1
|
Cheng T, Hu Y, Qin X, Ma J, Zha D, Xie H, Ji T, Liu Q, Wang Z, Hao H, Wu Y, Li L. A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy. CNS Neurosci Ther 2024; 30:e14751. [PMID: 39015946 PMCID: PMC11252558 DOI: 10.1111/cns.14751] [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: 09/19/2023] [Revised: 04/22/2024] [Accepted: 04/23/2024] [Indexed: 07/18/2024] Open
Abstract
AIMS To predict the vagus nerve stimulation (VNS) efficacy for pediatric drug-resistant epilepsy (DRE) patients, we aim to identify preimplantation biomarkers through clinical features and electroencephalogram (EEG) signals and thus establish a predictive model from a multi-modal feature set with high prediction accuracy. METHODS Sixty-five pediatric DRE patients implanted with VNS were included and followed up. We explored the topological network and entropy features of preimplantation EEG signals to identify the biomarkers for VNS efficacy. A Support Vector Machine (SVM) integrated these biomarkers to distinguish the efficacy groups. RESULTS The proportion of VNS responders was 58.5% (38/65) at the last follow-up. In the analysis of parieto-occipital α band activity, higher synchronization level and nodal efficiency were found in responders. The central-frontal θ band activity showed significantly lower entropy in responders. The prediction model reached an accuracy of 81.5%, a precision of 80.1%, and an AUC (area under the receiver operating characteristic curve) of 0.838. CONCLUSION Our results revealed that, compared to nonresponders, VNS responders had a more efficient α band brain network, especially in the parieto-occipital region, and less spectral complexity of θ brain activities in the central-frontal region. We established a predictive model integrating both preimplantation clinical and EEG features and exhibited great potential for discriminating the VNS responders. This study contributed to the understanding of the VNS mechanism and improved the performance of the current predictive model.
Collapse
Affiliation(s)
- Tung‐yang Cheng
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
| | - Yingbing Hu
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
- Tsinghua‐Berkeley Shenzhen InstituteTsinghua UniversityShenzhenChina
| | - Xiaoya Qin
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
- Tsinghua‐Berkeley Shenzhen InstituteTsinghua UniversityShenzhenChina
| | - Jiayi Ma
- Department of PediatricsPeking University First HospitalBeijingChina
| | - Daqi Zha
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
| | - Han Xie
- Department of PediatricsPeking University First HospitalBeijingChina
| | - Taoyun Ji
- Department of PediatricsPeking University First HospitalBeijingChina
- Pediatric Epilepsy CenterPeking University First HospitalBeijingChina
| | - Qingzhu Liu
- Pediatric Epilepsy CenterPeking University First HospitalBeijingChina
| | - Zhiyan Wang
- CAS Key Laboratory of Mental Health, Institute of PsychologyChinese Academy of SciencesBeijingChina
- Department of PsychologyUniversity of Chinese Academy of SciencesBeijingChina
| | - Hongwei Hao
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
| | - Ye Wu
- Department of PediatricsPeking University First HospitalBeijingChina
- Pediatric Epilepsy CenterPeking University First HospitalBeijingChina
| | - Luming Li
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
- IDG/McGovern Institute for Brain Research at Tsinghua UniversityBeijingChina
| |
Collapse
|
2
|
Liu Z, Luo X, Yan-Do R, Wang Y, Xie X, Li Z, Cheng SH, Shi P. Vertebrates on a Chip: Noninvasive Electrical and Optical Mapping of Whole Brain Activity Associated with Pharmacological Treatments. ACS Chem Neurosci 2024; 15:2121-2131. [PMID: 38775291 DOI: 10.1021/acschemneuro.4c00158] [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] [Indexed: 06/06/2024] Open
Abstract
Mapping brain activities is necessary for understanding brain physiology and discovering new treatments for neurological disorders. Such efforts have greatly benefited from the advancement in technologies for analyzing neural activity with improving temporal or spatial resolution. Here, we constructed a multielectrode array based brain activity mapping (BAM) system capable of stabilizing and orienting zebrafish larvae for recording electroencephalogram (EEG) like local field potential (LFP) signals and brain-wide calcium dynamics in awake zebrafish. Particularly, we designed a zebrafish trap chip that integrates with an eight-by-eight surface electrode array, so that brain electrophysiology can be noninvasively recorded in an agarose-free and anesthetic-free format with a high temporal resolution of 40 μs, matching the capability typically achieved by invasive LFP recording. Benefiting from the specially designed hybrid system, we can also conduct calcium imaging directly on immobilized awake larval zebrafish, which further supplies us with high spatial resolution brain-wide activity data. All of these innovations reconcile the limitations of sole LFP recording or calcium imaging, emphasizing a synergy of combining electrical and optical modalities within one unified device for activity mapping across a whole vertebrate brain with both improved spatial and temporal resolutions. The compatibility with in vivo drug treatment further makes it suitable for pharmacology studies based on multimodal measurement of brain-wide physiology.
Collapse
Affiliation(s)
- Zhen Liu
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China
| | - Xuan Luo
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China
| | - Richard Yan-Do
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering Hong Kong Science Park, Hong Kong SAR
| | - Yuan Wang
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China
| | - Xi Xie
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510006, China
| | - Zhongping Li
- Institute of Environmental Science, Shanxi University, Taiyuan 030006, China
| | - Shuk Han Cheng
- Department of Biomedical Science, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China
| | - Peng Shi
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering Hong Kong Science Park, Hong Kong SAR
- Center of Super-Diamond and Advanced Films (COSDAF), City University of Hong Kong Kowloon, Hong Kong SAR
- Shenzhen Research Institute, City University of Hong Kong Shenzhen, Guangdong 518057, China
| |
Collapse
|
3
|
Di Gennaro G, Lattanzi S, Mecarelli O, Saverio Mennini F, Vigevano F. Current challenges in focal epilepsy treatment: An Italian Delphi consensus. Epilepsy Behav 2024; 155:109796. [PMID: 38643659 DOI: 10.1016/j.yebeh.2024.109796] [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: 12/21/2023] [Revised: 03/18/2024] [Accepted: 04/14/2024] [Indexed: 04/23/2024]
Abstract
BACKGROUND Epilepsy, a globally prevalent neurological condition, presents distinct challenges in management, particularly for focal-onset types. This study aimed at addressing the current challenges and perspectives in focal epilepsy management, with focus on the Italian reality. METHODS Using the Delphi methodology, this research collected and analyzed the level of consensus of a panel of Italian epilepsy experts on key aspects of focal epilepsy care. Areas of focus included patient flow, treatment pathways, controlled versus uncontrolled epilepsy, follow-up protocols, and the relevance of patient-reported outcomes (PROs). This method allowed for a comprehensive assessment of consensus and divergences in clinical opinions and practices. RESULTS The study achieved consensus on 23 out of 26 statements, with three items failing to reach a consensus. There was strong agreement on the importance of timely intervention, individualized treatment plans, regular follow-ups at Epilepsy Centers, and the role of PROs in clinical practice. In cases of uncontrolled focal epilepsy, there was a clear inclination to pursue alternative treatment options following the failure of two previous therapies. Divergent views were evident on the inclusion of epilepsy surgery in treatment for uncontrolled epilepsy and the routine necessity of EEG evaluations in follow-ups. Other key findings included concerns about the lack of pediatric-specific research limiting current therapeutic options in this patient population, insufficient attention to the transition from pediatric to adult care, and need for improved communication. The results highlighted the complexities in managing epilepsy, with broad consensus on patient care aspects, yet notable divergences in specific treatment and management approaches. CONCLUSION The study offered valuable insights into the current state and complexities of managing focal-onset epilepsy. It highlighted many deficiencies in the therapeutic pathway of focal-onset epilepsy in the Italian reality, while it also underscored the importance of patient-centric care, the necessity of early and appropriate intervention, and individualized treatment approaches. The findings also called for continued research, policy development, and healthcare system improvements to enhance epilepsy management, highlighting the ongoing need for tailored healthcare solutions in this evolving field.
Collapse
Affiliation(s)
| | - Simona Lattanzi
- Neurological Clinic, Department of Experimental and Clinical Medicine, Marche Polytechnic University, Ancona, Italy
| | - Oriano Mecarelli
- Department of Human Neurosciences, Sapienza University, Rome (Retired) and Past President of LICE, Italian League Against Epilepsy, Rome, Italy
| | - Francesco Saverio Mennini
- Faculty of Economics, Economic Evaluation and HTA (EEHTA), CEIS, University of Rome "Tor Vergata", Rome, Italy; Institute for Leadership and Management in Health, Kingston University London, London, UK.
| | - Federico Vigevano
- Head of Paediatric Neurorehabilitation Department, IRCCS San Raffaele, Rome, Italy.
| |
Collapse
|
4
|
Shafiezadeh S, Duma GM, Mento G, Danieli A, Antoniazzi L, Del Popolo Cristaldi F, Bonanni P, Testolin A. Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting. SENSORS (BASEL, SWITZERLAND) 2024; 24:2863. [PMID: 38732969 PMCID: PMC11086106 DOI: 10.3390/s24092863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/26/2024] [Accepted: 04/29/2024] [Indexed: 05/13/2024]
Abstract
The recent scientific literature abounds in proposals of seizure forecasting methods that exploit machine learning to automatically analyze electroencephalogram (EEG) signals. Deep learning algorithms seem to achieve a particularly remarkable performance, suggesting that the implementation of clinical devices for seizure prediction might be within reach. However, most of the research evaluated the robustness of automatic forecasting methods through randomized cross-validation techniques, while clinical applications require much more stringent validation based on patient-independent testing. In this study, we show that automatic seizure forecasting can be performed, to some extent, even on independent patients who have never been seen during the training phase, thanks to the implementation of a simple calibration pipeline that can fine-tune deep learning models, even on a single epileptic event recorded from a new patient. We evaluate our calibration procedure using two datasets containing EEG signals recorded from a large cohort of epileptic subjects, demonstrating that the forecast accuracy of deep learning methods can increase on average by more than 20%, and that performance improves systematically in all independent patients. We further show that our calibration procedure works best for deep learning models, but can also be successfully applied to machine learning algorithms based on engineered signal features. Although our method still requires at least one epileptic event per patient to calibrate the forecasting model, we conclude that focusing on realistic validation methods allows to more reliably compare different machine learning approaches for seizure prediction, enabling the implementation of robust and effective forecasting systems that can be used in daily healthcare practice.
Collapse
Affiliation(s)
- Sina Shafiezadeh
- Department of General Psychology, University of Padova, 35131 Padova, Italy; (G.M.); (F.D.P.C.)
| | - Gian Marco Duma
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS E. Medea, 31015 Conegliano, Italy; (G.M.D.); (A.D.); (L.A.); (P.B.)
| | - Giovanni Mento
- Department of General Psychology, University of Padova, 35131 Padova, Italy; (G.M.); (F.D.P.C.)
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Alberto Danieli
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS E. Medea, 31015 Conegliano, Italy; (G.M.D.); (A.D.); (L.A.); (P.B.)
| | - Lisa Antoniazzi
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS E. Medea, 31015 Conegliano, Italy; (G.M.D.); (A.D.); (L.A.); (P.B.)
| | | | - Paolo Bonanni
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS E. Medea, 31015 Conegliano, Italy; (G.M.D.); (A.D.); (L.A.); (P.B.)
| | - Alberto Testolin
- Department of General Psychology, University of Padova, 35131 Padova, Italy; (G.M.); (F.D.P.C.)
