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Rajaraman RR, Smith RJ, Oana S, Daida A, Shrey DW, Nariai H, Lopour BA, Hussain SA. Computational EEG attributes predict response to therapy for epileptic spasms. Clin Neurophysiol 2024; 163:39-46. [PMID: 38703698 DOI: 10.1016/j.clinph.2024.03.035] [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: 09/27/2023] [Revised: 03/10/2024] [Accepted: 03/28/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE We set out to evaluate whether response to treatment for epileptic spasms is associated with specific candidate computational EEG biomarkers, independent of clinical attributes. METHODS We identified 50 children with epileptic spasms, with pre- and post-treatment overnight video-EEG. After EEG samples were preprocessed in an automated fashion to remove artifacts, we calculated amplitude, power spectrum, functional connectivity, entropy, and long-range temporal correlations (LRTCs). To evaluate the extent to which each feature is independently associated with response and relapse, we conducted logistic and proportional hazards regression, respectively. RESULTS After statistical adjustment for the duration of epileptic spasms prior to treatment, we observed an association between response and stronger baseline and post-treatment LRTCs (P = 0.042 and P = 0.004, respectively), and higher post-treatment entropy (P = 0.003). On an exploratory basis, freedom from relapse was associated with stronger post-treatment LRTCs (P = 0.006) and higher post-treatment entropy (P = 0.044). CONCLUSION This study suggests that multiple EEG features-especially LRTCs and entropy-may predict response and relapse. SIGNIFICANCE This study represents a step toward a more precise approach to measure and predict response to treatment for epileptic spasms.
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Affiliation(s)
- Rajsekar R Rajaraman
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Shingo Oana
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Atsuro Daida
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel W Shrey
- Division of Pediatric Neurology, University of California, Irvine, Irvine, CA, USA; Department of Neurology, Children's Hospital of Orange County, Orange, CA, USA
| | - Hiroki Nariai
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Beth A Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Shaun A Hussain
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA.
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Stanyard RA, Mason D, Ellis C, Dickson H, Short R, Batalle D, Arichi T. Aperiodic and Hurst EEG exponents across early human brain development: A systematic review. Dev Cogn Neurosci 2024; 68:101402. [PMID: 38917647 DOI: 10.1016/j.dcn.2024.101402] [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: 02/20/2024] [Revised: 04/12/2024] [Accepted: 06/03/2024] [Indexed: 06/27/2024] Open
Abstract
In electroencephalographic (EEG) data, power-frequency slope exponents (1/f_β) can provide non-invasive markers of in vivo neural activity excitation-inhibition (E:I) balance. E:I balance may be altered in neurodevelopmental conditions; hence, understanding how 1/fβ evolves across infancy/childhood has implications for developing early assessments/interventions. This systematic review (PROSPERO-ID: CRD42023363294) explored the early maturation (0-26 yrs) of resting-state EEG 1/f measures (aperiodic [AE], power law [PLE] and Hurst [HE] exponents), including studies containing ≥1 1/f measures and ≥10 typically developing participants. Five databases (including Embase and Scopus) were searched during March 2023. Forty-two studies were identified (Nparticipants=3478). Risk of bias was assessed using the Quality Assessment with Diverse Studies tool. Narrative synthesis of HE data suggests non-stationary EEG activity occurs throughout development. Age-related trends were complex, with rapid decreases in AEs during infancy and heterogenous changes thereafter. Regionally, AE maxima shifted developmentally, potentially reflecting spatial trends in maturing brain connectivity. This work highlights the importance of further characterising the development of 1/f measures to better understand how E:I balance shapes brain and cognitive development.
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Affiliation(s)
- R A Stanyard
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
| | - D Mason
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - C Ellis
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - H Dickson
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - R Short
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - D Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - T Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, United Kingdom; Children's Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, United Kingdom; Department of Bioengineering, Imperial College London, United Kingdom
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Deckard E, Sathe R, Tabibzadeh D, Terango A, Groves A, Rajaraman RR, Nariai H, Hussain SA. Epileptic spasms relapse is associated with response latency but not conventional attributes of post-treatment EEG. Epilepsia Open 2024; 9:1034-1041. [PMID: 38588009 PMCID: PMC11145600 DOI: 10.1002/epi4.12931] [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: 09/20/2023] [Revised: 02/06/2024] [Accepted: 03/09/2024] [Indexed: 04/10/2024] Open
Abstract
OBJECTIVE Relapse of epileptic spasms after initial treatment of infantile epileptic spasms syndrome (IESS) is common. However, past studies of small cohorts have inconsistently linked relapse risk to etiology, treatment modality, and EEG features upon response. Using a large single-center IESS cohort, we set out to quantify the risk of epileptic spasms relapse and identify specific risk factors. METHODS We identified all children with epileptic spasms at our center using a clinical EEG database. Using the electronic medical record, we confirmed IESS syndrome classification and ascertained treatment, response, time to relapse, etiology, EEG features, and other demographic factors. Relapse-free survival analysis was carried out using Cox proportional hazards regression. RESULTS Among 599 children with IESS, 197 specifically responded to hormonal therapy and/or vigabatrin (as opposed to surgery or other second-line treatments). In this study, 41 (21%) subjects exhibited relapse of epileptic spasms within 12 months of response. Longer duration of IESS prior to response (>3 months) was strongly associated with shorter latency to relapse (hazard ratio = 3.11; 95% CI 1.59-6.10; p = 0.001). Relapse was not associated with etiology, developmental status, or any post-treatment EEG feature. SIGNIFICANCE This study suggests that long duration of IESS before response is the single largest clinical predictor of relapse risk, and therefore underscores the importance of prompt and successful initial treatment. Further study is needed to evaluate candidate biomarkers of epileptic spasms relapse and identify treatments to mitigate this risk. PLAIN LANGUAGE SUMMARY Relapse of infantile spasms is common after initially successful treatment. With study of a large group of children with infantile spasms, we determined that relapse is linked to long duration of infantile spasms. In contrast, relapse was not associated with the cause of infantile spasms, developmental measures, or EEG features at the time of initial response. Further study is needed to identify tools to predict impending relapse of infantile spasms.
