Headache-related circuits and high frequencies evaluated by EEG, MRI, PET as potential biomarkers to differentiate chronic and episodic migraine: Evidence from a systematic review

Study selection and characteristics

The digital database search resulted in a total of 106 records (Fig. 1a). Two additional articles were identified through a manual search of the reference lists of articles and reviews. These 108 articles were assessed for duplicates, retrieving 52 of them for the subsequent screening process. The articles were then screened by reading the title, abstract and keywords (when available). Twenty-one articles do not meet the eligibility criteria (Table 2) after this first initial screening, thus, 31 documents including original studies and review articles were selected for an in-deep evaluation (i.e., an in-depth reading of the full text). Concurrently, only 4 studies from the 80 identified RCTs were eligible for evaluation. After a second screening process, a comprehensive review of the 35 documents according to PRISMA reporting guidelines and following the eligibility criteria were conducted. Thus, 24 studies were finally included in this systematic review since 11 did not meet all requirements.

Fig. 1figure 1

a Flowchart of the study selection process as carried out in accordance with the PRISMA guidelines. b Distribution of included publications over time, from year 2000 onwards. c Number of included publications by recording type (e.g., EEG, MEG, fMRI, or PET). Note that Pan and colleagues [14] included both EEG and fMRI recordings in their study. For that reason, panel (a) shows 24 studies but panels (b) and (c) indicates 25 recording modalities

No studies were found that meet inclusion criteria until 2011 (see Fig. 1b). More than half of the studies were published in the last 5 years. Table 3 summarizes the main data obtained from the 24 selected studies. Of them, 22 were original articles, while 2 were review articles [14, 15]. Results of the original articles were based on EEG (3 studies) [16,17,18], MEG (6 studies) [19,20,21,22,23,24], fMRI (10 studies) [25,26,27,28,29,30,31,32,33,34], and PET (3 studies) [35,36,37] (see Fig. 1c). Noteworthy, none of the 24 included studies come from RCTs or used fNIRS recordings.

Table 3 Overview of included studies. For each recording modality, more recent articles appear first in the tableEvidence from magnetic and electric cerebral activity (M/EEG)

Nine original papers and two review articles [14,15,16,17,18,19,20,21,22,23,24] investigated, directly or indirectly, the differences in neural patterns between CM and EM from an electrophysiological or magnetophysiological perspective. The statistical power of the studies was diverse, with studies using populations ranging from 25 subjects (15 CM and 10 remitted EM) [22] to over 300 subjects (24 healthy controls, 48 CM and 232 EM) [18].

Two of these studies were review articles [14, 15]. In the most recent of them [14], authors investigated resting-state activity as a potential brain signature for migraine patients (both for CM and EM). Although the search for differences between CM and EM was not the objective of the study, the authors described and summarized very interesting findings on characteristic patterns in migraine both from the purely oscillatory point of view and from the more advanced perspective of the analysis of functional connectivity (i.e., non-directional as opposed to effective connectivity) as well as its characterization using parameters derived from graph theory. In addition, they highlighted a previous study [19] (we further analyse it latter) in which the node degree (sum of the connectivity of a certain node with all the others in the network) showed significant differences between CM and EM in primary and secondary somatosensory cortices, insula, anterior cingulate cortex (ACC) and medial frontal cortex.

In the other review article [15], the authors shed light on the underlying mechanisms that associate sleep disturbances and chronic headaches. Interestingly, a relationship between an increase in slow-wave sleep accompanied by a reduction in beta activity during migraine attacks was described. According to the authors, this could suggest that the observed changes in sleep dysregulation reflect the process of headache chronification (i.e., the transition from EM to CM), rather than simply reflecting differences between the ictal and interictal states of migraine.

In the most recent of the original articles on EEG, Gomez-Pilar and colleagues [16] performed a spectral analysis to find spectral bands of interest in 39 controls, 42 CM and 45 EM. Using bootstrap and other robust statistical techniques, the authors showed a specific frequency band around high beta in which the CM group statistically differed from the EM group during resting state. Although the differences are widespread on the scalp, they seem to be more concentrated in the left hemisphere.

