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Background Objective Methods Results Conclusion Understanding the neural mechanisms underlying migraine and other primary headache disorders is critical for the development of long‐term cures. Magnetoencephalography (MEG), an imaging modality that measures neuronal currents and cortical excitability with high temporal and superior spatial resolution, has been increasingly used in neurological research. Initial MEG studies showed promise in directly recording cortical spreading depression—a cortical correlate of migraine with aura. However, lately MEG technology has highly evolved with greater potential to reveal underlying pathophysiology of migraine and primary headache disorders, and aid in the identification of biomarkers.To systematically review the use of MEG in migraine and other primary headache disorders and summarize findings.We conducted a systematic search and selection of MEG studies in migraine and primary headache disorders from inception until June 8, 2023, in Medline, Embase, Cochrane, and Scopus databases. Peer‐reviewed English articles reporting the use of MEG for clinical or research purposes in migraine and primary headache disorders were selected.We found 560 articles and included 38 in this review after screening. Twelve studies investigated resting‐state, while others investigated a sensory modality using an evoked or event‐related paradigm with a total of 35 cohort and 3 case studies. Thirty‐two studies focused exclusively on migraine, while the rest reported other primary headache disorders.The findings show an evolution of MEG from a 7‐ to a 306‐channel system and analysis evolving from sensor‐level evoked responses to more advanced source‐level connectivity measures. A relatively few MEG studies portrayed migraine and primary headache disorders as a sensory abnormality, especially of the visual system. We found heterogeneity in the datasets, data reporting standards (due to constantly evolving MEG technology and analysis methods), and patient characteristics. Studies were inadequately powered and there was no evidence of blinding procedures to avoid selection bias in case–control studies, which could have led to false‐positive findings. More studies are needed to investigate the affective–cognitive aspects that exacerbate pain and disability in migraine and primary headache disorders. [ABSTRACT FROM AUTHOR]

While ipsilesional cortical electroencephalography has been associated with poststroke recovery mechanisms and outcomes, the role of the cerebellum and its interaction with the ipsilesional cortex is still largely unknown. We have previously shown that poststroke motor control relies on increased corticocerebellar coherence (CCC) in the low beta band to maintain motor task accuracy and to compensate for decreased excitability of the ipsilesional cortex. We now extend our work to investigate corticocerebellar network changes associated with chronic stimulation of the dentato-thalamo-cortical pathway aimed at promoting poststroke motor rehabilitation. We investigated the excitability of the ipsilesional cortex, the dentate (DN), and their interaction as a function of treatment outcome measures. Relative to baseline, 10 human participants (two women) at the end of 4-8 months of DN deep brain stimulation (DBS) showed (1) significantly improved motor control indexed by computerized motor tasks; (2) significant increase in ipsilesional premotor cortex event-related desynchronization that correlated with improvements in motor function; and (3) significant decrease in CCC, including causal interactions between the DN and ipsilesional cortex, which also correlated with motor function improvements. Furthermore, we show that the functional state of the DN in the poststroke state and its connectivity with the ipsilesional cortex were predictive of motor outcomes associated with DN-DBS. The findings suggest that as participants recovered, the ipsilesional cortex became more involved in motor control, with less demand on the cerebellum to support task planning and execution. Our data provide unique mechanistic insights into the functional state of corticocerebellar-cortical network after stroke and its modulation by DN-DBS. [ABSTRACT FROM AUTHOR]

The robust, reciprocal anatomic connections between the cerebellum and contralateral sensorimotor cerebral hemisphere underscore the strong physiological interdependence between these two regions in relation to human behavior. Previous studies have shown that damage to sensorimotor cortex can result in a lasting reduction of cerebellar metabolism, the magnitude of which has been linked to poor rehabilitative outcomes. A better understanding of movement-related cerebellar physiology as well as cortico-cerebellar coherence (CCC) in the chronic, poststroke state may be key to developing novel neuromodulatory techniques that promote upper limb motor rehabilitation. As a part of the first in-human phase I trial investigating the effects of deep brain stimulation of the cerebellar dentate nucleus (DN) on chronic poststroke motor rehabilitation, we collected invasive recordings from DN and scalp EEG in participants (both sexes) with middle cerebral artery stroke during a visuo-motor tracking task. We investigated the excitability of ipsilesional cortex, DN, and their interaction as a function of motor impairment and performance. Our results indicate the following: (1) event-related oscillations in the ipsilesional cortex and DN were significantly correlated at movement onset in the low beta band, with moderately and severely impaired participants showing desynchronization and synchronization, respectively; and (2) significant CCC was observed during the isometric hold period in the low beta band, which was critical for maintaining task accuracy. Our findings support a strong coupling between ipsilesional cortex and DN in the low beta band during motor control across all impairment levels, which encourages the exploitation of the cerebello–thalamo–cortical pathway as a neuromodulation target to promote rehabilitation. [ABSTRACT FROM AUTHOR]