- Department of Mathematics, University of Padova, 35131 Padova, Italy
| |
Collapse
|
5
|
Yang Y, Luo S, Wang W, Gao X, Yao X, Wu T. From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications. Neuroimage Clin 2024; 42:103608. [PMID: 38653131 PMCID: PMC11059345 DOI: 10.1016/j.nicl.2024.103608] [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: 11/22/2023] [Revised: 04/14/2024] [Accepted: 04/16/2024] [Indexed: 04/25/2024]
Abstract
Magnetoencephalography (MEG) is a non-invasive technique that can precisely capture the dynamic spatiotemporal patterns of the brain by measuring the magnetic fields arising from neuronal activity along the order of milliseconds. Observations of brain dynamics have been used in cognitive neuroscience, the diagnosis of neurological diseases, and the brain-computer interface (BCI). In this study, we outline the basic principle, signal processing, and source localization of MEG, and describe its clinical applications for cognitive assessment, the diagnoses of neurological diseases and mental disorders, preoperative evaluation, and the BCI. This review not only provides an overall perspective of MEG, ranging from practical techniques to clinical applications, but also enhances the prevalent understanding of neural mechanisms. The use of MEG is expected to lead to significant breakthroughs in neuroscience.
Collapse
Affiliation(s)
- Yanling Yang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Shichang Luo
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Wenjie Wang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Xiumin Gao
- School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Xufeng Yao
- College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China.
| | - Tao Wu
- College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| |
Collapse
|
6
|
Dong X, Wen Y, Ji D, Yuan S, Liu Z, Shang W, Zhou W. Epileptic Seizure Detection with an End-to-End Temporal Convolutional Network and Bidirectional Long Short-Term Memory Model. Int J Neural Syst 2024; 34:2450012. [PMID: 38230571 DOI: 10.1142/s0129065724500126] [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] [Indexed: 01/18/2024]
Abstract
Automatic seizure detection plays a key role in assisting clinicians for rapid diagnosis and treatment of epilepsy. In view of the parallelism of temporal convolutional network (TCN) and the capability of bidirectional long short-term memory (BiLSTM) in mining the long-range dependency of multi-channel time-series, we propose an automatic seizure detection method with a novel end-to-end TCN-BiLSTM model in this work. First, raw EEG is filtered with a 0.5-45 Hz band-pass filter, and the filtered data are input into the proposed TCN-BiLSTM network for feature extraction and classification. Post-processing process including moving average filtering, thresholding and collar technique is then employed to further improve the detection performance. The method was evaluated on two EEG database. On the CHB-MIT scalp EEG database, our method achieved a segment-based sensitivity of 94.31%, specificity of 97.13%, and accuracy of 97.09%. Meanwhile, an event-based sensitivity of 96.48% and an average false detection rate (FDR) of 0.38/h were obtained. On the SH-SDU database we collected, the segment-based sensitivity of 94.99%, specificity of 93.25%, and accuracy of 93.27% were achieved. In addition, an event-based sensitivity of 99.35% and a false detection rate of 0.54/h were yielded. The total detection time consumed for 1[Formula: see text]h EEG data was 5.65[Formula: see text]s. These results demonstrate the superiority and promising potential of the proposed method in real-time monitoring of epileptic seizures.
Collapse
Affiliation(s)
- Xingchen Dong
- School of Integrated Circuits, Shandong University, Jinan 250100, P. R. China
- Shenzhen Institute of Shandong University, Shenzhen 518057, P. R. China
| | - Yiming Wen
- School of Integrated Circuits, Shandong University, Jinan 250100, P. R. China
- Shenzhen Institute of Shandong University, Shenzhen 518057, P. R. China
| | - Dezan Ji
- School of Integrated Circuits, Shandong University, Jinan 250100, P. R. China
- Shenzhen Institute of Shandong University, Shenzhen 518057, P. R. China
| | - Shasha Yuan
- School of Computer Science, Qufu Normal University, Rizhao 276826, P. R. China
| | - Zhen Liu
- Second Hospital of Shandong University, Jinan 250100, P. R. China
| | - Wei Shang
- Second Hospital of Shandong University, Jinan 250100, P. R. China
| | - Weidong Zhou
- School of Integrated Circuits, Shandong University, Jinan 250100, P. R. China
- Shenzhen Institute of Shandong University, Shenzhen 518057, P. R. China
| |
Collapse
|
7
|
Zhang X, Yu X, Tuo M, Zhao Z, Wang J, Jiang T, Zhang M, Wang Y, Sun Y. Parvalbumin neurons in the anterior nucleus of thalamus control absence seizures. Epilepsia Open 2023; 8:1002-1012. [PMID: 37277986 PMCID: PMC10472414 DOI: 10.1002/epi4.12771] [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: 03/08/2023] [Accepted: 06/03/2023] [Indexed: 06/07/2023] Open
Abstract
OBJECTIVE Anterior nucleus of thalamus (ANT) has been widely accepted as a potential therapeutic target for drug-resistant epilepsy. Although increased volume of the ANT was also reported in patients with absence epilepsy, the relationship between the ANT and absence epilepsy has been barely illustrated. METHODS Using chemogenetics, we evaluated the effect of ANT parvalbumin (PV) neurons on pentylenetetrazole (PTZ)-induced absence seizures in mice. RESULTS We found that intraperitoneal injection of PTZ (30 mg/kg) can stably induce absence-like seizures characterized by bilaterally synchronous spike-wave discharges (SWDs). Selective activation of PV neurons in the ANT by chemogenetics could aggravate the severity of absence seizures, whereas selective inhibition of that cannot reverse this condition and even promote absence seizures as well. Moreover, chemogenetic inhibition of ANT PV neurons without administration of PTZ was also sufficient to generate SWDs. Analysis of background EEG showed that chemogenetic activation or inhibition of ANT PV neurons could both significantly increase the EEG power of delta oscillation in the frontal cortex, which might mediate the pro-seizure effect of ANT PV neurons. SIGNIFICANCE Our findings indicated that either activation or inhibition of ANT PV neurons might disturb the intrinsic delta rhythms in the cortex and worsen absence seizures, which highlighted the importance of maintaining the activity of ANT PV neurons in absence seizure.
Collapse
Affiliation(s)
- Xiaohan Zhang
- Department of NeurologyThe Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdaoChina
| | - Xiaofeng Yu
- Department of NeurologyThe Eighth People's Hospital of QingdaoQingdaoChina
| | - Miao Tuo
- Department of NeurologyThe Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdaoChina
| | - Zhenran Zhao
- Department of NeurosurgeryLinyi Hospital of Traditional Chinese MedicineLinyiChina
| | - Junhong Wang
- Department of NeurologyThe Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdaoChina
| | - Tong Jiang
- Department of NeurologyThe Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdaoChina
| | - Mengwen Zhang
- Department of NeurologyThe Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdaoChina
| | - Ying Wang
- Institute of Neuropsychiatric DiseasesThe Affiliated Hospital of Qingdao University, Qingdao UniversityQingdaoChina
| | - Yanping Sun
- Department of NeurologyThe Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdaoChina
| |
Collapse
|
8
|
Sugden RJ, Pham-Kim-Nghiem-Phu VLL, Campbell I, Leon A, Diamandis P. Remote collection of electrophysiological data with brain wearables: opportunities and challenges. Bioelectron Med 2023; 9:12. [PMID: 37340487 DOI: 10.1186/s42234-023-00114-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 05/30/2023] [Indexed: 06/22/2023] Open
Abstract
Collection of electroencephalographic (EEG) data provides an opportunity to non-invasively study human brain plasticity, learning and the evolution of various neuropsychiatric disorders. Traditionally, due to sophisticated hardware, EEG studies have been largely limited to research centers which restrict both testing contexts and repeated longitudinal measures. The emergence of low-cost "wearable" EEG devices now provides the prospect of frequent and remote monitoring of the human brain for a variety of physiological and pathological brain states. In this manuscript, we survey evidence that EEG wearables provide high-quality data and review various software used for remote data collection. We then discuss the growing body of evidence supporting the feasibility of remote and longitudinal EEG data collection using wearables including a discussion of potential biomedical applications of these protocols. Lastly, we discuss some additional challenges needed for EEG wearable research to gain further widespread adoption.
Collapse
Affiliation(s)
- Richard James Sugden
- Department of Medical Biophysics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- Princess Margaret Cancer Center, University Health Network, 610 University Avenue, Toronto, ON, M5G 2C1, Canada
| | | | - Ingrid Campbell
- Princess Margaret Cancer Center, University Health Network, 610 University Avenue, Toronto, ON, M5G 2C1, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Alberto Leon
- Princess Margaret Cancer Center, University Health Network, 610 University Avenue, Toronto, ON, M5G 2C1, Canada
| | - Phedias Diamandis
- Department of Medical Biophysics, University of Toronto, Toronto, ON, M5S 1A8, Canada.
- Laboratory Medicine Program, University Health Network, 200 Elizabeth Street, Toronto, ON, M5G 2C4, Canada.
| |
Collapse
|
9
|
West J, Dasht Bozorgi Z, Herron J, Chizeck HJ, Chambers JD, Li L. Machine learning seizure prediction: one problematic but accepted practice. J Neural Eng 2023; 20. [PMID: 36548993 DOI: 10.1088/1741-2552/acae09] [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: 10/06/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022]
Abstract
Objective.Epilepsy is one of the most common neurological disorders and can have a devastating effect on a person's quality of life. As such, the search for markers which indicate an upcoming seizure is a critically important area of research which would allow either on-demand treatment or early warning for people suffering with these disorders. There is a growing body of work which uses machine learning methods to detect pre-seizure biomarkers from electroencephalography (EEG), however the high prediction rates published do not translate into the clinical setting. Our objective is to investigate a potential reason for this.Approach.We conduct an empirical study of a commonly used data labelling method for EEG seizure prediction which relies on labelling small windows of EEG data in temporal groups then selecting randomly from those windows to validate results. We investigate a confound for this approach for seizure prediction and demonstrate the ease at which it can be inadvertently learned by a machine learning system.Main results.We find that non-seizure signals can create decision surfaces for machine learning approaches which can result in false high prediction accuracy on validation datasets. We prove this by training an artificial neural network to learn fake seizures (fully decoupled from biology) in real EEG.Significance.The significance of our findings is that many existing works may be reporting results based on this confound and that future work should adhere to stricter requirements in mitigating this confound. The problematic, but commonly accepted approach in the literature for seizure prediction labelling is potentially preventing real advances in developing solutions for these sufferers. By adhering to the guidelines in this paper future work in machine learning seizure prediction is more likely to be clinically relevant.
