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Neuronal ensemble activity entrained by local field potential (LFP) patterns underlies a variety of brain functions, including emotion, cognition, and pain perception. Recent advances in machine learning approaches may enable more effective methods for analyzing LFP patterns across multiple brain areas than conventional time-frequency analysis. In this study, we tested the performance of two machine learning algorithms, AlexNet and the Transformer models, to classify LFP patterns in eight pain-related brain regions before and during acetic acid-induced visceral pain behaviors. Over short time windows lasting several seconds, applying AlexNet to LFP power datasets, but not to raw time-series LFP traces from multiple brain areas, successfully achieved superior classification performance compared with simple LFP power analysis. Furthermore, applying the Transformer directly to the raw LFP traces achieved significantly superior classification performance than AlexNet when using LFP power datasets. These results demonstrate the utility of the Transformer in the analysis of neurophysiological signals, and pave the way for its future applications in the decoding of more complex neuronal activity patterns. [ABSTRACT FROM AUTHOR]

Although anesthesia provides favorable conditions for surgical procedures, recent studies have revealed that the brain remains active in processing noxious signals even during anesthesia. However, whether and how these responses affect the anesthesia effect remains unclear. The ventrolateral periaqueductal gray (vlPAG), a crucial hub for pain regulation, also plays an essential role in controlling general anesthesia. Hence, it was hypothesized that the vlPAG may be involved in the regulation of general anesthesia by noxious stimuli. Here, we found that acute noxious stimuli, including capsaicin-induced inflammatory pain, acetic acid-induced visceral pain, and incision-induced surgical pain, significantly delayed recovery from sevoflurane anesthesia in male mice, whereas this effect was absent in the spared nerve injury-induced chronic pain. Pretreatment with peripheral analgesics could prevent the delayed recovery induced by acute nociception. Furthermore, we found that acute noxious stimuli, induced by the injection of capsaicin under sevoflurane anesthesia, increased c-Fos expression and activity in the GABAergic neurons of the ventrolateral periaqueductal gray. Specific reactivation of capsaicin-activated vlPAGGABA neurons mimicked the effect of capsaicin and its chemogenetic inhibition prevented the delayed recovery from anesthesia induced by capsaicin. Finally, we revealed that the vlPAGGABA neurons regulated the recovery from anesthesia through the inhibition of ventral tegmental area dopaminergic neuronal activity, thus decreasing dopamine (DA) release and activation of DA D1-like receptors in the brain. These findings reveal a novel, cell- and circuit-based mechanism for regulating anesthesia recovery by nociception, and it is important to provide new insights for guiding the management of the anesthesia recovery period. [ABSTRACT FROM AUTHOR]

Abstract: Preventive treatment is crucial for patients with chronic migraine (CM). This study explored the association between resting-state cortical oscillations and 3-month treatment outcome in patients with CM. Treatment-naïve patients with CM were recruited with their demographic data, psychosocial data, and headache profiles as well as the healthy controls (HCs). Resting-state cortical activities were recorded using an electroencephalogram and analysed using source-based and electrode-based spectral power method. The regions of interest were the bilateral primary somatosensory (S1) and visual (V1) cortices. After 3-month treatment with flunarizine, patients with CM were categorized into responders and nonresponders. Demographic, clinical, and electroencephalogram data from 72 patients with CM and 50 HCs were analysed. Elevated anxiety, depression, and stress were observed in patients with CM. Theta power in bilateral S1 and alpha and gamma powers in the right S1 increased in patients with CM. Nonresponders (n = 34) exhibited larger alpha powers in bilateral V1 than those in responders (n = 38). Alpha powers also exhibited significant correlations with changes of monthly headache days. Notably, in responders and nonresponders, occipital alpha powers did not differ at baseline and in the third month. In conclusion, patients with CM who were not responsive to preventive treatment were associated with augmented resting-state occipital alpha activity. Moreover, changes in migraine attack frequency were associated with baseline occipital alpha power. However, the prognostic feature of visual alpha oscillation seems to be inherent because it is not altered by flunarizine treatment. These findings may be useful for developing personalised migraine treatment plans., (Copyright © 2021 International Association for the Study of Pain.)

The thalamocortical (TC) circuit is closely associated with pain processing. The hyperpolarization-activated cyclic nucleotide-gated (HCN) 2 channel is predominantly expressed in the ventral posterolateral thalamus (VPL) that has been shown to mediate neuropathic pain. However, the role of VPL HCN2 in modulating TC circuit activity is largely unknown. Here, by using optogenetics, neuronal tracing, electrophysiological recordings, and virus knockdown strategies, we showed that the activation of VPL TC neurons potentiates excitatory synaptic transmission to the hindlimb region of the primary somatosensory cortex (S1HL) as well as mechanical hypersensitivity following spared nerve injury (SNI)-induced neuropathic pain in mice. Either pharmacological blockade or virus knockdown of HCN2 (shRNA-Hcn2) in the VPL was sufficient to alleviate SNI-induced hyperalgesia. Moreover, shRNA-Hcn2 decreased the excitability of TC neurons and synaptic transmission of the VPL–S1HL circuit. Together, our studies provide a novel mechanism by which HCN2 enhances the excitability of the TC circuit to facilitate neuropathic pain. [ABSTRACT FROM AUTHOR]

To identify and validate the neural signatures of resting-state oscillatory connectivity for chronic migraine (CM), we used machine learning techniques to classify patients with CM from healthy controls (HC) and patients with other pain disorders. The cross-sectional study obtained resting-state magnetoencephalographic data from 240 participants (70 HC, 100 CM, 35 episodic migraine [EM], and 35 fibromyalgia [FM]). Source-based oscillatory connectivity of relevant cortical regions was calculated to determine intrinsic connectivity at 1–40 Hz. A classification model that employed a support vector machine was developed using the magnetoencephalographic data to assess the reliability and generalizability of CM identification. In the findings, the discriminative features that differentiate CM from HC were principally observed from the functional interactions between salience, sensorimotor, and part of the default mode networks. The classification model with these features exhibited excellent performance in distinguishing patients with CM from HC (accuracy ≥ 86.8%, area under the curve (AUC) ≥ 0.9) and from those with EM (accuracy: 94.5%, AUC: 0.96). The model also achieved high performance (accuracy: 89.1%, AUC: 0.91) in classifying CM from other pain disorders (FM in this study). These resting-state magnetoencephalographic electrophysiological features yield oscillatory connectivity to identify patients with CM from those with a different type of migraine and pain disorder, with adequate reliability and generalizability. [ABSTRACT FROM AUTHOR]

Chronic pain is a severely debilitating condition that reflects a long-term sensitization of signal transduction in the afferent pain pathway. Among the key players in this pathway are T-type calcium channels, in particular the Cav3.2 isoform. Because of their biophysical characteristics, these channels are ideally suited towards regulating neuronal excitability. Recent evidence suggests that T-type channels contribute to excitability of neurons all along the ascending and descending pain pathways, within primary afferent neurons, spinal dorsal horn neurons, and within pain-processing neurons in the midbrain and cortex. Here we review the contribution of T-type channels to neuronal excitability and function in each of these neuronal populations and how they are dysregulated in chronic pain conditions. Finally, we discuss their molecular pharmacology and the potential role of these channels as therapeutic targets for chronic pain. [ABSTRACT FROM AUTHOR]