Resting State Functional Connectivity in Cluster Headache

Overview

Cluster headache is a highly disabling primary headache disorder, characterized by severe, excruciating, recurrent unilateral headache attacks. Typically, attacks' onset displays a circadian rhythm, and bout recurrence happens in a circannual fashion. Notably, the mechanisms underlying the shift between the remission phase and cluster bout are poorly understood. Thus, the investigators aim to study brain connectivity in episodic cluster headache patients. Additionally, an explorative analysis of functional connectivity in chronic cluster headache patients will be performed.

Electroencephalogram (EEG) is widely available as a powerful mean to non-invasively study brain connectivity. High density EEG (HD-EEG), enables to record electrical brain activity with high temporal and spatial resolution. Through the analysis of brain oscillations across different frequency bands (from alpha to delta), it can evaluate sensory, pain processing and information integration, thus detecting potential markers or predictors for therapeutic interventions. Previous neurophysiological studies focused on EEG and to assess functional connectivity or spectral analysis in migraine patients, with no data in cluster headache. Conventional studies found higher slow wave activity (predominantly theta) in the inter-ictal phase and higher excitability in the visual cortex during visual aura. In 2016 a resting state study showed a predominance of low frequency bands in the ictal phase. The interictal and ictal phases patients also presented a diffuse lower coherence, suggesting low functional connectivity. Furthermore, an altered spatial connectivity for lower alpha-band activities was found in the interictal phases during sensory stimulation by means of HD-EEG, suggesting a thalamocortical dysrhythmia. The primary aim of the study is to evaluate changes in functional connectivity in episodic cluster headache patients, comparing the active phase with the remission phase. Additionally, an explorative analysis of functional connectivity in chronic cluster headache patients will be performed. Study design: Episodic cluster headache patients (eCH) will be evaluated in two separate timepoints: during the active phase (T0), defined as at least one week of active bout, and in remission phase (T1), defined as at leat 14 days without headache and without any ongoing preventive medication. During each visit, clinical data will be collected, and an HD-EEG will be performed. Chronic cluster headache patients (cCH) will be evaluated in a single timepoint, and healthy controls will undergo HD-EEG registration once. HD-EEG registration: Participants will perform 4 recordings (6 minutes each) in resting-state condition, 2 with opened eyes, and 2 with closed eyes, in a randomized order. The investigators will analyze the resting state FC among six resting state networks (Default mode network, Dorsal attention network, Ventral attention network, Language network , Somatomotor network and Visual network) in the following frequency bands: alfa 8-12 Hz, beta 13-30 Hz, gamma 31-80 Hz, theta 4-7 Hz. delta 1-3 Hz. Acquisition parameters will be: High-Pass: 0.5 Hz; Low-Pass: 100 Hz; Notch: 50 Hz. For analysis of HD-EEG data, a tailored analysis pipe-line that was previously developed and validated to reconstruct neural sources from cortical/subcortical gray matter will be performed. EEG signals will be band-pass filtered (1-80 Hz) and down-sampled at 250 Hz. Biological artifacts will be rejected using Independent Component Analysis (ICA). EEG signals will be referenced with a customized version of the Reference Electrode Standardization Technique (REST). A matrix will estimate the relationship between the measured scalp potentials and the dipoles corresponding to brain sources. Sources reconstruction will be performed with the exact low-resolution brain electromagnetic tomography (eLORETA) algorithm Statistical plan: The sample size was computed with the freeware online platform www.openepi.com. As there are no previous studies on HD-EEG functional connectivity in cluster headache, our sample size analysis was based on the work of Bjork (Bjork et al., 2009). A difference between groups in the theta relative power band equal to 0.04 (±0.04) will be considered as clinically meaningful. Considering a two-tailed t-test for the comparison with confidence interval 95%; power: 80%, the minimum suggested sample size was 20 subjects for group. A preliminary normality analysis will be performed to decide whether to use parametric or non-parametric methods, through Shapiro Wilk test. Numerical variables will be described as mean and standard deviation (or median and quartiles if appropriate), categorical variables as raw numbers and percentages. Functional connectivity analyses will be conducted for separate bands and eyes closed registration.