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.

Quantification Approaches in Non-Target LC/ESI/HRMS Analysis: An Interlaboratory Comparison.

Nontargeted screening (NTS) utilizing liquid chromatography electrospray ionization high-resolution mass spectrometry (LC/ESI/HRMS) is increasingly used to identify environmental contaminants. Major differences in the ionization efficiency of compounds in ESI/HRMS result in widely varying responses and complicate quantitative analysis. Despite an increasing number of methods for quantification without authentic standards in NTS, the approaches are evaluated on limited and diverse data sets with varying chemical coverage collected on different instruments, complicating an unbiased comparison. In this interlaboratory comparison, organized by the NORMAN Network, we evaluated the accuracy and performance variability of five quantification approaches across 41 NTS methods from 37 laboratories. Three approaches are based on surrogate standard quantification (parent-transformation product, structurally similar or close eluting) and two on predicted ionization efficiencies (RandFor-IE and MLR-IE). Shortly, HPLC grade water, tap water, and surface water spiked with 45 compounds at 2 concentration levels were analyzed together with 41 calibrants at 6 known concentrations by the laboratories using in-house NTS workflows. The accuracy of the approaches was evaluated by comparing the estimated and spiked concentrations across quantification approaches, instrumentation, and laboratories. The RandFor-IE approach performed best with a reported mean prediction error of 15× and over 83% of compounds quantified within 10× error. Despite different instrumentation and workflows, the performance was stable across laboratories and did not depend on the complexity of water matrices.

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.

Lack of a direct link between macular cones function and photophobia in interictal migraine.

BACKGROUND: It is still debatable whether the mechanisms underlying photophobia are related to altered visual cortex excitability or specific abnormalities of colour-related focal macular retino-thalamic information processing. METHODS: This cross-sectional study examined Ganzfeld blue-red (B-R) and blue-yellow (B-Y) focal macular cone flash ERG (ffERG) and focal-flash visual evoked potentials (ffVEPs) simultaneously in a group of migraine patients with (n = 18) and without (n = 19) aura during the interictal phase, in comparison to a group of healthy volunteers (HVs) (n = 20). We correlate the resulting retinal and cortical electrophysiological responses with subjective discomfort from exposure to bright light verified on a numerical scale. RESULTS: Compared to HVs, the amplitude and phase of the first and second harmonic of ffERG and ffVEPs were non-significantly different in migraine patients without aura and migraine patients with aura for both the B-R and the B-Y focal stimuli. Pearson's correlation test did not disclose correlations between clinical variables, including the photophobia scale and electrophysiological variables. CONCLUSIONS: These results do not favour interictal functional abnormalities in L-M- and S-cone opponent visual pathways in patients with migraine. They also suggest that the discomfort resulting from exposure to bright light is not related to focal macular retinal-to-visual cortex pathway.

Subsegmentation of the hippocampus in subgroups of migraine with aura patients: advanced structural neuroimaging study.

BACKGROUND: This study investigated for a possible contributing role of hippocampus in the different clinical phenotypic manifestations of migraine aura. METHODS: Herein, patients were categorized as those with pure visual aura (MwAv), those who reported additional somatosensory and dysphasic symptoms (MwAvsd), and healthy controls (HCs). Neuroimaging data obtained using FreeSurfer-based segmentation of hippocampal subfields were compared between HCs and patients with migraine with aura, as well as between HCs and those with MwAv and MwAvsd. The average migraine aura complexity score (MACS) was calculated for each patient to investigate the correlation between hippocampal subfield volume and migraine aura complexity. RESULTS: Herein, 46 patients with migraine with aura (28 MwAvsd and 18 MwAv) and 31 HCs were included. There were no significant differences in the hippocampal subfields between HCs and patients with migraine with aura. The average MACS negatively correlated with the volumes of the left and right hippocampi, Cornu Ammonis (CA) 1, CA3, CA4, molecular layer, left granule cell layer of the dentate gyrus, hippocampal fissure, and hippocampus-amygdala transition area. The MwAvsd subgroup had significantly smaller whole hippocampal volumes in both hemispheres, as well as in both subicula, compared with the MwAv subgroup and HCs. In addition, the left molecular layer, right CA1, and hippocampal fissures were significantly smaller in the MwAvsd group than in the MwAv subgroup and HCs. CONCLUSIONS: Smaller left and right hippocampal volumes, particularly of the subiculum/CA1 area, may play an important role in the pathophysiology of somatosensory and dysphasic symptoms in migraine with aura.

