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Aanestad E, Gilhus NE, Brogger J. A New Score for Sharp Discharges in the EEG Predicts Epilepsy. J Clin Neurophysiol 2023; 40:9-16. [PMID: 33935218 PMCID: PMC9799053 DOI: 10.1097/wnp.0000000000000849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
PURPOSE A challenge in EEG interpretation is to correctly classify suspicious focal sharp activity as epileptiform or not. A predictive score was developed from morphologic features of the first focal sharp discharge, which can help in this decision. METHODS From a clinical standard EEG database, the authors identified 2,063 patients without a previous epilepsy diagnosis who had a focal sharp discharge in their EEG. Morphologic features (amplitude, area of slow wave, etc.) were extracted using an open source one-click algorithm in EEGLAB, masked to clinical classification. A score was developed from these features and validated with the clinical diagnosis of epilepsy over 2 to 6 years of follow-up. Independent external validation was performed in Kural long-term video-EEG monitoring dataset. RESULTS The score for the first focal sharp discharge had a moderate predictive performance for the clinical designation as the EEG being epileptiform (area under the receiver operating characteristics curve = 0.86). Best specificity was 91% and sensitivity 55%. The score also predicted a future epilepsy diagnosis (area under the receiver operating characteristics curve = 0.70). Best specificity was 86% and sensitivity 38%. Validation on the external dataset had an area under the receiver operating characteristics curve = 0.80. Clinical EEG identification of focal interictal epileptiform discharges had an area under the receiver operating characteristics curve = 0.73 for prediction of epilepsy. The score was based on amplitude, slope, difference from background, slow after-wave area, and age. Interrater reproducibility was high (ICC = 0.91). CONCLUSIONS The designation of the first focal sharp discharge as epileptiform depends on reproducible morphologic features. Characteristic features were amplitude, slope, slow after-wave area, and difference from background. The score was predictive of future epilepsy. Halford semiquantitative scale had similar diagnostic performance but lower reproducibility.
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Affiliation(s)
- Eivind Aanestad
- Section for Clinical Neurophysiology, Department of Neurology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Nils E. Gilhus
- Department of Neurology, Haukeland University Hospital, Bergen, Norway; and
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Jan Brogger
- Section for Clinical Neurophysiology, Department of Neurology, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
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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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Bruining H, Hardstone R, Juarez-Martinez EL, Sprengers J, Avramiea AE, Simpraga S, Houtman SJ, Poil SS, Dallares E, Palva S, Oranje B, Matias Palva J, Mansvelder HD, Linkenkaer-Hansen K. Measurement of excitation-inhibition ratio in autism spectrum disorder using critical brain dynamics. Sci Rep 2020; 10:9195. [PMID: 32513931 PMCID: PMC7280527 DOI: 10.1038/s41598-020-65500-4] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 05/04/2020] [Indexed: 12/20/2022] Open
Abstract
Balance between excitation (E) and inhibition (I) is a key principle for neuronal network organization and information processing. Consistent with this notion, excitation-inhibition imbalances are considered a pathophysiological mechanism in many brain disorders including autism spectrum disorder (ASD). However, methods to measure E/I ratios in human brain networks are lacking. Here, we present a method to quantify a functional E/I ratio (fE/I) from neuronal oscillations, and validate it in healthy subjects and children with ASD. We define structural E/I ratio in an in silico neuronal network, investigate how it relates to power and long-range temporal correlations (LRTC) of the network's activity, and use these relationships to design the fE/I algorithm. Application of this algorithm to the EEGs of healthy adults showed that fE/I is balanced at the population level and is decreased through GABAergic enforcement. In children with ASD, we observed larger fE/I variability and stronger LRTC compared to typically developing children (TDC). Interestingly, visual grading for EEG abnormalities that are thought to reflect E/I imbalances revealed elevated fE/I and LRTC in ASD children with normal EEG compared to TDC or ASD with abnormal EEG. We speculate that our approach will help understand physiological heterogeneity also in other brain disorders.
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Affiliation(s)
- Hilgo Bruining
- Department of Child and Adolescent Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Heidelberglaan 100, 3584CG, Utrecht, The Netherlands
| | - Richard Hardstone
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Neuroscience Institute, New York University School of Medicine, 435 East 30th Street, New York, NY, 10016, USA
| | - Erika L Juarez-Martinez
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Heidelberglaan 100, 3584CG, Utrecht, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Jan Sprengers
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Heidelberglaan 100, 3584CG, Utrecht, The Netherlands
| | - Arthur-Ervin Avramiea
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Sonja Simpraga
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands
- NBT Analytics BV, Amsterdam, The Netherlands
| | - Simon J Houtman
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | | | - Eva Dallares
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Satu Palva
- Neuroscience Center, Helsinki Institute for Life Sciences, University of Helsinki, FIN-00014, Helsinki, Finland
| | - Bob Oranje
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Heidelberglaan 100, 3584CG, Utrecht, The Netherlands
| | - J Matias Palva
- Neuroscience Center, Helsinki Institute for Life Sciences, University of Helsinki, FIN-00014, Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Central Hospital, FIN-00029, Hus, Finland
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands.
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Abstract
Idiopathic generalized epilepsy (IGE) is classified into several subsyndromes based on clinical and electroencephalography (EEG) features. The EEG signature of IGE is bisynchronous, symmetric, and generalized spike-wave complex; although focal, irregular, and so called "fragments" of discharges are not uncommon. Other characteristic EEG features include polyspikes, polyspike-wave discharges, occipital intermittent rhythmic delta activity, and photoparoxysmal response. Both human and animal data suggest involvement of the thalamus and the cortex in the generation of spike-wave discharges in IGE. Circadian variations of generalized epileptiform discharges are well described, and these can be useful in diagnostic confirmation. Those discharges tend to occur more often after awakening and during cyclic alternating pattern phase-A of non-rapid eye movement sleep. Activation procedures such as hyperventilation, intermittent photic stimulation, eye closure, and fixation-off are useful techniques to increase the yield of both interictal and ictal EEG abnormalities. Although not in routine use, specific triggers such as pattern stimulation and cognitive tasks may also be of value in eliciting rare reflex seizure-related EEG abnormalities. Variations of EEG abnormalities are evident between different electroclinical syndromes. EEG is also affected by certain external as well as internal factors, which should be borne in mind when interpreting EEG studies in IGE.
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Affiliation(s)
- Udaya Seneviratne
- Department of Medicine, St. Vincent's Hospital, University of Melbourne, Melbourne, Victoria, Australia.
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