Prolonged Pain Reliably Slows Peak Alpha Frequency by Reducing Fast Alpha Power

  1. Program in Neuroscience, University of Maryland School of Medicine, Baltimore, MD, 21201, United States
  2. Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore, MD, 21201, United States
  3. Center to Advance Chronic Pain Research, University of Maryland Baltimore, Baltimore, MD, 21201, United States
  4. Department of Epidemiology and Public Health, University of Maryland Baltimore, Baltimore, MD, 21201, United States
  5. School of Psychology, University of Birmingham, B15 2TT, United Kingdom

Peer review process

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.

Read more about eLife’s peer review process.

Editors

  • Reviewing Editor
    Markus Ploner
    Department of Neurology and TUM-Neuroimaging Center, TUM School of Medicine and Health, Technical University of Munich (TUM), Munich, Germany
  • Senior Editor
    Christian Büchel
    University Medical Center Hamburg-Eppendorf, Hamburg, Germany

Reviewer #1 (Public review):

Summary:

Furman et al. reanalyze data from a previous study and investigate alterations of peak alpha frequency (PAF) and alpha power (AP) in the context of prolonged pain with electroencephalography (EEG). Using two experimental pain models (phasic and capsaicin heat pain), they set out to clarify if previously reported changes in alpha activity in chronic pain can already be observed during prolonged pain in healthy human participants. They conclude that PAF is reliably slowed, and AP reliably decreased in response to prolonged pain. From the patterns of their findings, they furthermore deduce that AP changes indicate the presence of ongoing pain while PAF changes reflect pain-associated states like sensitization which can outlast ongoing pain percepts and indicate a potential for experiencing pain. Lastly, they conclude that the reported changes in alpha activity are likely due to specific power decreases in the faster alpha range between 10 and 12 Hz and discuss potential clinical implications of their findings in terms of risk biomarkers and early pain interventions.

Strengths:

The study focuses on a timely topic with potential implications for chronic pain diagnosis and treatment, an area that urgently needs new approaches. The addressed questions nicely build upon and extend the previous work of the authors. The analyzed data set is comprehensive including two different prolonged pain paradigms, two visits following the same experimental procedures, and a total sample size of n = 61 participants. Thereby, it enabled internal replications of findings across both paradigms and visits, which is important to confirm the consistency of findings.

Weaknesses:

One overarching difficulty is the high number of analyses presented by the authors. They were in part developed "on the go", are not always easy to follow, and sidetrack the reader from the main findings. Only a minor part of the analyses is described in the methods section, while many analyses are outlined within the results, the supplementary material, and/or figure legends. In addition, a range of purely descriptive findings are displayed. Overall, the manuscript would clearly benefit from a more streamlined and consistent presentation of the applied methods and results.

Concerning the main findings, the presented evidence for a slowing of PAF and a reduction of AP in the context of both phasic and capsaicin heat pain and across both visits is convincing. The location of the peak of the effect at left frontocentral areas, however, remains puzzling. The authors convincingly show that the effect cannot be explained by activity related to the pain rating procedure and provide evidence that an effect of the same direction can also observed at corresponding electrodes contralateral to pain stimulation. However, further reasons are not discussed.

The conclusion that PAF slowing might be more related to pain-associated states like sensitization rather than the presence of ongoing pain is deduced from a continued slowing of PAF after capsaicin-induced pain has subsided, while AP goes back to baseline values. Although this speculation is interesting, the readers should be aware that this dissociation was unexpected and resulted in changes in the main a-priori-defined statistical contrasts presented in the methods section. Further replications in future studies are needed to strengthen this finding.

The last conclusion made by the authors is that the observed changes in alpha activity are caused by specific changes in the faster alpha range and are the least convincing. If I understand correctly, the only presented statistical evidence corroborating this conclusion is based on the single selected electrode C3 shown in Figure 5 A, D, and E. With the remaining parts of Figure 5 and Figure 6, differences are discussed but Figures do not include statistical results. Unless the discussed findings are backed up more clearly, the degree of mechanistic conclusions concerning the 10-12 Hz power changes throughout the title, abstract, and main manuscript and in relation to the multiple oscillators model seems not justified.

Lastly, it is important to note that the current manuscript was published as a preprint in 2021. Thus, the cited literature still needs to be updated, and the present findings need to be integrated with the work published since. For example, a recent systematic review on potential M/EEG-based biomarkers of chronic pain (Zebhauser et al., 2023, Pain) revealed that previous evidence concerning changes of alpha activity in chronic pain is much less consistent than currently outlined in the manuscript.

Overall:

All in all, the presented findings extend previous knowledge concerning the role of alpha activity in pain and thus represent a valuable contribution towards a better understanding of the mechanisms of pain and potential new treatment targets.

Reviewer #2 (Public review):

Summary:

This study investigated the modulation of alpha oscillations, specifically peak alpha frequency (PAF) and alpha power, during prolonged pain. The findings suggest that the alpha rhythm consists of multiple, independent oscillators, and suggest that the modulation of a "fast" oscillator may represent a promising therapeutic target for ongoing pain management.

Strengths:

EEG data were collected from a relatively large sample of participants, and the experiment was conducted using two prolonged pain models - phasic heat pain and capsaicin heat pain - at two separate testing visits approximately 8 weeks apart. The study produced reliable results across different pain models and at different testing intervals.

Weaknesses:

There are discrepancies between the results and their interpretation, indicating a need for more appropriate data analyses. Additionally, the experimental design does not adequately control for the potential time effects, which cannot be ruled out as a confounding factor.

Reviewer #3 (Public review):

Summary:

Furman et al. investigated how exposure to prolonged pain impacts human alpha oscillations recorded by electroencephalography (EEG). Two experimental models of prolonged pain were employed in healthy participants, phasic heat pain (PHP) and capsaicin heat pain (CHP). 61 participants completed two identical study visits separated by at least 8 weeks. Peak alpha frequency was reliably slowed by exposure to prolonged pain, whereas overall alpha power was reliably reduced. Both effects appeared to reflect a specific decrease in higher frequency (10-12Hz) alpha activity. The authors suggest that slowing of alpha oscillations is a reliable neural correlate of pain exposure and that manipulation of alpha activity may hold promise for treating chronic pain.

Strengths:

The study uses a within-participants design to show that exposure to pain is associated with acute changes in both the power and frequency of alpha oscillations.

By employing two experimental models of pain exposure and two separate testing visits, the authors were able to show that the effects of pain exposure on alpha activity are replicable across models and time.

Rigorous analysis approaches are used throughout.

Weaknesses:

No a priori power analysis is presented and (due to exclusions) most of the analyses conducted included (sometimes considerably) fewer participants than the overall sample size.

It is not clear whether the power and frequency changes represent two sides of the same coin or whether they reflect distinct mechanisms. The authors suggest in the manuscript that both effects may be explained by decreased power in 'fast' (8-12 Hz) alpha activity, but at other times interpret the effects to potentially represent distinct mechanisms. It would be useful for the authors to further clarify their thoughts on this point.

The statistical significance of some of the effects was dependent on analysis choices such as the exact frequency range chosen to identify alpha peaks.

No control condition was used, and I was left wondering if the effects would be specific to painful stimuli, or would also see the same effects for pleasant or neutral somatosensory stimuli?

  1. Howard Hughes Medical Institute
  2. Wellcome Trust
  3. Max-Planck-Gesellschaft
  4. Knut and Alice Wallenberg Foundation