Information is stored in the brain through the formation of neural networks that encode memories. New networks are formed when the strength of synapses connecting groups of neurons increases. To achieve accurate and efficient storage of information in the brain, synaptic plasticity in the cortex and hippocampus is delicately regulated by the patterns of activity at each synapse. Ca2+ influx through NMDA-type glutamate receptors triggers the biochemical processes that lead to either long-term potentiation (LTP) of the strength of the synapse, or long-term depression (LTD). We still do not understand how a small change in the rate and extent of flux of Ca2+ into the spine can bring about a large change in the nature of the alteration of the structure of the spine and the strength of the synapse. Understanding the molecular processes that govern synaptic strength is important for our understanding of brain function as a whole; however, it is especially important in the context of mental illness. Mutation of proteins that control synaptic plasticity, or that tune the dynamics of biochemistry in the spine by acting as scaffolds, produces increased risk for the development of mental illnesses such as schizophrenia, autism, and bipolar disease, and for certain forms of mental retardation. I will discuss how we are applying computational methods and computer modeling to aid our understanding of the dynamics of enzyme regulation by Ca2+ in the spine. We use a well-established agent-based, stochastic modeling program called MCell. The nature of signaling machinery inside the spine requires “agent-based” modeling. The program MCell and the open-source model-building tool Blender, provide a powerful system for constructing and visualizing such models. I will present early results from our modeling efforts in collaboration with Tom Bartol of the Sejnowski laboratory at the Salk Institute, and Kristen Harris and Chandrajit Bajaj at University of Texas, Austin.