Prestimulus Theta Oscillations and Connectivity Modulate Pain Perception

Effect of music therapy on short-term psychological and physiological outcomes in mechanically ventilated patients: A randomized clinical pilot study

Background

Elevated anxiety levels are common in patients on mechanical ventilation (MV) and may challenge recovery. Research suggests music-based interventions may reduce anxiety during MV. However, studies investigating specific music therapy techniques, addressing psychological and physiological well-being in patients on MV, are scarce.

Methods

This three-arm randomized clinical pilot study was conducted with MV patients admitted to the intensive care unit (ICU) of Hospital San José in Bogotá, Colombia between March 7, 2022, and July 11, 2022. Patients were divided into three groups: intervention group 1 (IG1), music-assisted relaxation; intervention group 2 (IG2), patient-preferred therapeutic music listening; and control group (CG), standard care. The main outcome measure was the 6-item State-Anxiety Inventory. Secondary outcomes were: pain (measured with a visual analog scale), resilience (measured with the Brief Resilience Scale), agitation/sedation (measured with the Richmond Agitation-Sedation Scale), vital signs (including heart rate, blood pressure, oxygen saturation, and respiratory rate), days of MV, extubation success, and days in the ICU. Additionally, three patients underwent electroencephalography during the interventions.

Results

Data from 23 patients were analyzed in this study. The age range of the patients was 24.0-84.0 years, with a median age of 66.0 years (interquartile range: 57.0-74.0). Of the 23 patients, 19 were female (82.6%). No statistically significant differences between the groups were observed for anxiety (P=0.330), pain (P=0.624), resilience (P=0.916), agitation/sedation (P=0.273), length of ICU stay (P=0.785), or vital signs. A statistically significant difference between the groups was found for days of MV (P=0.019). Electroencephalography measurements showed a trend toward delta and theta band power decrease for two patients and a power increase on both beta frequencies (slow and fast) in the frontal areas of the brain for one patient.

Conclusions

In this pilot study, music therapy did not significantly affect the anxiety levels in patients on MV. However, the interventions were widely accepted by the staff, patients, and caregivers and were safe, considering the critical medical status of the participants. Further large-scale randomized controlled trials are needed to investigate the potential benefits of music therapeutic interventions in this population.Trial Registration ISRCTN trial registry identifier: ISRCTN16964680.

A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children

OBJECTIVE

Common pain assessment approaches such as self-evaluation and observation scales are inappropriate for children as they require patients to have reasonable communication ability. Subjective, inconsistent, and discontinuous pain assessment in children may reduce therapeutic effectiveness and thus affect their later life.

METHODS

To address the need for suitable assessment measures, this paper proposes a spatiotemporal deep learning framework for scalp electroencephalogram (EEG)-based automated pain assessment in children. The dataset comprises scalp EEG data recorded from 33 pediatric patients with an arterial puncture as a pain stimulus. Two electrode reduction plans in line with clinical findings are proposed. Combining three-dimensional hand-crafted features and preprocessed raw signals, the proposed transformer-based pain assessment network (STPA-Net) integrates both spatial and temporal information.

RESULTS

STPA-Net achieves superior performance with a subject-independent accuracy of 87.83% for pain recognition, and outperforms other state-of-the-art approaches. The effectiveness of electrode combinations is explored to analyze pain-related cortical activities and correspondingly reduce cost. The two proposed electrode reduction plans both demonstrate competitive pain assessment performance qualitatively and quantitatively.

CONCLUSION AND SIGNIFICANCE

This study is the first to develop a scalp EEG-based automated pain assessment for children adopting a method that is objective, standardized, and consistent. The findings provide a potential reference for future clinical research.

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.

Cerebellar somatotopy of the trigemino-cervical complex during nociception

INTRODUCTION

The somatotopic organization of the human cerebellum processes somato-motoric input. Its role during pain perception for nociceptive input remains ambiguous. A standardized experimental trigeminal nociceptive input in functional imaging might clarify the role of the cerebellum in trigeminal nociception. Also of interest is the greater occipital nerve, which innervates the back of the head, and can influence the trigeminal perception due to functional coupling within the brainstem, forming the so-called trigemino-cervical complex.

METHODS

In our preregistered study (clinicaltrials.gov: NTC03999060), we stimulated the greater occipital as well as the three main branches of the trigeminal nerve during functional magnetic resonance imaging in two independent cohorts of young healthy volunteers without psychiatric, neurological or pain-related disorders to disentangle overlapping somatotopic cerebellar organization of the nerves innervating the human head.

RESULTS

We found a dominant effect of the first trigeminal branch in the cerebellum, underpinning its particular role for headache diseases, and somatotopic representations in bilateral cerebellar lobules I-IV, V, VIIb, VIIIa and Crus I as well as in the brainstem.

SIGNIFICANCE

The study expands the current knowledge on facial and head pain processing by the cerebellum and provides an initial somatotopic map of the trigemino-cervical complex in the human cerebellum with a predominant representation of the first trigeminal branch.

