[Mne_analysis] lowpass filtering data in sensor or source space

[Matthew Panichello]

Thanks Sheraz! The function works great.

Beyond computational cost, there's no reason to worry about filtering in 
source space?

Thanks,

Matt

On 11/15/12 1:31 PM, sheraz at nmr.mgh.harvard.edu wrote:
> Filtering in source space is very costly, number of sources >> number of
> sensors, best filter to use which granted zero phase shift in Matlab is
> eegfilt (attached).
>
> Sheraz
>
>> Hello,
>>
>> I have used mne_compute_raw_inverse to produce the inverse solution for
>> raw data, and loaded this data into matlab.
>>
>> However, I have inspected the data and would like to lowpass filter the
>> data further before extracting the statistics that I am interested in.
>>
>> It seems like my options are to either low pass filter the raw sensor
>> data further before computing the inverse solution, or to filter the
>> source data directly in matlab. Is there any methodological reason to
>> prefer one method over the other?
>>
>> If filtering the source data in matlab is preferred (or if both methods
>> are fine), could anyone recommend a particular filter type? I've looked
>> into documentation for filtering in matlab and it seems like there are a
>> tremendous amount of options.
>>
>> Thanks,
>>
>> --
>> Matthew Panichello
>> Research Coordinator, Bar Group
>> Massachusetts General Hospital
>> Phone: 617-726-9034
>>
>> _______________________________________________
>> Mne_analysis mailing list
>> Mne_analysis at nmr.mgh.harvard.edu
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-- 
Matthew Panichello
Research Coordinator, Bar Group
Massachusetts General Hospital
Phone: 617-726-9034