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Chen Y, Xie S, Zhang L, Li D, Su H, Wang R, Ao R, Lin X, Liu Y, Zhang S, Zhai D, Sun Y, Wang S, Hu L, Dong Z, Lu X. Attentional network deficits in patients with migraine: behavioral and electrophysiological evidence. J Headache Pain 2024; 25:195. [PMID: 39528969 PMCID: PMC11552239 DOI: 10.1186/s10194-024-01905-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Accepted: 11/03/2024] [Indexed: 11/16/2024] Open
Abstract
BACKGROUND Patients with migraine often experience not only headache pain but also cognitive dysfunction, particularly in attention, which is frequently overlooked in both diagnosis and treatment. The influence of these attentional deficits on the pain-related clinical characteristics of migraine remains poorly understood, and clarifying this relationship could improve care strategies. METHODS This study included 52 patients with migraine and 34 healthy controls. We employed the Attentional Network Test for Interactions and Vigilance-Executive and Arousal Components paradigm, combined with electroencephalography, to assess attentional deficits in patients with migraine, with an emphasis on phasic alerting, orienting, executive control, executive vigilance, and arousal vigilance. An extreme gradient boosting binary classifier was trained on features showing group differences to distinguish patients with migraine from healthy controls. Moreover, an extreme gradient boosting regression model was developed to predict clinical characteristics of patients with migraine using their attentional deficit features. RESULTS For general performance, patients with migraine presented a larger inverse efficiency score, a higher prestimulus beta-band power spectral density and a lower gamma-band event-related synchronization at Cz electrode, and stronger high alpha-band activity at the primary visual cortex, compared to healthy controls. Although no behavior differences in three basic attentional networks were found, patients showed magnified N1 amplitude and prolonged latency of P2 for phasic alerting-trials as well as an increased orienting evoked-P1 amplitude. For vigilance function, improvements in the hit rate of executive vigilance-trials were exhibited in controls but not in patients. Besides, patients with migraine exhibited longer reaction time as well as larger variability in arousal vigilance-trials than controls. The binary classifier developed by such attentional deficit features achieved an F1 score of 0.762 and an accuracy of 0.779 in distinguishing patients with migraine from healthy controls. Crucially, the predicted value available from the regression model involving attentional deficit features significantly correlated with the real value for the frequency of headache. CONCLUSIONS Patients with migraine demonstrated significant attentional deficits, which can be used to differentiate migraine patients from healthy populations and to predict clinical characteristics. These findings highlight the need to address cognitive dysfunction, particularly attentional deficits, in the clinical management of migraine.
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Affiliation(s)
- Yuxin Chen
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Xie
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Libo Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
- Neuroscience and Behaviour Laboratory, Italian Institute of Technology, Rome, 00161, Italy
| | - Desheng Li
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Hui Su
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Rongfei Wang
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Ran Ao
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Xiaoxue Lin
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Yingyuan Liu
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Shuhua Zhang
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Deqi Zhai
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Yin Sun
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Shuqing Wang
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Li Hu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhao Dong
- Department of Neurology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, China.
- School of Medicine, Nankai University, Tianjin, 300071, China.
| | - Xuejing Lu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
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Raghuraman L, Joshi SH. Application of EEG in the Diagnosis and Classification of Migraine: A Scoping Review. Cureus 2024; 16:e64961. [PMID: 39171023 PMCID: PMC11336234 DOI: 10.7759/cureus.64961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 07/19/2024] [Indexed: 08/23/2024] Open
Abstract
Migraine is a chronic debilitating disease affecting a significant number of people, more often women than men. The gold standard for diagnosis is the International Classification of Headache Disorders-3 (ICHD-3). Authors have identified multiple tight spots in the present method of diagnosis. An alternative method of diagnosis has always been coveted. Electroencephalogram (EEG) is one of the most researched of such alternatives. The visually evoked potential is the most studied; auditory evoked potentials and transcranial direct current stimulation are also being studied. Cortical hyperexcitability and habituation deficit to sensory stimuli are some of the consistent findings. Alpha oscillations are among the most frequently studied bands; spectral analysis of EEG waves has often shown more reliable and consistent results than features read off the EEG directly. EEG microstate is a novel and promising method showing characteristic identifiable features that may help diagnose Migraine patients. An alternative to the ICHD-3 criterion for diagnosing Migraines would be instrumental in promptly diagnosing the disease. EEG is one of the most explored alternatives within which enumerable features can be used to identify Migraines, of which the most promising are EEG microstates.
