Hereditary spastic paraparesis type 46 (SPG46): new GBA2 variants in a large Italian case series and review of the literature.

Hereditary spastic paraparesis (HSP) is a group of central nervous system diseases primarily affecting the spinal upper motor neurons, with different inheritance patterns and phenotypes. SPG46 is a rare, early-onset and autosomal recessive HSP, linked to biallelic GBA2 mutations. About thirty families have been described worldwide, with different phenotypes like complicated HSP, recessive cerebellar ataxia or Marinesco-Sjögren Syndrome. Herein, we report five SPG46 patients harbouring five novel GBA2 mutations, the largest series described in Italy so far. Probands were enrolled in five different centres and underwent neurological examination, clinical cognitive assessment, column imaging for scoliosis assessment, ophthalmologic examination, brain imaging, GBA2 activity in peripheral blood cells and genetic testing. Their phenotype was consistent with HSP, with notable features like upper gaze palsy and movement disorders. We review demographic, genetic, biochemical and clinical information from all documented cases in the existing literature, focusing on the global distribution of cases, the features of the syndrome, its variable presentation, new potential identifying features and the significance of measuring GBA2 enzyme activity.

Local Dynamic Stability of Trunk During Gait is Responsive to Rehabilitation in Subjects with Primary Degenerative Cerebellar Ataxia.

This study aimed to assess the responsiveness to the rehabilitation of three trunk acceleration-derived gait indexes, namely the harmonic ratio (HR), the short-term longest Lyapunov's exponent (sLLE), and the step-to-step coefficient of variation (CV), in a sample of subjects with primary degenerative cerebellar ataxia (swCA), and investigate the correlations between their improvements (∆), clinical characteristics, and spatio-temporal and kinematic gait features. The trunk acceleration patterns in the antero-posterior (AP), medio-lateral (ML), and vertical (V) directions during gait of 21 swCA were recorded using a magneto-inertial measurement unit placed at the lower back before (T0) and after (T1) a period of inpatient rehabilitation. For comparison, a sample of 21 age- and gait speed-matched healthy subjects (HSmatched) was also included. At T1, sLLE in the AP (sLLEAP) and ML (sLLEML) directions significantly improved with moderate to large effect sizes, as well as SARA scores, stride length, and pelvic rotation. sLLEML and pelvic rotation also approached the HSmatched values at T1, suggesting a normalization of the parameter. HRs and CV did not significantly modify after rehabilitation. ∆sLLEML correlated with ∆ of the gait subscore of the SARA scale (SARAGAIT) and ∆stride length and ∆sLLEAP correlated with ∆pelvic rotation and ∆SARAGAIT. The minimal clinically important differences for sLLEML and sLLEAP were ≥ 36.16% and ≥ 28.19%, respectively, as the minimal score reflects a clinical improvement in SARA scores. When using inertial measurement units, sLLEAP and sLLEML can be considered responsive outcome measures for assessing the effectiveness of rehabilitation on trunk stability during walking in swCA.

Pathophysiology of cluster headache: From the trigeminovascular system to the cerebral networks.

BACKGROUND: Despite advances in neuroimaging and electrophysiology, cluster headache's pathogenesis remains unclear. This review will examine clinical neurophysiology studies, including electrophysiological and functional neuroimaging, to determine if they might help us construct a neurophysiological model of cluster headache. RESULTS: Clinical, biochemical, and electrophysiological research have implicated the trigeminal-parasympathetic system in cluster headache pain generation, although the order in which these two systems are activated, which may be somewhat independent, is unknown. Electrophysiology and neuroimaging have found one or more central factors that may cause seasonal and circadian attacks. The well-known posterior hypothalamus, with its primary circadian pacemaker suprachiasmatic nucleus, the brainstem monoaminergic systems, the midbrain, with an emphasis on the dopaminergic system, especially when cluster headache is chronic, and the descending pain control systems appear to be involved. Functional connection investigations have verified electrophysiological evidence of functional changes in distant brain regions connecting to wide cerebral networks other than pain. CONCLUSION: We propose that under the impact of external time, an inherited misalignment between the primary circadian pacemaker suprachiasmatic nucleus and other secondary extra- suprachiasmatic nucleus clocks may promote disturbance of the body's internal physiological clock, lowering the threshold for bout recurrence.

Decoding pain through facial expressions: a study of patients with migraine.