Resting-state electroencephalography delta and theta bands as compensatory oscillations in chronic neuropathic pain: a secondary data analysis

Chronic neuropathic pain (CNP) remains a significant clinical challenge, with complex neurophysiological underpinnings that are not fully understood. Identifying specific neural oscillatory patterns related to pain perception and interference can enhance our understanding and management of CNP. To analyze resting electroencephalography data from individuals with chronic neuropathic pain to explore the possible neural signatures associated with pain intensity, pain interference, and specific neuropathic pain characteristics. We conducted a secondary analysis from a cross-sectional study using electroencephalography data from a previous study, and Brief Pain Inventory from 36 patients with chronic neuropathic pain. For statistical analysis, we modeled a linear or logistic regression by dependent variable for each model. As independent variables, we used electroencephalography data with such brain oscillations: as delta, theta, alpha, and beta, as well as the oscillations low alpha, high alpha, low beta, and high beta, for the central, frontal, and parietal regions. All models tested for confounding factors such as age and medication. There were no significant models for Pain interference in general activity, walking, work, relationships, sleep, and enjoyment of life. However, the model for pain intensity during the past four weeks showed decreased alpha oscillations, and increased delta and theta oscillations were associated with decreased levels of pain, especially in the central area. In terms of pain interference in mood, the model showed high oscillatory Alpha signals in the frontal and central regions correlated with mood impairment due to pain. Our models confirm recent findings proposing that lower oscillatory frequencies, likely related to subcortical pain sources, may be associated with brain compensatory mechanisms and thus may be associated with decreased pain levels. On the other hand, higher frequencies, including alpha oscillations, may disrupt top-down compensatory mechanisms.

Higher cortical excitability to negative emotions involved in musculoskeletal pain in Parkinson's disease

OBJECTIVE

Changes in brain structure and neurotransmitter systems are involved in pain in Parkinson's disease (PD), and emotional factors are closely related to pain. Our study applied electroencephalography (EEG) to investigate the role of emotion in PD patients with chronic musculoskeletal pain.

METHODS

Forty-two PD patients with chronic musculoskeletal pain and 38 without were enrolled. EEG data were recorded under resting conditions, and while viewing pictures with neutral, positive, and negative content. We compared spectrum power, functional connectivity, and late positive potential (LPP), an event-related potential (ERP), between the groups.

RESULTS

PD patients with pain tended to have higher scores for the Hamilton Rating Scale for Depression (HRSD). In the resting EEG, mean β-band amplitude was significantly higher in patients with pain than in those without. Logistic regression analysis showed that higher HRSD scores and higher mean β-band amplitude were associated with pain. ERP analysis revealed that the amplitudes of LPP difference waves (the absolute difference between positive and negative condition LPP and neutral condition LPP) at the central-parietal region were significantly reduced in patients with pain (P = 0.029). Spearman correlation analysis showed that the amplitudes of late (700-1000 ms) negative versus neutral condition LPP difference waves were negatively correlated with pain intensity, assessed by visual analogue scale, (r = -0.393, P = 0.010) and HRSD scores (r = -0.366, P = 0.017).

CONCLUSION

Dopaminergic and non-dopaminergic systems may be involved in musculoskeletal pain in PD by increasing β-band activity and weakening the connection of the θ-band at the central-parietal region. PD patients with musculoskeletal pain have higher cortical excitability to negative emotions. The changes in pain-related EEG may be used as electrophysiological markers and therapeutic targets in PD patients with chronic pain.

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.

Relationship between individual differences in pain empathy and task- and resting-state EEG

Pain empathy is a complex form of psychological inference that enables us to understand how others feel in the context of pain. Since pain empathy may be grounded in our own pain experiences, it exhibits huge inter-individual variability. However, the neural mechanisms behind the individual differences in pain empathy and its association with pain perception are still poorly understood. In this study, we aimed to characterize brain mechanisms associated with individual differences in pain empathy in adult participants (n = 24). The 32-channel electroencephalography (EEG) was recorded at rest and during a pain empathy task, and participants viewed static visual stimuli of the limbs submitted to painful and nonpainful stimulation to solicit empathy. The pain sensitivity of each participant was measured using a series of direct current stimulations. In our results, the N2 of Fz and the LPP of P3 and P4 were affected by painful pictures. We found that both delta and alpha bands in the frontal and parietal cortex were involved in the regulation of pain empathy. For the delta band, a close relationship was found between average power, either in the resting or task state, and individual differences in pain empathy. It suggested that the spectral power in Fz's delta band may reflect subjective pain empathy across individuals. For the alpha band, the functional connectivity between Fz and P3 under painful picture stimulation was correlated to individuals' pain sensitivity. It indicated that the alpha band may reflect individual differences in pain sensitivity and be involved in pain empathy processing. Our results suggested the distinct role of the delta and alpha bands of EEG signals in pain empathy processing and may deepen our understanding of the neural mechanisms underpinning pain empathy.

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.

Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain

To unravel the complexity of the neuropathic pain experience, researchers have tried to identify reliable pain signatures (biomarkers) using electroencephalography (EEG) and skin conductance (SC). Nevertheless, their use as a clinical aid to design personalized therapies remains scarce and patients are prescribed with common and inefficient painkillers. To address this need, novel non-pharmacological interventions, such as transcutaneous electrical nerve stimulation (TENS) to activate peripheral pain relief via neuromodulation and virtual reality (VR) to modulate patients' attention, have emerged. However, all present treatments suffer from the inherent bias of the patient's self-reported pain intensity, depending on their predisposition and tolerance, together with unspecific, pre-defined scheduling of sessions which does not consider the timing of pain episodes onset. Here, we show a Brain-Computer Interface (BCI) detecting in real-time neurophysiological signatures of neuropathic pain from EEG combined with SC and accordingly triggering a multisensory intervention combining TENS and VR. After validating that the multisensory intervention effectively decreased experimentally induced pain, the BCI was tested with thirteen healthy subjects by electrically inducing pain and showed 82% recall in decoding pain in real time. Such constructed BCI was then validated with eight neuropathic patients reaching 75% online pain precision, and consequently releasing the intervention inducing a significant decrease (50% NPSI score) in neuropathic patients' pain perception. Our results demonstrate the feasibility of real-time pain detection from objective neurophysiological signals, and the effectiveness of a triggered combination of VR and TENS to decrease neuropathic pain. This paves the way towards personalized, data-driven pain therapies using fully portable technologies.

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.

Post-injury pain and behaviour: a control theory perspective

Injuries of various types occur commonly in the lives of humans and other animals and lead to a pattern of persistent pain and recuperative behaviour that allows safe and effective recovery. In this Perspective, we propose a control-theoretic framework to explain the adaptive processes in the brain that drive physiological post-injury behaviour. We set out an evolutionary and ethological view on how animals respond to injury, illustrating how the behavioural state associated with persistent pain and recuperation may be just as important as phasic pain in ensuring survival. Adopting a normative approach, we suggest that the brain implements a continuous optimal inference of the current state of injury from diverse sensory and physiological signals. This drives the various effector control mechanisms of behavioural homeostasis, which span the modulation of ongoing motivation and perception to drive rest and hyper-protective behaviours. However, an inherent problem with this is that these protective behaviours may partially obscure information about whether injury has resolved. Such information restriction may seed a tendency to aberrantly or persistently infer injury, and may thus promote the transition to pathological chronic pain states.

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.

Accounting for endogenous effects in decision-making with a non-linear diffusion decision model

The Drift-Diffusion Model (DDM) is widely accepted for two-alternative forced-choice decision paradigms thanks to its simple formalism and close fit to behavioral and neurophysiological data. However, this formalism presents strong limitations in capturing inter-trial dynamics at the single-trial level and endogenous influences. We propose a novel model, the non-linear Drift-Diffusion Model (nl-DDM), that addresses these issues by allowing the existence of several trajectories to the decision boundary. We show that the non-linear model performs better than the drift-diffusion model for an equivalent complexity. To give better intuition on the meaning of nl-DDM parameters, we compare the DDM and the nl-DDM through correlation analysis. This paper provides evidence of the functioning of our model as an extension of the DDM. Moreover, we show that the nl-DDM captures time effects better than the DDM. Our model paves the way toward more accurately analyzing across-trial variability for perceptual decisions and accounts for peri-stimulus influences.

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.

Electroencephalogram-based prediction and detection of responsiveness to noxious stimulation in critical care patients: a retrospective single-centre analysis

BACKGROUND

Monitoring of pain and nociception in critical care patients unable to self-report pain remains a challenge, as clinical signs are neither sensitive nor specific. Available technical approaches are limited by various constraints. We investigated the electroencephalogram (EEG) for correlates that precede or coincide with behavioural nociceptive responses to noxious stimulation.

METHODS

In this retrospective study, we analysed frontal EEG recordings of 64 critical care patients who were tracheally intubated and ventilated before, during, and after tracheal suctioning. We investigated EEG power bands for correlates preceding or coinciding with behavioural responses (Behavioural Pain Scale ≥7). We applied the Mann-Whitney U-test to calculate corresponding P-values.

RESULTS

Strong behavioural responses were preceded by higher normalised power in the 2.5-5 Hz band (+17.1%; P<0.001) and lower normalised power in the 0.1-1.5 Hz band (-10.5%; P=0.029). After the intervention, strong behavioural responses were associated with higher normalised EEG power in the 2.5-5 Hz band (+16.6%; P=0.021) and lower normalised power in the 8-12 Hz band (-51.2%; P=0.037) CONCLUSIONS: We observed correlates in EEG band power that precede and coincide with behavioural responses to noxious stimulation. Based on previous findings, some of the power bands could be linked to processing of nociception, arousal, or sedation effects. The power bands more closely related to nociception and arousal could be used to improve monitoring of nociception and to optimise analgesic management in critical care patients.

CLINICAL TRIAL REGISTRATION

DRKS00011206.

A study based on functional near-infrared spectroscopy: Cortical responses to music interventions in patients with myofascial pain syndrome

Object

This study measured cerebral blood oxygen changes in patients with myofascial pain syndrome (MPS) using functional near-infrared spectroscopy (fNIRS). The aim was to investigate the effect of music intervention on pain relief in MPS patients.

