Distribución cortical de la potencia absoluta de la actividad Beta 12Hz-25 Hz en niños varones con trastorno por déficit de atención e hiperactividad combinado

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2021-06-30

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Téllez-Villagra, C., & González Pedraza Avilés, A. (2021). Distribución cortical de la potencia absoluta de la actividad Beta 12Hz-25 Hz en niños varones con trastorno por déficit de atención e hiperactividad combinado. Revista De Psiquiatría Infanto-Juvenil, 38(2), 4–25. https://doi.org/10.31766/revpsij.v38n2a2

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https://doi.org/10.31766/revpsij.v38n2a2

Palabras clave:

Trastorno por déficit de atención e hiperactividad, QEEG, Ritmo Beta, T.O.V.A, variabilidad y tiempo de reacción, atención visual, atención auditiva, redes neuronales artificiales

Resumen

Introducción: El ritmo Beta del electroencefalograma cuantitativo (QEEG) está vinculado con inatención y alteraciones del movimiento. En niños con trastorno por déficit de atención e hiperactividad (TDAH) se han reportado potencia absoluta (PA) con incremento en frecuencias lentas y disminución en rápidas especialmente Beta-total. Objetivo: Identificar la distribución cortical de PA disminuida o incrementada en el QEEG en reposo-ojos-cerrados de cada frecuencia Beta (12Hz-25Hz) como predictora de inatención visual o auditiva y de la iniciación e inhibición del movimiento en niños varones con TDAH de presentación combinada. Material y Métodos: Estudio retrospectivo (2008-2019) en 131 niños varones (6-14 años), diagnosticados de TDAH de presentación combinada. De cada niño, se obtuvieron 532 datos: PA + 2 de la norma (base Neuroguide), Beta (12-25Hz) en 19 derivaciones del QEEG se asociaron a inatención visual, auditiva y al movimiento (puntuación < 80 TOVA-Visual y Auditiva). Resultados: Se obtuvo una PA disminuida en 1738 derivaciones (81,5%); PA incrementada en 394 (18,48%). Beta 20-25Hz PA disminuida predominó en Frontal y Centro-témporo-occipital; 12-13Hz PA-incrementada en Parietal. Inatención visual más baja que auditiva. Variabilidad y Tiempo de Respuesta visual caracterizaron la mala ejecución. PA-disminuida Beta 25Hz en Frontal caracterizó 30 (43%) niños con inatención visual y auditiva; Beta 23-25Hz en Centro-témporo-occipital a 33 (75%) con inatención visual; PA-incrementada 21Hz en Frontal y 25Hz en Parietal a 2 (29%) con inatención-auditiva. Beta 13-25Hz PA-disminuida en Frontal y Centro-témporo-occipital y 20-25Hz en Parietal influyeron en inatención visual en todas sus variables; mientras que inatención-auditiva en todas sus variables fue influenciada por Beta 16-25Hz en Centro-témporo-occipital. Beta 16-25Hz PA-disminuida en Frontal y Centro-témporo-occipital influyeron en hiperactividad visual y auditiva; Beta 22-25Hz en Centro-témporo-occipital en impulsividad visual y auditiva. Conclusión: Beta 20-25Hz con PA disminuida en Centro-témporo-occipital y 12-13Hz con PA-incrementada en Parietal junto con Variabilidad y Tiempo de Respuesta visual, pudieran ser biomarcadores del TDAH combinado. Los biomarcadores podrán apoyar el diagnóstico preciso y el uso de terapia no farmacológica con tecnología de punta que regule la actividad eléctrica.

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Sayal K, Prasad V, Daley D, Ford T, Coghill D. ADHD in children and young people: prevalence, care pathways, and service provision. Lancet Psychiatry. 2018; 5(2). https://doi.org/10.1016/S2215-0366(17)30167-0

Gallardo-Saavedra GA, Martínez-Wbaldo MDC, Padrón-García AL. Prevalence of ADHD in Mexican schoolchildren through screening with Conners scales 3. Actas Esp Psiquiatr. 2019; 47(2): 45-53.

