Dynamic brainstem and somatosensory cortical excitability during migraine cycles

Region-specific changes in brain glutamate and gamma-aminobutyric acid across the migraine attack in children and adolescents

ABSTRACT

In patients with migraine, an excitation-inhibition imbalance that fluctuates relative to attack onset has been proposed to contribute to the underlying pathophysiology of migraine, but this has yet to be explored in children and adolescents. This prospective, observational, cohort study examined glutamate and gamma-aminobutyric acid (GABA) levels across the phases of a migraine attack and interictally in children and adolescents using magnetic resonance spectroscopy. Macromolecule-suppressed GABA (sensorimotor cortex and thalamus) and glutamate (occipital cortex, sensorimotor cortex, and thalamus) were measured in children and adolescents (10-17 years) with a migraine diagnosis with or without aura 4 times over 2 weeks. Linear mixed-effects models examined changes in glutamate and GABA during the 72 hours leading up to, and after the onset of an attack. We found significant region-specific changes in glutamate and GABA. Specifically, sensorimotor GABA significantly increased leading up to the headache phase, whereas glutamate significantly decreased following the headache onset in the occipital cortex and the thalamus. Post hoc analyses examined the 24 hours leading up to or following the onset of the headache phase. In the 24 hours before the headache onset, sensorimotor glutamate, occipital glutamate, and thalamic GABA decreased. In the 24 hours post headache onset, sensorimotor glutamate continued to decrease. Our results suggest changes in glutamate and GABA that are consistent with the thalamocortical dysrhythmia hypothesis. These findings provide insight into developmental migraine pathophysiology and may open future avenues for treatment targets specific to children and adolescents.

[Characterization of a German cohort with visual snow syndrome]

BACKGROUND

Visual snow is a disorder of visual perception that is manifested as a constant flickering or "TV-like" noise in the entire visual field. Visual snow syndrome (VSS) describes a combination with other additional visual symptoms, such as sensitivity to light, afterimages, night blindness and entoptic phenomena. Cases of VS have been described in the literature using a wide variety of terms, often misunderstood as persistent migraine aura. Established diagnostic criteria have existed for more than 10 years now; however, the pathophysiology is still incompletely understood. The exact prevalence also remains unknown and high numbers of unreported cases are suspected. This is the first detailed description of a cohort of VSS patients from Germany.

METHODS

Patients with VSS from several studies conducted at our center were pooled and retrospectively evaluated with respect to demographic, epidemiological and clinical data.

RESULTS

In this study 66 patients with VSS were included (age 31.3 ± 8.3 years, 30 women). The most commonly associated visual symptoms were photophobia (67%) and afterimages (65%). Of the patients 36 (54%) had comorbid migraine of whom 25 (70%) had migraine with aura, 26 (39%) reported depressive symptoms and 32 (48%) symptoms of an anxiety disorder. Tinnitus was reported by 32 (48%) patients.

CONCLUSION

The characteristics of the German cohort described here are similar to other international descriptions. Due to the frequent psychological comorbidity there is still a risk of psychosomatic stigmatization.

Hallmarks of primary headache: part 1 - migraine

BACKGROUND AND AIM

Migraine is a common disabling conditions which, globally, affects 15.2% of the population. It is the second cause of health loss in terms of years lived with disability, the first among women. Despite being so common, it is poorly recognised and too often undertreated. Specialty centres and neurologists with specific expertise on headache disorders have the knowledge to provide specific care: however, those who do not regularly treat patients with migraine will benefit from a synopsis on the most relevant and updated information about this condition. This paper presents a comprehensive view on the hallmarks of migraine, from genetics and diagnostic markers, up to treatments and societal impact, and reports the elements that identify migraine specific features.

MAIN RESULTS

The most relevant hallmark of migraine is that it has common and individual features together. Besides the known clinical manifestations, migraine presentation is heterogeneous with regard to frequency of attacks, presence of aura, response to therapy, associated comorbidities or other symptoms, which likely reflect migraine heterogeneous genetic and molecular basis. The amount of therapies for acute and for prophylactic treatment is really wide, and one of the difficulties is with finding the best treatment for the single patient. In addition to this, patients carry out different daily life activities, and might show lifestyle habits which are not entirely adequate to manage migraine day by day. Education will be more and more important as a strategy of brain health promotion, because this will enable reducing the amount of subjects needing specialty care, thus leaving it to those who require it in reason of refractory condition or presence of comorbidities.

