[Eeglablist] Sampling rate

[mori larin]

Dear Makoto and Stephen,

Thank you for your detailed responses.
I agree with you about using an integral multiple of the the original
sampling rate (5000Hz) such as 250Hz and it is higher enough than the
highest-frequency
signal in the data (low pass filtering at 40 Hz).
However, I have been told by someone to use 256Hz which is 2^8. Is there
any reason behind choosing such number?
Unfortunately I don't have that person's contact details and I am not sure
about any logical reason to use 256Hz.

Regards,
Mori


On 1 July 2014 04:22, Stephen Politzer-Ahles <spa268 at nyu.edu> wrote:

> Hi Mori,
>
> In addition to what Makoto pointed out, your new sampling rate needs to be
> at or above the Nyquist rate to avoid aliasing---a good rule of thumb is
> the sampling rate should be at least 3 times higher than the
> highest-frequency signal in the data. So if you low-pass at 40 Hz, for
> example, the sampling rate should not be below 120 Hz. Personally, I like
> to use 1000 Hz because that just makes the data easy to work with (1 sample
> is 1 ms), although that could result in very large files for long
> experiments.
>
> Best,
> Steve
>
>
>
> Stephen Politzer-Ahles
> New York University, Abu Dhabi
> Neuroscience of Language Lab
> http://www.nyu.edu/projects/politzer-ahles/
>
>
> On Mon, Jun 30, 2014 at 7:04 PM, 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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