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Affiliation(s)
- Emmi Deckard
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Rujuta Sathe
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - David Tabibzadeh
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Aria Terango
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Aran Groves
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Rajsekar R. Rajaraman
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Hiroki Nariai
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
| | - Shaun A. Hussain
- Department of PediatricsDivision of NeurologyUniversity of California Los Angeles and UCLA Mattel Children's HospitalCaliforniaLos AngelesUSA
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Wang Z, Feng Z, Yuan Y, Guo Z, Cui J, Jiang T. Dynamics of neuronal firing modulated by high-frequency electrical pulse stimulations at axons in rat hippocampus. J Neural Eng 2024; 21:026025. [PMID: 38530299 DOI: 10.1088/1741-2552/ad37da] [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: 09/12/2023] [Accepted: 03/26/2024] [Indexed: 03/27/2024]
Abstract
Objective. The development of electrical pulse stimulations in brain, including deep brain stimulation, is promising for treating various brain diseases. However, the mechanisms of brain stimulations are not yet fully understood. Previous studies have shown that the commonly used high-frequency stimulation (HFS) can increase the firing of neurons and modulate the pattern of neuronal firing. Because the generation of neuronal firing in brain is a nonlinear process, investigating the characteristics of nonlinear dynamics induced by HFS could be helpful to reveal more mechanisms of brain stimulations. The aim of present study is to investigate the fractal properties in the neuronal firing generated by HFS.Approach. HFS pulse sequences with a constant frequency 100 Hz were applied in the afferent fiber tracts of rat hippocampal CA1 region. Unit spikes of both the pyramidal cells and the interneurons in the downstream area of stimulations were recorded. Two fractal indexes-the Fano factor and Hurst exponent were calculated to evaluate the changes of long-range temporal correlations (LRTCs), a typical characteristic of fractal process, in spike sequences of neuronal firing.Mainresults. Neuronal firing at both baseline and during HFS exhibited LRTCs over multiple time scales. In addition, the LRTCs significantly increased during HFS, which was confirmed by simulation data of both randomly shuffled sequences and surrogate sequences.Conclusion. The purely periodic stimulation of HFS pulses, a non-fractal process without LRTCs, can increase rather than decrease the LRTCs in neuronal firing.Significance. The finding provides new nonlinear mechanisms of brain stimulation and suggests that LRTCs could be a new biomarker to evaluate the nonlinear effects of HFS.
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Affiliation(s)
- Zhaoxiang Wang
- Zhejiang Lab, Hangzhou, People's Republic of China
- Key Lab of Biomedical Engineering for Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Zhouyan Feng
- Key Lab of Biomedical Engineering for Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Yue Yuan
- Zhejiang Lab, Hangzhou, People's Republic of China
- Key Lab of Biomedical Engineering for Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Zheshan Guo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, Hainan, People's Republic of China
| | - Jian Cui
- Zhejiang Lab, Hangzhou, People's Republic of China
| | - Tianzi Jiang
- Zhejiang Lab, Hangzhou, People's Republic of China
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, People's Republic of China
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Romero Milà B, Remakanthakurup Sindhu K, Mytinger JR, Shrey DW, Lopour BA. EEG biomarkers for the diagnosis and treatment of infantile spasms. Front Neurol 2022; 13:960454. [PMID: 35968272 PMCID: PMC9366674 DOI: 10.3389/fneur.2022.960454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Early diagnosis and treatment are critical for young children with infantile spasms (IS), as this maximizes the possibility of the best possible child-specific outcome. However, there are major barriers to achieving this, including high rates of misdiagnosis or failure to recognize the seizures, medication failure, and relapse. There are currently no validated tools to aid clinicians in assessing objective diagnostic criteria, predicting or measuring medication response, or predicting the likelihood of relapse. However, the pivotal role of EEG in the clinical management of IS has prompted many recent studies of potential EEG biomarkers of the disease. These include both visual EEG biomarkers based on human visual interpretation of the EEG and computational EEG biomarkers in which computers calculate quantitative features of the EEG. Here, we review the literature on both types of biomarkers, organized based on the application (diagnosis, treatment response, prediction, etc.). Visual biomarkers include the assessment of hypsarrhythmia, epileptiform discharges, fast oscillations, and the Burden of AmplitudeS and Epileptiform Discharges (BASED) score. Computational markers include EEG amplitude and power spectrum, entropy, functional connectivity, high frequency oscillations (HFOs), long-range temporal correlations, and phase-amplitude coupling. We also introduce each of the computational measures and provide representative examples. Finally, we highlight remaining gaps in the literature, describe practical guidelines for future biomarker discovery and validation studies, and discuss remaining roadblocks to clinical implementation, with the goal of facilitating future work in this critical area.
