Brain Rhythms of Pain

Closed-Loop Infraslow Brain-Computer Interface can Modulate Cortical Activity and Connectivity in Individuals With Chronic Painful Knee Osteoarthritis: A Secondary Analysis of a Randomized Placebo-Controlled Clinical Trial

Introduction. Chronic pain is a percept due to an imbalance in the activity between sensory-discriminative, motivational-affective, and descending pain-inhibitory brain regions. Evidence suggests that electroencephalography (EEG) infraslow fluctuation neurofeedback (ISF-NF) training can improve clinical outcomes. It is unknown whether such training can induce EEG activity and functional connectivity (FC) changes. A secondary data analysis of a feasibility clinical trial was conducted to determine whether EEG ISF-NF training can significantly alter EEG activity and FC between the targeted cortical regions in people with chronic painful knee osteoarthritis (OA). Methods. A parallel, two-arm, double-blind, randomized, sham-controlled clinical trial was conducted. People with chronic knee pain associated with OA were randomized to receive sham NF training or source-localized ratio ISF-NF training protocol to down-train ISF bands at the somatosensory (SSC), dorsal anterior cingulate (dACC), and uptrain pregenual anterior cingulate cortices (pgACC). Resting state EEG was recorded at baseline and immediate post-training. Results. The source localization mapping demonstrated a reduction (P = .04) in the ISF band activity at the left dorsolateral prefrontal cortex (LdlPFC) in the active NF group. Region of interest analysis yielded significant differences for ISF (P = .008), slow (P = .007), beta (P = .043), and gamma (P = .012) band activities at LdlPFC, dACC, and bilateral SSC. The FC between pgACC and left SSC in the delta band was negatively correlated with pain bothersomeness in the ISF-NF group. Conclusion. The EEG ISF-NF training can modulate EEG activity and connectivity in individuals with chronic painful knee osteoarthritis, and the observed EEG changes correlate with clinical pain measures.

Establishing the relationship between subjective perception and neural responses: Insights from correlation analysis and representational similarity analysis

Exploring the relationship between sensory perception and brain responses holds important theoretical and clinical implications. However, commonly used methodologies like correlation analysis performed either intra- or inter- individually often yield inconsistent results across studies, limiting their generalizability. Representational similarity analysis (RSA), a method that assesses the perception-response relationship by calculating the correlation between behavioral and neural patterns, may offer a fresh perspective to reveal novel findings. Here, we delivered a series of graded sensory stimuli of four modalities (i.e., nociceptive somatosensory, non-nociceptive somatosensory, visual, and auditory) to/near the left or right hand of 107 healthy subjects and collected their single-trial perceptual ratings and electroencephalographic (EEG) responses. We examined the relationship between sensory perception and brain responses using within- and between-subject correlation analysis and RSA, and assessed their stability across different numbers of subjects and trials. We found that within-subject and between-subject correlations yielded distinct results: within-subject correlation revealed strong and reliable correlations between perceptual ratings and most brain responses, while between-subject correlation showed weak correlations that were vulnerable to the change of subject number. In addition to verifying the correlation results, RSA revealed some novel findings, i.e., correlations between behavioral and neural patterns were observed in some additional neural responses, such as "γ-ERS" in the visual modality. RSA results were sensitive to the trial number, but not to the subject number, suggesting that consistent results could be obtained for studies with relatively small sample sizes. In conclusion, our study provides a novel perspective on establishing the relationship between behavior and brain activity, emphasizing that RSA holds promise as a method for exploring this pattern relationship in future research.

Time-varying phase synchronization of resting-state functional magnetic resonance imaging reveals a shift toward self-referential processes during sustained pain

ABSTRACT

Growing evidence has suggested that time-varying functional connectivity between different brain regions might underlie the dynamic experience of pain. This study used a novel, data-driven framework to characterize the dynamic interactions of large-scale brain networks during sustained pain by estimating recurrent patterns of phase-synchronization. Resting-state functional magnetic resonance imaging signals were collected from 50 healthy participants before (once) and after (twice) the onset of sustained pain that was induced by topical application of capsaicin cream. We first decoded the instantaneous phase of neural activity and then applied leading eigenvector dynamic analysis on the time-varying phase-synchronization. We identified 3 recurrent brain states that show distinctive phase-synchronization. The presence of state 1, characterized by phase-synchronization between the default mode network and auditory, visual, and sensorimotor networks, together with transitions towards this brain state, increased during sustained pain. These changes can account for the perceived pain intensity and reported unpleasantness induced by capsaicin application. In contrast, state 3, characterized by phase-synchronization between the cognitive control network and sensory networks, decreased after the onset of sustained pain. These results are indicative of a shift toward internally directed self-referential processes (state 1) and away from externally directed cognitive control processes (state 3) during sustained pain.

Enhanced EEG power density during painful stretching in individuals with cerebral palsy

BACKGROUND

Pain perception mechanisms in cerebral palsy remain largely unclear.

AIMS

This study investigates brain activity in adults with cerebral palsy during painful and non-painful stretching to elucidate their pain processing characteristics.

METHODS AND PROCEDURES

Twenty adults with cerebral palsy and 20 controls underwent EEG in three conditions: rest, non-painful stretching, and painful stretching. Time-frequency power density of theta, alpha, and beta waves in somatosensory and frontal cortices was analyzed, alongside baseline pressure pain thresholds.

OUTCOMES AND RESULTS

Cerebral palsy individuals exhibited higher theta, alpha, and beta power density in both cortices during painful stretching compared to rest, and lower during non-painful stretching. Controls showed higher power density during non-painful stretching but lower during painful stretching. Cerebral palsy individuals had higher pain sensitivity, with those more sensitive experiencing greater alpha power density.

CONCLUSIONS AND IMPLICATIONS

These findings confirm alterations in the cerebral processing of pain in individuals with cerebral palsy. This knowledge could enhance future approaches to the diagnosis and treatment of pain in this vulnerable population.

Modulation of pain perception through transcranial alternating current stimulation and its nonlinear relationship with the simulated electric field magnitude

BACKGROUND

Oscillatory activities observed in multiple regions are closely associated with the experience of pain. Specifically, oscillatory activities within the theta- and beta-frequency bands, observed in the left dorsolateral prefrontal cortex (DLPFC), have been implicated in pain perception among healthy individuals and those with chronic pain. However, their physiological significance remains unclear.

METHODS

We explored the modulation of pain perception in healthy individuals by theta- and beta-band transcranial alternating current stimulation (tACS) over the left DLPFC and examined the relationship between the modulation effect and magnitude of the electric field elicited by tACS in the left DLPFC using computational simulation.

RESULTS

Our findings revealed that both theta- and beta-tACS increased the heat pain threshold during and after stimulation. Notably, the simulated electric field magnitude in the left DLPFC exhibited an inverted U-shaped relationship with the pain modulation effect for theta-tACS.

CONCLUSIONS

Our study findings suggested that there would be an optimal electric field strength to produce a high analgesic effect for theta-tACS.

SIGNIFICANCE

The application of theta- and beta-tACS interventions targeting the left DLPFC might facilitate the treatment of chronic pain. Furthermore, the attainment of effective pain modulation via theta-tACS over the DLPFC warrants the use of optimal stimulus intensity.

Noninvasive neuromodulation of subregions of the human insula differentially affect pain processing and heart-rate variability: a within-subjects pseudo-randomized trial

ABSTRACT

The insula is an intriguing target for pain modulation. Unfortunately, it lies deep to the cortex making spatially specific noninvasive access difficult. Here, we leverage the high spatial resolution and deep penetration depth of low-intensity focused ultrasound (LIFU) to nonsurgically modulate the anterior insula (AI) or posterior insula (PI) in humans for effect on subjective pain ratings, electroencephalographic (EEG) contact heat-evoked potentials, as well as autonomic measures including heart-rate variability (HRV). In a within-subjects, repeated-measures, pseudo-randomized trial design, 23 healthy volunteers received brief noxious heat pain stimuli to the dorsum of their right hand during continuous heart-rate, electrodermal, electrocardiography and EEG recording. Low-intensity focused ultrasound was delivered to the AI (anterior short gyrus), PI (posterior longus gyrus), or under an inert Sham condition. The primary outcome measure was pain rating. Low-intensity focused ultrasound to both AI and PI similarly reduced pain ratings but had differential effects on EEG activity. Low-intensity focused ultrasound to PI affected earlier EEG amplitudes, whereas LIFU to AI affected later EEG amplitudes. Only LIFU to the AI affected HRV as indexed by an increase in SD of N-N intervals and mean HRV low-frequency power. Taken together, LIFU is an effective noninvasive method to individually target subregions of the insula in humans for site-specific effects on brain biomarkers of pain processing and autonomic reactivity that translates to reduced perceived pain to a transient heat stimulus.

