About 290 million electrical action potentials (spikes) occur every second in the human brain, facilitating the propagation of signals among cells in the nervous system (neurons) and driving most of our daily operations; alongside, plasticity in the connections among neurons is largely responsible for our ability to learn and adapt. Deciphering brain function requires access to the neural network’s state and connectivity on a time scale relevant to behavior and learning. No modern neuroscience technique can achieve this goal; consequently, fundamental scientific questions such as connectivity and network dynamics in healthy and diseased brains are frustratingly underexplored. Filling this gap requires new methods. Here we propose to develop a framework to simultaneously monitor and perturb populations of individual neurons with millisecond precision. By leveraging this technology, we will first establish a protocol to track connectivity patterns in the living brain across time, and then demonstrate how network dynamics map to specific behaviors.