medigraphic.com
Academia Mexicana de Neurología, A.C.

2017, Número 4

<< Anterior Siguiente >>

Rev Mex Neuroci 2017; 18 (4)


Trastorno del Espectro Autista: un reto para las neurociencias

Machado C, Rodríguez R, Estévez M, Leisman G, Chinchilla M; Portela L

Idioma: Español
Referencias bibliográficas: 41
Paginas: 30-45
Archivo PDF: 485.30 Kb.


RESUMEN

Introducción: Hoy en día se considera que el Trastorno del Espectro Autista (TEA) es un modelo para el estudio de la conectividad cerebral.
Objetivo: Para entender mejor la naturaleza de las conectividades cerebrales en los autistas electrofisiológicamente.
Métodos: La conectividad se subdivide en Conectividad Estructural o Anatómica (CA) y la Conectividad Funcional (CF). Se estudió un grupo de 21 autistas diestros, 13 hombres y 8, de 3 a 9 años de edad. Un grupo control, pareados en edad y sexo con los pacientes se incluyó en el estudio.
Resultados: Se observó una conexión aumentada en estructuras localizas cercanamente, lo que indica una sobre-conectividad (overconnectivity) local en el niño autista, pero se demostró un menor valor de la densidad, probabilidad, y fuerza de las conexiones (subconnectivity) para las redes de media y larga distancia. El “grand average” de la Anisotropía Fraccional (AF) medida en los tractos Fascículo Longitudinal Superior (FLS), Fascículo Longitudinal Inferior (FLI), y Arquatus (Arq), demostró que existe una AF significativamente mayor en el hemisferio cerebral derecho en comparación con el izquierdo. Se encontró una concentración significativamente menor del NAA/Cr en el hemisferio izquierdo, y al calcular la correlación entre la FA y la concentración del NAA/Cr, se demostró una correlación significativa positiva para el hemisferio izquierdo, mientras que en el hemisferio derecho la correlación significativa negativa. Los autistas mostraron menores valores de coherencia en el hemisferio derecho en la condición video sin audio.
Conclusiones: Se concluye que en la fisiopatología del TEA, puede coincidir un exceso de conectividad local, con un déficit de conectividad a media y larga distancia, quizás como consecuencia de alteraciones en la eliminación o formación de sinapsis.


REFERENCIAS (EN ESTE ARTÍCULO)

  1. Sheikhani A, Behnam H, Mohammadi MR, et al. Detection of abnormalities for diagnosing of children with autism disorders using of quantitative electroencephalography analysis. J Med Syst. 2012; 36.

  2. Naranjo-Álvarez RJ. El autismo.Generalidades, neurobiología, diagnóstico y tratamiento. Rev. Hosp. Psiquiátrico de la Habana. 2011; 8: 1-18.

  3. Volkmar FR, McPartland JC. From Kanner to DSM-5: autism as an evolving diagnostic concept. Annu Rev Clin Psychol. 2014; 10: 193-212.

  4. Lyons V, Fitzgerald, M. Asperger (1906-1980) and Kanner (1894-1981), the two pioneers of autism. J Autism Dev Disord. 2007; 37:2022-2023.

  5. Machado C, Estevez M, Leisman G, et al. qEEG Spectral and Coherence Assessment of Autistic Children in Three Different Experimental Conditions. J Autism Dev Disord. 2015; 45: 406-424.

  6. Levy F. The autism spectrum disorder ‘epidemic’: need for biopsychosocial formulation. Aust N Z J Psychiatry. 2014; 48: 91-92.

  7. Wingate M, Kirby RS, Pettygrove S, Cunniff C, Schulz E, Ghosh T, Robinson C, Lee LC, Landa R, Constantino J, Fitzgerald R. Prevalence of autism spectrum disorder among children aged 8 yearsautism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveillance Summaries. 2014; 63(2).

  8. Kulage KM, Smaldone AM, Cohn EG. How will DSM-5 affect autism diagnosis? A systematic literature review and meta-analysis. J Autism Dev Disord. 2014; 44: 1918-1932.

  9. Baron-Cohen S Belmonte MK. Autism: a window onto the development of the social and the analytic brain. Annu Rev Neurosci. 2005; 28:109-126.

  10. Baron-Cohen S, Knickmeyer RC, Belmonte MK. Sex differences in the brain: implications for explaining autism. Science. 2005; 310: 819-823.

  11. Best CS, Moffat VJ, Power MJ, et al. The boundaries of the cognitive phenotype of autism: theory of mind, central coherence and ambiguous figure perception in young people with autistic traits. J Autism Dev Disord. 2008; 38: 840-847.

  12. Hill, EL, Frith, U. Understanding autism: insights from mind and brain. Philos Trans R Soc Lond B Biol Sci. 2003; 358: 281-289.

  13. Tye C, Bolton P. Neural connectivity abnormalities in autism: insights from the Tuberous Sclerosis model. BMC Med. 2013; 11: 55.

  14. Peters JM, Taquet M, Vega C, et al. Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity. BMC Med. 2013; 11: 54.

  15. Charman T, Pickles A, Simonoff E, et al. IQ in children with autism spectrum disorders: data from the Special Needs and Autism Project (SNAP). Psychol Med. 2011; 41: 619-627.