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Affiliation(s)
- Blanca Romero Milà
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electronics and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain
| | | | - John R. Mytinger
- Division of Pediatric Neurology, Department of Pediatrics, Nationwide Children's Hospital, The Ohio State University, Columbus, OH, United States
| | - Daniel W. Shrey
- Division of Neurology, Children's Hospital Orange County, Orange, CA, United States
- Department of Pediatrics, University of California, Irvine, Irvine, CA, United States
| | - Beth A. Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- *Correspondence: Beth A. Lopour
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Liu X, Chen J, Wan L, Li Z, Liang Y, Yan H, Zhu G, Zhang B, Yang G. Interrater and Intrarater Agreement of Epileptic Encephalopathy Among Electroencephalographers for Children with Infantile Spasms Using the Burden of Amplitudes and Epileptiform Discharges (BASED) EEG Grading Scale: Study Design and Statistical Considerations. Neurol Ther 2022; 11:1427-1437. [PMID: 35809161 PMCID: PMC9338191 DOI: 10.1007/s40120-022-00382-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 06/17/2022] [Indexed: 11/26/2022] Open
Abstract
Background Infantile spasms are a serious epilepsy syndrome with a poor prognosis. Electroencephalography (EEG) has been a key component in the prognosis and treatment of infantile spasms. This multi-center study protocol is developed to investigate interrater and intrarater agreement of an electroencephalographic grading scale—the Burden of Amplitudes and Epileptiform Discharges (BASED) score among electroencephalographers. Methods Thirty children, aged 0–2 years, with infantile spasms who were hospitalized in the Chinese PLA General Hospital will be recruited into this study by stratified sampling. Seven electroencephalographers from different Class A tertiary hospitals will select a 5-min epoch with the most severe epileptiform discharge, score the EEG reports, and provide the basis for the scoring. The 420 (30 × 7 × 2) scoring results provided by electroencephalographers in two rounds can be analyzed statistically using weighted kappa (weighted \documentclass[12pt]{minimal}
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\begin{document}$$\kappa$$\end{document}κ) statistic, and intraclass correlation coefficient (ICC) to calculate the interrater and intrarater agreement. Discussion We will recruit more electroencephalographers than were included in previous studies to assess the interrater and intrarater agreement in the selection of 5-min EEG epochs, the BASED scores, and the basis for scoring. If the BASED score has an adequate interrater and intrarater agreement, the score will have more significance for guiding the clinical management and for predicting the prognosis of patients with infantile spasms. Supplementary Information The online version contains supplementary material available at 10.1007/s40120-022-00382-4.
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Affiliation(s)
- Xinting Liu
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Jian Chen
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Lin Wan
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Zhichao Li
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Yan Liang
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Huimin Yan
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China
| | - Guangyu Zhu
- Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI, USA
| | - Bo Zhang
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
- Biostatistics and Research Design Center, Institutional Centers for Clinical and Translational Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Guang Yang
- Department of Pediatrics, First Medical Center, Chinese PLA General Hospital, Beijing, China.
- Senior Department of Pediatrics, Seventh Medical Center, PLA General Hospital, Beijing, 100000, China.
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
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7
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Juarez-Martinez EL, van Andel DM, Sprengers JJ, Avramiea AE, Oranje B, Scheepers FE, Jansen FE, Mansvelder HD, Linkenkaer-Hansen K, Bruining H. Bumetanide Effects on Resting-State EEG in Tuberous Sclerosis Complex in Relation to Clinical Outcome: An Open-Label Study. Front Neurosci 2022; 16:879451. [PMID: 35645706 PMCID: PMC9134117 DOI: 10.3389/fnins.2022.879451] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 04/15/2022] [Indexed: 12/05/2022] Open
Abstract
Neuronal excitation-inhibition (E/I) imbalances are considered an important pathophysiological mechanism in neurodevelopmental disorders. Preclinical studies on tuberous sclerosis complex (TSC), suggest that altered chloride homeostasis may impair GABAergic inhibition and thereby E/I-balance regulation. Correction of chloride homeostasis may thus constitute a treatment target to alleviate behavioral symptoms. Recently, we showed that bumetanide-a chloride-regulating agent-improved behavioral symptoms in the open-label study Bumetanide to Ameliorate Tuberous Sclerosis Complex Hyperexcitable Behaviors trial (BATSCH trial; Eudra-CT: 2016-002408-13). Here, we present resting-state EEG as secondary analysis of BATSCH to investigate associations between EEG measures sensitive to network-level changes in E/I balance and clinical response to bumetanide. EEGs of 10 participants with TSC (aged 8-21 years) were available. Spectral power, long-range temporal correlations (LRTC), and functional E/I ratio (fE/I) in the alpha-frequency band were compared before and after 91 days of treatment. Pre-treatment measures were compared against 29 typically developing children (TDC). EEG measures were correlated with the Aberrant Behavioral Checklist-Irritability subscale (ABC-I), the Social Responsiveness Scale-2 (SRS-2), and the Repetitive Behavior Scale-Revised (RBS-R). At baseline, TSC showed lower alpha-band absolute power and fE/I than TDC. Absolute power increased through bumetanide treatment, which showed a moderate, albeit non-significant, correlation with improvement in RBS-R. Interestingly, correlations between baseline EEG measures and clinical outcomes suggest that most responsiveness might be expected in children with network characteristics around the E/I balance point. In sum, E/I imbalances pointing toward an inhibition-dominated network are present in TSC. We established neurophysiological effects of bumetanide although with an inconclusive relationship with clinical improvement. Nonetheless, our results further indicate that baseline network characteristics might influence treatment response. These findings highlight the possible utility of E/I-sensitive EEG measures to accompany new treatment interventions for TSC. Clinical Trial Registration EU Clinical Trial Register, EudraCT 2016-002408-13 (www.clinicaltrialsregister.eu/ctr-search/trial/2016-002408-13/NL). Registered 25 July 2016.