Materials and methods

A total of 15 patients with MPS participated in this study. A self-controlled block task design was used to collect the oxy-hemoglobin ([HbO2]) and deoxy-hemoglobin ([HbR]) concentrations in the prefrontal cortex (PFC) and motor cortex using fNIRS. The cerebral cortex response and channel connectivity were further analyzed. In the experiment, the therapist was asked to apply compression of 3-4 kg/cm2 vertically using the thumb to induce pain. Soothing synthetic music with frequencies of 8-150 Hz and 50-70 dB was used as the audio for the music intervention.

Result

Compared to the group without music intervention, the activation of brain regions showed a decreasing trend in the group with music intervention under the onset of pain. The results of paired t-tests showed that nine of the data were significantly different (p < 0.05). It was also found that with music intervention, inter-channel connectivity was diminished. Besides, their dorsolateral prefrontal cortex (dlPFC) was significantly correlated with the anterior prefrontal cortex (aPFC) for pain response (r = 0.82), and weakly correlated with the premotor cortex (r = 0.40).

Conclusion

This study combines objective assessment indicators and subjective scale assessments to demonstrate that appropriate music interventions can be effective in helping to relieve pain to some extent. The analgesic mechanisms between relevant brain regions under music intervention were explored in depth. New insights into effective analgesic methods and quantitative assessment of pain conditions are presented.

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.

Neuroimaging Assessment of Pain

Pain is an unpleasant sensory and emotional experience. Understanding the neural mechanisms of acute and chronic pain and the brain changes affecting pain factors is important for finding pain treatment methods. The emergence and progress of non-invasive neuroimaging technology can help us better understand pain at the neural level. Recent developments in identifying brain-based biomarkers of pain through advances in advanced imaging can provide some foundations for predicting and detecting pain. For example, a neurologic pain signature (involving brain regions that receive nociceptive afferents) and a stimulus intensity-independent pain signature (involving brain regions that do not show increased activity in proportion to noxious stimulus intensity) were developed based on multivariate modeling to identify processes related to the pain experience. However, an accurate and comprehensive review of common neuroimaging techniques for evaluating pain is lacking. This paper reviews the mechanism, clinical application, reliability, strengths, and limitations of common neuroimaging techniques for assessing pain to promote our further understanding of pain.

Altered prefrontal-striatal theta-band oscillatory dynamics underlie working memory deficits in neuropathic pain rats

BACKGROUND

Prelimbic medial prefrontal cortex (PL-mPFC) and nucleus accumbens core region (NAcc) play an important role in supporting several executive cognitive mechanisms, such as spatial working-memory (WM). Recently, this circuit has been also associated with both sensory and affective components of pain. However, it is still unclear whether this circuit is endogenously engaged in neuropathic pain-related cognitive dysfunctions.

METHODS

To answer this question, we induced the expression of halorhodopsin in local PL-mPFC neurons projecting to NAcc, and then selectively inhibited the terminals of these neurons in the NAcc while recording neural activity during the performance of a delayed non-match to sample (DNMS) spatial WM task. Within-subject behavioral performance and PL-mPFC to NAcc circuit neural activity was assessed after the onset of a persistent rodent neuropathic pain model - spared nerve injury (SNI).

RESULTS

Our results revealed that the induction of the neuropathy reduced WM performance, and altered the interplay between PL-mPFC and NAcc neurons namely in increasing the functional connectivity from NAcc to PL-mPFC, particularly in the theta-band spontaneous oscillations; in addition, these behavioral and functional perturbations were partially reversed by selective optogenetic inhibition of PL-mPFC neuron terminals into the NAcc during the DNMS task delay-period, without significant antinociceptive effects.

CONCLUSIONS

Altogether, these results strongly suggest that the PL-mPFC excitatory output into the NAcc plays an important role in the deregulation of WM under pain conditions.

SIGNIFICANCE

Selective optogenetic inhibition of prefrontal-striatal microcircuit reverses pain-related working memory deficits, but has no significant impact on pain responses. Neuropathic pain underlies an increase of functional connectivity between the nucleus accumbens core area and the prelimbic medial prefrontal cortex mediated by theta-band activity.

High-Density Electroencephalography-Informed Multiband Functional Magnetic Resonance Imaging Reveals Rhythm-Specific Activations Within the Trigeminal Nociceptive Network

The interest in exploring trigeminal pain processing has grown in recent years, mainly due to various pathologies (such as migraine) related to this system. However, research efforts have mainly focused on understanding molecular mechanisms or studying pathological states. On the contrary, non-invasive imaging studies are limited by either spatial or temporal resolution depending on the modality used. This can be overcome by using multimodal imaging techniques such as simultaneous functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Although this technique has already been applied to neuroscientific research areas and consequently gained insights into diverse sensory systems and pathologies, only a few studies have applied EEG-fMRI in the field of pain processing and none in the trigeminal system. Focusing on trigeminal nociception, we used a trigeminal pain paradigm, which has been well-studied in either modality. For validation, we first acquired stand-alone measures with each imaging modality before fusing them in a simultaneous session. Furthermore, we introduced a new, yet simple, non-parametric correlation technique, which exploits trial-to-trial variance of both measurement techniques with Spearman’s correlations, to consolidate the results gained by the two modalities. This new technique does not presume a linear relationship and needs a few repetitions per subject. We also showed cross-validation by analyzing visual stimulations. Using these techniques, we showed that EEG power changes in the theta-band induced by trigeminal pain correlate with fMRI activation within the brainstem, whereas those of gamma-band oscillations correlate with BOLD signals in higher cortical areas.