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.

Altered brainstem-cortex activation and interaction in migraine patients: somatosensory evoked EEG responses with machine learning.

BACKGROUND: To gain a comprehensive understanding of the altered sensory processing in patients with migraine, in this study, we developed an electroencephalography (EEG) protocol for examining brainstem and cortical responses to sensory stimulation. Furthermore, machine learning techniques were employed to identify neural signatures from evoked brainstem-cortex activation and their interactions, facilitating the identification of the presence and subtype of migraine. METHODS: This study analysed 1,000-epoch-averaged somatosensory evoked responses from 342 participants, comprising 113 healthy controls (HCs), 106 patients with chronic migraine (CM), and 123 patients with episodic migraine (EM). Activation amplitude and effective connectivity were obtained using weighted minimum norm estimates with spectral Granger causality analysis. This study used support vector machine algorithms to develop classification models; multimodal data (amplitude, connectivity, and scores of psychometric assessments) were applied to assess the reliability and generalisability of the identification results from the classification models. RESULTS: The findings revealed that patients with migraine exhibited reduced amplitudes for responses in both the brainstem and cortical regions and increased effective connectivity between these regions in the gamma and high-gamma frequency bands. The classification model with characteristic features performed well in distinguishing patients with CM from HCs, achieving an accuracy of 81.8% and an area under the curve (AUC) of 0.86 during training and an accuracy of 76.2% and an AUC of 0.89 during independent testing. Similarly, the model effectively identified patients with EM, with an accuracy of 77.5% and an AUC of 0.84 during training and an accuracy of 87% and an AUC of 0.88 during independent testing. Additionally, the model successfully differentiated patients with CM from patients with EM, with an accuracy of 70.5% and an AUC of 0.73 during training and an accuracy of 72.7% and an AUC of 0.74 during independent testing. CONCLUSION: Altered brainstem-cortex activation and interaction are characteristic of the abnormal sensory processing in migraine. Combining evoked activity analysis with machine learning offers a reliable and generalisable tool for identifying patients with migraine and for assessing the severity of their condition. Thus, this approach is an effective and rapid diagnostic tool for clinicians.

Hallmarks of primary headache: part 1 - migraine.

BACKGROUND AND AIM: Migraine is a common disabling conditions which, globally, affects 15.2% of the population. It is the second cause of health loss in terms of years lived with disability, the first among women. Despite being so common, it is poorly recognised and too often undertreated. Specialty centres and neurologists with specific expertise on headache disorders have the knowledge to provide specific care: however, those who do not regularly treat patients with migraine will benefit from a synopsis on the most relevant and updated information about this condition. This paper presents a comprehensive view on the hallmarks of migraine, from genetics and diagnostic markers, up to treatments and societal impact, and reports the elements that identify migraine specific features. MAIN RESULTS: The most relevant hallmark of migraine is that it has common and individual features together. Besides the known clinical manifestations, migraine presentation is heterogeneous with regard to frequency of attacks, presence of aura, response to therapy, associated comorbidities or other symptoms, which likely reflect migraine heterogeneous genetic and molecular basis. The amount of therapies for acute and for prophylactic treatment is really wide, and one of the difficulties is with finding the best treatment for the single patient. In addition to this, patients carry out different daily life activities, and might show lifestyle habits which are not entirely adequate to manage migraine day by day. Education will be more and more important as a strategy of brain health promotion, because this will enable reducing the amount of subjects needing specialty care, thus leaving it to those who require it in reason of refractory condition or presence of comorbidities. CONCLUSIONS: Recognizing the hallmarks of migraine and the features of single patients enables prescribing specific pharmacological and non-pharmacological treatments. Medical research on headaches today particularly suffers from the syndrome of single-disease approach, but it is important to have a cross-sectional and joint vision with other close specialties, in order to treat our patients with a comprehensive approach that a heterogeneous condition like migraine requires.

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.