The other two EEG studies used visual evoked potentials (VEPs) [17] or steady-state visual evoked potentials (SSVEPs) [18] to compare CM and EM groups. In both cases, significant differences were found in high frequency bands: in the beta band in the SSVEPs study (occipital region, photic driving power response at 20 Hz) and in the gamma band in the VEPs study. It should be noted, however, that the differences in the gamma band seem to be due to differences of the power line artifact around 60 Hz, which should be removed in spectral studies [38,39,40]. As the authors indicated in the limitations of their study, this removal was not performed, so the results should be interpreted with caution.

Only one of the 6 MEG studies used recordings during resting state [20]. As mentioned in the review study [14], the connectivity in different areas was analysed by node degree. The connectivity was calculated using the imaginary part of the coherence, which reduces volume conduction effects [41]. The beta band showed significant differences between CM and EM in various brain regions after source analysis, but ACC was the region that showed the greatest between-group differences.

The 5 remaining MEG studies showed heterogeneous results. Two of them did not report significant differences between the two groups using time–frequency analysis of emotional stimulation responses [21] o temporal analysis of visual evoked fields (VEF) [23]. Hsiao and colleagues [20] reported a similar somatosensory gating response associated with the treatment outcomes both in CM and EM groups. However, in this case, authors did report between-group differences in the amplitude of the somatosensory evoked field (characterized by a peak around 50 ms) after 3-month treatment. Finally, two studies from Chen and colleagues [22, 24] found differences in the temporal analysis of VEFs. Using a well-designed block-based procedure, the authors studied patients’ habituation to stimuli by measuring the percent change in P100m amplitude between the first block and subsequent blocks. Statistically significant differences were found between the interictal EM group and the CM patients. Since the percentage change was greater in EM, this indicated a habituation of the CM group compared to a potentiation in EM patients.

Together, these M/EEG studies account for between-group differences frequently based on the early response in evoked potentials (i.e., fast frequency responses) or on alterations in beta band in resting state studies.

Evidence from fMRI studies

fMRI is the brain activity acquisition modality with the largest number of studies for the comparison between CM and EM (see Fig. 1c). Although the temporal resolution of this technique is several orders of magnitude lower than EEG or MEG, its spatial resolution allows a fine inspection of the specific activity of different brain regions. Given the somewhat obvious relationship one might expect between migraine and pain-related circuits [42, 43], or the less obvious relationship with emotion regulation [44, 45], fMRI facilitates researchers to directly study these networks. Thereby, after the screening, ten studies using the blood oxygenation level dependent (BOLD) activity from fMRI recordings to distinguish between CM and EM were selected for the systematic review.

Three studies [27, 28, 31] showed differences between CM and EM in functional connectivity in the hypothalamus, this being the most reproducible result. Chen and colleagues [27] analysed structural and functional connectivity in a conventional resting state design. Being its anatomical results the most significant, in particular the proposal of the volume of the hypothalamus as a marker of CM, they also showed an interesting finding on the functional level. Specifically, authors reported statistically significant differences between CM and EM in functional connectivity between the hypothalamus and the right medial orbital gyrus (MorG). According to the authors, the increased connectivity in CM may reveal the role of the anterior hypothalamus in altered sleep responses or emotional and execution dysfunction in CM. The results reported by Lerebours et al. [28] agreed with these findings. They found a significantly increased connectivity between the anterior hypothalamus and the spinal trigeminal nucleus in CM in comparison with EM. This highlights the major role of the anterior hypothalamus in migraine, particularly its relationship with medication overuse. In the third study whose findings involved the hypothalamus (the first published of the three) [31], the authors used four different stimuli in a pseudorandomized order. During the administration of gaseous ammonia (as a painful stimulus), activity within the right anterior hypothalamus was significantly higher in CM group than in EM group during ictal stage. Together, these studies speak for the importance of the anterior hypothalamus in attack generation and migraine chronification (mainly via medication overuse).

The findings of the other studies might seem, at first glance, heterogeneous. However, all of them involved, in a direct or indirect way, neural pathways related to pain circuits and/or emotion processing. A clear example is the study from Chen and colleagues [34], in which the authors studied the functional connectivity of the marginal division of neostriatum, involved in the modulation of pain. A decreased connectivity in CM and CM with medication-overuse headache was found in this region as compared to EM group. Also, in the study of Imai et al. [30], an increased functional connectivity between ACC and the right occipital gyrus was reported in a set of 31 CM patients as compared to 31 EM patients. It is noteworthy that the ACC is probably the cortical area that has been most frequently linked to pain [46]; specifically, it appears to be involved in the emotional reaction to pain, rather than to the perception of pain itself [47]. As ACC, amygdala is associated with the emotional-affective dimension of pain [48]. Interestingly, CM patients show increased functional connectivity between amygdala and inferior temporal gyrus (ITG) and orbitofrontal gyrus (OFG) compared to EM, as reported by [32], shedding light on the role of the amygdala in the neurolimbic pain-modulating in the migraine.

