Neural Assembly

Neural assemblies represent groups of neurons that fire together, encoding information through their coordinated activity. Current research focuses on understanding how these assemblies form, interact to process temporal sequences, and contribute to complex cognitive functions, employing models ranging from graph neural networks analyzing molecular interactions to biologically-inspired networks simulating associative memory and learning. This work aims to bridge the gap between theoretical models of neural computation and experimental observations, with implications for advancing our understanding of brain function and informing the design of more efficient and robust artificial intelligence systems. The development of improved algorithms for representing and manipulating neural assemblies promises to enhance applications in areas such as drug discovery and pattern recognition.