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Guerrero-Aranda A, Alvarado-Rodríguez FJ, Enríquez-Zaragoza A, Carmona-Huerta J, González-Garrido AA. Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders. Clin EEG Neurosci 2024; 55:296-304. [PMID: 37849312 DOI: 10.1177/15500594231208245] [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] [Indexed: 10/19/2023]
Abstract
Background: People diagnosed with substance use disorders (SUDs) are at risk for impairment of brain function and structure. However, physicians still do not have any clinical biomarker of brain impairment that helps diagnose or treat these patients when needed. The most common method to study these patients is the classical electroencephalographic (EEG) analyses of absolute and relative powers, but this has limited individual clinical applicability. Other non-classical measures such as frequency band ratios and entropy show promise in these patients. Therefore, there is a need to expand the use of quantitative (q)EEG beyond classical measures in clinical populations. Our aim is to assess a group of classical and non-classical qEEG measures in a population with SUDs. Methods: We selected 56 non-medicated and drug-free adult patients (30 males) diagnosed with SUDs and admitted to Rehabilitation Clinics. According to qualitative EEG findings, patients were divided into four groups. We estimated the absolute and relative powers and calculated the entropy, and the alpha/(delta + theta) ratio. Results: Our findings showed a significant variability of absolute and relative powers among patients with SUDs. We also observed a decrease in the EEG-based entropy index and alpha/(theta + delta) ratio, mainly in posterior regions, in the patients with abnormal qualitative EEG. Conclusions: Our findings support the view that the power spectrum is not a reliable biomarker on an individual level. Thus, we suggest shifting the approach from the power spectrum toward other potential methods and designs that may offer greater clinical possibilities.
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Affiliation(s)
- Alioth Guerrero-Aranda
- University Center "Los Valles", University of Guadalajara, Ameca, México
- Department of EEG and Brain Mapping, Teleeg, México
| | | | | | - Jaime Carmona-Huerta
- University Center of Health Sciences, University of Guadalajara, Guadalajara, México
- Jalisco Institute of Mental Health, Salme, México
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2
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van der Molen MW, Snellings P, Aravena S, Fraga González G, Zeguers MHT, Verwimp C, Tijms J. Dyslexia, the Amsterdam Way. Behav Sci (Basel) 2024; 14:72. [PMID: 38275355 PMCID: PMC10813111 DOI: 10.3390/bs14010072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/27/2024] Open
Abstract
The current aim is to illustrate our research on dyslexia conducted at the Developmental Psychology section of the Department of Psychology, University of Amsterdam, in collaboration with the nationwide IWAL institute for learning disabilities (now RID). The collaborative efforts are institutionalized in the Rudolf Berlin Center. The first series of studies aimed at furthering the understanding of dyslexia using a gamified tool based on an artificial script. Behavioral measures were augmented with diffusion modeling in one study, and indices derived from the electroencephalogram were used in others. Next, we illustrated a series of studies aiming to assess individuals who struggle with reading and spelling using similar research strategies. In one study, we used methodology derived from the machine learning literature. The third series of studies involved intervention targeting the phonics of language. These studies included a network analysis that is now rapidly gaining prominence in the psychopathology literature. Collectively, the studies demonstrate the importance of letter-speech sound mapping and word decoding in the acquisition of reading. It was demonstrated that focusing on these abilities may inform the prediction, classification, and intervention of reading difficulties and their neural underpinnings. A final section examined dyslexia, conceived as a neurobiological disorder. This analysis converged on the conclusion that recent developments in the psychopathology literature inspired by the focus on research domain criteria and network analysis might further the field by staying away from longstanding debates in the dyslexia literature (single vs. a multiple deficit, category vs. dimension, disorder vs. lack of skill).
