[Eeglablist] Which is the best way to measure the "alpha" oscillation?

Thu May 14 14:08:06 PDT 2026

Scott, well said re reification!  I completely agree!  It is very clear, 
for example, that the frontal alpha asymmetry measured in emotion 
studies is entirely different from the posterior alpha observed when 
someone is mind wandering or otherwise spacing out. I've long wondered 
why the frequency-domain literature hasn't made the same sort of 
systematic effort made in the time-domain literature to differentiate 
between different components with the same time peak, although some 
authors have been advocating for classifying "microstates", which seems 
a worthy effort to me (it's good to recognize the work of other labs!).  
For example:

Khanna, A., Pascual-Leone, A., Michel, C. M., & Farzan, F. (2015). 
Microstates in resting-state EEG: Current status and future directions. 
/Neuroscience & Biobehavioral Reviews/, /49/, 105–113. 
https://urldefense.com/v3/__https://doi.org/10.1016/j.neubiorev.2014.12.01__;!!Mih3wA!G58S4iLv6tQC6e1hoMgUlsvBcvUnA_m9zbAVIXUa4qqWm2i1hFzuebm1bBpJevlkH4cNXxWZqFQYHjWgUdw$ 

The spatial signature is critical to consider in these things as it is a 
direct reflection of differing neural sources, although scalp topography 
alone cannot be relied upon for source analysis (i.e., inverse 
problem).  It seems to me it is therefore unfortunate that in the 
time-domain literature we have settled on a time-polarity nomenclature 
(e.g., P300).  My own suggestion has been to add the peak channel to the 
labels (as in P300pz), rather than to use the sometimes confusing 
nomenclature of adding an arbitrary letter (e.g., P3a or N2b).

Dien, J. (2009). The Neurocognitive Basis of Reading Single Words As 
Seen Through Early Latency ERPs: A Model of Converging Pathways. 
/Biological Psychology/, /80/(1), 10–22. 
https://urldefense.com/v3/__https://doi.org/10.1016/j.biopsycho.2008.04.013__;!!Mih3wA!G58S4iLv6tQC6e1hoMgUlsvBcvUnA_m9zbAVIXUa4qqWm2i1hFzuebm1bBpJevlkH4cNXxWZqFQYt7Qwf2E$ 

Just to expand on your remarks for those newer to the field:  The first 
statistical demonstration that the "P300" needs to be differentiated 
into the P3a and the P3b was made by Manny Donchin and myself and Kevin 
Spencer:

Spencer, K. M., Dien, J., & Donchin, E. (1999). A componential analysis 
of the ERP elicited by novel events using a dense electrode array. 
/Psychophysiology/, /36/(3), 409–414. 
https://urldefense.com/v3/__https://doi.org/10.1017/S0048577299981180__;!!Mih3wA!G58S4iLv6tQC6e1hoMgUlsvBcvUnA_m9zbAVIXUa4qqWm2i1hFzuebm1bBpJevlkH4cNXxWZqFQY7L7fzYA$ 
Spencer, K. M., Dien, J., & Donchin, E. (2001). Spatiotemporal Analysis 
of the Late ERP Responses to Deviant Stimuli. /Psychophysiology/, 
/38/(2), 343–358.

Simons and colleagues also had an early paper on this topic:

Simons, R. F., Graham, F. K., Miles, M. A., & Chen, X. (2001). On the 
relationship of P3a and the Novelty-P3. /Biological Psychology/, 
/56/(3), 207–218. https://urldefense.com/v3/__https://doi.org/10.1016/S0301-0511(01)00078-3__;!!Mih3wA!G58S4iLv6tQC6e1hoMgUlsvBcvUnA_m9zbAVIXUa4qqWm2i1hFzuebm1bBpJevlkH4cNXxWZqFQYHMXrups$ 

Manny pioneered the application of PCA to ERPs in the 60's precisely 
because he understood the need to separate superposed ERP components, 
notably the P300, long before either of us.  I appreciate your own 
contributions to further developing the topic, as in the citations you 
shared!