CONCLUSIONS

Recognizing the hallmarks of migraine and the features of single patients enables prescribing specific pharmacological and non-pharmacological treatments. Medical research on headaches today particularly suffers from the syndrome of single-disease approach, but it is important to have a cross-sectional and joint vision with other close specialties, in order to treat our patients with a comprehensive approach that a heterogeneous condition like migraine requires.

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.

Insights from triggers and prodromal symptoms on how migraine attacks start: The threshold hypothesis

BACKGROUND

The prodrome or premonitory phase is the initial phase of a migraine attack, and it is considered as a symptomatic phase in which prodromal symptoms may occur. There is evidence that attacks start 24-48 hours before the headache phase. Individuals with migraine also report several potential triggers for their attacks, which may be mistaken for premonitory symptoms and hinder migraine research.

METHODS

This review aims to summarize published studies that describe contributions to understanding the fine difference between prodromal/premonitory symptoms and triggers, give insights for research, and propose a way forward to study these phenomena. We finally aim to formulate a theory to unify migraine triggers and prodromal symptoms. For this purpose, a comprehensive narrative review of the published literature on clinical, neurophysiological and imaging evidence on migraine prodromal symptoms and triggers was conducted using the PubMed database.

RESULTS

Brain activity and network connectivity changes occur during the prodromal phase. These changes give rise to prodromal/premonitory symptoms in some individuals, which may be falsely interpreted as triggers at the same time as representing the early manifestation of the beginning of the attack. By contrast, certain migraine triggers, such as stress, hormone changes or sleep deprivation, acting as a catalyst in reducing the migraine threshold, might facilitate these changes and increase the chances of a migraine attack. Migraine triggers and prodromal/premonitory symptoms can be confused and have an intertwined relationship with the hypothalamus as the central hub for integrating external and internal body signals.

CONCLUSIONS

Differentiating migraine triggers and prodromal symptoms is crucial for shedding light on migraine pathophysiology and improve migraine management.

EEG Changes in Migraine-Can EEG Help to Monitor Attack Susceptibility?

Migraine is a highly prevalent brain condition with paroxysmal changes in brain excitability believed to contribute to the initiation of an attack. The attacks and their unpredictability have a major impact on the lives of patients. Clinical management is hampered by a lack of reliable predictors for upcoming attacks, which may help in understanding pathophysiological mechanisms to identify new treatment targets that may be positioned between the acute and preventive possibilities that are currently available. So far, a large range of studies using conventional hospital-based EEG recordings have provided contradictory results, with indications of both cortical hyper- as well as hypo-excitability. These heterogeneous findings may largely be because most studies were cross-sectional in design, providing only a snapshot in time of a patient's brain state without capturing day-to-day fluctuations. The scope of this narrative review is to (i) reflect on current knowledge on EEG changes in the context of migraine, the attack cycle, and underlying pathophysiology; (ii) consider the effects of migraine treatment on EEG features; (iii) outline challenges and opportunities in using EEG for monitoring attack susceptibility; and (iv) discuss future applications of EEG in home-based settings.

Potential of focal cortical dysplasia in migraine pathogenesis

Focal cortical dysplasias are abnormalities of the cerebral cortex associated with an elevated risk of neurological disturbances. Cortical spreading depolarization/depression is a correlate of migraine aura/headache and a trigger of migraine pain mechanisms. However, cortical spreading depolarization/depression is associated with cortical structural changes, which can be classified as transient focal cortical dysplasias. Migraine is reported to be associated with changes in various brain structures, including malformations and lesions in the cortex. Such malformations may be related to focal cortical dysplasias, which may play a role in migraine pathogenesis. Results obtained so far suggest that focal cortical dysplasias may belong to the causes and consequences of migraine. Certain focal cortical dysplasias may lower the threshold of cortical excitability and facilitate the action of migraine triggers. Migraine prevalence in epileptic patients is higher than in the general population, and focal cortical dysplasias are an established element of epilepsy pathogenesis. In this narrative/hypothesis review, we present mainly information on cortical structural changes in migraine, but studies on structural alterations in deep white matter and other brain regions are also presented. We develop the hypothesis that focal cortical dysplasias may be causally associated with migraine and link pathogeneses of migraine and epilepsy.