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Affiliation(s)
- Maurits W. van der Molen
- Developmental Psychology, Department of Psychology, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
- Rudolf Berlin Center for Learning Disabilities, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
| | - Patrick Snellings
- Developmental Psychology, Department of Psychology, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
- Rudolf Berlin Center for Learning Disabilities, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
| | | | | | - Maaike H. T. Zeguers
- Samenwerkingsverband VO Amsterdam-Diemen, Bijlmermeerdreef 1289, 1103 TV Amsterdam, The Netherlands
| | - Cara Verwimp
- Developmental Psychology, Department of Psychology, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
- Rudolf Berlin Center for Learning Disabilities, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
| | - Jurgen Tijms
- Developmental Psychology, Department of Psychology, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
- Rudolf Berlin Center for Learning Disabilities, University of Amsterdam, 1018 WS Amsterdam, The Netherlands
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3
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Zanus C, Miladinović A, De Dea F, Skabar A, Stecca M, Ajčević M, Accardo A, Carrozzi M. Sleep Spindle-Related EEG Connectivity in Children with Attention-Deficit/Hyperactivity Disorder: An Exploratory Study. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1244. [PMID: 37761543 PMCID: PMC10530036 DOI: 10.3390/e25091244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/20/2023] [Accepted: 08/16/2023] [Indexed: 09/29/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a neurobehavioral disorder with known brain abnormalities but no biomarkers to support clinical diagnosis. Recently, EEG analysis methods such as functional connectivity have rekindled interest in using EEG for ADHD diagnosis. Most studies have focused on resting-state EEG, while connectivity during sleep and spindle activity has been underexplored. Here we present the results of a preliminary study exploring spindle-related connectivity as a possible biomarker for ADHD. We compared sensor-space connectivity parameters in eight children with ADHD and nine age/sex-matched healthy controls during sleep, before, during, and after spindle activity in various frequency bands. All connectivity parameters were significantly different between the two groups in the delta and gamma bands, and Principal Component Analysis (PCA) in the gamma band distinguished ADHD from healthy subjects. Cluster coefficient and path length values in the sigma band were also significantly different between epochs, indicating different spindle-related brain activity in ADHD.
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Affiliation(s)
- Caterina Zanus
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, 34137 Trieste, Italy; (C.Z.); (M.C.)
| | - Aleksandar Miladinović
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, 34137 Trieste, Italy; (C.Z.); (M.C.)
| | - Federica De Dea
- Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy (M.A.); (A.A.)
- Department of Life Science, University of Trieste, 34127 Trieste, Italy
| | - Aldo Skabar
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, 34137 Trieste, Italy; (C.Z.); (M.C.)
| | - Matteo Stecca
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, 34137 Trieste, Italy; (C.Z.); (M.C.)
| | - Miloš Ajčević
- Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy (M.A.); (A.A.)
| | - Agostino Accardo
- Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy (M.A.); (A.A.)
| | - Marco Carrozzi
- Institute for Maternal and Child Health—IRCCS “Burlo Garofolo”, 34137 Trieste, Italy; (C.Z.); (M.C.)
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4
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Pellegrino M, Ben-Soussan TD, Paoletti P. A Scoping Review on Movement, Neurobiology and Functional Deficits in Dyslexia: Suggestions for a Three-Fold Integrated Perspective. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3315. [PMID: 36834011 PMCID: PMC9966639 DOI: 10.3390/ijerph20043315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/08/2023] [Accepted: 02/12/2023] [Indexed: 06/18/2023]
Abstract
Developmental dyslexia is a common complex neurodevelopmental disorder. Many theories and models tried to explain its symptomatology and find ways to improve poor reading abilities. The aim of this scoping review is to summarize current findings and several approaches and theories, focusing on the interconnectedness between motion, emotion and cognition and their connection to dyslexia. Consequently, we present first a brief overview of the main theories and models regarding dyslexia and its proposed neural correlates, with a particular focus on cerebellar regions and their involvement in this disorder. After examining different types of intervention programs and remedial training, we highlight the effects of a specific structured sensorimotor intervention named Quadrato Motor Training (QMT). QMT utilizes several cognitive and motor functions known to be relevant in developmental dyslexia. We introduce its potential beneficial effects on reading skills, including working memory, coordination and attention. We sum its effects ranging from behavioral to functional, structural and neuroplastic, especially in relation to dyslexia. We report several recent studies that employed this training technique with dyslexic participants, discussing the specific features that distinguish it from other training within the specific framework of the Sphere Model of Consciousness. Finally, we advocate for a new perspective on developmental dyslexia integrating motion, emotion and cognition to fully encompass this complex disorder.