BACKGROUND: The present study used the Facial Action Coding System (FACS) to analyse changes in facial activities in individuals with migraine during resting conditions to determine the potential of facial expressions to convey information about pain during headache episodes. METHODS: Facial activity was recorded in calm and resting conditions by using a camera for both healthy controls (HC) and patients with episodic migraine (EM) and chronic migraine (CM). The FACS was employed to analyse the collected facial images, and intensity scores for each of the 20 action units (AUs) representing expressions were generated. The groups and headache pain conditions were then examined for each AU. RESULTS: The study involved 304 participants, that is, 46 HCs, 174 patients with EM, and 84 patients with CM. Elevated headache pain levels were associated with increased lid tightener activity and reduced mouth stretch. In the CM group, moderate to severe headache attacks exhibited decreased activation in the mouth stretch, alongside increased activation in the lid tightener, nose wrinkle, and cheek raiser, compared to mild headache attacks (all corrected p < 0.05). Notably, lid tightener activation was positively correlated with the Numeric Rating Scale (NRS) level of headache (p = 0.012). Moreover, the lip corner depressor was identified to be indicative of emotional depression severity (p < 0.001). CONCLUSION: Facial expressions, particularly lid tightener actions, served as inherent indicators of headache intensity in individuals with migraine, even during resting conditions. This indicates that the proposed approach holds promise for providing a subjective evaluation of headaches, offering the benefits of real-time assessment and convenience for patients with migraine.

Identification of Gait Unbalance and Fallers Among Subjects with Cerebellar Ataxia by a Set of Trunk Acceleration-Derived Indices of Gait.

This study aimed to assess the ability of 25 gait indices to characterize gait instability and recurrent fallers among persons with primary degenerative cerebellar ataxia (pwCA), regardless of gait speed, and investigate their correlation with clinical and kinematic variables. Trunk acceleration patterns were acquired during the gait of 34 pwCA, and 34 age- and speed-matched healthy subjects (HSmatched) using an inertial measurement unit. We calculated harmonic ratios (HR), percent recurrence, percent determinism, step length coefficient of variation, short-time largest Lyapunov exponent (sLLE), normalized jerk score, log-dimensionless jerk (LDLJ-A), root mean square (RMS), and root mean square ratio of accelerations (RMSR) in each spatial direction for each participant. Unpaired t-tests or Mann-Whitney tests were performed to identify significant differences between the pwCA and HSmatched groups. Receiver operating characteristics were plotted to assess the ability to characterize gait alterations in pwCA and fallers. Optimal cutoff points were identified, and post-test probabilities were calculated. The HRs showed to characterize gait instability and pwCA fallers with high probabilities. They were correlated with disease severity and stance, swing, and double support duration, regardless of gait speed. sLLEs, RMSs, RMSRs, and LDLJ-A were slightly able to characterize the gait of pwCA but failed to characterize fallers.

Electrophysiological findings in migraine may reflect abnormal synaptic plasticity mechanisms: A narrative review.

BACKGROUND: The cyclical brain disorder of sensory processing accompanying migraine phases lacks an explanatory unified theory. METHODS: We searched Pubmed for non-invasive neurophysiological studies on migraine and related conditions using transcranial magnetic stimulation, electroencephalography, visual and somatosensory evoked potentials. We summarized the literature, reviewed methods, and proposed a unified theory for the pathophysiology of electrophysiological abnormalities underlying migraine recurrence. RESULTS: All electrophysiological modalities have determined specific changes in brain dynamics across the different phases of the migraine cycle. Transcranial magnetic stimulation studies show unbalanced recruitment of inhibitory and excitatory circuits, more consistently in aura, which ultimately results in a substantially distorted response to neuromodulation protocols. Electroencephalography investigations highlight a steady pattern of reduced alpha and increased slow rhythms, largely located in posterior brain regions, which tends to normalize closer to the attacks. Finally, non-painful evoked potentials suggest dysfunctions in habituation mechanisms of sensory cortices that revert during ictal phases. CONCLUSION: Electrophysiology shows dynamic and recurrent functional alterations within the brainstem-thalamus-cortex loop varies continuously and recurrently in migraineurs. Given the central role of these structures in the selection, elaboration, and learning of sensory information, these functional alterations suggest chronic, probably genetically determined dysfunctions of the synaptic short- and long-term learning mechanisms.

Identification of patients with chronic migraine by using sensory-evoked oscillations from the electroencephalogram classifier.

