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Thibault S, Wong AL, Buxbaum LJ. Cognitive neuropsychological and neuroanatomic predictors of naturalistic action performance in left hemisphere stroke: a retrospective analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.01.601398. [PMID: 39005391 PMCID: PMC11244907 DOI: 10.1101/2024.07.01.601398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Individuals who have experienced a left hemisphere cerebrovascular accident (LCVA) have been shown to make errors in naturalistic action tasks designed to assess the ability to perform everyday activities such as preparing a cup of coffee. Naturalistic action errors in this population are often attributed to limb apraxia, a common deficit in the representation and performance of object-related actions. However, naturalistic action impairments are also observed in right hemisphere stroke and traumatic brain injury, populations infrequently associated with apraxia, and errors across all these populations are influenced by overall severity. Based on these and other data, an alternative (though not mutually exclusive) account is that naturalistic action errors in LCVA are also a consequence of deficits in general attentional resource availability or allocation. In this study, we conducted a retrospective analysis of data from a large group of 51 individuals with LCVA who had completed a test of naturalistic action, along with a battery of tests assessing praxis, attention allocation and control, reasoning, and language abilities to determine which of these capacities contribute uniquely to naturalistic action impairments. Using a regularized regression method, we found that naturalistic action impairments are predicted by both praxis deficits (hand posture sequencing and gesture recognition), as well as attention allocation and control deficits (orienting and dividing attention), along with language comprehension ability and age. Using support vector regression-lesion symptom mapping (SVR-LSM), we also demonstrated that naturalistic action impairments are associated with lesions to posterior middle temporal gyrus and anterior inferior parietal lobule - regions known to be implicated in praxis; as well the middle frontal gyrus that has been implicated in both praxis and attention allocation and control. Taken together, these findings support the hypothesis that naturalistic action impairments in LCVA are a consequence of apraxia as well as deficits in attention allocation and control.
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Affiliation(s)
- Simon Thibault
- Moss Rehabilitation Research Institute, Thomas Jefferson University, Elkins Park, PA
| | - Aaron L. Wong
- Moss Rehabilitation Research Institute, Thomas Jefferson University, Elkins Park, PA
- Department of Rehabilitation Medicine, Thomas Jefferson University, Philadelphia, PA
| | - Laurel J. Buxbaum
- Moss Rehabilitation Research Institute, Thomas Jefferson University, Elkins Park, PA
- Department of Rehabilitation Medicine, Thomas Jefferson University, Philadelphia, PA
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Boxum M, Voetterl H, van Dijk H, Gordon E, DeBeus R, Arnold LE, Arns M. Challenging the Diagnostic Value of Theta/Beta Ratio: Insights From an EEG Subtyping Meta-Analytical Approach in ADHD. Appl Psychophysiol Biofeedback 2024:10.1007/s10484-024-09649-y. [PMID: 38858282 DOI: 10.1007/s10484-024-09649-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
The frequently reported high theta/beta ratio (TBR) in the electroencephalograms (EEGs) of children with attention-deficit/hyperactivity disorder (ADHD) has been suggested to include at least two distinct neurophysiological subgroups, a subgroup with high TBR and one with slow alpha peak frequency, overlapping the theta range. We combined three large ADHD cohorts recorded under standardized procedures and used a meta-analytical approach to leverage the large sample size (N = 417; age range: 6-18 years), classify these EEG subtypes and investigate their behavioral correlates to clarify their brain-behavior relationships. To control for the fact that slow alpha might contribute to theta power, three distinct EEG subgroups (non-slow-alpha TBR (NSAT) subgroup, slow alpha peak frequency (SAF) subgroup, not applicable (NA) subgroup) were determined, based on a halfway cut-off in age- and sex-normalized theta and alpha, informed by previous literature. For the meta-analysis, Cohen's d was calculated to assess the differences between EEG subgroups for baseline effects, using means and standard deviations of baseline inattention and hyperactivity-impulsivity scores. Non-significant, small Grand Mean effect sizes (-0.212 < d < 0.218) were obtained when comparing baseline behavioral scores between the EEG subgroups. This study could not confirm any association of EEG subtype with behavioral traits. This confirms previous findings suggesting that TBR has no diagnostic value for ADHD. TBR could, however, serve as an aid to stratify patients between neurofeedback protocols based on baseline TBR. A free online tool was made available for clinicians to calculate age- and sex-corrected TBR decile scores (Brainmarker-IV) for stratification of neurofeedback protocols.
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Affiliation(s)
- Marit Boxum
- Radboud University, Nijmegen, The Netherlands
- Research Institute Brainclinics, Brainclinics Foundation, Bijleveldsingel 32, 6524 AD, Nijmegen, The Netherlands
| | - Helena Voetterl
- Research Institute Brainclinics, Brainclinics Foundation, Bijleveldsingel 32, 6524 AD, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Hanneke van Dijk
- Research Institute Brainclinics, Brainclinics Foundation, Bijleveldsingel 32, 6524 AD, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Synaeda Psycho Medisch Centrum, Leeuwarden, The Netherlands
| | | | - Roger DeBeus
- The University of North Carolina at Asheville, Asheville, NC, USA
| | - L Eugene Arnold
- Department of Psychiatry &, Behavioral Health, Nisonger Center, Ohio State University, Columbus, OH, USA
| | - Martijn Arns
- Research Institute Brainclinics, Brainclinics Foundation, Bijleveldsingel 32, 6524 AD, Nijmegen, The Netherlands.
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
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Peterson BS, Trampush J, Brown M, Maglione M, Bolshakova M, Rozelle M, Miles J, Pakdaman S, Yagyu S, Motala A, Hempel S. Tools for the Diagnosis of ADHD in Children and Adolescents: A Systematic Review. Pediatrics 2024; 153:e2024065854. [PMID: 38523599 DOI: 10.1542/peds.2024-065854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/26/2024] [Indexed: 03/26/2024] Open
Abstract
CONTEXT Correct diagnosis is essential for the appropriate clinical management of attention-deficit/hyperactivity disorder (ADHD) in children and adolescents. OBJECTIVE This systematic review provides an overview of the available diagnostic tools. DATA SOURCES We identified diagnostic accuracy studies in 12 databases published from 1980 through June 2023. STUDY SELECTION Any ADHD tool evaluation for the diagnosis of ADHD, requiring a reference standard of a clinical diagnosis by a mental health specialist. DATA EXTRACTION Data were abstracted and critically appraised by 1 reviewer and checked by a methodologist. Strength of evidence and applicability assessments followed Evidence-based Practice Center standards. RESULTS In total, 231 studies met eligibility criteria. Studies evaluated parental ratings, teacher ratings, youth self-reports, clinician tools, neuropsychological tests, biospecimen, EEG, and neuroimaging. Multiple tools showed promising diagnostic performance, but estimates varied considerably across studies, with a generally low strength of evidence. Performance depended on whether ADHD youth were being differentiated from neurotypically developing children or from clinically referred children. LIMITATIONS Studies used different components of available tools and did not report sufficient data for meta-analytic models. CONCLUSIONS A valid and reliable diagnosis of ADHD requires the judgment of a clinician who is experienced in the evaluation of youth with and without ADHD, along with the aid of standardized rating scales and input from multiple informants across multiple settings, including parents, teachers, and youth themselves.
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Affiliation(s)
- Bradley S Peterson
- Institute for the Developing Mind, Children's Hospital Los Angeles, Los Angeles, California
- Department of Psychiatry, Keck School of Medicine at the University of Southern California, Los Angeles, California
| | - Joey Trampush
- Department of Psychiatry, Keck School of Medicine at the University of Southern California, Los Angeles, California
| | - Morah Brown
- Southern California Evidence Review Center, Los Angeles, California
| | | | - Maria Bolshakova
- Southern California Evidence Review Center, Los Angeles, California
| | - Mary Rozelle
- Southern California Evidence Review Center, Los Angeles, California
| | - Jeremy Miles
- Southern California Evidence Review Center, Los Angeles, California
| | - Sheila Pakdaman
- Southern California Evidence Review Center, Los Angeles, California
| | - Sachi Yagyu
- Southern California Evidence Review Center, Los Angeles, California
| | - Aneesa Motala
- Southern California Evidence Review Center, Los Angeles, California
| | - Susanne Hempel
- Southern California Evidence Review Center, Los Angeles, California
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Medrano Nava E, Flores-Lázaro JC, Nicolini Sánchez H, Juárez García F. Effects of comorbidity on executive functions among children with ADHD, finding trends. APPLIED NEUROPSYCHOLOGY. CHILD 2024; 13:100-112. [PMID: 36395527 DOI: 10.1080/21622965.2022.2135440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
There is still no basic overview about the effect of various types of comorbidity in executive functions due to two main reasons: (1) the type and number of comorbidities in ADHD is significantly varied, (2) EFs are very diverse and have different neuropsychological properties. Our objective was to determine the effect of comorbid disorders (number and type) on the performance in a wide range (seven) of executive functions in a sample of children with ADHD. Fifty-five male children aged seven to nine years with ADHD were divided into six groups: G1 = ADHD only (ADHD-O), G1 = Oppositional defiant disorder (ODD), G3 = (anxiety/depressive disorder (ADD), G4 = ODD + ADD, G5 = ODD + learning disorder (LD), G6 = ODD + LD + conduct disorder (CD). The six groups exhibited different number of deficits in EFs; G1 showed only 1 deficit in contrast, G6 presented 11. Statistical analysis (ANOVA and logistic regression) identified three most affected EFs: Working memory, generation/classification of semantic categories, and inhibitory control. Alterations in EFs increased mainly in relation to the increase of the specific number and type of comorbidity. To date, no studies have addressed comorbidity from this perspective. A wide range approach of EF confirms the need to further study comorbidity in ADHD from a wide range/variety perspective and determine all possible combinations (number/type) to clarify its contribution to the complex neuropsychology functioning in ADHD.
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Affiliation(s)
- Eliana Medrano Nava
- Child Psychiatry Hospital, SAP-DJNN, Ministry of Health, Mexico City, Mexico
- Postgraduate program in Health Sciences, Faculty of Medicine, UNAM, Mexico City, Mexico
| | - Julio C Flores-Lázaro
- Child Psychiatry Hospital, SAP-DJNN, Ministry of Health, Mexico City, Mexico
- Psychology Faculty, UNAM, Mexico City, Mexico
| | - Humberto Nicolini Sánchez
- Genomics of Psychiatric and Neurodegenerative Diseases Laboratory, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico
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Teruel MA, Sanchis J, Ruiz-Robledillo N, Albaladejo-Blázquez N, Ferrer-Cascales R, Trujillo J. Measuring attention of ADHD patients by means of a computer game featuring biometrical data gathering. Heliyon 2024; 10:e26555. [PMID: 38434359 PMCID: PMC10907648 DOI: 10.1016/j.heliyon.2024.e26555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 02/15/2024] [Indexed: 03/05/2024] Open
Abstract
ADHD is a neurodevelopmental disorder diagnosed mainly in children, marked by inattention and hyperactivity-impulsivity. The symptoms are highly variable, such as different ages of onset and potential comorbidities, contributing to frequent misdiagnoses. Professionals note a gap in modern diagnostic tools, making accurate identification challenging. To address this, recent studies recommend gamification for better ADHD diagnosis and treatment, though further research is essential to confirm its efficacy. This work aims to create a serious game, namely "Attention Slackline", to assess attention levels. The game, designed with expert input, requires players to concentrate on a specific point to recognize specific patterns while managing distractions. A controlled experiment tested its precision, and results were compared with established attention tests by a correlation analysis. Statistical analysis confirmed the game's validity, especially in tracking attention through correct responses and errors. Preliminary evidence suggests that "Attention Slackline" may serve as a credible instrument for the assessment of attentional capacities in individuals with ADHD, given that its outcomes have been empirically shown to correlate with those derived from a well-established attention assessment methodology.