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Affiliation(s)
- Erika L. Juarez-Martinez
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
- Child and Adolescent Psychiatry and Psychosocial Care, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorinde M. van Andel
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Jan J. Sprengers
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Arthur-Ervin Avramiea
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Bob Oranje
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Floortje E. Scheepers
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Floor E. Jansen
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Huibert D. Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Hilgo Bruining
- Child and Adolescent Psychiatry and Psychosocial Care, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht, Netherlands
- N=You Neurodevelopmental Precision Center, Amsterdam Neuroscience, Amsterdam Reproduction and Development, Amsterdam UMC, Amsterdam, Netherlands
- Levvel, Academic Center for Child and Adolescent Psychiatry, Amsterdam, Netherlands
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8
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Huang J, Ahlers E, Bogatsch H, Böhme P, Ethofer T, Fallgatter AJ, Gallinat J, Hegerl U, Heuser I, Hoffmann K, Kittel-Schneider S, Reif A, Schöttle D, Unterecker S, Gärtner M, Strauß M. The role of comorbid depressive symptoms on long-range temporal correlations in resting EEG in adults with ADHD. Eur Arch Psychiatry Clin Neurosci 2022; 272:1421-1435. [PMID: 35781841 PMCID: PMC9653316 DOI: 10.1007/s00406-022-01452-2] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 06/12/2022] [Indexed: 11/23/2022]
Abstract
Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder, characterized by core symptoms of inattention, hyperactivity and impulsivity. Comorbid depression is commonly observed in ADHD-patients. Psychostimulants are recommended as first-line treatment for ADHD. Aberrant long-range temporal correlations (LRTCs) of neuronal activities in resting-state are known to be associated with disorganized thinking and concentrating difficulties (typical in ADHD) and with maladaptive thinking (typical in depression). It has yet to be examined whether (1) LRTC occur in ADHD-patients, and if so, (2) whether LRTC might be a competent biomarker in ADHD comorbid with current depression and (3) how depression affects psychostimulant therapy of ADHD symptoms. The present study registered and compared LRTCs in different EEG frequency bands in 85 adults with ADHD between groups with (n = 28) and without (n = 57) additional depressive symptoms at baseline. Treatment-related changes in ADHD, depressive symptoms and LRTC were investigated in the whole population and within each group. Our results revealed significant LRTCs existed in all investigated frequency bands. There were, however, no significant LRTC-differences between ADHD-patients with and without depressive symptoms at baseline and no LRTC-changes following treatment. However, depressed ADHD patients did seem to benefit more from the therapy with psychostimulant based on self-report.
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Affiliation(s)
- Jue Huang
- Department of Psychiatry and Psychotherapy, University of Leipzig, 04103, Leipzig, Germany.
| | - Eike Ahlers
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin, 10117 Berlin, Germany
| | - Holger Bogatsch
- grid.9647.c0000 0004 7669 9786Clinical Trial Centre Leipzig, Faculty of Medicine, University of Leipzig, 04107 Leipzig, Germany
| | - Pierre Böhme
- grid.411091.cDepartment of Psychiatry Psychotherapy and Preventive Medicine, University Hospital of Bochum, 44791 Bochum, Germany
| | - Thomas Ethofer
- grid.411544.10000 0001 0196 8249Department of Biomedical Magnetic Resonance, University Hospital of Tübingen, 72076 Tübingen, Germany ,grid.10392.390000 0001 2190 1447Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, 72076 Tübingen, Germany
| | - Andreas J. Fallgatter
- grid.10392.390000 0001 2190 1447Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, 72076 Tübingen, Germany
| | - Jürgen Gallinat
- grid.13648.380000 0001 2180 3484Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Ulrich Hegerl
- grid.411088.40000 0004 0578 8220Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, University Hospital of Frankfurt – Goethe University, 60528 Frankfurt am Main, Germany
| | - Isabella Heuser
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin, 10117 Berlin, Germany
| | - Knut Hoffmann
- grid.411091.cDepartment of Psychiatry Psychotherapy and Preventive Medicine, University Hospital of Bochum, 44791 Bochum, Germany
| | - Sarah Kittel-Schneider
- grid.411088.40000 0004 0578 8220Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, University Hospital of Frankfurt – Goethe University, 60528 Frankfurt am Main, Germany ,grid.411760.50000 0001 1378 7891Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, 97080 Würzburg, Germany
| | - Andreas Reif
- grid.411088.40000 0004 0578 8220Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, University Hospital of Frankfurt – Goethe University, 60528 Frankfurt am Main, Germany
| | - Daniel Schöttle
- grid.13648.380000 0001 2180 3484Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Stefan Unterecker
- grid.411760.50000 0001 1378 7891Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, 97080 Würzburg, Germany
| | - Matti Gärtner
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin, 10117 Berlin, Germany ,grid.466457.20000 0004 1794 7698MSB Medical School Berlin, 14179 Berlin, Germany
| | - Maria Strauß
- grid.9647.c0000 0004 7669 9786Department of Psychiatry and Psychotherapy, University of Leipzig, 04103 Leipzig, Germany
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9
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Smith RJ, Hu DK, Shrey DW, Rajaraman R, Hussain SA, Lopour BA. Computational characteristics of interictal EEG as objective markers of epileptic spasms. Epilepsy Res 2021; 176:106704. [PMID: 34218209 DOI: 10.1016/j.eplepsyres.2021.106704] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 05/26/2021] [Accepted: 06/23/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVE Favorable neurodevelopmental outcomes in epileptic spasms (ES) are tied to early diagnosis and prompt treatment, but uncertainty in the identification of the disease can delay this process. Therefore, we investigated five categories of computational electroencephalographic (EEG) measures as markers of ES. METHODS We measured 1) amplitude, 2) power spectra, 3) Shannon entropy and permutation entropy, 4) long-range temporal correlations, via detrended fluctuation analysis (DFA) and 5) functional connectivity using cross-correlation and phase lag index (PLI). EEG data were analyzed from ES patients (n = 40 patients) and healthy controls (n = 20 subjects), with multiple blinded measurements during wakefulness and sleep for each patient. RESULTS In ES patients, EEG amplitude was significantly higher in all electrodes when compared to controls. Shannon and permutation entropy were lower in ES patients than control subjects. The DFA intercept values in ES patients were significantly higher than control subjects, while DFA exponent values were not significantly different between the groups. EEG functional connectivity networks in ES patients were significantly stronger than controls when based on both cross-correlation and PLI. Significance for all statistical tests was p < 0.05, adjusted for multiple comparisons using the Benjamini-Hochberg procedure as appropriate. Finally, using logistic regression, a multi-attribute classifier was derived that accurately distinguished cases from controls (area under curve of 0.96). CONCLUSIONS Computational EEG features successfully distinguish ES patients from controls in a large, blinded study. SIGNIFICANCE These objective EEG markers, in combination with other clinical factors, may speed the diagnosis and treatment of the disease, thereby improving long-term outcomes.