BACKGROUND: To examine whether the modulating evoked cortical oscillations could be brain signatures among patients with chronic migraine, we investigated cortical modulation using an electroencephalogram with machine learning techniques. METHODS: We directly record evoked electroencephalogram activity during nonpainful, painful, and repetitive painful electrical stimulation tasks. Cortical modulation for experimental pain and habituation processing was analyzed and used to differentiate patients with chronic migraine from healthy controls using a validated machine-learning model. RESULTS: This study included 80 participants: 40 healthy controls and 40 patients with chronic migraine. Evoked somatosensory oscillations were dominant in the alpha band. Longer latency (nonpainful and repetitive painful) and augmented power (nonpainful and repetitive painful) were present among patients with chronic migraine. However, for painful tasks, alpha increases were observed among healthy controls. The oscillatory activity ratios between repetitive painful and painful tasks represented the frequency modulation and power habituation among healthy controls, respectively, but not among patients with chronic migraine. The classification models with oscillatory features exhibited high performance in differentiating patients with chronic migraine from healthy controls. CONCLUSION: Altered oscillatory characteristics of sensory processing and cortical modulation reflected the neuropathology of patients with chronic migraine. These characteristics can be reliably used to identify patients with chronic migraine using a machine-learning approach.

Central sensitization mechanisms in chronic migraine with medication overuse headache: a study of thalamocortical activation and lateral cortical inhibition.

BACKGROUND: It is unclear whether cortical hyperexcitability in chronic migraine with medication overuse headache (CM-MOH) is due to increased thalamocortical drive or aberrant cortical inhibitory mechanisms. METHODS: Somatosensory evoked potentials (SSEP) were performed by electrical stimulation of the median nerve (M), ulnar nerve (U) and simultaneous stimulation of both nerves (MU) in 27 patients with CM-MOH and, for comparison, in 23 healthy volunteers (HVs) of a comparable age distribution. We calculated the degree of cortical lateral inhibition using the formula: 100 - [MU/(M + U) × 100] and the level of thalamocortical activation by analyzing the high frequency oscillations (HFOs) embedded in parietal N20 median SSEPs. RESULTS: Compared to HV, CM-MOH patients showed higher lateral inhibition (CM-MOH 52.2% ± 15.4 vs. HV 40.4% ± 13.3; p = 0.005), which positively correlated with monthly headache days, and greater amplitude of pre-synaptic HFOs (p = 0.010) but normal post-synaptic HFOs (p = 0.122). CONCLUSION: Our findings suggest that central neuronal circuits are highly sensitized in CM-MOH patients, at both thalamocortical and cortical levels. The observed changes could be due to the combination of dysfunctional central pain control mechanisms, hypersensitivity and hyperresponsiveness directly linked to the chronic intake of acute migraine drugs.

Validation of the Italian version of the Cluster Headache Impact Questionnaire (CHIQ).

BACKGROUND: The Cluster Headache Impact Questionnaire (CHIQ) is a specific and easy-to-use questionnaire to assess the current impact of cluster headache (CH). The aim of this study was to validate the Italian version of the CHIQ. METHODS: We included patients diagnosed with episodic CH (eCH) or chronic CH (cCH) according to the ICHD-3 criteria and included in the "Italian Headache Registry" (RICe). The questionnaire was administered to patients through an electronic form in two sessions: at first visit for validation, and after 7 days for test-retest reliability. For internal consistency, Cronbach's alpha was calculated. Convergent validity of the CHIQ with CH features and the results of questionnaires assessing anxiety, depression, stress, and quality of life was evaluated using Spearman's correlation coefficient. RESULTS: We included 181 patients subdivided in 96 patients with active eCH, 14 with cCH, and 71 with eCH in remission. The 110 patients with either active eCH or cCH were included in the validation cohort; only 24 patients with CH were characterized by a stable attack frequency after 7 days, and were included in the test-retest cohort. Internal consistency of the CHIQ was good with a Cronbach alpha value of 0.891. The CHIQ score showed a significant positive correlation with anxiety, depression, and stress scores, while showing a significant negative correlation with quality-of-life scale scores. CONCLUSION: Our data show the validity of the Italian version of the CHIQ, which represents a suitable tool for evaluating the social and psychological impact of CH in clinical practice and research.

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease.

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

Characteristic oscillatory brain networks for predicting patients with chronic migraine.