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Affiliation(s)
- Michele Pellegrino
- Research Institute for Neuroscience, Education and Didactics, Patrizio Paoletti Foundation for Development and Communication, 06081 Assisi, Italy
| | - Tal Dotan Ben-Soussan
- Research Institute for Neuroscience, Education and Didactics, Patrizio Paoletti Foundation for Development and Communication, 06081 Assisi, Italy
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5
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Bauer W, Dylag KA, Lysiak A, Wieczorek-Stawinska W, Pelc M, Szmajda M, Martinek R, Zygarlicki J, Bańdo B, Stomal-Slowinska M, Kawala-Sterniuk A. Initial study on quantitative electroencephalographic analysis of bioelectrical activity of the brain of children with fetal alcohol spectrum disorders (FASD) without epilepsy. Sci Rep 2023; 13:109. [PMID: 36596841 PMCID: PMC9810692 DOI: 10.1038/s41598-022-26590-4] [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: 04/20/2022] [Accepted: 12/16/2022] [Indexed: 01/04/2023] Open
Abstract
Fetal alcohol spectrum disorders (FASD) are spectrum of neurodevelopmental conditions associated with prenatal alcohol exposure. The FASD manifests mostly with facial dysmorphism, prenatal and postnatal growth retardation, and selected birth defects (including central nervous system defects). Unrecognized and untreated FASD leads to severe disability in adulthood. The diagnosis of FASD is based on clinical criteria and neither biomarkers nor imaging tests can be used in order to confirm the diagnosis. The quantitative electroencephalography (QEEG) is a type of EEG analysis, which involves the use of mathematical algorithms, and which has brought new possibilities of EEG signal evaluation, among the other things-the analysis of a specific frequency band. The main objective of this study was to identify characteristic patterns in QEEG among individuals affected with FASD. This study was of a pilot prospective study character with experimental group consisting of patients with newly diagnosed FASD and of the control group consisting of children with gastroenterological issues. The EEG recordings of both groups were obtained, than analyzed using a commercial QEEG module. As a results we were able to establish the dominance of the alpha rhythm over the beta rhythm in FASD-participants compared to those from the control group, mostly in frontal and temporal regions. Second important finding is an increased theta/beta ratio among patients with FASD. These findings are consistent with the current knowledge on the pathological processes resulting from the prenatal alcohol exposure. The obtained results and conclusions were promising, however, further research is necessary (and planned) in order to validate the use of QEEG tools in FASD diagnostics.
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Affiliation(s)
- Waldemar Bauer
- grid.9922.00000 0000 9174 1488Department of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland
| | - Katarzyna Anna Dylag
- St. Louis Children Hospital in Krakow, 30-663 Kraków, Poland ,grid.5522.00000 0001 2162 9631Department of Pathophysiology, Jagiellonian University in Krakow – Collegium Medicum, 31-121 Kraków, Poland
| | - Adam Lysiak
- grid.440608.e0000 0000 9187 132XFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
| | | | - Mariusz Pelc
- grid.440608.e0000 0000 9187 132XFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland ,grid.36316.310000 0001 0806 5472School of Computing and Mathematical Sciences, University of Greenwich, London, SE10 9LS UK
| | - Miroslaw Szmajda
- grid.440608.e0000 0000 9187 132XFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
| | - Radek Martinek
- grid.440608.e0000 0000 9187 132XFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland ,grid.440850.d0000 0000 9643 2828Department of Cybernetics and Biomedical Engineering, VSB—Technical University Ostrava—FEECS, 708 00 Ostrava-Poruba, Czech Republic
| | - Jaroslaw Zygarlicki
- grid.440608.e0000 0000 9187 132XFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
| | - Bożena Bańdo
- St. Louis Children Hospital in Krakow, 30-663 Kraków, Poland
| | | | - Aleksandra Kawala-Sterniuk
- grid.440608.e0000 0000 9187 132XFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
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6
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Oliaee A, Mohebbi M, Shirani S, Rostami R. Extraction of discriminative features from EEG signals of dyslexic children; before and after the treatment. Cogn Neurodyn 2022; 16:1249-1259. [PMID: 36408072 PMCID: PMC9666605 DOI: 10.1007/s11571-022-09794-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 02/16/2022] [Accepted: 02/20/2022] [Indexed: 11/25/2022] Open
Abstract
Dyslexia is a neurological disorder manifested as difficulty reading and writing. It can occur despite adequate instruction, intelligence, and intact sensory abilities. Different electroencephalogram (EEG) patterns have been demonstrated between dyslexic and healthy subjects in previous studies. This study focuses on the difference between patients before and after treatment. The main goal is to identify the subset of features that adequately discriminate subjects before and after a specific treatment plan. The treatment consists of Transcranial Direct Current Stimulation (tDCS) and occupational therapy using the BrainWare SAFARI software. The EEG signals of sixteen dyslexic children were recorded during the eyes-closed resting state before and after treatment. The preprocessing step was followed by the extraction of a wide range of features to investigate the differences related to the treatment. An optimal subset of features extracted from recorded EEG signals was determined using Principal Component Analysis (PCA) in conjunction with the Sequential Floating Forward Selection (SFFS) algorithm. The results showed that treatment leads to significant changes in EEG features like spectral and phase-related EEG features, in various regions. It has been demonstrated that the extracted subset of discriminative features can be useful for classification applications in treatment assessment. The most discriminative subset of features could classify the data with an accuracy of 92% with SVM classifier. The above result confirms the efficacy of the treatment plans in improving dyslexic children's cognitive skills.
