Magnetoencephalography studies in migraine and headache disorders: A systematic review

BACKGROUND

Understanding the neural mechanisms underlying migraine and other primary headache disorders is critical for the development of long-term cures. Magnetoencephalography (MEG), an imaging modality that measures neuronal currents and cortical excitability with high temporal and superior spatial resolution, has been increasingly used in neurological research. Initial MEG studies showed promise in directly recording cortical spreading depression-a cortical correlate of migraine with aura. However, lately MEG technology has highly evolved with greater potential to reveal underlying pathophysiology of migraine and primary headache disorders, and aid in the identification of biomarkers.

OBJECTIVE

To systematically review the use of MEG in migraine and other primary headache disorders and summarize findings.

METHODS

We conducted a systematic search and selection of MEG studies in migraine and primary headache disorders from inception until June 8, 2023, in Medline, Embase, Cochrane, and Scopus databases. Peer-reviewed English articles reporting the use of MEG for clinical or research purposes in migraine and primary headache disorders were selected.

RESULTS

We found 560 articles and included 38 in this review after screening. Twelve studies investigated resting-state, while others investigated a sensory modality using an evoked or event-related paradigm with a total of 35 cohort and 3 case studies. Thirty-two studies focused exclusively on migraine, while the rest reported other primary headache disorders.

CONCLUSION

The findings show an evolution of MEG from a 7- to a 306-channel system and analysis evolving from sensor-level evoked responses to more advanced source-level connectivity measures. A relatively few MEG studies portrayed migraine and primary headache disorders as a sensory abnormality, especially of the visual system. We found heterogeneity in the datasets, data reporting standards (due to constantly evolving MEG technology and analysis methods), and patient characteristics. Studies were inadequately powered and there was no evidence of blinding procedures to avoid selection bias in case-control studies, which could have led to false-positive findings. More studies are needed to investigate the affective-cognitive aspects that exacerbate pain and disability in migraine and primary headache disorders.

Altered brainstem-cortex activation and interaction in migraine patients: somatosensory evoked EEG responses with machine learning

BACKGROUND

To gain a comprehensive understanding of the altered sensory processing in patients with migraine, in this study, we developed an electroencephalography (EEG) protocol for examining brainstem and cortical responses to sensory stimulation. Furthermore, machine learning techniques were employed to identify neural signatures from evoked brainstem-cortex activation and their interactions, facilitating the identification of the presence and subtype of migraine.

METHODS

This study analysed 1,000-epoch-averaged somatosensory evoked responses from 342 participants, comprising 113 healthy controls (HCs), 106 patients with chronic migraine (CM), and 123 patients with episodic migraine (EM). Activation amplitude and effective connectivity were obtained using weighted minimum norm estimates with spectral Granger causality analysis. This study used support vector machine algorithms to develop classification models; multimodal data (amplitude, connectivity, and scores of psychometric assessments) were applied to assess the reliability and generalisability of the identification results from the classification models.

RESULTS

The findings revealed that patients with migraine exhibited reduced amplitudes for responses in both the brainstem and cortical regions and increased effective connectivity between these regions in the gamma and high-gamma frequency bands. The classification model with characteristic features performed well in distinguishing patients with CM from HCs, achieving an accuracy of 81.8% and an area under the curve (AUC) of 0.86 during training and an accuracy of 76.2% and an AUC of 0.89 during independent testing. Similarly, the model effectively identified patients with EM, with an accuracy of 77.5% and an AUC of 0.84 during training and an accuracy of 87% and an AUC of 0.88 during independent testing. Additionally, the model successfully differentiated patients with CM from patients with EM, with an accuracy of 70.5% and an AUC of 0.73 during training and an accuracy of 72.7% and an AUC of 0.74 during independent testing.