Brain effect mechanism of lever positioning manipulation on LDH analgesia based on multimodal MRI: a study protocol

INTRODUCTION

The clinical symptoms of Lumbar Disc Herniation (LDH) can be effectively ameliorated through Lever Positioning Manipulation (LPM), which is closely linked to the brain's pain-regulating mechanisms. Magnetic Resonance Imaging (MRI) offers an objective and visual means to study how the brain orchestrates the characteristics of analgesic effects. From the perspective of multimodal MRI, we applied functional MRI (fMRI) and Magnetic Resonance Spectrum (MRS) techniques to comprehensively evaluate the characteristics of the effects of LPM on the brain region of LDH from the aspects of brain structure, brain function and brain metabolism. This multimodal MRI technique provides a biological basis for the clinical application of LPM in LDH.

METHODS AND ANALYSIS

A total of 60 LDH patients and 30 healthy controls, matched by gender, age, and years of education, will be enrolled in this study. The LDH patients will be divided into two groups (Group 1, n = 30; Group 2, n = 30) using a random number table method. Group 1 will receive LPM treatment once every two days, for a total of 12 times over 4 weeks. Group 2 will receive sham LPM treatment during the same period as Group 1. All 30 healthy controls will be divided into Group 3. Multimodal MRI will be performed on Group 1 and Group 2 at three time points (TPs): before LPM (TP1), after one LPM session (TP2), and after a full course of LPM treatment. The healthy controls (Group 3) will not undergo LPM and will be subject to only a single multimodal MRI scan. Participants in both Group 1 and Group 2 will be required to complete clinical questionnaires. These assessments will focus on pain intensity and functional disorders, using the Visual Analog Scale (VAS) and the Japanese Orthopaedic Association (JOA) scoring systems, respectively.

DISCUSSION

The purpose of this study is to investigate the multimodal brain response characteristics of LDH patients after treatment with LPM, with the goal of providing a biological basis for clinical applications.

TRIAL REGISTRATION NUMBER

https://clinicaltrials.gov/ct2/show/NCT05613179 , identifier: NCT05613179.

Intracranial EEG signals disentangle multi-areal neural dynamics of vicarious pain perception

Empathy enables understanding and sharing of others' feelings. Human neuroimaging studies have identified critical brain regions supporting empathy for pain, including the anterior insula (AI), anterior cingulate (ACC), amygdala, and inferior frontal gyrus (IFG). However, to date, the precise spatio-temporal profiles of empathic neural responses and inter-regional communications remain elusive. Here, using intracranial electroencephalography, we investigated electrophysiological signatures of vicarious pain perception. Others' pain perception induced early increases in high-gamma activity in IFG, beta power increases in ACC, but decreased beta power in AI and amygdala. Vicarious pain perception also altered the beta-band-coordinated coupling between ACC, AI, and amygdala, as well as increased modulation of IFG high-gamma amplitudes by beta phases of amygdala/AI/ACC. We identified a necessary combination of neural features for decoding vicarious pain perception. These spatio-temporally specific regional activities and inter-regional interactions within the empathy network suggest a neurodynamic model of human pain empathy.

Effect of dry needling on pain and central sensitization in women with chronic pelvic pain: A randomized parallel-group controlled clinical trial

Chronic pelvic pain (CPP) is a debilitating problem in women with clear evidence of myofascial dysfunction. It seems that Myofascial trigger points (MTrPs) contribute to the development of central sensitization (CS). This study aimed to investigate the effect of dry needling on pain and CS in women with CPP. Thirty-six women with CPP participated in this randomized controlled clinical trial and randomly assigned into three groups: dry needling group (DNG), placebo needling group (PNG) and control group (CG). The DNG received five sessions of DN using the "static needling", the PNG received non-penetrating method, and the CG did not receive any intervention. Assessment of outcomes including central sensitization inventory (CSI), short-form McGill pain questionnaire (SF-MPQ), electroencephalography (EEG), conditioned pain modulation (CPM), salivary cortisol concentration, 7-item general anxiety disorder scale (GAD-7), pain catastrophizing scale (PCS), and SF-36 questionnaire was performed pre-intervention, post-intervention, and three months post-intervention by a blind examiner. The result showed a significant group-by-time interaction for CSI, SF-MPQ, and PCS. There was a significant decrease in CSI score in post-intervention and three-months post-intervention compare to pre-intervention in the DNG and PNG. SF-MPQ-PPI score in DNG significantly decreased post-intervention. PCS-Total score decreased significantly post-intervention in DNG and PNG. No significant group-by-time interactions were observed for other variables. EEG results showed regional changes in the activity of frequency bands in both eye closed and eye open conditions. It seems that DN can affect central pain processing by removing the source of peripheral nociception. Trial registration: Iranian Registry of Clinical Trials (IRCT20211114053057N1, registered on: December 03, 2021. https://irct.behdasht.gov.ir/search/result?query=IRCT20211114053057N1).

Validity of central pain processing biomarkers for predicting the occurrence of oncological chronic pain: a study protocol

BACKGROUND

Despite recent improvements in cancer detection and survival rates, managing cancer-related pain remains a significant challenge. Compared to neuropathic and inflammatory pain conditions, cancer pain mechanisms are poorly understood, despite pain being one of the most feared symptoms by cancer patients and significantly impairing their quality of life, daily activities, and social interactions. The objective of this work was to select a panel of biomarkers of central pain processing and modulation and assess their ability to predict chronic pain in patients with cancer using predictive artificial intelligence (AI) algorithms.

METHODS

We will perform a prospective longitudinal cohort, multicentric study involving 450 patients with a recent cancer diagnosis. These patients will undergo an in-person assessment at three different time points: pretreatment, 6 months, and 12 months after the first visit. All patients will be assessed through demographic and clinical questionnaires and self-report measures, quantitative sensory testing (QST), and electroencephalography (EEG) evaluations. We will select the variables that best predict the future occurrence of pain using a comprehensive approach that includes clinical, psychosocial, and neurophysiological variables.

DISCUSSION

This study aimed to provide evidence regarding the links between poor pain modulation mechanisms at precancer treatment in patients who will later develop chronic pain and to clarify the role of treatment modality (modulated by age, sex and type of cancer) on pain. As a final output, we expect to develop a predictive tool based on AI that can contribute to the anticipation of the future occurrence of pain and help in therapeutic decision making.

Altered dynamic functional connectivity in rectal cancer patients with and without chemotherapy: a resting-state fMRI study

Purpose: Understanding the mechanism of brain functional alterations in rectal cancer (RC) patients is of great significance to improve the prognosis and quality of life of patients. Additionally, the influence of chemotherapy on brain function in RC patients is still unclear. In this study, we aimed to investigate the alterations of brain functional network dynamics in RC patients and explore the effects of chemotherapy on temporal dynamics of dynamic functional connectivity (DFC).

Methods: The group independent component analysis (GICA) and sliding window method were applied to investigate abnormalities of DFC based on resting-state functional magnetic resonance imaging (rs-fMRI) of 18 RC patients without chemotherapy (RC_NC), 21 RC patients with chemotherapy (RC_C) and 33 healthy controls (HC). Then, the Spearman correlation between aberrant properties and clinical measures was calculated.

Results: Two discrete states were identified. Compared to HC, RC_NC exhibited increased mean dwell time (MDT) and fractional windows (FW) in state 2 and decreased transition numbers between the two states. Notably, three temporal properties in RC_C showed an intermediate trend in comparison with RC_NC and HC. Furthermore, RC_C also demonstrated abnormal intra- and inter-network connections, involving the visual (VIS), default mode (DM), and cognitive control (CC) networks, and most connections related to VIS were correlated with the severity of anxiety and depression.

Conclusions: Our study suggested that abnormal DFC patterns could be manifested in RC patients and chemotherapy would further correct abnormalities of network dynamics, which may provide new insights into the brain functional alterations in patients with RC from the time-varying connectivity perspective.

