Resumen
El trastorno del espectro autista (TEA) representa un desafío para la caracterización neurofisiológica debido a su heterogeneidad clínica. En este contexto, la electroencefalografía en reposo (rsEEG) ha emergido como una herramienta accesible para explorar patrones funcionales en población infantil. El objetivo de esta revisión fue sintetizar la evidencia disponible sobre hallazgos del rsEEG en niños y adolescentes con TEA y analizar los enfoques metodológicos empleados en la literatura reciente. Para ello, se realizó una búsqueda en la base de datos PubMed, restringida a estudios en humanos, con texto completo disponible y centrada en población infantil. Se identificaron 38 investigaciones empíricas que cumplieron con esos criterios. Además, se utilizó VOSviewer para efectuar un análisis de co-ocurrencias semánticas en títulos y resúmenes para agrupar la evidencia en cuatro núcleos temáticos: desarrollo neurofuncional, alteraciones en ritmos cerebrales, dinámica de conectividad funcional y algoritmos computacionales aplicados al diagnóstico. Los resultados muestran trayectorias atípicas en la maduración de la actividad oscilatoria y de la conectividad cerebral, disminución de la complejidad de las señales, reorganización funcional a nivel regional y disociaciones entre integración global e inestabilidad local. Asimismo, se documentan avances en el uso de modelos de aprendizaje profundo como redes convolucionales de memoria a corto y largo plazo y de grafos que han alcanzado alta precisión diagnóstica con rsEEG. En conclusión, la evidencia revisada consolida al rsEEG como herramienta prometedora para el desarrollo de biomarcadores en TEA, subrayando que su integración con inteligencia artificial optimiza la caracterización de la arquitectura cerebral atípica en el autismo.
Citas
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