Brain oscillations reflecting pain-related behavior in freely moving rats

Neural mechanisms underlying reduced nocifensive sensitivity in autism-associated Shank3 mutant dogs

Autistic individuals carrying mutations in SHANK3 (encoding a synaptic scaffolding protein) have been consistently reported to exhibit reduced pain sensitivity. However, the neural mechanisms underlying impaired pain processing remain unclear. To investigate the role of SHANK3 in pain processing, we conducted behavioral, electrophysiological, and pharmacological tests upon nociceptive stimulation in a Shank3 mutant dog model. Behaviorally, Shank3 mutant dogs showed reduced nocifensive sensitivity compared to wild-type (WT) dogs. Electrophysiologically, Shank3 mutant dogs exhibited reduced neural responses elicited by the activations of both Aδ- and C-fiber nociceptors. Additionally, Shank3 mutants showed a lower level of aperiodic exponents, which serve as a marker for the excitatory-inhibitory balance of neural activity. The aperiodic exponents mediated the relationship between genotype and nocifensive sensitivity as well as between genotype and neural responses elicited by nociceptive stimuli. Pharmacologically, the reduced nocifensive sensitivity and atypical excitatory-inhibitory balance were rescued by a GABAAR antagonist pentylenetetrazole. These findings highlight the critical role of Shank3 in pain processing and suggest that an impaired excitatory-inhibitory balance may be responsible for the reduced nocifensive reactivity in autism.

Transformer-based classification of visceral pain-related local field potential patterns in the brain

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.

Advances and challenges in neuroimaging-based pain biomarkers

Identifying neural biomarkers of pain has long been a central theme in pain neuroscience. Here, we review the state-of-the-art candidates for neural biomarkers of acute and chronic pain. We classify these potential neural biomarkers into five categories based on the nature of their target variables, including neural biomarkers of (1) within-individual perception, (2) between-individual sensitivity, and (3) discriminability for acute pain, as well as (4) assessment and (5) prospective neural biomarkers for chronic pain. For each category, we provide a synthesized review of candidate biomarkers developed using neuroimaging techniques including functional magnetic resonance imaging (fMRI), structural magnetic resonance imaging (sMRI), and electroencephalography (EEG). We also discuss the conceptual and practical challenges in developing neural biomarkers of pain. Addressing these challenges, optimal biomarkers of pain can be developed to deepen our understanding of how the brain represents pain and ultimately help alleviate patients' suffering and improve their well-being.

Neuroplasticity changes in knee osteoarthritis (KOA) indexed by event-related desynchronization/synchronization during a motor inhibition task

PURPOSE

Event-related desynchronisation (ERD) and event-related synchronisation (ERS) reflect pain perception and integration of the nociceptive sensory inputs. This may contribute to the understanding of how neurophysiological markers of Knee Osteoarthritis (KOA) patients can differ from control individuals, which would improve aspects such as prediction and prognosis. We performed a cross-sectional analysis of our cohort study (DEFINE cohort), KOA arm, with 71 patients, compared with 65 control participants. The study aimed to examine possible differences between ERD and ERS in control participants compared to Knee Osteoarthritis (KOA) patients when adjusting for important covariates.

MATERIALS AND METHODS

We performed independent multivariate regression models considering as dependent variables the power value related to ERD and ERS for four different sensorimotor tasks (Motor Execution, Motor Imagery, Active Observation and Passive Observation) and four sensorimotor oscillations (Alpha, Beta, Low Beta, and High Beta), each model, controlled by age and sex.

RESULTS

We demonstrate that the differences between KOA and healthy subjects are frequency specific, as most differences are in the beta bandwidth range. Also, we observed that subjects in the KOA group had significantly higher ERD and ERS. This may be correlated to the amount of lack of brain organisation and a subsequent attempt at compensation induced by KOA.

CONCLUSIONS

Our findings strengthen the notion that subjects with KOA have a higher degree of brain plasticity changes that are also likely correlated to the degree of compensation and behavioural dysfunction.