CONCLUSION

Altered brainstem-cortex activation and interaction are characteristic of the abnormal sensory processing in migraine. Combining evoked activity analysis with machine learning offers a reliable and generalisable tool for identifying patients with migraine and for assessing the severity of their condition. Thus, this approach is an effective and rapid diagnostic tool for clinicians.

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.

Decoding pain through facial expressions: a study of patients with migraine

BACKGROUND

The present study used the Facial Action Coding System (FACS) to analyse changes in facial activities in individuals with migraine during resting conditions to determine the potential of facial expressions to convey information about pain during headache episodes.

METHODS

Facial activity was recorded in calm and resting conditions by using a camera for both healthy controls (HC) and patients with episodic migraine (EM) and chronic migraine (CM). The FACS was employed to analyse the collected facial images, and intensity scores for each of the 20 action units (AUs) representing expressions were generated. The groups and headache pain conditions were then examined for each AU.

RESULTS

The study involved 304 participants, that is, 46 HCs, 174 patients with EM, and 84 patients with CM. Elevated headache pain levels were associated with increased lid tightener activity and reduced mouth stretch. In the CM group, moderate to severe headache attacks exhibited decreased activation in the mouth stretch, alongside increased activation in the lid tightener, nose wrinkle, and cheek raiser, compared to mild headache attacks (all corrected p < 0.05). Notably, lid tightener activation was positively correlated with the Numeric Rating Scale (NRS) level of headache (p = 0.012). Moreover, the lip corner depressor was identified to be indicative of emotional depression severity (p < 0.001).

CONCLUSION

Facial expressions, particularly lid tightener actions, served as inherent indicators of headache intensity in individuals with migraine, even during resting conditions. This indicates that the proposed approach holds promise for providing a subjective evaluation of headaches, offering the benefits of real-time assessment and convenience for patients with migraine.

Translation, cross-cultural adaptation and measurement proprieties of the German version of the Allodynia Symptom Checklist (ASC-12)

BACKGROUND

Cutaneous allodynia is highly prevalent among migraineurs and is associated with a poor prognosis. The Allodynia Symptom Checklist (ASC-12) is a comprehensive questionnaire to identify the presence and severity of allodynia. Our aim was to translate and adapt the ASC-12 to German and evaluate its measurement properties.

METHODS

Following the COSMIN guidelines, 80 migraine patients were enrolled in the study to evaluate the stages of translation (n=30) and measurement propriety assessment (n=50), respectively. After reaching a final version, the German ASC-12 was assessed for structural validity, internal consistency, test-retest reliability, construct validity and absolute agreement, using mechanical and thermal pain thresholds as reference method.

RESULTS

The German version of the ASC-12 presented an adequate structural validity compatible with the original version of the questionnaire. Its internal consistency ranged from 0.70 to 0.80 considering the total score and the thermic, static and dynamic mechanic subdomains. The total score presented excellent reliability (ICC: 0.85) with a standard error of measurement of 1.15 points and smallest detectable change of 3.40 points. ASC-12 total scores were correlated with headache intensity (r=0.38, p=0.004), headache disability (r=0.37, p=0.004) and cold pain thresholds (r=0.28, p=0.025). The thermic allodynia ASC-12 scores were correlated with cold (r=0.36, p=0.005) and heat (r=-0.30, p=0.010) pain thresholds, while the static mechanical allodynia ASC-12 scores correlated with mechanical pain threshold (r=0.29, p=0.019) and with mechanical pain sensitivity (r=0.24 to 0.28, p< 0.045). Despite no significant bias between methods, quantitative sensory testing (QST) results and ASC-12 scores tend to disagree.

CONCLUSION

The German version of the ASC-12 is available for research and clinical settings and presented adequate measurement proprieties, as the original version. Despite the correlation between the ASC-12 and QST, one method cannot be replaced by the other.