Collapse
Affiliation(s)
- Joseph West
- School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia.,Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Zahra Dasht Bozorgi
- School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia
| | - Jeffrey Herron
- Department of Neurological Surgery, University of Washington, Seattle, Washington, United States of America
| | - Howard J Chizeck
- Department of Electrical and Computer Engineering, University of Washington, Seattle, Washington, United States of America
| | - Jordan D Chambers
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Lyra Li
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
10
|
Wu B, Xu W. Case report: Neonatal diabetes mellitus caused by KCNJ11 mutation presenting with intracranial hemorrhage. Front Neurol 2023; 14:1072078. [PMID: 36937531 PMCID: PMC10022729 DOI: 10.3389/fneur.2023.1072078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 02/06/2023] [Indexed: 03/06/2023] Open
Abstract
Neonatal diabetes mellitus (NDM) is a rare type of monogenic diabetes. At present, most published studies have focused on the types of gene mutations associated with NDM and the therapeutic effect of sulfonylureas (SUs) on the disease; few studies on NDM-associated intracranial hemorrhage (ICH) exist. In addition, p.V59M mutations generally lead to intermediate DEND (iDEND: intermediate developmental delay and neonatal diabetes) syndrome without epilepsy. Here, we present a case of a 1-month-old male infant who was diagnosed with NDM caused by a KCNJ11 missense mutation (p.V59M), presenting with cerebral injury. In the early stage of the disease, continuous insulin dose adjustment did not achieve an ideal level of blood glucose. Although blood glucose was subsequently controlled by oral SUs, which were administered after the genetic test result, the patient still displayed epilepsy and developmental delay. In this case report, we present our experience in the treatment of the infant, switching from insulin to oral SUs and we thought that SUs have limited effects on improving the prognosis of neurodevelopmental disturbances in NDM with foci of encephalomalacia. In addition, there may be a relationship between KCNJ11 missense mutations and cerebral injury, and further research must be carried out to confirm these points.
Collapse
|
11
|
Kirabira J, Rukundo GZ, Kibuuka M. Electroencephalogram utilization and psychiatric comorbidities among children and adolescents with epilepsy in rural Southwestern Uganda. Int J Psychiatry Med 2023; 58:56-68. [PMID: 35034513 DOI: 10.1177/00912174211058136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVE This study aimed at describing routine electroencephalogram (EEG) findings among children and adolescents with a clinical diagnosis of epilepsy and determines how interictal EEG abnormalities vary with the psychiatric comorbidities. METHODS We conducted a cross-sectional study among children and adolescents with epilepsy aged 5-18 years receiving care from a regional referral hospital in Southwestern Uganda. Psychiatric comorbidities were assessed using an adapted parent version of Child and Adolescent Symptom Inventory-5. Thirty-minute EEG samples were taken from routine EEG recordings that were locally performed and remotely interpreted for all participants. RESULTS Of the 140 participants, 71 (50.7%) had normal EEG findings and 51 (36.4%) had epileptiform abnormalities while 18 (12.9%) had non-epileptiform. Of those who had epileptiform abnormalities on EEG, 23 (45.1%) were focal, 26 (51.0%) were generalized, and 2 (3.9%) were focal with bilateral spread. There was no significant association between the different psychiatric comorbidities and the interictal EEG abnormalities. CONCLUSIONS Among children and adolescents with a clinical diagnosis of epilepsy in Southwestern Uganda, only 36% showed epileptiform abnormalities on their EEG recordings. There was no association between the interictal EEG abnormalities and psychiatric comorbidities.
Collapse
Affiliation(s)
- Joseph Kirabira
- Department of Psychiatry, Faculty of Medicine, 108123Mbarara University of Science and Technology, Mbarara, Uganda.,Department of Mental Health, 183050Busitema University - Mbale Campus, Mbale, Uganda.,Department of Mental Health and Psychiatry, Kampala International University, Western Campus, Bushenyi, Uganda
| | - Godfrey Z Rukundo
- Department of Psychiatry, Faculty of Medicine, 108123Mbarara University of Science and Technology, Mbarara, Uganda
| | - Moses Kibuuka
- Department of Clinical Neurophysiology, Royal London Hospital, Whitechapel, London, United Kingdom
| |
Collapse
|
12
|
Kawamura A, Yoshiike T, Matsuo M, Kadotani H, Oike Y, Kawasaki M, Kurumai Y, Nagao K, Takami M, Yamada N, Kuriyama K. Comparison of the usability of an automatic sleep staging program via portable 1-channel electroencephalograph and manual sleep staging with traditional polysomnography. Sleep Biol Rhythms 2023; 21:85-95. [PMID: 38468906 PMCID: PMC10899901 DOI: 10.1007/s41105-022-00421-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 08/16/2022] [Indexed: 10/15/2022]
Abstract
Automatic algorithms are a proposed alternative to manual assessment of polysomnography data for analyzing sleep structure; however, none are acceptably accurate for clinical use. We investigated the feasibility of an automated sleep stage scoring system called Sleep Scope, which is intended for use with portable 1-channel electroencephalograph, and compared it with the traditional polysomnography scoring method. Twenty-six outpatients and fourteen healthy volunteers underwent Sleep Scope and polysomnography assessments simultaneously. Polysomnography records were manually scored by three sleep experts. Sleep Scope records were scored using a dedicated auto-staging algorithm. Sleep parameters, including total sleep time, sleep latency, wake after sleep onset, and sleep efficiency, were calculated. The epoch-by-epoch pairwise concordance based on the classification of sleep into five stages (i.e., wake, rapid eye movement, N1, N2, and N3) was also evaluated after validating homogeneity and bias between Sleep Scope and polysomnography. Compared with polysomnography, Sleep Scope seemed to overestimate sleep latency by approximately 3 min, but there was no consistent tendency in bias in other sleep parameters. The Κ values ranged from 0.66 to 0.75 for experts' inter-rater polysomnography scores and from 0.62 to 0.67 for Sleep Scope versus polysomnography scores, which indicated sufficient agreement in the determination of sleep stages based on the Landis and Koch criteria. We observed sufficient concordance between Sleep Scope and polysomnography despite lower concordance in sleep disorder patients. Thus, this auto-staging system might serve as a novel clinical tool for reducing the time and expenses required of medical staff and patients. Supplementary Information The online version contains supplementary material available at 10.1007/s41105-022-00421-5.
Collapse
Affiliation(s)
- Aoi Kawamura
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
- Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551 Japan
| | - Takuya Yoshiike
- Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551 Japan
| | - Masahiro Matsuo
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
| | - Hiroshi Kadotani
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
| | - Yuki Oike
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
| | - Midori Kawasaki
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
| | - Yuichi Kurumai
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
| | - Kentaro Nagao
- Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551 Japan
| | - Masanori Takami
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
| | - Naoto Yamada
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
| | - Kenichi Kuriyama
- Department of Psychiatry, Shiga University of Medical Science, Otsu, Japan
- Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551 Japan
| |
Collapse
|
13
|
Li X, Huang Y, Lhatoo SD, Tao S, Vilella Bertran L, Zhang GQ, Cui L. A hybrid unsupervised and supervised learning approach for postictal generalized EEG suppression detection. Front Neuroinform 2022; 16:1040084. [PMID: 36601382 PMCID: PMC9806125 DOI: 10.3389/fninf.2022.1040084] [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: 09/08/2022] [Accepted: 11/07/2022] [Indexed: 12/23/2022] Open
Abstract
Sudden unexpected death of epilepsy (SUDEP) is a catastrophic and fatal complication of epilepsy and is the primary cause of mortality in those who have uncontrolled seizures. While several multifactorial processes have been implicated including cardiac, respiratory, autonomic dysfunction leading to arrhythmia, hypoxia, and cessation of cerebral and brainstem function, the mechanisms underlying SUDEP are not completely understood. Postictal generalized electroencephalogram (EEG) suppression (PGES) is a potential risk marker for SUDEP, as studies have shown that prolonged PGES was significantly associated with a higher risk of SUDEP. Automated PGES detection techniques have been developed to efficiently obtain PGES durations for SUDEP risk assessment. However, real-world data recorded in epilepsy monitoring units (EMUs) may contain high-amplitude signals due to physiological artifacts, such as breathing, muscle, and movement artifacts, making it difficult to determine the end of PGES. In this paper, we present a hybrid approach that combines the benefits of unsupervised and supervised learning for PGES detection using multi-channel EEG recordings. A K-means clustering model is leveraged to group EEG recordings with similar artifact features. We introduce a new learning strategy for training a set of random forest (RF) models based on clustering results to improve PGES detection performance. Our approach achieved a 5-second tolerance-based detection accuracy of 64.92%, a 10-second tolerance-based detection accuracy of 79.85%, and an average predicted time distance of 8.26 seconds with 286 EEG recordings using leave-one-out (LOO) cross-validation. The results demonstrated that our hybrid approach provided better performance compared to other existing approaches.
Collapse
Affiliation(s)
- Xiaojin Li
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, United States,Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Yan Huang
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, United States,Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Samden D. Lhatoo
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, United States,Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Shiqiang Tao
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, United States,Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Laura Vilella Bertran
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, United States,Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Guo-Qiang Zhang
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, United States,Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, TX, United States,School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States,*Correspondence: Guo-Qiang Zhang
| | - Licong Cui
- Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, TX, United States,School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States,Licong Cui
| |
Collapse
|
14
|
Apolot D, Erem G, Nassanga R, Kiggundu D, Tumusiime CM, Teu A, Mugisha AM, Sebunya R. Brain magnetic resonance imaging findings among children with epilepsy in two urban hospital settings, Kampala-Uganda: a descriptive study. BMC Med Imaging 2022; 22:175. [PMID: 36203127 PMCID: PMC9541090 DOI: 10.1186/s12880-022-00901-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Background Epilepsy is one of the most common neurological conditions in children worldwide. Its presentation is heterogeneous, with diverse underlying aetiology, clinical presentation, and prognosis. Structural brain abnormalities are among the recognized causes of epilepsy. Brain Magnetic Resonance Imaging (MRI) is the imaging modality of choice for epilepsy workup. We aimed to determine the prevalence and describe the structural abnormalities identified in the brain MRI studies performed on children with epilepsy from two urban hospitals in Kampala, Uganda. Methods This was a cross-sectional descriptive study performed at two urban hospital MRI centres. The study population was 147 children aged 1 day to 17 years with confirmed epilepsy. Brain MRI was performed for each child and a questionnaire was used to collect clinical data. Results The prevalence of structural abnormalities among children with epilepsy was 74.15% (109 out of 147). Of these, 68.81% were male, and the rest were female. Among these, the majority, 40.14% (59 of 144) were aged 1 month to 4 years. Acquired structural brain abnormalities were the commonest at 69.22% with hippocampal sclerosis (HS) leading while disorders of cortical development were the most common congenital causes. An abnormal electroencephalogram (EEG) was significant for brain MRI abnormalities among children with epilepsy with 95% of participants with an abnormal EEG study having epileptogenic structural abnormalities detected in their brain MRI studies. Conclusion and recommendation Two-thirds of children with epilepsy had structural brain abnormalities. Abnormal activity in the EEG study was found to positively correlate with abnormal brain MRI findings. As such, EEG study should be considered where possible before MRI studies as a determinant for children with epilepsy who will be having imaging studies done in the Ugandan setting.