Temporal summation of second pain is affected by cognitive load

This work attempted to clarify the interaction of cognition and pain sensitization during a paradigm of Temporal Summation of Second Pain (TSSP). We analyzed pain ratings and electroencephalographic (EEG) activity obtained from 21 healthy participants during the presentation of four experimental conditions that differed in the manipulation of attention to painful stimuli or working memory load (Attention to hand & TSSP; 0-back & TSSP (low cognitive load); 2-back & TSSP (high cognitive load); 2-back (without pain)). We found that the TSSP was reduced when the attention was diverted and the cognitive load increased, and this reduction was accompanied by higher midfrontal theta activity and lower posterior alpha and central beta activity. Although it is well established that TSSP is a phenomenon that occurs at the spinal level, here we show that it is also affected by supraspinal attentional mechanisms. Delivery of painful repeated stimuli did not affect the performance of the 2-back task but was associated with smaller amplitudes of attentional event-related potentials (ERPs) after standard stimuli (not the target). The study of brain activity during TSSP allowed to clarify the role of top-down attentional modulation in pain sensitization processes. Results contribute to a better understanding of cognitive dysfunction in pain conditions and reinforce the use of therapeutic strategies based on distracting attention away from pain.

Can non-invasive brain stimulation modulate peak alpha frequency in the human brain? A systematic review and meta-analysis

Peak alpha frequency (PAF), the dominant oscillatory frequency within the alpha range (8-12 Hz), is associated with cognitive function and several neurological conditions, including chronic pain. Manipulating PAF could offer valuable insight into the relationship between PAF and various functions and conditions, potentially providing new treatment avenues. This systematic review aimed to comprehensively synthesise effects of non-invasive brain stimulation (NIBS) on PAF speed. Relevant studies assessing PAF pre- and post-NIBS in healthy adults were identified through systematic searches of electronic databases (Embase, PubMed, PsychINFO, Scopus, The Cochrane Library) and trial registers. The Cochrane risk-of-bias tool was employed for assessing study quality. Quantitative analysis was conducted through pairwise meta-analysis when possible; otherwise, qualitative synthesis was performed. The review protocol was registered with PROSPERO (CRD42020190512) and the Open Science Framework (https://osf.io/2yaxz/). Eleven NIBS studies were included, all with a low risk-of-bias, comprising seven transcranial alternating current stimulation (tACS), three repetitive transcranial magnetic stimulation (rTMS), and one transcranial direct current stimulation (tDCS) study. Meta-analysis of active tACS conditions (eight conditions from five studies) revealed no significant effects on PAF (mean difference [MD] = -0.12, 95% CI = -0.32 to 0.08, p = 0.24). Qualitative synthesis provided no evidence that tDCS altered PAF and moderate evidence for transient increases in PAF with 10 Hz rTMS. However, it is crucial to note that small sample sizes were used, there was substantial variation in stimulation protocols, and most studies did not specifically target PAF alteration. Further studies are needed to determine NIBS's potential for modulating PAF.

A Scoping Review of the Effect of EEG Neurofeedback on Pain Complaints in Adults with Chronic Pain

Background and Aim: Non-pharmacological treatments such as electroencephalogram (EEG) neurofeedback have become more important in multidisciplinary approaches to treat chronic pain. The aim of this scoping review is to identify the literature on the effects of EEG neurofeedback in reducing pain complaints in adult chronic-pain patients and to elaborate on the neurophysiological rationale for using specific frequency bands as targets for EEG neurofeedback. Methods: A pre-registered scoping review was set up and reported following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) extension for Scoping Reviews (PRISMA-ScR). The data were collected by searching for studies published between 1985 and January 2023 in PubMed, EMBASE, and PsycINFO. Results: Thirty-two studies on various types of chronic pain were included. The intervention was well-tolerated. Approximately half of the studies used a protocol that reinforced alpha or sensorimotor rhythms and suppressed theta or beta activity. However, the underlying neurophysiological rationale behind these specific frequency bands remains unclear. Conclusions: There are indications that neurofeedback in patients with chronic pain probably has short-term analgesic effects; however, the long-term effects are less clear. In order to draw more stable conclusions on the effectiveness of neurofeedback in chronic pain, additional research on the neurophysiological mechanisms of targeted frequency bands is definitely worthwhile. Several recommendations for setting up and evaluating the effect of neurofeedback protocols are suggested.

EEG-Based Cortical Alterations in Individuals With Chronic Knee Pain Secondary to Osteoarthritis: A Cross-sectional Investigation

Chronic painful knee osteoarthritis (OA) is a disabling physical health condition. Alterations in brain responses to arthritic changes in the knee may explain persistent pain. This study investigated source localized, resting-state electroencephalography activity and functional connectivity in people with knee OA, compared to healthy controls. Adults aged 44 to 85 years with knee OA (n = 37) and healthy control (n = 39) were recruited. Resting-state electroencephalography was collected for 10 minutes and decomposed into infraslow frequency (ISF) to gamma frequency bands. Standard low-resolution electromagnetic brain tomography statistical nonparametric maps were conducted, current densities of regions of interest were compared between groups and correlation analyses were performed between electroencephalography (EEG) measures and clinical pain and functional outcomes in the knee OA group. Standard low-resolution electromagnetic brain tomography nonparametric maps revealed higher (P = .006) gamma band activity over the right insula (RIns) in the knee OA group. A significant (P < .0001) reduction in ISF band activity at the pregenual anterior cingulate cortex, whereas higher theta, alpha, beta, and gamma band activity at the dorsal anterior cingulate cortex, pregenual anterior cingulate cortex, the somatosensory cortex, and RIns in the knee OA group were identified. ISF activity of the dorsal anterior cingulate cortex was positively correlated with pain measures and psychological distress scores. Theta and alpha activity of RIns were negatively correlated with pain interference. In conclusion, aberrations in infraslow and faster frequency EEG oscillations at sensory discriminative, motivational-affective, and descending inhibitory cortical regions were demonstrated in people with chronic painful knee OA. Moreover, EEG oscillations were correlated with pain and functional outcome measures. PERSPECTIVE: This study confirms alterations in the rsEEG oscillations and its relationship with pain experience in people with knee OA. The study provides potential cortical targets and the EEG frequency bands for neuromodulatory interventions for managing chronic pain experience in knee OA.

Evoked oscillatory cortical activity during acute pain: Probing brain in pain by transcranial magnetic stimulation combined with electroencephalogram

Temporal dynamics of local cortical rhythms during acute pain remain largely unknown. The current study used a novel approach based on transcranial magnetic stimulation combined with electroencephalogram (TMS-EEG) to investigate evoked-oscillatory cortical activity during acute pain. Motor (M1) and dorsolateral prefrontal cortex (DLPFC) were probed by TMS, respectively, to record oscillatory power (event-related spectral perturbation and relative spectral power) and phase synchronization (inter-trial coherence) by 63 EEG channels during experimentally induced acute heat pain in 24 healthy participants. TMS-EEG was recorded before, during, and after noxious heat (acute pain condition) and non-noxious warm (Control condition), delivered in a randomized sequence. The main frequency bands (α, β1, and β2) of TMS-evoked potentials after M1 and DLPFC stimulation were recorded close to the TMS coil and remotely. Cold and heat pain thresholds were measured before TMS-EEG. Over M1, acute pain decreased α-band oscillatory power locally and α-band phase synchronization remotely in parietal-occipital clusters compared with non-noxious warm (all p < .05). The remote (parietal-occipital) decrease in α-band phase synchronization during acute pain correlated with the cold (p = .001) and heat pain thresholds (p = .023) and to local (M1) α-band oscillatory power decrease (p = .024). Over DLPFC, acute pain only decreased β1-band power locally compared with non-noxious warm (p = .015). Thus, evoked-oscillatory cortical activity to M1 stimulation is reduced by acute pain in central and parietal-occipital regions and correlated with pain sensitivity, in contrast to DLPFC, which had only local effects. This finding expands the significance of α and β band oscillations and may have relevance for pain therapies.

Neuroscientific results of experimental studies on the control of acute pain with hypnosis and suggested analgesia

This narrative review summarizes a representative collection of electrophysiological and imaging studies on the neural processes and brain sources underlying hypnotic trance and the effects of hypnotic suggestions on the processing of experimentally induced painful events. It complements several reviews on the effect of hypnosis on brain processes and structures of chronic pain processing. Based on a summary of previous findings on the neuronal processing of experimentally applied pain stimuli and their effects on neuronal brain structures in healthy subjects, three neurophysiological methods are then presented that examine which of these neuronal processes and structures get demonstrably altered by hypnosis and can thus be interpreted as neuronal signatures of the effect of analgesic suggestions: (A) On a more global neuronal level, these are electrical processes of the brain that can be recorded from the cranial surface of the brain with magnetoencephalography (MEG) and electroencephalography (EEG). (B) On a second level, so-called evoked (EPs) or event-related potentials (ERPs) are discussed, which represent a subset of the brain electrical parameters of the EEG. (C) Thirdly, imaging procedures are summarized that focus on brain structures involved in the processing of pain states and belong to the main imaging procedures of magnetic resonance imaging (MRI/fMRI) and positron emission tomography (PET). Finally, these different approaches are summarized in a discussion, and some research and methodological suggestions are made as to how this research could be improved in the future.

