[Eeglablist] Sampling rate

[Makoto Miyakoshi]

Mori, that's because sometimes EEG amplifier's native sampling rate is
1024, 512, 256 Hz... or alternatively, I've also heard that back in the
time using 2^n was favorable due to limited hardware performance.

Makoto


On Tue, Jul 1, 2014 at 7:14 AM, mori larin <morilarin88 at gmail.com> wrote:

> 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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>>
>>
>


-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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