Collapse
Affiliation(s)
- Denise Apolot
- Department of Radiology, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
| | - Geoffrey Erem
- Department of Radiology, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Rita Nassanga
- Department of Radiology, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Daniel Kiggundu
- Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Crescent Max Tumusiime
- Department of Radiology, Mother Kevin Postgraduate Medical School, Uganda Martyrs University School of Medicine, Kampala, Uganda.,St.Francis hospital, Nsambya, Uganda
| | - Anneth Teu
- Department of Radiology, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Alex Mwesigwa Mugisha
- Department of Radiology, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Robert Sebunya
- Department of Pediatrics, Mother Kevin Postgraduate Medical School, Uganda Martyrs University School of Medicine, Kampala, Uganda.,St.Francis hospital, Nsambya, Uganda
| |
Collapse
|
15
|
Luján MÁ, Sotos JM, Santos JL, Borja AL. Accurate neural network classification model for schizophrenia disease based on electroencephalogram data. INT J MACH LEARN CYB 2022. [DOI: 10.1007/s13042-022-01668-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2022]
|
16
|
Nascimento CP, Ferreira LO, da Silva ALM, da Silva ABN, Rodrigues JCM, Teixeira LL, Azevedo JEC, de Araujo DB, Hamoy AO, Gonçalves BH, Coelho BHDO, Lopes DCF, Hamoy M. A Combination of Curcuma longa and Diazepam Attenuates Seizures and Subsequent Hippocampal Neurodegeneration. Front Cell Neurosci 2022; 16:884813. [PMID: 35774084 PMCID: PMC9237424 DOI: 10.3389/fncel.2022.884813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 05/16/2022] [Indexed: 11/17/2022] Open
Abstract
Epilepsy is one of the most common neurological disorders, which occurs due to the instability in the inhibitory and excitatory synaptic transmissions in the brain. However, many patients develop resistance to the available drugs, which results in cell degeneration caused due to inadequate control of the seizures. Curcumin, Curcuma longa, is known to be effective for the treatment of organic disorders and may prevent seizures, reduce oxidative stress, and decrease brain damage. Given this, the present study evaluated the antiepileptic effects of C. longa in comparison with both the diazepam and the combined application of these two substances, in terms of their effects on the brain activity and the potential histopathological changes in the hippocampus. This study used male Wistar rats (age: 10–12 weeks; weight: 260 ± 20 g), which were pretreated for 4 days with either saline, C. longa, diazepam, or C. longa + diazepam; and on the fifth day, pentylenetetrazol (PTZ) was administered to induce the seizure. In the C. longa group, a significant increase was observed in the latency of the onset of seizure-related behavior. Surprisingly, however, the combined treatment resulted in the best control of the seizure-related behavior, with the greatest latency of the onset of spasms and isolated clonic seizures. This group also obtained the best results in the electroencephalographic trace and seizure control, with a reduction in the frequency and amplitude of the spike-waves. In the saline group, PTZ significantly reduced the number of cells present in the CA1 and CA3 regions of the hippocampus, while the combined treatment obtained the best results in terms of the preservation of the neuron-like cells. These findings indicate that C. longa may contribute to the control of both seizures and the cell damage induced by PTZ, and that its association with diazepam may be a potentially effective option for the treatment of epilepsy in the future.
Collapse
Affiliation(s)
- Chirlene Pinheiro Nascimento
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Luan Oliveira Ferreira
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Alex Luiz Menezes da Silva
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Ana Beatriz Nardelli da Silva
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Joao Cleiton Martins Rodrigues
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Leonan Lima Teixeira
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
| | - Julianne Elba Cunha Azevedo
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Daniella Bastos de Araujo
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Akira Otake Hamoy
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Beatriz Holanda Gonçalves
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Brenda Hosana De Oliveira Coelho
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
| | - Dielly Catrina Favacho Lopes
- Laboratory of Experimental Neuropathology, João de Barros Barreto University Hospital, Federal University of Pará, Belém, Brazil
- *Correspondence: Dielly Catrina Favacho Lopes,
| | - Moisés Hamoy
- Laboratory of Pharmacology and Toxicology of Natural Products, Institute Biological Science, Federal University of Pará, Belém, Brazil
- Moisés Hamoy,
| |
Collapse
|
17
|
Liang Z, Chen S, Zhang J. Feature Extraction of the Brain's Dynamic Complex Network Based on EEG and a Framework for Discrimination of Pediatric Epilepsy. SENSORS 2022; 22:s22072553. [PMID: 35408168 PMCID: PMC9003013 DOI: 10.3390/s22072553] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 03/22/2022] [Accepted: 03/24/2022] [Indexed: 02/04/2023]
Abstract
Most of the current complex network studies about epilepsy used the electroencephalogram (EEG) to directly construct the static complex network for analysis and discarded the dynamic characteristics. This study constructed the dynamic complex network on EEG from pediatric epilepsy and pediatric control when they were asleep by the sliding window method. Dynamic features were extracted and incorporated into various machine learning classifiers to explore their classification performances. We compared these performances between the static and dynamic complex network. In the univariate analysis, the initially insignificant topological characteristics in the static complex network can be transformed to be significant in the dynamic complex network. Under most connectivity calculation methods between leads, the accuracy of using dynamic complex network features for discrimination was higher than that of static complex network features. Particularly in the imaginary part of the coherency function (iCOH) method under the full-frequency band, the discrimination accuracies of most machine learning classifiers were higher than 95%, and the discrimination accuracies in the higher-frequency band (beta-frequency band) and the full-frequency band were higher than that of the lower-frequency bands. Our proposed method and framework could efficiently summarize more time-varying features in the EEG and improve the accuracies of the discrimination of the machine learning classifiers more than using static complex network features.
Collapse
|
18
|
Ding X, Zhou J, Zhao L, Chen M, Wang S, Zhang M, Zhang X, Jiang G. Intestinal Flora Composition Determines Microglia Activation and Improves Epileptic Episode Progress. Front Cell Infect Microbiol 2022; 12:835217. [PMID: 35356535 PMCID: PMC8959590 DOI: 10.3389/fcimb.2022.835217] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 02/16/2022] [Indexed: 11/13/2022] Open
Abstract
In response to environmental stimuli, immune memory mediates the plasticity of myeloid cells. Immune training and immune tolerance are two aspects of plasticity. Microglia that are immunologically trained or immunologically tolerant are endowed with a tendency to differentiate into alternative dominant phenotypes (M1/M2). Male C57BL/6 mice (immune-training group, immune-tolerant group, and control group) were used to establish the kainic acid epilepsy model. The seizure grade, duration, latency, hippocampal potential, and energy density were used to evaluate seizures, and the changes in the polarization of microglia were detected by western blot. 16S rDNA sequencing showed that the abundance of Ruminococcus in the immune-tolerant group was the dominant flora. Our research connections Intestinal microorganisms, brain immune status, and epilepsy behavior together. Pro-inflammatory M1 phenotype and anti-inflammatory M2 phenotype mediate and enhance and suppress subsequent inflammation, respectively. We conclude that intestinal microorganisms influence the occurrence and development of epilepsy by regulating the polarization of microglia.
Collapse
|
19
|
Chang L, Wang R, Zhang Y. Decoding SSVEP patterns from EEG via multivariate variational mode decomposition-informed canonical correlation analysis. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103209] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
|
20
|
Detection of Epilepsy in EEGs Using Deep Sequence Models – A Comparative Study. PATTERN RECOGNITION AND IMAGE ANALYSIS 2022. [DOI: 10.1007/978-3-031-04881-4_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
21
|
Jaseja H. Pedunculopontine Nucleus--Rapid Eye Movement Sleep--Electroencephalogram--Desynchronization (PRED) Axis in the Evolution of Epilepsy: A Novel Concept. J Epilepsy Res 2021; 11:1-5. [PMID: 34395217 PMCID: PMC8357554 DOI: 10.14581/jer.21001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 02/28/2021] [Accepted: 03/07/2021] [Indexed: 11/03/2022] Open
Abstract
Epilepsy is one of the commonest and oldest neurological diseases in the history of mankind, the exact pathophysiology of the evolution of which still remains elusive. The intimate and intriguing relation between epilepsy and sleep has been known for a long time. Rapid eye movement sleep (REMS) is well documented to exert potent antiepileptic action in human epilepsies and the underlying mechanism of which is largely based on its property to induce widespread electroencephalogram (EEG)-desynchronization. The pedunculopontine nucleus (PPN) owing to its property to enhance REMS has recently been under study for its potential role in intractable epilepsy (IE) and has been proposed as a novel deep brain stimulation target in IE. This brief paper unfolds the existing role of PPN, REMS, and EEG-desynchronization (PRED) in the evolution of epilepsy in an axial manner, the realization and comprehension of which is likely to open new avenues for further understanding of epileptogenesis, improved treatment of epilepsy and reducing the risk of IE.
Collapse
|
22
|
Gobbo D, Scheller A, Kirchhoff F. From Physiology to Pathology of Cortico-Thalamo-Cortical Oscillations: Astroglia as a Target for Further Research. Front Neurol 2021; 12:661408. [PMID: 34177766 PMCID: PMC8219957 DOI: 10.3389/fneur.2021.661408] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 05/11/2021] [Indexed: 12/21/2022] Open
Abstract
The electrographic hallmark of childhood absence epilepsy (CAE) and other idiopathic forms of epilepsy are 2.5-4 Hz spike and wave discharges (SWDs) originating from abnormal electrical oscillations of the cortico-thalamo-cortical network. SWDs are generally associated with sudden and brief non-convulsive epileptic events mostly generating impairment of consciousness and correlating with attention and learning as well as cognitive deficits. To date, SWDs are known to arise from locally restricted imbalances of excitation and inhibition in the deep layers of the primary somatosensory cortex. SWDs propagate to the mostly GABAergic nucleus reticularis thalami (NRT) and the somatosensory thalamic nuclei that project back to the cortex, leading to the typical generalized spike and wave oscillations. Given their shared anatomical basis, SWDs have been originally considered the pathological transition of 11-16 Hz bursts of neural oscillatory activity (the so-called sleep spindles) occurring during Non-Rapid Eye Movement (NREM) sleep, but more recent research revealed fundamental functional differences between sleep spindles and SWDs, suggesting the latter could be more closely related to the slow (<1 Hz) oscillations alternating active (Up) and silent (Down) cortical activity and concomitantly occurring during NREM. Indeed, several lines of evidence support the fact that SWDs impair sleep architecture as well as sleep/wake cycles and sleep pressure, which, in turn, affect seizure circadian frequency and distribution. Given the accumulating evidence on the role of astroglia in the field of epilepsy in the modulation of excitation and inhibition in the brain as well as on the development of aberrant synchronous network activity, we aim at pointing at putative contributions of astrocytes to the physiology of slow-wave sleep and to the pathology of SWDs. Particularly, we will address the astroglial functions known to be involved in the control of network excitability and synchronicity and so far mainly addressed in the context of convulsive seizures, namely (i) interstitial fluid homeostasis, (ii) K+ clearance and neurotransmitter uptake from the extracellular space and the synaptic cleft, (iii) gap junction mechanical and functional coupling as well as hemichannel function, (iv) gliotransmission, (v) astroglial Ca2+ signaling and downstream effectors, (vi) reactive astrogliosis and cytokine release.
