Abnormal alpha band power in the dynamic pain connectome is a marker of chronic pain with a neuropathic component
Bibliographic record
Abstract
We previously identified alpha frequency slowing and beta attenuation in the dynamic pain connectome related to pain severity and interference in patients with multiple sclerosis-related neuropathic pain (NP). Here, we determined whether these abnormalities, are markers of aberrant temporal dynamics in non-neuropathic inflammatory pain (non-NP) or when NP is also suspected. We measured resting-state magnetoencephalography (MEG) spectral density in 45 people (17 females, 28 males) with chronic back pain due to ankylosing spondylitis (AS) and 38 age/sex matched healthy controls. We used painDETECT scores to divide the chronic pain group into those with only non-NP (NNP) and those who likely also had a component of NP in addition to their inflammatory pain. We also assessed pain severity, pain interference, and disease activity with the Brief Pain Inventory and Bath AS Disease Activity Index (BASDAI). We examined spectral power in the dynamic pain connectome, including nodes of the ascending nociceptive pathway (ANP), default mode (DMN), and salience networks (SN). Compared to the healthy controls, the AS patients exhibited increased theta power in the DMN and decreased low-gamma power in the DMN and ANP, but did not exhibit beta-band attenuation or peak-alpha slowing. The NNP patients were not different from HCs. Compared to both healthy controls and NNP, NP patients had increased alpha power in the ANP. Increased alpha power within the ANP was associated with reduced BASDAI in the NNP group, and increased pain in the mixed-NP group within the DMN, SN, and ANP. Thus, high theta and low gamma activity may be markers of chronic pain but high alpha-band activity may relate to particular features of neuropathic chronic pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".