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. 2020 Jan-Dec:16:1744806920902350.
doi: 10.1177/1744806920902350.

Sleep spindles as a diagnostic and therapeutic target for chronic pain

Bassir Caravan  1 , Lizbeth Hu  1 , Daniel Veyg  2 , Prathamesh Kulkarni  3 , Qiaosheng Zhang  4 , Zhe S Chen  3   5   6 , Jing Wang  4   5   6
Affiliations

Sleep spindles as a diagnostic and therapeutic target for chronic pain

Bassir Caravan et al. Mol Pain. 2020 Jan-Dec.

Abstract

Pain is known to disrupt sleep patterns, and disturbances in sleep can further worsen pain symptoms. Sleep spindles occur during slow wave sleep and have established effects on sensory and affective processing in mammals. A number of chronic neuropsychiatric conditions, meanwhile, are known to alter sleep spindle density. The effect of persistent pain on sleep spindle waves, however, remains unknown, and studies of sleep spindles are challenging due to long period of monitoring and data analysis. Utilizing automated sleep spindle detection algorithms built on deep learning, we can monitor the effect of pain states on sleep spindle activity. In this study, we show that in a chronic pain model in rodents, there is a significant decrease in sleep spindle activity compared to controls. Meanwhile, methods to restore sleep spindles are associated with decreased pain symptoms. These results suggest that sleep spindle density correlates with chronic pain and may be both a potential biomarker for chronic pain and a target for neuromodulation therapy.

Keywords: Sleep spindles; chronic pain; diagnostic; pink noise; therapeutic.

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Figures

Figure 1.
Figure 1.
Automated sleep spindle density measurements. (a) This schematic represents the experimental setup with cameras recording rats movement in sleep and awake states. (b) Rat movements obtained from an accelerometer during sleep, indicating activity of the rat during a representative recording session. (c) Sleep scores manually obtained from monitoring video feed of the rat during experimentation. (d) Raw EEG signal at 1 kHz (blue) obtained from sleep superimposed with downsampled to 200 Hz signal (orange). (e) Raw output (orange) probabilities from the SpindleNet automated detection network threshold (blue) for recognizing spindles.
Figure 2.
Figure 2.
Sleep spindle density decreases in the chronic pain state. Individual rats have different baseline spindle densities, thus all were normalized to the average of their baseline recordings. (a) Relative spindle density for CFA-treated rats (n = 3) and saline controls (n = 4) on days 1 and 7 after injection. An unpaired t-test showed statistically significant decrease in average spindle density in the CFA-treated rats compared to controls one day post-injection (P = 0.0189). Differences in spindle density diminished over time as rodents recovered from inflammatory pain induced by the CFA model and since baseline recordings increased as seen on day 7 post-injection (unpaired t-test; P = 0.1902). (b) The mechanical nociceptive threshold (50% MNT) for CFA- and saline-treated rats. After injection with CFA, rodents experienced significant reductions in nociceptive threshold from baseline compared to saline; unpaired t-test on day 1 (P = 0.0002), day 3 (P = 0.0008), day 5 (P = 0.0004), and day 7 (P = 0.0016). (c) As CFA-treated rats recovered from persistent pain, as indicated by nociceptive threshold measurements, we observed a correlation between nociceptive threshold and spindle density in S1, using a linear regression analysis (R2 = 0.4548). CFA: Complete Freund’s Adjuvant; MNT: mechanical nociceptive threshold.
Figure 3.
Figure 3.
Pink noise stimulation reduces pain behaviors. (a) In the presence of pink noise, we found that for (n = 3) sessions across (n = 3) CFA-treated rats, there was a significant increase (P = 0.04, unpaired Student’s t-tests) in spindle density. (b) A representative sleep session where blue indicates spindles during silence and pink denotes the presence of aforementioned pink noise stimulation, revealing spindle enhancement. (c) The raw trace of the EEG signal (blue) superimposed with pink noise waveform (pink) shows how spindles might be stimulated. Spindles detected were in previously accepted frequency ranges of 10–15 Hz. (d) There was no statistically significant difference in detected spindle frequency (P = 0.0508), power (P = 0.9357), or duration (P = 0.9357) between artificial and natural spindles after unpaired t-test analysis. (e) Effect of pink noise stimulation on nociceptive threshold in rats with spared nerve injury. After pink noise stimulation of (n = 7) rats for 14 consecutive days, we compared 50% withdrawal threshold with allodynia testing before and after treatment and found that there was a significant increase after treatment with an average increase of 2.77 g (P = 0.016; unpaired Student’s t-tests).
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