Collapse
Affiliation(s)
- Davide Gobbo
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany
| | - Anja Scheller
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany
| | - Frank Kirchhoff
- Molecular Physiology, Center for Integrative Physiology and Molecular Medicine (CIPMM), University of Saarland, Homburg, Germany
| |
Collapse
|
23
|
McIntosh AM, Tan KM, Hakami TM, Newton MR, Carney PW, Yang M, Saya S, Marco DJT, Perucca P, Kwan P, O’Brien TJ, Berkovic SF. Newly diagnosed seizures assessed at two established first seizure clinics: Clinic characteristics, investigations, and findings over 11 years. Epilepsia Open 2021; 6:171-180. [PMID: 33681660 PMCID: PMC7918310 DOI: 10.1002/epi4.12460] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 11/12/2020] [Accepted: 12/14/2020] [Indexed: 11/11/2022] Open
Abstract
Objective 'First seizure' clinics (FSCs) aim to achieve early expert assessment for individuals with possible new-onset epilepsy. These clinics also have substantial potential for research into epilepsy evolution, outcomes, and costs. However, a paucity of FSCs details has implications for interpretation and utilization of this research. Methods We reviewed investigation findings over 11 years (2000-2010) from two established independent FSCs at Austin Health (AH) and Royal Melbourne Hospital (RMH), Australia. These adult clinics are in major public hospitals and operate with similar levels of expertise. Organizational differences include screening and dedicated administration at AH. Included were N = 1555 patients diagnosed with new-onset unprovoked seizures/epilepsy (AH n = 901, RMH n = 654). Protocol-driven interviews and investigations had been recorded prospectively and were extracted from medical records for study. Results Median patient age was 37 (IQR 26-52, range 18-94) years (AH 34 vs RMH 42 years; P < .001). Eighty-six percent of patients attended FSC within three weeks postindex seizure (median AH 12 vs RMH 25 days; P < .01). By their first appointment, 42% had experienced ≥2 seizures. An EEG was obtained within three weeks postindex seizure in 73% of patients, demonstrating epileptiform discharges in 25% (AH 33% vs RMH 15%). Seventy-six percent of patients had an MRI within 6 weeks. Of those with imaging (n = 1500), 19% had potentially epileptogenic abnormalities (RMH 28% vs AH 12%; P < .01). At both sites, changes due to previous stroke/hemorrhage were the commonest lesions, followed by traumatic brain injury. ≥WHO level 1 brain tumors diagnosed at presentation comprised a very small proportion (<1%) at each clinic. At both sites, epilepsy type could be determined in 60% of patients; RMH had more focal and AH more generalized epilepsy diagnoses. Significance Differences between the clinics' administrative and screening practices may contribute to differences in investigation findings. Insight into these differences will facilitate interpretation and utilization, and planning of future research.
Collapse
Affiliation(s)
- Anne M. McIntosh
- The Melbourne Brain CentreThe Department of MedicineThe University of MelbourneMelbourneAustralia
- The Department of NeurologyThe Royal Melbourne HospitalMelbourneAustralia
- Epilepsy Research CentreDepartment of Medicine (Austin Health)University of MelbourneMelbourneAustralia
- Department of NeuroscienceCentral Clinical SchoolMonash UniversityMelbourneAustralia
| | - K. Meng Tan
- The Melbourne Brain CentreThe Department of MedicineThe University of MelbourneMelbourneAustralia
- The Department of NeurologyThe Royal Melbourne HospitalMelbourneAustralia
- Gold Coast University Medical CentreSouthportAustralia
| | - Tahir M. Hakami
- The Melbourne Brain CentreThe Department of MedicineThe University of MelbourneMelbourneAustralia
- The Faculty of MedicineUniversity of JazanJazanSaudi Arabia
| | - Mark R. Newton
- Epilepsy Research CentreDepartment of Medicine (Austin Health)University of MelbourneMelbourneAustralia
- Department of NeurologyAustin HealthHeidelbergAustralia
| | - Patrick W. Carney
- Department of NeurologyAustin HealthHeidelbergAustralia
- Florey Institute of Neuroscience and Mental HealthParkvilleAustralia
- Department of MedicineMonash UniversityMelbourneAustralia
- Eastern HealthBox HillAustralia
| | - Mengjiazhi Yang
- The Melbourne Brain CentreThe Department of MedicineThe University of MelbourneMelbourneAustralia
- The Department of NeurologyThe Royal Melbourne HospitalMelbourneAustralia
| | - Sibel Saya
- Epilepsy Research CentreDepartment of Medicine (Austin Health)University of MelbourneMelbourneAustralia
- Centre for Cancer ResearchThe University of MelbourneMelbourneAustralia
- Department of General PracticeThe University of MelbourneMelbourneAustralia
| | - David J. T. Marco
- Epilepsy Research CentreDepartment of Medicine (Austin Health)University of MelbourneMelbourneAustralia
- Centre for Palliative CareSt Vincent’s HospitalMelbourneAustralia
| | - Piero Perucca
- The Melbourne Brain CentreThe Department of MedicineThe University of MelbourneMelbourneAustralia
- The Department of NeurologyThe Royal Melbourne HospitalMelbourneAustralia
- Department of NeuroscienceCentral Clinical SchoolMonash UniversityMelbourneAustralia
- Department of NeurologyAlfred HealthMelbourneAustralia
| | - Patrick Kwan
- The Melbourne Brain CentreThe Department of MedicineThe University of MelbourneMelbourneAustralia
- The Department of NeurologyThe Royal Melbourne HospitalMelbourneAustralia
- Department of NeuroscienceCentral Clinical SchoolMonash UniversityMelbourneAustralia
- Department of MedicineMonash UniversityMelbourneAustralia
- Department of NeurologyAlfred HealthMelbourneAustralia
| | - Terence J. O’Brien
- The Melbourne Brain CentreThe Department of MedicineThe University of MelbourneMelbourneAustralia
- The Department of NeurologyThe Royal Melbourne HospitalMelbourneAustralia
- Department of NeuroscienceCentral Clinical SchoolMonash UniversityMelbourneAustralia
- Department of NeurologyAlfred HealthMelbourneAustralia
| | - Samuel F. Berkovic
- Epilepsy Research CentreDepartment of Medicine (Austin Health)University of MelbourneMelbourneAustralia
- Department of NeurologyAustin HealthHeidelbergAustralia
| |
Collapse
|
24
|
Dordevic M, Gruber J, Schmitt FC, Mueller N. Impairments in path integration, rotational memory and balancing in patients with temporal lobe epilepsy. BMJ Neurol Open 2020; 2:e000077. [PMID: 33681800 PMCID: PMC7903167 DOI: 10.1136/bmjno-2020-000077] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/17/2020] [Accepted: 08/23/2020] [Indexed: 11/08/2022] Open
Abstract
Objectives The vestibulo-medial temporal lobe (MTL) axis model proposes that the vestibular system and the MTL are tightly linked both structurally and functionally so that alterations of one structure should entail disturbances in the other. Accordingly, patients with temporal lobe epilepsy (TLE) with their functional and possible structural temporal lobe pathology should show deficits in vestibular-related behaviour. This study aimed at assessing behavioural deficits related to a suspected disturbance of the vestibulo-MTL axis in patients with TLE. Methods Twenty patients with TLE (46.7±15.1 years, seven females) and their age-matched and gender-matched controls (46.7±15.1, seven females) underwent three test batteries that challenged vestibular and MTL functions: balancing, path integration (triangle completion test) and rotational memory. In addition, participants underwent a structural MRI for grey matter analysis using voxel-based morphometry. Results Compared with controls, patients with TLE showed significantly inferior performance in all three behavioural tests, with large effect sizes. There were no significant grey matter differences between the two groups. Conclusion These results indicate a potential disturbance in the vestibulo-MTL axis in TLE; these are to be verified by future large-scale studies. In the current study, these behavioural deficits emerged without evidence of any brain volume differences between the patients and their controls as depicted by high-resolution MRI. This speaks for a dissociation between functional and structural alterations in TLE.
Collapse
Affiliation(s)
- Milos Dordevic
- Department of Neurology, Otto-von-Guericke-Universitat Magdeburg Medizinische Fakultät, Magdeburg, Sachsen-Anhalt, Germany.,DZNE, Magdeburg, Sachsen-Anhalt, Germany
| | | | - Friedhelm C Schmitt
- Department of Neurology, Otto-von-Guericke-Universitat Magdeburg Medizinische Fakultät, Magdeburg, Sachsen-Anhalt, Germany
| | - Notger Mueller
- Department of Neurology, Otto-von-Guericke-Universitat Magdeburg Medizinische Fakultät, Magdeburg, Sachsen-Anhalt, Germany.,DZNE, Magdeburg, Sachsen-Anhalt, Germany
| |
Collapse
|
25
|
Puteikis K, Streckytė D, Pociuvienė G, Wolf P, Mameniškienė R. How are results of EEG activation procedures associated with patient perception of seizure provocative factors? A single-center cross-sectional pilot study. Epilepsy Res 2020; 167:106438. [PMID: 32810766 DOI: 10.1016/j.eplepsyres.2020.106438] [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: 03/23/2020] [Revised: 07/02/2020] [Accepted: 08/01/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE The purpose of this study was to examine the relationship between subjectively perceived seizure provocative factors or inhibitors and objectively recorded changes in epileptiform activity (EA) during EEG activation procedures. MATERIAL AND METHODS Consenting epilepsy patients (≥18 years old) were asked to complete a questionnaire by indicating whether items on a list provoke, inhibit or have no effect on their seizures. A scalp EEG was recorded afterwards to evaluate baseline epileptiform activity and its change (increase/decrease in frequency) during a set of activation procedures. These included hyperventilation, intermittent photic stimulation (IPS), eye-closing/eye-opening, tasks of reading aloud in a native and a foreign language, solving a Rubik's cube and crossing-out letters. We used correlation and multiple regression analysis to search for associations between the sum of self-reported provocative/inhibiting items and changes in EA. RESULTS Of the 90 patients recruited 75 (83.3%) indicated at least one seizure provocative factor. Sleep deprivation, emotional stress, negative emotions and alcohol use were most frequently selected as provoking seizures. Positive feelings, focused thinking, mental calculation and exercising were the most predominant seizure inhibitors. EEG data revealed a weak, but statistically significant correlation with the sum of items in distinct questionnaire groups (0.20 ≤ Spearman's ρ ≤ 0.39). Sensory stimuli (olfactory, gustatory, auditory and visual), cognitive phenomena (thoughts and feelings) and substance use were found to be significantly correlated with EEG results by being self-reported as both provoking and inhibiting seizures. A statistically significant relationship was also found between the increase in EA while reading aloud in a native language and the number of physiological states (sleep deprivation, stress etc.) indicated as provoking seizures (Spearman's ρ = 0.320, P = 0.005). A suitable stepwise multiple regression model was feasible for this finding (F(3, 71) = 7.396, P < 0.001, adjusted R squared = 0.206) with the additional inclusion of EA change during IPS and epilepsy type as explanatory variables. CONCLUSION Our pilot study indicates that there is a previously non-explored association between patients' self-perception of seizure provocative/inhibiting factors and objectively recorded changes in epileptiform activity during activation EEGs. Distinct EEG tests might be useful in activating ictogenic networks that are sensitive to indirect influence by hormonal, emotional or diurnally variable factors.
