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Wei Z, Wang X, Liu C, Feng Y, Gan Y, Shi Y, Wang X, Liu Y, Deng Y. Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach. Neuroimage 2024; 296:120683. [PMID: 38880308 DOI: 10.1016/j.neuroimage.2024.120683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 06/02/2024] [Accepted: 06/10/2024] [Indexed: 06/18/2024] Open
Abstract
Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.
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Affiliation(s)
- Zihan Wei
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China
| | - Xinpei Wang
- School of Aerospace Medicine, Fourth Military Medical University, Xi'an, China
| | - Chao Liu
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China
| | - Yan Feng
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China; Xi'an Medical University, Xi'an 710021, PR China
| | - Yajing Gan
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China
| | - Yuqing Shi
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China; Xi'an Medical University, Xi'an 710021, PR China
| | - Xiaoli Wang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China
| | - Yonghong Liu
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China
| | - Yanchun Deng
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, PR China.
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Rong R, Zhang R, Xu Y, Wang X, Wang H, Wang X. The Role of EEG microstates in predicting oxcarbazepine treatment outcomes in patients with newly-diagnosed focal epilepsy. Seizure 2024; 119:63-70. [PMID: 38796953 DOI: 10.1016/j.seizure.2024.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 05/10/2024] [Accepted: 05/22/2024] [Indexed: 05/29/2024] Open
Abstract
PURPOSE Microstates represent the global and topographical distribution of electrical brain activity from scalp-recorded EEG. This study aims to explore EEG microstates of patients with focal epilepsy prior to medication, and employ extracted microstate metrics for predicting treatment outcomes with Oxcarbazepine monotherapy. METHODS This study involved 25 newly-diagnosed focal epilepsy patients (13 females), aged 12 to 68, with various etiologies. Patients were categorized into Non-Seizure-Free (NSF) and Seizure-Free (SF) groups according to their first follow-up outcomes. From pre-medication EEGs, four representative microstates were identified by using clustering. The temporal parameters and transition probabilities of microstates were extracted and analyzed to discern group differences. With generating sample method, Support Vector Machine (SVM), Logistic Regression (LR), and Naïve Bayes (NB) classifiers were employed for predicting treatment outcomes. RESULTS In the NSF group, Microstate 1 (MS1) exhibited a significantly higher duration (mean±std. = 0.092±0.008 vs. 0.085±0.008, p = 0.047), occurrence (mean±std. = 2.587±0.334 vs. 2.260±0.278, p = 0.014), and coverage (mean±std. = 0.240±0.046 vs. 0.194±0.040, p = 0.014) compared to the SF group. Additionally, the transition probabilities from Microstate 2 (MS2) and Microstate 3 (MS3) to MS1 were increased. In MS2, the NSF group displayed a stronger correlation (mean±std. = 0.618±0.025 vs. 0.571±0.034, p < 0.001) and a higher global explained variance (mean±std. = 0.083±0.035 vs. 0.055±0.023, p = 0.027) than the SF group. Conversely, Microstate 4 (MS4) in the SF group demonstrated significantly greater coverage (mean±std. = 0.388±0.074 vs. 0.334±0.052, p = 0.046) and more frequent transitions from MS2 to MS4, indicating a distinct pattern. Temporal parameters contribute major predictive role in predicting treatment outcomes of Oxcarbazepine, with area under curves (AUCs) of 0.95, 0.70, and 0.86, achieved by LR, NB and SVM, respectively. CONCLUSION This study underscores the potential of EEG microstates as predictive biomarkers for Oxcarbazepine treatment responses in newly-diagnosed focal epilepsy patients.
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Affiliation(s)
- Rong Rong
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing Medical University, Nanjing 210008, Jiangsu, PR China
| | - Runkai Zhang
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, PR China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing Medical University, Nanjing 210008, Jiangsu, PR China
| | - Xiaoyun Wang
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing Medical University, Nanjing 210008, Jiangsu, PR China
| | - Haixian Wang
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, PR China.