The influence of EEG oscillations, heart rate variability changes, and personality on self-pain and empathy for pain under placebo analgesia

We induced placebo analgesia (PA), a phenomenon explicitly attenuating the self-pain feeling, to assess whether this resulted in reduced empathy pain when witnessing a confederate undergoing such pain experience. We recorded EEG and electrocardiogram during a painful Control and PA treatment in healthy adults who rated their experienced pain and empathy for pain. We derived HRV changes and, using wavelet analysis of non-phase-locked event-related EEG oscillations, EEG spectral power differences for self-pain and other-pain conditions. First-hand PA reduced self-pain and self-unpleasantness, whereas we observed only a slight decrease in other unpleasantness. We derived linear combinations of HRV and EEG band power changes significantly associated with self-pain and empathy for pain changes using PCAs. Lower Behavioral Inhibition System scores predicted self-pain reduction through the mediating effect of a relative HR-slowing and a decreased midline ϑ-band (4-8 Hz) power factor moderated by lower Fight-Flight-Freeze System trait scores. In the other-pain condition, we detected a direct positive influence of Total Empathic Ability on the other-pain decline with a mediating role of the midline β2-band (22-30 Hz) power reduction. These findings suggest that PA modulation of first-hand versus other pain relies on functionally different physiological processes involving different personality traits.

EEG Recordings as Biomarkers of Pain Perception: Where Do We Stand and Where to Go?

Introduction

The universality and complexity of pain, which is highly prevalent, yield its significance to both patients and researchers. Developing a non-invasive tool that can objectively measure pain is of the utmost importance for clinical and research purposes. Traditionally electroencephalography (EEG) has been mostly used in epilepsy; however, over the recent years EEG has become an important non-invasive clinical tool that has helped increase our understanding of brain network complexities and for the identification of areas of dysfunction. This review aimed to investigate the role of EEG recordings as potential biomarkers of pain perception.

Methods

A systematic search of the PubMed database led to the identification of 938 papers, of which 919 were excluded as a result of not meeting the eligibility criteria, and one article was identified through screening of the reference lists of the 19 eligible studies. Ultimately, 20 papers were included in this systematic review.

Results

Changes of the cortical activation have potential, though the described changes are not always consistent. The most consistent finding is the increase in the delta and gamma power activity. Only a limited number of studies have looked into brain networks encoding pain perception.

Conclusion

Although no robust EEG biomarkers of pain perception have been identified yet, EEG has potential and future research should be attempted. Designing strong research protocols, controlling for potential risk of biases, as well as investigating brain networks rather than isolated cortical changes will be crucial in this attempt.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40122-022-00372-2.

Multivariate prediction of pain perception based on pre-stimulus activity

The perception of pain is modulated by different processes such as, for example, expectations and attention regarding the upcoming stimulus. Such processes are initiated prior to the actual stimulus and are reflected in ongoing brain activity. Different processes that are by definition also complex in itself are reflected in pre-stimulus activity and therefore the detection of this activity pattern should benefit from a multivariate approach. To identify specific pre-stimulus EEG activity patterns related to subsequent pain perception in humans, we contrasted painful with non-painful sensations delivered at the individual threshold level during EEG measurements. The results of the multivariate EEG analysis revealed a high level of accuracy (group mean 68%) in predicting the pain categorization solely based on pre-stimulus activity. In particular, fronto-central regions and activity in the higher gamma band (60:120 Hz) were of maximal importance for classification. Additional analyses supported the specific role of the pattern of high gamma band activity prior to the stimulus for predicting the behavioral outcome and demonstrated that the informational value embedded in the pre-stimulus activity is nearly as informative as the post-stimulus processing and reflects a specific preparatory state. Further, a close relation between pre- and post-stimulus processing in the high gamma band was observed. These findings support the important role of a multivariate cognitive state prior to stimulus appearance for the emergence of the subjective perception of pain and the functional role of widespread high gamma band activity.

The modulation of neural insular activity by a brain computer interface differentially affects pain discrimination

The experience of pain is generated by activations throughout a complex pain network with the insular cortex as a central processing area. The state of ongoing oscillatory activity can influence subsequent processing throughout this network. In particular the ongoing theta-band power can be relevant for later pain processing, however a direct functional relation to post-stimulus processing or behaviour is missing. Here, we used a non-invasive brain-computer interface to either increase or decrease ongoing theta-band power originating in the insular cortex. Our results show a differential modulation of oscillatory power and even more important a transfer to independently measured pain processing and sensation. Pain evoked neural power and subjective pain discrimination were differentially affected by the induced modulations of the oscillatory state. The results demonstrate a functional relevance of insular based theta-band oscillatory states for the processing and subjective discrimination of nociceptive stimuli and offer the perspective for clinical applications.