Another study [33] from Hubbard and colleagues showed decreased functional connectivity in CM between primary somatosensory cortex (S1) and both lateral occipital cortex (LOC) and dorsomedial prefrontal cortex (DMPFC). As the authors stated, S1 has a relevant role in processing the sensory-discriminative components of pain. In line with these findings, Chen and colleagues [26] used the regional homology analysis method (ReHo) to analyse the BOLD fluctuations. Although, unfortunately, no comparison was reported between infrequent EM and CM, a large variety of brain areas showed significant differences between frequent EM and CM (see Table 6 in [26] for details). The areas exhibiting the higher statistically significant differences were the left and right precentral gyrus, i.e., the S1, supporting the results of Hubbard and colleagues [33].

In the study of Dai and colleagues [25], an increased functional connectivity between habenula and salience network was exhibited in CM relative to EM group. Habenula brings input from the hippocampus and basal ganglia structures, among others [49], while salience network (primarily composed of the anterior insula and dorsal ACC) collaborates in the integration of emotional and cognitive information [50]. Finally, in the study of Bogdanov et al. [29], the analysis of the salience network also shows interesting results. Along showing differences in the motor cortex and superior temporal sulcus, authors reported significant differences between CM and interictal EM in salience network regions, such as the insula, the thalamus, the ACC and the S1.

All together, these studies support the involvement of neural circuits and brain networks that process, directly or indirectly, the stimuli and responses related to pain and emotion. The differences found between CM and EM using fMRI seem to be robust, converging across conditions (resting state vs. stimuli processing), migraine stage (ictal, interictal) in a variety of designs and analysis (functional connectivity, neural activation or ReHo).

Evidence from PET studies

Only three studies [35,36,37] analysed the differences in metabolic activity between EM and CM via PET neuroimaging. Metabolic differences between both migraine subgroups were only found in terms of µ-opioid (µOR) availability [36], but not when measuring 5-HT [37] or fluorodeoxyglucose [35] levels.

Jassar et al. [36] used [11C]carfentanil to measure µ-opioid (µOR) availability in 7 CM patients, 8 EM patients, and 7 healthy controls (HC). CM showed significantly lower µOR non-displaceable binding potentials than HC in thalamus and left caudate. This ictal µOR dysfunction of CM extended to the limbic system, i.e., right parahippocampal region and right amygdala, in CM relative to EM. Additional analyses suggested that the increased µOR receptor-mediated neurotransmission in limbic system of CM is highly modulated by the attack frequency, pain severity and sensitivity. These results are in line with the evidence from fMRI studies, since this µOR dysfunction is involved in pain networks.

On the contrary, negative results were found by Deen and colleagues [37] in the evaluation of brain serotonin 5-HT levels after injection of [11C]SB207145 (a specific 5-HT4 receptor radioligand) in 16 CM patients, 15 EM patients, and 16 HC subjects. Although CM group exhibited significantly higher 5-HT levels than HC group, no significant differences between CM and EM levels and no association between this metric and number of monthly migraine days were found. Authors concluded that high brain 5-HT levels may be a trait marker of the migraine brain rather than a risk factor for conversion from EM to CM.

In line with the previous study, Torres-Ferrus and colleagues [35] used [18F]FDG radiotracer to perform interictal PET and MRI scans to 7 MC patients, 8 EM patients, and 11 HC subjects. The authors, however, did not find statistically significant differences between CM and EM groups. CM showed significant frontotemporal hypometabolism than HC, while EM presented intermediate values. Only the bilateral temporal lobe in EM yielded significant differences as compared to HC. However, as mentioned, no significant differences between CM and EM were found in terms of cerebral metabolism. Interestingly, no significant differences were found when compared both migraine groups as a whole (i.e., CM and EM together) versus HC group.

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