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210008, Jiangsu, PR China.
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Fang S, Zhu C, Zhang J, Wu L, Zhang Y, Huang H, Lin W. EEG microstates in epilepsy with and without cognitive dysfunction: Alteration in intrinsic brain activity. Epilepsy Behav 2024; 154:109729. [PMID: 38513568 DOI: 10.1016/j.yebeh.2024.109729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 03/23/2024]
Abstract
OBJECTIVE This study aims to investigate the difference between epilepsy comorbid with and without cognitive dysfunction. METHOD Participants were classified into patients with epilepsy comorbid cognitive dysfunction (PCCD) and patients with epilepsy without comorbid cognitive dysfunction (nPCCD). Microstate analysis was applied based on 20-channel electroencephalography (EEG) to detect the dynamic changes in the whole brain. The coverage, occurrence per second, duration, and transition probability were calculated. RESULT The occurrence per second and the coverage of microstate B in the PCCD group were higher than that of the nPCCD group. Coverage in microstate D was lower in the PCCD group than in the nPCCD group. In addition, the PCCD group has a higher probability of A to B and B to A transitions and a lower probability of A to D and D to A transitions. CONCLUSION Our research scrutinizes the disparities observed within EEG microstates among epilepsy patients both with and without comorbid cognitive dysfunction. SIGNIFICANCE EEG microstate analysis offers a novel metric for assessing neuropsychiatric disorders and supplies evidence for investigating the mechanisms and the dynamic change of epilepsy comorbid cognitive dysfunction.
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Affiliation(s)
- Shenzhi Fang
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, PR China
| | - Chaofeng Zhu
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, PR China
| | - Jinying Zhang
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, PR China
| | - Luyan Wu
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, PR China
| | - Yuying Zhang
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, PR China
| | - Huapin Huang
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, PR China; Fujian Key Laboratory of Molecular Neurology, Fuzhou, PR China; Department of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, PR China.
| | - Wanhui Lin
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, PR China; Fujian Key Laboratory of Molecular Neurology, Fuzhou, PR China.
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Chen J, Jin L, Lin N. Utilization of EEG microstates as a prospective biomarker for assessing the impact of ketogenic diet in GLUT1-DS. Neurol Sci 2024:10.1007/s10072-024-07519-3. [PMID: 38589768 DOI: 10.1007/s10072-024-07519-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/02/2024] [Indexed: 04/10/2024]
Abstract
OBJECTIVE The aim of the study is to analyze microstate patterns in GLUT1-DS, both before and after the ketogenic diet (KD). METHODS We conducted microstate analysis of a patient with GLUT-1 DS and 27 healthy controls. A systematic literature review and meta-analysis was done. We compared the parameters of the patients with those of healthy controls and the incorporating findings in literature. RESULTS The durations of the patient were notably shorter, and the occurrence rates were longer than those of healthy controls and incorporating findings from the review. After 10 months of KD, the patient's microstate durations exhibited an increase from 53.05 ms, 57.17 ms, 61.80 ms, and 49.49 ms to 60.53 ms, 63.27 ms, 71.11 ms, and 66.55 ms. The occurrence rates changed from 4.0774 Hz, 4.9462 Hz, 4.8006 Hz, and 4.0579 Hz to 3.3354 Hz, 3.7893 Hz, 3.5956 Hz, and 4.1672 Hz. In healthy controls, the durations of microstate class A, B, C, and D were 61.86 ms, 63.58 ms, 70.57 ms, and 72.00 ms, respectively. CONCLUSIONS Our findings suggest EEG microstates may be a promising biomarker for monitoring the effect of KD. Administration of KD may normalize the dysfunctional patterns of temporal parameters.
