Background & Aims

Understanding how sleep disturbance contributes to chronic pain is a topic which has garnered substantial attention in recent years. However, the majority of work to date has overlooked a crucial piece of the pathophysiological puzzle, by attempting to decipher biomarkers from EEG features obtained during sleep. Frequent nighttime awakenings, often initiated by pain, are chief complaints amongst chronic pain patients, and often lead to engagement with maladaptive cognitions. Therefore, EEG sampled during these periods may offer valuable insights into pain mechanisms among individuals with sleep disturbance. Recent findings from daytime EEG point to fruitful biomarkers, such as peak alpha frequency, which map onto pain sensitivity and disease chronicity. Therefore, we sought to investigate whether parameters of alpha power measured during nocturnal awakenings were associated with pain experienced the following day in patients with chronic low back pain receiving chronic opioid therapy.

Methods

One night of wireless sleep-EEG were obtained in patients with chronic low back pain on chronic opioid therapy (N=30), alongside pain severity and interference, using ecological momentary assessments. EEG was scored to identify wake occurring after sleep onset. We then used multi-taper spectral analyses to calculate power (log10*µv/Hz2) across the alpha band (9-11hz), the frequency (Hz) and power (log10*µv/Hz2) of the largest peak within the alpha spectrum. As alpha power estimates contain components of the aperiodic and periodic spectra, we also calculated the center frequency and power of the periodic alpha peak using FOOOF[1] parameterization, in order to determine specificity to periodic oscillations. Unadjusted linear regressions, tested for a relationship between alpha parameters during awakenings with reports obtained the following morning (current morning pain, average nighttime pain over the previous night) and evening, rating pain and pain impact (PEG) throughout the day.

Results

Linear regression models demonstrated that none of the alpha parameters measured were significantly associated with current pain in the morning. However, reduced broadband alpha power during awakenings was associated with increased average pain intensity (b = -0.46, p = 0.03) and increased average pain impact (b = -0.51, p = 0.01) across the daytime period. The power of the alpha peak was significantly associated with pain impact (b = -0.44, p = 0.04), however this effect was not significant when examining the periodic alpha peak. The center frequency of the alpha peak was not significantly associated with average pain intensity or pain impact when measured either aperiodic or periodic assessment methods.

Conclusions

We present here novel findings underscoring the potential of nocturnal EEG recordings to elicit future insights into chronic pain and potentially unexplored mechanisms. Our findings, which depict a lack of relationship of alpha power with morning pain, yet a strong relation to daytime pain, are consistent with the concept of nocturnal awakenings contributing to the progressive worsening of pain throughout the subsequent daytime. Future work with a larger sample should examine the interaction of alpha power and frequency of nocturnal awakenings to evaluate if the effect of nocturnal wake alpha power on next-day pain is independent of the known effect of nocturnal awakenings. Additionally, as a relationship between peak alpha frequency and next-day pain was not observed, future work should evaluate potential differences between daytime and nocturnal EEG recordings. Furthermore, differences in findings between aperiodic and periodic estimates warrant investigation in future studies.

References

[1] Haller, M., Donoghue, T., Peterson, E., Varma, P., Sebastian, P., Gao, R., Noto, T., Knight, R. T., Shestyuk, A., & Voytek, B. (2018). Parameterizing neural power spectra. Neuroscience.

Presenting Author

Matthew J Reid

Poster Authors

Matthew Reid

BMedSci MSc DPhil

Johns Hopkins School of Medicin

Lead Author

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Alec Ritter BS

University of Virginia, Charlottesville

Lead Author

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Liza Abraham BS

Johns Hopkins School of Medicine

Lead Author

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Michelle Mei BS

Johns Hopkins School of Medicine

Lead Author

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Michael T Smith PhD CBSM

Johns Hopkins School of Medicine

Lead Author

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Alexandros BA

Veterans Affairs, Durham, NC.

Lead Author

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Julia Camacho-Wejbrandt BSc

Kings College London

Lead Author

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Patrick H Finan. PhD

University of Virginia, Charlottesville

Lead Author

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Topics

  • Lifestyle Issues: Sleep/Diet/Exercise/Social Interactions