Synaptic Connectivity

Synaptic connectivity research focuses on understanding how connections between neurons shape brain function and behavior, aiming to decipher the complex interplay between static network structure and dynamic activity patterns. Current research emphasizes developing computational models, including spiking neural networks and recurrent neural networks with diverse connectivity patterns, to analyze multi-region dynamics and explore biologically plausible learning rules like variations of Hebbian learning and backpropagation. These efforts are crucial for advancing our understanding of neural computation and informing the design of energy-efficient neuromorphic computing architectures for applications ranging from robotics to artificial intelligence.