Donchin, E. (1966). A multivariate approach to the analysis of average 
evoked potentials. /IEEE Transactions on Bio-Medical Engineering/, 
/BME-13/, 131–139. https://urldefense.com/v3/__https://doi.org/10.1109/TBME.1966.4502423__;!!Mih3wA!G58S4iLv6tQC6e1hoMgUlsvBcvUnA_m9zbAVIXUa4qqWm2i1hFzuebm1bBpJevlkH4cNXxWZqFQYt_LHkL4$ 

Donchin, E., & Heffley, E. (1978). Multivariate analysis of 
event-related potential data: A tutorial review. In D. Otto (Ed.), 
/Multidisciplinary perspectives in event-related potential research (EPA 
600/9-77-043)/ (pp. 555–572). U.S. Government Printing Office.

It is also worth noting that, while in this context, the LPC (not LCP) 
acronym stands for Late Positive Complex in order to convey that there 
are multiple components, as you say, it is also often mistranslated as 
standing for Late Positive Component, thus reifying the very term that 
was meant to caution against reification (sigh).

Anyway, thanks for making this very apropros cautionary reminder!

Joe

On 5/14/26 01:41, Scott Makeig via eeglablist wrote:
> Cedric -
>
> When you write of detecting (the) "Individual Alpha Frequency (IAF)", you
> reify the term introduced 30 years ago by Klimesch
> <https://urldefense.com/v3/__https://journals.lww.com/clinicalneurophys/fulltext/1996/11000/Alpha_Frequency,_Reaction_Time,_and_the_Speed_of.6.aspx?casa_token=oAAhkPMByY0AAAAA:OXBNWqxRPYfRdk-oqwrPa9gGH8oibz3ujgYREp5YQ1kRsHCjfCozo8ChE6KN2k4MoP-x8NBacQQygifizS7MNJw__;!!Mih3wA!H8nFsgPl6moOZD26yYE4dWZNiyufmDPpw3sS1NMOe-5Q1Tmi7DHdgBiHGRT4pH3IzDHim5JQnt1wEPHW--Re$ 
> >
> -- a term that our work (specifically, results shown in this poster
> <https://sccn.ucsd.edu/~julie/AlphaPosterMini.pdf  > by Julie Onton)
> demonstrated to us was clearly a major oversimplification. Alpha range
> activities, whether from occipital/parietal ('alpha'), somatomotor ('mu'),
> auditory ('tau') cortex, or elsewhere, are in general not fixed within
> subject -- neither over space (cortical source location) nor over time
> (within session, as shown in this poster)
> <https://sccn.ucsd.edu/~julie/AlphaIMposter.pdf  >.
>
> I've often seen how, in science, giving some phenomenon a (singular) name
> can give rise to an uncritically held belief that what is being named is in
> fact a singular phenomenon -- e.g., 'the' (supposedly unitary) 'P300' ERP
> peak versus its other originally proposed designation ('Late Positive
> Complex (LCP)' summing distinct evoked activities in multiple cortical
> areas. In these papers, we showed a late positive peak in scalp ERPs
> (across a range of scalp channels) can be accounted as summing
> positive-going potentials (with differing time courses) from a number of
> cortical areas whose projected signals -- either across the session
> <https://urldefense.com/v3/__https://journals.plos.org/plosone/article/file?id=10.1371*journal.pbio.0020176&type=printable__;Lw!!Mih3wA!H8nFsgPl6moOZD26yYE4dWZNiyufmDPpw3sS1NMOe-5Q1Tmi7DHdgBiHGRT4pH3IzDHim5JQnt1wEFa70Axu$ 
> >
> or across ERPs<https://urldefense.com/v3/__https://www.jneurosci.org/content/jneuro/19/7/2665.full.pdf__;!!Mih3wA!H8nFsgPl6moOZD26yYE4dWZNiyufmDPpw3sS1NMOe-5Q1Tmi7DHdgBiHGRT4pH3IzDHim5JQnt1wEJ3JjEyj$ 
> >
> each averaging event-related activity in one of the many task conditions --
> are maximally distinct.
>
> Here, the example is the concept of '*the*' IAF. giving it a unitary name
> ('the IAF') does not means it exists as such -- though the claim did build
> on early visual observations
> <https://urldefense.com/v3/__https://journals.sagepub.com/doi/pdf/10.1177/003591575705001013__;!!Mih3wA!H8nFsgPl6moOZD26yYE4dWZNiyufmDPpw3sS1NMOe-5Q1Tmi7DHdgBiHGRT4pH3IzDHim5JQnt1wECayF4uA$ 
> > (more
> than 70 years ago) that alpha peak frequencies in EEG data recorded under
> similar conditions can and do differ between individuals. [Note interesting
