[Eeglablist] Sampling rate
morilarin88 at gmail.com
Tue Jul 1 07:14:34 PDT 2014
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
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.
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
> Stephen Politzer-Ahles
> New York University, Abu Dhabi
> Neuroscience of Language Lab
> 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,
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