Research Paper: NeuroIA y Repositorios Científicos. Abstract/Summary: ARTICLE NeuroAI Repositories: Cataloguing Biological and Artificial Neural Networks, Deep Learning Architectures, and Brain-Computer Interface Resources Juan Moisés de la Serna 1,* 1 , Logroño, Spain; juanmoises.delaserna@.net * Correspondence: juanmoises.delaserna@.net; ORCID: 0000-0002-8401-8018 Abstract: The convergence of neuroscience and artificial intelligence has generated an expanding ecosystem of open-access repositories, datasets, and computational tools that bridge biological neural systems and machine learning architectures. This study presents a systematic catalogue of 127 NeuroAI repositories sourced from Mendeley Data, spanning five major categories: biological neural networks, artificial neural networks, deep learning architectures inspired by neuroscience, computational neuroscience tools, and brain-computer interface (BCI) datasets. Each repository is indexed with metadata including primary research focus, data modality, accessibility level, associated publication venue, and implementation platform. The catalogue reveals that repositories cluster around three dominant research themes: (1) connectomics and neural