Characteristic oscillatory brain networks for predicting patients with chronic migraine

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

Repeated exposure to aversive sensations differentially affects neural gating and bodily perception

Habituation to bodily sensations is highly relevant for the experience of chronic bodily symptoms, but the neural mechanisms behind diminished habituation are currently unclear. One potentially relevant mechanism is neural gating (NG), reflected as the short-term suppression of cortical responses to redundant stimuli. We investigated the effects of repeated exposure to aversive sensations on NG and subjective perception in 91 healthy adults, by measuring their NG of respiratory and electrocutaneous stimuli using electroencephalography during two sessions separated by one week, in addition to their self-report of intensity and unpleasantness of the sensations. To test for intra- and cross-modal effects, 1/2 participants returned three times in the intervening week to experience additional aversive respiratory stimulation, while the other 1/2 received aversive electrocutaneous stimulation. Participants reported lower unpleasantness of all sensations in the final session (intra- and cross-modal habituation). NG was improved for respiratory sensations only in the group receiving additional respiratory stimulation (intra-modal habituation). We found no relationships between NG and perceptual habituation, adding to the mixed results on the relevance of NG to perceptual changes in healthy adults. Future research with clinical populations and different methods is encouraged to further clarify the mechanisms behind neural gating and diminished symptom habituation.

Levcromakalim provokes an acute rapid-onset migraine-like phenotype without inducing cortical spreading depolarization

BACKGROUND

Migraine headache attacks and accompanying sensory augmentation can be induced by several agents including levcromakalim (LVC), that is also capable of provoking aura-like symptoms in migraineurs. We investigated whether single LVC injection causes acute migraine-like phenotype in rats and induces/modulates cortical spreading depolarization (CSD), a rodent model of migraine aura.

METHODS

Wistar rats were administered LVC (1 mg/kg, i.p.) and compared to control (CTRL, vehicle, i.p.) and nitroglycerin (NTG, 10 mg/kg, i.p.) groups. Von Frey filaments were used to examine the periorbital and hind paw mechanical allodynia. Dark-light box (DLB), elevated plus maze (EPM), and open field arena (OFA) were used to evaluate light sensitivity and anxiety-related behaviors. The effects of LVC on CSD parameters, somatosensory evoked potentials, and baseline dural EEG (electroencephalography) were investigated. Possible CSD-induced c-fos expression was studied with Western Blot. Blood-brain barrier integrity in cortex was examined with Evans blue assay.

RESULTS

LVC and NTG administration robustly reduced periorbital mechanical thresholds in rats and induced anxiety-like behaviors and photophobia within 30 and 120 min, respectively. LVC induced migraine-like phenotype recovered in 2 h while NTG group did not fully recover before 4 h. Both LVC and NTG did not provoke DC (direct current) shift, EEG alterations or cortical c-fos expression characteristic to CSD. LVC did not induce de novo CSD and affect KCl (potassium chloride)-induced CSD parameters except for an increase in propagation failure. However, NTG significantly increased both CSD susceptibility and propagation failure. Somatosensory evoked potential (SSEP) configurations were not altered in both LVC and NTG groups, but SSEP latencies were prolonged after CSD. Acute LVC or NTG injection did not increase cortical BBB permeability.

CONCLUSIONS

Single LVC administration induced the fastest manifestation and recovery of acute migraine-like phenotype which was not mediated by CSD waves in the cerebral cortex. We suppose LVC triggered rapid-onset migraine-like symptoms are probably related to functional alterations in the trigeminal nociceptive system and K⁺ channel opening properties of LVC. Understanding the neurobiological mechanisms of this nociceptive window, may provide a novel target in migraine treatment.