Brain state-dependent responses of midbrain dopaminergic neurons to footshock under urethane anaesthesia

For a long time, it has been assumed that dopaminergic (DA) neurons in both the ventral tegmental area (VTA) and the substantia nigra pars compacta (SNc) uniformly respond to rewarding and aversive stimuli by either increasing or decreasing their activity, respectively. This response was believed to signal information about the perceived stimuli's values. The identification of VTA&SNc DA neurons that are excited by both rewarding and aversive stimuli has led to the categorisation of VTA&SNc DA neurons into two subpopulations: one signalling the value and the other signalling the salience of the stimuli. It has been shown that the general state of the brain can modulate the electrical activity of VTA&SNc DA neurons, but it remains unknown whether this factor may also influence responses to aversive stimuli, such as a footshock (FS). To address this question, we have recorded the responses of VTA&SNc DA neurons to FSs across cortical activation and slow wave activity brain states in urethane-anaesthetised rats. Adding to the knowledge of aversion signalling by midbrain DA neurons, we report that significant proportion of VTA&SNc DA neurons can change their responses to an aversive stimulus in a brain state-dependent manner. The majority of these neurons decreased their activity in response to FS during cortical activation but switched to increasing it during slow wave activity. It can be hypothesised that this subpopulation of DA neurons may be involved in the 'dual signalling' of both the value and the salience of the stimuli, depending on the general state of the brain.

Brain network hypersensitivity underlies pain crises in sickle cell disease

Sickle cell disease (SCD) is a genetic disorder causing painful and unpredictable Vaso-occlusive crises (VOCs) through blood vessel blockages. In this study, we propose explosive synchronization (ES) as a novel approach to comprehend the hypersensitivity and occurrence of VOCs in the SCD brain network. We hypothesized that the accumulated disruptions in the brain network induced by SCD might lead to strengthened ES and hypersensitivity. We explored ES's relationship with patient reported outcome measures (PROMs) as well as VOCs by analyzing EEG data from 25 SCD patients and 18 matched controls. SCD patients exhibited lower alpha frequency than controls. SCD patients showed correlation between frequency disassortativity (FDA), an ES condition, and three important PROMs. Furthermore, stronger FDA was observed in SCD patients with a higher frequency of VOCs and EEG recording near VOC. We also conducted computational modeling on SCD brain network to study FDA's role in network sensitivity. Our model demonstrated that a stronger FDA could be linked to increased sensitivity and frequency of VOCs. This study establishes connections between SCD pain and the universal network mechanism, ES, offering a strong theoretical foundation. This understanding will aid predicting VOCs and refining pain management for SCD patients.

Neural oscillations underlying the neural gating of respiratory sensations in generalized anxiety disorder

Individuals with generalized anxiety disorder (GAD) have been shown to have altered neural gating of respiratory sensations (NGRS) using respiratory-related evoked potentials (RREP); however, corresponding neural oscillatory activities remain unexplored. The present study aimed to investigate altered NGRS in individuals with GAD using both time and time-frequency analysis. Nineteen individuals with GAD and 28 healthy controls were recruited. Paired inspiratory occlusions were delivered to elicit cortical neural activations measured from electroencephalography. The GAD group showed smaller N1 amplitudes to the first stimulus (S1), lower evoked gamma and larger evoked beta oscillations compared to controls. Both groups showed larger N1, P3, beta power and theta power in response to S1 compared to S2, suggesting a neural gating phenomenon. These findings suggest that N1, gamma and beta frequency oscillations may be indicators for altered respiratory sensation in GAD populations and that the N1, P3, beta and theta oscillations can reflect the neural gating of respiratory sensations.

From pain to tumor immunity: influence of peripheral sensory neurons in cancer

The nervous and immune systems are the primary sensory interfaces of the body, allowing it to recognize, process, and respond to various stimuli from both the external and internal environment. These systems work in concert through various mechanisms of neuro-immune crosstalk to detect threats, provide defense against pathogens, and maintain or restore homeostasis, but can also contribute to the development of diseases. Among peripheral sensory neurons (PSNs), nociceptive PSNs are of particular interest. They possess a remarkable capability to detect noxious stimuli in the periphery and transmit this information to the brain, resulting in the perception of pain and the activation of adaptive responses. Pain is an early symptom of cancer, often leading to its diagnosis, but it is also a major source of distress for patients as the disease progresses. In this review, we aim to provide an overview of the mechanisms within tumors that are likely to induce cancer pain, exploring a range of factors from etiological elements to cellular and molecular mediators. In addition to transmitting sensory information to the central nervous system, PSNs are also capable, when activated, to produce and release neuropeptides (e.g., CGRP and SP) from their peripheral terminals. These neuropeptides have been shown to modulate immunity in cases of inflammation, infection, and cancer. PSNs, often found within solid tumors, are likely to play a significant role in the tumor microenvironment, potentially influencing both tumor growth and anti-tumor immune responses. In this review, we discuss the current state of knowledge about the degree of sensory innervation in tumors. We also seek to understand whether and how PSNs may influence the tumor growth and associated anti-tumor immunity in different mouse models of cancer. Finally, we discuss the extent to which the tumor is able to influence the development and functions of the PSNs that innervate it.

Does brain entrainment using binaural auditory beats affect pain perception in acute and chronic pain?: a systematic review

BACKGROUND

Pain is a major clinical problem across all ages with serious social and economic consequences and a great negative impact on quality of life. Brain entrainment using binaural beats is a non-pharmaceutical intervention that is claimed to have analgesic effects in acute and chronic pain. We aimed to systematically review the available randomized clinical trials on the efficacy of binaural auditory beats in reducing adults' pain perception in acute and chronic pain. A systematic search in electronic databases including Medline (via PubMed), Web of Science, Scopus, Cochrane Central Register of Controlled Trials (CENTRAL), and Embase was performed. The search was completed through Google Scholar and a manual search of the reference lists of all included studies. Randomized clinical trials with full text available in English that investigated the effect of binaural auditory beats on pain perception in acute and chronic pain in adults were included. The risk of bias was assessed by the revised Cochrane risk-of-bias (RoB 2) tool. Furthermore, The GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach was used to assess the quality of the evidence. Sixteen studies (three on chronic pain and thirteen on acute pain perception) fulfilled the eligibility criteria. Because of substantial heterogeneity of the studies, a meta-analysis was inappropriate and this review focused on the narrative interpretation of the results. The risk of bias in most studies was high and the quality of evidence was low to very low. Although the effects of binaural beats on pain perception seem to be influenced by the etiology of pain or medical procedures, our review identifies alpha or a combination of tones in the range of delta to alpha as a potential non-pharmacological intervention in reducing acute pain. However, drawing a conclusion regarding the efficacy of binaural beats for chronic pain requires more high-quality studies.

REGISTRATION

The protocol of this review was registered in PROSPERO (No. CRD42023425091).

Sleep disturbance correlated with severity of neuropathic pain in sciatic nerve crush injury model

The association between sleep and pain has been investigated widely. However, inconsistent results from animal studies compared with human data show the need for a validated animal model in the sleep-pain association field. Our study aims to validate common neuropathic pain models as a tool for evaluating the sleep-pain association. Electrodes electroencephalogram (EEG) and electromyogram (EMG) were surgically implanted to measure sleep. The von Frey test was used to measure pain sensitivity. Following the baseline data acquisition, two pain-modelling procedures were performed: sciatic nerve crush injury (SCI) and common peroneal nerve ligation (CPL). Post-injury measurements were performed on days 1, 5, 10, and 15 post-surgery. The results presented decreased paw withdrawal thresholds and reduced NREM sleep duration in both models on the first post-surgery day. In the SCI model, NREM sleep duration was negatively correlated with paw withdrawal thresholds (p = 0.0466), but not in the CPL model. Wake alpha and theta EEG powers were also correlated with the pain threshold. The results confirm that the SCI model shows disturbed sleep patterns associated with increased pain sensitivity, suggesting it is a reliable tool for investigating sleep disturbances associated with neuropathic pain.