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Affiliation(s)
- Rachel J Smith
- Department of Biomedical Engineering, University of California, Irvine, CA, United States
| | - Derek K Hu
- Department of Biomedical Engineering, University of California, Irvine, CA, United States
| | - Daniel W Shrey
- Division of Neurology, Children's Hospital of Orange County, Orange, CA, United States; Department of Pediatrics, University of California, Irvine, CA, United States
| | - Rajsekar Rajaraman
- Division of Pediatric Neurology, University of California, Los Angeles, CA, United States
| | - Shaun A Hussain
- Division of Pediatric Neurology, University of California, Los Angeles, CA, United States
| | - Beth A Lopour
- Department of Biomedical Engineering, University of California, Irvine, CA, United States.
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10
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Smith RJ, Alipourjeddi E, Garner C, Maser AL, Shrey DW, Lopour BA. Infant functional networks are modulated by state of consciousness and circadian rhythm. Netw Neurosci 2021; 5:614-630. [PMID: 34189380 PMCID: PMC8233111 DOI: 10.1162/netn_a_00194] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 03/22/2021] [Indexed: 01/05/2023] Open
Abstract
Functional connectivity networks are valuable tools for studying development, cognition, and disease in the infant brain. In adults, such networks are modulated by the state of consciousness and the circadian rhythm; however, it is unknown if infant brain networks exhibit similar variation, given the unique temporal properties of infant sleep and circadian patterning. To address this, we analyzed functional connectivity networks calculated from long-term EEG recordings (average duration 20.8 hr) from 19 healthy infants. Networks were subject specific, as intersubject correlations between weighted adjacency matrices were low. However, within individual subjects, both sleep and wake networks were stable over time, with stronger functional connectivity during sleep than wakefulness. Principal component analysis revealed the presence of two dominant networks; visual sleep scoring confirmed that these corresponded to sleep and wakefulness. Lastly, we found that network strength, degree, clustering coefficient, and path length significantly varied with time of day, when measured in either wakefulness or sleep at the group level. Together, these results suggest that modulation of healthy functional networks occurs over ∼24 hr and is robust and repeatable. Accounting for such temporal periodicities may improve the physiological interpretation and use of functional connectivity analysis to investigate brain function in health and disease.
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Affiliation(s)
- Rachel J. Smith
- Department of Biomedical Engineering, University of California, Irvine, CA, USA
| | - Ehsan Alipourjeddi
- Department of Biomedical Engineering, University of California, Irvine, CA, USA
| | - Cristal Garner
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Amy L. Maser
- Department of Psychology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Daniel W. Shrey
- Division of Neurology, Children’s Hospital of Orange County, Orange, CA, USA
- Department of Pediatrics, University of California, Irvine, Irvine, CA, USA
| | - Beth A. Lopour
- Department of Biomedical Engineering, University of California, Irvine, CA, USA
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11
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Hou F, Zhang L, Qin B, Gaggioni G, Liu X, Vandewalle G. Changes in EEG permutation entropy in the evening and in the transition from wake to sleep. Sleep 2021; 44:5959865. [PMID: 33159205 DOI: 10.1093/sleep/zsaa226] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 09/30/2020] [Indexed: 02/02/2023] Open
Abstract
Quantifying the complexity of the EEG signal during prolonged wakefulness and during sleep is gaining interest as an additional mean to characterize the mechanisms associated with sleep and wakefulness regulation. Here, we characterized how EEG complexity, as indexed by Multiscale Permutation Entropy (MSPE), changed progressively in the evening prior to light off and during the transition from wakefulness to sleep. We further explored whether MSPE was able to discriminate between wakefulness and sleep around sleep onset and whether MSPE changes were correlated with spectral measures of the EEG related to sleep need during concomitant wakefulness (theta power-Ptheta: 4-8 Hz). To address these questions, we took advantage of large datasets of several hundred of ambulatory EEG recordings of individual of both sexes aged 25-101 years. Results show that MSPE significantly decreases before light off (i.e. before sleep time) and in the transition from wakefulness to sleep onset. Furthermore, MSPE allows for an excellent discrimination between pre-sleep wakefulness and early sleep. Finally, we show that MSPE is correlated with concomitant Ptheta. Yet, the direction of the latter correlation changed from before light-off to the transition to sleep. Given the association between EEG complexity and consciousness, MSPE may track efficiently putative changes in consciousness preceding sleep onset. An MSPE stands as a comprehensive measure that is not limited to a given frequency band and reflects a progressive change brain state associated with sleep and wakefulness regulation. It may be an effective mean to detect when the brain is in a state close to sleep onset.
