The primary focus of this project is to quantify the dynamic dimensionality of the neural code along its trajectory. This involves developing an innovative adaptive encoder that can accurately capture and adapt to the changing dimensionality of neural activity in a specific brain area over time. The encoder, designed using advanced machine learning or deep learning techniques, will dynamically adjust its parameters to mirror the variability in the neural activity’s dimensionality. This approach will provide a more accurate and dynamic analysis of neural activity, potentially leading to significant breakthroughs in our understanding of brain function and the development of neuroprosthetics. The project represents an exciting opportunity to explore a new frontier in neuroscience and develop a tool that can significantly enhance our understanding of the brain. Please, have a look here for more context about potential research projects.