Deciphering Authentic Nociceptive Thalamic Responses in Rats

The thalamus and its cortical connections play a pivotal role in pain information processing, yet the exploration of its electrophysiological responses to nociceptive stimuli has been limited. Here, in 2 experiments we recorded neural responses to nociceptive laser stimuli in the thalamic (ventral posterior lateral nucleus and medial dorsal nucleus) and cortical regions (primary somatosensory cortex [S1] and anterior cingulate cortex) within the lateral and medial pain pathways. We found remarkable similarities in laser-evoked brain responses that encoded pain intensity within thalamic and cortical regions. Contrary to the expected temporal sequence of ascending information flow, the recorded thalamic response (N1) was temporally later than its cortical counterparts, suggesting that it may not be a genuine thalamus-generated response. Importantly, we also identified a distinctive component in the thalamus, i.e., the early negativity (EN) occurring around 100 ms after the onset of nociceptive stimuli. This EN component represents an authentic nociceptive thalamic response and closely synchronizes with the directional information flow from the thalamus to the cortex. These findings underscore the importance of isolating genuine thalamic neural responses, thereby contributing to a more comprehensive understanding of the thalamic function in pain processing. Additionally, these findings hold potential clinical implications, particularly in the advancement of closed-loop neuromodulation treatments for neurological diseases targeting this vital brain region.

Astrocytes in Pain Perception: A Systems Neuroscience Approach

Astrocytes play an active role in the function of the brain integrating neuronal activity and regulating back neuronal dynamic. They have recently emerged as active contributors of brain's emergent properties such as perceptions. Here, we analyzed the role of astrocytes in pain perception from the lens of systems neuroscience, and we do this by analyzing how astrocytes encode nociceptive information within brain processing areas and how they are key regulators of the internal state that determines pain perception. Specifically, we discuss the dynamic interactions between astrocytes and neuromodulators, such as noradrenaline, highlighting their role in shaping the level of activation of the neuronal ensemble, thereby influencing the experience of pain. Also, we will discuss the possible implications of an "Astro-NeuroMatrix" in the integration of pain across sensory, affective, and cognitive dimensions of pain perception.

Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients

Introduction

Chronic pain negatively impacts a range of sensory and affective behaviors. Previous studies have shown that the presence of chronic pain not only causes hypersensitivity at the site of injury but may also be associated with pain-aversive experiences at anatomically unrelated sites. While animal studies have indicated that the cingulate and prefrontal cortices are involved in this generalized hyperalgesia, the mechanisms distinguishing increased sensitivity at the site of injury from a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs are not well known.

Methods

We compared measured pain responses to peripheral mechanical stimuli applied to a site of chronic pain and at a pain-free site in participants suffering from chronic lower back pain (n = 15) versus pain-free control participants (n = 15) by analyzing behavioral and electroencephalographic (EEG) data.

Results

As expected, participants with chronic pain endorsed enhanced pain with mechanical stimuli in both back and hand. We further analyzed electroencephalographic (EEG) recordings during these evoked pain episodes. Brain oscillations in theta and alpha bands in the medial orbitofrontal cortex (mOFC) were associated with localized hypersensitivity, while increased gamma oscillations in the anterior cingulate cortex (ACC) and increased theta oscillations in the dorsolateral prefrontal cortex (dlPFC) were associated with generalized hyperalgesia.

Discussion

These findings indicate that chronic pain may disrupt multiple cortical circuits to impact nociceptive processing.

Pain sensitivity related to gamma oscillation of parvalbumin interneuron in primary somatosensory cortex in Dync1i1-/- mice

Cytoplasmic dynein is an important intracellular motor protein that plays an important role in neuronal growth, axonal polarity formation, dendritic differentiation, and dendritic spine development among others. The intermediate chain of dynein, encoded by Dync1i1, plays a vital role in the dynein complex. Therefore, we assessed the behavioral and related neuronal activities in mice with dync1i1 gene knockout. Neuronal activities in primary somatosensory cortex were recorded by in vivo electrophysiology and manipulated by optogenetic and chemogenetics. Nociception of mechanical, thermal, and cold pain in Dync1i1^-/- mice were impaired. The activities of parvalbumin (PV) interneurons and gamma oscillation in primary somatosensory were also impaired when exposed to mechanical nociceptive stimulation. This neuronal dysfunction was rescued by optogenetic activation of PV neurons in Dync1i1^-/- mice, and mimicked by suppressing PV neurons using chemogenetics in WT mice. Impaired pain sensations in Dync1i1^-/- mice were correlated with impaired gamma oscillations due to a loss of interneurons, especially the PV type. This genotype-driven approach revealed an association between impaired pain sensation and cytoplasmic dynein complex.

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.

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.