The temporal and spectral characteristics of expectations and prediction errors in pain and thermoception

In the context of a generative model, such as predictive coding, pain and heat perception can be construed as the integration of expectation and input with their difference denoted as a prediction error. In a previous neuroimaging study (Geuter et al., 2017) we observed an important role of the insula in such a model but could not establish its temporal aspects. Here, we employed electroencephalography to investigate neural representations of predictions and prediction errors in heat and pain processing. Our data show that alpha-to-beta activity was associated with stimulus intensity expectation, followed by a negative modulation of gamma band activity by absolute prediction errors. This is in contrast to prediction errors in visual and auditory perception, which are associated with increased gamma band activity, but is in agreement with observations in working memory and word matching, which show gamma band activity for correct, rather than violated, predictions.

Individual pain sensitivity is associated with resting-state cortical activities in healthy individuals but not in patients with migraine: a magnetoencephalography study

Background

Pain sensitivity may determine the risk, severity, prognosis, and efficacy of treatment of clinical pain. Magnetic resonance imaging studies have linked thermal pain sensitivity to changes in brain structure. However, the neural correlates of mechanical pain sensitivity remain to be clarified through investigation of direct neural activities on the resting-state cortical oscillation and synchrony.

Methods

We recorded the resting-state magnetoencephalographic (MEG) activities of 27 healthy individuals and 30 patients with episodic migraine (EM) and analyzed the source-based oscillatory powers and functional connectivity at 2 to 59 Hz in pain-related cortical regions, which are the bilateral anterior cingulate cortex (ACC), medial orbitofrontal (MOF) cortex, lateral orbitofrontal (LOF) cortex, insula cortex, primary somatosensory cortex (SI), primary motor cortex (MI), and posterior cingulate cortex (PCC). The mechanical punctate pain threshold (MPPT) was obtained at the supraorbital area (the first branch of the trigeminal nerve dermatome, V1) and the forearm (the first thoracic nerve dermatome, T1) and further correlated with MEG measures.

Results

The MPPT is inversely correlated with the resting-state relative powers of gamma oscillation in healthy individuals (all corrected P < 0.05). Specifically, inverse correlation was noted between the MPPT at V1 and gamma powers in the bilateral insula (r = − 0.592 [left] and − 0.529 [right]), PCC (r = − 0.619 and − 0.541) and MI (r = − 0.497 and − 0.549) and between the MPPT at T1 and powers in the left PCC (r = − 0.561) and bilateral MI (r = − 0.509 and − 0.520). Furthermore, resting-state functional connectivity at the delta to beta bands, especially between frontal (MOF, ACC, LOF, and MI), parietal (PCC), and sensorimotor (bilateral SI and MI) regions, showed a positive correlation with the MPPT at V1 and T1 (all corrected P < 0.05). By contrast, in patients with EM, the MPPT was not associated with resting-state cortical activities.

Conclusions

Pain sensitivity in healthy individuals is associated with the resting-state gamma oscillation and functional connectivity in pain-related cortical regions. Further studies must be conducted in a large population to confirm whether resting-state cortical activities can be an objective measurement of pain sensitivity in individuals without clinical pain.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10194-020-01200-8.

Neural Oscillations: Understanding a Neural Code of Pain

Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.

Frequency-Specific Resting Connectome in Bipolar Disorder: An MEG Study

BACKGROUND

Bipolar disorder (BD) is a serious psychiatric disorder that is associated with a high suicide rate, and for which no clinical biomarker has yet been identified. To address this issue, we investigated the use of magnetoencephalography (MEG) as a new prospective tool. MEG has been used to evaluate frequency-specific connectivity between brain regions; however, no previous study has investigated the frequency-specific resting-state connectome in patients with BD. This resting-state MEG study explored the oscillatory representations of clinical symptoms of BD via graph analysis.

METHODS

In this prospective case-control study, 17 patients with BD and 22 healthy controls (HCs) underwent resting-state MEG and evaluations for depressive and manic symptoms. After estimating the source current distribution, orthogonalized envelope correlations between multiple brain regions were evaluated for each frequency band. We separated regions-of-interest into seven left and right network modules, including the frontoparietal network (FPN), limbic network (LM), salience network (SAL), and default mode network (DMN), to compare the intra- and inter-community edges between the two groups.

RESULTS

In the BD group, we found significantly increased inter-community edges of the right LM-right DMN at the gamma band, and decreased inter-community edges of the right SAL-right FPN at the delta band and the left SAL-right SAL at the theta band. Intra-community edges in the left LM at the high beta band were significantly higher in the BD group than in the HC group. The number of connections in the left LM at the high beta band showed positive correlations with the subjective and objective depressive symptoms in the BD group.

CONCLUSION

We introduced graph theory into resting-state MEG studies to investigate the functional connectivity in patients with BD. To the best of our knowledge, this is a novel approach that may be beneficial in the diagnosis of BD. This study describes the spontaneous oscillatory brain networks that compensate for the time-domain issues associated with functional magnetic resonance imaging. These findings suggest that the connectivity of the LM at the beta band may be a good objective biological biomarker of the depressive symptoms associated with BD.