Exploring altered oscillatory activity in the anterior cingulate cortex after nerve injury: Insights into mechanisms of neuropathic allodynia

While neural oscillations play a critical role in sensory perception, it remains unclear how these rhythms function under conditions of neuropathic allodynia. Recent studies demonstrated that the anterior cingulate cortex (ACC) is associated with the affective-aversive component of pain, and plasticity changes in this region are closely linked to abnormal allodynic sensations. Here, to study the mechanisms of allodynia, we recorded local field potentials (LFPs) in the bilateral ACC of awake-behaving rats and compared the spectral power and center frequency of brain oscillations between healthy and CCI (chronic constriction injury) induced neuropathic pain conditions. Our results indicated that activation of the ACC occurs bilaterally in the presence of neuropathic pain, similar to the healthy condition. Furthermore, CCI affects both spontaneous and stimulus-induced activity of ACC neurons. Specifically, we observed an increase in spontaneous beta activity after nerve injury compared to the healthy condition. By stimulating operated or unoperated paws, we found more intense event-related desynchronization (ERD) responses in the theta, alpha, and beta frequency bands and faster alpha center frequency after CCI compared to before CCI. Although the behavioral manifestation of allodynia was more pronounced in the operated paw than the unoperated paw following CCI, there was no significant difference in the center frequency and ERD responses observed in the ACC between stimulation of the operated and unoperated limbs. Our findings offer evidence supporting the notion that aberrancies in ACC oscillations may contribute to the maintenance and development of neuropathic allodynia.

Multilevel Laser-Induced Pain Measurement with Wasserstein Generative Adversarial Network - Gradient Penalty Model

Pain is an experience of unpleasant sensations and emotions associated with actual or potential tissue damage. In the global context, billions of people are affected by pain disorders. There are particular challenges in the measurement and assessment of pain, and the commonly used pain measuring tools include traditional subjective scoring methods and biomarker-based measures. The main tools for biomarker-based analysis are electroencephalography (EEG), electrocardiography and functional magnetic resonance. The EEG-based quantitative pain measurements are of immense value in clinical pain management and can provide objective assessments of pain intensity. The assessment of pain is now primarily limited to the identification of the presence or absence of pain, with less research on multilevel pain. High power laser stimulation pain experimental paradigm and five pain level classification methods based on EEG data augmentation are presented. First, the EEG features are extracted using modified S-transform, and the time-frequency information of the features is retained. Based on the pain recognition effect, the 20-40[Formula: see text]Hz frequency band features are optimized. Afterwards the Wasserstein generative adversarial network with gradient penalty is used for feature data augmentation. It can be inferred from the good classification performance of features in the parietal region of the brain that the sensory function of the parietal lobe region is effectively activated during the occurrence of pain. By comparing the latest data augmentation methods and classification algorithms, the proposed method has significant advantages for the five-level pain dataset. This research provides new ways of thinking and research methods related to pain recognition, which is essential for the study of neural mechanisms and regulatory mechanisms of pain.

The temporal effect of uncertain context on the perceptual processing of painful and non-painful stimulation

Uncertainty has been demonstrated to influence the perception of noxious stimuli, but little is known about the effects of prolonged uncertain contexts on the perception of painful and non-painful stimuli. To address this knowledge gap, the present study utilized a cue-based NPU-threat task, where uncertain and certain trials were separated into distinct blocks. The objective was to investigate the impact of uncertain contexts on the temporal dynamics of electroencephalogram (EEG) activity during the processing of painful and non-painful stimuli. The results revealed that the influence of uncertain contexts on neural responses extends beyond painful trials and is also evident in non-painful trials. In uncertain contexts, it has been observed that painful stimuli elicit larger P2 amplitudes and late beta band (13-30 Hz) event-related desynchronization (ERD) around 500-700 ms. However, in certain contexts, painful stimuli evoke stronger late gamma band (50-70 Hz) event-related synchronization (ERS) around 600-700 ms. For non-painful trials, in uncertain contexts, significantly higher amplitudes of the late positive potential (LPP) component and delta-theta band (2-7 Hz) ERS were observed compared to certain non-painful stimuli. These findings demonstrate that uncertain contexts exert a significant impact on the processing of both painful and non-painful stimuli, and this influence is mediated by distinct neural mechanisms.

Is There a Difference in EEG Characteristics in Acute, Chronic, and Experimentally Induced Musculoskeletal Pain States? a Systematic Review

Electroencephalographic (EEG) alterations have been demonstrated in acute, chronic, and experimentally induced musculoskeletal (MSK) pain conditions. However, there is no cumulative evidence on the associated EEG characteristics differentiating acute, chronic, and experimentally induced musculoskeletal pain states, especially compared to healthy controls. The present systematic review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines (PRISMA) to review and summarize available evidence for cortical brain activity and connectivity alterations in acute, chronic, and experimentally induced MSK pain states. Five electronic databases were systematically searched from their inception to 2022. A total of 3471 articles were screened, and 26 full articles (five studies on chronic pain and 21 studies on experimentally induced pain) were included for the final synthesis. Using the Downs and Black risk of assessment tool, 92% of the studies were assessed as low to moderate quality. The review identified a 'very low' level of evidence for the changes in EEG and subjective outcome measures for both chronic and experimentally induced MSK pain based on the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. Overall, the findings of this review indicate a trend toward decreased alpha and beta EEG power in evoked chronic clinical pain conditions and increased theta and alpha power in resting-state EEG recorded from chronic MSK pain conditions. EEG characteristics are unclear under experimentally induced pain conditions.

Effectiveness of transcranial alternating current stimulation for controlling chronic pain: a systematic review

Background

Chronic pain is common, disruptive, and often treatment-resistant. Hence, researchers and clinicians seek alternative therapies for chronic pain. Transcranial alternating current stimulation (tACS) is an emerging neuromodulation technique that non-invasively modulates neural oscillations in the human brain. tACS induces pain relief by allowing the neural network to restore adequate synchronization. We reviewed studies on the effectiveness of tACS in controlling chronic pain.

Methods

The PubMed, SCOPUS, Embase, and Cochrane Library databases were systematically searched for relevant studies published until December 6, 2023. The key search phrase for identifying potentially relevant articles was [(Transcranial Alternating Current Stimulation OR tACS) AND pain]. The following inclusion criteria were applied for article selection: (1) studies involving patients with chronic pain; (2) tACS was applied for controlling pain; and (3) follow-up evaluations were performed to assess the degree of pain reduction after the application of tACS.

Results

We identified 2,330 potentially relevant articles. After reading the titles and abstracts and assessing eligibility based on the full-text articles, we included four articles in our review. Among the included studies, tACS was used for fibromyalgia in one study, low back pain (LBP) in two studies, and migraine in one study. In the study on fibromyalgia, it did not show a better pain-reducing effect of tACS compared with sham stimulation. Two studies on LBP showed conflicting results. In migraine, tACS showed a positive pain-reducing effect 24-48 h after its application.

Conclusion

There is insufficient research to draw a conclusive judgment on the effectiveness of tACS in controlling chronic pain. More studies across various chronic pain-related diseases are required for a definitive conclusion.

Decreased bladder contraction interval induced by periaqueductal grey stimulation is reversed by subthalamic stimulation in a Parkinson's disease model rat

The medial prefrontal cortex (mPFC) regulates bladder contractions via the periaqueductal grey (PAG). Subthalamic nucleus deep brain stimulation (STN-DBS) modulates urinary afferent information from PAG in Parkinson's disease (PD). We do not know how STN-DBS modulates the activities of mPFC induced by PAG stimulation. We aim to clarify how STN-DBS modulates the neuronal activity of mPFC induced by PAG stimulation and its effects on bladder contraction Experiments were conducted under urethane anesthesia in normal (n = 9) and 6-hydroxydopamine hemi-lesioned PD rats (n = 7). Left-sided PAG stimulation and STN-DBS were applied with simultaneous bladder contraction monitoring. Local field potential (LFP) recording and collection of extracellular fluid in the mPFC were performed before stimulation, during PAG stimulation, during PAG+STN stimulation, and after stimulation. The bladder inter-contraction intervals significantly decreased with PAG stimulation with a concomitant decrease in mPFC LFP power in PD rats. Adding STN stimulation to PAG stimulation significantly increased the bladder inter-contraction intervals with a concomitant increase in mPFC LFP power in PD rats. Several mPFC catecholamine levels were modulated by PAG or PAG+STN stimulation in PD rats. The present study revealed that STN-DBS modulate the activities of mPFC induced by PAG, thereby leading to normalization of bladder contraction.

