Need help finding abstract - Zinn's qEEG study presented at Stanford

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Try as I might, I cannot find where their study was published or if it was even published. I cannot find the abstract on Pubmed, Co-cure, or any blogs that came out during the Stanford Symposium last spring. It is the one that found patients emitting delta waves during the daytime, among other findings.

I am going in for a daytime study at the sleep clinic in a couple weeks, which is testing for narcolepsy. I doubt I have narcolepsy, but I would like to show the Zinns' research to the sleep specialist. My expectations are low, and I'm doubtful it will make much impact on him, but it may at least be of interest.

The name of the study is EEG Peak Alpha Frequency is Associated with Chronic Fatigue Syndrome: A Case-Control Observational Study Marcie Zinn, Ph.D., Mark Zinn, MM, Jose Maldonado, MD

If anyone can help me find this study I would appreciate it. At this point it is more out of curiosity than anything... why can't I find any links to it?
 

Pyrrhus

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The Zinns presented some other qEEG work at the 2014 IACFS/ME conference. Of that work, Komaroff said the changes they saw demonstrate brain dysregulation seen “in a whole host of well-documented neurologic diseases.” If I remember, the findings correlated with severity.

http://iacfsme.org/PDFS/2014Syllabus25.aspx - page 42.

EEG peak alpha frequency is associated with chronic fatigue syndrome: a case-control observational study Marcie Zinn, Ph.D., Mark Zinn, MM, Jose Maldonado, MD, FAPM, Jane Norris, PA-C, Ian Valencia, BS, Jose G. Montoya, MD

Abstract Objectives: The two cardinal symptoms of chronic fatigue syndrome (CFS) are ubiquitous, severe, disabling fatigue and cognitive impairment known as ‘brain fog.’ Remarkably, neuroimaging and neuropsychological studies have mixed results in finding structural changes commensurate with these two cardinal symptoms of CFS. The objectives of this pilot study were to evaluate the relationship between electroencephalogram (EEG) peak alpha frequency (PAF) in CFS as compared to age- and sex-matched controls and to develop a diagnostic criteria using qEEG.

Methods: A 19- channel quantitative EEG and two fatigue measures were obtained on 50 CFS patients and 50 healthy control participants in a 3-minute eyes closed condition using a resting-state only case-control design.

Results: Mixed ANOVA results found decreased PAF over 58% of the entire cortex in CFS patients when compared to controls, Wilks’ L = .66, (F(18,80) = 2.424, p = .006, partial h2 =.31); bonferroni-corrected followup indicated significant differences in PAF at the following electrode sites: C3, C4, Cz, F3, F4, FP1, FP2, Fz, P3, Pz and T3 (p<.05). Two hierarchical multiple regression models found the best linear combination of predictors to predict fatigue: analysis 1 used the MFI-20 as the criterion variable,[ R2 = .897, F(5,1894) = 3287.76, p =.000], analysis 2 used the Fatigue Severity Scale as the criterion, [R2 = .887, R2 change = .865, F(5, 1894) = 3058.93, p=.000]. To assess fatigue levels between groups, we used the Mann-Whitney U Test, first with MFI-20 (z = -37.474, p < .000) then the FSS (z = -37.757, p < .000).

Conclusions: These findings are consistent with reduced efficiency of thalamo-cortical connections in CFS participants. EEG PAF measurement of cognitive fog and fatigue in CFS may have prognostic value and facilitate the evaluation of CFS as part of a diagnostic regimen.

The IACFS/ME abstract also said
"qEEG measurement provides a quick, inexpensive and reliable diagnostic tool for most types of cortical issues. qEEG does not provide a stand-alone diagnostic, but integrates well into a clinical diagnostic regimen."
 

Pyrrhus

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Related discussion:

There is another important aspect to the connections between the thalamus and the cortical brain- the aspect of alert consciousness. There is recurring stimulation from the thalamus to the cortical brain and then back to the thalamus, forming a loop. This recurring stimulation through the loop leads to "thalamo-cortical oscillations". Some of these oscillations can be roughly recorded using an electroencephalogram (EEG) as "alpha frequency waves". These alpha frequency waves in EEG typically represent a state of alert consciousness. If there is a problem with the thalamo-cortical oscillations, it may be hard to maintain a state of alert consciousness. (brain fog?)