Cortical and thalamic modulation of auditory gating in the posterior parietal cortex of awake mice

Auditory gating (AG) is an adaptive mechanism for filtering out redundant acoustic stimuli to protect the brain against information overload. AG deficits have been found in many mental illnesses, including schizophrenia (SZ). However, the neural correlates of AG remain poorly understood. Here, we found that the posterior parietal cortex (PPC) shows an intermediate level of AG in auditory thalamocortical circuits, with a laminar profile in which the strongest AG is in the granular layer. Furthermore, AG of the PPC was decreased and increased by optogenetic inactivation of the medial dorsal thalamic nucleus (MD) and auditory cortex (AC), respectively. Optogenetically activating the axons from the MD and AC drove neural activities in the PPC without an obvious AG. These results indicated that AG in the PPC is determined by the integrated signal streams from the MD and AC in a bottom-up manner. We also found that a mouse model of SZ (postnatal administration of noncompetitive N-methyl-d-aspartate receptor antagonist) presented an AG deficit in the PPC, which may be inherited from the dysfunction of MD. Together, our findings reveal a neural circuit underlying the generation of AG in the PPC and its involvement in the AG deficit of SZ.

What has neurophysiology revealed about migraine and chronic migraine?

Since the first electroencephalographic recordings obtained by Golla and Winter in 1959, researchers have used a variety of neurophysiological techniques to determine the mechanisms underlying recurrent migraine attacks. Neurophysiological methods have shown that the brain during the interictal phase of an episodic migraine is characterized by a general hyperresponsiveness to sensory stimuli, a malfunction of the monoaminergic brainstem circuits, and by functional alterations of the thalamus and thalamocortical loop. All of these alterations vary plastically during the phases of the migraine cycle and interictally with the days following the attack. Both episodic migraineurs recorded during an attack and chronic migraineurs are characterized by a general increase in the cortical amplitude response to peripheral sensory stimuli; this is an electrophysiological hallmark of a central sensitization process that is further reinforced through medication overuse. Considering the large-scale functional involvement and the main roles played by the brainstem-thalamo-cortical network in selection, elaboration, and learning of relevant sensory information, future research should move from searching for one specific primary site of dysfunction at the macroscopic level, to the chronic, probably genetically determined, molecular dysfunctions at the synaptic level, responsible for short- and long-term learning mechanisms.

A study on alterations in functional activity in migraineurs during the interictal period

Migraine is a recurrent disease in which the cumulative effect of repeated pain attacks over a long period of time causes changes in brain function. Although there are some studies focusing on the interictal period of migraine, the reproducibility of these results is poor. Therefore, we intend to use a data-driven functional connectivity (FC) approach to probe the alterations in cerebral functional activity during the interictal period, as well as underlying no-task mechanisms of inducing headache attack in migraine patients. In the current research, 24 episodic migraine patients and 23 healthy controls (HCs) were recruited. By analyzing the magnitude of regional homogeneity (ReHo) and low-frequency fractional fluctuation (fALFF), We identified alterations in spontaneous brain activity in migraineurs, including the bilateral middle frontal gyrus, left postcentral, and right lingual gyrus. Thereafter such abnormalities were selected as seeds (ROIs) for FC analysis to further explore the underlying changes between ROIs and the whole brain areas. Compared with HCs, FC between the right middle frontal gyrus with the left precuneus cortex, and bilateral thalamus were enhanced in migraineurs. In addition, increased FC has been showed between the left postcentral gyrus with the bilateral thalamus. Furthermore, negative correlation existed between fALFF values of the left middle frontal gyrus and the pain intensity of migraine attacks (r = -0.4578, p = 0.0245). In summary, abnormal FC between the bilateral thalamus and right middle frontal gyrus, or the left retrocentral gyrus may occur between attacks in migraineurs, which may be the basis for sensory integration and pain regulation dysfunction. Thus, this could become a promising biomarker for the early diagnosis and evaluation of migraine in the interictal period, and provide a novel view for further investigation of the pathogenesis and etiology of recurrent migraine.