The role of ongoing oscillation in pain perception: Absence of modulation by a concomitant arithmetic task

Sustained nociceptive stimuli have been shown to modulate the amplitude of ongoing neural oscillations in the theta, alpha and beta frequency bands at the frequency of stimulation, suggesting a relationship between these ongoing oscillations and pain perception. Yet, whether these ongoing oscillations are actually related to the pain experience remains unclear. If it were the case, then cognitive processes that are known to affect pain intensity should also affect these ongoing oscillations. To this end, we used electroencephalography (EEG) to investigate whether distraction - an attentional state known to affect pain perception - also modulates the amplitude of these neural oscillations. More specifically, we hypothesized that performing an unrelated arithmetic task during sustained nociceptive stimulation would lead to a decrease in the modulations of ongoing oscillations exerted by the stimulation. To assess the selectivity of this modulation for nociception, we compared the modulations of ongoing oscillations exerted by sustained periodic thermonociceptive and non-nociceptive vibrotactile stimulation (.2 Hz, 75 sec), while participants were either asked to solve an unrelated arithmetic task (distraction task) or received no specific instruction (baseline). The intensity of perception was significantly reduced by the arithmetic task in both the thermonociceptive and the vibrotactile modality, and the sustained periodic stimulation elicited a periodic response at the frequency of stimulation in both modalities. However, the distraction task did not show a differential effect for the two stimulation modalities in any of the frequency bands. The fact that, unlike pain perception, these oscillations did not appear to be affected by the task suggests that they are dissociable from pain perception. Whether a different task (leading to a stronger degree of distraction) could lead to different results is unclear.

Characteristic oscillatory brain networks for predicting patients with chronic migraine

To determine specific resting-state network patterns underlying alterations in chronic migraine, we employed oscillatory connectivity and machine learning techniques to distinguish patients with chronic migraine from healthy controls and patients with other pain disorders. This cross-sectional study included 350 participants (70 healthy controls, 100 patients with chronic migraine, 40 patients with chronic migraine with comorbid fibromyalgia, 35 patients with fibromyalgia, 30 patients with chronic tension-type headache, and 75 patients with episodic migraine). We collected resting-state magnetoencephalographic data for analysis. Source-based oscillatory connectivity within each network, including the pain-related network, default mode network, sensorimotor network, visual network, and insula to default mode network, was examined to determine intrinsic connectivity across a frequency range of 1-40 Hz. Features were extracted to establish and validate classification models constructed using machine learning algorithms. The findings indicated that oscillatory connectivity revealed brain network abnormalities in patients with chronic migraine compared with healthy controls, and that oscillatory connectivity exhibited distinct patterns between various pain disorders. After the incorporation of network features, the best classification model demonstrated excellent performance in distinguishing patients with chronic migraine from healthy controls, achieving high accuracy on both training and testing datasets (accuracy > 92.6% and area under the curve > 0.93). Moreover, in validation tests, classification models exhibited high accuracy in discriminating patients with chronic migraine from all other groups of patients (accuracy > 75.7% and area under the curve > 0.8). In conclusion, oscillatory synchrony within the pain-related network and default mode network corresponded to altered neurophysiological processes in patients with chronic migraine. Thus, these networks can serve as pivotal signatures in the model for identifying patients with chronic migraine, providing reliable and generalisable results. This approach may facilitate the objective and individualised diagnosis of migraine.

Effects of social presence on behavioral, neural, and physiological aspects of empathy for pain

In mediated interactions (e.g. video calls), less information is available about the other. To investigate how this affects our empathy for one another, we conducted an electroencephalogram study, in which 30 human participants observed 1 of 5 targets undergoing painful electric stimulation, once in a direct interaction and once in a live, video-mediated interaction. We found that observers were as accurate in judging others' pain and showed as much affective empathy via video as in a direct encounter. While mu suppression, a common neural marker of empathy, was not sensitive to others' pain, theta responses to others' pain as well as skin conductance coupling between participants were reduced in the video-mediated condition. We conclude that physical proximity with its rich social cues is important for nuanced physiological resonance with the other's experience. More studies are warranted to confirm these results and to understand their behavioral significance for remote social interactions.

Breathing in waves: Understanding respiratory-brain coupling as a gradient of predictive oscillations

Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.

From pulse width modulated TENS to cortical modulation: based on EEG functional connectivity analysis

Modulation in the temporal pattern of transcutaneous electrical nerve stimulation (TENS), such as Pulse width modulated (PWM), has been considered a new dimension in pain and neurorehabilitation therapy. Recently, the potentials of PWM TENS have been studied on sensory profiles and corticospinal activity. However, the underlying mechanism of PWM TENS on cortical network which might lead to pain alleviation is not yet investigated. Therefore, we recorded cortical activity using electroencephalography (EEG) from 12 healthy subjects and assessed the alternation of the functional connectivity at the cortex level up to an hour following the PWM TENS and compared that with the effect of conventional TENS. The connectivity between eight brain regions involved in sensory and pain processing was calculated based on phase lag index and spearman correlation. The alteration in segregation and integration of information in the network were investigated using graph theory. The proposed analysis discovered several statistically significant network changes between PWM TENS and conventional TENS, such as increased local strength and efficiency of the network in high gamma-band in primary and secondary somatosensory sources one hour following stimulation. Our findings regarding the long-lasting desired effects of PWM TENS support its potential as a therapeutic intervention in clinical research.

BurstDR spinal cord stimulation rebalances pain input and pain suppression in the brain in chronic neuropathic pain

OBJECTIVE

Chronic pain is processed by at least three well-known pathways, two pain provoking pathways including a medial 'suffering' and lateral 'painfulness' pathway. A third descending pain pathway modulates pain but is predominantly inhibitory. Chronic pain can be seen as an imbalance between the two pain-provoking and the pain inhibitory pathways. If this assumption is correct, then the imbalance between pain input and pain suppression should reverse and normalize in response to successful, i.e., pain reducing burstDR spinal cord stimulation, one of the current treatment options for neuropathic pain.

MATERIALS AND METHODS

Fifteen patients, who received spinal cord stimulation for failed back surgery were included in this study, using source localized electrical brain activity and connectivity recording via EEG to identify the purported imbalance.

RESULTS

BurstDR spinal cord stimulation induces a significant change in EEG activity in both the left and right somatosensory cortex (SSC) for both θ and γ oscillations. In the dorsal anterior cingulate cortex (dACC), we observed a significant drop in both α and β oscillations. This reduction is accompanied by a change in pain intensity and suffering. BurstDR spinal cord stimulation is also associated with a reduction in θ at the pregenual anterior cingulate cortex (pgACC). Analyzing effective connectivity indicates that for the θ band, more information is sent from the pgACC to the left and right SSC. For α, increased information is sent from the pgACC to the dACC and both the left and right SSC. This is associated with a reduced θ-γ coupling in the SSC and reduced α-β coupling in dACC.

CONCLUSION

This study suggests that chronic pain is indeed an imbalance between the ascending and descending pathways in the brain and that burst spinal cord stimulation can normalize this imbalance in the brain.

Validation of Cross-Individual Pain Assessment with Individual Recognition Model from Electroencephalogram

Cross-individual pain assessment models based on electroencephalography (EEG) allow pain assessment in individuals who cannot report pain (e.g., unresponsive patients). The main obstacle to the generalisation of pain assessment models is the individual variation of brain responses to pain. Hence, we took the individual variation into account in cross-individual model development. We developed two convolutional neural networks (CNN) sharing an encoder architecture. One CNN predicts pain, while the other predicts the identity of an individual. We performed a leave-one-out (LOO) test with the exclusion of each subject and applied evidence accumulation to it for validating the pain prediction model's performance, where the binary classifier involves the states of pain (Hot) and resting state (Eyes-open). The mean accuracy produced by the LOO tests was 57.81% (max: 73.33%), and the mean accuracy of evidence accumulation achieved 69.75% (max: 100.00%). The individual recognition model achieved an accuracy of 99.63%. Nevertheless, when we acquired the most similar subject to a novel subject using the individual recognition model, where the most similar subject was used to train a subject-wise pain prediction model. The accuracy of predicting the pain-related conditions of the novel subject by the subject-wise model was only 53.73% (max: 79.50%). Therefore, the approach to utilising the features related to individual variation extracted by the CNN model needs more investigation for improving cross-individual pain assessment.Clinical relevance- This model can be applied to assess pain from EEG signals at the bedside with future improvement, which can help caretakers of unresponsive patients.

Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts. The purpose of this article is to discuss the state of the art of research and perspectives on APA applications in both research and clinical scenarios. Principles of AI functioning will be addressed. For narrative purposes, AI-based methods are grouped into behavioral-based approaches and neurophysiology-based pain detection methods. Since pain is generally accompanied by spontaneous facial behaviors, several approaches for APA are based on image classification and feature extraction. Language features through natural language strategies, body postures, and respiratory-derived elements are other investigated behavioral-based approaches. Neurophysiology-based pain detection is obtained through electroencephalography, electromyography, electrodermal activity, and other biosignals. Recent approaches involve multimode strategies by combining behaviors with neurophysiological findings. Concerning methods, early studies were conducted by machine learning algorithms such as support vector machine, decision tree, and random forest classifiers. More recently, artificial neural networks such as convolutional and recurrent neural network algorithms are implemented, even in combination. Collaboration programs involving clinicians and computer scientists must be aimed at structuring and processing robust datasets that can be used in various settings, from acute to different chronic pain conditions. Finally, it is crucial to apply the concepts of explainability and ethics when examining AI applications for pain research and management.

