Quantitative electroencephalogram analysis of frontal cortex functional changes in patients with migraine

Brain health in diverse settings: How age, demographics and cognition shape brain function

Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.

Preliminary efficacy of aerobic training among university students with migraine symptoms: Study protocol for a pilot randomized controlled trial

BACKGROUND

Migraine is a primary neurological headache. Treatment of this condition includes medications; however, these medications, when given for a longer duration, can have side effects. If migraine is left untreated or undiagnosed, it is reported that around 2.5% of individuals with migraine may develop to have a chronic condition. This study aims to analyse the preliminary effectiveness of aerobic training on migraine pain level, sleep quality, quality of life, and resting-state brain waves among university students with migraine symptoms.

METHODOLOGY

88 university students with migraine symptoms are the target participants. 4 of 5 on the Migraine Screen Questionnaire, 5 of 7 on the International Classification of Headache Disorders 3rd edition (ICHD-3), and both genders aged 18-40 years will be included. The participants with a score of more than or equal to 5 on the visual aura rating scale, diagnosed with a secondary headache, pregnancy, medication for neurological and cardiorespiratory conditions, and unwilling to participate will be excluded. Based on the disability questionnaire, the participants will be randomly assigned to either of the three groups. The primary outcome is resting-state electroencephalography (EEG) brain, and the secondary outcomes are sleep quality, quality of life, and migraine pain level. The post-test assessments will be performed at week 6.

RESULT

After the primary EEG analysis using MATLAB, the amplitude, frequency, frequency band ratio, and power spectrum density will be analysed. Mixed design analysis and intention-to-treat analysis will be used to assess the efficacy of aerobic training.

DISCUSSION

Migraines can be unpredictable, sometimes occurring without symptoms. If underdiagnosed or over-looked, it encompasses a serious of long-term effects. Hence with appropriate intervention, the symptoms can be prevented from worsening. But there is an unmet need for evidence-based non-pharmacological approaches to complement pharmacotherapy in migraine prevention. Moreover, an exercise intervention may be more suitable for people with migraine considering their tendency toward inactivity. Although some studies developed exercise programs for untrained patients with migraine, the outcome was primarily in terms of exercise capacity rather than the primary characteristics and secondary brain wave/ sleep quality changes, indicating the need for this study.

Application of EEG in migraine

Migraine is a common disease of the nervous system that seriously affects the quality of life of patients and constitutes a growing global health crisis. However, many limitations and challenges exist in migraine research, including the unclear etiology and the lack of specific biomarkers for diagnosis and treatment. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity. With the updating of data processing and analysis methods in recent years, EEG offers the possibility to explore altered brain functional patterns and brain network characteristics of migraines in depth. In this paper, we provide an overview of the methodology that can be applied to EEG data processing and analysis and a narrative review of EEG-based migraine-related research. To better understand the neural changes of migraine or to provide a new idea for the clinical diagnosis and treatment of migraine in the future, we discussed the study of EEG and evoked potential in migraine, compared the relevant research methods, and put forwards suggestions for future migraine EEG studies.

Resting State Electrophysiological Cortical Activity: A Brain Signature Candidate for Patients with Migraine

PURPOSE OF REVIEW

Studies on event-related evoked potentials have indicated that altered cortical processing of sensory stimuli is associated with migraine. However, the results depend on the experimental method and patients. Electrophysiology of resting state cortical activity has revealed compelling results regarding the pathophysiology of migraine. This review summarized the available information related to patients with episodic and chronic migraine to determine whether certain features can be used as signatures for migraine.

RECENT FINDINGS

A recent study examined differences in resting state functional connectivity among the pain-related regions and revealed that beta connectivity was attenuated in migraine and that altered connectivity in the anterior cingulate cortex was linked to migraine chronification. These findings suggested that chronification leads to neuroplasticity in the pain areas of higher-level processing rather than in areas involved in basic sensory discrimination (i.e., primary and secondary somatosensory areas). Another study discovered that the betweenness centrality of delta band in right precuneus was significantly lower in those with longer history of migraine. Electroencephalogram may also predict the treatment outcomes in patients with chronic migraine that those with lower pre-treatment occipital alpha power tend to show greater reduction in headache frequency. Studies on resting state activity have yielded convincing findings regarding aberrant oscillatory power and functional connectivity in relation to migraine, thus contributing to identifying brain signatures for migraine. The role of such assessment in precision medicine should be further investigated.