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Affiliation(s)
- Lakshana Raghuraman
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Shiv H Joshi
- Community Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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Conti M, Bovenzi R, Palmieri MG, Placidi F, Stefani A, Mercuri NB, Albanese M. Early effect of onabotulinumtoxinA on EEG-based functional connectivity in patients with chronic migraine: A pilot study. Headache 2024; 64:825-837. [PMID: 38837259 DOI: 10.1111/head.14750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 03/27/2024] [Accepted: 04/03/2024] [Indexed: 06/07/2024]
Abstract
OBJECTIVE In this pilot prospective cohort study, we aimed to evaluate, using high-density electroencephalography (HD-EEG), the longitudinal changes in functional connectivity (FC) in patients with chronic migraine (CM) treated with onabotulinumtoxinA (OBTA). BACKGROUND OBTA is a treatment for CM. Several studies have shown the modulatory action of OBTA on the central nervous system; however, research on migraine is limited. METHODS This study was conducted at the Neurology Unit of "Policlinico Tor Vergata," Rome, Italy, and included 12 adult patients with CM treated with OBTA and 15 healthy controls (HC). Patients underwent clinical scales at enrollment (T0) and 3 months (T1) from the start of treatment. HD-EEG was recorded using a 64-channel system in patients with CM at T0 and T1. A source reconstruction method was used to identify brain activity. FC in δ-θ-α-β-low-γ bands was analyzed using the weighted phase-lag index. FC changes between HCs and CM at T0 and T1 were assessed using cross-validation methods to estimate the results' reliability. RESULTS Compared to HCs at T0, patients with CM showed hyperconnected networks in δ (p = 0.046, area under the receiver operating characteristic curve [AUC: 0.76-0.98], Cohen's κ [0.65-0.93]) and β (p = 0.031, AUC [0.68-0.95], Cohen's κ [0.51-0.84]), mainly involving orbitofrontal, occipital, temporal pole and orbitofrontal, superior temporal, occipital, cingulate areas, and hypoconnected networks in α band (p = 0.029, AUC [0.80-0.99], Cohen's κ [0.42-0.77]), predominantly involving cingulate, temporal pole, and precuneus. Patients with CM at T1, compared to T0, showed hypoconnected networks in δ band (p = 0.032, AUC [0.73-0.99], Cohen's κ [0.53-0.90]) and hyperconnected networks in α band (p = 0.048, AUC [0.58-0.93], Cohen's κ [0.37-0.78]), involving the sensorimotor, orbitofrontal, cingulate, and temporal cortex. CONCLUSION These preliminary results showed that patients with CM presented disrupted EEG-FC compared to controls restored by a single session of OBTA treatment, suggesting a primary central modulatory action of OBTA.
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Affiliation(s)
- Matteo Conti
- Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Roberta Bovenzi
- Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | | | - Fabio Placidi
- Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Alessandro Stefani
- Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | | | - Maria Albanese
- Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
- Neurology Unit, Regional Referral Headache Center, University of Rome "Tor Vergata", Rome, Italy
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4
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Meneghetti N, Vannini E, Mazzoni A. Rodents' visual gamma as a biomarker of pathological neural conditions. J Physiol 2024; 602:1017-1048. [PMID: 38372352 DOI: 10.1113/jp283858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 01/23/2024] [Indexed: 02/20/2024] Open
Abstract
Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.