Resting-state magnetoencephalographic oscillatory connectivity to identify patients with chronic migraine using machine learning

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

Resting-state occipital alpha power is associated with treatment outcome in patients with chronic migraine

ABSTRACT

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

Dynamic brainstem and somatosensory cortical excitability during migraine cycles

Abstract

Background

Migraine has complex pathophysiological characteristics and episodic attacks. To decipher the cyclic neurophysiological features of migraine attacks, in this study, we compared neuronal excitability in the brainstem and primary somatosensory (S1) region between migraine phases for 30 consecutive days in two patients with episodic migraine.

Methods

Both patients underwent EEG recording of event-related potentials with the somatosensory and paired-pulse paradigms for 30 consecutive days. The migraine cycle was divided into the following phases: 24–48 h before headache onset (Pre2), within 24 h before headache onset (Pre1), during the migraine attack (Ictal), within 24 h after headache offset (Post1), and the interval of ˃48 h between the last and next headache phase (Interictal). The normalised current intensity in the brainstem and S1 and gating ratio in the S1 were recorded and examined.

Results

Six migraine cycles (three for each patient) were analysed. In both patients, the somatosensory excitability in the brainstem (peaking at 12–14 ms after stimulation) and S1 (peaking at 18–19 ms after stimulation) peaked in the Pre1 phase. The S1 inhibitory capability was higher in the Ictal phase than in the Pre1 phase.

Conclusion

This study demonstrates that migraine is a cyclic excitatory disorder and that the neural substrates involved include the somatosensory system, starting in the brainstem and spanning subsequently to the S1 before the migraine occurs. Further investigations with larger sample sizes are warranted.

Cortical mechanisms in migraine

Migraine is the second most prevalent disorder in the world; yet, its underlying mechanisms are still poorly understood. Cumulative studies have revealed pivotal roles of cerebral cortex in the initiation, propagation, and termination of migraine attacks as well as the interictal phase. Investigation of basic mechanisms of the cortex in migraine not only brings insight into the underlying pathophysiology but also provides the basis for designing novel treatments. We aim to summarize the current research literatures and give a brief overview of the cortex and its role in migraine, including the basic structure and function; structural, functional, and biochemical neuroimaging; migraine-related genes; and theories related to cortex in migraine pathophysiology. We propose that long-term plasticity of synaptic transmission in the cortex encodes migraine.

Sodium valproate improves sensorimotor gating deficit induced by sleep deprivation at low doses

Background/aim

Sleep deprivation disrupts prepulse inhibition of acoustic startle reflex and can be used to mimic psychosis in ex- perimental animals. On the other hand, it is also a model for other disorders of sensory processing, including migraine. This study aims to assess the effects of sodium valproate, a drug that is used in a variety of neuropsychiatric disorders, on normal and disrupted sensorimotor gating in rats.

Materials and methods

Sixty-two Wistar albino rats were randomly distributed into 8 groups. Subchronic and intraperitoneal sodium valproate were administrated to the sleep-deprived and nonsleep-deprived rats by either 50–100 or 200 mg/kg/day. Prepulse inhibition test and locomotor activity test were performed. Sleep deprivation induced by the modified multiple platform method.

Results

Sleep deprivation impaired prepulse inhibition, decreased startle amplitude, and increased locomotor activity. Sodium valpro- ate did not significantly alter prepulse inhibition and locomotor activity in nonsleep-deprived and sleep-deprived groups. On the other hand, all doses decreased locomotor activity in drug-treated groups, and low dose improved sensorimotor gating and startle amplitude after sleep deprivation.

Conclusion

Low-dose sodium valproate improves sleep deprivation-disrupted sensorimotor gating, and this finding may rationalize the use of sodium valproate in psychotic states and other sensory processing disorders. Dose-dependent effects of sodium valproate on sensorimotor gating should be investigated in detail.