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Affiliation(s)
- Miguel A. Teruel
- Lucentia Research Group, University of Alicante, Alicante Institute for Health and Biomedical Research (ISABIAL), Carretera San Vicente Del Raspeig S/n, 03690, San Vicente Del Raspeig, Alicante, Spain
| | - Javier Sanchis
- Lucentia Research Group, University of Alicante, Alicante Institute for Health and Biomedical Research (ISABIAL), Carretera San Vicente Del Raspeig S/n, 03690, San Vicente Del Raspeig, Alicante, Spain
- XSB Disseny I Multimedia, S.L., Carrer Del Mercat, 21, 03430, Onil, Alicante, Spain
| | - Nicolás Ruiz-Robledillo
- Department of Health Psychology, Faculty of Health Science, University of Alicante, Alicante Institute for Health and Biomedical Research (ISABIAL), Carretera San Vicente Del Raspeig S/n, 03690, San Vicente Del Raspeig, Alicante, Spain
| | - Natalia Albaladejo-Blázquez
- Department of Health Psychology, Faculty of Health Science, University of Alicante, Alicante Institute for Health and Biomedical Research (ISABIAL), Carretera San Vicente Del Raspeig S/n, 03690, San Vicente Del Raspeig, Alicante, Spain
| | - Rosario Ferrer-Cascales
- Department of Health Psychology, Faculty of Health Science, University of Alicante, Alicante Institute for Health and Biomedical Research (ISABIAL), Carretera San Vicente Del Raspeig S/n, 03690, San Vicente Del Raspeig, Alicante, Spain
| | - Juan Trujillo
- Lucentia Research Group, University of Alicante, Alicante Institute for Health and Biomedical Research (ISABIAL), Carretera San Vicente Del Raspeig S/n, 03690, San Vicente Del Raspeig, Alicante, Spain
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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: 2] [Impact Index Per Article: 2.0] [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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Mendez-Encinas D, Sujar A, Bayona S, Delgado-Gomez D. Attention and impulsivity assessment using virtual reality games. Sci Rep 2023; 13:13689. [PMID: 37608015 PMCID: PMC10444747 DOI: 10.1038/s41598-023-40455-4] [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: 01/10/2023] [Accepted: 08/10/2023] [Indexed: 08/24/2023] Open
Abstract
The assessment of cognitive functions is mainly based on standardized neuropsychological tests, widely used in various fields such as personnel recruitment, education, or health. This paper presents a virtual reality game that allows collecting continuous measurements of both the performance and behaviour of the subject in an immersive, controllable, and naturalistic experience. The application registers variables related to the user's eye movements through the use of virtual reality goggles, as well as variables of the game performance. We study how virtual reality can provide data to help predict scores on the Attention Control Scale Test and the Barratt Impulsiveness Scale. We design the application and test it with a pilot group. We build a random forest regressor model to predict the attention and impulsivity scales' total score. When evaluating the performance of the model, we obtain a positive correlation with attention (0.434) and with impulsivity (0.382). In addition, our model identified that the most significant variables are the time spent looking at the target or at distractors, the eye movements variability, the number of blinks and the pupil dilation in both attention and impulsivity. Our results are consistent with previous results in the literature showing that it is possible to use data collected in virtual reality to predict the degree of attention and impulsivity.
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Affiliation(s)
| | - Aaron Sujar
- Departamento de Ciencias de la Computación, Universidad Rey Juan Carlos, Móstoles, Spain.
| | - Sofia Bayona
- Departamento de Ciencias de la Computación, Universidad Rey Juan Carlos, Móstoles, Spain
| | - David Delgado-Gomez
- Departamento de Estádistica, Universidad Carlos III de Madrid, Leganes, Spain
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Jang C, Oh S, Lee H, Lee J, Song I, Park Y, Lee E, Joung YS. The impact of comorbid anxiety on quantitative EEG heterogeneity in children with attention-deficit/hyperactivity disorder. Front Psychiatry 2023; 14:1190713. [PMID: 37502808 PMCID: PMC10368871 DOI: 10.3389/fpsyt.2023.1190713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/26/2023] [Indexed: 07/29/2023] Open
Abstract
Objective The objective of this study was to compare quantitative electroencephalography (Q-EEG) characteristics of children with Attention-deficit/hyperactivity disorder (ADHD), taking into account the presence of a comorbidity for anxiety disorder. It also sought to investigate the impact of comorbid anxiety on the Q-EEG heterogeneity of children with ADHD. Method A total of 141 children with ADHD but without comorbid anxiety (ADHD-Only), 25 children with a comorbidity for anxiety disorder (ADHD-ANX) and 43 children in the control group were assessed. To compare Q-EEG characteristics between groups, we performed ANCOVA (Analysis of Covariance) on relative power and theta/beta ratio (TBR) controlling for covariates such as age, sex, and FSIQ. Relative power values from 19 electrodes were averaged for three regions (frontal, central and posterior). Furthermore, cluster analysis (Ward's method) using the squared Euclidian distance was conducted on participants with ADHD to explore the impact of anxiety on the heterogeneity of Q-EEG characteristics in ADHD. Results There were no significant group differences in cognitive and behavioral measures. However, significant differences between groups were observed in the theta values in the central region, and the beta values in the frontal, central and posterior regions. In post hoc analyses, It was found that the ADHD-ANX group has significantly higher beta power values than the ADHD-Only group in all regions. For the theta/beta ratio, the ADHD-Only group had significantly higher values than the ADHD-ANX group in frontal, central and posterior regions. However, the control group did not show significant differences compared to both the ADHD-Only and ADHD-ANX group. Through clustering analysis, the participants in the ADHD-Only and ADHD-ANX groups were classified into four clusters. The ratios of children with comorbidities for anxiety disorder within each cluster were significantly different (χ2 = 10.018, p = 0.019). Conclusion Attention-deficit/hyperactivity disorder children with comorbid anxiety disorder showed lower theta power in the central region, higher beta power in all regions and lower TBR in all regions compared to those without comorbid anxiety disorder. The ratios of children with comorbidities for anxiety disorder within each cluster were significantly different.
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Affiliation(s)
- Changwon Jang
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Soowhan Oh
- Department of Psychiatry, Changwon Samsung Hospital, Changwon-si, Gyengsangnam-do, Republic of Korea
| | - Hyerin Lee
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Junho Lee
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Inmok Song
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Yerin Park
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Eunji Lee
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Yoo-Sook Joung
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
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Takahara Y, Ota T, Nakanishi Y, Ueda S, Jurica P, Struzik ZR, Nishitomi K, Iida J, Kishimoto T, Cichocki A, Hasegawa M, Ogawa K. Exploration of electroencephalogram response to MPH treatment in ADHD patients. Psychiatry Res Neuroimaging 2023; 332:111631. [PMID: 37030146 DOI: 10.1016/j.pscychresns.2023.111631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 03/04/2023] [Accepted: 03/11/2023] [Indexed: 04/10/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is known to be associated with several diagnostic resting-state electroencephalography (EEG) patterns, including the theta/beta ratio, but no objective predictive markers for each medication. In this study, we explored EEG markers with which the therapeutic efficacy of medications could be estimated at the 1st clinical visit. Thirty-two ADHD patients and thirty-one healthy subjects participated in this study. EEG was recorded during eyes-closed resting conditions, and ADHD symptoms were scored before and after the therapeutic intervention (8 ± 2 weeks). Although comparing EEG patterns between ADHD patients and healthy subjects showed significant differences, EEG dynamics, e.g., theta/beta ratio, in ADHD patients before and after MPH treatment were not significantly different despite improvements in ADHD symptoms. We demonstrated that MPH good responders and poor responders, defined by the efficacy of MPH, had significantly different theta band power in right temporal areas, alpha in left occipital and frontal areas, and beta in left frontal areas. Moreover, we showed that MPH good responders had significant improvements toward normalization in several coherence measures after MPH treatment. Our study implies the possibility of these EEG indices as predictive markers for ADHD therapeutic efficacy.
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Affiliation(s)
- Yuji Takahara
- Laboratory for Drug Discovery and Disease Research, SHIONOGI & CO., LTD., Toyonaka-shi, Osaka, Japan
| | - Toyosaku Ota
- Nara Medical University School of Medicine, Shijo-cho Kashihara, Nara, Japan
| | - Yoko Nakanishi
- Nara Medical University School of Medicine, Shijo-cho Kashihara, Nara, Japan
| | - Shotaro Ueda
- Nara Medical University School of Medicine, Shijo-cho Kashihara, Nara, Japan
| | - Peter Jurica
- Cellular Informatics Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama, Japan
| | - Zbignew R Struzik
- RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama, Japan; Graduate School of Education, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo Japan; Faculty of Physics, The University of Warsaw, Pasteur, Warsaw, Poland
| | - Kohei Nishitomi
- Laboratory for Drug Discovery and Disease Research, SHIONOGI & CO., LTD., Toyonaka-shi, Osaka, Japan
| | - Junzo Iida
- Nara Medical University School of Medicine, Shijo-cho Kashihara, Nara, Japan
| | - Toshifumi Kishimoto
- Nara Medical University School of Medicine, Shijo-cho Kashihara, Nara, Japan
| | - Andrzej Cichocki
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Minoru Hasegawa
- Laboratory for Drug Discovery and Disease Research, SHIONOGI & CO., LTD., Toyonaka-shi, Osaka, Japan
| | - Koichi Ogawa
- Laboratory for Drug Discovery and Disease Research, SHIONOGI & CO., LTD., Toyonaka-shi, Osaka, Japan.
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Lazarou I, Oikonomou VP, Mpaltadoros L, Grammatikopoulou M, Alepopoulos V, Stavropoulos TG, Bezerianos A, Nikolopoulos S, Kompatsiaris I, Tsolaki M. Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study. Front Aging Neurosci 2023; 15:1167410. [PMID: 37388185 PMCID: PMC10306118 DOI: 10.3389/fnagi.2023.1167410] [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: 02/16/2023] [Accepted: 05/03/2023] [Indexed: 07/01/2023] Open
Abstract
Objectives Meditation imparts relaxation and constitutes an important non-pharmacological intervention for people with cognitive impairment. Moreover, EEG has been widely used as a tool for detecting brain changes even at the early stages of Alzheimer's Disease (AD). The current study investigates the effect of meditation practices on the human brain across the AD spectrum by using a novel portable EEG headband in a smart-home environment. Methods Forty (40) people (13 Healthy Controls-HC, 14 with Subjective Cognitive Decline-SCD and 13 with Mild Cognitive Impairment-MCI) participated practicing Mindfulness Based Stress Reduction (Session 2-MBSR) and a novel adaptation of the Kirtan Kriya meditation to the Greek culture setting (Session 3-KK), while a Resting State (RS) condition was undertaken at baseline and follow-up (Session 1-RS Baseline and Session 4-RS Follow-Up). The signals were recorded by using the Muse EEG device and brain waves were computed (alpha, theta, gamma, and beta). Results Analysis was conducted on four-electrodes (AF7, AF8, TP9, and TP10). Statistical analysis included the Kruskal-Wallis (KW) nonparametric analysis of variance. The results revealed that both states of MBSR and KK lead to a marked difference in the brain's activation patterns across people at different cognitive states. Wilcoxon Signed-ranks test indicated for HC that theta waves at TP9, TP10 and AF7, AF8 in Session 3-KK were statistically significantly reduced compared to Session 1-RS Z = -2.271, p = 0.023, Z = -3.110, p = 0.002 and Z = -2.341, p = 0.019, Z = -2.132, p = 0.033, respectively. Conclusion The results showed the potential of the parameters used between the various groups (HC, SCD, and MCI) as well as between the two meditation sessions (MBSR and KK) in discriminating early cognitive decline and brain alterations in a smart-home environment without medical support.
