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Updated: Jan 31, 2026
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Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
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Neurosynth Compose: Una plataforma web para meta-análisis de neuroimagen flexibles y reproducibles
James D Kent1, Nicholas Lee1, Angela R Laird2
1Department of Psychology, University of Texas at Austin, Austin, TX, United States.
Imaging neuroscience (Cambridge, Mass.)
|January 30, 2026
Resumen
Neurosynth Compose ofrece una plataforma optimizada para crear meta-análisis de neuroimagen reproducibles. Esta herramienta mejora la síntesis de datos al integrar la recopilación automatizada con la curación experta, fomentando una base de conocimiento colaborativa para la investigación en neuroimagen funcional.
Área de la Ciencia:
- Neurociencia
- Ciencia Cognitiva
- Ciencia de Datos
Sus antecedentes:
- El crecimiento exponencial de los estudios de neuroimagen funcional complica la síntesis de los hallazgos de la investigación.
- Las plataformas automatizadas existentes tienen limitaciones para abordar preguntas de investigación complejas.
- Los meta-análisis manuales consumen mucho tiempo, carecen de reproducibilidad y corren el riesgo de pérdida de datos.
Objetivo del estudio:
- Presentar Neurosynth Compose, una plataforma web para simplificar la creación de meta-análisis de neuroimagen transparentes y reproducibles.
- Abordar las limitaciones de los métodos actuales de meta-análisis en neuroimagen funcional.
Principales métodos:
- Interfaz fácil de usar para la curación y anotación de estudios siguiendo las pautas PRISMA.
- Integración con la base de datos NeuroStore (más de 30.000 estudios) para obtener coordenadas de activación pre-extraídas.
- Utiliza el estándar de datos de meta-análisis de neuroimagen (NiMADS) y la biblioteca de Python NiMARE para el análisis.
- Soporta la ejecución local o en la nube con paquetes portátiles.
Principales resultados:
- Agiliza la creación de meta-análisis de neuroimagen de alta calidad.
- Facilita la revisión interactiva y el intercambio rápido de resultados.
- Fomenta una base de conocimiento de crowdsourcing a través de anotaciones compartidas y meta-análisis.
- Permite el desarrollo de meta-análisis 'vivos' en continua actualización.
Conclusiones:
- Neurosynth Compose mejora la eficiencia, la transparencia y la reproducibilidad de los meta-análisis de neuroimagen.
- La plataforma fomenta la colaboración y la creación de una base de conocimiento dinámica y en evolución en el campo.
- Facilita la síntesis de datos de neuroimagen funcional para avanzar en la investigación.
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