> fact: the first EEG Fourier analysis was reported by Grass
> <https://urldefense.com/v3/__https://journals.physiology.org/doi/pdf/10.1152/jn.1938.1.6.521__;!!Mih3wA!H8nFsgPl6moOZD26yYE4dWZNiyufmDPpw3sS1NMOe-5Q1Tmi7DHdgBiHGRT4pH3IzDHim5JQnt1wEMklNYiQ$ 
> > nearly 90
> years ago -- in 1938!]
>
> On Wed, May 13, 2026 at 7:31 PM Cedric Cannard via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
>> There is also the non-parametric technique for detecting Individual Alpha
>> Frequency (IAF) developed by Corcoran:
>>
>> https://urldefense.com/v3/__https://pubmed.ncbi.nlm.nih.gov/29357113/__;!!Mih3wA!Fo8w8N5UBFlY7iDyii253gF46GFSvgj4a3s8T2MvPfEjRiwul0MvwVpdQewM9tiwTQWymxmZ5e-GTAXmq2V2j4I-Ew$
>> It offers both the alpha peak frequency, and center of gravity, to account
>> for I individuals with split peaks, absent peaks, etc.
>> And detects the insidious end frequency bounds from the data, so it is
>> assumption free.
>>
>> -> This method is easily available via the BranBeats EEGLAB plugin
>> (feature extraction mode):
>> https://urldefense.com/v3/__https://github.com/amisepa/BrainBeats__;!!Mih3wA!Fo8w8N5UBFlY7iDyii253gF46GFSvgj4a3s8T2MvPfEjRiwul0MvwVpdQewM9tiwTQWymxmZ5e-GTAXmq2XDs00OGw$
>>
>>
>> Although I think Scott’s IMAT recommendation is the strongest.
>>
>> Cedric
>>
>> Sent from Proton Mail for iOS.
>>
>> -------- Original Message --------
>> On Sunday, 05/03/26 at 07:59 m za via eeglablist<eeglablist at sccn.ucsd.edu>
>> wrote:
>> Hi all,
>>
>> I think one key limitation of many traditional approaches is that they rely
>> purely on stationary spectral analysis, while EEG is inherently
>> non-stationary and dynamic.
>> In that sense, time–frequency methods (e.g., wavelet-based approaches) can
>> provide a more informative characterization of alpha by capturing its
>> temporal variability, rather than relying only on averaged spectral power.
>> At the same time, separating oscillatory peaks from the aperiodic
>> background (e.g., using methods like FOOOF (Fitting Oscillations and One
>> Over F)) is important to avoid confounds in alpha power estimation.
>> This is particularly important given inter-individual variability, where
>> using individualized peak frequencies and accounting for aperiodic activity
>> can improve the reliability of alpha characterization. Adaptive
>> decomposition methods may also offer complementary ways to capture
>> subject-specific structure, although this requires further validation.
>>
>> On Thu, 30 Apr 2026, 06:10 장진원 via eeglablist,<eeglablist at sccn.ucsd.edu>
>> wrote:
>>
>>> Hi all,
>>>
>>> There have been long controversies on measuring alpha frequency power.
>> Some
>>> researchers (especially in clinical fields where electrical engineering
>> is
>>> not familiar) use frequency bands (8-12Hz or 8-13Hz) with FFT or Welch's
>>> method to obtain spectral power. Other behavioral scientists prefer
>>> subdivisions such as lower alpha band (8-10Hz) and higher alpha band
>>> (10-12Hz). Recent advancement on FOOOF also enables the isolation of
>>> periodic components to discover individual frequency peaks. There are
>>> numerous other techniques that could specify the regions of eeg
>> activities.
>>> Which do you think is the best way to characterize the neurophysiological
>>> activity often represented as "alpha" oscillation?
>>>
>>> Best Regards,
>>> Jinwon Chang
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>
>
-- 
--------------------------------------------------------------------------------

Joseph Dien, PhD
Senior Research Scientist
Department of Human Development and Quantitative Methodology
University of Maryland, College Park
E-mail:jdien at umd.edu
Cell Phone: 202-297-8117
https://urldefense.com/v3/__http://joedien.com__;!!Mih3wA!G58S4iLv6tQC6e1hoMgUlsvBcvUnA_m9zbAVIXUa4qqWm2i1hFzuebm1bBpJevlkH4cNXxWZqFQYTPYrChs$ 