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Affiliation(s)
- Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), Pisa, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
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5
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O’Hare L, Tarasi L, Asher JM, Hibbard PB, Romei V. Excitation-Inhibition Imbalance in Migraine: From Neurotransmitters to Brain Oscillations. Int J Mol Sci 2023; 24:10093. [PMID: 37373244 PMCID: PMC10299141 DOI: 10.3390/ijms241210093] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/07/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
Migraine is among the most common and debilitating neurological disorders typically affecting people of working age. It is characterised by a unilateral, pulsating headache often associated with severe pain. Despite the intensive research, there is still little understanding of the pathophysiology of migraine. At the electrophysiological level, altered oscillatory parameters have been reported within the alpha and gamma bands. At the molecular level, altered glutamate and GABA concentrations have been reported. However, there has been little cross-talk between these lines of research. Thus, the relationship between oscillatory activity and neurotransmitter concentrations remains to be empirically traced. Importantly, how these indices link back to altered sensory processing has to be clearly established as yet. Accordingly, pharmacologic treatments have been mostly symptom-based, and yet sometimes proving ineffective in resolving pain or related issues. This review provides an integrative theoretical framework of excitation-inhibition imbalance for the understanding of current evidence and to address outstanding questions concerning the pathophysiology of migraine. We propose the use of computational modelling for the rigorous formulation of testable hypotheses on mechanisms of homeostatic imbalance and for the development of mechanism-based pharmacological treatments and neurostimulation interventions.
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Affiliation(s)
- Louise O’Hare
- Division of Psychology, Nottingham Trent University, Nottingham NG1 4FQ, UK
| | - Luca Tarasi
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, Campus di Cesena, Via Rasi e Spinelli, 176, 47521 Cesena, Italy;
| | - Jordi M. Asher
- Department of Psychology, University of Essex, Colchester CO4 3SQ, UK; (J.M.A.); (P.B.H.)
| | - Paul B. Hibbard
- Department of Psychology, University of Essex, Colchester CO4 3SQ, UK; (J.M.A.); (P.B.H.)
| | - Vincenzo Romei
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, Campus di Cesena, Via Rasi e Spinelli, 176, 47521 Cesena, Italy;
- Facultad de Lenguas y Educación, Universidad Antonio de Nebrija, 28015 Madrid, Spain
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6
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Zhang N, Pan Y, Chen Q, Zhai Q, Liu N, Huang Y, Sun T, Lin Y, He L, Hou Y, Yu Q, Li H, Chen S. Application of EEG in migraine. Front Hum Neurosci 2023; 17:1082317. [PMID: 36875229 PMCID: PMC9982126 DOI: 10.3389/fnhum.2023.1082317] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/03/2023] [Indexed: 02/19/2023] Open
Abstract
Migraine is a common disease of the nervous system that seriously affects the quality of life of patients and constitutes a growing global health crisis. However, many limitations and challenges exist in migraine research, including the unclear etiology and the lack of specific biomarkers for diagnosis and treatment. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity. With the updating of data processing and analysis methods in recent years, EEG offers the possibility to explore altered brain functional patterns and brain network characteristics of migraines in depth. In this paper, we provide an overview of the methodology that can be applied to EEG data processing and analysis and a narrative review of EEG-based migraine-related research. To better understand the neural changes of migraine or to provide a new idea for the clinical diagnosis and treatment of migraine in the future, we discussed the study of EEG and evoked potential in migraine, compared the relevant research methods, and put forwards suggestions for future migraine EEG studies.
