Neural Signal

Neural signal research focuses on understanding and utilizing the information encoded in brain activity, primarily aiming to decode neural representations of sensory inputs, motor commands, and cognitive states. Current research heavily employs deep learning architectures, including convolutional and recurrent neural networks, along with novel approaches like spiking neural networks and generative models, to analyze diverse neural signal modalities (EEG, fMRI, etc.) and improve decoding accuracy and robustness. These advancements have significant implications for brain-computer interfaces, neuroprosthetics, and the development of more interpretable AI systems by enhancing our understanding of brain function and enabling more effective interaction between brains and machines.