Neurobiological Representation

Neurobiological representation research aims to understand how information is encoded and processed in the brain, focusing on how neural activity patterns represent sensory inputs, internal states, and cognitive processes. Current research leverages machine learning, particularly on multimodal neuroimaging data and convolutional neural networks (CNNs), to analyze and model these representations, often comparing them to artificial neural network architectures. This work seeks to improve the robustness and generalizability of artificial intelligence by drawing inspiration from biological systems, and to better understand brain function in health and disease, potentially leading to improved diagnostics and treatments for neurological and psychiatric disorders.