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> 909.607.0914
>
> and
>
> Visiting Associate Scientist
> Psychology & Neuroscience
> Division of Humanities & Social Sciences
> Caltech
> Pasadena, CA 91125
> [log in to unmask]
>>>> Vladimir Litvak 02/02/11 3:19 AM >>>
> Dear Michael,
>
> On Wed, Feb 2, 2011 at 7:02 AM, Michael Spezio
> wrote:
>> Hi Vladimir,
>>
>> I saw in your post 041502, dated 2010-05-07, that for some reason bandpass
>> filtering with wide bands (e.g., 0.1 to 30 Hz) elicits bad performance by
>> the Matlab SP Toolbox and causes displays of the subsequent data to fail.
>>
>> Can you specify why this is occurring? It doesn't seem to make sense given
>> that wide bandpass filters are used in signal processing routinely.
>>
>
> It's not a display issue but actual data corruption issue. There are
> numerical stability problems that I have since also observed in
> high-pass filters for some combinations of filter settings and
> sampling rate. These problems are common for wide bandpass filters,
> especially for ones with low cut-off close to DC (e.g. 0.1-40 Hz).
> Therefore, I recommended that people use separate high-pass and
> low-pass in these cases. In the next SPM8 update there is a change in
> the code that detects automatically when a filter is unstable and
> gives an error so people will not have to figure it out later when
> their display crashes.
>
>> Also, for the Multimodal Face tutorial, why isn't filtering done prior to
>> downsampling? Downsampling, especially to 200 Hz or lower, should only be
>> done after filtering out higher frequency contaminating signals, measured
>> at
>> a high sampling rate (500 Hz or above), to avoid aliasing from muscle
>> signals at frequencies of 90 Hz to 200 Hz. Can you help me understand what
>> is going on with the bandpass processing and why filtering is left out of
>> the tutorial?
>>
>
> Aliasing can occur when downsampling is done by simple decimation in
> the time domain (e.g. taking every other sample). SP toolbox
> downsampling routine is smarter than that and it pre-filters data to
> avoid aliasing so it is not necessary to do it explicitly. In the
> absence of SP toolbox we use or own routine that downsamples in the
> frequency domain by truncating the DFT coefficients. This way there is
> also no aliasing. The only problem that can occur is that if there are
> large DC offsets in the data, low-pass filter will cause ringing at
> the edges. Therefore I'd suggest to apply high-pass filtering before
> downsampling especially for epoched data. In the case of the faces
> tutorial this is not a problem because downsampling is done on
> continuous data (for EEG) or on baseline-corrected data (for MEG).
>
> Best,
>
> Vladimir
>
>> Thanks so much.
>>
>> Best,
>>
>> Michael
>>
>> Michael L. Spezio, Ph.D.
>> Assistant Professor of Psychology
>> Department of Psychology
>> Scripps College
>> Claremont, CA
>> [log in to unmask]
>> 909.607.0914
>>
>> and
>>
>> Visiting Associate Scientist
>> Psychology & Neuroscience
>> DiviĀD/ |
