The primary brain dysfunctions leading to the onset of a migraine attack remain largely unknown. Other important open questions concern the mechanisms of initiation, continuation, and termination of migraine pain, and the changes in brain function underlying migraine transformation. Brief trains of high-frequency repetitive transcranial magnetic stimulation (rTMS), when applied to the primary motor cortex at suprathreshold intensity (⩾120% of resting motor threshold [RMT]), elicit in healthy subjects a progressive, glutamate-dependent facilitation of the motor evoked potentials (MEP). Conversely, in conditions of increased cortical excitability, the rTMS trains induce inhibitory MEP responses likely mediated by cortical homeostatic mechanisms. We enrolled 66 migraine-without-aura patients, 48 migraine-with-aura patients, 14 patients affected by chronic migraine (CM), and 20 healthy controls. We assessed motor cortical response to 5-Hz rTMS trains of 10 stimuli given at 120% RMT. Patients with episodic migraine were studied in different phases of the migraine cycle: interictal, preictal, ictal, and postictal states. Results showed a facilitatory MEP response during the trains in patients evaluated in the preictal phase, whereas inhibitory responses were observed during and after a migraine attack, as well as in CM patients. In the interictal phase, different responses were observed, depending on attack frequency: facilitation in patients with low and inhibition in those with high attack recurrence. Our findings suggest that changes in cortical excitability and fluctuations in the threshold for inhibitory metaplasticity underlie the migraine attack recurrence, and could be involved in the process of migraine transformation.

Objective: Sound-induced flash illusions depend on visual cortical excitability. In this study, we explored whether sound-induced flash illusions are perceived differently in migraine, a condition associated with pathologic cortical hyperexcitability. Methods: Sound-induced flash illusions were examined in 59 migraine patients (mean age = 32 ± 16 years; 36 females), 32 without aura and 27 with aura, and in 24 healthy controls (mean age = 42 ± 17 years; 16 females). Patients were studied during attacks and interictally. Visual stimuli (flashes) accompanied by sounds (beeps) were presented in different combinations: a single flash with multiple beeps was given to induce the perception of multiple flashes (“fission” illusion), and multiple flashes with a single beep were used to reduce the number of perceived flashes (“fusion” illusion). Results: For migraineurs, the fission illusion was reduced, especially during the attack, and almost abolished when a single flash was combined with 2 beeps (except for those without aura tested interictally); the fusion illusion was less consistently reported in both migraine groups, but not completely disrupted. Conclusions: Results from this study add novel clues to our understanding of visual cortex hyperexcitability in migraine, especially migraine with aura. Furthermore, these analyses underscore how pathologic changes in cortical excitability affect multisensory interactions. Cross-modal illusions represent a valid tool for exploration of functional connectivity between sensory areas, which likely has an important role in the pathophysiology of migraine.

Migraine is a burdensome neurological disorder that still lacks clear and easily accessible diagnostic biomarkers. Furthermore, a straightforward pathway is hard to find for migraineurs’ management, so the search for response predictors has become urgent. Nowadays, artificial intelligence (AI) has pervaded almost every aspect of our lives, and medicine has not been missed. Its applications are nearly limitless, and the ability to use machine learning approaches has given researchers a chance to give huge amounts of data new insights. When it comes to migraine, AI may play a fundamental role, helping clinicians and patients in many ways. For example, AI-based models can increase diagnostic accuracy, especially for non-headache specialists, and may help in correctly classifying the different groups of patients. Moreover, AI models analysing brain imaging studies reveal promising results in identifying disease biomarkers. Regarding migraine management, AI applications showed value in identifying outcome measures, the best treatment choices, and therapy response prediction. In the present review, the authors introduce the various and most recent clinical applications of AI regarding migraine.

Congenital insensitivity to pain (CIP) is a rare autosomal recessive disorder presenting with a spectrum of clinical features caused by mutations in different genes. A 10‐year‐old girl with CIP, hyposmia and hypogeusia, and her unaffected twin and parents underwent next generation sequencing of SCN9A exons and flanking splice sites. Transcript analysis from whole blood successfully assayed the effect of the mutation on the mRNA splicing by polymerase chain reaction amplification on cDNA and Sanger sequencing. We identified the novel splicing variant c.1108‐2A>G compound with the p.Arg896Gln (c.2687G>A) missense mutation previously described in a homozygous patient. The new intronic variant was predicted to induce exon 10 skipping. Conversely, SCN9A mRNA assay demonstrated its partial deletion with a loss of 46 nucleotides causing a premature stop codon in position p.Gln369 (NP_002968). Genetic analysis showed that the two variants were biallelic, being the mother and brother heterozygous carriers of the missense mutation, and the father heterozygous for the splicing mutation. Skin biopsy showed lack of Meissner's corpuscles, loss of epidermal nociceptors and normal autonomic organ innervation. We report a novel splicing mutation and provide clues on its pathogenic effect, broadening the spectrum of genotypes and phenotypes associated to CIP.