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Affiliation(s)
- Ning Zhang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Yonghui Pan
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Qihui Chen
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Qingling Zhai
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Ni Liu
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Yanan Huang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Tingting Sun
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Yake Lin
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Linyuan He
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Yue Hou
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Qijun Yu
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Hongyan Li
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Shijiao Chen
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
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7
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Gomez-Pilar J, Martínez-Cagigal V, García-Azorín D, Gómez C, Guerrero Á, Hornero R. 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. J Headache Pain 2022; 23:95. [PMID: 35927625 PMCID: PMC9354370 DOI: 10.1186/s10194-022-01465-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 07/21/2022] [Indexed: 11/25/2022] Open
Abstract
Background The diagnosis of migraine is mainly clinical and self-reported, which makes additional examinations unnecessary in most cases. Migraine can be subtyped into chronic (CM) and episodic (EM). Despite the very high prevalence of migraine, there are no evidence-based guidelines for differentiating between these subtypes other than the number of days of migraine headache per month. Thus, we consider it timely to perform a systematic review to search for physiological evidence from functional activity (as opposed to anatomical structure) for the differentiation between CM and EM, as well as potential functional biomarkers. For this purpose, Web of Science (WoS), Scopus, and PubMed databases were screened. Findings Among the 24 studies included in this review, most of them (22) reported statistically significant differences between the groups of CM and EM. This finding is consistent regardless of brain activity acquisition modality, ictal stage, and recording condition for a wide variety of analyses. That speaks for a supramodal and domain-general differences between CM and EM that goes beyond a differentiation based on the days of migraine per month. Together, the reviewed studies demonstrates that electro- and magneto-physiological brain activity (M/EEG), as well as neurovascular and metabolic recordings from functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), show characteristic patterns that allow to differentiate between CM and EM groups. Conclusions Although a clear brain activity-based biomarker has not yet been identified to distinguish these subtypes of migraine, research is approaching headache specialists to a migraine diagnosis based not only on symptoms and signs reported by patients. Future studies based on M/EEG should pay special attention to the brain activity in medium and fast frequency bands, mainly the beta band. On the other hand, fMRI and PET studies should focus on neural circuits and regions related to pain and emotional processing.
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Affiliation(s)
- Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Víctor Martínez-Cagigal
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - David García-Azorín
- Headache Unit, Neurology Department, Hospital Clínico Universitario de Valladolid, Ramón y Cajal 3, 47003, Valladolid, Spain.
| | - Carlos Gómez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Ángel Guerrero
- Headache Unit, Neurology Department, Hospital Clínico Universitario de Valladolid, Ramón y Cajal 3, 47003, Valladolid, Spain.,Department of Medicine, University of Valladolid, Valladolid, Spain
| | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
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8
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Hepschke JL, Seymour RA, He W, Etchell A, Sowman PF, Fraser CL. Cortical oscillatory dysrhythmias in visual snow syndrome: a magnetoencephalography study. Brain Commun 2021; 4:fcab296. [PMID: 35169699 PMCID: PMC8833316 DOI: 10.1093/braincomms/fcab296] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 09/15/2021] [Accepted: 12/15/2021] [Indexed: 12/30/2022] Open
Abstract
Visual snow refers to the persistent visual experience of static in the whole visual field of both eyes. It is often reported by patients with migraine and co-occurs with conditions such as tinnitus and tremor. The underlying pathophysiology of the condition is poorly understood. Previously, we hypothesized that visual snow syndrome may be characterized by disruptions to rhythmical activity within the visual system. To test this, data from 18 patients diagnosed with visual snow syndrome, and 16 matched controls, were acquired using magnetoencephalography. Participants were presented with visual grating stimuli, known to elicit decreases in alpha-band (8–13 Hz) power and increases in gamma-band power (40–70 Hz). Data were mapped to source-space using a beamformer. Across both groups, decreased alpha power and increased gamma power localized to early visual cortex. Data from the primary visual cortex were compared between groups. No differences were found in either alpha or gamma peak frequency or the magnitude of alpha power, p > 0.05. However, compared with controls, our visual snow syndrome cohort displayed significantly increased primary visual cortex gamma power, p = 0.035. This new electromagnetic finding concurs with previous functional MRI and PET findings, suggesting that in visual snow syndrome, the visual cortex is hyperexcitable. The coupling of alpha-phase to gamma amplitude within the primary visual cortex was also quantified. Compared with controls, the visual snow syndrome group had significantly reduced alpha–gamma phase–amplitude coupling, p < 0.05, indicating a potential excitation–inhibition imbalance in visual snow syndrome, as well as a potential disruption to top-down ‘noise-cancellation’ mechanisms. Overall, these results suggest that rhythmical brain activity in the primary visual cortex is both hyperexcitable and disorganized in visual snow syndrome, consistent with this being a condition of thalamocortical dysrhythmia.