In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand?

Machine learning is becoming an increasingly common component of routine data analyses in clinical research. The past decade in pain research has witnessed great advances in human neuroimaging and machine learning. With each finding, the pain research community takes one step closer to uncovering fundamental mechanisms underlying chronic pain and at the same time proposing neurophysiological biomarkers. However, it remains challenging to fully understand chronic pain due to its multidimensional representations within the brain. By utilizing cost-effective and non-invasive imaging techniques such as electroencephalography (EEG) and analyzing the resulting data with advanced analytic methods, we have the opportunity to better understand and identify specific neural mechanisms associated with the processing and perception of chronic pain. This narrative literature review summarizes studies from the last decade describing the utility of EEG as a potential biomarker for chronic pain by synergizing clinical and computational perspectives.

First-in-human prediction of chronic pain state using intracranial neural biomarkers

Chronic pain syndromes are often refractory to treatment and cause substantial suffering and disability. Pain severity is often measured through subjective report, while objective biomarkers that may guide diagnosis and treatment are lacking. Also, which brain activity underlies chronic pain on clinically relevant timescales, or how this relates to acute pain, remains unclear. Here four individuals with refractory neuropathic pain were implanted with chronic intracranial electrodes in the anterior cingulate cortex and orbitofrontal cortex (OFC). Participants reported pain metrics coincident with ambulatory, direct neural recordings obtained multiple times daily over months. We successfully predicted intraindividual chronic pain severity scores from neural activity with high sensitivity using machine learning methods. Chronic pain decoding relied on sustained power changes from the OFC, which tended to differ from transient patterns of activity associated with acute, evoked pain states during a task. Thus, intracranial OFC signals can be used to predict spontaneous, chronic pain state in patients.

Resting-state electroencephalography and magnetoencephalography as biomarkers of chronic pain: a systematic review

ABSTRACT

Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy to use, and cost efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. Therefore, we conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting-state EEG and magnetoencephalography (MEG) studies in adult patients with different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semiquantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and EMBASE. For cross-sectional studies that can serve to develop diagnostic biomarkers, we found higher theta and beta power in patients with chronic pain than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Similarly, descriptive studies that can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, this systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might help to guide future M/EEG studies on the development of pain biomarkers.

Non-invasive neuromodulation of sub-regions of the human insula differentially affect pain processing and heart-rate variability

The insula is a portion of the cerebral cortex folded deep within the lateral sulcus covered by the overlying opercula of the inferior frontal lobe and superior portion of the temporal lobe. The insula has been parsed into sub-regions based upon cytoarchitectonics and structural and functional connectivity with multiple lines of evidence supporting specific roles for each of these sub-regions in pain processing and interoception. In the past, causal interrogation of the insula was only possible in patients with surgically implanted electrodes. Here, we leverage the high spatial resolution combined with the deep penetration depth of low-intensity focused ultrasound (LIFU) to non-surgically modulate either the anterior insula (AI) or posterior insula (PI) in humans for effect on subjective pain ratings, electroencephalographic (EEG) contact head evoked potentials (CHEPs) and time-frequency power as well as autonomic measures including heart-rate variability (HRV) and electrodermal response (EDR). N = 23 healthy volunteers received brief noxious heat pain stimuli to the dorsum of their right hand during continuous heart-rate, EDR and EEG recording. LIFU was delivered to either the AI (anterior short gyrus), PI (posterior longus gyrus) or under an inert sham condition time-locked to the heat stimulus. Results demonstrate that single-element 500 kHz LIFU is capable of individually targeting specific gyri of the insula. LIFU to both AI and PI similarly reduced perceived pain ratings but had differential effects on EEG activity. LIFU to PI affected earlier EEG amplitudes around 300 milliseconds whereas LIFU to AI affected EEG amplitudes around 500 milliseconds. In addition, only LIFU to the AI affected HRV as indexed by an increase in standard deviation of N-N intervals (SDNN) and mean HRV low frequency power. There was no effect of LIFU to either AI or PI on EDR or blood pressure. Taken together, LIFU looks to be an effective method to individually target sub-regions of the insula in humans for site-specific effects on brain biomarkers of pain processing and autonomic reactivity that translates to reduced perceived pain to a transient heat stimulus. These data have implications for the treatment of chronic pain and several neuropsychological diseases like anxiety, depression and addiction that all demonstrate abnormal activity in the insula concomitant with dysregulated autonomic function.

Interhemispheric neural characteristics of noxious mechano-nociceptive stimulation in the anterior cingulate cortex

Background

Pain is an unpleasant sensory and emotional experience. One of the most critical regions of the brain for pain processing is the anterior cingulate cortex (ACC). Several studies have examined the role of this region in thermal nociceptive pain. However, studies on mechanical nociceptive pain have been very limited to date. Although several studies have investigated pain, the interactions between the two hemispheres are still not clear. This study aimed to investigate nociceptive mechanical pain in the ACC bilaterally.

Methods

Local field potential (LFP) signals were recorded from seven male Wistar rats' ACC regions of both hemispheres. Mechanical stimulations with two intensities, high-intensity noxious (HN) and non-noxious (NN) were applied to the left hind paw. At the same time, the LFP signals were recorded bilaterally from awake and freely moving rats. The recorded signals were analyzed from different perspectives, including spectral analysis, intensity classification, evoked potential (EP) analysis, and synchrony and similarity of two hemispheres.

Results

By using spectro-temporal features and support vector machine (SVM) classifier, HN vs. no-stimulation (NS), NN vs. NS, and HN vs. NN were classified with accuracies of 89.6, 71.1, and 84.7%, respectively. Analyses of the signals from the two hemispheres showed that the EPs in the two hemispheres were very similar and occurred simultaneously; however, the correlation and phase locking value (PLV) between the two hemispheres changed significantly after HN stimulation. These variations persisted for up to 4 s after the stimulation. In contrast, variations in the PLV and correlation for NN stimulation were not significant.

Conclusions

This study showed that the ACC area was able to distinguish the intensity of mechanical stimulation based on the power activities of neural responses. In addition, our results suggest that the ACC region is activated bilaterally due to nociceptive mechanical pain. Additionally, stimulations above the pain threshold (HN) significantly affect the synchronicity and correlation between the two hemispheres compared to non-noxious stimuli.

Local brain oscillations and interregional connectivity differentially serve sensory and expectation effects on pain

Pain emerges from the integration of sensory information about threats and contextual information such as an individual's expectations. However, how sensory and contextual effects on pain are served by the brain is not fully understood so far. To address this question, we applied brief painful stimuli to 40 healthy human participants and independently varied stimulus intensity and expectations. Concurrently, we recorded electroencephalography. We assessed local oscillatory brain activity and interregional functional connectivity in a network of six brain regions playing key roles in the processing of pain. We found that sensory information predominantly influenced local brain oscillations. In contrast, expectations exclusively influenced interregional connectivity. Specifically, expectations altered connectivity at alpha (8 to 12 hertz) frequencies from prefrontal to somatosensory cortex. Moreover, discrepancies between sensory information and expectations, i.e., prediction errors, influenced connectivity at gamma (60 to 100 hertz) frequencies. These findings reveal how fundamentally different brain mechanisms serve sensory and contextual effects on pain.

Cerebral cortical hemodynamic metrics to aid in assessing pain levels? A pilot study of functional near-infrared spectroscopy

Introduction

Establishing an accurate way to quantify pain is one of the most formidable tasks in neuroscience and medical practice. Functional near-infrared spectroscopy (fNIRS) can be utilized to detect the brain’s reaction to pain. The study sought to assess the neural mechanisms of the wrist-ankle acupuncture transcutaneous electrical nerve stimulation analgesic bracelet (E-WAA) in providing pain relief and altering cerebral blood volume dynamics, and to ascertain the reliability of cortical activation patterns as a means of objectively measuring pain.

Methods

The participants (mean age 36.6 ± 7.2 years) with the cervical-shoulder syndrome (CSS) underwent pain testing prior to, 1 min following, and 30 min after the left point Jianyu treatment. The E-WAA was used to administer an electrical stimulation therapy that lasted for 5 min. A 24-channel fNIRS system was utilized to monitor brain oxyhemoglobin (HbO) levels, and changes in HbO concentrations, cortical activation areas, and subjective pain assessment scales were documented.