Temporal pain processing in the primary somatosensory cortex and anterior cingulate cortex

Pain is known to have sensory and affective components. The sensory pain component is encoded by neurons in the primary somatosensory cortex (S1), whereas the emotional or affective pain experience is in large part processed by neural activities in the anterior cingulate cortex (ACC). The timing of how a mechanical or thermal noxious stimulus triggers activation of peripheral pain fibers is well-known. However, the temporal processing of nociceptive inputs in the cortex remains little studied. Here, we took two approaches to examine how nociceptive inputs are processed by the S1 and ACC. We simultaneously recorded local field potentials in both regions, during the application of a brain-computer interface (BCI). First, we compared event related potentials in the S1 and ACC. Next, we used an algorithmic pain decoder enabled by machine-learning to detect the onset of pain which was used during the implementation of the BCI to automatically treat pain. We found that whereas mechanical pain triggered neural activity changes first in the S1, the S1 and ACC processed thermal pain with a reasonably similar time course. These results indicate that the temporal processing of nociceptive information in different regions of the cortex is likely important for the overall pain experience.

The neurobiology of pain and facial movements in rodents: Clinical applications and current research

One of the most controversial aspects of the use of animals in science is the production of pain. Pain is a central ethical concern. The activation of neural pathways involved in the pain response has physiological, endocrine, and behavioral consequences, that can affect both the health and welfare of the animals, as well as the validity of research. The strategy to prevent these consequences requires understanding of the nociception process, pain itself, and how assessment can be performed using validated, non-invasive methods. The study of facial expressions related to pain has undergone considerable study with the finding that certain movements of the facial muscles (called facial action units) are associated with the presence and intensity of pain. This review, focused on rodents, discusses the neurobiology of facial expressions, clinical applications, and current research designed to better understand pain and the nociceptive pathway as a strategy for implementing refinement in biomedical research.

Awareness and consciousness in humans and animals - neural and behavioral correlates in an evolutionary perspective

Awareness or consciousness in the context of stimulus perception can directly be assessed in well controlled test situations with humans via the persons' reports about their subjective experiences with the stimuli. Since we have no direct access to subjective experiences in animals, their possible awareness or consciousness in stimulus perception tasks has often been inferred from behavior and cognitive abilities previously observed in aware and conscious humans. Here, we analyze published human data primarily on event-related potentials and brain-wave generation during perception and responding to sensory stimuli and extract neural markers (mainly latencies of evoked-potential peaks and of gamma-wave occurrence) indicating that a person became aware or conscious of the perceived stimulus. These neural correlates of consciousness were then applied to sets of corresponding data from various animals including several species of mammals, and one species each of birds, fish, cephalopods, and insects. We found that the neural markers from studies in humans could also successfully be applied to the mammal and bird data suggesting that species in these animal groups can become subjectively aware of and conscious about perceived stimuli. Fish, cephalopod and insect data remained inconclusive. In an evolutionary perspective we have to consider that both awareness of and consciousness about perceived stimuli appear as evolved, attention-dependent options added to the ongoing neural activities of stimulus processing and action generation. Since gamma-wave generation for functional coupling of brain areas in aware/conscious states is energetically highly cost-intensive, it remains to be shown which animal species under which conditions of lifestyle and ecological niche may achieve significant advantages in reproductive fitness by drawing upon these options. Hence, we started our discussion about awareness and consciousness in animals with the question in how far these expressions of brain activity are necessary attributes for perceiving stimuli and responding in an adaptive way.

Involvement of Parvalbumin-Positive Neurons in the Development of Hyperalgesia in a Mouse Model of Fibromyalgia

Fibromyalgia (FM) presents as chronic systemic pain, which might be ascribed to central sensitization, in which pain information processing is amplified in the central nervous system. Since patients with FM display elevated gamma oscillations in the pain matrix and parvalbumin (PV)-positive neurons play a critical role in induction of gamma oscillations, we hypothesized that changes in PV-positive neurons are involved in hyperalgesia in fibromyalgia. In the present study, to investigate a role of PV-positive neurons in neuropathic pain, mice received reserpine administration for 3 consecutive days as an animal model of FM (RES group), while control mice received vehicle injections in the same way (VEH group). The mice were subjected to hot-plate and forced swim tests, and immuno-stained PV-positive neurons were counted in the pain matrix. We investigated relationships between PV-positive neuron density in the pain matrix and pain avoidance behaviors. The results indicated that the mice in the RES group showed transient bodyweight loss and longer immobility time in the forced swim test than the mice in the VEH group. In the hot-plate test, the RES group showed shorter response latencies and a larger number of jumps in response to nociceptive thermal stimulus than the VEH group. Histological examination indicated an increase in the density of PV-positive neurons in the primary somatosensory cortex (S1) in the RES group. Furthermore, response latencies to the hot-plate were significantly and negatively correlated with the density of PV-positive neurons in the S1. These results suggest a critical role for PV-positive neurons in the S1 to develop hyperalgesia in FM.