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Affiliation(s)
- Ioulietta Lazarou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Vangelis P. Oikonomou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Lampros Mpaltadoros
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Margarita Grammatikopoulou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Vasilis Alepopoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Thanos G. Stavropoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Anastasios Bezerianos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Spiros Nikolopoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Ioannis Kompatsiaris
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Magda Tsolaki
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
- 1st Department of Neurology, Faculty of Health Sciences, G.H. “AHEPA”, School of Medicine, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders (GAADRD), Thessaloniki, Greece
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI–AUTh), Aristotle University of Thessaloniki, Thessaloniki, Greece
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11
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Dagnino PC, Braboszcz C, Kroupi E, Splittgerber M, Brauer H, Dempfle A, Breitling-Ziegler C, Prehn-Kristensen A, Krauel K, Siniatchkin M, Moliadze V, Soria-Frisch A. Stratification of responses to tDCS intervention in a healthy pediatric population based on resting-state EEG profiles. Sci Rep 2023; 13:8438. [PMID: 37231030 DOI: 10.1038/s41598-023-34724-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 05/06/2023] [Indexed: 05/27/2023] Open
Abstract
Transcranial Direct Current Stimulation (tDCS) is a non-invasive neuromodulation technique with a wide variety of clinical and research applications. As increasingly acknowledged, its effectiveness is subject dependent, which may lead to time consuming and cost ineffective treatment development phases. We propose the combination of electroencephalography (EEG) and unsupervised learning for the stratification and prediction of individual responses to tDCS. A randomized, sham-controlled, double-blind crossover study design was conducted within a clinical trial for the development of pediatric treatments based on tDCS. The tDCS stimulation (sham and active) was applied either in the left dorsolateral prefrontal cortex or in the right inferior frontal gyrus. Following the stimulation session, participants performed 3 cognitive tasks to assess the response to the intervention: the Flanker Task, N-Back Task and Continuous Performance Test (CPT). We used data from 56 healthy children and adolescents to implement an unsupervised clustering approach that stratify participants based on their resting-state EEG spectral features before the tDCS intervention. We then applied a correlational analysis to characterize the clusters of EEG profiles in terms of participant's difference in the behavioral outcome (accuracy and response time) of the cognitive tasks when performed after a tDCS-sham or a tDCS-active session. Better behavioral performance following the active tDCS session compared to the sham tDCS session is considered a positive intervention response, whilst the reverse is considered a negative one. Optimal results in terms of validity measures was obtained for 4 clusters. These results show that specific EEG-based digital phenotypes can be associated to particular responses. While one cluster presents neurotypical EEG activity, the remaining clusters present non-typical EEG characteristics, which seem to be associated with a positive response. Findings suggest that unsupervised machine learning can be successfully used to stratify and eventually predict responses of individuals to a tDCS treatment.
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Affiliation(s)
| | - Claire Braboszcz
- Neuroscience BU, Starlab Barcelona SL, Av Tibidabo 47 bis, Barcelona, Spain
| | - Eleni Kroupi
- Neuroscience BU, Starlab Barcelona SL, Av Tibidabo 47 bis, Barcelona, Spain
| | - Maike Splittgerber
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | - Hannah Brauer
- Department of Child and Adolescent Psychiatry, Center for Integrative Psychiatry Kiel, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Astrid Dempfle
- Institute of Medical Informatics and Statistics, University Hospital Schleswig Holstein, Kiel University, Kiel, Germany
| | - Carolin Breitling-Ziegler
- Department of Child and Adolescent Psychiatry and Psychotherapy, University of Magdeburg, Magdeburg, Germany
| | - Alexander Prehn-Kristensen
- Department of Child and Adolescent Psychiatry, Center for Integrative Psychiatry Kiel, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Kerstin Krauel
- Department of Child and Adolescent Psychiatry and Psychotherapy, University of Magdeburg, Magdeburg, Germany
| | - Michael Siniatchkin
- Clinic for Child and Adolescent Psychiatry and Psychotherapy, Protestant Hospital Bethel, University of Bielefeld, Campus Bielefeld Bethel, Bielefeld, Germany
| | - Vera Moliadze
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | - Aureli Soria-Frisch
- Neuroscience BU, Starlab Barcelona SL, Av Tibidabo 47 bis, Barcelona, Spain.
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12
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Krell J, Dolecki PK, Todd A. School-Based Neurofeedback Training for Sustained Attention. J Atten Disord 2023:10870547231168430. [PMID: 37122234 DOI: 10.1177/10870547231168430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
OBJECTIVE To determine whether in situ neurofeedback training can be used as a tool to build sustained attention in the general student population and whether gains in attention translate to more effective work habits and learning skills. METHOD Students participated in attention training game-based neurofeedback in situ for a period of 35 sessions of 25 min each. The study was built as a one-group pretest-posttest quasi-experimental design. RESULTS This study supports that classroom-based neurofeedback may be an effective tool to build sustained attention and translate these gains into observable work habits and learning behaviors including planning and organization. CONCLUSION Neurofeedback has shown specificity in the treatment of Attention Deficit Hyperactivity Disorder. Published research has not, however, focused on its efficacy in developing attentional capacities in the general population. The promising results of this exploratory investigation warrant further applied research.
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13
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Chen H, Yang Y, Odisho D, Wu S, Yi C, Oliver BG. Can biomarkers be used to diagnose attention deficit hyperactivity disorder? Front Psychiatry 2023; 14:1026616. [PMID: 36970271 PMCID: PMC10030688 DOI: 10.3389/fpsyt.2023.1026616] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 02/14/2023] [Indexed: 03/10/2023] Open
Abstract
Currently, the diagnosis of attention deficit hyperactivity disorder (ADHD) is solely based on behavioral tests prescribed by the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5). However, biomarkers can be more objective and accurate for diagnosis and evaluating treatment efficacy. Thus, this review aimed to identify potential biomarkers for ADHD. Search terms “ADHD,” and “biomarker” combined with one of “protein,” “blood/serum,” “gene,” and “neuro” were used to identify human and animal studies in PubMed, Ovid Medline, and Web of Science. Only papers in English were included. Potential biomarkers were categorized into radiographic, molecular, physiologic, or histologic markers. The radiographic analysis can identify specific activity changes in several brain regions in individuals with ADHD. Several molecular biomarkers in peripheral blood cells and some physiologic biomarkers were found in a small number of participants. There were no published histologic biomarkers for ADHD. Overall, most associations between ADHD and potential biomarkers were properly controlled. In conclusion, a series of biomarkers in the literature are promising as objective parameters to more accurately diagnose ADHD, especially in those with comorbidities that prevent the use of DSM-5. However, more research is needed to confirm the reliability of the biomarkers in larger cohort studies.
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Affiliation(s)
- Hui Chen
- Department of Pathology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China
- School of Life Sciences, Faculty of Science, University of Technology Sydney, Ultimo, NSW, Australia
| | - Yang Yang
- Research Centre, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Diana Odisho
- School of Life Sciences, Faculty of Science, University of Technology Sydney, Ultimo, NSW, Australia
| | - Siqi Wu
- Research Centre, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Chenju Yi
- Department of Pathology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China
- Research Centre, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
- Shenzhen Key Laboratory of Chinese Medicine Active Substance Screening and Translational Research, Shenzhen, China
- *Correspondence: Chenju Yi,
| | - Brian G. Oliver
- School of Life Sciences, Faculty of Science, University of Technology Sydney, Ultimo, NSW, Australia
- Respiratory Cellular and Molecular Biology, Woolcock Institute of Medical Research, The University of Sydney, Glebe, NSW, Australia
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14
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Uyulan C, Erguzel TT, Turk O, Farhad S, Metin B, Tarhan N. A Class Activation Map-Based Interpretable Transfer Learning Model for Automated Detection of ADHD from fMRI Data. Clin EEG Neurosci 2023; 54:151-159. [PMID: 36052402 DOI: 10.1177/15500594221122699] [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: 01/10/2023]
Abstract
Automatic detection of Attention Deficit Hyperactivity Disorder (ADHD) based on the functional Magnetic Resonance Imaging (fMRI) through Deep Learning (DL) is becoming a quite useful methodology due to the curse of-dimensionality problem of the data is solved. Also, this method proposes an invasive and robust solution to the variances in data acquisition and class distribution imbalances. In this paper, a transfer learning approach, specifically ResNet-50 type pre-trained 2D-Convolutional Neural Network (CNN) was used to automatically classify ADHD and healthy children. The results demonstrated that ResNet-50 architecture with 10-k cross-validation (CV) achieves an overall classification accuracy of 93.45%. The interpretation of the results was done via the Class Activation Map (CAM) analysis which showed that children with ADHD differed from controls in a wide range of brain areas including frontal, parietal and temporal lobes.
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Affiliation(s)
- Caglar Uyulan
- Department of Mechanical Engineering, Faculty of Engineering and Architecture, İzmir Katip Çelebi University, İzmir, Turkey
| | | | - Omer Turk
- Department of Computer Programming, Vocational School, Mardin Artuklu University, Mardin, Turkey
| | - Shams Farhad
- Department of Neuroscience, 232990Uskudar University, Istanbul, Turkey
| | - Baris Metin
- Department of Neuroscience, 232990Uskudar University, Istanbul, Turkey
| | - Nevzat Tarhan
- Department of Psychiatry, NPIstanbul Brain Hospital, Istanbul, Turkey
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15
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Naguy A, Pridmore S, Alwetayan S, Elsori D, Alamiri B. ADHD-A Clinician's Bird's Eye View of Current Status and New Vistas! PSYCHOPHARMACOLOGY BULLETIN 2023; 53:46-54. [PMID: 36873919 PMCID: PMC9981341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
Abstract
Objectives Literature on ADHD has taken long strides recently as heaps of new data are pouring in through countless papers. Here, authors try to outline changing paradigms in ADHD practice. DSM-5 changes regarding the typology and diagnostic criteria are highlighted. Overview of co-morbidities, associations, developmental trajectories, and syndromic continuity across lifespan is outlined. Recent insights into aetiology and diagnostic tools are briefly discussed. New medications in the pipeline are also described. Methods EMBASE, Ovid MEDLINE, PubMed, Scopus, Web of Science, and Cochrane Database of Systemic Reviews were searched for all relevant updates in ADHD literature as of June, 2022. Results DSM-5 brought about changes to the diagnostic criteria of ADHD. These included replacing types with presentations, pushing age to 12, and, incorporating adult diagnostic criteria. In the same vein, DSM-5 allows now for diagnosing concurrent ADHD and ASD. Associations of ADHD to allergy, obesity, sleep disorders, and, epilepsy have been demonstrated in recent literature. Neurocircuity underlying ADHD has been extended beyond frontal-striatal to include CTC as well as DMN accounting for ADHD heterogeneity. NEBA was FDA-approved to differentiate ADHD from hyperkinetic ID. Atypical antipsychotics use to address behavioural facets in ADHD is on the rise with no solid evidence-base. α-2 agonists are FDA-approved as monotherapy or adjunctive to stimulants. Pharmacogenetic testing is readily available for ADHD. Different formulations of stimulants abound on the market widening clinicians' repertoire. Stimulant-related exacerbation of anxiety and tics were challenged in recent studies. Drugs for ADHD in the pipeline include-dasotraline, armodafinil, tipepidine, edivoxetine, metadoxine, and memantine. Conclusions Literature on ADHD keeps expanding towards advancing our understanding of the complex and heterogeneous intricacies of this commonplace neurodevelopmental disorder and hence informing better decisions on how best to manage its diverse cognitive, behavioural, social and medical facets.