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.

Visual input drives increased occipital responsiveness and harmonized oscillations in multiple cortical areas in migraineurs

Migraineurs are hypersensitive for most sensory domains like visual, auditory or somatosensory processing even outside of attacks. This behavioral peculiarity is mirrored by findings of cortical hyper-responsivity already in the interictal state. Using repetitive visual stimulation to elicit steady state visually evoked potentials (SSVEP) in 30 interictal episodic migraineurs and 30 controls we show hyper-responsivity of the visual cortex in the migraineurs. Additionally, the occipital regions were remarkably stronger coupled to the temporal, premotor and the anterior cingulate cortex than in headache free controls. These data suggest harmonized oscillations of different cortical areas as a response to visual input which might be driven by the cuneus. Furthermore, the increased coupling is modulated by the current state of the migraine cycle as the coupling was significantly stronger in patients with longer interictal periods.

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Migraineurs visual cortex compared to controls is hyper-responsiveness in response to repetitive visual stimulation.

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The hyper-responsiveness is stronger coupled to temporal, premotor and anterior cingulate cortex than in controls.

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This increased coupling is modulated by the current state of the migraine cycle.

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Our data suggest that visual input in migraineurs leads to harmonized oscillations of multiple cortical areas.

Chronic stress increases pain sensitivity via activation of the rACC-BLA pathway in rats

Exposure to chronic stress can produce maladaptive neurobiological changes in pathways associated with pain processing, which may cause stress-induced hyperalgesia (SIH). However, the underlying mechanisms still remain largely unknown. In previous studies, we have reported that the amygdala is involved in chronic forced swim (FS) stress-induced depressive-like behaviors and the exacerbation of neuropathic pain in rats, of which, the basolateral amygdala (BLA) and the central nucleus of the amygdala (CeA) are shown to play important roles in the integration of affective and sensory information including nociception. Here, using in vivo multichannel recording from rostal anterior cingulate cortex (rACC) and BLA, we found that chronic FS stress (CFSS) could increase the pain sensitivity of rats in response to low intensity innoxious stimuli (LIS) and high intensity noxious stimuli (HNS) imposed upon the hindpaw, validating the occurrence of SIH in stressed rats. Moreover, we discovered that CFSS not only induced an increased activity of rACC neuronal population but also produced an augmented field potential power (FPP) of rACC local field potential (LFP), especially in low frequency theta band as well as in high frequency low gamma band ranges, both at the baseline state and under LIS and HNS conditions. In addition, by using a cross-correlation method and a partial directed coherence (PDC) algorithm to analyze the LFP oscillating activity in rACC and BLA, we demonstrated that CFSS could substantially promote the synchronization between rACC and BLA regions, and also enhanced the neural information flow from rACC to BLA. We conclude that exposure of chronic FS stress to rats could result in an increased activity of rACC neuronal population and promote the functional connectivity and the synchronization between rACC and BLA regions, and also enhance the pain-related neural information flow from rACC to BLA, which likely underlie the pathogenesis of SIH.

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.

Research: Use of Dry Electroencephalogram and Support Vector for Objective Pain Assessment

The reliability of normal gel-based electrode electroencephalogram (EEG) for measuring pain has been validated. To date, however, few documented trials have used dry EEG for pain quantification. The primary goal of this study was to objectively quantify pain using dry EEG in conjunction with a support vector machine (SVM). SVMs have been proven accurate for classifying pain intensity. The authors believe that EEG combined with an SVM could increase the statistical power of pain assessment. Currently, clinicians primarily rely on verbal (i.e., subjective) reports for assessing pain; therefore, the research described here could offer a method to objectively monitor pain, eliminate observer error, and individualize treatment.

Cortical nociceptive processes are reduced by visual alpha-band entrainment in the human brain

BACKGROUND

Acute noxious stimuli induce a suppression of cortical alpha activity, yet little is known about whether increasing alpha activity affects the processing of noxious stimuli. We have previously shown that visual alpha stimulation reduces experimental pain. Here, we demonstrate that increasing alpha power causes a reciprocal suppression of acute nociceptive processing.

METHODS

We attempted to increase cortical alpha activity through visual entrainment at 8 Hz, 10 Hz and 12 Hz to investigate the influence on the electrophysiological pain response. Moderately painful laser-heat stimuli were delivered following 10 minutes of visual entrainment across the alpha range.

RESULTS

Alpha power increased significantly relative to the 1 Hz control condition following 8 Hz and 10 Hz visual stimulation. Significant reductions in the P2 peak amplitude of the laser-evoked potential were found following visual entrainment at 10 Hz; the frequency stimulation resulting in the largest reduction in pain perception. Source analysis revealed that, following the 10 Hz stimulation, sources of increased alpha power and decreased nociceptive processing overlapped in precuneus and posterior cingulate cortex, with further reductions in nociceptive processing in insula cortex.

CONCLUSIONS

As far as we are aware, this is the first study to provide direct evidence that experimental induction of increased alpha power suppresses the cortical processing of acute pain.