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Affiliation(s)
- Jianhua Chen
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, 100730, China.
| | - Liri Jin
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, 100730, China.
| | - Nan Lin
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, 100730, China
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Kučikienė D, Rajkumar R, Timpte K, Heckelmann J, Neuner I, Weber Y, Wolking S. EEG microstates show different features in focal epilepsy and psychogenic nonepileptic seizures. Epilepsia 2024; 65:974-983. [PMID: 38289522 DOI: 10.1111/epi.17897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 01/12/2024] [Accepted: 01/12/2024] [Indexed: 04/16/2024]
Abstract
OBJECTIVE Electroencephalography (EEG) microstate analysis seeks to cluster the scalp's electric field into semistable topographical EEG activity maps at different time points. Our study aimed to investigate the features of EEG microstates in subjects with focal epilepsy and psychogenic nonepileptic seizures (PNES). METHODS We included 62 adult subjects with focal epilepsy or PNES who received video-EEG monitoring at the epilepsy monitoring unit. The subjects (mean age = 42.8 ± 21.2 years) were distributed equally between epilepsy and PNES groups. We extracted microstates from a 4.4 ± 1.0-min, 21-channel resting-state EEG. We excluded subjects with interictal epileptiform discharges during resting-state EEGs. After preprocessing, we derived five main EEG microstates-MS1 to MS5-for the full frequency band (1-30 Hz) and frequency subbands (delta, 1-4 Hz; theta, 4-8 Hz; alpha, 8-12 Hz; beta, 12-30 Hz), using the MATLAB-based EEGLAB toolkit. Statistical features of microstates (duration, occurrence, contribution, global field power [GFP]) were compared between the groups, using logistic regression corrected for age and sex. RESULTS We detected no differences in microstate parameters in the full frequency band. We found a longer duration (delta: B = -7.680, p = .046; theta: B = -16.200, p = .043) and a higher contribution (delta: B = -7.414, p = .035; theta: B = -7.509, p = .031) of MS4 in lower frequency bands in the epilepsy group. The PNES group showed a higher occurrence of MS5 in the delta subband (B = 3.283, p = .032). In the theta subband, a higher GFP of MS1 was associated with the PNES group (B = 5.674, p = .025), whereas a higher GFP of MS2 was associated with the epilepsy group (B = -6.579, p = .026). SIGNIFICANCE Microstate features show differences between patients with focal epilepsy and PNES. EEG microstates could be a promising parameter, helping to understand changes in brain dynamics in subjects with epilepsy, and should be explored as a potential biomarker.
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Affiliation(s)
- Domantė Kučikienė
- Department of Epileptology and Neurology, Rheinisch-Westfälische Technische Hochschule (RWTH) University Hospital Aachen, Aachen, Germany
| | - Ravichandran Rajkumar
- Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN-Translational Medicine, Jülich, Germany
- Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich, Jülich, Germany
| | - Katharina Timpte
- Department of Epileptology and Neurology, Rheinisch-Westfälische Technische Hochschule (RWTH) University Hospital Aachen, Aachen, Germany
| | - Jan Heckelmann
- Department of Epileptology and Neurology, Rheinisch-Westfälische Technische Hochschule (RWTH) University Hospital Aachen, Aachen, Germany
| | - Irene Neuner
- Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN-Translational Medicine, Jülich, Germany
- Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich, Jülich, Germany
| | - Yvonne Weber
- Department of Epileptology and Neurology, Rheinisch-Westfälische Technische Hochschule (RWTH) University Hospital Aachen, Aachen, Germany
| | - Stefan Wolking
- Department of Epileptology and Neurology, Rheinisch-Westfälische Technische Hochschule (RWTH) University Hospital Aachen, Aachen, Germany
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Daquin G, Bonini F. The landscape of drug resistant absence seizures in adolescents and adults: Pathophysiology, electroclinical spectrum and treatment options. Rev Neurol (Paris) 2024; 180:256-270. [PMID: 38413268 DOI: 10.1016/j.neurol.2023.11.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 11/17/2023] [Accepted: 11/21/2023] [Indexed: 02/29/2024]
Abstract
The persistence of typical absence seizures (AS) in adolescence and adulthood may reduce the quality of life of patients with genetic generalized epilepsies (GGEs). The prevalence of drug resistant AS is probably underestimated in this patient population, and treatment options are relatively scarce. Similarly, atypical absence seizures in developmental and epileptic encephalopathies (DEEs) may be unrecognized, and often persist into adulthood despite improvement of more severe seizures. These two seemingly distant conditions, represented by typical AS in GGE and atypical AS in DEE, share at least partially overlapping pathophysiological and genetic mechanisms, which may be the target of drug and neurostimulation therapies. In addition, some patients with drug-resistant typical AS may present electroclinical features that lie in between the two extremes represented by these generalized forms of epilepsy.