American Psychiatric Association, APA. Diagnostic and Statistical Manual of Mental Disorders (DSM-5) 2013-2020 Arlington: APA.

Galiana-Simal A, Vecina-Navarro P, Sánchez-Ruiz P, Vela-Romero M. Electroencefalografía cuantitativa como herramienta para el diagnóstico y seguimiento del paciente con trastorno por déficit de atención/hiperactividad. Rev Neurol. 2020; 70(06): 197-205. https://doi.org/10.33588/rn.7006.2019311

Sanei S, Chambers JA. EEG signal proccesing Inglaterra: John Wiley & Sons Ltd.; 2007. Online ISBN:9780470511923. https://doi.org/10.1002/9780470511923

Lopes Da Silva F. EEG and MEG: relevance to neuroscience. Neuron. 2013; 80(5): 1112–28. https://doi.org/10.1016/j.neuron.2013.10.017

Steriade M. Grouping of brain rhythms in corticothalamic systems. Neuroscience. 2006; 137(4): 1087-106. https://doi.org/10.1016/j.neuroscience.2005.10.029

Mizuseki K, Sirota A, Pastalkova E, Buzsáki G. Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron. 2009; 64(2): 267-80. https://doi.org/10.1016/j.neuron.2009.08.037

Amzica F, Lopes da Silva FH. Electroencephalography: Basic Principles, Clinical Applications and Related Fields. En Niedermeyer E, editor. Electroencephalography: Basic Principles, Clinical Applications and Related Fields. Philadelphia: Lippincott Williams & Wilkins; 2011. 33-63.

Barry RJ, Clarke AR, Johnstone SJ. A review of electrophysiology in attention-deficithyperactivity disorder: I. Qualitative and quantitative electroencephalography. Clin Neurophysiol. 2003; 114(2): 171-83. https://doi.org/10.1016/s1388-2457(02)00362-0

Clarke AR, Barry RJ, Johnstone S. Resting state EEG power research in Attention-Deficit / Hyperactivity Hyperactivity Disorder: A review update. Clin Neurophysiol. 2020; 131(7): 1463-79. https://doi.org/10.1016/j.clinph.2020.03.029

Clarke AR, Barry RJ, Dupuy FE, McCarthy R, Selikowitz M, Heaven PCL. Childhood EEG as a predictor of adult attention-deficit/hyperactivity disorder. Clin Neurophysiol. 2011; 122(1): 73-80. https://doi.org/10.1016/j.clinph.2010.05.032

Ortiz-Pérez A, Moreno-García I. Perfil electroencefalográfico de niños con TDAH. RPCNA. 2015; 2(2): 129-34.

Cheng QR, Shen HJ, Tu WJ, Zhang QF, Dong X. Electroencephalogram power development of cognitive function at age 7 to 12 years: a comparative study between attention deficit hyperactivity disorder and healthy children (Article in Chinese). Zhonghua Er Ke Za Zhi. 2016; 54(12): 913-16. https://doi.org/10.3760/cma.j.issn.0578-1310.2016.12.008

Halawa IF, El Sayed BB, Amin OR, Meguid NA, Abdel Kader AA. Frontal theta/beta ratio changes during TOVA in Egyptian ADHD children. Neurosciences (Riyadh). 2017; 22(4): 287–91. https://doi.org/10.17712/nsj.2017.4.20170067

Rodríguez-Martínez EI, Angulo-Ruiz BY, Arjona-Valladares A, Rufo M, Gómez-González J. Frecuency coupling of low and high frecuencies in the EEG of ADHD children and adolescents in close and open eyes conditions. Res Dev Disabil. 2020; 96(103520). https://doi.org/10.1016/j.ridd.2019.103520

Newson JJ, Thiagarajan TC. EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies. Front Hum Neurosci. 2019; 12(521). https://doi.org/10.3389/fnhum.2018.00521

Bashiri A, Shahmoradi L, Beigy H, Savareh BA, Nosratabadi M, N Kalhori SR, et al. Quantitative EEG features selection in the classification of attention and response control in the children and adolescents with attention deficit hyperactivity disorder. Future Sci OA. 2018; 4(5): FSO292. https://doi.org/10.4155/fsoa-2017-0138