Quantitative Electrophysiological Evaluation of the Analgesic Efficacy of Two Lappaconitine Derivatives: A Window into Antinociceptive Drug Mechanisms

Quantitative evaluation of analgesic efficacy improves understanding of the antinociceptive mechanisms of new analgesics and provides important guidance for their development. Lappaconitine (LA), a potent analgesic drug extracted from the root of natural Aconitum species, has been clinically used for years because of its effective analgesic and non-addictive properties. However, being limited to ethological experiments, previous studies have mainly investigated the analgesic effect of LA at the behavioral level, and the associated antinociceptive mechanisms are still unclear. In this study, electrocorticogram (ECoG) technology was used to investigate the analgesic effects of two homologous derivatives of LA, Lappaconitine hydrobromide (LAH) and Lappaconitine trifluoroacetate (LAF), on Sprague-Dawley rats subjected to nociceptive laser stimuli, and to further explore their antinociceptive mechanisms. We found that both LAH and LAF were effective in reducing pain, as manifested in the remarkable reduction of nocifensive behaviors and laser-evoked potentials (LEPs) amplitudes (N2 and P2 waves, and gamma-band oscillations), and significantly prolonged latencies of the LEP-N2/P2. These changes in LEPs reflect the similar antinociceptive mechanism of LAF and LAH, i.e., inhibition of the fast signaling pathways. In addition, there were no changes in the auditory-evoked potential (AEP-N1 component) before and after LAF or LAH treatment, suggesting that neither drug had a central anesthetic effect. Importantly, compared with LAH, LAF was superior in its effects on the magnitudes of gamma-band oscillations and the resting-state spectra, which may be associated with their differences in the octanol/water partition coefficient, degree of dissociation, toxicity, and glycine receptor regulation. Altogether, jointly applying nociceptive laser stimuli and ECoG recordings in rats, we provide solid neural evidence for the analgesic efficacy and antinociceptive mechanisms of derivatives of LA.

Neurobiology of brain oscillations in acute and chronic pain

Pain is a complex perceptual phenomenon. Coordinated activity among local and distant brain networks is a central element of the neural underpinnings of pain. Brain oscillatory rhythms across diverse frequency ranges provide a functional substrate for coordinating activity across local neuronal ensembles and anatomically distant brain areas in pain networks. This review addresses parallels between insights from human and rodent analyses of oscillatory rhythms in acute and chronic pain and discusses recent rodent-based studies that have shed light on mechanistic underpinnings of brain oscillatory dynamics in pain-related behaviors. We highlight the potential for therapeutic modulation of oscillatory rhythms, and identify outstanding questions and challenges to be addressed in future research.

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

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

Predictive coding models for pain perception

Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats-two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out-thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.

A New Apparatus for Recording Evoked Responses to Painful and Non-painful Sensory Stimulation in Freely Moving Mice

Experiments on pain processing in animals face several methodological challenges including the reproducible application of painful stimuli. Ideally, behavioral and physiological correlates of pain should be assessed in freely behaving mice, avoiding stress, fear or behavioral restriction as confounding factors. Moreover, the time of pain-evoked brain activity should be precisely related to the time of stimulation, such that pain-specific neuronal activity can be unambiguously identified. This can be achieved with laser-evoked heat stimuli which are also well established for human pain research. However, laser-evoked neuronal potentials are rarely investigated in awake unrestrained rodents, partially due to the practical difficulties in precisely and reliably targeting and triggering stimulation. In order to facilitate such studies we have developed a versatile stimulation and recording system for freely moving mice. The custom-made apparatus can provide both laser- and mechanical stimuli with simultaneous recording of evoked potentials and behavioral responses. Evoked potentials can be recorded from superficial and deep brain areas showing graded pain responses which correlate with pain-specific behavioral reactions. Non-painful mechanical stimuli can be applied as a control, yielding clearly different electrophysiological and behavioral responses. The apparatus is suited for simultaneous acquisition of precisely timed electrophysiological and behavioral evoked responses in freely moving mice. Besides its application in pain research it may be also useful in other fields of sensory physiology.

