[Eeglablist] Sampling rate

[mori larin]

Dear Makoto,

In your experience, does the remaining effect of gradient artefact appear
in a single component (after singular value decomposition approach and running
ICA ) similar to other types of artefacts like muscle and blink components?
If yes, what are the characteristics of the gradient component (in time,
topography and frequential domains)?

Best regards,
Mori


On 30 June 2014 18:48, Makoto Miyakoshi <mmiyakoshi at ucsd.edu> wrote:

> Dear Morin,
>
> Generally speaking...
>
> > Could it be any number and which criteria needs to be considered?
>
> Isn't it better to choose the one so that the original sampling rate is an
> integral multiple of the one chosen?
>
> > should I have to remove gradient artefacts before running ICA and then
> trying to find the remaining effect of gradient artefact in ICA components?
>
> Yes definitely. It is because grandient artifact has very high amplitude.
> Actually I recommend you try it yourself to see what happens. For artifact
> subtraction I liked Liu's singular value decomposition approach (NeuroImage
> 2012) because it does not smear out artifacts.
>
> Makoto
>
> On Mon, Jun 30, 2014 at 8:04 AM, mori larin <morilarin88 at gmail.com> wrote:
>
>> Dear list,
>>
>> I am using EEG data and I have two questions:
>> 1) I am not sure about sampling rate. The EEG data was recorded at 5000
>> Hz and I have to down sample it for further work. I used 256 Hz and I do
>> not know is it correct or not. How should we select the re-sampling rate?
>> Could it be any number and which criteria needs to be considered?
>>
>> 2) For the EEG data which is recorded simultaneously with fMRI data, in
>> order to remove gradient and BCG artefacts automatically from the data
>> using ICA , should I have to remove gradient artefacts before running ICA
>> and then trying to find the remaining effect of gradient artefact in ICA
>> components? (and what are the methods to remove it) or I have to run ICA on
>> the contaminated data directly? The latter I think I have to expect more
>> components associated to gradient artefacts because the amplitude of the
>> gradient artefacts are larger than brain signals.
>>
>> I really appreciate it if you could help me,
>>
>> Regards,
>> Morin
>>
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>
>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>
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