The Neural Origin of Nociceptive-Induced Gamma-Band Oscillations

Yue, Lupeng; Iannetti, Gian Domenico; Hu, Li

doi:10.1523/jneurosci.0255-20.2020

Cited by 36 publications

(35 citation statements)

References 75 publications

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“…Pain-related gamma oscillatory activity in the somatosensory S1 predicts pain sensitivity (Hauck et al, 2007;Heid et al, 2020;Hu and Iannetti, 2019) and inducing gamma oscillations in SI enhances nociceptive sensitivity and induces aversive avoidance behavior (Tan et al, 2019). Furthermore, noxious laser evoked spiking in superficial S1 interneurons has strong phase coherence with gamma oscillations in awake rats (Yue et al, 2020). C fibre activity was also associated with increases in beta energy at >500ms latency post stimulus.…”

Section: Discussionmentioning

confidence: 95%

“…For example, the amplitudes of both alpha and beta rhythms in rat S1 are suppressed by a tactile stimulus, with a comparable time course to humans (Fransen et al, 2016) and noxious skin stimulation results in selective increases in S1 gamma activity in both rodents and human subjects (Hu and Iannetti, 2019). Gamma activity reflects stimulus encoding in S1 (Yue et al, 2020) and experimental induction of S1 gamma oscillations via optogenetic activation of parvalbumin-expressing inhibitory interneurons enhances nociceptive sensitivity and induces aversive avoidance behaviour (Tan et al, 2019). Changes in other oscillatory frequencies are also reported following skin stimulation, including decreases in alpha and beta energy related to cutaneous stimulus intensity (Nickel et al, 2017) and synchronization of theta-alpha energy following noxious stimulation (Peng et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Distinct Age-Dependent C Fiber-Driven Oscillatory Activity in the Rat Somatosensory Cortex

Chang

Fabrizi

Fitzgerald

2020

eNeuro

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When skin afferents are activated, the sensory signals are transmitted to the spinal cord and eventually reach the primary somatosensory cortex (SI), initiating the encoding of the sensory percept in the brain. While subsets of primary afferents mediate specific somatosensory information from an early age, the subcortical pathways that transmit this information undergo striking changes over the first weeks of life, reflected in the gradual emergence of specific sensory behaviours. We therefore hypothesised that this period is associated with differential changes in the encoding of incoming afferent volleys in SI. To test this, we compared SI responses to A fibre skin afferent stimulation and A+C skin afferent fibre stimulation in lightly anaesthetised male rats at postnatal day (P) 7, 14, 21 and 30. Differences in SI activity following A and A+C fibre stimulation changed dramatically over this period. At P30, A+C fibre stimulation evoked significantly larger gamma, beta and alpha energy increases compared to A fibre stimulation alone. At younger ages, the changes in S1 oscillatory activity evoked by the two afferent volleys were not significantly different. Silencing TRPV1+ C fibres with QX-314 significantly reduced the gamma and beta SI oscillatory energy increases evoked by A+C fibres, at P30 and P21, but not at younger ages. Thus, C fibres differentially modulate SI oscillatory activity only from the third postnatal week, well after the functional maturation of the somatosensory cortex. This age-related change in afferent evoked S1 oscillatory activity may underpin the maturation of sensory discrimination in the developing brain. Significance Statement Behavioural responses to sensory stimulation of the skin undergo major developmental changes over the first postnatal weeks. Here we show that this is accompanied by a shift in the differential frequency encoding of sensory A fibre and C fibre afferent inputs into the developing rat somatosensory cortex. The results demonstrate major postnatal changes in the ability of the cortex to differentiate between afferent sensory inputs arriving in the mammalian brain.

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Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Distinct Age-Dependent C Fiber-Driven Oscillatory Activity in the Rat Somatosensory Cortex

Chang

Fabrizi

Fitzgerald

2020

eNeuro

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“…In the present study, we observed that the spectral power density of gamma band oscillations was positively correlated with the subjective report of postoperative pain. This observation provided additional evidence for the close relationship between gamma band oscillation and pain perception across different human subjects and might be related to the possible communication between distributed neuronal ensembles for subsequent pain-related behaviors [ 5 , 11 ].…”

Section: Discussionmentioning

confidence: 95%

The Prediction of Acute Postoperative Pain Based on Neural Oscillations Measured before the Surgery

et al. 2021

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Even with an improved understanding of pain mechanisms and advances in perioperative pain management, inadequately controlled postoperative pain remains. Predicting acute postoperative pain based on presurgery physiological measures could provide valuable insights into individualized, effective analgesic strategies, thus helping improve the analgesic efficacy. Considering the strong correlation between pain perception and neural oscillations, we hypothesize that acute postoperative pain could be predicted by neural oscillations measured shortly before the surgery. Here, we explored the relationship between neural oscillations 2 hours before the thoracoscopic surgery and the subjective intensity of acute postoperative pain. The spectral power density of resting-state beta and gamma band oscillations at the frontocentral region was significantly different between patients with different levels of acute postoperative pain (i.e., low pain vs. moderate/high pain). A positive correlation was also observed between the spectral power density of resting-state beta and gamma band oscillations and subjective reports of postoperative pain. Then, we predicted the level of acute postoperative pain based on features of neural oscillations using machine learning techniques, which achieved a prediction accuracy of 92.54% and a correlation coefficient between the real pain intensities and the predicted pain intensities of 0.84. Altogether, the prediction of acute postoperative pain based on neural oscillations measured before the surgery is feasible and could meet the clinical needs in the future for better control of postoperative pain and other unwanted negative effects. The study was registered on the Clinical Trial Registry (https://clinicaltrials.gov/ct2/show/NCT03761576?term=NCT03761576&draw=2&rank=1) with the registration number NCT03761576.

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“…此外, 在长时疼痛和慢性 [63] , 且疼痛诱发的GBOs和听觉诱发的GBOs有明显差异 [51] . 此外, 炎症痛小鼠的自发GBOs增强, 且其诱发GBOs与其痛觉超敏行为相关 [64] , 提示长时疼痛下的GBOs与疼痛行 [66] , 揭示了激光热痛诱发的GBOs主要来自刺激部位对侧 S1浅层中间神经元(interneurons)放电 [67] .…”

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