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

When skin afferents are activated, the sensory signals are transmitted to the spinal cord and eventually reach the primary somatosensory cortex (S1), initiating the encoding of the sensory percept in the brain. While subsets of primary afferents mediate specific somatosensory information from an early age, the subcortical pathways that transmit this information undergo striking changes over the first weeks of life, reflected in the gradual emergence of specific sensory behaviors. We therefore hypothesized that this period is associated with differential changes in the encoding of incoming afferent volleys in S1. To test this, we compared S1 responses to A fiber skin afferent stimulation and A + C skin afferent fiber stimulation in lightly anaesthetized male rats at postnatal day (P)7, P14, P21, and P30. Differences in S1 activity following A and A + C fiber stimulation changed dramatically over this period. At P30, A + C fiber stimulation evoked significantly larger γ, β, and α energy increases compared with A fiber stimulation alone. At younger ages, the changes in S1 oscillatory activity evoked by the two afferent volleys were not significantly different. Silencing TRPV1+ C fibers with QX-314 significantly reduced the γ and β S1 oscillatory energy increases evoked by A + C fibers, at P30 and P21, but not at younger ages. Thus, C fibers differentially modulate S1 oscillatory activity only from the third postnatal week, well after the functional maturation of the somatosensory cortex. This age-related change in afferent evoked S1 oscillatory activity may underpin the maturation of sensory discrimination in the developing brain.

Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities

Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain. The use of objective biomarkers and clinical trial end points throughout the drug discovery and development process is crucial to help define pathophysiological subsets of pain, evaluate target engagement of new drugs and predict the analgesic efficacy of new drugs. In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement.

Involvement of Frontal Functions in Pain Tolerance in Aging: Evidence From Neuropsychological Assessments and Gamma-Band Oscillations

Reduced pain tolerance may be one of the possible explanations for high prevalence of chronic pain among older people. We hypothesized that age-related alterations in pain tolerance are associated with functioning deterioration of the frontal cortex during normal aging. Twenty-one young and 41 elderly healthy participants underwent a tonic heat pain test, during which cerebral activity was recorded using electroencephalography (EEG). Elderly participants were divided into two subgroups according to their scores on executive tests, high performers (HPs; n = 21) and low performers (LPs; n = 20). Pain measures [exposure times (ETs) and perceived pain ratings] and cerebral activity were compared among the three groups. ETs were significantly lower in elderly LPs than in young participants and elderly HPs. Electroencephalographic analyses showed that gamma-band oscillations (GBOs) were significantly increased in pain state for all subjects, especially in the frontal sites. Source analysis showed that GBO increase in elderly LPs was contributed not only by frontal but also by central, parietal, and occipital regions. These findings suggest that better preservation of frontal functions may result in better pain tolerance by elderly subjects.

A Predictive Coding Model for Evoked and Spontaneous Pain Perception

Pain is a complex multidimensional experience, and pain perception is still incompletely understood. Here we combine animal behavior, electrophysiology, and computer modeling to dissect mechanisms of evoked and spontaneous pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC) of freely behaving rats during pain episodes, and develop a predictive coding model to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Our preliminary results from computational simulations support the experimental findings and provide new predictions.

The Neural Origin of Nociceptive-Induced Gamma-Band Oscillations

Gamma-band oscillations (GBOs) elicited by transient nociceptive stimuli are one of the most promising biomarkers of pain across species. Still, whether these GBOs reflect stimulus encoding in the primary somatosensory cortex (S1) or nocifensive behavior in the primary motor cortex (M1) is debated. Here we recorded neural activity simultaneously from the brain surface as well as at different depths of the bilateral S1/M1 in freely-moving male rats receiving nociceptive stimulation. GBOs measured from superficial layers of S1 contralateral to the stimulated paw not only had the largest magnitude, but also showed the strongest temporal and phase coupling with epidural GBOs. Also, spiking of superficial S1 interneurons had the strongest phase coherence with epidural GBOs. These results provide the first direct demonstration that scalp GBOs, one of the most promising pain biomarkers, reflect neural activity strongly coupled with the fast spiking of interneurons in the superficial layers of the S1 contralateral to the stimulated side.SIGNIFICANCE STATEMENT Nociceptive-induced gamma-band oscillations (GBOs) measured at population level are one of the most promising biomarkers of pain perception. Our results provide the direct demonstration that these GBOs reflect neural activity coupled with the spike firing of interneurons in the superficial layers of the primary somatosensory cortex (S1) contralateral to the side of nociceptive stimulation. These results address the ongoing debate about whether nociceptive-induced GBOs recorded with scalp EEG or epidurally reflect stimulus encoding in the S1 or nocifensive behavior in the primary motor cortex (M1), and will therefore influence how experiments in pain neuroscience will be designed and interpreted.