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Affiliation(s)
- G Daquin
- Epileptology and Cerebral Rythmology, AP-HM, Timone hospital, Marseille, France
| | - F Bonini
- Epileptology and Cerebral Rythmology, AP-HM, Timone hospital, Marseille, France; Aix Marseille Univ, Inserm, INS, Inst Neurosci Syst, Marseille, France.
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Zanesco AP. Normative Temporal Dynamics of Resting EEG Microstates. Brain Topogr 2024; 37:243-264. [PMID: 37702825 DOI: 10.1007/s10548-023-01004-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/23/2023] [Indexed: 09/14/2023]
Abstract
The large-scale electrophysiological events known as electroencephalographic microstates provide an important window into the intrinsic activity of whole-brain neuronal networks. The spontaneous activity of coordinated brain networks, including the ongoing temporal dynamics expressed by microstates, are thought to reflect individuals' neurocognitive functioning, and predict development, disease progression, and psychological differences among varied populations. A comprehensive understanding of human brain function therefore requires characterizing typical and atypical patterns in the temporal dynamics of microstates. But population-level estimates of normative microstate temporal dynamics are still unknown. To address this gap, I conducted a systematic search of the literature and accompanying meta-analysis of the average dynamics of microstates obtained from studies investigating spontaneous brain activity in individuals during periods of eyes-closed and eyes-open rest. Meta-analyses provided estimates of the average temporal dynamics of microstates across 93 studies totaling 6583 unique individual participants drawn from diverse populations. Results quantified the expected range of plausible estimates of average microstate dynamics across study samples, as well as characterized heterogeneity resulting from sampling variability and systematic differences in development, clinical diagnoses, or other study methodological factors. Specifically, microstate dynamics significantly differed for samples with specific developmental differences or clinical diagnoses, relative to healthy, typically developing samples. This research supports the notion that microstates and their dynamics reflect functionally relevant properties of large-scale brain networks, encoding typical and atypical neurocognitive functioning.
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Affiliation(s)
- Anthony P Zanesco
- Department of Psychology, University of Miami, Coral Gables, FL, USA.
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Mazzeo A, Cerulli Irelli E, Leodori G, Mancuso M, Morano A, Giallonardo AT, Di Bonaventura C. Resting-state electroencephalography microstates as a marker of photosensitivity in juvenile myoclonic epilepsy. Brain Commun 2024; 6:fcae054. [PMID: 38444911 PMCID: PMC10914451 DOI: 10.1093/braincomms/fcae054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 12/14/2023] [Accepted: 02/16/2024] [Indexed: 03/07/2024] Open
Abstract
Juvenile myoclonic epilepsy is an idiopathic generalized epilepsy syndrome associated with photosensitivity in approximately 30-40% of cases. Microstates consist of a brief period of time during which the topography of the whole resting-state electroencephalography signal is characterized by a specific configuration. Previous neurophysiological and neuroimaging studies have suggested that Microstate B may represent activity within the visual network. In this case-control study, we aimed to investigate whether anatomical and functional alterations in the visual network observed in individuals with photosensitivity could lead to changes in Microstate B dynamics in photosensitive patients with juvenile myoclonic epilepsy. Resting-state electroencephalography microstate analysis was performed on 28 patients with juvenile myoclonic epilepsy. Of these, 15 patients exhibited photosensitivity, while the remaining 13 served as non-photosensitive controls. The two groups were carefully matched in terms of age, sex, seizure control and anti-seizure medications. Multivariate analysis of variance and repeated-measures analysis of variance were performed to assess significant differences in microstate metrics and syntax between the photosensitive and the non-photosensitive group. Post hoc false discovery rate adjusted unpaired t-tests were used to determine differences in specific