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Affiliation(s)
- Ahmed Naguy
- Naguy, MBBch, MSc, Child/Adolescent Psychiatrist, Al-Manara CAP Centre, Kuwait Centre for Mental Health (KCMH), Jamal Abdul-Nassir St, Shuwaikh, State of Kuwai. Prof
| | - Saxby Pridmore
- Pridmore, MD, Professor of Psychiatry, University of Tasmania, Hobart, Australia
| | - Salem Alwetayan
- Alwetayan, MD, MRCPsych (UK), General Adult Psychiatrist, Birmingham and Solihull Mental Health Foundation Trust, UK
| | - Dalal Elsori
- Elsori, MD, ABP, Pediatrician, Rhode Island Hospital, Brown University, Providence, Rhode Island, United States
| | - Bibi Alamiri
- Alamiri, MD, ABPN, ScD, Consultant Child/Adolescent Psychiatrist, Head of Al-Manara CAP Centre, KCMH, Kuwait, and Assistant Professor, Tufts University, Medford, United States
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16
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Zhang-James Y, Razavi AS, Hoogman M, Franke B, Faraone SV. Machine Learning and MRI-based Diagnostic Models for ADHD: Are We There Yet? J Atten Disord 2023; 27:335-353. [PMID: 36651494 DOI: 10.1177/10870547221146256] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Machine learning (ML) has been applied to develop magnetic resonance imaging (MRI)-based diagnostic classifiers for attention-deficit/hyperactivity disorder (ADHD). This systematic review examines this literature to clarify its clinical significance and to assess the implications of the various analytic methods applied. METHODS A comprehensive literature search on MRI-based diagnostic classifiers for ADHD was performed and data regarding the utilized models and samples were gathered. RESULTS We found that, although most studies reported the classification accuracies, they varied in choice of MRI modalities, ML models, cross-validation and testing methods, and sample sizes. We found that the accuracies of cross-validation methods inflated the performance estimation compared with those of a held-out test, compromising the model generalizability. Test accuracies have increased with publication year but were not associated with training sample sizes. Improved test accuracy over time was likely due to the use of better ML methods along with strategies to deal with data imbalances. CONCLUSION Ultimately, large multi-modal imaging datasets, and potentially the combination with other types of data, like cognitive data and/or genetics, will be essential to achieve the goal of developing clinically useful imaging classification tools for ADHD in the future.
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Affiliation(s)
| | | | - Martine Hoogman
- Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
| | - Barbara Franke
- Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
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17
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Morrone CD, Tsang AA, Giorshev SM, Craig EE, Yu WH. Concurrent behavioral and electrophysiological longitudinal recordings for in vivo assessment of aging. Front Aging Neurosci 2023; 14:952101. [PMID: 36742209 PMCID: PMC9891465 DOI: 10.3389/fnagi.2022.952101] [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: 05/24/2022] [Accepted: 12/12/2022] [Indexed: 01/19/2023] Open
Abstract
Electrophysiological and behavioral alterations, including sleep and cognitive impairments, are critical components of age-related decline and neurodegenerative diseases. In preclinical investigation, many refined techniques are employed to probe these phenotypes, but they are often conducted separately. Herein, we provide a protocol for one-time surgical implantation of EMG wires in the nuchal muscle and a skull-surface EEG headcap in mice, capable of 9-to-12-month recording longevity. All data acquisitions are wireless, making them compatible with simultaneous EEG recording coupled to multiple behavioral tasks, as we demonstrate with locomotion/sleep staging during home-cage video assessments, cognitive testing in the Barnes maze, and sleep disruption. Time-course EEG and EMG data can be accurately mapped to the behavioral phenotype and synchronized with neuronal frequencies for movement and the location to target in the Barnes maze. We discuss critical steps for optimizing headcap surgery and alternative approaches, including increasing the number of EEG channels or utilizing depth electrodes with the system. Combining electrophysiological and behavioral measurements in preclinical models of aging and neurodegeneration has great potential for improving mechanistic and therapeutic assessments and determining early markers of brain disorders.
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Affiliation(s)
- Christopher Daniel Morrone
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada,*Correspondence: Christopher Daniel Morrone,
| | - Arielle A. Tsang
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Biological Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Sarah M. Giorshev
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Psychology, University of Toronto Scarborough, Toronto, ON, Canada
| | - Emily E. Craig
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Wai Haung Yu
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada,Geriatric Mental Health Research Services, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada,Wai Haung Yu,
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18
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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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19
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Buchhalter J, Neuray C, Cheng JY, D’Cruz O, Datta AN, Dlugos D, French J, Haubenberger D, Hulihan J, Klein P, Komorowski RW, Kramer L, Lothe A, Nabbout R, Perucca E, der Ark PV. EEG Parameters as Endpoints in Epilepsy Clinical Trials- An Expert Panel Opinion Paper. Epilepsy Res 2022; 187:107028. [DOI: 10.1016/j.eplepsyres.2022.107028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/29/2022] [Accepted: 09/26/2022] [Indexed: 11/30/2022]
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20
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Park EJ, Park YM, Lee SH, Kim B. The Loudness Dependence of Auditory Evoked Potentials is associated with the Symptom Severity and Treatment in Boys with Attention Deficit Hyperactivity Disorder. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2022; 20:514-525. [PMID: 35879036 PMCID: PMC9329111 DOI: 10.9758/cpn.2022.20.3.514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 01/20/2022] [Accepted: 02/02/2022] [Indexed: 11/18/2022]
Abstract
Objective Methods Results Conclusion
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Affiliation(s)
- Eun Jin Park
- Department of Psychiatry, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Young-Min Park
- Department of Psychiatry, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Seung-Hwan Lee
- Department of Psychiatry, Inje University Ilsan Paik Hospital, Goyang, Korea
| | - Bongseog Kim
- Department of Psychiatry, Inje University Sanggye Paik Hospital, Seoul, Korea
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21
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Chen IC, Lee PW, Wang LJ, Chang CH, Lin CH, Ko LW. Incremental Validity of Multi-Method and Multi-Informant Evaluations in the Clinical Diagnosis of Preschool ADHD. J Atten Disord 2022; 26:1293-1303. [PMID: 34949123 DOI: 10.1177/10870547211045739] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVES This study investigated the discriminative validity of various single or combined measurements of electroencephalogram (EEG) data, Conners' Kiddie Continuous Performance Test (K-CPT), and Disruptive Behavior Disorder Rating Scale (DBDRS) to differentiate preschool children with ADHD from those with typical development (TD). METHOD We recruited 70 preschoolers, of whom 38 were diagnosed with ADHD and 32 exhibited TD; all participants underwent the K-CPT and wireless EEG recording in different conditions (rest, slow-rate, and fast-rate task). RESULTS Slow-rate task-related central parietal delta (1-4 Hz) and central alpha (8-13 Hz) and beta (13-30 Hz) powers between groups with ADHD and TD were significantly distinct (p < .05). A combination of DBDRS, K-CPT, and specific EEG data provided the best probability scores (area under curve = 0.926, p < .001) and discriminative validity to identify preschool children with ADHD (overall correct classification rate = 85.71%). CONCLUSIONS Multi-method and multi-informant evaluations should be emphasized in clinical diagnosis of preschool ADHD.
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Affiliation(s)
- I-Chun Chen
- National Yang Ming Chiao Tung University, Hsinchu.,Ton Yen General Hospital, Hsinchu
| | | | - Liang-Jen Wang
- Chang Gung Memorial Hospital, Kaohsiung.,Chang Gung University, Taoyuan
| | | | | | - Li-Wei Ko
- National Yang Ming Chiao Tung University, Hsinchu
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22
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Buitelaar J, Bölte S, Brandeis D, Caye A, Christmann N, Cortese S, Coghill D, Faraone SV, Franke B, Gleitz M, Greven CU, Kooij S, Leffa DT, Rommelse N, Newcorn JH, Polanczyk GV, Rohde LA, Simonoff E, Stein M, Vitiello B, Yazgan Y, Roesler M, Doepfner M, Banaschewski T. Toward Precision Medicine in ADHD. Front Behav Neurosci 2022; 16:900981. [PMID: 35874653 PMCID: PMC9299434 DOI: 10.3389/fnbeh.2022.900981] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/16/2022] [Indexed: 11/17/2022] Open
Abstract
Attention-Deficit Hyperactivity Disorder (ADHD) is a complex and heterogeneous neurodevelopmental condition for which curative treatments are lacking. Whilst pharmacological treatments are generally effective and safe, there is considerable inter-individual variability among patients regarding treatment response, required dose, and tolerability. Many of the non-pharmacological treatments, which are preferred to drug-treatment by some patients, either lack efficacy for core symptoms or are associated with small effect sizes. No evidence-based decision tools are currently available to allocate pharmacological or psychosocial treatments based on the patient's clinical, environmental, cognitive, genetic, or biological characteristics. We systematically reviewed potential biomarkers that may help in diagnosing ADHD and/or stratifying ADHD into more homogeneous subgroups and/or predict clinical course, treatment response, and long-term outcome across the lifespan. Most work involved exploratory studies with cognitive, actigraphic and EEG diagnostic markers to predict ADHD, along with relatively few studies exploring markers to subtype ADHD and predict response to treatment. There is a critical need for multisite prospective carefully designed experimentally controlled or observational studies to identify biomarkers that index inter-individual variability and/or predict treatment response.
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Affiliation(s)
- Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands.,Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Solna, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Stockholm, Sweden.,Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, WA, Australia
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany.,Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Arthur Caye
- Department of Psychiatry, Hospital de Clinicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil
| | - Nina Christmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Samuele Cortese
- Centre for Innovation in Mental Health, Academic Unit of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, United Kingdom.,Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, United Kingdom.,Solent National Health System Trust, Southampton, United Kingdom.,Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, United States.,Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - David Coghill
- Departments of Paediatrics and Psychiatry, Royal Children's Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Stephen V Faraone
- Departments of Psychiatry, Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York, NY, United States
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Markus Gleitz
- Medice Arzneimittel Pütter GmbH & Co. KG, Iserlohn, Germany
| | - Corina U Greven
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands.,Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands.,King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom
| | - Sandra Kooij
- Amsterdam University Medical Center, Location VUMc, Amsterdam, Netherlands.,PsyQ, Expertise Center Adult ADHD, The Hague, Netherlands
| | - Douglas Teixeira Leffa
- Department of Psychiatry, Hospital de Clinicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil
| | - Nanda Rommelse
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands.,Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Jeffrey H Newcorn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Guilherme V Polanczyk
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Luis Augusto Rohde
- National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil.,ADHD Outpatient Program and Developmental Psychiatry Program, Hospital de Clinica de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Emily Simonoff
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Mark Stein
- Department of Psychiatry and Behavioral Sciences, Seattle, WA, United States
| | - Benedetto Vitiello
- Department of Public Health and Pediatric Sciences, Section of Child and Adolescent Neuropsychiatry, University of Turin, Turin, Italy.,Department of Public Health, Johns Hopkins University, Baltimore, MA, United States
| | - Yanki Yazgan
- GuzelGunler Clinic, Istanbul, Turkey.,Yale Child Study Center, New Haven, CT, United States
| | - Michael Roesler
- Institute for Forensic Psychology and Psychiatry, Neurocenter, Saarland, Germany
| | - Manfred Doepfner
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Medical Faculty of the University of Cologne, Cologne, Germany.,School for Child and Adolescent Cognitive Behavioural Therapy, University Hospital of Cologne, Cologne, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
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23
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Li J, You J, Yin G, Xu J, Zhang Y, Yuan X, Chen Q, Ye J. Electroencephalography Theta/Beta Ratio Decreases in Patients with Severe Obstructive Sleep Apnea. Nat Sci Sleep 2022; 14:1021-1030. [PMID: 35669412 PMCID: PMC9165653 DOI: 10.2147/nss.s357722] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 05/16/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose Accumulating evidence suggests that theta/beta ratio (TBR), an electroencephalographic (EEG) frequency band parameter, might serve as an objective marker of executive cognitive control in healthy adults. Obstructive sleep apnea (OSA) has a detrimental impact on patients' behavior and cognitive performance while whether TBR is different in OSA population has not been reported. This study aimed to explore the difference in relative EEG spectral power and TBR during sleep between patients with severe OSA and non-OSA groups. Patients and Methods 142 participants with in-laboratory nocturnal PSG recording were included, among which 100 participants suffered severe OSA (apnea hypopnea index, AHI > 30 events/hour; OSA group) and 42 participants had no OSA (AHI ≤ 5 events/h; control group). The fast Fourier transformation was used to compute the EEG power spectrum for total sleep duration within contiguous 30-second epochs of sleep. The demographic and polysomnographic characteristics, relative EEG spectral power and TBR of the two groups were compared. Results It was found that the beta band power during NREM sleep and total sleep was significantly higher in the OSA group than controls (p < 0.001, p = 0.012, respectively), and the theta band power during NREM sleep and total sleep was significantly lower in the OSA group than controls (p = 0.019, p = 0.014, respectively). TBR during NREM sleep, REM sleep and total sleep was significantly lower in the OSA group compared to the control group (p < 0.001 for NREM sleep and total sleep, p = 0.015 for REM sleep). TBR was negatively correlated with AHI during NREM sleep (r=-0.324, p < 0.001) and total sleep (r=-0. 312, p < 0.001). Conclusion TBR was significantly decreased in severe OSA patients compared to the controls, which was attributed to both increased beta power and decreased theta power. TBR may be a stable EEG-biomarker of OSA patients, which may accurately and reliably identify phenotype of patients.