Bi-sinusoidal light stimulation reveals an enhanced response power and reduced phase coherence at the visual cortex in migraine

Introduction

Migraine is associated with enhanced visual sensitivity during and outside attacks. Processing of visual information is a highly non-linear process involving complex interactions across (sub)cortical networks. In this exploratory study, we combined electroencephalography with bi-sinusoidal light stimulation to assess non-linear features of visual processing in participants with migraine.

Methods

Twenty participants with migraine (10 with aura, 10 without aura) and ten non-headache controls were measured (outside attacks). Participants received bi-sinusoidal 13 + 23 Hz red light visual stimulation. Electroencephalography spectral power and multi-spectral phase coherence were compared between groups at the driving stimulation frequencies together with multiples and combinations of these frequencies (harmonic and intermodulation frequencies) caused by non-linearities.

Results

Only at the driving frequency of 13 Hz higher spectral power was found in migraine with aura participants compared with those with migraine without aura and controls. Differences in phase coherence were present for 2nd, 4th, and 5th-order non-linearities in those with migraine (migraine with and without aura) compared with controls. Bi-sinusoidal light stimulation revealed evident non-linearities in the brain's electroencephalography response up to the 5th order with reduced phase coherence for higher order interactions in interictal participants with migraine.

Discussion

Insight into interictal non-linear visual processing may help understand brain dynamics underlying migraine attack susceptibility. Future research is needed to determine the clinical value of the results.

Electrophysiological findings in migraine may reflect abnormal synaptic plasticity mechanisms: A narrative review

BACKGROUND

The cyclical brain disorder of sensory processing accompanying migraine phases lacks an explanatory unified theory.

METHODS

We searched Pubmed for non-invasive neurophysiological studies on migraine and related conditions using transcranial magnetic stimulation, electroencephalography, visual and somatosensory evoked potentials. We summarized the literature, reviewed methods, and proposed a unified theory for the pathophysiology of electrophysiological abnormalities underlying migraine recurrence.

RESULTS

All electrophysiological modalities have determined specific changes in brain dynamics across the different phases of the migraine cycle. Transcranial magnetic stimulation studies show unbalanced recruitment of inhibitory and excitatory circuits, more consistently in aura, which ultimately results in a substantially distorted response to neuromodulation protocols. Electroencephalography investigations highlight a steady pattern of reduced alpha and increased slow rhythms, largely located in posterior brain regions, which tends to normalize closer to the attacks. Finally, non-painful evoked potentials suggest dysfunctions in habituation mechanisms of sensory cortices that revert during ictal phases.

CONCLUSION

Electrophysiology shows dynamic and recurrent functional alterations within the brainstem-thalamus-cortex loop varies continuously and recurrently in migraineurs. Given the central role of these structures in the selection, elaboration, and learning of sensory information, these functional alterations suggest chronic, probably genetically determined dysfunctions of the synaptic short- and long-term learning mechanisms.

Migraine: from pathophysiology to treatment

Migraine is an extremely disabling, common neurological disorder characterized by a complex neurobiology, involving a series of central and peripheral nervous system areas and networks. A growing increase in the understanding of migraine pathophysiology in recent years has facilitated translation of that knowledge into novel treatments, which are currently becoming available to patients in many parts of the world and are substantially changing the clinical approach to the disease. In the first part of this review, we will provide an up to date overview of migraine pathophysiology by analyzing the anatomy and function of the main regions involved in the disease, focusing on how these give rise to the plethora of symptoms characterizing the attacks and overall disease. The second part of the paper will discuss the novel therapeutic agents that have emerged for the treatment of migraine, including molecules targeting calcitonin gene-related peptide (gepants and monoclonal antibodies), serotonin 5-HT_1F receptor agonists (ditans) and non-invasive neuromodulation, as well as providing a brief overview of new evidence for classic migraine treatments.