Kopell N, Kramer MA, Malerba P, Whittington MA. Are different rhythms good for different functions? Front Hum Neurosci. 2010; 4(187). https://doi.org/10.3389/fnhum.2010.00187

Clarke AR, Barry JR, McCarthy R, Selikowitz M. EEG-defined subtypes of children with attention-deficit/hyperactivity disorder. Clin Neurophysiol. 2001; 112(11): 2098-105. https://doi.org/10.1016/s1388- 2457(01)00668-x

Monastra VJ, Lubar JF, Linden M, VanDeusen P, Green G, Wing W, et al. Assessing attention deficit hyperactivity disorder via quantitative electroencephalography: an initial validation study. Neuropsychology. 1999; 13(3): 424-433. https://doi.org/10.1037/0894-4105.13.3.424

Magee CA, Clarke AR, Barry RJ, McCarthy R, Selikowitz M. Examining the diagnostic utility of EEG power measures in children with attention deficit/hyperactivity disorder. Clin Neurophysiol. 2005; 116(5): 1033-40. https://doi.org/10.1016/j.clinph.2004.12.007

Snyder SM, Rugino TA, Horning M, Stein MA. Integration of an EEG biomarker with a clinician's ADHD evaluation. Brain Behav. 2015; 5(4). https://doi.org/10.1002/brb3.330

Buyck I, Wiersema JR. Resting electroencephalogram in attention deficit hyperactivity disorder. Psychiatry Res. 2014; 216(3): 391-7. https://doi.org/10.1016/j.psychres.2013.12.055

Mowlem FD, Rosenqvist MA, Martin J, Lichtenstein P, Asherson P, Larsson H. Sex differences in predicting ADHD clinical diagnosis and pharmacological treatment. Eur. Child. Adolesc. Psychiatry. 2019; 28(4): 481-9. https://doi.org/10.1007/s00787-018-1211-3

Ghaderi AH, Nazari MA, Shahrokhi H, Darooneh AH. Functional Brain Connectivity Differences Between Different ADHD Presentations: Impaired Functional Segregation in ADHD-Combined Presentation but not in ADHD-Inattentive Presentation. Basic Clin Neurosci. 2017; 8(4): 267-78. https://doi.org/10.18869/nirp.bcn.8.4.267

Aldemir R, Demirci E, Per H, Canpolat M, Özmen S, M T. Investigation of attention deficit hyperactivity disorder (ADHD) sub-types in children via EEG frequency domain analysis. Int J Neurosci. 2018; 128(4): 349-60. https://doi.org/10.1080/00207454.2017.1382493

Congredo M, Lubar JF. Parametric and non-parametric analysis of QEEG: Normative database. Journal of Neurotherapy. 2003; 7(3-4): 1-29.

Siegel M, Donner TH, Oostenveld R, Fries P, Engel AK. Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron. 2008; 60(4): 709-19. https://doi.org/10.1016/j.neuron.2008.09.010

Shin H, Law R, Tsutsui S, Moore CI, Jones SR. The rate of transient beta frequency events predicts behavior across tasks and species. ELife. 2017; 6: e29086. https://doi.org/10.7554%2FeLife.29086

Tzagarakis C, Thompson A, Rogers RD, Pellizzer G. The Degree of Modulation of Beta Band Activity During Motor Planning Is Related to Trait Impulsivity. Front Integr Neurosci. 2019; 13(1). https://doi.org/10.3389%2Ffnint.2019.00001

Sherman MA, Lee S, Law R, Haegens S, Thorn CA, Hämäläinen MS, et al. Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice. Proc Natl Acad Sci U S A. 2016; 113(33): 4885-94. https://doi.org/10.1073/pnas.1604135113

Kim J, Lee Y, Han D, Min K, Kim D, Lee C. The utility of quantitative electroencephalography and Integrated Visual and Auditory Continuous Performance Test as auxiliary tools for the Attention Deficit Hyperactivity Disorder diagnosis. Clin Neurophysiol. 2015; 126(3): 532-40. https://doi.org/10.10. 1016/j.clinph.2014.06.034

