This computational infrastructure is designed for the advanced processing, integration, and analysis of large-scale, multimodal neurological datasets utilizing high-performance computing (HPC) architectures. To efficiently manage the volume and complexity of high-density neurophysiological data, we develop and implement state-of-the-art artificial intelligence algorithms rooted in deep learning and machine learning techniques. Through these sophisticated data-driven approaches, complex brain networks and dynamic connectomes are mathematically modeled.