Somatosensory Gating Responses Are Associated with Prognosis in Patients with Migraine

Sensory gating, a habituation-related but more basic protective mechanism against brain sensory overload, is altered in patients with migraine and linked to headache severity. This study investigated whether somatosensory (SI) gating responses determined 3-months treatment outcomes in patients with episodic migraine (EM) and chronic migraine (CM). A 306-channel magnetoencephalography (MEG) with paired-pulse stimulation paradigm was used to record their neuromagnetic responses. To calculate the peak amplitude and latency and compute the gating ratios (second vs. first amplitude), the first and second responses to the paired stimuli from the primary somatosensory cortex were obtained. All patients were assigned to subgroups labeled good or poor according to their headache frequency at baseline compared with at the third month of treatment. The gating ratio in the CM group (n = 37) was significantly different between those identified as good and poor (p = 0.009). In the EM group (n = 30), the latency in the second response differed by treatment outcomes (p = 0.007). In the receiver operating characteristic analysis, the areas under the curve for the CM and EM groups were 0.737 and 0.761, respectively. Somatosensory gating responses were associated with treatment outcomes in patients with migraine; future studies with large patient samples are warranted.

Brain Excitability in Tension-Type Headache: a Separate Entity from Migraine?

PURPOSE OF REVIEW

Tension-type headache is often regarded as the "normal" headache due to its high prevalence and mild disability in contrast with migraine. Clinically, both headaches are common comorbidities to each other. To date there has been many studies linked migraine to a brain excitability disorder. This review summarized earlier studies on brain excitability of TTH and discuss if TTH is a separate clinical entity from migraine as suggested by the diagnostic criteria.

RECENT FINDINGS

A recent magnetoencephalographic study from our group enrolled patients with "strict-criteria" TTH (i.e., absence of any migraine characteristics and associated symptoms) to compare the somatosensory excitability with patients with migraine and controls. This study provided evidence that TTH and migraine differ in excitability profiles and the measurement of preactivation excitability was able to discriminate TTH from migraine. Earlier studies on brain excitability of TTH yielded negative findings or a common change shared with migraine. Future studies using strict diagnostic criteria to avoid the unwanted interference from migraine comorbidity may help decipher the "true" pathophysiology of TTH, which may pave the way to a TTH-specific brain signature and treatment.

How does the brain change in chronic migraine? Developing disease biomarkers

BACKGROUND

Validated chronic migraine biomarkers could improve diagnostic, prognostic, and predictive abilities for clinicians and researchers, as well as increase knowledge on migraine pathophysiology.

OBJECTIVE

The objective of this narrative review is to summarise and interpret the published literature regarding the current state of development of chronic migraine biomarkers.

FINDINGS

Data from functional and structural imaging, neurophysiological, and biochemical studies have been utilised towards the development of chronic migraine biomarkers. These biomarkers could contribute to chronic migraine classification/diagnosis, prognosticating patient outcomes, predicting response to treatment, and measuring treatment responses early after initiation. Results show promise for using measures of brain structure and function, evoked potentials, and sensory neuropeptide concentrations for the development of chronic migraine biomarkers, yet further optimisation and validation are still required.

CONCLUSIONS

Imaging, neurophysiological, and biochemical changes that occur with the progression from episodic to chronic migraine could be utilised for developing chronic migraine biomarkers that might assist with diagnosis, prognosticating individual patient outcomes, and predicting responses to migraine therapies. Ultimately, validated biomarkers could move us closer to being able to practice precision medicine in the field and thus improve patient care.

Neuromagnetic Amygdala Response to Pain-Related Fear as a Brain Signature of Fibromyalgia

INTRODUCTION

Fibromyalgia (FM) is a chronic pain condition characterized by impaired emotional regulation. This study explored the brain response to pain-related fear as a potential brain signature of FM.

METHODS

We used a conditioned fear task and magnetoencephalography to record pain-related fear responses in patients with FM. Two blocks of 30 fear responses were collected to compute the response strength in the first block and the strength difference between the first and second blocks (fear habituation). These measurements were investigated for their clinical relevance and compared with measurements obtained from healthy controls and patients with chronic migraine (CM), a different chronic pain condition often comorbid with FM.