Sangal RB, Sangal JM. Use of EEG Beta-1 Power and Theta/Beta Ratio Over Broca's Area to confirm Diagnosis of Attention Deficit/Hyperactivity Disorder in Children. Clin EEG Neurosci. 2015; 46(3): 177-82. https://doi.org/10.1177/1550059414527284

Clarke AR, Barry RJ, Dupuy FE, McCarthy R, Selikowitz M, Johnstone SJ. Excess beta activity in the EEG of children with attention-deficit/hyperactivity disorder: a disorder of arousal? Int. J. Psychophysiol. 2013; 89(3): 314-19. https://doi.org/10.1016/j.ijpsycho.2013.04.00

Kamida A, Shimabayashi K, Oguri M, Takamori T, Ueda N, Koyanagi Y, et al. EEG power spectrum analysis in children with ADHD. Yonago Acta Med. 2016; 59(2): 169-73.

R MM, Khaleghi A, Nasrabadi AM, Rafieivand S, Begol M, Zarafshan H. EEG classification of ADHD and normal children using non-linear features and neural network. Biomed Eng Lett. 2016; 6(2): 66-73. https://doi.org/10.1007/s13534-016-0218-2

Saad JF, Kohn MR, Clarke S, Lagopoulos J, Hermens DF. Is the Theta/Beta EEG Marker for ADHD Inherently Flawed? J Atten Disord. 2018; 22(9): 815-26. https://doi.org/10.1177/1087054715578270

Spitzer B, Haegens S. Beyond the Status Quo: A Role for Beta Oscillations in Endogenous Content (Re)Activation. eNeuro. 2017; 4(4). https://doi.org/10.1523/ENEURO.0170-17.2017

Kilavik BE, Zaepffel M, Brovelli A, MacKay WA, Riehle A. The ups and downs of β oscillations in sensorimotor cortex. Exp Neurol. 2013; 245: 15-26. https://doi.org/10.1016/j.expneurol.2012.09.014

Thatcher RW. Software Neuroguide 2.8.1: Applied Neuroscience, Inc; 1998-2020.

García-Monge A, Rodríguez-Navarro H, González-Calvo G, Bores-García D. Brain Activity during Different Throwing Games: EEG Exploratory Study. Int J Environ Res Public Health. 2020; 17(18): 6796. https://doi.org/10.3390/ijerph17186796

Biederman J, Mick E, Faraone SV, Braaten E, Doyle A, Spencer T, et al. Influence of gender on attention deficit hyperactivity disorder in children referred to a psychiatric clinic. Am J Psychiatry. 2002; 159(1): 36-42. https://doi.org/10.1176/appi.ajp.159.1.36

Rueda MR, Fan J, McCandess BD, Halpering JD, Gruber DB, Lercari LP et al. Development attentional networks in childhood. Neuropsychologia. 2004; 42(8): 1029-40. https://doi.org/10.1016/j.neuropsychologia.2003.12.012

Manual Diagnóstico y Estadístico de los Trastornos Mentales DSM-IV-TR. Texto revisado. Cuarta ed. Barcelona: Mason; 2002-2013.

Farré A, Narbona J. Escalas para la evaluación del trastorno por Déficit de Atención con Hiperactividad (EDAH). Séptima ed. Madrid: Tea Ediciones; 2013.

Wechsler D, Flanagan D, Kaufman A. WISC-IV. Escala de Inteligencia de Wechsler para niños - IV: Manual técnico y de interpretación / David Wechsler. Cuarta ed. Madrid: Tea Ediciones; 2005-2019.

Leark R, Dupuy T, Greenberg L, Corman C, Kindschi C. T.O.V.A. Test of Variables of Attention Professional Manual / Clinical Guide. Primera ed.: Universal Attention Disorders, Inc; 2000.

Greenberg LM, Waldman ID. Developmental normative data on the test of variables of attention (T.O.V.A.). J Child Psychol Psychiatry. 1993; 34(6): 1019-30. https://doi.org/10.1111/j.1469-7610.1993.tb01105.x

Statistical Package for the Social Sciences (SPSS) software V.25; 2019.