To determine specific resting-state network patterns underlying alterations in chronic migraine, we employed oscillatory connectivity and machine learning techniques to distinguish patients with chronic migraine from healthy controls and patients with other pain disorders. This cross-sectional study included 350 participants (70 healthy controls, 100 patients with chronic migraine, 40 patients with chronic migraine with comorbid fibromyalgia, 35 patients with fibromyalgia, 30 patients with chronic tension-type headache, and 75 patients with episodic migraine). We collected resting-state magnetoencephalographic data for analysis. Source-based oscillatory connectivity within each network, including the pain-related network, default mode network, sensorimotor network, visual network, and insula to default mode network, was examined to determine intrinsic connectivity across a frequency range of 1-40 Hz. Features were extracted to establish and validate classification models constructed using machine learning algorithms. The findings indicated that oscillatory connectivity revealed brain network abnormalities in patients with chronic migraine compared with healthy controls, and that oscillatory connectivity exhibited distinct patterns between various pain disorders. After the incorporation of network features, the best classification model demonstrated excellent performance in distinguishing patients with chronic migraine from healthy controls, achieving high accuracy on both training and testing datasets (accuracy > 92.6% and area under the curve > 0.93). Moreover, in validation tests, classification models exhibited high accuracy in discriminating patients with chronic migraine from all other groups of patients (accuracy > 75.7% and area under the curve > 0.8). In conclusion, oscillatory synchrony within the pain-related network and default mode network corresponded to altered neurophysiological processes in patients with chronic migraine. Thus, these networks can serve as pivotal signatures in the model for identifying patients with chronic migraine, providing reliable and generalisable results. This approach may facilitate the objective and individualised diagnosis of migraine.

The monoclonal CGRP-receptor blocking antibody erenumab has different effects on brainstem and cortical sensory-evoked responses.

OBJECTIVES: It is unclear whether the electrophysiological effects of erenumab, a monoclonal antibody against the calcitonin gene-related peptide receptor, occur only at the periphery of the trigeminal system or centrally and at the cortical level. METHODS: We prospectively enrolled 20 patients with migraine who had failed at least two preventative treatments. We measured the nociceptive blink reflex and non-noxious somatosensory evoked potentials in all participants. The area under the curve and habituation of the second polysynaptic nociceptive blink reflex component (R2) as well as the amplitude and habituation of somatosensory evoked potentials N20-P25 were measured. Electrophysiological data were collected at baseline (T0), 28 days (T1), and 56 days (T2) before each injection of erenumab (70 mg). RESULTS: Erenumab reduced the patients' mean monthly headache days, headache intensity, and acute medication intake considerably at T1 and T2 (all p < 0.05). The nociceptive blink reflex area under the curve was considerably lower at T1 and T2 than at baseline without changing the habituation slope. At T2, there was a significant increase in the delayed somatosensory evoked potentials amplitude reduction (habituation) but not in the initial cortical activation. CONCLUSION: Our findings showed that erenumab, in addition to its well-known peripheral effects, can induce central effects earlier in the brainstem and later in the cortex. We cannot rule out whether these results are due to a direct effect of erenumab on the central nervous system or an indirect effect secondary to peripheral drug modulation.

Bimodal sensory integration in migraine: A study of the effect of visual stimulation on somatosensory evoked cortical responses.

BACKGROUND: Merging of sensory information is a crucial process for adapting the behaviour to the environment in all species. It is not known if this multisensory integration might be dysfunctioning interictally in migraine without aura, where sensory stimuli of various modalities are processed abnormally when delivered separately. To investigate this question, we compared the effects of a concomitant visual stimulation on conventional low-frequency somatosensory evoked potentials and embedded high-frequency oscillations between migraine patients and healthy volunteers. METHODS: We recorded somatosensory evoked potentials in 19 healthy volunteers and in 19 interictal migraine without aura patients before, during, and 5 min after (T2) simultaneous synchronous pattern-reversal visual stimulation. At each time point, we measured amplitude and habituation of the N20-P25 low-frequency-somatosensory evoked potentials component and maximal peak-to-peak amplitude of early and late bursts of high-frequency oscillations. RESULTS: In healthy volunteers, the bimodal stimulation significantly reduced low-frequency-somatosensory evoked potentials habituation and tended to reduce early high-frequency oscillations that reflect thalamocortical activity. By contrast, in migraine without aura patients, bimodal stimulation significantly increased low-frequency-somatosensory evoked potentials habituation and early high-frequency oscillations. At T2, all visual stimulation-induced changes of somatosensory processing had vanished. CONCLUSION: These results suggest a malfunctioning multisensory integration process, which could be favoured by an abnormal excitability level of thalamo-cortical loops.