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Affiliation(s)
- Jingjing Li
- Department of Otorhinopharyngology–Head and Neck Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China
| | - Jingyuan You
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People’s Republic of China
| | - Guoping Yin
- Department of Otorhinopharyngology–Head and Neck Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China
| | - Jinkun Xu
- Department of Otorhinopharyngology–Head and Neck Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China
| | - Yuhuan Zhang
- Department of Otorhinopharyngology–Head and Neck Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China
| | - Xuemei Yuan
- Department of Otorhinopharyngology–Head and Neck Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China
| | - Qiang Chen
- Department of Otorhinopharyngology–Head and Neck Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China
| | - Jingying Ye
- Department of Otorhinopharyngology–Head and Neck Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, People’s Republic of China
- Institute of Precision Medicine, Tsinghua University, Beijing, People's Republic of China
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24
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A. Markovics J. Training the Conductor of the Brainwave Symphony: In Search of a Common Mechanism of Action for All Methods of Neurofeedback. ARTIF INTELL 2022. [DOI: 10.5772/intechopen.98343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
There are several different methods of neurofeedback, most of which presume an operant conditioning model whereby the subject learns to control their brain activity in particular regions of the brain and/or at particular brainwave frequencies based on reinforcement. One method, however, called infra-low frequency [ILF] neurofeedback cannot be explained through this paradigm, yet it has profound effects on brain function. Like a conductor of a symphony, recent evidence demonstrates that the primary ILF (typically between 0.01–0.1 Hz), which correlates with the fluctuation of oxygenated and deoxygenated blood in the brain, regulates all of the classic brainwave bands (i.e. alpha, theta, delta, beta, gamma). The success of ILF neurofeedback suggests that all forms of neurofeedback may work through a similar mechanism that does not fit the operant conditioning paradigm. This chapter focuses on the possible mechanisms of action for ILF neurofeedback, which may be generalized, based on current evidence.
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25
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Bhattacharyya N, Singh S, Banerjee A, Ghosh R, Sinha O, Das N, Gayen R, Pal SS, Ganguly S, Dasgupta T, Dasgupta T, Mondal P, Adhikari A, Sarkar S, Bhattacharyya D, Mallick AK, Singh OP, Pal SK. Integration of electroencephalogram (EEG) and motion tracking sensors for objective measure of attention-deficit hyperactivity disorder (MAHD) in pre-schoolers. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:054101. [PMID: 35649790 DOI: 10.1063/5.0088044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 04/07/2022] [Indexed: 06/15/2023]
Abstract
We developed an integrated device composed of a single-probe Electroencephalogram (EEG) and Charge Coupled Device (CCD) based motion sensors for objective measurement of Attention-deficit Hyperactivity Disorder (ADHD). While the measurement of attention-deficit hyperactivity disorder (MAHD) relies on the EEG signal for the assessment of attention during a given structured task, the CCD sensor depicts the movement pattern of the subjects engaged in a continuous performance task. A statistical analysis of attention and movement patterns was performed, and the accuracy of completed tasks was analyzed using indigenously developed software. The device with the embedded software is intended to improve certainty with criterion E. We used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 year old pre-schoolers). During the performance of the task power for delta and beta, EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task. We used our indigenously developed software for statistical analysis to derive a scale for the objective assessment of ADHD. We also compared our scale with clinical ADHD evaluations and found a significant correlation between the objective assessment of the ADHD subjects and the clinician's conventional evaluation. MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.
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Affiliation(s)
- Neha Bhattacharyya
- Department of Radio Physics and Electronics, University of Calcutta, 92, Acharya Prafulla Chandra Rd., Machuabazar, Kolkata 700009, India
| | - Soumendra Singh
- Technical Research Centre, S. N. Bose National Centre for Basic Sciences, Block JD, Sector III, Salt Lake, Kolkata, West Bengal 700106, India
| | - Amrita Banerjee
- Technical Research Centre, S. N. Bose National Centre for Basic Sciences, Block JD, Sector III, Salt Lake, Kolkata, West Bengal 700106, India
| | - Ria Ghosh
- Technical Research Centre, S. N. Bose National Centre for Basic Sciences, Block JD, Sector III, Salt Lake, Kolkata, West Bengal 700106, India
| | - Oindrila Sinha
- Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Nairit Das
- Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Drive 3114 Engineering Building II, Raleigh, North Carolina 27606, USA
| | - Rajkumar Gayen
- Department of Paediatrics, Nil Ratan Sircar Medical College and Hospital, Kolkata 700014, India
| | - Somya Shubhra Pal
- California State University Los Angeles, 5151 State University Drive, Los Angeles, California 90032, USA
| | - Sahely Ganguly
- Department of Clinical Psychologist, AMRI Hospital Dhakuria, Block-A, Scheme-L11, P-4&5, Gariahat Rd., Dhakuria, Ward Number 90, Kolkata, West Bengal 700029, India
| | - Tanmoy Dasgupta
- Department of Chemical, Biological and Macromolecular Sciences, S. N. Bose National Centre for Basic Sciences, Block JD, Sector 3, Salt Lake, Kolkata 700106, India
| | - Tanusree Dasgupta
- Department of Chemical, Biological and Macromolecular Sciences, S. N. Bose National Centre for Basic Sciences, Block JD, Sector 3, Salt Lake, Kolkata 700106, India
| | - Pulak Mondal
- Department of Radio Physics and Electronics, University of Calcutta, 92, Acharya Prafulla Chandra Rd., Machuabazar, Kolkata 700009, India
| | - Aniruddha Adhikari
- Department of Chemical and Biomolecular Engineering, Henry Samueli School of Engineering, University of California, Los Angeles, California 90095, USA
| | - Sharmila Sarkar
- Department of Psychiatry, Calcutta National Medical College, 32, Gorachand Rd., Beniapukur, Kolkata, West Bengal 700014, India
| | - Debasish Bhattacharyya
- Department of Gynecology and Obstetrics, Nil Ratan Sircar Medical College and Hospital, 138, AJC Bose Road, Sealdah, Raja Bazar, Kolkata 700014, India
| | - Asim Kumar Mallick
- Department of Paediatrics, Nil Ratan Sircar Medical College and Hospital, Kolkata 700014, India
| | - Om Prakash Singh
- West Bengal Medical Education Services Government of West Bengal, Swasthya Bhawan, GN-29, Sector-V, Salt Lake, Kolkata 700 091, India
| | - Samir Kumar Pal
- Department of Radio Physics and Electronics, University of Calcutta, 92, Acharya Prafulla Chandra Rd., Machuabazar, Kolkata 700009, India
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26
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Chen IC, Chen CL, Chang CH, Fan ZC, Chang Y, Lin CH, Ko LW. Task-Rate-Related Neural Dynamics Using Wireless EEG to Assist Diagnosis and Intervention Planning for Preschoolers with ADHD Exhibiting Heterogeneous Cognitive Proficiency. J Pers Med 2022; 12:jpm12050731. [PMID: 35629153 PMCID: PMC9143733 DOI: 10.3390/jpm12050731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/21/2022] [Accepted: 04/25/2022] [Indexed: 02/01/2023] Open
Abstract
This study used a wireless EEG system to investigate neural dynamics in preschoolers with ADHD who exhibited varying cognitive proficiency pertaining to working memory and processing speed abilities. Preschoolers with ADHD exhibiting high cognitive proficiency (ADHD-H, n = 24), those with ADHD exhibiting low cognitive proficiency (ADHD-L, n = 18), and preschoolers with typical development (TD, n = 31) underwent the Conners’ Kiddie Continuous Performance Test and wireless EEG recording under different conditions (rest, slow-rate, and fast-rate task). In the slow-rate task condition, compared with the TD group, the ADHD-H group manifested higher delta and lower beta power in the central region, while the ADHD-L group manifested higher parietal delta power. In the fast-rate task condition, in the parietal region, ADHD-L manifested higher delta power than those in the other two groups (ADHD-H and TD); additionally, ADHD-L manifested higher theta as well as lower alpha and beta power than those with ADHD-H. Unlike those in the TD group, the delta power of both ADHD groups was enhanced in shifting from rest to task conditions. These findings suggest that task-rate-related neural dynamics contain specific neural biomarkers to assist clinical planning for ADHD in preschoolers with heterogeneous cognitive proficiency. The novel wireless EEG system used was convenient and highly suitable for clinical application.
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Affiliation(s)
- I-Chun Chen
- International Ph.D. Program in Interdisciplinary Neuroscience, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
- Department of Physical Medicine and Rehabilitation, Ton-Yen General Hospital, Hsinchu 30268, Taiwan
| | - Chia-Ling Chen
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou, Taoyuan 33305, Taiwan
- Graduate Institute of Early Intervention, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Correspondence: (C.-L.C.); (L.-W.K.)
| | - Chih-Hao Chang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan; (C.-H.C.); (Z.-C.F.)
- Brain Research Center and the Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
| | - Zuo-Cian Fan
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan; (C.-H.C.); (Z.-C.F.)
- Brain Research Center and the Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
| | - Yang Chang
- Brain Research Center and the Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
- Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | | | - Li-Wei Ko
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan; (C.-H.C.); (Z.-C.F.)
- Brain Research Center and the Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan;
- Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
- Department of Electronics and Electrical Engineering, Institute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
- Drug Development and Value Creation Research Center, Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Correspondence: (C.-L.C.); (L.-W.K.)
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27
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Bhavnani S, Parameshwaran D, Sharma KK, Mukherjee D, Divan G, Patel V, Thiagarajan TC. The Acceptability, Feasibility, and Utility of Portable Electroencephalography to Study Resting-State Neurophysiology in Rural Communities. Front Hum Neurosci 2022; 16:802764. [PMID: 35386581 PMCID: PMC8978891 DOI: 10.3389/fnhum.2022.802764] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/17/2022] [Indexed: 11/23/2022] Open
Abstract
Electroencephalography (EEG) provides a non-invasive means to advancing our understanding of the development and function of the brain. However, the majority of the world’s population residing in low and middle income countries has historically been limited from contributing to, and thereby benefiting from, such neurophysiological research, due to lack of scalable validated methods of EEG data collection. In this study, we establish a standard operating protocol to collect approximately 3 min each of eyes-open and eyes-closed resting-state EEG data using a low-cost portable EEG device in rural households through formative work in the community. We then evaluate the acceptability of these EEG assessments to young children and feasibility of administering them through non-specialist workers. Finally, we describe properties of the EEG recordings obtained using this novel approach to EEG data collection. The formative phase was conducted with 9 families which informed protocols for consenting, child engagement strategies and data collection. The protocol was then implemented on 1265 families. 977 children (Mean age = 38.8 months, SD = 0.9) and 1199 adults (Mean age = 27.0 years, SD = 4) provided resting-state data for this study. 259 children refused to wear the EEG cap or removed it, and 58 children refused the eyes-closed recording session. Hardware or software issues were experienced during 30 and 25 recordings in eyes-open and eyes-closed conditions respectively. Disturbances during the recording sessions were rare and included participants moving their heads, touching the EEG headset with their hands, opening their eyes within the eyes-closed recording session, and presence of loud sounds in the testing environment. Similar to findings in laboratory-based studies from high-income settings, the percentage of recordings which showed an alpha peak was higher in eyes-closed than eyes-open condition, with the peak occurring most frequently in electrodes at O1 and O2 positions, and the mean frequency of the alpha peak was found to be lower in children (8.43 Hz, SD = 1.73) as compared to adults (10.71 Hz, SD = 3.96). We observed a deterioration in the EEG signal with prolonged device usage. This study demonstrates the acceptability, feasibility and utility of conducting EEG research at scale in a rural low-resource community, while highlighting its potential limitations, and offers the impetus needed to further refine the methods and devices and validate such scalable methods to overcome existing research inequity.