microstate classes between the two groups. The four classical microstates (Classes A, B, C and D) accounted for 72.8% of the total electroencephalography signal variance in the photosensitive group and 75.64% in the non-photosensitive group. Multivariate analysis of variance revealed a statistically significant class-group interaction on microstate temporal metrics (P = 0.021). False discovery rate adjusted univariate analyses of variance indicated a significant class-group interaction for both mean occurrence (P = 0.002) and coverage (P = 0.03), but not for mean duration (P = 0.14). Post hoc false discovery rate adjusted unpaired t-tests showed significantly higher coverage (P = 0.02) and occurrence (P = 0.04) of Microstate B in photosensitive patients compared with non-photosensitive participants, along with an increased probability of transitioning from Microstates C (P = 0.04) and D (P = 0.02) to Microstate B. No significant differences were found concerning the other microstate classes between the two groups. Our study provides novel insights on resting-state electroencephalography microstate dynamics underlying photosensitivity in patients with juvenile myoclonic epilepsy. The increased representation of Microstate B in these patients might reflect the resting-state overactivation of the visual system underlying photosensitivity. Further research is warranted to investigate microstate dynamics in other photosensitive epilepsy syndromes.
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Affiliation(s)
- Adolfo Mazzeo
- Department of Human Neurosciences, Sapienza University, Rome 00185, Italy
| | | | - Giorgio Leodori
- Department of Human Neurosciences, Sapienza University, Rome 00185, Italy
- IRCCS Neuromed, Pozzilli 86077, Italy
| | - Marco Mancuso
- Department of Human Neurosciences, Sapienza University, Rome 00185, Italy
| | - Alessandra Morano
- Department of Human Neurosciences, Sapienza University, Rome 00185, Italy
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Zhu C, Li J, Wei D, Wu L, Zhang Y, Huang H, Lin W. Intrinsic brain activity differences in perampanel-responsive and non-responsive drug-resistant epilepsy patients: an EEG microstate analysis. Ther Adv Neurol Disord 2024; 17:17562864241227293. [PMID: 38298737 PMCID: PMC10829497 DOI: 10.1177/17562864241227293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 01/03/2024] [Indexed: 02/02/2024] Open
Abstract
Background Drug-resistant epilepsy (DRE) patients exhibit aberrant large-scale brain networks. Perampanel may be a therapeutic option for controlling seizures in these patients. Objective We aim to explore the differences of resting-state electroencephalogram (EEG) microstate in perampanel-responsive and non-responsive DRE patients. Design Retrospective study. Methods Clinical data were collected from DRE patients who received perampanel treatment at the Fujian Medical University Union Hospital from June 2020 to September 2021, with a minimum follow-up of 6 months. Patients were classified into three groups based on the extent of reduction in seizure frequency: non-responsive (seizure reduction <50%), responsive (seizure reduction >50% but not seizure-free), and seizure-free. Resting-state EEG data sets of all participants were subjected to EEG microstate analysis. The study comprehensively compared the mean duration, frequency per second, and temporal coverage of each microstate among the three groups. Results A total of 76 perampanel-treated DRE patients were categorized into three groups based on their response to treatment: non-responsive (n = 20), responsive (n = 36), and seizure-free (n = 20), according to the degree of seizure frequency reduction. The results of EEG microstate analysis revealed no statistically significant distinctions in frequency, duration, and coverage of microstate D in these DRE patients. However, the seizure-free group showed significantly increased duration and coverage of microstate A, frequency and coverage of microstate B, and significantly decreased duration, frequency, and coverage of microstate C when compared with the other groups. Conclusion Microstate A, B, and D is associated with the sensorimotor network, visual network, salience network, and attention network, respectively. This study demonstrates statistically significant differences in the sensorimotor, visual, and salience networks, but not in the attention network, between perampanel-responsive and non-responsive DRE patients.