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Affiliation(s)
- Fengzhen Hou
- School of Science, China Pharmaceutical University, Nanjing, China
| | - Lulu Zhang
- School of Science, China Pharmaceutical University, Nanjing, China
| | - Baokun Qin
- School of Computer, Chongqing University, Chongqing, China
| | - Giulia Gaggioni
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Xinyu Liu
- School of Science, China Pharmaceutical University, Nanjing, China
| | - Gilles Vandewalle
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
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12
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Chu YJ, Chang CF, Weng WC, Fan PC, Shieh JS, Lee WT. Electroencephalography complexity in infantile spasms and its association with treatment response. Clin Neurophysiol 2021; 132:480-486. [PMID: 33450568 DOI: 10.1016/j.clinph.2020.12.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/03/2020] [Accepted: 12/14/2020] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To investigate the potential of EEG multiscale entropy and complexity as biomarkers in infantile spasms. METHODS We collected EEG data retrospectively from 16 newly diagnosed patients, 16 age- and gender-matched healthy controls, and 15 drug-resistant patients. The multiscale entropy (MSE) and total EEG complexity before anti-epileptic drug (AED) treatment, before adrenocorticotropic hormone (ACTH) treatment, 14 days after ACTH therapy, and after 6 months of follow-up were calculated. RESULTS The total EEG complexity of 16 newly diagnosed infantile spasms patients was lower than the 16 healthy controls (median [IQR]: 351.5 [323.1-388.1] vs 461.6 [407.7-583.4]). The total EEG complexity before treatment was higher in the six patients with good response to AED than the 10 patients without response (median [IQR]: 410.0 [388.1-475.0] vs 344.5 [319.6-352.0]). The total EEG complexity before and after 14-days of ACTH therapy was not different between 13 ACTH therapy responders and nine non-responders. After 6-months follow-up, the total EEG complexity of ACTH therapy responders were higher than non-responders (median [IQR]: 598.5 [517.4-623.3] vs 448.6 [347.1-536.3]). CONCLUSIONS The total EEG complexity before AED and 6 months after ACTH are associated with spasm-freedom. SIGNIFICANCE The total EEG complexity is a potential biomarker to predict and monitor the treatment effect in infantile spasms.
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Affiliation(s)
- Yen-Ju Chu
- Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan; Department of Pediatric Neurology, National Taiwan University Children's Hospital, Taipei, Taiwan
| | - Chi-Feng Chang
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Wen-Chin Weng
- Department of Pediatric Neurology, National Taiwan University Children's Hospital, Taipei, Taiwan; Department of Pediatrics, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Pi-Chuan Fan
- Department of Pediatric Neurology, National Taiwan University Children's Hospital, Taipei, Taiwan; Department of Pediatrics, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Jiann-Shing Shieh
- Department of Mechanical Engineering, Yuan Ze University, Taoyuan, Taiwan; Innovation Center for Biomedical and Healthcare Technology, Yuan Ze University, Taoyuan, Taiwan; Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan
| | - Wang-Tso Lee
- Department of Pediatric Neurology, National Taiwan University Children's Hospital, Taipei, Taiwan; Department of Pediatrics, National Taiwan University College of Medicine, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan.
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13
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Höller Y, Nardone R. Quantitative EEG biomarkers for epilepsy and their relation to chemical biomarkers. Adv Clin Chem 2020; 102:271-336. [PMID: 34044912 DOI: 10.1016/bs.acc.2020.08.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The electroencephalogram (EEG) is the most important method to diagnose epilepsy. In clinical settings, it is evaluated by experts who identify patterns visually. Quantitative EEG is the application of digital signal processing to clinical recordings in order to automatize diagnostic procedures, and to make patterns visible that are hidden to the human eye. The EEG is related to chemical biomarkers, as electrical activity is based on chemical signals. The most well-known chemical biomarkers are blood laboratory tests to identify seizures after they have happened. However, research on chemical biomarkers is much less extensive than research on quantitative EEG, and combined studies are rarely published, but highly warranted. Quantitative EEG is as old as the EEG itself, but still, the methods are not yet standard in clinical practice. The most evident application is an automation of manual work, but also a quantitative description and localization of interictal epileptiform events as well as seizures can reveal important hints for diagnosis and contribute to presurgical evaluation. In addition, the assessment of network characteristics and entropy measures were found to reveal important insights into epileptic brain activity. Application scenarios of quantitative EEG in epilepsy include seizure prediction, pharmaco-EEG, treatment monitoring, evaluation of cognition, and neurofeedback. The main challenges to quantitative EEG are poor reliability and poor generalizability of measures, as well as the need for individualization of procedures. A main hindrance for quantitative EEG to enter clinical routine is also that training is not yet part of standard curricula for clinical neurophysiologists.