RESULTS

Pain-related fear clearly activated the bilateral amygdala and anterior insula in patients with FM (n = 52), patients with CM (n = 50), and the controls (n = 30); the response strength in the first block was consistent across groups. However, fear habituation in the right amygdala decreased in the FM group (vs. CM and control groups, both p ≤ 0.001, no difference between CM and control groups). At the 3-month follow-up, the patients with FM reporting < 30% improvement in pain severity (n = 15) after pregabalin treatment exhibited lower fear habituation in the left amygdala at baseline (vs. ≥ 30% improvement, n = 22, p = 0.019). Receiver operating characteristic analysis confirmed that amygdala fear habituation is a suitable predictor of diagnosis and treatment outcomes of FM (area under the curve > 0.7).

CONCLUSIONS

Amygdala activation to pain-related fear is maladaptive and linked to treatment outcomes in patients with FM. Because the aberrant amygdala response was not observed in the CM group, this response is a potential brain signature of FM.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier, NCT02747940.

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.

Current understanding of cortical structure and function in migraine

OBJECTIVE

To review and discuss the literature on the role of cortical structure and function in migraine.

DISCUSSION

Structural and functional findings suggest that changes in cortical morphology and function contribute to migraine susceptibility by modulating dynamic interactions across cortical and subcortical networks. The involvement of the cortex in migraine is well established for the aura phase with the underlying phenomenon of cortical spreading depolarization, while increasing evidence suggests an important role for the cortex in perception of head pain and associated sensations. As part of trigeminovascular pain and sensory processing networks, cortical dysfunction is likely to also affect initiation of attacks.

CONCLUSION

Morphological and functional changes identified across cortical regions are likely to contribute to initiation, cyclic recurrence and chronification of migraine. Future studies are needed to address underlying mechanisms, including interactions between cortical and subcortical regions and effects of internal (e.g. genetics, gender) and external (e.g. sensory inputs, stress) modifying factors, as well as possible clinical and therapeutic implications.

Abnormal functional connectivity under somatosensory stimulation in migraine: a multi-frequency magnetoencephalography study

BACKGROUND

Although altered neural networks have been demonstrated in recent MEG (magnetoencephalography) research in migraine patients during resting state, it is unknown whether this alteration can be detected in task-related networks. The present study aimed to investigate the abnormalities of the frequency-specific somatosensory-related network in migraine patients by using MEG.

METHODS

Twenty-two migraineurs in the interictal phase and twenty-two sex- and age-matched healthy volunteers were studied using a whole-head magnetoencephalography (MEG) system. Electrical stimuli were delivered alternately to the median nerve on the right wrists of all subjects. MEG data were analyzed in a frequency range of 1-1000 Hz in multiple bands.

RESULTS

The brain network patterns revealed that the patients with migraine exhibited remarkably increased functional connectivity in the high-frequency (250-1000 Hz) band between the sensory cortex and the frontal lobe. The results of quantitative analysis of graph theory showed that the patients had (1) an increased degree of connectivity in the theta (4-8 Hz), beta (13-30 Hz) and gamma (30-80 Hz) bands; (2) an increased connectivity strength in the beta (13-30 Hz) and gamma (30-80 Hz) bands; (3) an increased path length in the beta (13-30 Hz), gamma (30-80 Hz) and ripple (80-250 Hz) bands; and (4) an increased clustering coefficient in the theta (4-8 Hz), beta (13-30 Hz) and gamma (30-80 Hz) bands.

CONCLUSIONS

The results indicate that migraine is associated with aberrant connections from the somatosensory cortex to the frontal lobe. The frequency-specific increases in connectivity in terms of strength, path length and clustering coefficients support the notion that migraineurs have elevated cortical networks. This alteration in functional connectivity may be involved in somatosensory processing in migraine patients and may contribute to understanding migraine pathophysiology and to providing convincing evidence for a spatially targeted migraine therapy.