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Affiliation(s)
- Chaofeng Zhu
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Juan Li
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Dazhu Wei
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Luyan Wu
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yuying Zhang
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Huapin Huang
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
- Fujian Key Laboratory of Molecular Neurology, Fuzhou, China
- Department of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, China
| | - Wanhui Lin
- Department of Neurology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou 350001, Fujian, China
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Zhang H, Yang X, Yao L, Liu Q, Lu Y, Chen X, Wang T. EEG microstates analysis after TMS in patients with subacute stroke during the resting state. Cereb Cortex 2024; 34:bhad480. [PMID: 38112223 PMCID: PMC10793572 DOI: 10.1093/cercor/bhad480] [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: 09/01/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 12/21/2023] Open
Abstract
To investigate whether intermittent theta burst stimulation over the cerebellum induces changes in resting-state electroencephalography microstates in patients with subacute stroke and its correlation with cognitive and emotional function. Twenty-four stroke patients and 17 healthy controls were included in this study. Patients and healthy controls were assessed at baseline, including resting-state electroencephalography and neuropsychological scales. Fifteen patients received lateral cerebellar intermittent theta burst stimulation as well as routine rehabilitation training (intermittent theta burst stimulation-RRT group), whereas 9 patients received only conventional rehabilitation training (routine rehabilitation training group). After 2 wk, baseline data were recorded again in both groups. Stroke patients exhibited reduced parameters in microstate D and increased parameters in microstate C compared with healthy controls. However, after the administration of intermittent theta burst stimulation over the lateral cerebellum, significant alterations were observed in the majority of metrics for both microstates D and C. Lateral cerebellar intermittent theta burst stimulation combined with conventional rehabilitation has a stronger tendency to improve emotional and cognitive function in patients with subacute stroke than conventional rehabilitation. The improvement of mood and cognitive function was significantly associated with microstates C and D. We identified electroencephalography microstate spatiotemporal dynamics associated with clinical improvement following a course of intermittent theta burst stimulation therapy.
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Affiliation(s)
- Hongmei Zhang
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, Yunnan, China
| | - Xue Yang
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, Yunnan, China
| | - Liqing Yao
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, Yunnan, China
| | - Qian Liu
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, Yunnan, China
| | - Yihuan Lu
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, Yunnan, China
| | - Xueting Chen
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, Yunnan, China
| | - Tianling Wang
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, Yunnan, China
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Li Y, Wang L, Han Q, Han Q, Jiang L, Wu Y, Feng Y. Preoperative resting-state microstate as a marker for chronic pain after breast cancer surgery. Brain Behav 2023; 13:e3196. [PMID: 37496396 PMCID: PMC10570483 DOI: 10.1002/brb3.3196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/18/2023] [Accepted: 07/19/2023] [Indexed: 07/28/2023] Open
Abstract
INTRODUCTION Chronic postoperative pain poses challenges, emphasizing the importance of accurately predicting pain in advance. Generally, pain perception is associated with the temporal dynamics of the brain, which can be represented by microstates. Specifically, microstates are transient and patterned brain topographies formed by temporally overlapping and spatially synchronized oscillatory activities. Consequently, by characterizing brain activity, microstates offer valuable insights into pain perception. METHODS In this prospective study, 66 female patients undergoing breast cancer surgery were included. Their preoperative resting-state electroencephalography (EEG) was recorded. Preoperative resting-state EEG was recorded and four specific brain microstates (labeled as A, B, C, and D) were extracted. Temporal characteristics were then analyzed from these microstates. Patients were classified into two groups based on their Numerical Rating Scale (NRS) scores at three months postoperatively. Those with NRS scores ranging from 4 to 10 were classified as the high pain group, while patients with NRS ranging from 0 to 3 were classified as the lowpain group. Statistical analyses were performed to compare the microstate characteristics between these two groups. RESULTS Twenty-one patients (32%) were classified as the high pain group and forty-five (68%) as the low-pain group. The occurrence and coverage of microstate C were significantly higher in the high pain group. Additionally, there were significant differences in the microstates transitions between the two groups. Furthermore, the study revealed a positive correlation between the coverage of microstate C and the NRS. CONCLUSIONS Preoperative resting-state microstate features have shown correlations with postoperative pain. This study presents a novel and advanced perspective on the potential of microstates as a marker for postoperative pain.