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Affiliation(s)
- Yvonne Höller
- Faculty of Psychology, University of Akureyri, Akureyri, Iceland.
| | - Raffaele Nardone
- Department of Neurology, Franz Tappeiner Hospital, Merano, Italy; Spinal Cord Injury and Tissue Regeneration Center, Salzburg, Austria; Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria
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14
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Velíšek L, Velíšková J. Modeling epileptic spasms during infancy: Are we heading for the treatment yet? Pharmacol Ther 2020; 212:107578. [PMID: 32417271 DOI: 10.1016/j.pharmthera.2020.107578] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 05/07/2020] [Indexed: 12/22/2022]
Abstract
Infantile spasms (IS or epileptic spasms during infancy) were first described by Dr. William James West (aka West syndrome) in his own son in 1841. While rare by definition (occurring in 1 per 3200-3400 live births), IS represent a major social and treatment burden. The etiology of IS varies - there are many (>200) different known pathologies resulting in IS and still in about one third of cases there is no obvious reason. With the advancement of genetic analysis, role of certain genes (such as ARX or CDKL5 and others) in IS appears to be important. Current treatment strategies with incomplete efficacy and serious potential adverse effects include adrenocorticotropin (ACTH), corticosteroids (prednisone, prednisolone) and vigabatrin, more recently also a combination of hormones and vigabatrin. Second line treatments include pyridoxine (vitamin B6) and ketogenic diet. Additional treatment approaches use rapamycin, cannabidiol, valproic acid and other anti-seizure medications. Efficacy of these second line medications is variable but usually inferior to hormonal treatments and vigabatrin. Thus, new and effective models of this devastating condition are required for the search of additional treatment options as well as for better understanding the mechanisms of IS. Currently, eight models of IS are reviewed along with the ideas and mechanisms behind these models, drugs tested using the models and their efficacy and usefulness. Etiological variety of IS is somewhat reflected in the variety of the models. However, it seems that for finding precise personalized approaches, this variety is necessary as there is no "one-size-fits-all" approach possible for both IS in particular and epilepsy in general.
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Affiliation(s)
- Libor Velíšek
- Departments of Cell Biology & Anatomy, New York Medical College, Valhalla, NY, USA; Departments of Pediatrics, New York Medical College, Valhalla, NY, USA; Departments of Neurology, New York Medical College, Valhalla, NY, USA.
| | - Jana Velíšková
- Departments of Cell Biology & Anatomy, New York Medical College, Valhalla, NY, USA; Departments of Neurology, New York Medical College, Valhalla, NY, USA; Departments of Obstetrics & Gynecology, New York Medical College, Valhalla, NY, USA
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15
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Smith RJ, Ombao HC, Shrey DW, Lopour BA. Inference on Long-Range Temporal Correlations in Human EEG Data. IEEE J Biomed Health Inform 2020; 24:1070-1079. [DOI: 10.1109/jbhi.2019.2936326] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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16
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Smith RJ, Shrey DW, Hussain SA, Lopour BA. Quantitative Characteristics of Hypsarrhythmia in Infantile Spasms. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2018:538-541. [PMID: 30440453 DOI: 10.1109/embc.2018.8512348] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Infantile spasms is a type of epilepsy characterized by clinical seizures termed "spasms" and often an electroencephalographic (EEG) pattern known as hypsarrhythmia. Multiple studies have shown that the interrater reliability for human visual recognition of hypsarrhythmia is poor. Quantitative measurements of this EEG pattern would provide objective basis for identification; however, the basic temporal and spectral characteristics of hypsarrhythmia have never been assessed. Thus, we measured EEG amplitude and power spectra in 21 infantile spasms patients before and after treatment, as well as 21 control subjects. The hypsarrhythmia EEG pattern was associated with (1) high broadband amplitude, especially in frontal and central brain regions, (2) high median power in the delta and alpha frequency bands, and (3) low spectral edge frequency. Our results indicate that hypsarrhythmia can be quantitatively distinguished from data without hypsarrhythmia. Introduction of these quantitative measures into clinical practice may increase diagnostic accuracy, expediting proper treatment and improving outcomes.
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17
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Seleznov I, Zyma I, Kiyono K, Tukaev S, Popov A, Chernykh M, Shpenkov O. Detrended Fluctuation, Coherence, and Spectral Power Analysis of Activation Rearrangement in EEG Dynamics During Cognitive Workload. Front Hum Neurosci 2019; 13:270. [PMID: 31440151 PMCID: PMC6694837 DOI: 10.3389/fnhum.2019.00270] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 07/19/2019] [Indexed: 12/31/2022] Open
Abstract
In the study of human cognitive activity using electroencephalogram (EEG), the brain dynamics parameters and characteristics play a crucial role. They allow to investigate the changes in functionality depending on the environment and task performance process, and also to access the intensity of the brain activity in various locations of the cortex and its dependencies. Usually, the dynamics of activation of different brain areas during the cognitive tasks are being studied by spectral analysis based on power spectral density (PSD) estimation, and coherence analysis, which are de facto standard tools in quantitative characterization of brain activity. PSD and coherence reflect the strength of oscillations and similarity of the emergence of these oscillations in the brain, respectively, while the concept of stability of brain activity over time is not well defined and less formalized. We propose to employ the detrended fluctuation analysis (DFA) as a measure of the EEG persistence over time, and use the DFA scaling exponent as its quantitative characteristics. We applied DFA to the study of the changes in activation in brain dynamics during mental calculations and united it with PSD and coherence estimation. In the experiment, EEGs during resting state and mental serial subtraction from 36 subjects were recorded and analyzed in four frequency ranges: θ1 (4.1-5.8 Hz), θ2 (5.9-7.4 Hz), β1 (13-19.9 Hz), and β2 (20-25 Hz). PSD maps to access the intensity of cortex activation and coherence to quantify the connections between different brain areas were calculated, the distribution of DFA scaling exponent over the head surface was exploited to measure the time characteristics of the dynamics of brain activity. Obtained arrangements of DFA scaling exponent suggest that normal functioning of the brain is characterized by long-term temporal correlations in the cortex. Topographical distribution of the DFA scaling exponent was comparable for θ and β frequency bands, demonstrating the largest values of DFA scaling exponent during cognitive activation. The study shows that the long-term temporal correlations evaluated by DFA can be of great interest for diagnosis of the variety of brain dysfunctions of different etiology in the future.
