[Eeglablist] measurement unit of EEGlab power spectrum analysis

[Makoto Miyakoshi]

Dear Kyongje,

> When the baseline is not removed, time-frequency analysis function gives
me the power calculated in different unit, which is 10*log_10 (uV^2/Hz).
This unit is also displayed when I just want to check out a specific
channel property (pop_prop function).  To me, this is quite confusing since
this unit is exactly the dB unit with respect to the identify unit of the
measurement (i.e., 1uV).  The term “uV^2/Hz” within the parenthesis is
nothing different from “(uV^2/Hz) / (1uV^2/Hz)”.

Well, this is one of those ever confusing things for me. One time I tested
it.
+/- 1 microV sine wave (peak to peak), the PSD peak level was 0dB.
+/- 10 microV, 20dB
+/-0.1 microV, -20dB

> Also, with limited knowledge on signal processing, I’m not aware of any
power calculation with Hz dividing the voltage measure (uV^2 /Hz). The
division by Hz would not matter if the power is calculated in this way:
“(uV^2/Hz) / (1uV^2/Hz)”, not just “(uV^2 /Hz)”. But, as it is now, the
term “(uV^2 /Hz)” is very confusing. I don’t think EEGlab is actually
dividing the voltage measure with the corresponding frequency. To me, the
“/Hz” term is semantics, not mathematics. I think the better way of
displaying the unit is something like this:  “10*log_10 (uV^2) per Hz” or
“10*log_10 (uV^2/ 1uV^2) per Hz” to be precise. But, again, these can
simply be written as “dB”.

I thought /Hz represents 'per second' (don't ask me why), if I understood
correctly.

> Am I misunderstanding anything here?

No, I think your understanding is good, unless I'm wrong.

Makoto



On Wed, May 18, 2016 at 8:39 AM, Kay Sung <ksung3 at jhmi.edu> wrote:

> Dear Eeglablisters,
>
>
>
> This is my thought about the measurement unit of power spectrum analysis
> in EEGlab and I want to make sure if I’m not misunderstanding something
> here.
>
>
>
> Typically, I use EEGlab (time-frequency analysis) to obtain two different
> power calculations. One is to baseline removed ERSP and the other without
> the baseline removal.
>
> When the baseline is removed, ERSP plot shows power in dB unit. This is
> clear since the power of cortical oscillation after, say, stimulus onset is
> calculated with respect to the baseline power, the reference point.
>
>
>
> When the baseline is not removed, time-frequency analysis function gives
> me the power calculated in different unit, which is 10*log_10 (uV^2/Hz).
> This unit is also displayed when I just want to check out a specific
> channel property (pop_prop function).  To me, this is quite confusing since
> this unit is exactly the dB unit with respect to the identify unit of the
> measurement (i.e., 1uV).  The term “uV^2/Hz” within the parenthesis is
> nothing different from “(uV^2/Hz) / (1uV^2/Hz)”.
>
> So, the power calculated in this way is always in dB unit with different
> referencing point even if we don’t remove the baseline.
>
>
>
> Also, with limited knowledge on signal processing, I’m not aware of any
> power calculation with Hz dividing the voltage measure (uV^2 /Hz). The
> division by Hz would not matter if the power is calculated in this way:
> “(uV^2/Hz) / (1uV^2/Hz)”, not just “(uV^2 /Hz)”. But, as it is now, the
> term “(uV^2 /Hz)” is very confusing. I don’t think EEGlab is actually
> dividing the voltage measure with the corresponding frequency. To me, the
> “/Hz” term is semantics, not mathematics. I think the better way of
> displaying the unit is something like this:  “10*log_10 (uV^2) per Hz” or
> “10*log_10 (uV^2/ 1uV^2) per Hz” to be precise. But, again, these can
> simply be written as “dB”.
>
>
>
> Am I misunderstanding anything here?
>
>
>
> Thanks.
>
>
>
>
>
>
>
> *Kyongje (Kay) Sung, Ph.D*
>
> Research Associate
> *Johns Hopkins University School of Medicine*
> Cognitive Neurology & Neuropsychology – Department of Neurology
>
>
>
> 1629 Thames Street, Suite 350
>
> Baltimore, MD 21231
> P 443-287-8019 | F 410-955-0188
> ksung3 at jhmi.edu
> web.jhu.edu/cognitiveneurology/index.html
>
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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