Neuromodulation for Chronic Daily Headache.

PURPOSE OF REVIEW: We reviewed the literature that explored the use of central and peripheral neuromodulation techniques for chronic daily headache (CDH) treatment. RECENT FINDINGS: Although the more invasive deep brain stimulation (DBS) is effective in chronic cluster headache (CCH), it should be reserved for extremely difficult-to-treat patients. Percutaneous occipital nerve stimulation has shown similar efficacy to DBS and is less risky in both CCH and chronic migraine (CM). Non-invasive transcutaneous vagus nerve stimulation is a promising add-on treatment for CCH but not for CM. Transcutaneous external trigeminal nerve stimulation may be effective in treating CM; however, it has not yet been tested for cluster headache. Transcranial magnetic and electric stimulations have promising preventive effects against CM and CCH. Although the precise mode of action of non-invasive neuromodulation techniques remains largely unknown and there is a paucity of controlled trials, they should be preferred to more invasive techniques for treating CDH.

Machine Learning Approach to Support the Detection of Parkinson's Disease in IMU-Based Gait Analysis.

The aim of this study was to determine which supervised machine learning (ML) algorithm can most accurately classify people with Parkinson's disease (pwPD) from speed-matched healthy subjects (HS) based on a selected minimum set of IMU-derived gait features. Twenty-two gait features were extrapolated from the trunk acceleration patterns of 81 pwPD and 80 HS, including spatiotemporal, pelvic kinematics, and acceleration-derived gait stability indexes. After a three-level feature selection procedure, seven gait features were considered for implementing five ML algorithms: support vector machine (SVM), artificial neural network, decision trees (DT), random forest (RF), and K-nearest neighbors. Accuracy, precision, recall, and F1 score were calculated. SVM, DT, and RF showed the best classification performances, with prediction accuracy higher than 80% on the test set. The conceptual model of approaching ML that we proposed could reduce the risk of overrepresenting multicollinear gait features in the model, reducing the risk of overfitting in the test performances while fostering the explainability of the results.

A Hypothalamic Mechanism Regulates the Duration of a Migraine Attack: Insights from Microstructural and Temporal Complexity of Cortical Functional Networks Analysis.

The role of the hypothalamus and the limbic system at the onset of a migraine attack has recently received significant interest. We analyzed diffusion tensor imaging (DTI) parameters of the entire hypothalamus and its subregions in 15 patients during a spontaneous migraine attack and in 20 control subjects. We also estimated the non-linear measure resting-state functional MRI BOLD signal's complexity using Higuchi fractal dimension (FD) and correlated DTI/fMRI findings with patients' clinical characteristics. In comparison with healthy controls, patients had significantly altered diffusivity metrics within the hypothalamus, mainly in posterior ROIs, and higher FD values in the salience network (SN). We observed a positive correlation of the hypothalamic axial diffusivity with migraine severity and FD of SN. DTI metrics of bilateral anterior hypothalamus positively correlated with the mean attack duration. Our results show plastic structural changes in the hypothalamus related to the attacks severity and the functional connectivity of the SN involved in the multidimensional neurocognitive processing of pain. Plastic changes to the hypothalamus may play a role in modulating the duration of the attack.

Visual stimulation and frequency of focal neurological symptoms engage distinctive neurocognitive resources in migraine with aura patients: a study of resting-state functional networks.

INTRODUCTION: Several functional neuroimaging studies on healthy controls and patients with migraine with aura have shown that the activation of functional networks during visual stimulation is not restricted to the striate system, but also includes several extrastriate networks. METHODS: Before and after 4 min of visual stimulation with a checkerboard pattern, we collected functional MRI in 21 migraine with aura (MwA) patients and 18 healthy subjects (HS). For each recording session, we identified independent resting-state networks in each group and correlated network connection strength changes with clinical disease features. RESULTS: Before visual stimulation, we found reduced connectivity between the default mode network and the left dorsal attention system (DAS) in MwA patients compared to HS. In HS, visual stimulation increases functional connectivity between the independent components of the bilateral DAS and the executive control network (ECN). In MwA, visual stimulation significantly improved functional connectivity between the independent component pairs salience network and DAS, and between DAS and ECN. The ECN Z-scores after visual stimulation were negatively related to the monthly frequency of aura. CONCLUSIONS: In individuals with MwA, 4 min of visual stimulation had stronger cognitive impact than in healthy people. A higher frequency of aura may lead to a diminished ability to obtain cognitive resources to cope with transitory but important events like aura-related focal neurological symptoms.