Early gamma-oscillations as correlate of localized nociceptive processing in primary sensorimotor cortex

Recent studies put forward the idea that stimulus-evoked gamma-band oscillations (GBOs; 30-100 Hz) play a specific role in nociception. So far, evidence for the specificity of GBOs for nociception, their possible involvement in nociceptive sensory discriminatory abilities, and knowledge regarding their cortical sources is just starting to grow. To address these questions, we used electroencephalography (EEG) to record brain activity evoked by phasic nociceptive laser stimuli and tactile stimuli applied at different intensities to the right hand and foot of 12 healthy volunteers. The EEG was analyzed in the time domain to extract phase-locked event-related brain potentials (ERPs) and in three regions of interest in the time-frequency domain (delta/theta, 40-Hz gamma, 70-Hz gamma) to extract stimulus-evoked changes in the magnitude of non-phase-locked brain oscillations. Both nociceptive and tactile stimuli, matched with respect to subjective intensity, elicited phase locked ERPs of increasing amplitude with increasing stimulus intensity. In contrast, only nociceptive stimuli elicited a significant enhancement of GBOs (65-85 Hz, 150-230 ms after stimulus onset), whose magnitude encoded stimulus intensity, whereas tactile stimuli led to a GBO decrease. Following nociceptive hand stimulation, the topographical distribution of GBOs was maximal at contralateral electrode C3, whereas maximum activity following foot stimulation was recorded at the midline electrode Cz, compatible with generation of GBOs in the representations of the hand and foot of the primary sensorimotor cortex, respectively. The differential behavior of high-frequency GBOs and low-frequency 40-Hz GBOs is indicating different functional roles and regions in sensory processing.NEW & NOTEWORTHY Gamma-band oscillations show hand-foot somatotopy compatible with generation in primary sensorimotor cortex and are present following nociceptive but not tactile stimulation of the hand and foot in humans.

Granger causality analysis of rat cortical functional connectivity in pain

OBJECTIVE

The primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) are two of the most important cortical brain regions encoding the sensory-discriminative and affective-emotional aspects of pain, respectively. However, the functional connectivity of these two areas during pain processing remains unclear. Developing methods to dissect the functional connectivity and directed information flow between cortical pain circuits can reveal insight into neural mechanisms of pain perception.

APPROACH

We recorded multichannel local field potentials (LFPs) from the S1 and ACC in freely behaving rats under various conditions of pain stimulus (thermal versus mechanical) and pain state (naive versus chronic pain). We applied Granger causality (GC) analysis to the LFP recordings and inferred frequency-dependent GC statistics between the S1 and ACC.

MAIN RESULTS

We found an increased information flow during noxious pain stimulus presentation in both S1[Formula: see text]ACC and ACC[Formula: see text]S1 directions, especially at theta and gamma frequency bands. Similar results were found for thermal and mechanical pain stimuli. The chronic pain state shares common observations, except for further elevated GC measures especially in the gamma band. Furthermore, time-varying GC analysis revealed a negative correlation between the direction-specific and frequency-dependent GC and animal's paw withdrawal latency. In addition, we used computer simulations to investigate the impact of model mismatch, noise, missing variables, and common input on the conditional GC estimate. We also compared the GC results with the transfer entropy (TE) estimates.

SIGNIFICANCE

Our results reveal functional connectivity and directed information flow between the S1 and ACC during various pain conditions. The dynamic GC analysis support the hypothesis of cortico-cortical information loop in pain perception, consistent with the computational predictive coding paradigm.

Others' Pain Appraisals Modulate the Anticipation and Experience of Subsequent Pain

