Signaling Pathways Involved in Striatal Synaptic Plasticity are Sensitive to Temporal Pattern and Exhibit Spatial Specificity

The basal ganglia is a brain region critically involved in reinforcement learning and motor control. Synaptic plasticity in the striatum of the basal ganglia is a cellular mechanism implicated in learning and neuronal information processing. Therefore, understanding how different spatio-temporal patterns of synaptic input select for different types of plasticity is key to understanding learning mechanisms. In striatal medium spiny projection neurons (MSPN), both long term potentiation (LTP) and long term depression (LTD) require an elevation in intracellular calcium concentration; however, it is unknown how the post-synaptic neuron discriminates between different patterns of calcium influx. Using computer modeling, we investigate the hypothesis that temporal pattern of stimulation can select for either endocannabinoid production (for LTD) or protein kinase C (PKC) activation (for LTP) in striatal MSPNs. We implement a stochastic model of the post-synaptic signaling pathways in a dendrite with one or more diffusionally coupled spines. The model is validated by comparison to experiments measuring endocannabinoid-dependent depolarization induced suppression of inhibition. Using the validated model, simulations demonstrate that theta burst stimulation, which produces LTP, increases the activation of PKC as compared to 20 Hz stimulation, which produces LTD. The model prediction that PKC activation is required for theta burst LTP is confirmed experimentally. Using the ratio of PKC to endocannabinoid production as an index of plasticity direction, model simulations demonstrate that LTP exhibits spine level spatial specificity, whereas LTD is more diffuse. These results suggest that spatio-temporal control of striatal information processing employs these Gq coupled pathways. Author Summary: Change in the strength of connections between brain cells in the basal ganglia is a mechanism implicated in learning and information processing. Learning to associate a sensory input or motor action with reward likely causes certain patterns of input to strengthen connections, a phenomenon known as long term potentiation (LTP), and other patterns of input to weaken those connections, known as long term depression (LTD). Both LTP and LTD require elevations in calcium, and a critical question is whether different patterns of input cause different patterns of calcium dynamics or activate different downstream molecules. To address this issue we develop a spatial, computational model of the signaling pathways in a dendrite with multiple spines. Model simulations show that stimulation patterns that produce LTP experimentally activate more protein kinase C than stimulation patterns that produce LTD. We experimentally confirm the model prediction that protein kinase C is required for LTP. The model also predicts that protein kinase C exhibits spatial specificity while endocanabinoids do not.