Neural oscillatory changes within and across different frequency bands are thought to underlie motor dysfunction in Parkinson's disease (PD) and may serve as biomarkers for closed-loop deep brain stimulation (DBS) approaches. Here, we used neural oscillatory signals derived from chronically implanted cortical and subcortical electrode arrays as features to train machine learning algorithms to discriminate between naive and mild PD states in a nonhuman primate model. Local field potential (LFP) data were collected over several months from a 12- channel subdural electrocorticography (ECoG) grid and a 6-channel custom array implanted in the subthalamic nucleus (STN). Relative to the naive state, the PD state showed elevated primary motor cortex (M1) and STN power in the beta, high gamma, and high-frequency oscillation (HFO) bands and decreased power in the delta band. Theta power was found to be decreased in STN but not M1. In the PD state there was elevated beta-HFO phase-amplitude coupling (PAC) in the STN. We applied machine learning with support vector machines with radial basis function (SVM-RBF) kernel and k-nearest neighbors (KNN) classifiers trained by features related to power and PAC changes to discriminate between the naive and mild states. Our results show that the most predictive feature of parkinsonism in the STN was high beta (~86% accuracy), whereas it was HFO in M1 (~98% accuracy). A feature fusion approach outperformed every individual feature, particularly in the M1, where ~98% accuracy was achieved with both classifiers. Overall, our data demonstrate the ability to use various frequency band power to classify the clinical state and are also beneficial in developing closed-loop DBS therapeutic approaches. [ABSTRACT FROM AUTHOR]

Poststroke pain syndrome (PSPS) is an often intractable disorder characterized by hemiparesis associated with unrelenting chronic pain. Although traditional analgesics have largely failed, integrative approaches targeting affective-cognitive spheres have started to show promise. Recently, we demonstrated that deep brain stimulation (DBS) of the ventral striatal area significantly improved the affective sphere of pain in patients with PSPS. In the present study, we examined whether electrophysiological correlates of pain anticipation were modulated by DBS that could serve as signatures of treatment effects. We recorded event-related fields (ERFs) of pain anticipation using magnetoencephalography (MEG) in 10 patients with PSPS preoperatively and postoperatively in DBS OFF and ON states. Simple visual cues evoked anticipation as patients awaited a painful (PS) or nonpainful stimulus (NPS) to the nonaffected or affected extremity. Preoperatively, ERFs showed no difference between PS and NPS anticipation to the affected extremity, possibly due to loss of salience in a network saturated by pain experience. DBS significantly modulated the early N1, consistent with improvements in affective networks involving restoration of salience and discrimination capacity. Additionally, DBS suppressed the posterior P2 (aberrant anticipatory anxiety) while enhancing the anterior N1 (cognitive and emotional regulation) in responders. DBS-induced changes in ERFs could potentially serve as signatures for clinical outcomes. [ABSTRACT FROM AUTHOR]

Central poststroke pain (CPSP) is characterized by hemianesthesia associated with unrelenting chronic pain. The final pain experience stems from interactions between sensory, affective, and cognitive components of chronic pain. Hence, managing CPSP will require integrated approaches aimed not only at the sensory but also the affective-cognitive spheres. A better understanding of the brain's processing of pain anticipation is critical for the development of novel therapeutic approaches that target affectivecognitive networks and alleviate pain-related disability. We used magnetoencephalography (MEG) to characterize the neural substrates of pain anticipation in patients suffering from intractable CPSP. Simple visual cues evoked anticipation while patients awaited impending painful (PS), nonpainful (NPS), or no stimulus (NOS) to their nonaffected and affected extremities. MEG responses were studied at gradiometer level using event-related fields analysis and timefrequency oscillatory analysis upon source localization. On the nonaffected side, significantly greater responses were recorded during PS. PS (vs. NPS and NOS) exhibited significant parietal and frontal cortical activations in the beta and gamma bands, respectively, whereas NPS (vs. NOS) displayed greater activation in the orbitofrontal cortex. On the affected extremity, PS (vs. NPS) did not show significantly greater responses. These data suggest that anticipatory phenomena can modulate neural activity when painful stimuli are applied to the nonaffected extremity but not the affected extremity in CPSP patients. This dichotomy may stem from the chronic effects of pain on neural networks leading to habituation or saturation. Future clinically effective therapies will likely be associated with partial normalization of the neurophysiological correlates of pain anticipation. [ABSTRACT FROM AUTHOR]

Anticipating pain is important for avoiding injury; however, in chronic pain patients, anticipatory behavior can become maladaptive, leading to sensitization and limiting function. Knowledge of networks involved in pain anticipation and conditioning over time could help devise novel, better-targeted therapies. With the use of magnetoencephalography, we evaluated in 10 healthy subjects the neural processing of pain anticipation. Anticipatory cortical activity elicited by consecutive visual cues that signified imminent painful stimulus was compared with cues signifying nonpainful and no stimulus. We found that the neural processing of visually evoked pain anticipation involves the primary visual cortex along with cingulate and frontal regions. Visual cortex could quickly and independently encode and discriminate between visual cues associated with pain anticipation and no pain during preconscious phases following object presentation.When evaluating the effect of task repetition on participating cortical areas, we found that activity of prefrontal and cingulate regions was mostly prominent early on when subjects were still naive to a cue's contextual meaning. Visual cortical activity was significant throughout later phases. Although visual cortex may precisely and time efficiently decode cues anticipating pain or no pain, prefrontal areas establish the context associated with each cue. These findings have important implications toward processes involved in pain anticipation and maladaptive pain conditioning. [ABSTRACT FROM AUTHOR]