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Affiliation(s)
- Anahita Oliaee
- Department of Biomedical Engineering, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran
| | - Maryam Mohebbi
- Department of Biomedical Engineering, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran
| | - Sepehr Shirani
- Department of Biomedical Engineering, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran
| | - Reza Rostami
- Department of Psychology, Faculty of Psychology, University of Tehran, Tehran, Iran
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7
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Catherine Joy R, Thomas George S, Albert Rajan A, Subathra MSP. Detection of ADHD From EEG Signals Using Different Entropy Measures and ANN. Clin EEG Neurosci 2022; 53:12-23. [PMID: 34424101 DOI: 10.1177/15500594211036788] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Attention deficit hyperactivity disorder (ADHD) is a prevalent behavioral, cognitive, neurodevelopmental pediatric disorder. Clinical evaluations, symptom surveys, and neuropsychological assessments are some of the ADHD assessment methods, which are time-consuming processes and have a certain degree of uncertainty. This research investigates an efficient computer-aided technological solution for detecting ADHD from the acquired electroencephalography (EEG) signals based on different nonlinear entropy estimators and an artificial neural network classifier. Features extracted through fuzzy entropy, log energy entropy, permutation entropy, SURE entropy, and Shannon entropy are analyzed for effective discrimination of ADHD subjects from the control group. The experimented results confirm that the proposed techniques can effectively detect and classify ADHD subjects. The permutation entropy gives the highest classification accuracy of 99.82%, sensitivity of 98.21%, and specificity of 98.82%. Also, the potency of different entropy estimators derived from the t-test reflects that the Shannon entropy has a higher P-value (>.001); therefore, it has a limited scope than other entropy estimators for ADHD diagnosis. Furthermore, the considerable variance found from potential features obtained in the frontal polar (FP) and frontal (F) lobes using different entropy estimators under the eyes-closed condition shows that the signals received in these lobes will have more significance in distinguishing ADHD from normal subjects.
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Affiliation(s)
- R Catherine Joy
- Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
| | - S Thomas George
- Department of Biomedical Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
| | - A Albert Rajan
- Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
| | - M S P Subathra
- Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
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8
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Calzada-Reyes A, Alvarez-Amador A, Galán-Garcia L, Valdés-Sosa M. Electroencephalographic and morphometric abnormalities in psychopath offenders. BEHAVIORAL SCIENCES & THE LAW 2021; 39:597-610. [PMID: 34800344 DOI: 10.1002/bsl.2548] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 10/21/2021] [Accepted: 11/02/2021] [Indexed: 06/13/2023]
Abstract
The main goals of the present study were to replicate and extend current knowledge related to paralimbic dysfunctions associated with psychopathy. The research evaluated the quantitative electroencephalography, current density (CD) source and synchronization likelihood analysis during the rest condition and structural magnetic resonance imaging images to compare volumetric and cortical thickness, in inmates recruited from two prisons located in Havana City. The Psychopathy Checklist-Revised (PCL-R) was used as a quantitative measure of psychopathy. This study showed most beta energy and less alpha activity in male psychopath offenders. Low-resolution electromagnetic tomography signified an increase of beta activity in psychopath offender groups within paralimbic regions. The superior temporal gyrus volume was associated with the F1 factor while the fusiform, anterior cingulate and associative occipital areas were primarily associated with the F2 factor of PCL-R scale. Cortical thickness in the left dorsal anterior cingulate cortex and the temporal pole was negatively associated with PCL-R total score.
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Affiliation(s)
- Ana Calzada-Reyes
- Department of Clinical Neurophysiology, Cuban Center for Neuroscience, Havana, Cuba
| | | | | | - Mitchell Valdés-Sosa
- Department of Cognitive Neurosciences, Cuban Center for Neuroscience, Havana, Cuba
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Individual Alpha Peak Frequency, an Important Biomarker for Live Z-Score Training Neurofeedback in Adolescents with Learning Disabilities. Brain Sci 2021; 11:brainsci11020167. [PMID: 33525458 PMCID: PMC7911657 DOI: 10.3390/brainsci11020167] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 01/22/2021] [Accepted: 01/24/2021] [Indexed: 01/19/2023] Open
Abstract
Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to offer a possible explanation for differences in EEG maturation. In this study, 40 adolescents aged 10–15 years with LDs underwent 10 sessions of Live Z-Score Training Neurofeedback (LZT-NF) Training to improve their cognition and behavior. Based on the individual alpha peak frequency (i-APF) values from the spectrogram, a group with normal i-APF (ni-APF) and a group with low i-APF (li-APF) were compared in a pre-and-post-LZT-NF intervention. There were no statistical differences in age, gender, or the distribution of LDs between the groups. The li-APF group showed a higher theta absolute power in P4 (p = 0.016) at baseline and higher Hi-Beta absolute power in F3 (p = 0.007) post-treatment compared with the ni-APF group. In both groups, extreme waves (absolute Z-score of ≥1.5) were more likely to move toward the normative values, with better results in the ni-APF group. Conversely, the waves within the normal range at baseline were more likely to move out of the range after treatment in the li-APF group. Our results provide evidence of a viable biomarker for identifying optimal responders for the LZT-NF technique based on the i-APF metric reflecting the patient’s neurophysiological individuality.