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Affiliation(s)
- Jenny L. Hepschke
- Save Sight Institute, Faculty of Health and Medicine, The University of Sydney, Sydney, NSW, Australia
- Department of Ophthalmology, Prince of Wales Hospital, High Street, Randwick, NSW, Australia
| | - Robert A. Seymour
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - Wei He
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - Andrew Etchell
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - Paul F. Sowman
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - Clare L. Fraser
- Save Sight Institute, Faculty of Health and Medicine, The University of Sydney, Sydney, NSW, Australia
- Macquarie Ophthalmology, Macquarie University, Sydney, NSW, Australia
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9
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Impaired short-term visual paired associative plasticity in patients with migraine between attacks. Pain 2021; 162:803-810. [PMID: 33136981 DOI: 10.1097/j.pain.0000000000002085] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 09/16/2020] [Indexed: 01/11/2023]
Abstract
ABSTRACT A common experimental neurophysiological method to study synaptic plasticity is pairing activity of somatosensory afferents and motor cortical circuits, so-called paired associative stimulation (PAS). Dysfunctional inhibitory and excitatory PAS mechanisms within the sensorimotor system were described in patients with migraine without aura (MO) between attacks. We have recently observed that the same bidirectional PAS rules also apply to the visual system. Here, we have tested whether dysfunctioning associative plasticity might characterize the visual system of patients with MO. In 14 patients with MO between attacks and in 15 healthy volunteers, we performed a previously validated visual PAS (vPAS) protocol by coupling 90 black-and-white checkerboard reversals with low-frequency transcranial magnetic stimulation pulses over the occipital cortex at 2 interstimulus intervals of -25/+25 ms around the visual-evoked potential (VEP) P1 latency. We recorded VEPs (600 sweeps) before, immediately after, and 10 min after each vPAS session. We analysed VEP N1-P1 amplitude and delayed habituation. Although vPAS-25 significantly enhanced and vPAS + 25 reduced VEP amplitude habituation in healthy volunteers, the same protocols did not significantly change VEP amplitude habituation in MO between attacks. We provide evidence for lack of habituation enhancing and habituation suppressing visual PAS mechanisms within the visual system in interictal migraine. This finding, in combination with those previously obtained studying the sensorimotor system, leads us to argue that migraine disease-related dysrhythmic thalamocortical activity prevents the occurrence of physiological bidirectional synaptic plasticity induced by vPAS.
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10
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Coppola G, Di Lorenzo C, Di Lenola D, Serrao M, Pierelli F, Parisi V. Visual Evoked Potential Responses after Photostress in Migraine Patients and Their Correlations with Clinical Features. J Clin Med 2021; 10:jcm10050982. [PMID: 33801187 PMCID: PMC7957878 DOI: 10.3390/jcm10050982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 02/11/2021] [Accepted: 02/18/2021] [Indexed: 11/16/2022] Open
Abstract
In the past few years, researchers have detected subtle macular vision abnormalities using different psychophysical experimental tasks in patients with migraine. Recording of visual evoked potential (VEP) after photostress (PS) represents an objective way to verify the integrity of the dynamic properties of macular performance after exposure to intense light. VEPs were recorded before and after PS in 51 patients with migraine (19 with aura (MA) and 22 without aura (MO) between attacks, and 10 recorded during an attack (MI)) and 14 healthy volunteers. All study participants were exposed to 30 s of PS through the use of a 200-watt bulb lamp. The P100 implicit time and N75-P100 amplitude of the baseline VEP were compared with those collected every 20 s up to 200 s after PS. VEP parameters recorded at baseline did not differ between groups. In all groups, the VEP recordings exhibited a significant increase in implicit times and a reduction in amplitude at 20 s after the PS. In migraine, the percentage decrease in amplitudes observed at 20 s after photostress was significantly lower than in healthy volunteers, in both MO and MA patients, but not in MI patients. When data for MO and MA patients were combined, the percentage of amplitude change at 20 s was negatively correlated with the number of days that had elapsed since the last migraine attack, and positive correlated with attack frequency. We showed dynamic changes of recovery of VEP after PS depending on the migraine cycle. This finding, in conjunction with those previously attained with other neuromodulatory interventions using VEPs, leads us to argue that migraine-disease-related dysrhythmic thalamocortical activity precludes amplitude suppression by PS.
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Affiliation(s)
- Gianluca Coppola
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino, Corso della Repubblica 79, 04100 Latina, Italy; (C.D.L.); (D.D.L.); (M.S.); (F.P.)