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Affiliation(s)
- Yaru Li
- Department of AnesthesiologyPeking University People's HospitalBeijingChina
| | - Lu Wang
- Department of AnesthesiologyPeking University People's HospitalBeijingChina
| | - Qiaoyu Han
- Department of AnesthesiologyPeking University People's HospitalBeijingChina
| | - Qi Han
- Key Laboratory of Carcinogenesis and Translational ResearchMinistry of EducationBeijingChina
- Department of AnesthesiologyPeking University Cancer Hospital & InstituteBeijingChina
| | - Luyang Jiang
- Department of AnesthesiologyPeking University People's HospitalBeijingChina
| | - Yaqing Wu
- Department of AnesthesiologyPeking University People's HospitalBeijingChina
| | - Yi Feng
- Department of AnesthesiologyPeking University People's HospitalBeijingChina
- Department of Pain MedicinePeking University People's HospitalBeijingChina
- Key Laboratory for NeuroscienceMinistry of Education of China and National Health CommissionBeijingChina
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Gavaret M, Iftimovici A, Pruvost-Robieux E. EEG: Current relevance and promising quantitative analyses. Rev Neurol (Paris) 2023; 179:352-360. [PMID: 36907708 DOI: 10.1016/j.neurol.2022.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/02/2022] [Accepted: 12/06/2022] [Indexed: 03/12/2023]
Abstract
Electroencephalography (EEG) remains an essential tool, characterized by an excellent temporal resolution and offering a real window on cerebral functions. Surface EEG signals are mainly generated by the postsynaptic activities of synchronously activated neural assemblies. EEG is also a low-cost tool, easy to use at bed-side, allowing to record brain electrical activities with a low number or up to 256 surface electrodes. For clinical purpose, EEG remains a critical investigation for epilepsies, sleep disorders, disorders of consciousness. Its temporal resolution and practicability also make EEG a necessary tool for cognitive neurosciences and brain-computer interfaces. EEG visual analysis is essential in clinical practice and the subject of recent progresses. Several EEG-based quantitative analyses may complete the visual analysis, such as event-related potentials, source localizations, brain connectivity and microstates analyses. Some developments in surface EEG electrodes appear also, potentially promising for long term continuous EEGs. We overview in this article some recent progresses in visual EEG analysis and promising quantitative analyses.
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Affiliation(s)
- M Gavaret
- Université Paris Cité, INSERM UMR 1266, IPNP (Institute of Psychiatry and Neuroscience of Paris), France; Service de Neurophysiologie Clinique et Epileptologie, GHU Paris Psychiatrie et Neurosciences, Paris, France; FHU NeuroVasc, Paris, France.
