Neural Activity

Neural activity research focuses on understanding how information is processed and represented by the intricate patterns of electrical signals in the brain. Current investigations employ diverse computational models, including spiking neural networks, quantum generative models, and deep learning architectures like transformers and convolutional neural networks, to analyze neural data from various recording modalities (EEG, fMRI, etc.) and decode its relationship to behavior and cognition. These efforts aim to improve our understanding of brain function, leading to advancements in artificial intelligence, brain-computer interfaces, and the treatment of neurological disorders. The development of more sophisticated analytical tools and the integration of large-scale datasets are key trends driving progress in this field.