Collapse
Affiliation(s)
- Kristijonas Puteikis
- Vilnius University, Faculty of Medicine, Vilnius, Lithuania; M. K. Čiurlionio str. 21, LT-03101, Vilnius, Lithuania.
| | - Dovilė Streckytė
- Vilnius University, Faculty of Medicine, Vilnius, Lithuania; M. K. Čiurlionio str. 21, LT-03101, Vilnius, Lithuania
| | - Gabrielė Pociuvienė
- Vilnius University, Faculty of Medicine, Vilnius, Lithuania; M. K. Čiurlionio str. 21, LT-03101, Vilnius, Lithuania
| | - Peter Wolf
- Danish Epilepsy Centre Filadelfia, Dianalund, Denmark; Programa de Pós-Graduação em Ciências Médicas, Universidad Federal de Santa Catarina, Florianópolis, SC, Brazil
| | | |
Collapse
|
26
|
Chang S, Wei X, Su F, Liu C, Yi G, Wang J, Han C, Che Y. Model Predictive Control for Seizure Suppression Based on Nonlinear Auto-Regressive Moving-Average Volterra Model. IEEE Trans Neural Syst Rehabil Eng 2020; 28:2173-2183. [PMID: 32763855 DOI: 10.1109/tnsre.2020.3014927] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
This article investigates a closed-loop brain stimulation method based on model predictive control strategy to suppress epileptic seizures. A neural mass model (NMM), exhibiting the normal and various epileptic seizures by changing physiologically meaningful parameters, is used as a black-box model of the brain. Based on system identification, an auto-regressive moving-average Volterra model is established to reveal the relationship between stimulation and neuronal responses. Then, the model predictive control strategy is implemented based the Volterra model, which can generate an optimal stimulation waveform to eliminate epileptiform waves. The computational simulation results indicate the proposed closed-loop control strategy can optimize the stimulation waveform without particular knowledge of the physiological properties of the system. The robustness of the proposed control strategy to system disturbances makes it more appropriate for future clinical application.
Collapse
|
27
|
Abstract
Pencils and papers are ubiquitous in our society and have been widely used for writing and drawing, because they are easy to use, low-cost, widely accessible, and disposable. However, their applications in emerging skin-interfaced health monitoring and interventions are still not well explored. Herein, we report a variety of pencil-paper-based on-skin electronic devices, including biophysical (temperature, biopotential) sensors, sweat biochemical (pH, uric acid, glucose) sensors, thermal stimulators, and humidity energy harvesters. Among these devices, pencil-drawn graphite patterns (or combined with other compounds) serve as conductive traces and sensing electrodes, and office-copy papers work as flexible supporting substrates. The enabled devices can perform real-time, continuous, and high-fidelity monitoring of a range of vital biophysical and biochemical signals from human bodies, including skin temperatures, electrocardiograms, electromyograms, alpha, beta, and theta rhythms, instantaneous heart rates, respiratory rates, and sweat pH, uric acid, and glucose, as well as deliver programmed thermal stimulations. Notably, the qualities of recorded signals are comparable to those measured with conventional methods. Moreover, humidity energy harvesters are prepared by creating a gradient distribution of oxygen-containing groups on office-copy papers between pencil-drawn electrodes. One single-unit device (0.87 cm2) can generate a sustained voltage of up to 480 mV for over 2 h from ambient humidity. Furthermore, a self-powered on-skin iontophoretic transdermal drug-delivery system is developed as an on-skin chemical intervention example. In addition, pencil-paper-based antennas, two-dimensional (2D) and three-dimensional (3D) circuits with light-emitting diodes (LEDs) and batteries, reconfigurable assembly and biodegradable electronics (based on water-soluble papers) are explored.
Collapse
|
28
|
Kananen J, Helakari H, Korhonen V, Huotari N, Järvelä M, Raitamaa L, Raatikainen V, Rajna Z, Tuovinen T, Nedergaard M, Jacobs J, LeVan P, Ansakorpi H, Kiviniemi V. Respiratory-related brain pulsations are increased in epilepsy-a two-centre functional MRI study. Brain Commun 2020; 2:fcaa076. [PMID: 32954328 PMCID: PMC7472909 DOI: 10.1093/braincomms/fcaa076] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/29/2020] [Accepted: 05/05/2020] [Indexed: 01/03/2023] Open
Abstract
Resting-state functional MRI has shown potential for detecting changes in cerebral blood oxygen level-dependent signal in patients with epilepsy, even in the absence of epileptiform activity. Furthermore, it has been suggested that coefficient of variation mapping of fast functional MRI signal may provide a powerful tool for the identification of intrinsic brain pulsations in neurological diseases such as dementia, stroke and epilepsy. In this study, we used fast functional MRI sequence (magnetic resonance encephalography) to acquire ten whole-brain images per second. We used the functional MRI data to compare physiological brain pulsations between healthy controls (n = 102) and patients with epilepsy (n = 33) and furthermore to drug-naive seizure patients (n = 9). Analyses were performed by calculating coefficient of variation and spectral power in full band and filtered sub-bands. Brain pulsations in the respiratory-related frequency sub-band (0.11-0.51 Hz) were significantly (P < 0.05) increased in patients with epilepsy, with an increase in both signal variance and power. At the individual level, over 80% of medicated and drug-naive seizure patients exhibited areas of abnormal brain signal power that correlated well with the known clinical diagnosis, while none of the controls showed signs of abnormality with the same threshold. The differences were most apparent in the basal brain structures, respiratory centres of brain stem, midbrain and temporal lobes. Notably, full-band, very low frequency (0.01-0.1 Hz) and cardiovascular (0.8-1.76 Hz) brain pulses showed no differences between groups. This study extends and confirms our previous results of abnormal fast functional MRI signal variance in epilepsy patients. Only respiratory-related brain pulsations were clearly increased with no changes in either physiological cardiorespiratory rates or head motion between the subjects. The regional alterations in brain pulsations suggest that mechanisms driving the cerebrospinal fluid homeostasis may be altered in epilepsy. Magnetic resonance encephalography has both increased sensitivity and high specificity for detecting the increased brain pulsations, particularly in times when other tools for locating epileptogenic areas remain inconclusive.
Collapse
Affiliation(s)
- Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Ville Raatikainen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Zalan Rajna
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu 90014, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY 14642, USA
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Julia Jacobs
- Department of Pediatric Neurology and Muscular Disease, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Pierre LeVan
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Hanna Ansakorpi
- Medical Research Center (MRC), Oulu 90220, Finland
- Research Unit of Neuroscience, Neurology, University of Oulu, Oulu 90220, Finland
- Department of Neurology, Oulu University Hospital, Oulu 90029, Finland
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| |
Collapse
|
29
|
Smyk MK, van Luijtelaar G. Circadian Rhythms and Epilepsy: A Suitable Case for Absence Epilepsy. Front Neurol 2020; 11:245. [PMID: 32411068 PMCID: PMC7198737 DOI: 10.3389/fneur.2020.00245] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 03/13/2020] [Indexed: 11/16/2022] Open
Abstract
Many physiological processes such as sleep, hormonal secretion, or thermoregulation, are expressed as daily rhythms orchestrated by the circadian timing system. A powerful internal clock mechanism ensures proper synchronization of vital functions within an organism on the one hand, and between the organism and the external environment on the other. Some of the pathological processes developing in the brain and body are subjected to circadian modulation as well. Epilepsy is one of the conditions which symptoms often worsen at a very specific time of a day. Variation in peak occurrence depends on the syndrome and localization of the epileptic focus. Moreover, the timing of some types of seizures is closely related to the sleep-wake cycle, one of the most prominent circadian rhythms. This review focuses on childhood absence epilepsy (CAE), a genetic generalized epilepsy syndrome, in which both, the circadian and sleep influences play a significant role in manifestation of symptoms. Human and animal studies report rhythmical occurrence of spike-wave discharges (SWDs), an EEG hallmark of CAE. The endogenous nature of the SWDs rhythm has been confirmed experimentally in a genetic animal model of the disease, rats of the WAG/Rij strain. Well-known detrimental effects of circadian misalignment were demonstrated to impact the severity of ongoing epileptic activity. SWDs are vigilance-dependent in both humans and animal models, occurring most frequently during passive behavioral states and light slow-wave sleep. The relationship with the sleep-wake cycle seems to be bidirectional, while sleep shapes the rhythm of seizures, epileptic phenotype changes sleep architecture. Circadian factors and the sleep-wake states dependency have a potential as add-ons in seizures' forecasting. Stability of the rhythm of recurrent seizures in individual patients has been already used as a variable which refines existing algorithms for seizures' prediction. On the other hand, apart from successful pharmacological approach, circadian hygiene including sufficient sleep and avoidance of internal desynchronization or sleep loss, may be beneficial for patients with epilepsy in everyday management of seizures.
Collapse
Affiliation(s)
- Magdalena K Smyk
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, Netherlands
| | - Gilles van Luijtelaar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| |
Collapse
|
30
|
Chaturvedi M, Bogaarts JG, Kozak Cozac VV, Hatz F, Gschwandtner U, Meyer A, Fuhr P, Roth V. Phase lag index and spectral power as QEEG features for identification of patients with mild cognitive impairment in Parkinson's disease. Clin Neurophysiol 2019; 130:1937-1944. [PMID: 31445388 DOI: 10.1016/j.clinph.2019.07.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 05/18/2019] [Accepted: 07/15/2019] [Indexed: 10/26/2022]
Abstract
OBJECTIVES To identify quantitative EEG frequency and connectivity features (Phase Lag Index) characteristic of mild cognitive impairment (MCI) in Parkinson's disease (PD) patients and to investigate if these features correlate with cognitive measures of the patients. METHODS We recorded EEG data for a group of PD patients with MCI (n = 27) and PD patients without cognitive impairment (n = 43) using a high-resolution recording system. The EEG files were processed and 66 frequency along with 330 connectivity (phase lag index, PLI) measures were calculated. These measures were used to classify MCI vs. MCI-free patients. We also assessed correlations of these features with cognitive tests based on comprehensive scores (domains). RESULTS PLI measures classified PD-MCI from non-MCI patients better than frequency measures. PLI in delta, theta band had highest importance for identifying patients with MCI. Amongst cognitive domains, we identified the most significant correlations between Memory and Theta PLI, Attention and Beta PLI. CONCLUSION PLI is an effective quantitative EEG measure to identify PD patients with MCI. SIGNIFICANCE We identified quantitative EEG measures which are important for early identification of cognitive decline in PD.
Collapse
Affiliation(s)
- Menorca Chaturvedi
- Department of Neurology, University Hospital Basel, Basel, Switzerland; Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland
| | - Jan Guy Bogaarts
- Department of Neurology, University Hospital Basel, Basel, Switzerland; Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland
| | - Vitalii V Kozak Cozac
- Department of Neurology, University Hospital Basel, Basel, Switzerland; Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland
| | - Florian Hatz
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Ute Gschwandtner
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Antonia Meyer
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Peter Fuhr
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Volker Roth
- Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland.
| |
Collapse
|
31
|
Sun B, McCay RN, Goswami S, Xu Y, Zhang C, Ling Y, Lin J, Yan Z. Gas-Permeable, Multifunctional On-Skin Electronics Based on Laser-Induced Porous Graphene and Sugar-Templated Elastomer Sponges. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2018; 30:e1804327. [PMID: 30306662 DOI: 10.1002/adma.201804327] [Citation(s) in RCA: 123] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2018] [Revised: 09/18/2018] [Indexed: 05/18/2023]
Abstract
Soft on-skin electronics have broad applications in human healthcare, human-machine interface, robotics, and others. However, most current on-skin electronic devices are made of materials with limited gas permeability, which constrain perspiration evaporation, resulting in adverse physiological and psychological effects, limiting their long-term feasibility. In addition, the device fabrication process usually involves e-beam or photolithography, thin-film deposition, etching, and/or other complicated procedures, which are costly and time-consuming, constraining their practical applications. Here, a simple, general, and effective approach for making multifunctional on-skin electronics using porous materials with high-gas permeability, consisting of laser-patterned porous graphene as the sensing components and sugar-templated silicone elastomer sponges as the substrates, is reported. The prototype device examples include electrophysiological sensors, hydration sensors, temperature sensors, and joule-heating elements, showing signal qualities comparable to conventional, rigid, gas-impermeable devices. Moreover, the devices exhibit high water-vapor permeability (≈18 mg cm-2 h-1 ), ≈18 times higher than that of the silicone elastomers without pores, and also show high water-wicking rates after polydopamine treatment, up to 1 cm per 30 s, which is comparable to that of cotton. The on-skin devices with such attributes could facilitate perspiration transport and evaporation, and minimize discomfort and inflammation risks, thereby improving their long-term feasiblity.