Dynamic brainstem and somatosensory cortical excitability during migraine cycles.

BACKGROUND: Migraine has complex pathophysiological characteristics and episodic attacks. To decipher the cyclic neurophysiological features of migraine attacks, in this study, we compared neuronal excitability in the brainstem and primary somatosensory (S1) region between migraine phases for 30 consecutive days in two patients with episodic migraine. METHODS: Both patients underwent EEG recording of event-related potentials with the somatosensory and paired-pulse paradigms for 30 consecutive days. The migraine cycle was divided into the following phases: 24-48 h before headache onset (Pre2), within 24 h before headache onset (Pre1), during the migraine attack (Ictal), within 24 h after headache offset (Post1), and the interval of ˃48 h between the last and next headache phase (Interictal). The normalised current intensity in the brainstem and S1 and gating ratio in the S1 were recorded and examined. RESULTS: Six migraine cycles (three for each patient) were analysed. In both patients, the somatosensory excitability in the brainstem (peaking at 12-14 ms after stimulation) and S1 (peaking at 18-19 ms after stimulation) peaked in the Pre1 phase. The S1 inhibitory capability was higher in the Ictal phase than in the Pre1 phase. CONCLUSION: This study demonstrates that migraine is a cyclic excitatory disorder and that the neural substrates involved include the somatosensory system, starting in the brainstem and spanning subsequently to the S1 before the migraine occurs. Further investigations with larger sample sizes are warranted.

Resting-state magnetoencephalographic oscillatory connectivity to identify patients with chronic migraine using machine learning.

To identify and validate the neural signatures of resting-state oscillatory connectivity for chronic migraine (CM), we used machine learning techniques to classify patients with CM from healthy controls (HC) and patients with other pain disorders. The cross-sectional study obtained resting-state magnetoencephalographic data from 240 participants (70 HC, 100 CM, 35 episodic migraine [EM], and 35 fibromyalgia [FM]). Source-based oscillatory connectivity of relevant cortical regions was calculated to determine intrinsic connectivity at 1-40 Hz. A classification model that employed a support vector machine was developed using the magnetoencephalographic data to assess the reliability and generalizability of CM identification. In the findings, the discriminative features that differentiate CM from HC were principally observed from the functional interactions between salience, sensorimotor, and part of the default mode networks. The classification model with these features exhibited excellent performance in distinguishing patients with CM from HC (accuracy ≥ 86.8%, area under the curve (AUC) ≥ 0.9) and from those with EM (accuracy: 94.5%, AUC: 0.96). The model also achieved high performance (accuracy: 89.1%, AUC: 0.91) in classifying CM from other pain disorders (FM in this study). These resting-state magnetoencephalographic electrophysiological features yield oscillatory connectivity to identify patients with CM from those with a different type of migraine and pain disorder, with adequate reliability and generalizability.

How does the brain change in chronic migraine? Developing disease biomarkers.

BACKGROUND: Validated chronic migraine biomarkers could improve diagnostic, prognostic, and predictive abilities for clinicians and researchers, as well as increase knowledge on migraine pathophysiology. OBJECTIVE: The objective of this narrative review is to summarise and interpret the published literature regarding the current state of development of chronic migraine biomarkers. FINDINGS: Data from functional and structural imaging, neurophysiological, and biochemical studies have been utilised towards the development of chronic migraine biomarkers. These biomarkers could contribute to chronic migraine classification/diagnosis, prognosticating patient outcomes, predicting response to treatment, and measuring treatment responses early after initiation. Results show promise for using measures of brain structure and function, evoked potentials, and sensory neuropeptide concentrations for the development of chronic migraine biomarkers, yet further optimisation and validation are still required. CONCLUSIONS: Imaging, neurophysiological, and biochemical changes that occur with the progression from episodic to chronic migraine could be utilised for developing chronic migraine biomarkers that might assist with diagnosis, prognosticating individual patient outcomes, and predicting responses to migraine therapies. Ultimately, validated biomarkers could move us closer to being able to practice precision medicine in the field and thus improve patient care.