SIGNIFICANCE

While it is known that visual stimulation can increase the brain's oscillatory alpha rhythms, here, we show that this increase in alpha power occurs alongside reduced cortical processing of nociception, as measured with EEG. This establishes an objective marker of alpha entrainment-based analgesia that may be useful in the development of neuromodulatory treatments for clinical pain.

Altered insula-default mode network connectivity in fibromyalgia: a resting-state magnetoencephalographic study

Background

Fibromyalgia (FM) is a disabling chronic pain syndrome with unknown pathophysiology. Functional magnetic resonance imaging studies on FM have suggested altered brain connectivity between the insula and the default mode network (DMN). However, this connectivity change has not been characterized through direct neural signals for exploring the embedded spectrotemporal features and the pertinent clinical relevance.

Methods

We recorded the resting-state magnetoencephalographic activities of 28 patients with FM and 28 age- and sex-matched controls, and analyzed the source-based functional connectivity between the insula and the DMN at 1–40 Hz by using the minimum norm estimates and imaginary coherence methods. We also measured the connectivity between the DMN and the primary visual (V1) and somatosensory (S1) cortices as intrapatient negative controls. Connectivity measurement was further correlated with the clinical parameters of FM.

Results

Compared with the controls, patients with FM reported more tender points (15.2±2.0 vs. 5.9±3.7) and higher total tenderness score (TTS; 29.1±7.0 vs. 7.7±5.5; both p < 0.001); they also had decreased insula–DMN connectivity at the theta band (4–8 Hz; left, p = 0.007; right, p = 0.035), but displayed unchanged V1–DMN and S1–DMN connectivity (p > 0.05). When patients with FM and the controls were combined together, the insula-DMN theta connectivity was negatively correlated with the number of tender points (left insula, r = −0.428, p = 0.001; right insula, r = −0.4, p = 0.002) and TTS score (left insula, r = −0.429, p = 0.001; right insula, r = −0.389, p = 0.003). Furthermore, in patients with FM, the right insula–DMN connectivity at the beta band (13–25 Hz) was negatively correlated with the number of tender points (r = −0.532, p = 0.004) and TTS (r = −0.428, p = 0.023), and the bilateral insula–DMN connectivity at the delta band (1–4 Hz) was negatively correlated with FM Symptom Severity (left: r = −0.423, p = 0.025; right: r = −0.437, p = 0.020) and functional disability (Fibromyalgia Impact Questionnaire; left: r = −0.415, p = 0.028; right: r = −0.374, p = 0.050).

Conclusions

We confirmed the frequency-specific reorganization of the insula–DMN connectivity in FM. The clinical relevance of this connectivity change may warrant future studies to elucidate its causal relationship and potential as a neurological signature for FM.

Electronic supplementary material

The online version of this article (doi:10.1186/s10194-017-0799-x) contains supplementary material, which is available to authorized users.

Brain Rhythms of Pain

Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain.

Psychophysically-anchored, Robust Thresholding in Studying Pain-related Lateralization of Oscillatory Prestimulus Activity

In perceptual studies, it is often important to objectively assess the equality of delivered stimulation across participants or to quantify the intra-individual sensation magnitude that is evoked by stimulation over multiple trials. This requires a robust mapping of stimulus magnitude to perceived intensity and is commonly achieved by psychophysical estimation methods such as the staircase procedure. Newer, more efficient procedures like the QUEST algorithm fit a psychophysical function to the data in real time while at the same time maximizing the efficiency of data collection. A robust estimate of the threshold intensity between painful and nonpainful perceptions can then be used to reduce the influence of variations in sensory input in subsequent analyses of oscillatory brain activity. By stimulating at a constant threshold intensity determined by an adaptive estimation procedure, the variance in the ratings can be directly attributed to perceptual processes. Oscillatory activity can then be contrasted between "pain" and "no-pain" trials directly, yielding activity that closely relates to perceptual classification processes in nociception.

The Neural Code for Pain: From Single-Cell Electrophysiology to the Dynamic Pain Connectome

Pain occurs in time. In naturalistic settings, pain perception is sometimes stable but often varies in intensity and quality over the course of seconds, minutes, and days. A principal aim in classic electrophysiology studies of pain was to uncover a neural code based on the temporal patterns of single neuron firing. In contrast, modern neuroimaging studies have placed emphasis on uncovering the spatial pattern of brain activity (or “map”) that may reflect the pain experience. However, in the emerging field of connectomics, communication within and among brain networks is characterized as intrinsically dynamic on multiple time scales. In this review, we revisit the single-cell electrophysiological evidence for a nociceptive neural code and consider how those findings relate to recent advances in understanding systems-level dynamic processes that suggest the existence of a “dynamic pain connectome” as a spatiotemporal physiological signature of pain. We explore how spontaneous activity fluctuations in this dynamic system shape, and are shaped by, acute and chronic pain experiences and individual differences in those experiences. Highlighting the temporal dimension of pain, we aim to move pain theory beyond the concept of a static neurosignature and toward an ethologically relevant account of naturalistic dynamics.