Neural Circuit

Neural circuits, the intricate networks of interconnected neurons, are the fundamental units of brain computation, and understanding their function is a central goal of neuroscience. Current research focuses on developing and analyzing biologically plausible models, including recurrent neural networks (RNNs) and spiking neural networks (SNNs), often incorporating principles like divisive normalization and predictive coding, to better understand information processing and learning within these circuits. These efforts leverage advanced techniques such as dynamical systems theory, deep learning, and causal inference to analyze both experimental data and model simulations, aiming to bridge the gap between biological observations and computational understanding. This research has implications for developing more efficient and interpretable artificial intelligence, as well as for understanding and treating neurological disorders.