Collapse
Affiliation(s)
- Bohan Sun
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Richard N McCay
- Department of Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Shivam Goswami
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Yadong Xu
- Department of Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Cheng Zhang
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Yun Ling
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Jian Lin
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
| | - Zheng Yan
- Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA
- Department of Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, MO, 65211, USA
| |
Collapse
|
32
|
Michaelis R, Schöller H, Höller Y, Kalss G, Kirschner M, Schmid E, Trinka E, Schiepek G. Integrating the systematic assessment of psychological states in the epilepsy monitoring unit: Concept and compliance. Epilepsy Behav 2018; 88:5-14. [PMID: 30212726 DOI: 10.1016/j.yebeh.2018.08.029] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Revised: 08/16/2018] [Accepted: 08/22/2018] [Indexed: 11/17/2022]
Abstract
BACKGROUND Admission to the epilepsy monitoring unit (EMU) for long-term video-electroencephalography (EEG) monitoring (VEEG) constitutes the gold standard for seizure diagnosis and presurgical evaluation. This study applied the concept of a high-frequency systematic monitoring of psychological states and tested patients' compliance in order to evaluate if its integration in the EMU is feasible and if patients benefit from the graphically underpinned discussion of their EMU stay-related cognitions and emotions. METHODS The process-monitoring is technically realized by an internet-based device for data collection and data analysis, the Synergetic Navigation System (SNS). A convenient sample was enrolled: All eligible patients who were admitted to the EMU of the Department of Neurology, Christian Doppler Medical Center, Salzburg, Austria, between November 6th 2017 and January 26th 2018 were approached and recruited upon consent. After a short resource-oriented interview, each enrolled patient was provided with a tablet. The daily questionnaire included eight standardized and up to three personalized items. Self-assessments were collected every 5 h prior to meal times (6:30 am, 11:30 am, and 4:30 pm) and at 9:30 pm. The detailed visualizations of the patients' replies were discussed with the participants during a feedback session at the end of the EMU stay. RESULTS Twenty-one patients (12 women/9 men, median age 29 years [range 18-74 years]) were consecutively recruited (72% of all eligible patients). Compliance rates were high (median: 82%, range 60%-100%) among the respondents. Mood correlated strongly with hopefulness (r = 0.71) and moderately with energy (r = 0.63) in all patients. When correlating the intraindividual medians of the process questionnaire time series with the pretest total scores, energy correlated moderately and negatively with the Perceived Stress Scale (PSS) (r = -0.45), while self-efficacy correlated moderately and negatively with the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) total scores in all patients (r = -0.5). Nine patients (43%) reported that they learned something meaningful about themselves after the feedback discussion of their individual time series. CONCLUSION The results support the feasibility of high-frequency monitoring of psychological states and processes in routine EMU settings. Repeated daily collections four times per day of psychological surveys allow for the assessment of highly resolved, equidistant time series data, which gives insight into psychological states and processes during EMU admission.
Collapse
Affiliation(s)
- Rosa Michaelis
- Department of Neurology, Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria; Department of Neurology, Gemeinschaftskrankenhaus Herdecke, Herdecke, Germany; Integrated Curriculum for Anthroposophical Medicine (ICURAM), Witten/Herdecke University, Herdecke, Germany.
| | - Helmut Schöller
- Institute of Synergetics and Psychotherapy Research, Paracelsus Medical University, Salzburg, Austria; Department of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, Austria
| | - Yvonne Höller
- Department of Neurology, Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria
| | - Gudrun Kalss
- Department of Neurology, Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria
| | - Margarita Kirschner
- Department of Neurology, Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria
| | - Elisabeth Schmid
- Department of Neurology, Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria
| | - Eugen Trinka
- Department of Neurology, Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria
| | - Günter Schiepek
- Institute of Synergetics and Psychotherapy Research, Paracelsus Medical University, Salzburg, Austria; Department of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, Austria
| |
Collapse
|
33
|
Owolabi LF, Sale S, Owolabi SD, Nalado A, Umar M, Taura AA. Electroencephalography abnormalities in generalized epilepsy and their predictors: A multicenter experience. Ann Afr Med 2018. [PMID: 29536959 PMCID: PMC5875121 DOI: 10.4103/aam.aam_2_17] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Background: In spite of the overwhelming significance of knowledge of basic elements of electroencephalography (EEG) in its application to the diagnostic workup and the management of patients with suspected or already established generalized epilepsy (GE), there is a dearth of data on the pattern and utility of clinical variables that can independently determine EEG abnormalities in GE. Objective: The study was designed to evaluate the frequency and pattern of EEG abnormality as well as assess the utility of clinical variables in predicting the likelihood of an abnormal EEG in GE. Methods: It was a cross-sectional study involving the analysis of EEGs of consecutive patients with clinical diagnosis of idiopathic GE from three centers over a 7-year period. Information on sociodemographic and seizure variables was obtained. The International Federation of Societies for Electroencephalography and Clinical Neurophysiology definition of interictal epileptiform discharges (interictal epileptiform activity [IEA]) was adopted in the study. Results: A total of 403 patients comprising 242 (60%) males and 161 (40%) females with clinical diagnosis of GE had EEG. Their age ranged between 2 weeks and 70 years, with a median age of 21 years and an interquartile age of 26 years. Two hundred and thirty-seven (58.8%) and 213 (52.9%) patients had abnormal EEG and IEA, respectively. Before adjustment for confounders, female gender (P = 0.0001), pediatric age group (P = 0.0388), duration of epilepsy of 1–4 years (P = 0.01387), uncontrolled seizure (P = 0.0060), and seizure frequency (P = 0.0001) were significantly associated with the presence of abnormal EEG. However, age, female gender, poor seizure control, and seizure frequencies were the independent predictors of EEG abnormality. Conclusion: The study showed that about 58% of patients with GE patients had abnormal EEG. Age, poor seizure control, and high frequency of seizure were independent predictors of the presence of EEG abnormality.
Collapse
Affiliation(s)
- Lukman Femi Owolabi
- Department of Medicine, Aminu Kano Teaching Hospital, Bayero University, Kano, Nigeria
| | - Shehu Sale
- Department of Psychiatry, Aminu Kano Teaching Hospital, Bayero University, Kano, Nigeria
| | | | - Aisha Nalado
- Department of Medicine, Aminu Kano Teaching Hospital, Bayero University, Kano, Nigeria
| | - Muhammad Umar
- Department of Psychiatry, Aminu Kano Teaching Hospital, Bayero University, Kano, Nigeria
| | - Aminu Abdullahi Taura
- Department of Psychiatry, Aminu Kano Teaching Hospital, Bayero University, Kano, Nigeria
| |
Collapse
|
34
|
Bauer PR, de Goede AA, Stern WM, Pawley AD, Chowdhury FA, Helling RM, Bouet R, Kalitzin SN, Visser GH, Sisodiya SM, Rothwell JC, Richardson MP, van Putten MJAM, Sander JW. Long-interval intracortical inhibition as biomarker for epilepsy: a transcranial magnetic stimulation study. Brain 2018; 141:409-421. [PMID: 29340584 PMCID: PMC5837684 DOI: 10.1093/brain/awx343] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 10/08/2017] [Accepted: 10/24/2017] [Indexed: 11/13/2022] Open
Abstract
Cortical excitability, as measured by transcranial magnetic stimulation combined with electromyography, is a potential biomarker for the diagnosis and follow-up of epilepsy. We report on long-interval intracortical inhibition data measured in four different centres in healthy controls (n = 95), subjects with refractory genetic generalized epilepsy (n = 40) and with refractory focal epilepsy (n = 69). Long-interval intracortical inhibition was measured by applying two supra-threshold stimuli with an interstimulus interval of 50, 100, 150, 200 and 250 ms and calculating the ratio between the response to the second (test stimulus) and to the first (conditioning stimulus). In all subjects, the median response ratio showed inhibition at all interstimulus intervals. Using a mixed linear-effects model, we compared the long-interval intracortical inhibition response ratios between the different subject types. We conducted two analyses; one including data from the four centres and one excluding data from Centre 2, as the methods in this centre differed from the others. In the first analysis, we found no differences in long-interval intracortical inhibition between the different subject types. In all subjects, the response ratios at interstimulus intervals 100 and 150 ms showed significantly more inhibition than the response ratios at 50, 200 and 250 ms. Our second analysis showed a significant interaction between interstimulus interval and subject type (P = 0.0003). Post hoc testing showed significant differences between controls and refractory focal epilepsy at interstimulus intervals of 100 ms (P = 0.02) and 200 ms (P = 0.04). There were no significant differences between controls and refractory generalized epilepsy groups or between the refractory generalized and focal epilepsy groups. Our results do not support the body of previous work that suggests that long-interval intracortical inhibition is significantly reduced in refractory focal and genetic generalized epilepsy. Results from the second analysis are even in sharper contrast with previous work, showing inhibition in refractory focal epilepsy at 200 ms instead of facilitation previously reported. Methodological differences, especially shorter intervals between the pulse pairs, may have contributed to our inability to reproduce previous findings. Based on our results, we suggest that long-interval intracortical inhibition as measured by transcranial magnetic stimulation and electromyography is unlikely to have clinical use as a biomarker of epilepsy.