| | - A Iftimovici
- Université Paris Cité, INSERM UMR 1266, IPNP (Institute of Psychiatry and Neuroscience of Paris), France; NeuroSpin, Atomic Energy Commission, Gif-sur-Yvette, France; Pôle PEPIT, GHU Paris Psychiatrie et Neurosciences, Paris, France
| | - E Pruvost-Robieux
- Université Paris Cité, INSERM UMR 1266, IPNP (Institute of Psychiatry and Neuroscience of Paris), France; Service de Neurophysiologie Clinique et Epileptologie, GHU Paris Psychiatrie et Neurosciences, Paris, France; FHU NeuroVasc, Paris, France
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Chen C, Han J, Zheng S, Zhang X, Sun H, Zhou T, Hu S, Yan X, Wang C, Wang K, Hu Y. Dynamic Changes of Brain Activity in Different Responsive Groups of Patients with Prolonged Disorders of Consciousness. Brain Sci 2022; 13:brainsci13010005. [PMID: 36671987 PMCID: PMC9856292 DOI: 10.3390/brainsci13010005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
As medical technology continues to improve, many patients diagnosed with brain injury survive after treatments but are still in a coma. Further, multiple clinical studies have demonstrated recovery of consciousness after transcranial direct current stimulation. To identify possible neurophysiological mechanisms underlying disorders of consciousness (DOCs) improvement, we examined the changes in multiple resting-state EEG microstate parameters after high-definition transcranial direct current stimulation (HD-tDCS). Because the left dorsolateral prefrontal cortex is closely related to consciousness, it is often chosen as a stimulation target for tDCS treatment of DOCs. A total of 21 patients diagnosed with prolonged DOCs were included in this study, and EEG microstate analysis of resting state EEG datasets was performed on all patients before and after interventions. Each of them underwent 10 anodal tDCS sessions of the left dorsolateral prefrontal cortex over 5 consecutive working days. According to whether the clinical manifestations improved, DOCs patients were divided into the responsive (RE) group and the non-responsive (N-RE) group. The dynamic changes of resting state EEG microstate parameters were also analyzed. After multiple HD-tDCS interventions, the duration and coverage of class C microstates in the RE group were significantly increased. This study also found that the transition between microstates A and C increased, while the transition between microstates B and D decreased in the responsive group. However, these changes in EEG microstate parameters in the N-RE group have not been reported. Our findings suggest that EEG neural signatures have the potential to assess consciousness states and that improvement in the dynamics of brain activity was associated with the recovery of DOCs. This study extends our understanding of the neural mechanism of DOCs patients in consciousness recovery.
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Affiliation(s)
- Chen Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Jinying Han
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Shuang Zheng
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Xintong Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Haibo Sun
- The First Clinical College of Anhui Medical University, Hefei 230032, China
| | - Ting Zhou
- Department of Neurology, The Second Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230001, China
| | - Shunyin Hu
- Department of Neurorehabilitation, Hefei Anhua Trauma Rehabilitation Hospital, Hefei 230011, China
| | - Xiaoxiang Yan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
| | - Changqing Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
- Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei 230032, China
| | - Yajuan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
- Correspondence: ; Tel.: +139-5691-2105
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EEG Markers of Treatment Resistance in Idiopathic Generalized Epilepsy: From Standard EEG Findings to Advanced Signal Analysis. Biomedicines 2022; 10:biomedicines10102428. [PMID: 36289690 PMCID: PMC9598660 DOI: 10.3390/biomedicines10102428] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 09/20/2022] [Accepted: 09/23/2022] [Indexed: 12/02/2022] Open
Abstract
Idiopathic generalized epilepsy (IGE) represents a common form of epilepsy in both adult and pediatric epilepsy units. Although IGE has been long considered a relatively benign epilepsy syndrome, a remarkable proportion of patients could be refractory to treatment. While some clinical prognostic factors have been largely validated among IGE patients, the impact of routine electroencephalography (EEG) findings in predicting drug resistance is still controversial and a growing number of authors highlighted the potential importance of capturing the sleep state in this setting. In addition, the development of advanced computational techniques to analyze EEG data has opened new opportunities in the identification of reliable and reproducible biomarkers of drug resistance in IGE patients. In this manuscript, we summarize the EEG findings associated with treatment resistance in IGE by reviewing the results of studies considering standard EEGs, 24-h EEG recordings, and resting-state protocols. We discuss the role of 24-h EEG recordings in assessing seizure recurrence in light of the potential prognostic relevance of generalized fast discharges occurring during sleep. In addition, we highlight new and promising biomarkers as identified by advanced EEG analysis, including hypothesis-driven functional connectivity measures of background activity and data-driven quantitative findings revealed by machine learning approaches. Finally, we thoroughly discuss the methodological limitations observed in existing studies and briefly outline future directions to identify reliable and replicable EEG biomarkers in IGE patients.
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