Population Encoding

Population encoding investigates how information is represented by the collective activity of groups of neurons, aiming to understand and replicate this process in artificial systems. Current research focuses on developing and analyzing models, including spiking neural networks with multi-compartment neurons and deep neural networks, to better understand how population codes handle complex inputs like speech and images, and to optimize their performance in applications such as cochlear implants and neural architecture search. These efforts are crucial for advancing our understanding of neural computation and for designing more efficient and biologically plausible artificial intelligence systems, as well as improving brain-computer interfaces.