The present study investigated how pain appraisals from other individuals modulated self-pain anticipation and perception. Appraisals of pain intensity from 10 other individuals were presented before the participants received identical electrical pain stimulation themselves. In reality, the presented other's pain appraisals, with either low or high in mean and variance, were generated by the experimenter, and were randomly paired with the subsequent electrical stimulation at either low or high intensity. Specifically, the mean and variance of others' pain appraisals were manipulated to induce participants' expectation and certainty to the upcoming pain. Subjective ratings of pain intensity and electroencephalographic (EEG) responses to the electrical stimulation, as well as anticipatory EEG activities measured prior to the onset of electrical stimulation, were compared. Results showed that the mean and variance of others' pain appraisal modulated the subjective pain ratings and the affective-motivational P2 responses elicited by the electrical stimulation, as well as anticipatory sensorimotor α-oscillation measured before the onset of pain stimulation. When the mean of others' pain appraisal was low, higher variance suppressed the sensorimotor α-oscillations and enhanced subsequent pain perception. In contrast, when the mean was high, the higher variance enhanced sensorimotor α-oscillations and suppressed subsequent pain perception. These results demonstrated that others' pain appraisals can modulate both of the anticipation and perception of first-hand pain. It also suggested that the top-down modulation of others' pain appraisals on pain perception could be partially driven by the different brain states during the anticipation stage, as captured by the prestimulus sensorimotor α-oscillations.

Cortical Pain Processing in the Rat Anterior Cingulate Cortex and Primary Somatosensory Cortex

Pain is a complex multidimensional experience encompassing sensory-discriminative, affective-motivational and cognitive-emotional components mediated by different neural mechanisms. Investigations of neurophysiological signals from simultaneous recordings of two or more cortical circuits may reveal important circuit mechanisms on cortical pain processing. The anterior cingulate cortex (ACC) and primary somatosensory cortex (S1) represent two most important cortical circuits related to sensory and affective processing of pain. Here, we recorded in vivo extracellular activity of the ACC and S1 simultaneously from male adult Sprague-Dale rats (n = 5), while repetitive noxious laser stimulations were delivered to animalÕs hindpaw during pain experiments. We identified spontaneous pain-like events based on stereotyped pain behaviors in rats. We further conducted systematic analyses of spike and local field potential (LFP) recordings from both ACC and S1 during evoked and spontaneous pain episodes. From LFP recordings, we found stronger phase-amplitude coupling (theta phase vs. gamma amplitude) in the S1 than the ACC (n = 10 sessions), in both evoked (p = 0.058) and spontaneous pain-like behaviors (p = 0.017, paired signed rank test). In addition, pain-modulated ACC and S1 neuronal firing correlated with the amplitude of stimulus-induced event-related potentials (ERPs) during evoked pain episodes. We further designed statistical and machine learning methods to detect pain signals by integrating ACC and S1 ensemble spikes and LFPs. Together, these results reveal differential coding roles between the ACC and S1 in cortical pain processing, as well as point to distinct neural mechanisms between evoked and putative spontaneous pain at both LFP and cellular levels.

Gamma oscillations in somatosensory cortex recruit prefrontal and descending serotonergic pathways in aversion and nociception

In humans, gamma-band oscillations in the primary somatosensory cortex (S1) correlate with subjective pain perception. However, functional contributions to pain and the nature of underlying circuits are unclear. Here we report that gamma oscillations, but not other rhythms, are specifically strengthened independently of any motor component in the S1 cortex of mice during nociception. Moreover, mice with inflammatory pain show elevated resting gamma and alpha activity and increased gamma power in response to sub-threshold stimuli, in association with behavioral nociceptive hypersensitivity. Inducing gamma oscillations via optogenetic activation of parvalbumin-expressing inhibitory interneurons in the S1 cortex enhances nociceptive sensitivity and induces aversive avoidance behavior. Activity mapping identified a network of prefrontal cortical and subcortical centers whilst morphological tracing and pharmacological studies demonstrate the requirement of descending serotonergic facilitatory pathways in these pain-related behaviors. This study thus describes a mechanistic framework for modulation of pain by specific activity patterns in the S1 cortex.

Gamma oscillations in somatosensory areas in humans correlate with pain perception and pain stimulus intensity, but could also reflect cognitive processes such as attention. Here the authors provide evidence in mice that these oscillations causally contribute to pain perception.

Neural indicators of perceptual variability of pain across species

While several features of brain activity can be used to predict the variability of painful percepts within a given individual, it is much more difficult to predict pain variability across individuals. Here, we used electrophysiology to sample brain activity of humans and rodents, and demonstrated that laser-induced gamma oscillations sampled by central electrodes predict pain sensitivity across individuals both reliably and selectively: reliably, because they consistently predict between-subject pain intensity in both humans and rodents; selectively, because they do not track the between-subject reported intensity of nonpainful but equally salient auditory, visual, and nonnociceptive somatosensory stimuli. This discovery indicates that variability in an individual’s pain sensitivity is, at least partly, explained by variability in the amplitude of gamma oscillations of that individual.