Insufficient sleep may alter cortical excitability near the migraine attack: A blinded TMS crossover study

BACKGROUND

Migraine is a brain disorder with a multifaceted and unexplained association to sleep. Brain excitability likely changes periodically throughout the migraine cycle. In this study we examine the effect of insufficient sleep on neuronal excitability during the course of the migraine cycle.

METHODS

We examined 54 migraine patients after two nights of eight-hour habitual sleep and two nights of four-hour restricted sleep in a randomised, blinded crossover study. We performed transcranial magnetic stimulation and measured cortical silent period, short- and long-interval intracortical inhibition, intracortical facilitation and short-latency afferent inhibition. We analysed how responses changed before and after attacks with linear mixed models.

RESULTS

Short- interval intracortical inhibition was more reduced after sleep restriction compared to habitual sleep the shorter the time that had elapsed since the attack (p = 0.041), and specifically in the postictal phase (p = 0.013). Long-interval intracortical inhibition was more increased after sleep restriction with time closer before the attack (p = 0.006), and specifically in the preictal phase (p = 0.034). Short-latency afferent inhibition was more decreased after sleep restriction with time closer to the start of the attack (p = 0.026).

CONCLUSION

Insufficient sleep in the period leading up to a migraine attack may cause dysfunction in cortical GABAergic inhibition. The results also suggest that migraine patients may have increased need for sufficient sleep during a migraine attack to maintain normal neurological function after the attack.

Acceptability and Tolerability of Extended Reality Relaxation Training with and without Wearable Neurofeedback in Pediatric Migraine

Objective. To determine the acceptability of using extended reality (XR) relaxation training as a preventive treatment for pediatric migraine. Methods. Youths aged 10-17 years old with migraine were recruited from a specialty headache clinic and completed baseline measures evaluating their vestibular symptoms and attitudes about technology. The patients were then instructed in three XR-based relaxation training conditions (fully immersive virtual reality with and without neurofeedback, and augmented reality with neurofeedback), in counterbalanced order, and completed acceptability and side effect questionnaires after each. The patients also took XR equipment home for one week to use for relaxation practice and again completed the measures about their experience. The acceptability and side effect data were compared against predetermined acceptable thresholds and were evaluated for their association with the participant characteristics. Results. The aggregate acceptability questionnaire scores exceeded our minimum threshold of 3.5/5, with the two fully immersive virtual reality conditions preferred over augmented reality for relaxation training (z = -3.02, p = 0.003, and z = -2.31, p = 0.02). The endorsed side effects were rated by all but one participant as mild, with vertigo being the most common. The acceptability ratings were not reliably associated with age, sex, typical hours per day of technology use, or technology attitudes, but were inversely related to the side effect scores. Conclusions. The preliminary data on acceptability and tolerability of immersive XR technology for relaxation training among youths with migraine supports further intervention development work.

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.

The Therapeutic Role of Ketogenic Diet in Neurological Disorders

The ketogenic diet (KD) is a high-fat, low-carbohydrate and adequate-protein diet that has gained popularity in recent years in the context of neurological diseases (NDs). The complexity of the pathogenesis of these diseases means that effective forms of treatment are still lacking. Conventional therapy is often associated with increasing tolerance and/or drug resistance. Consequently, more effective therapeutic strategies are being sought to increase the effectiveness of available forms of therapy and improve the quality of life of patients. For the moment, it seems that KD can provide therapeutic benefits in patients with neurological problems by effectively controlling the balance between pro- and antioxidant processes and pro-excitatory and inhibitory neurotransmitters, and modulating inflammation or changing the composition of the gut microbiome. In this review we evaluated the potential therapeutic efficacy of KD in epilepsy, depression, migraine, Alzheimer’s disease and Parkinson’s disease. In our opinion, KD should be considered as an adjuvant therapeutic option for some neurological diseases.