Neural Simulations and Brain-Computer Interfaces; Algorithmic Challenges and Future Perspectives

This document presents a comprehensive state-of-the-art review on the convergence between computational neuroscience and artificial intelligence, focusing on neural simulations and brain-computer interfaces (BCIs). The thesis explores their theoretical foundations, current applications, ethical challenges, and future research directions. Special emphasis is placed on algorithmic challenges, particularly the role of machine learning in improving BCIs. This work aims to contribute to the understanding of the interdisciplinary approach between neuroscience and AI for the development of more efficient and ethical neurotechnologies.