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Affiliation(s)
- Ivan Seleznov
- Department of Electronic Engineering, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine
| | - Igor Zyma
- Department of Physiology and Anatomy, Educational and Scientific Center “Institute of Biology and Medicine”, National Taras Shevchenko University of Kyiv, Kyiv, Ukraine
| | - Ken Kiyono
- Division of Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan
| | - Sergii Tukaev
- Department of Physiology of Brain and Psychophysiology, Educational and Scientific Centre “Institute of Biology and Medicine”, National Taras Shevchenko University of Kyiv, Kyiv, Ukraine
- Department of Social Communication, Institute of Journalism, National Taras Shevchenko University of Kyiv, Kyiv, Ukraine
- Laboratory on Theory and Methodic of Sport Preparation and Reserve Capabilities of Athletes, Scientific Research Institute, National University of Physical Education and Sports of Ukraine, Kyiv, Ukraine
| | - Anton Popov
- Department of Electronic Engineering, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine
- R&D Engineering, Ciklum, London, United Kingdom
| | - Mariia Chernykh
- Department of Biophysics and Medical Informatics, Educational and Scientific Center “Institute of Biology and Medicine”, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
| | - Oleksii Shpenkov
- Department of Physiology and Anatomy, Educational and Scientific Center “Institute of Biology and Medicine”, National Taras Shevchenko University of Kyiv, Kyiv, Ukraine
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18
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Davis PE, Kapur K, Filip-Dhima R, Trowbridge SK, Little E, Wilson A, Leuchter A, Bebin EM, Krueger D, Northrup H, Wu JY, Sahin M, Peters JM. Increased electroencephalography connectivity precedes epileptic spasm onset in infants with tuberous sclerosis complex. Epilepsia 2019; 60:1721-1732. [PMID: 31297797 PMCID: PMC6687536 DOI: 10.1111/epi.16284] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Revised: 06/16/2019] [Accepted: 06/17/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To identify whether abnormal electroencephalography (EEG) connectivity is present before the onset of epileptic spasms (ES) in infants with tuberous sclerosis complex (TSC). METHODS Scalp EEG recordings were collected prospectively in infants diagnosed with TSC in the first year of life. This study compared the earliest recorded EEG from infants prior to ES onset (n = 16) and from infants who did not develop ES (n = 28). Five minutes of stage II or quiet sleep was clipped and filtered into canonical EEG frequency bands. Mutual information values between each pair of EEG channels were compared directly and used as a weighted graph to calculate graph measures of global efficiency, characteristic path length, average clustering coefficient, and modularity. RESULTS At the group level, infants who later developed ES had increased EEG connectivity in sleep. They had higher mutual information values between most EEG channels in all frequency bands adjusted for age. Infants who later developed ES had higher global efficiency and average clustering coefficients, shorter characteristic path lengths, and lower modularity across most frequency bands adjusted for age. This suggests that infants who went on to develop ES had increased local and long-range EEG connectivity with less segregation of graph regions into distinct modules. SIGNIFICANCE This study suggests that increased neural connectivity precedes clinical ES onset in a cohort of infants with TSC. Overconnectivity may reflect progressive pathologic network synchronization culminating in generalized ES. Further research is needed before scalp EEG connectivity measures can be used as a potential biomarker of ES risk and treatment response in pre-symptomatic infants with TSC.
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Affiliation(s)
- Peter E. Davis
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Kush Kapur
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Rajna Filip-Dhima
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Sara K. Trowbridge
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Elaina Little
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Andrew Wilson
- Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California
| | - Andrew Leuchter
- Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California
| | - E. Martina Bebin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama
| | - Darcy Krueger
- Department of Neurology and Rehabilitation Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
| | - Hope Northrup
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Joyce Y. Wu
- Division of Pediatric Neurology, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - Mustafa Sahin
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
- F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jurriaan M. Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
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19
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Identification of Hypsarrhythmia in Children with Microcephaly Infected by Zika Virus. ENTROPY 2019; 21:e21030232. [PMID: 33266947 PMCID: PMC7514713 DOI: 10.3390/e21030232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 02/08/2019] [Accepted: 02/22/2019] [Indexed: 11/17/2022]
Abstract
Hypsarrhythmia is an electroencephalographic pattern specific to some epileptic syndromes that affect children under one year of age. The identification of this pattern, in some cases, causes disagreements between experts, which is worrisome since an inaccurate diagnosis can bring complications to the infant. Despite the difficulties in visually identifying hypsarrhythmia, options of computerized assistance are scarce. Aiming to collaborate with the recognition of this electropathological pattern, we propose in this paper a mathematical index that can help electroencephalography experts to identify hypsarrhythmia. We performed hypothesis tests that indicated significant differences in the groups under analysis, where the p-values were found to be extremely small.
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