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Affiliation(s)
- Supriya Bhavnani
- Child Development Group, Sangath, Goa, India.,Public Health Foundation of India, New Delhi, India
| | | | | | - Debarati Mukherjee
- Indian Institute of Public Health-Bengaluru, Public Health Foundation of India, Bengaluru, India
| | - Gauri Divan
- Child Development Group, Sangath, Goa, India
| | - Vikram Patel
- Child Development Group, Sangath, Goa, India.,Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, United States.,Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States
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28
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On the Treatment and Diagnosis of Attention Deficit Hyperactivity Disorder with EEG Assistance. ELECTRONICS 2022. [DOI: 10.3390/electronics11040606] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Attention deficit hyperactivity disorder (ADHD) is a mental disorder most notable in children. The disease may affect the ability to focus and cause a physical and mental restlessness and risky behavior. Recommended treatment consists of stimulant administration and behavioral therapy. However, medicating children is problematic since there are indications that brain development is affected by ADHD medication agents. Therefore, behavioral therapy is the preferred approach in ADHD treatment for children. In order to monitor and optimize the success of such behavioral therapies, neuro-feedback methods can be used. The most notable technology used in such methods is Electroencephalography (EEG). In this article, an overview of the pathology of ADHD, EEG and its usage as a diagnostic and therapeutic tool in the context of ADHD is given. Based on that knowledge, novel EEG measurement modes, new development principles, and system on chip implementations are presented and discussed.
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29
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Maya-Piedrahita MC, Herrera-Gomez PM, Berrío-Mesa L, Cárdenas-Peña DA, Orozco-Gutierrez AA. Supported Diagnosis of Attention Deficit and Hyperactivity Disorder from EEG Based on Interpretable Kernels for Hidden Markov Models. Int J Neural Syst 2022; 32:2250008. [PMID: 34996341 DOI: 10.1142/s0129065722500083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
As a neurodevelopmental pathology, Attention Deficit Hyperactivity Disorder (ADHD) mainly arises during childhood. Persistent patterns of generalized inattention, impulsivity, or hyperactivity characterize ADHD that may persist into adulthood. The conventional diagnosis relies on clinical observational processes yielding high rates of overdiagnosis due to varying interpretations among specialists or missing information. Although several studies have designed objective behavioral features to overcome such an issue, they lack significance. Despite electroencephalography (EEG) analyses extracting alternative biomarkers using signal processing techniques, the nonlinearity and nonstationarity of EEG signals restrain performance and generalization of hand-crafted features. This work proposes a methodology to support ADHD diagnosis by characterizing EEG signals from hidden Markov models (HMM), classifying subjects based on similarity measures for probability functions, and spatially interpreting the results using graphic embeddings of stochastic dynamic models. The methodology learns a single HMM for EEG signal from each patient, so favoring the inter-subject variability. Then, the Probability Product Kernel, specifically developed for assessing the similarity between HMMs, fed a support vector machine that classifies subjects according to their stochastic dynamics. Lastly, the kernel variant of Principal Component Analysis provided a means to visualize the EEG transitions in a two-dimensional space, evidencing dynamic differences between ADHD and Healthy Control children. From the electrophysiological perspective, we recorded EEG under the Stop Signal Task modified with reward levels, which considers cognitive features of interest as insufficient motivational circuits recruitment. The methodology compares the supported diagnosis in two EEG channel setups (whole channel set and channels of interest in frontocentral area) and four frequency bands (Theta, Alpha, Beta rhythms, and a wideband). Results evidence an accuracy rate of 97.0% in the Beta band and in the channels where previous works found error-related negativity events. Such accuracy rate strongly supports the dual pathway hypothesis and motivational deficit concerning the pathophysiology of ADHD. It also demonstrates the utility of joining inhibitory and motivational paradigms with dynamic EEG analysis into a noninvasive and affordable diagnostic tool for ADHD patients.
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Affiliation(s)
- M C Maya-Piedrahita
- Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Risaralda, Colombia
| | - P M Herrera-Gomez
- Research Group Psiquiatría Neurociencias y Comunidad, Universidad Tecnológica de Pereira, Pereira, Risaralda, Colombia
| | - L Berrío-Mesa
- Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Risaralda, Colombia
| | - D A Cárdenas-Peña
- Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Risaralda, Colombia
| | - A A Orozco-Gutierrez
- Automatics Research Group, Universidad Tecnológica de Pereira, Pereira, Risaralda, Colombia
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30
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McLoughlin G, Gyurkovics M, Aydin Ü. What Has Been Learned from Using EEG Methods in Research of ADHD? Curr Top Behav Neurosci 2022; 57:415-444. [PMID: 35637406 DOI: 10.1007/7854_2022_344] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Electrophysiological recording methods, including electroencephalography (EEG) and magnetoencephalography (MEG), have an unparalleled capacity to provide insights into the timing and frequency (spectral) composition of rapidly changing neural activity associated with various cognitive processes. The current chapter provides an overview of EEG studies examining alterations in brain activity in ADHD, measured both at rest and during cognitive tasks. While EEG resting state studies of ADHD indicate no universal alterations in the disorder, event-related studies reveal consistent deficits in attentional and inhibitory control and consequently inform the proposed cognitive models of ADHD. Similar to other neuroimaging measures, EEG research indicates alterations in multiple neural circuits and cognitive functions. EEG methods - supported by the constant refinement of analytic strategies - have the potential to contribute to improved diagnostics and interventions for ADHD, underlining their clinical utility.
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Affiliation(s)
- Gráinne McLoughlin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Máté Gyurkovics
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Ümit Aydin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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31
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Ko J, Park U, Kim D, Kang SW. Quantitative Electroencephalogram Standardization: A Sex- and Age-Differentiated Normative Database. Front Neurosci 2021; 15:766781. [PMID: 34975376 PMCID: PMC8718919 DOI: 10.3389/fnins.2021.766781] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 11/16/2021] [Indexed: 11/13/2022] Open
Abstract
We describe the utility of a standardized index (Z-score) in quantitative EEG (QEEG) capable of when referenced to a resting-state, sex- and age-differentiated QEEG normative database (ISB-NormDB). Our ISB-NormDB comprises data for 1,289 subjects (553 males, 736 females) ages 4.5 to 81 years that met strict normative data criteria. A de-noising process allowed stratification based on QEEG variability between normal healthy men and women at various age ranges. The ISB-NormDB data set that is stratified by sex provides a unique, highly accurate ISB-NormDB model (ISB-NormDB: ISB-NormDB-Male, ISB-NormDB-Female). To evaluate the trends and accuracy of the ISB-NormDB, we used actual data to compare Z-scores obtained through the ISB-NormDB with those obtained through a traditional QEEG normative database to confirm that basic trends are maintained in most bands and are sensitive to abnormal test data. Finally, we demonstrate the value of our standardized index of QEEG, and highlight it's capacity to minimize the confounding variables of sex and age in any analysis.
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Affiliation(s)
- Juhee Ko
- iMediSync Inc., Seoul, South Korea
| | | | | | - Seung Wan Kang
- iMediSync Inc., Seoul, South Korea
- National Standard Reference Data Center for Korean EEG, Seoul National University College of Nursing, Seoul, South Korea
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32
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Yamamoto H, Nakagawa E, Kita Y, Kaga Y, Inagaki M. Effect of anti-attention-deficit hyperactivity disorder (ADHD) medication on clinical seizures and sleep EEG: A retrospective study of Japanese children with ADHD. Neuropsychopharmacol Rep 2021; 41:511-521. [PMID: 34668641 PMCID: PMC8698674 DOI: 10.1002/npr2.12215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/23/2021] [Accepted: 10/04/2021] [Indexed: 11/22/2022] Open
Abstract
Aims Patients with attention‐deficit hyperactivity disorder (ADHD) often exhibit basic or paroxysmal wave abnormalities on electroencephalography (EEG). Methylphenidate (MPH), an anti‐ADHD stimulant, has been reported to lower the seizure threshold. However, there have been no reports comparing EEG changes before and after administration of the central nervous system (CNS) stimulant MPH, or atomoxetine (ATX) hydrochloride, a non‐CNS stimulant. In this study, we investigated changes in sleep EEG before and after the administration of ADHD treatment drugs. Method With the approval of the ethics committee, the medical records of 28 children with ADHD (23 men and 5 women) who gave consent were retrospectively investigated. The appearance of sudden abnormal waves during a 10‐minute sleep EEG recording was measured in 0.1‐second units, and the duration of these waves was calculated as the paroxysmal index (PI). Results Paroxysmal index did not differ significantly between patients who received MPH and those who received ATX. In addition, there were no exacerbations of clinical seizures. Conclusion It was concluded that ADHD medications do not have an adverse effect on epileptic seizures or abnormal sleep EEGs. Patients with attention‐deficit hyperactivity disorder (ADHD) often exhibit basic or paroxysmal wave abnormalities on electroencephalography (EEG). We investigated changes in sleep EEG before and after the administration of ADHD treatment drugs. ADHD medications do not have an adverse effect on epileptic seizures or abnormal sleep EEGs.![]()
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Affiliation(s)
- Hisako Yamamoto
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan.,Department of Pediatrics, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Eiji Nakagawa
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry (NCNP), Kodaira, Japan
| | - Yousuke Kita
- Mori Arinori Center for Higher Education and Global Mobility, Hitotsubashi University, Tokyo, Japan.,Cognitive Brain Research Unit (CBRU), Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Yoshimi Kaga
- Department of Developmental Disorders, National Institute of Mental Health, NCNP, Kodaira, Japan.,Department of Pediatrics, Faculty of Medicine, Yamanashi University, Yamanashi, Japan
| | - Masumi Inagaki
- Department of Developmental Disorders, National Institute of Mental Health, NCNP, Kodaira, Japan
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33
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DSM-5 Adult Attention-Deficit/Hyperactivity Disorder: Sex Differences in EEG Activity. Appl Psychophysiol Biofeedback 2021; 46:377-388. [PMID: 34529233 DOI: 10.1007/s10484-021-09522-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/01/2021] [Indexed: 10/20/2022]
Abstract
This study examined sex differences in the EEG of adults diagnosed with Attention-Deficit/Hyperactivity Disorder (AD/HD) according to DSM-5 criteria. Sixteen females and 16 males with AD/HD, and age- and sex-matched control groups, had an eyes-closed resting EEG recorded from 19 electrode sites. EEGs were Fast Fourier transformed and estimates for total power, absolute and relative power in the delta, theta, alpha, beta and gamma bands, and the theta/beta ratio, were analysed across nine cortical regions. Males with AD/HD, compared with male controls, had globally reduced absolute beta, globally elevated relative theta, and a larger theta/beta ratio. In contrast, no global effects emerged between females with and without AD/HD. Significant group interactions indicated that globally elevated relative theta and elevated frontal-midline theta/beta ratio noted in males with AD/HD differed significantly from results in females. There are statistically significant EEG differences in relative theta and the theta/beta ratio between males and females with and without AD/HD. These results indicate that AD/HD affects the EEG activity of males and females differently. This study helps confirm the need for further independent examination of AD/HD within female populations.