Results

We discovered that HbO concentrations in the prefrontal cortex significantly increased when CSS patients were exposed to painful stimuli at the cerebral cortex level. The second pain test saw a considerable decrease in the average HbO change amount in the prefrontal cortex when E-WAA was applied, which in turn led to a reduction in the amount of activation and the size of the activated area in the cortex.

Discussion

This study revealed that the frontal polar (FP) and dorsolateral prefrontal cortex (DLPFC) were linked to the analgesic modulation activated by the E-WAA.

Gamma-band oscillations of pain and nociception: A systematic review and meta-analysis of human and rodent studies

Pain-induced gamma-band oscillations (GBOs) are one of the most promising biomarkers of the pain experience. Although GBOs reliably encode pain perception across different individuals and species, considerable heterogeneity could be observed in the characteristics and functions of GBOs. However, such heterogeneity of GBOs and its underlying sources have rarely been detailed previously. Here, we conducted a systematic review and meta-analysis to characterize the temporal, frequential, and spatial characteristics of GBOs and summarize the functional significance of distinct GBOs. We found that GBO heterogeneity was mainly related to pain types, with a higher frequency (∼66 Hz) GBOs at the sensorimotor cortex elicited by phasic pain and a lower frequency (∼55 Hz) GBOs at the prefrontal cortex associated with tonic and chronic pains. Positive correlations between GBO magnitudes and pain intensity were observed in healthy participants. Notably, the characteristics and functions of GBOs seemed to be phylogenetically conserved across humans and rodents. Altogether, we provided a comprehensive description of heterogeneous GBOs in pain and nociception, laying the foundation for clinical applications of GBOs.

EEG frequency band analysis in chronic neuropathic pain: A linear and nonlinear approach to classify pain severity

BACKGROUND AND OBJECTIVE

Chronic neuropathic pain (NP) is a chronic pain condition that severely impacts a patient's life. Pain management has proved to be inefficient due to a lack of a simple clinical tool that may identify and monitor NP. A low-cost, noninvasive tool that provides relevant information on NP is the electroencephalogram (EEG). However, the commonly used linear EEG features have proved to be limited in characterizing NP pathophysiology. This study sought to determine whether nonlinear EEG features such as approximate entropy (ApEn) would better differentiate pain severity than absolute band power.

METHODS

A non-parametric statistical approach based on the Brief Pain Inventory (BPI), along with linear and nonlinear EEG features, is proposed in this study. For this purpose, thirty-six chronic NP patients were recruited, and 22 channels were registered. Additionally, a control database of 13 participants with no NP was used as a reference, where 19 channels were registered. For both groups, EEG was recorded for 10 min in a resting state: 5 min with eyes open (EO) and 5 min with eyes closed (EC). Absolute band power and ApEn EEG features in the five clinical frequency bands (delta, theta, alpha, beta, and gamma) were estimated for all channels in both groups. As a result, 220-dimensional and 190-dimensional feature vectors were obtained for experimental and control classes respectively. For the experimental class, NP patients were grouped according to their BPI evaluation in three groups: low, moderate, and high pain. Finally, feature vectors were compared between groups using Kruskal Wallis and post-hoc Dunn's tests.

RESULTS

ApEn revealed significant statistical difference (p <=0.0001) in most frequency bands and conditions among the groups. In contrast, power had less significant differences between groups, particularly with EO. Furthermore, NP groups were notably clustered using only ApEn in theta, alpha, and beta bands.

CONCLUSIONS

The results indicate that ApEn effectively characterizes the different severities of chronic NP rather than the commonly used linear features. ApEn and other nonlinear techniques (e.g., spectral entropy, Shannon entropy) might be a more suitable methodology to monitor chronic NP experience.

Brain Wave Patterns in Patients With Chronic Low Back Pain: A Case-control Study

Introduction

Research evidence indicates that maladaptive reorganization of the brain plays a critical role in amplifying pain experiences and pain chronification; however, no clear evidence of change exists in brain wave activity among patients with chronic low back pain (CLBP). The objective of this study was to assess brain wave activity in patients with CLBP, compared to healthy controls.

Methods

Twenty-five patients with CLBP and twenty-four healthy controls participated in the study. A quantitative electroencephalography device was used to assess brain wave activity in eyes-open and eyes-closed (EO and EC) conditions. The regional absolute and relative power of brain waves were compared between the groups.

Results

Our results showed a significant increase in the absolute power of theta (F=5.905, P=0.019), alpha (F=5.404, P=0.024) waves in patients with CLBP compared to healthy subjects in both EC and EO conditions. Patients with CLBP showed a reduced delta absolute power in the frontal region (F=5.852, P=0.019) and augmented delta absolute power in the central region (F=5.597, P=0.022) in the EO condition. An increased delta absolute power was observed in the frontal (F=7.563 P=0.008), central (F=10.430, P=0.002), and parietal (F=4.596, P=0.037) regions in patients with CLBP compared to the healthy subjects in the EC condition. In the EC condition, significant increases in theta relative power (F=4.680, P=0.036) in the parietal region were also found in patients with CLBP.

Conclusion

The increased absolute power of brain waves in people with CLBP may indicate cortical overactivity and changes in the pain processing mechanisms in these patients.

Highlights

Chronic low back pain (CLBP) increases the alpha, theta, and delta power in the brain.CLBP is associated with increased brain wave activity in the frontal, central, and parietal regions.Our findings suggest altered central pain processing in CLBP.

Plain Language Summary

Traditional diagnosis and treatment of CLBP are mainly focused on peripheral pathology. But, the modern neuroscience approach to pain highlights the role of cortical plasticity in chronic musculoskeletal pain. In this regard, several studies found structural and functional changes in the brain in patients with chronic pain. Detailed knowledge about cortical changes in CLBP can improve our understanding of mechanisms involved in CLBP, opening a new window to better treatment of LBP (Low back pain). This study investigated brain wave activity in patients with CLBP compared to healthy individuals. Our findings suggest increased brain activity in various parts of the brain in patients with chronic LBP. This finding indicates that CLBP treatment should focus on both peripheral and cortical factors rather than local tissue damage.

Fusion of pain avoidance and the contingent negative variation induced by punitive condition predict suicide ideation in a college population

This study examined behavioral and ERP features involved in pain processing as predictors of suicide ideation. Twenty-seven depressed undergraduates with high suicide ideation (HSI), 23 depressed undergraduates with low suicide ideation (LSI), and 32 healthy controls (HCs) completed the clinical Scales. The amplitudes of LPP, P2, P3, CNV, FRN, power in the beta, theta, and delta bands in the SAID task were multimodal EEG features. A machine learning algorithm known as support vector machine was used to select optimal feature sets for predicting pain avoidance, depression, and suicide ideation. The accuracy of suicide ideation classification was significantly higher for multimodal features (78.16%) which pain avoidance ranked the first and the CNV ranked the fifth than a single ERP feature model (66.62%). Pain avoidance emerged as the most optimal feature of suicide ideation classification than depression. And the CNV elicited by punitive cues may be a biomarker in suicide ideation. Pain avoidance and its related EEG components may improve the efficacy of suicide ideation classification as compared to depression.

Electrophysiology as a Tool to Decipher the Network Mechanism of Visceral Pain in Functional Gastrointestinal Disorders

Abdominal pain, including visceral pain, is prevalent in functional gastrointestinal (GI) disorders (FGIDs), affecting the overall quality of a patient's life. Neural circuits in the brain encode, store, and transfer pain information across brain regions. Ascending pain signals actively shape brain dynamics; in turn, the descending system responds to the pain through neuronal inhibition. Pain processing mechanisms in patients are currently mainly studied with neuroimaging techniques; however, these techniques have a relatively poor temporal resolution. A high temporal resolution method is warranted to decode the dynamics of the pain processing mechanisms. Here, we reviewed crucial brain regions that exhibited pain-modulatory effects in an ascending and descending manner. Moreover, we discussed a uniquely well-suited method, namely extracellular electrophysiology, that captures natural language from the brain with high spatiotemporal resolution. This approach allows parallel recording of large populations of neurons in interconnected brain areas and permits the monitoring of neuronal firing patterns and comparative characterization of the brain oscillations. In addition, we discussed the contribution of these oscillations to pain states. In summary, using innovative, state-of-the-art methods, the large-scale recordings of multiple neurons will guide us to better understanding of pain mechanisms in FGIDs.