[Eeglablist] Time-frequency analysis (subtraction first or analysis first)

[Chilukuri Venkata Mahendra]

Dear All,

Time-frequency analysis is just another way of looking at signals,
especially non-stationary signals. Since, the study of non stationary
signals in time domain is difficult one needs to apply
wavelet/STFT/Time-Frequency analysis to study the time and frequency at
both time. So, any features can be studied only after converting signal to
time-frequency domain alone and one can do this in many ways.

> I agree that the time/frequency analysis should be performed first, and
> THEN subtraction.
> Subtraction of the EEG time courses (ie, in the time domain) will give a
> very different result
> compared to the (frequency domain) ERSP subtraction. EEGLAB's newtimef()
> called from the
> commandline performs this very operation on two datasets corresponding to
> two different
> conditions.
>
> Best, Julie
>
> --
> Julie Onton, PhD
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation
> University of California, San Diego
> (858) 458-1927 ext 17
> http://sccn.ucsd.edu/~julie
>
>> Dear Arnaud,
>> Are you sure about your recommendation of the first statement being
>> correct?
>> Suppose the two conditions happen to be quite similar in producing alpha
>> or
>> gamma oscillations. Since the two conditions are the same, one would
>> like
>> the desired outcome to be a *cancellation *of the two power plots.
>> However,
>> since the occurrence of the oscillations likely happen at different time
>> points (and with different phases) early subtraction would still leave
>> the
>> oscillations and the outcome would be equal or even stronger power
>> rather
>> than cancellation. Or am I thinking about it improperly?
>> Stan
>>
>> On Sun, Apr 13, 2008 at 10:53 AM, Arnaud Delorme
>> <arno at cerco.ups-tlse.fr>
>> wrote:
>>
>>> Dear Hsu,
>>>
>>> only your first statement is correct. The second one could be correct
>>> if
>>> you could pair the trials, but it would be very rare that you would
>>> want
>>> to do this (since trials are recorded at different times and are
>>> usually
>>> not paired between conditions). Look up the help of the newtimef
>>> function which allows computing differences between power between
>>> different conditions and newcrossf which allows computing difference
>>> between phase coherence images.
>>>
>>> Best,
>>>
>>> Arno
>>>
>>> Hsu, Shen-Mou wrote:
>>> > Dear list-memebers,
>>> >
>>> > Suppose that I am interested in comparing two conditions A and B in
>>> terms of their power and phase coherence. I was wondering which one of
>>> the
>>> following steps is more theoretically correct. 1. After segmentation,
>>> calculate the EEG differences between the condition A and B and then
>>> perform
>>> time-frequency analysis on the differences. 2. After segmentation,
>>> perform
>>> time-frequency analysis on the EEG data of the condition A and B
>>> respectively and then compute the power or phase coherence differences
>>> between two conditions. Any comments would be much appreciated.
>>> >
>>> > Many thanks,
>>> >
>>> > Shen-Mou Hsu
>>> >
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