Machida K, Murias M, Johnson K. Electrophysiological Correlates of Response Time Variability During a Sustained Attention Task. Front. Hum. Neurosci. 2019; 13: 363. https://doi.org/10.3389/fnhum.2019.00363

Zulueta A, Torrano F, López Fernández V, Crespo-Eguílaz N. Tiempo de reacción y variabilidad intraindividual en el tiempo de reacción de niños con trastorno por déficit de atención y/o hiperactividad. Rev Mex de Psicol. 2019; 36(1): 17-29.

Russell VA, Oades RD, Tannock R, Killeen PR, Auerbach JG, et al. Response variability in Attention-Deficit/Hyperactivity Disorder: a neuronal and glial energetics hypothesis. Behav Brain Funct. 2006; 2: 30. https://doi.org/10.1186/1744-9081-2-30

Núñez-Jaramillo L, Herrera-Solís A, Herrera-Morales WV. ADHD: Reviewing the Causes and Evaluating Solutions. J Pers Med. 2021; 11(3): 166. https://doi.org/10.3390/jpm11030166

Badgaiyan RD, Sinha S, Sajjad M, Wack DS. Attenuated Tonic and Enhanced Phasic Release of Dopamine in Attention Deficit Hyperactivity Disorder. PLoS One. 2015; 10(9): e0137326. https://doi.org/10.1371/journal.pone.0137326

Thatcher RW (2010-2020). Symptom Check List and Functional Specialization in the Brain Link Between Structure and Function: Software Neuroguide Copyright ©; 2010-2020.

Steinberg B, Blum K, McLaughlin T, Lubar J, Febo M, Braverman ER, et al. Low-Resolution Electromagnetic Tomography (LORETA) of changed Brain Function Provoked by Pro-Dopamine Regulator (KB220z) in one Adult ADHD case. Open J Clin Med Case Rep. 2016; 2(11): 1121.

Latest developments in live z-score training: Symptom check list, phase reset, and LORETA z-score biofeedback. Journal of Neurotherapy. 2013; 17(1): 69-87. https://doi.org/10.1080.10874208.2013.759032

Hobbs MJ, Clarke AR, Barry RJ, McCarthy R, Selikowitz M. EEG abnormalities in adolescent males with AD/HD. Clin. Neurophysiol. 2007; 118(2): 363-71. https://doi.org/10.1016/j.clinph.2006.10.013

Chiang CT, Ouyang CS, Yang RC, Wu RC, Lin LC. Increased Temporal Lobe Beta Activity in Boys with Attention-Deficit Hyperactivity Disorder by LORETA. Analysis. Front. Behav. Neurosci. 2020; 14: 85. https://doi.org/10.3389/fnbeh.2020.00085

Lindsay GW. Attention in Psychology, Neuroscience, and Machine Learning. Front. Comput. Neurosci. 2020; 14: 29. https://doi.org/10.3389/fncom.2020.00029

Barry RJ, De Blasio FM, Fogarty JS, Clarke AR. Natural alpha frequency components in resting EEG and their relation to arousal. Clin Neurophysiol. 2020; 131(1): 205-12. https://doi.org/10.1016/j.clinph.2019.10.018

Neuper C, Pfurtscheller G. Event-related dynamics of cortical rhythms: frequency-specific features and functional correlates. Int J Psychophysiol. 2001; 43(1): 41-58. https://doi.org/10.1016/S0167-8760

Fu D, ,Weber C, Yang G, Kerzel M, Nan W, Barros P, et al. What Can Computational Models Learn from Human Selective Attention? A Review from an Audiovisual Unimodal and Crossmodal Perspective. Front Integr Neurosci. 2020; 14: 10. https://doi.org/10.3389/fnint.2020.00010

Giertuga K, Zakrzewska MZ, Bielecki M, Racicka-Pawlukiewicz E, Kossut M, Cybulska-Klosowicz A. Age-Related Changes in Resting-State EEG Activity in Attention Deficit/Hyperactivity Disorder: A Cross-Sectional Study. Front Hum Neurosci. 2017; 11: 285. https://doi.org/10.3389%2Ffnhum.2017.00285