.edu>> wrote:
wooo, that's great!

--

On Sun, Oct 22, 2017 at 8:12 AM Alexandre Gramfort <alexandre.gramfort at inria.fr<mailto:alexandre.gramfort at inria.fr>> wrote:
hi,

let me share here a nice blog post by Clemens Brunner
using MNE-Python to clean up EOG by linear regression:

https://cbrnr.github.io/2017/10/20/removing-eog-regression/<https://secure-web.cisco.com/1ROZtzf_JVx9JVl2jR0vWkhG1jCqXMoWGqkX79zHqaPgh2sdV8qbKC1HqyeoNwSH9SE-7b9McwSkCHi4La_L8kV9X7XHgJGzmRbWR6AVlq9aprthTgN4DF19-oO-MDTpTUutmZJds_o50dIO1UGX8mjTnTZd50j4r5481o8NVKBwB_fz2KdSSrtISoEp15U7L5z8tUSydf1ExtAf7D3Rg7E9eDgCm9kdTDJ7Uauc2ocbUVM7pku5EZ2oOIICame-8HNFuCUxvkZK5MVmucYT2JKFy2f-ZyjQO_rj_ATvcjO7XOGQSJdsUu7a4AS0TyKfrmDcCrJh51LoghiFkvbPWkhkJj0A3HvW9S83INReaJUo/https%3A%2F%2Fcbrnr.github.io%2F2017%2F10%2F20%2Fremoving-eog-regression%2F>

thanks Clemens

Alex


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