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10
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Proteau-Lemieux M, Knoth IS, Agbogba K, Côté V, Barlahan Biag HM, Thurman AJ, Martin CO, Bélanger AM, Rosenfelt C, Tassone F, Abbeduto LJ, Jacquemont S, Hagerman R, Bolduc F, Hessl D, Schneider A, Lippé S. EEG Signal Complexity Is Reduced During Resting-State in Fragile X Syndrome. Front Psychiatry 2021; 12:716707. [PMID: 34858220 PMCID: PMC8632368 DOI: 10.3389/fpsyt.2021.716707] [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: 06/23/2021] [Accepted: 10/06/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction: Fragile X syndrome (FXS) is a genetic disorder caused by a mutation of the fragile X mental retardation 1 gene (FMR1). FXS is associated with neurophysiological abnormalities, including cortical hyperexcitability. Alterations in electroencephalogram (EEG) resting-state power spectral density (PSD) are well-defined in FXS and were found to be linked to neurodevelopmental delays. Whether non-linear dynamics of the brain signal are also altered remains to be studied. Methods: In this study, resting-state EEG power, including alpha peak frequency (APF) and theta/beta ratio (TBR), as well as signal complexity using multi-scale entropy (MSE) were compared between 26 FXS participants (ages 5-28 years), and 7 neurotypical (NT) controls with a similar age distribution. Subsequently a replication study was carried out, comparing our cohort to 19 FXS participants independently recorded at a different site. Results: PSD results confirmed the increased gamma, decreased alpha power and APF in FXS participants compared to NT controls. No alterations in TBR were found. Importantly, results revealed reduced signal complexity in FXS participants, specifically in higher scales, suggesting that altered signal complexity is sensitive to brain alterations in this population. The replication study mostly confirmed these results and suggested critical points of stagnation in the neurodevelopmental curve of FXS. Conclusion: Signal complexity is a powerful feature that can be added to the electrophysiological biomarkers of brain maturation in FXS.
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Affiliation(s)
- Mélodie Proteau-Lemieux
- Department of Psychology, University of Montreal, Montreal, QC, Canada.,Research Center of the Sainte-Justine University Hospital, Montreal, QC, Canada
| | - Inga Sophia Knoth
- Research Center of the Sainte-Justine University Hospital, Montreal, QC, Canada
| | - Kristian Agbogba
- Research Center of the Sainte-Justine University Hospital, Montreal, QC, Canada
| | - Valérie Côté
- Research Center of the Sainte-Justine University Hospital, Montreal, QC, Canada
| | - Hazel Maridith Barlahan Biag
- University of California Davis Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Sacramento, CA, United States
| | - Angela John Thurman
- University of California Davis Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Sacramento, CA, United States
| | | | - Anne-Marie Bélanger
- Research Center of the Sainte-Justine University Hospital, Montreal, QC, Canada
| | - Cory Rosenfelt
- Department of Pediatric Neurology, University of Alberta, Edmonton, AB, Canada
| | - Flora Tassone
- University of California Davis Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Sacramento, CA, United States.,Department of Biochemistry and Molecular Medicine, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Leonard J Abbeduto
- University of California Davis Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Sacramento, CA, United States.,Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Sébastien Jacquemont
- Research Center of the Sainte-Justine University Hospital, Montreal, QC, Canada.,Department of Pediatrics, University of Montreal, Montreal, QC, Canada
| | - Randi Hagerman
- University of California Davis Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Sacramento, CA, United States
| | - François Bolduc
- Department of Pediatric Neurology, University of Alberta, Edmonton, AB, Canada
| | - David Hessl
- University of California Davis Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Sacramento, CA, United States.,Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Andrea Schneider
- University of California Davis Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, Sacramento, CA, United States.,California North State University, College of Psychology, Rancho Cordova, CA, United States
| | - Sarah Lippé
- Department of Psychology, University of Montreal, Montreal, QC, Canada.,Research Center of the Sainte-Justine University Hospital, Montreal, QC, Canada
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