Project Summary Schizophrenia is a psychiatric disorder that affects approximately 24 million people worldwide and can lead to emotional distress, disability, and reduced lifespan. Cognitive dysfunction is the best predictor of patient outcome in schizophrenia, yet current pharmacological treatments often fail to treat cognitive symptoms such as working memory deficits. In addition, it is not yet understood how certain biological abnormalities associated with schizophrenia – for example, decreased cortical expression of N-methyl-D-aspartate (NMDA) receptors – lead to changes in brain circuit function, especially when these abnormalities progress over the course of the lifespan and may be affected by in vivo compensatory mechanisms in the brain. My proposed research seeks to investigate the effects of chronic NMDA receptor loss upon synaptic function and architecture in the prefrontal cortex, and its potential implications for neural network activity and working memory deficits. Specifically, this computational psychiatry project will focus on examining functional and structural abnormalities at excitatory-to- excitatory synapses, which produce the reverberant neural activity that allows information to be retained in working memory and are particularly vulnerable to disconnection in schizophrenia. I will measure functional changes in excitatory-to-excitatory synaptic strength using ex vivo slice electrophysiology in prefrontal cortex pyramidal neurons, and I will examine structural changes in dendritic spine morphology and density in the same neurons using confocal imaging. I will then leverage insights gained from these electrophysiology and imaging experiments to build and test predictions regarding stability and synchrony of brain activity in a spiking network model.