  16. Golomb BA, Erickson LC, Scott-Van Zeeland AA, et al. Assessing bioenergetic compromise in autism spectrum disorder with 31P magnetic resonance spectroscopy: preliminary report. J Child Neurol. 2014; 29: 187-193.

  17. Iturria-Medina Y, Sotero RC, Toussaint PJ, et al. Epidemic spreading model to characterize misfolded proteins propagation in aging and associated neurodegenerative disorders. PLoS Comput Biol. 2014; 10: e1003956.

  18. Iturria-Medina Y. Anatomical brain networks on the prediction of abnormal brain states. Brain Connect. 2013; 3: 1-21.

  19. Coben R, Clarke AR, Hudspeth W, et al. EEG power and coherence in autistic spectrum disorder. Clin Neurophysiol. 2008; 119.

  20. Hutsler JJ, Casanova MF. Cortical Construction in Autism Spectrum Disorder: Columns, Connectivity and the Subplate. Neuropathol Appl Neurobiol. 2015. doi: 10.1111/nan.12227.

  21. Chien, HY Lin HY, Lai MC, et al. Hyperconnectivity of the Right Posterior Temporo-parietal Junction Predicts Social Difficulties in Boys with Autism Spectrum Disorder. Autism Res. 2015.doi: 10.1002/ aur.1457.

  22. Palau-Baduell, M, Salvado-Salvado, B, Clofent-Torrento, M, et al. [Autism and neural connectivity]. Rev Neurol. 2012; 54 Suppl 1: S31-S39.

  23. Horwitz B, Rumsey JM, Grady CL, et al. The cerebral metabolic landscape in autism. Intercorrelations of regional glucose utilization. Arch Neurol. 1988; 45: 749-755.

  24. Just MA, Cherkassky VL, Keller TA, et al. Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity. Brain. 2004; 127: 1811- 1821.

  25. Hughes JR. Autism: the first firm finding = underconnectivity? Epilepsy Behav. 2007; 11: 20-4.

  26. Rudie JD, Dapretto M. Convergent evidence of brain overconnectivity in children with autism? Cell Rep. 2013; 5: 565-66.

  27. Belmonte, MK, Gomot, M, and Baron-Cohen, S. Visual attention in autism families: ‘unaffected’ sibs share atypical frontal activation. J Child Psychol Psychiatry. 2010; 51.

  28. Just MA, Keller TA, Malave VL, et al. Autism as a neural systems disorder: a theory of frontalposterior underconnectivity. Neurosci Biobehav Rev. 2012; 36:1292-1313.

  29. Yamada, T, Ohta, H, Watanabe, H, et al. Functional alterations in neural substrates of geometric reasoning in adults with high-functioning autism. PLoS One. 2012; 7.

  30. Ohta H, Yamada T, Watanabe H, et al. An fMRI study of reduced perceptual load-dependent modulation of task-irrelevant activity in adults with autism spectrum conditions. Neuroimage. 2012; 61:1176-1187.

  31. Chang EF, Raygor KP, Berger MS. Contemporary model of language organization: an overview for neurosurgeons. J Neurosurg. 2015; 122: 250-261.

  32. Hellendoorn A, Wijnroks L, van Daalen E, Dietz C, Buitelaar JK, Leseman P. Motor functioning, exploration, visuospatial cognition and language development in preschool children with autism. Res Develop Disabil. 2015; 39: 32-42.

  33. Kubas B, Kulak W, Sobaniec W, et al. Metabolite alterations in autistic children: a 1H MR spectroscopy study. Adv Med Sci. 2012; 57: 152-156.

  34. Cauda F, Costa T, Palermo S, et al. Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study. Hum Brain Mapp. 2014; 35: 2073- 2098.

  35. Haar S, Berman S, Behrmann M, et al. Anatomical Abnormalities in Autism? Cereb Cortex. 2014, pii: bhu242

  36. Courchesne E, Pierce K. Why the frontal cortex in autism might be talking only to itself: local overconnectivity but long-distance disconnection. Curr Opin Neurobiol. 2005; 15: 225-230.

  37. Buxhoeveden DP, Semendeferi K, Buckwalter J, et al. Reduced minicolumns in the frontal cortex of patients with autism. Neuropathol Appl Neurobiol. 2006; 32: 483-491.

  38. Hadjikhani N, Joseph RM, Snyder J, et al. Anatomical differences in the mirror neuron system and social cognition network in autism. Cereb Cortex 2006; 16: 1276-1282.

  39. Allen ML. Brief report: decoding representations: how children with autism understand drawings. J Autism Dev Disord. 2009; 39: 539-543.

  40. Russo N, Foxe JJ, Brandwein AB, et al. Multisensory processing in children with autism: high-density electrical mapping of auditory-somatosensory integration. Autism Res. 2010; 3: 253-267.

  41. Foss-Feig JH, Kwakye LD, Cascio CJ, et al. An extended multisensory temporal binding window in autism spectrum disorders. Exp Brain Res. 2010; 203: 381-389.




2020     |     www.medigraphic.com