EEG studies in ME have had a hard time documenting specific abnormalities. But one study noted that "In the eyes closed condition, peak alpha frequency (the frequency between 8 to 13 Hz at which the greatest amount of energy was observed) correlated negatively with the 'fatigue today' rating." This means that patients who reported more fatigue had slower alpha-frequency waves.[1] And a 2014 conference presentation "found decreased [peak alpha frequency] over 58% of the entire cortex in CFS patients when compared to controls. [...] These findings are consistent with reduced efficiency of thalamo-cortical connections in CFS participants." [2]
 
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Pyrrhus

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For those interested, here is one of the earliest papers that established a link between the speed of thalamo-cortical oscillations and attention or information processing:

EEG-alpha rhythms and memory processes (Klimesch, 1997)
https://pubmed.ncbi.nlm.nih.gov/9203012/

Excerpt:
Klimesch 1997 said:
The results of several experiments indicate that alpha frequency varies as a function of memory performance. It was found that in samples of age matched subjects alpha frequency of good memory performers is about 1 Hz-higher than those of bad performers. The difference in alpha frequency between good and bad performers reaches a maximum during the retrieval of information, is much smaller during encoding and is minimal--but still significant--during a resting period. These results suggest that alpha frequency may be a permanent and not only a functional parameter that determines the speed with which information can be retrieved from memory.

The calculation of changes in band power indicate further that the upper alpha band is particularly sensitive to semantic memory demands. The lower alpha band, on the other hand, seems to reflect attentional processes. These findings are discussed on the basis of a hypothesis which assumes that EEG frequencies within the alpha band stem at least in part from the thalamus and that the activity of thalamo-cortical networks reflects processes that are related to searching, accessing and retrieving information from (semantic) long-term memory.

The author's later work expands on how thalamo-cortical oscillations are involved in both attention/concentration and in information processing/retrieval:
https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(12)00243-4
 

Pyrrhus

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Also note that the data from this 2014 presentation was re-analyzed by the same authors, but using eLORETA analysis instead of qEEG analysis:

Cortical Hypoactivation During Resting EEG Suggests Central Nervous System Pathology (Zinn et al., 2018)
https://forums.phoenixrising.me/thr...gests-central-nervous-system-pathology.60068/

(although the work was performed by 2014, the results were published in 2018)

Whereas qEEG analysis calculates "peak alpha frequency", eLORETA analysis calculates "alpha source density".

Whereas "peak alpha frequency" is a measure of the speed of thalamo-cortical oscillations, "alpha source density" is a measure of the intensity of thalamo-cortical oscillations at a particular location in the outer portion of the brain.

Although the eLORETA re-analysis did not report any significant findings related to "alpha source density", a follow-up study by the same authors found significantly reduced alpha source density in cortical areas:

Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study. (Zinn, Zinn, and Jason, 2016)
https://forums.phoenixrising.me/thr...tivity-in-core-neurocognitive-networks.43006/
Deviant current source density values were found in alpha (ME: 0.065, HC: 0.429) and alpha-2 bands (ME: 0.075, HC: 0.305), (log-F-ratio threshold = -1.65, p = 0.033, two-tailed, corrected) in the bilateral parietal, occipital and posterior temporal lobes.
 
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Pyrrhus

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Michael VanElzakker and the Workwell foundation presented a poster at the recent 2021 IACFS/ME conference that also suggests that EEG could be used to detect the presence of brain fog:

1630259577909.png
 

Viala

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Thanks @Pyrrhus for interesting information. I was wondering recently if there would be any differences in our EEGs.

It reminds me that in the beginning of my CFS I thought that this strange body heaviness and fatigue was similar to the one I experienced when I woke up from a deep sleep when I was still healthy, a state of being not entirely awake but also not asleep. CFS feels a bit like being in that deep sleep, but also being awake.

Do you think that listening to binaural beats could help? I used to play with it years ago, maybe this could help to readjust our brainwaves.