[Mne_analysis] high pass filtering

Dan McCloy drmccloy at uw.edu
Thu Oct 20 13:02:22 EDT 2016
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This paper is also a good resource on filtering ERP data:

@article{TannerEtAl2015,
  title = {How Inappropriate High-Pass Filters Can Produce Artifactual
Effects and Incorrect Conclusions in {ERP} Studies of Language and
Cognition},
  volume = {52},
  shorttitle = {High-Pass Filtering and Artifactual {{ERP}} Effects},
  doi = {10.1111/psyp.12437},
  number = {8},
  urldate = {2015-10-27},
  journal = {Psychophysiology},
  author = {Tanner, Darren and Morgan-Short, Kara and Luck, Steven J.},
  month = aug,
  year = {2015},
  pages = {997--1009}
}




On Thu, Oct 20, 2016 at 9:40 AM, Eric Larson <larson.eric.d at gmail.com>
wrote:

> There has been quite a bit of discussion about high-pasing lately. Have
> you looked at the filtering tutorial in MNE-Python?
>
> https://mne-tools.github.io/stable/auto_tutorials/plot_
> background_filtering.html
>
> You might in particular be interested in the pitfalls related to
> high-passing:
>
> https://mne-tools.github.io/stable/auto_tutorials/plot_
> background_filtering.html#some-pitfalls-of-filtering
>
> Recent publications suggest that the appropriate choice of high-pass
> involves choosing tradeoffs based on the expected signal and noise
> characteristics of your recording, so unfortunately I don't know of a
> single best answer.
>
> Eric
>
>
> On Thu, Oct 20, 2016 at 12:27 PM, Rezvan Farahi <rezvan.farahi at gmail.com>
> wrote:
>
>> Hi all,
>> a quick question.
>> I'm wondering if you'd have suggestion for which high pass filter to use
>> on the ERP data?
>> 0.1Hz is common in ERP studies (particularly language that I'm working on)
>> But from what I remember from the signal processing text books, 1Hz is
>> safer regarding the slow drift movement artifacts.
>> I'm wondering if someone has explored this further and/or has
>> recommendations?
>>
>> Many thanks
>> Rezvan
>>
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