Individuals exhibit considerable and unpredictable variability in painful percepts in response to the same nociceptive stimulus. Previous work has found neural responses that, while not necessarily responsible for the painful percepts themselves, can still correlate well with intensity of pain perception within a given individual. However, there is no reliable neural response reflecting the variability in pain perception across individuals. Here, we use an electrophysiological approach in humans and rodents to demonstrate that brain oscillations in the gamma band [gamma-band event-related synchronization (γ-ERS)] sampled by central electrodes reliably predict pain sensitivity across individuals. We observed a clear dissociation between the large number of neural measures that reflected subjective pain ratings at within-subject level but not across individuals, and γ-ERS, which reliably distinguished subjective ratings within the same individual but also coded pain sensitivity across different individuals. Importantly, the ability of γ-ERS to track pain sensitivity across individuals was selective because it did not track the between-subject reported intensity of nonpainful but equally salient auditory, visual, and nonnociceptive somatosensory stimuli. These results also demonstrate that graded neural activity related to within-subject variability should be minimized to accurately investigate the relationship between nociceptive-evoked neural activities and pain sensitivity across individuals.

Distinct patterns of brain activity mediate perceptual and motor and autonomic responses to noxious stimuli

Pain is a complex phenomenon involving perceptual, motor, and autonomic responses, but how the brain translates noxious stimuli into these different dimensions of pain is unclear. Here, we assessed perceptual, motor, and autonomic responses to brief noxious heat stimuli and recorded brain activity using electroencephalography (EEG) in humans. Multilevel mediation analysis reveals that each pain dimension is subserved by a distinct pattern of EEG responses and, conversely, that each EEG response differentially contributes to the different dimensions of pain. In particular, the translation of noxious stimuli into autonomic and motor responses involved the earliest N1 wave, whereas pain perception was mediated by later N2 and P2 waves. Gamma oscillations mediated motor responses rather than pain perception. These findings represent progress towards a mechanistic understanding of the brain processes translating noxious stimuli into pain and suggest that perceptual, motor, and autonomic dimensions of pain are partially independent rather than serial processes.

Pain is a complex phenomenon involving not just the perception of pain, but also autonomic and motor responses. Here, the authors show that these different dimensions of pain are associated with distinct patterns of neural responses to noxious stimuli as measured using EEG.

Ensembles of change-point detectors: implications for real-time BMI applications

Brain-machine interfaces (BMIs) have been widely used to study basic and translational neuroscience questions. In real-time closed-loop neuroscience experiments, many practical issues arise, such as trial-by-trial variability, and spike sorting noise or multi-unit activity. In this paper, we propose a new framework for change-point detection based on ensembles of independent detectors in the context of BMI application for detecting acute pain signals. Motivated from ensemble learning, our proposed "ensembles of change-point detectors" (ECPDs) integrate multiple decisions from independent detectors, which may be derived based on data recorded from different trials, data recorded from different brain regions, data of different modalities, or models derived from different learning methods. By integrating multiple sources of information, the ECPDs aim to improve detection accuracy (in terms of true positive and true negative rates) and achieve an optimal trade-off of sensitivity and specificity. We validate our method using computer simulations and experimental recordings from freely behaving rats. Our results have shown superior and robust performance of ECPDS in detecting the onset of acute pain signals based on neuronal population spike activity (or combined with local field potentials) recorded from single or multiple brain regions.

Local field potential decoding of the onset and intensity of acute pain in rats

Pain is a complex sensory and affective experience. The current definition for pain relies on verbal reports in clinical settings and behavioral assays in animal models. These definitions can be subjective and do not take into consideration signals in the neural system. Local field potentials (LFPs) represent summed electrical currents from multiple neurons in a defined brain area. Although single neuronal spike activity has been shown to modulate the acute pain, it is not yet clear how ensemble activities in the form of LFPs can be used to decode the precise timing and intensity of pain. The anterior cingulate cortex (ACC) is known to play a role in the affective-aversive component of pain in human and animal studies. Few studies, however, have examined how neural activities in the ACC can be used to interpret or predict acute noxious inputs. Here, we recorded in vivo extracellular activity in the ACC from freely behaving rats after stimulus with non-noxious, low-intensity noxious, and high-intensity noxious stimuli, both in the absence and chronic pain. Using a supervised machine learning classifier with selected LFP features, we predicted the intensity and the onset of acute nociceptive signals with high degree of precision. These results suggest the potential to use LFPs to decode acute pain.