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Rubia K, Westwood S, Aggensteiner PM, Brandeis D. Neurotherapeutics for Attention Deficit/Hyperactivity Disorder (ADHD): A Review. Cells 2021; 10:2156. [PMID: 34440925 PMCID: PMC8394071 DOI: 10.3390/cells10082156] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/07/2021] [Accepted: 08/18/2021] [Indexed: 01/19/2023] Open
Abstract
This review focuses on the evidence for neurotherapeutics for attention deficit/hyperactivity disorder (ADHD). EEG-neurofeedback has been tested for about 45 years, with the latest meta-analyses of randomised controlled trials (RCT) showing small/medium effects compared to non-active controls only. Three small studies piloted neurofeedback of frontal activations in ADHD using functional magnetic resonance imaging or near-infrared spectroscopy, finding no superior effects over control conditions. Brain stimulation has been applied to ADHD using mostly repetitive transcranial magnetic and direct current stimulation (rTMS/tDCS). rTMS has shown mostly negative findings on improving cognition or symptoms. Meta-analyses of tDCS studies targeting mostly the dorsolateral prefrontal cortex show small effects on cognitive improvements with only two out of three studies showing clinical improvements. Trigeminal nerve stimulation has been shown to improve ADHD symptoms with medium effect in one RCT. Modern neurotherapeutics are attractive due to their relative safety and potential neuroplastic effects. However, they need to be thoroughly tested for clinical and cognitive efficacy across settings and beyond core symptoms and for their potential for individualised treatment.
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Affiliation(s)
- Katya Rubia
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK;
- Department of Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK
- Department of Child & Adolescent Psychiatry, Transcampus, Dresden University, 01307 Dresden, Germany
| | - Samuel Westwood
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK;
- Department of Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK
- Department of Psychology, Wolverhampton University, Wolverhampton WV1 1LY, UK
| | - Pascal-M. Aggensteiner
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, 68159 Mannheim, Germany; (P.-M.A.); (D.B.)
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, 68159 Mannheim, Germany; (P.-M.A.); (D.B.)
- Department of Child and Adolescent Psychiatry and Psychotherapy, Hospital of Psychiatry, Psychiatric Hospital University, University of Zürich, 8032 Zürich, Switzerland
- Neuroscience Center Zürich, Swiss Federal Institute of Technology and University of Zürich, 8057 Zürich, Switzerland
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35
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Chen IC, Chang CH, Chang Y, Lin DS, Lin CH, Ko LW. Neural Dynamics for Facilitating ADHD Diagnosis in Preschoolers: Central and Parietal Delta Synchronization in the Kiddie Continuous Performance Test. IEEE Trans Neural Syst Rehabil Eng 2021; 29:1524-1533. [PMID: 34280103 DOI: 10.1109/tnsre.2021.3097551] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The present study aimed to characterize children at risk of attention-deficit/hyperactivity disorder (ADHD) during preschool age and provide early intervention. The continuous performance test (CPT) and electroencephalography (EEG) can contribute additional valuable information to facilitate diagnosis. This study measured brain dynamics at slow and fast task rates in the CPT using a wireless wearable EEG and identified correlations between the EEG and CPT data in preschool children with ADHD. Forty-nine preschool children participated in this study, of which 29 were diagnosed with ADHD and 20 exhibited typical development (TD). The Conners Kiddie Continuous Performance Test (K-CPT) and wireless wearable EEG recordings were employed simultaneously. Significant differences were observed between the groups with ADHD and TD in task-related EEG spectral powers (central as well as parietal delta, P < 0.01), which were distinct only in the slow-rate task condition. A shift from resting to the CPT task condition induced overall alpha powers decrease in the ADHD group. In the task condition, the delta powers were positively correlated with the CPT perseveration scores, whereas the alpha powers were negatively correlated with specific CPT scores mainly on perseveration and detectability (P < 0.05). These results, which complement the findings of other sparse studies that have investigated within-task-related brain dynamics, particularly in preschool children, can assist specialists working in early intervention to plan training and educational programs for preschoolers with ADHD.
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36
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A Novel Knowledge Distillation-Based Feature Selection for the Classification of ADHD. Biomolecules 2021; 11:biom11081093. [PMID: 34439759 PMCID: PMC8393979 DOI: 10.3390/biom11081093] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 07/21/2021] [Accepted: 07/21/2021] [Indexed: 01/17/2023] Open
Abstract
Attention Deficit Hyperactivity Disorder (ADHD) is a brain disorder with characteristics such as lack of concentration, excessive fidgeting, outbursts of emotions, lack of patience, difficulty in organizing tasks, increased forgetfulness, and interrupting conversation, and it is affecting millions of people worldwide. There is, until now, not a gold standard test using which an ADHD expert can differentiate between an individual with ADHD and a healthy subject, making accurate diagnosis of ADHD a challenging task. We are proposing a Knowledge Distillation-based approach to search for discriminating features between the ADHD and healthy subjects. Learned embeddings from a large neural network, trained on the functional connectivity features, were fed to one hidden layer Autoencoder for reproduction of the embeddings using the same connectivity features. Finally, a forward feature selection algorithm was used to select a combination of most discriminating features between the ADHD and the Healthy Controls. We achieved promising classification results for each of the five individual sites. A combined accuracy of 81% in KKI, 60% Peking, 56% in NYU, 64% NI, and 56% OHSU and individual site wise accuracy of 72% in KKI, 60% Peking, 73% in NYU, 70% NI, and 71% OHSU were obtained using our extracted features. Our results also outperformed state-of-the-art methods in literature which validates the efficacy of our proposed approach.
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37
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Bong SH, Kim JW. The Role of Quantitative Electroencephalogram in the Diagnosis and Subgrouping of Attention-Deficit/Hyperactivity Disorder. Soa Chongsonyon Chongsin Uihak 2021; 32:85-92. [PMID: 34285632 PMCID: PMC8262972 DOI: 10.5765/jkacap.210010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 05/03/2021] [Accepted: 05/07/2021] [Indexed: 12/03/2022] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) leads to functional decline in academic performance, interpersonal relationships, and development in school-aged children. Early diagnosis and appropriate intervention can significantly reduce the functional decline caused by ADHD. Currently, there is no established biological marker for ADHD. Some studies have suggested that various indicators from the quantitative electroencephalogram (QEEG) may be useful biological markers for the diagnosis of ADHD. Until the 2010s, theta/beta ratio (TBR) was a biomarker candidate for ADHD that consistently showed high diagnostic value. However, limitations of TBR have recently been reported. Studies have demonstrated that phase-amplitude coupling, especially theta phase-gamma amplitude coupling, are related to cognitive dysfunction and may assist in the diagnosis of ADHD. As yet, the underlying mechanism is not clearly established, and the clinical efficacy of these biomarkers needs to be proven through well-controlled studies. Based on the heterogeneous characteristics of ADHD, subgrouping through QEEG plays a key role in diagnosis and treatment planning. Sophisticated, well-designed studies and meta-analyses are necessary to confirm these findings.
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Affiliation(s)
- Su Hyun Bong
- Department of Psychiatry, Catholic University of Daegu School of Medicine, Daegu, Korea
| | - Jun Won Kim
- Department of Psychiatry, Catholic University of Daegu School of Medicine, Daegu, Korea
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38
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Abstract
Our current diagnostic methods for treatment planning in Psychiatry and Neurodevelopmental Disabilities leave room for improvement, and null results in clinical trials in these fields may be a result of insufficient tools for patient stratification. Great hope has been placed in novel technologies to improve clinical and trial outcomes, but we have yet to see a substantial change in clinical practice. As we examine attempts at biomarker validation within these fields, we find that it may be the diagnoses themselves that fall short. We now need to improve neuropsychiatric nosologies with a focus on validity based not solely on behavioral features, but on a synthesis that includes genetic and biological data as well. The eventual goal is diagnostic biomarkers and diagnoses themselves based on distinct mechanisms, but such an understanding of the causal relationship across levels of analysis is likely to be elusive for some time. Rather, we propose an approach in the near-term that deconstructs diagnosis into a series of independent, empiric and clinically relevant associations among a single, defined patient group, a single biomarker, a single intervention and a single clinical outcome. Incremental study across patient groups, interventions, outcomes and modalities will lead to a more interdigitated network of knowledge, and correlations in metrics across levels of analysis will eventually give way to the causal understanding that will allow for mechanistically based diagnoses.
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39
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Aiding diagnosis of childhood attention-deficit/hyperactivity disorder of the inattentive presentation: Discriminant function analysis of multi-domain measures including EEG. Biol Psychol 2021; 161:108080. [PMID: 33744372 DOI: 10.1016/j.biopsycho.2021.108080] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 03/09/2021] [Accepted: 03/12/2021] [Indexed: 11/20/2022]
Abstract
INTRODUCTION We developed a neurocognitive assessment tool (NCAT) in consultation with mental health professionals working with children with AD/HD as a diagnostic aid and screening tool. This study examines the predictive utility of NCAT in the classification of children with AD/HD Inattentive presentation. METHOD Fifty three children with AD/HD Inattentive presentation and 161 typically-developing children completed an NCAT assessment. Discriminant function analyses examined group membership prediction for separate components of NCAT and for the components combined. RESULTS The combined model correctly classified 93.4 % of participants, with 91.4 % sensitivity and 93.9 % specificity. Contributions to classification were from SNAP-IV, psychological needs satisfaction, self-regulation, executive function performance, and EEG. The combined model resulted in a 9.3 % increase in specificity and 5.9 % increase in sensitivity compared to SNAP-IV alone. CONCLUSIONS NCAT provides good discrimination between children with and without AD/HD of the Inattentive presentation, and further investigation including other subtypes and comorbidities is warranted.
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Abstract
Two major trends have been dominant in health care in recent years. First, there is a growing consensus that standardization of health care procedures and methods can result in improved effectiveness and safety of treatments. Second, there is increased interest in "personalized medicine," which refers to the tailoring of treatments to individual patients. Here I discuss how these trends apply to the field of quantitative EEG (qEEG), where de-artifacted resting state EEGs of individuals are compared with a normative database in order to assess clinically meaningful deviations, which can be used for diagnostic procedures, to guide personalized treatment protocols, and to assess treatment effectiveness. Standardized and automated de-artifacting procedures are increasingly being used in scientific research and in clinical practice. The advantages of these procedures over manual de-artifacting will be discussed. The results of a systematic comparison between 2 commonly used qEEG databases show that these databases produce very comparable results, illustrating not only the validity and reliability of both databases but also the opportunity to move forward to a standardized use of qEEG in clinical practice. Finally, the standardization of qEEG interpretation as both a diagnostic and treatment selection tool provides an example of how qEEG can merge both personalized medicine and standardization in the treatment of psychological disorders.
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Affiliation(s)
- André W Keizer
- Neurofeedback Instituut Nederland, Eindhoven, the Netherlands.,qEEG-Pro. Eindhoven, the Netherlands
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41
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Skalski S, Pochwatko G, Balas R. Impact of Motivation on Selected Aspects of Attention in Children with ADHD. Child Psychiatry Hum Dev 2021; 52:586-595. [PMID: 32816140 PMCID: PMC8238702 DOI: 10.1007/s10578-020-01042-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 06/03/2020] [Accepted: 08/09/2020] [Indexed: 02/06/2023]
Abstract
Earlier reports showed the co-occurrence of a motivation deficit in children with ADHD. The purpose of this study was to assess the impact of extrinsic motivation on selected aspects of attention in children with ADHD, as well as to measure cortical activity and dimensions of motivation as per the self-determination theory. The study included 30 children with ADHD and 30 typically developing (TD) children aged 9-13 years. Children with ADHD exhibited a higher theta/beta power ratio (TBR) in the midline and a lower regional cerebral blood oxygenation (rCBO2) level in prefrontal areas measured using the HEG ratio compared to TD children. Children with ADHD were more likely to undertake activity under the pressure of external stimuli and exhibited attention deficits regarding vigilance, visual search and divided attention. Differences between groups regarding attention decreased in conditions of increased motivation, indicating that motivation can reduce cognitive deficits in children with ADHD.