- Correspondence: ; Tel.: +39-0773-6513337; Fax: +39-0773-651230
| | - Cherubino Di Lorenzo
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino, Corso della Repubblica 79, 04100 Latina, Italy; (C.D.L.); (D.D.L.); (M.S.); (F.P.)
| | - Davide Di Lenola
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino, Corso della Repubblica 79, 04100 Latina, Italy; (C.D.L.); (D.D.L.); (M.S.); (F.P.)
| | - Mariano Serrao
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino, Corso della Repubblica 79, 04100 Latina, Italy; (C.D.L.); (D.D.L.); (M.S.); (F.P.)
| | - Francesco Pierelli
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino, Corso della Repubblica 79, 04100 Latina, Italy; (C.D.L.); (D.D.L.); (M.S.); (F.P.)
- IRCCS—Neuromed, Headache Center, Via Atinense 18, 86077 Pozzilli, IS, Italy
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De Luca C, Gori S, Mazzucchi S, Dini E, Cafalli M, Siciliano G, Papa M, Baldacci F. Supersaturation of VEP in Migraine without Aura Patients Treated with Topiramate: An Anatomo-Functional Biomarker of the Disease. J Clin Med 2021; 10:jcm10040769. [PMID: 33671875 PMCID: PMC7918918 DOI: 10.3390/jcm10040769] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 01/31/2021] [Accepted: 02/11/2021] [Indexed: 12/15/2022] Open
Abstract
Migraine is a primary headache with high prevalence among the general population, characterized by functional hypersensitivity to both exogenous and endogenous stimuli particularly affecting the nociceptive system. The hyperresponsivity of cortical neurons could be due to a disequilibrium in the excitatory/inhibitory signaling. This study aimed to investigate the anatomo-functional pathway from the retina to the primary visual cortex using visual evoked potentials (VEP). Contrast gain protocol was used in 15 patients diagnosed with migraine without aura (at baseline and after 3 months of topiramate therapy) and 13 controls. A saturation (S) index was assessed to monitor the response of VEP’s amplitude to contrast gain. Non-linear nor monotone growth of VEP (S < 0.95) was defined as supersaturation. A greater percentage of migraine patients (53%) relative to controls (7%) showed this characteristic. A strong inverse correlation was found between the S index and the number of days separating the registration of VEP from the next migraine attack. Moreover, allodynia measured through the Allodynia Symptoms Check-list (ASC-12) correlates with the S index both at baseline and after 3 months of topiramate treatment. Other clinical characteristics were not related to supersaturation. Topiramate therapy, although effective, did not influence electrophysiological parameters suggesting a non-intracortical nor retinal origin of the supersaturation (with possible involvement of relay cells from the lateral geniculate nucleus). In conclusion, the elaboration of visual stimuli and visual cortex activity is different in migraine patients compared to controls. More data are necessary to confirm the potential use of the S index as a biomarker for the migraine cycle (association with the pain-phase) and cortical sensitization (allodynia).
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Affiliation(s)
- Ciro De Luca
- Laboratory of Morphology of Neuronal Network, Department of Public Medicine, University of Campania “Luigi Vanvitelli”, 80138 Napoli, Italy;
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.M.); (E.D.); (G.S.); (F.B.)
- Correspondence:
| | - Sara Gori
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.M.); (E.D.); (G.S.); (F.B.)
| | - Sonia Mazzucchi
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.M.); (E.D.); (G.S.); (F.B.)
| | - Elisa Dini
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.M.); (E.D.); (G.S.); (F.B.)
| | - Martina Cafalli
- Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, 56126 Pisa, Italy;
| | - Gabriele Siciliano
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.M.); (E.D.); (G.S.); (F.B.)
| | - Michele Papa
- Laboratory of Morphology of Neuronal Network, Department of Public Medicine, University of Campania “Luigi Vanvitelli”, 80138 Napoli, Italy;
- SYSBIO Centre of Systems Biology ISBE.ITALY, University of Milano-Bicocca, 20126 Milano, Italy
| | - Filippo Baldacci
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.M.); (E.D.); (G.S.); (F.B.)
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