Neural Recording

Neural recording focuses on acquiring and interpreting electrical and magnetic signals from the brain to understand neural activity and behavior. Current research emphasizes developing advanced decoding algorithms, often employing deep learning architectures like recurrent neural networks (RNNs), transformers, and spiking neural networks (SNNs), to extract meaningful information from high-dimensional, noisy data. These efforts are improving the accuracy and efficiency of brain-computer interfaces (BCIs) and providing new insights into brain function, with applications ranging from restoring communication in patients with paralysis to advancing our understanding of cognitive processes. The field is also seeing increased use of self-supervised and unsupervised learning methods to reduce reliance on large labeled datasets.