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Affiliation(s)
- Sebastian Skalski
- Institute of Psychology, Polish Academy of Sciences, 1 Jaracza Street, 00-378, Warsaw, Poland.
| | - Grzegorz Pochwatko
- grid.413454.30000 0001 1958 0162Institute of Psychology, Polish Academy of Sciences, 1 Jaracza Street, 00-378 Warsaw, Poland
| | - Robert Balas
- grid.413454.30000 0001 1958 0162Institute of Psychology, Polish Academy of Sciences, 1 Jaracza Street, 00-378 Warsaw, Poland
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Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity. eNeuro 2020; 7:ENEURO.0192-20.2020. [PMID: 32978216 PMCID: PMC7768281 DOI: 10.1523/eneuro.0192-20.2020] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 09/01/2020] [Accepted: 09/08/2020] [Indexed: 12/11/2022] Open
Abstract
Band ratio measures, computed as the ratio of power between two frequency bands, are a common analysis measure in neuroelectrophysiological recordings. Band ratio measures are typically interpreted as reflecting quantitative measures of periodic, or oscillatory, activity. This assumes that the measure reflects relative powers of distinct periodic components that are well captured by predefined frequency ranges. However, electrophysiological signals contain periodic components and a 1/f-like aperiodic component, the latter of which contributes power across all frequencies. Here, we investigate whether band ratio measures truly reflect oscillatory power differences, and/or to what extent ratios may instead reflect other periodic changes, such as in center frequency or bandwidth, and/or aperiodic activity. In simulation, we investigate how band ratio measures relate to changes in multiple spectral features, and show how multiple periodic and aperiodic features influence band ratio measures. We validate these findings in human electroencephalography (EEG) data, comparing band ratio measures to parameterizations of power spectral features and find that multiple disparate features influence ratio measures. For example, the commonly applied θ/β ratio is most reflective of differences in aperiodic activity, and not oscillatory θ or β power. Collectively, we show that periodic and aperiodic features can create the same observed changes in band ratio measures, and that this is inconsistent with their typical interpretations as measures of periodic power. We conclude that band ratio measures are a non-specific measure, conflating multiple possible underlying spectral changes, and recommend explicit parameterization of neural power spectra as a more specific approach.
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43
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Moghaddari M, Lighvan MZ, Danishvar S. Diagnose ADHD disorder in children using convolutional neural network based on continuous mental task EEG. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 197:105738. [PMID: 32927404 DOI: 10.1016/j.cmpb.2020.105738] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 08/31/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND AND OBJECTIVE Attention-Deficit/Hyperactivity Disorder (ADHD) is a chronic behavioral disorder in children. Children with ADHD face many difficulties in maintaining their concentration and controlling their behaviors. Early diagnosis of this disorder is one of the most important challenges in its control and treatment. No definitive expert method has been found to detect this disorder early. Our goal in this study is to develop an assistive tool for physicians to recognize ADHD children from healthy children using electroencephalography (EEG) based on a continuous mental task. METHODS We used EEG signals recorded from 31 ADHD children and 30 healthy children. In this study, we developed a deep learning model using a convolutional neural network that have had significant performance in image processing fields. For this purpose, we first preprocessed EEG signals to eliminate noise and artifacts. Then we segmented preprocessed samples into more samples. We extracted the theta, alpha, beta, and gamma frequency bands from each segmented sample and formed a color RGB image with three channels. Eventually, we imported the resulting images into a 13-layer convolutional neural network for feature extraction and classification. RESULTS The proposed model was evaluated by 5-fold cross validation for train, evaluation, and test data and achieved an average accuracy of 99.06%, 97.81%, 97.47% for segmented samples. The average accuracy for subject-based test samples was 98.48%. Also, the performance of the model was evaluated using the confusion matrix with precision, recall, and f1-score metrics. The results of these metrics also confirmed the outstanding performance of the model. CONCLUSIONS The accuracy, precision, recall, and f1-score of our model were better than all previous works for diagnosing ADHD in children. Based on these prominent and reliable results, this technique can be used as an assistive tool for the physicians in the early diagnosis of ADHD in children.
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Affiliation(s)
- Majid Moghaddari
- Department of Electronic and Computer Engineering, University of Tabriz, Tabriz, Iran
| | - Mina Zolfy Lighvan
- Department of Electronic and Computer Engineering, University of Tabriz, Tabriz, Iran.
| | - Sebelan Danishvar
- Department of Electronic and Computer Engineering, University of Tabriz, Tabriz, Iran; Department of Electronic and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University, UK
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44
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Drechsler R, Brem S, Brandeis D, Grünblatt E, Berger G, Walitza S. ADHD: Current Concepts and Treatments in Children and Adolescents. Neuropediatrics 2020; 51:315-335. [PMID: 32559806 PMCID: PMC7508636 DOI: 10.1055/s-0040-1701658] [Citation(s) in RCA: 95] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 11/28/2019] [Indexed: 12/17/2022]
Abstract
Attention deficit hyperactivity disorder (ADHD) is among the most frequent disorders within child and adolescent psychiatry, with a prevalence of over 5%. Nosological systems, such as the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) and the International Classification of Diseases, editions 10 and 11 (ICD-10/11) continue to define ADHD according to behavioral criteria, based on observation and on informant reports. Despite an overwhelming body of research on ADHD over the last 10 to 20 years, valid neurobiological markers or other objective criteria that may lead to unequivocal diagnostic classification are still lacking. On the contrary, the concept of ADHD seems to have become broader and more heterogeneous. Thus, the diagnosis and treatment of ADHD are still challenging for clinicians, necessitating increased reliance on their expertise and experience. The first part of this review presents an overview of the current definitions of the disorder (DSM-5, ICD-10/11). Furthermore, it discusses more controversial aspects of the construct of ADHD, including the dimensional versus categorical approach, alternative ADHD constructs, and aspects pertaining to epidemiology and prevalence. The second part focuses on comorbidities, on the difficulty of distinguishing between "primary" and "secondary" ADHD for purposes of differential diagnosis, and on clinical diagnostic procedures. In the third and most prominent part, an overview of current neurobiological concepts of ADHD is given, including neuropsychological and neurophysiological researches and summaries of current neuroimaging and genetic studies. Finally, treatment options are reviewed, including a discussion of multimodal, pharmacological, and nonpharmacological interventions and their evidence base.
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Affiliation(s)
- Renate Drechsler
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Edna Grünblatt
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Gregor Berger
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
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Ahmadi M, Kazemi K, Kuc K, Cybulska-Klosowicz A, Zakrzewska M, Racicka-Pawlukiewicz E, Helfroush MS, Aarabi A. Cortical source analysis of resting state EEG data in children with attention deficit hyperactivity disorder. Clin Neurophysiol 2020; 131:2115-2130. [DOI: 10.1016/j.clinph.2020.05.028] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Revised: 04/03/2020] [Accepted: 05/16/2020] [Indexed: 12/14/2022]
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46
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Rostami M, Khosrowabadi R, Albrecht B, Pouretemad H, Rothenberger A. ADHD subtypes: Do they hold beyond core symptoms? A multilevel testing of an additive model. APPLIED NEUROPSYCHOLOGY-CHILD 2020; 11:280-290. [DOI: 10.1080/21622965.2020.1806067] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Mohammad Rostami
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Reza Khosrowabadi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Björn Albrecht
- Clinic for Child and Adolescent Psychiatry and Psychotherapy, University Medical Centers of Göttingen, Göttingen, Germany
| | - Hamidreza Pouretemad
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Aribert Rothenberger
- Clinic for Child and Adolescent Psychiatry and Psychotherapy, University Medical Centers of Göttingen, Göttingen, Germany
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47
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Waszkiewicz N. Mentally Sick or Not-(Bio)Markers of Psychiatric Disorders Needed. J Clin Med 2020; 9:jcm9082375. [PMID: 32722366 PMCID: PMC7465438 DOI: 10.3390/jcm9082375] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 12/11/2022] Open
Affiliation(s)
- Napoleon Waszkiewicz
- Department of Psychiatry, Medical University of Białystok, Plac Brodowicza 1, 16-070 Choroszcz, Poland
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Clarke AR, Barry RJ, Johnstone S. Resting state EEG power research in Attention-Deficit/Hyperactivity Disorder: A review update. Clin Neurophysiol 2020; 131:1463-1479. [DOI: 10.1016/j.clinph.2020.03.029] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 02/20/2020] [Accepted: 03/16/2020] [Indexed: 01/19/2023]
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Nonlinear Analysis of Visually Normal EEGs to Differentiate Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS). Sci Rep 2020; 10:8419. [PMID: 32439999 PMCID: PMC7242341 DOI: 10.1038/s41598-020-65112-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 03/30/2020] [Indexed: 02/07/2023] Open
Abstract
Childhood epilepsy with centrotemporal spikes, previously known as Benign Epilepsy with Centro-temporal Spikes (BECTS) or Rolandic Epilepsy, is one of the most common forms of focal childhood epilepsy. Despite its prevalence, BECTS is often misdiagnosed or missed entirely. This is in part due to the nocturnal and brief nature of the seizures, making it difficult to identify during a routine electroencephalogram (EEG). Detecting brain activity that is highly associated with BECTS on a brief, awake EEG has the potential to improve diagnostic screening for BECTS and predict clinical outcomes. For this study, 31 patients with BECTS were retrospectively selected from the BCH Epilepsy Center database along with a contrast group of 31 patients in the database who had no form of epilepsy and a normal EEG based on a clinical chart review. Nonlinear features, including multiscale entropy and recurrence quantitative analysis, were computed from 30-second segments of awake EEG signals. Differences were found between these multiscale nonlinear measures in the two groups at all sensor locations, while visual EEG inspection by a board-certified child neurologist did not reveal any distinguishing features. Moreover, a quantitative difference in the nonlinear measures (sample entropy, trapping time and the Lyapunov exponents) was found in the centrotemporal region of the brain, the area associated with a greater tendency to have unprovoked seizures, versus the rest of the brain in the BECTS patients. This difference was not present in the contrast group. As a result, the epileptic zone in the BECTS patients appears to exhibit lower complexity, and these nonlinear measures may potentially serve as a clinical screening tool for BECTS, if replicated in a larger study population.
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Rostami M, Farashi S, Khosrowabadi R, Pouretemad H. Discrimination of ADHD Subtypes Using Decision Tree on Behavioral, Neuropsychological, and Neural Markers. Basic Clin Neurosci 2020; 11:359-367. [PMID: 32963728 PMCID: PMC7502189 DOI: 10.32598/bcn.9.10.115] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 06/05/2019] [Accepted: 07/28/2019] [Indexed: 11/30/2022] Open
Abstract
Introduction: Attention-Deficit/Hyperactivity Disorder (ADHD) is a well-known neurodevelopmental disorder. Diagnosis and treatment of ADHD can often lead to a developmental trajectory toward positive results. The present study aimed at implementing the decision tree method to recognize children with and without ADHD, as well as ADHD subtypes. Methods: In the present study, the subjects included 61 children with ADHD (subdivided into ADHD-I (n=25), ADHD-H (n=14), and ADHD-C (n=22) groups) and 43 typically developing controls matched by IQ and age. The Child Behavior Checklist (CBCL), Integrated Visual And Auditory (IVA) test, and quantitative EEG during eyes-closed resting-state were utilized to evaluate the level of behavioral, neuropsychology, and electrophysiology markers using a decision tree algorithm, respectively. Results: Based on the results, excellent classification accuracy (100%) was obtained to discriminate children with ADHD from the control group. Also, the ADHD subtypes, including combined, inattention, and hyperactive/impulsive subtypes were recognized from others with an accuracy of 80.41%, 84.17%, and 71.46%, respectively. Conclusion: Our results showed that children with ADHD can be recognized from the healthy controls based on the neuropsychological data (sensory-motor parameters of IVA). Also, subtypes of ADHD can be distinguished from each other using behavioral, neuropsychiatric and electrophysiological parameters. The findings suggested that the decision tree method may present an efficient and accurate diagnostic tool for the clinicians.
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Affiliation(s)
- Mohammad Rostami
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Sajjad Farashi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Reza Khosrowabadi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Hamidreza Pouretemad
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
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