Collapse
Affiliation(s)
- Prisca R Bauer
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
| | - Annika A de Goede
- Department of Clinical Neurophysiology, MIRA – Institute for Biomedical Technology and Technical Medicine, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
| | - William M Stern
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, SL9 0RJ, UK
| | - Adam D Pawley
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London 16 De Crespigny Park, London, SE5 8AF, UK
| | - Fahmida A Chowdhury
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London 16 De Crespigny Park, London, SE5 8AF, UK
| | - Robert M Helling
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
- Image Sciences Institute, University Medical Centre Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands
| | - Romain Bouet
- Lyon Neuroscience Research Center, INSERM U1028 - CNRS UMR5292, Université Claude Bernard Lyon1, Brain Dynamics and Cognition Team, Centre Hospitalier Le Vinatier (Bât. 452), 95 Bd Pinel, 69500 Bron, France
| | - Stiliyan N Kalitzin
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
- Image Sciences Institute, University Medical Centre Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands
| | - Gerhard H Visser
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
| | - Sanjay M Sisodiya
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, SL9 0RJ, UK
| | - John C Rothwell
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Mark P Richardson
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London 16 De Crespigny Park, London, SE5 8AF, UK
| | - Michel J A M van Putten
- Department of Clinical Neurophysiology, MIRA – Institute for Biomedical Technology and Technical Medicine, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
- Department of Clinical Neurophysiology and Neurology, Medisch Spectrum Twente, Koningsplein 1, 7512 KZ Enschede, The Netherlands
| | - Josemir W Sander
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
- Chalfont Centre for Epilepsy, Chalfont St Peter, SL9 0RJ, UK
| |
Collapse
|
35
|
Allen SE, Limdi N, Westrick AC, Ver Hoef LW, Szaflarski JP, Knowlton RC. Racial disparities in temporal lobe epilepsy. Epilepsy Res 2017; 140:56-60. [PMID: 29272743 DOI: 10.1016/j.eplepsyres.2017.12.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2017] [Revised: 12/10/2017] [Accepted: 12/14/2017] [Indexed: 11/16/2022]
Abstract
OBJECTIVE This study reports on epilepsy type period prevalence and black-white racial differences in a large patient population in the Southeastern United States. METHODS For all patients visiting the University of Alabama at Birmingham's seizure monitoring unit between 2000 and 2011 (n = 3240), video EEG diagnosis was recorded along with basic demographic information. Descriptive statistics and multivariate logistic regression were used to identify factors associated with temporal lobe epilepsy (TLE) diagnosis. RESULTS The racial distribution was 77.3% white, and 20.0% black (other races were only 2.3% of the population). Most patients had either TLE (n = 630) or PNES (n = 1150) compared to other focal (n = 424) or generalized epilepsies (n = 224). The diagnosis of TLE was significantly greater for blacks than whites (odds ratio [OR] = 1.87, 95% confidence interval [CI] 1.47-2.37). The period prevalence measures for the other conclusively diagnosed epilepsies were not significantly different. Women were disproportionately represented in the study population, and black women carried the most statistical weight for the TLE prevalence difference. INTERPRETATION The nearly two-fold larger period prevalence of TLE among black patients is a striking finding that merits explanation. Although some selection bias exists due to a moderately lower than expected representation of blacks, socioeconomic status or access to care should not be assumed to be the only factors that might be responsible for the prevalence difference. Rather, all clues for distinct pathophysiological racial differences should be explored.
Collapse
Affiliation(s)
- Samantha E Allen
- Oregon Health Sciences University, Department of Neurology, United States.
| | - Nita Limdi
- University of Alabama Birmingham, Department of Neurology, United States
| | - Ashly C Westrick
- University of Miami, Department of Public Health Sciences, United States.
| | | | - Jerzy P Szaflarski
- University of Alabama Birmingham, Department of Neurology, United States.
| | - Robert C Knowlton
- University of California San Francisco, Department of Neurology, United States.
| |
Collapse
|
36
|
Chi Y, Wu B, Guan J, Xiao K, Lu Z, Li X, Xu Y, Xue S, Xu Q, Rao J, Guo Y. Establishment of a rhesus monkey model of chronic temporal lobe epilepsy using repetitive unilateral intra-amygdala kainic acid injections. Brain Res Bull 2017; 134:273-282. [PMID: 28842304 DOI: 10.1016/j.brainresbull.2017.08.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2016] [Revised: 08/09/2017] [Accepted: 08/18/2017] [Indexed: 12/23/2022]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) is a common type of acquired epilepsy refractory to medical treatment. As such, establishing animal models of this disease is critical to developing new and effective treatment modalities. Because of their small head size, rodents are not suitable for comprehensive electroencephalography (EEG) evaluation via scalp or subdural electrodes. Therefore, a larger primate model that closely recapitulates signs of TLE is needed; here we describe a rhesus monkey model resembling chronic TLE. METHODS Eight monkeys were divided into two groups: kainic acid (KA) group (n=6) and saline control group (n=2). Intra-amygdala KA injections were performed biweekly via an Ommaya device until obvious epileptiform discharges were recorded. Video-EEG recording was conducted intermittently throughout the experiment using both scalp and subdural electrodes. Brains were then analyzed for Nissl and glial fibrillary acid protein (GFAP) immunostaining. RESULTS After 2-4 injections of KA (approximately 1.2-2.4mg, 0.12-0.24mg/kg), interictal epileptiform discharges (IEDs) were recorded in all KA-treated animals. Spontaneous recurrent seizures (SRSs) accompanied by symptoms mimicking temporal lobe absence (undetectable without EEG recording), but few mild motor signs, were recorded in 66.7% (four of six) KA-treated animals. Both IEDs and seizures indicated a primary epileptic zone in the right temporal region and contralateral discharges were later detected. Segmental pyramidal cell loss and gliosis were detected in the brain of a KA-treated monkey. CONCLUSIONS Through a modified protocol of unilateral repetitive intra-amygdala KA injections, a rhesus monkey model with similar behavioral and brain electrical features as TLE was developed.
Collapse
Affiliation(s)
- Yajie Chi
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China; Department of Neurosurgery, Shunde Hospital of Southern Medical University, Foshan, 528300, China
| | - Bolin Wu
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Jianwei Guan
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Kuntai Xiao
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Ziming Lu
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Xiao Li
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Yuting Xu
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Shan Xue
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
| | - Qiang Xu
- Department of Neurosurgery, Affiliated Shunde Heping Surgical Hospital of GUCM, Foshan, 528308, China.
| | - Junhua Rao
- Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou, 510282, China.
| | - Yanwu Guo
- The National Key Clinic Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
| |
Collapse
|
37
|
Chae KM, Sung HH, Kim DS. A Study on the Relationship between Seizure Recurrence and EEG for Epilepsy. KOREAN JOURNAL OF CLINICAL LABORATORY SCIENCE 2016. [DOI: 10.15324/kjcls.2016.48.4.388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- Kyoung-Min Chae
- Department of Neurology, Seoul National University Hospital, Seoul 03080, Korea
| | - Hyun-Ho Sung
- Department of Clinical Laboratory Science, Dongnam Health University, Suwon 16328, Korea
| | - Dae-Sik Kim
- Department of Clinical Laboratory Science, Dongnam Health University, Suwon 16328, Korea
| |
Collapse
|
38
|
Yang XY, Long LL, Xiao B. [Role of video electroencephalogram in diagnosis and localization of epilepsy in children]. ZHONGGUO DANG DAI ER KE ZA ZHI = CHINESE JOURNAL OF CONTEMPORARY PEDIATRICS 2016; 18:971-974. [PMID: 27751213 PMCID: PMC7389555 DOI: 10.7499/j.issn.1008-8830.2016.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 04/16/2016] [Accepted: 05/20/2016] [Indexed: 06/06/2023]
Abstract
OBJECTIVE To study the role of video electroencephalogram (VEEG) versus regular electroencephalogram (REEG) in the diagnosis of epilepsy and localization of origin of epileptic discharge in children through a comparative analysis. METHODS A retrospective analysis was performed for the clinical data of 223 children with clinical paroxysmal symptoms in the past and suspected epilepsy. VEEG and REEG were compared from the aspects of monitoring of clinical seizures, interictal epileptiform discharge (IED), localization of the origin of IED, and identification of non-epileptic seizures, and the detection rate of IED during awakening and sleep stages was also compared. RESULTS Compared with REEG, VEEG had significantly higher detection rates of IED and synchronous clinical seizures in children with epileptiform discharge (P<0.01). Of all children, 86 were diagnosed with epilepsy, 78 were diagnosed with epilepsy syndrome, 31 were diagnosed with non-epileptic seizures, and 81 had a definite location of the origin of epileptic discharge according to the VEEG. The detection rate of IED in the sleep stage was higher than that in the awakening stage (46% vs 13.2%; P<0.01), and IED was mainly detected in the NREM I-II stages according to the VEEG. CONCLUSIONS VEEG has a significantly better performance than REEG in the diagnosis and localization of epilepsy in children and has a high value in clinical practice.
Collapse
Affiliation(s)
- Xiao-Yan Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
| | | | | |
Collapse
|
39
|
Rosenow F. Is it time to look for frontal lobe seizures onset zone after they are over?--Defining the value of the postical irritative zone (PIZ) and postictal functional deficit zone (PFDZ) in localizing the epileptogenic zone. Clin Neurophysiol 2015; 127:1757-8. [PMID: 26724912 DOI: 10.1016/j.clinph.2015.12.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Revised: 12/01/2015] [Accepted: 12/05/2015] [Indexed: 11/25/2022]
Affiliation(s)
- Felix Rosenow
- Epilepsy Center Frankfurt Rhine-Main, Department of Neurology, Neurocenter, Goethe-University Frankfurt, Frankfurt a. M., Germany
| |
Collapse
|
40
|
The role of outpatient ambulatory electroencephalography in the diagnosis and management of adults with epilepsy or nonepileptic attack disorder: A systematic literature review. Epilepsy Behav 2015; 53:26-30. [PMID: 26515156 DOI: 10.1016/j.yebeh.2015.09.032] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2015] [Revised: 09/21/2015] [Accepted: 09/24/2015] [Indexed: 11/22/2022]
Abstract
Electroencephalography (EEG) is an established diagnostic tool with important implications for the clinical management of patients with epilepsy or nonepileptic attack disorder. Different types of long-term EEG recording strategies have been developed over the last decades, including the widespread use of ambulatory electroencephalography (AEEG), which holds great potential in terms of both clinical usefulness and cost-effectiveness. In this paper, we present the results of a systematic review of the scientific literature on the use of AEEG in the diagnosis of epilepsy and nonepileptic attacks in adult patients. Taken together, our findings confirmed that AEEG is a useful diagnostic tool in patients with equivocal findings on routine EEG studies and influences management decisions in the majority of studies. There is evidence that AEEG is also more likely to capture events than sleep-deprived EEG; however, there are currently insufficient data available to compare the diagnostic utility of modern AEEG technology with inpatient video-telemetry. Further research on the combined use of AEEG and home-video recording is, therefore, warranted.
Collapse
|
41
|
Yang S, Chen YC, Nicolini L, Pasupathy P, Sacks J, Su B, Yang R, Sanchez D, Chang YF, Wang P, Schnyer D, Neikirk D, Lu N. "Cut-and-Paste" Manufacture of Multiparametric Epidermal Sensor Systems. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2015; 27:6423-6430. [PMID: 26398335 DOI: 10.1002/adma.201502386] [Citation(s) in RCA: 133] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 08/05/2015] [Indexed: 06/05/2023]
Abstract
Multifunctional epidermal sensor systems (ESS) are manufactured with a highly cost and time effective, benchtop, and large-area "cut-and-paste" method. The ESS made out of thin and stretchable metal and conductive polymer ribbons can be noninvasively laminated onto the skin surface to sense electrophysiological signals, skin temperature, skin hydration, and respiratory rate.
Collapse
Affiliation(s)
- Shixuan Yang
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
| | - Ying-Chen Chen
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Luke Nicolini
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
- Texas Materials Institute, University of Texas at Austin, Austin, TX, 78712, USA
| | - Praveenkumar Pasupathy
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Jacob Sacks
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
| | - Becky Su
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
| | - Russell Yang
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
| | - Daniel Sanchez
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
| | - Yao-Feng Chang
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Pulin Wang
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
| | - David Schnyer
- Department of Psychology, University of Texas at Austin, Austin, TX, 78712, USA
| | - Dean Neikirk
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Nanshu Lu
- Center for Mechanics of Solids, Structures and Materials, Department of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712, USA
- Texas Materials Institute, University of Texas at Austin, Austin, TX, 78712, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| |
Collapse
|