The model illustrates how the plastic integration of spatially stable grid-cell inputs could contribute to hippocampal place fields' generation and dynamic character. Theoretically, the grid-to-place transformation is possible if a place cell can respond selectively to a combination of suitably aligned grids. A synaptic plasticity rule whereby postsynaptic activation gates synaptic change while presynaptic activation determines its direction can accomplish this task during rat foraging behavior. The synaptic competition can outlast the formation of place fields, contributing to their spatial reorganization over time when the model is run in larger environments and the topographical/modular organization of grid inputs is considered. Co-simulated cells that differ only by their randomly assigned grid inputs display different degrees and kinds of spatial reorganization - ranging from place-field remapping to more subtle in-field changes or lapses in firing. The model predicts a greater number of place fields and propensity for remapping in place cells recorded from more septal regions of the hippocampus and/or in larger environments, motivating future experimental standardization across studies and animal models.
Model Type: Spiking neural network
Region(s) or Organism(s): Hippocampus
Cell Type(s): Abstract integrate-and-fire neuron
Model Concept(s): Synaptic Plasticity; Place cell/field; Hebbian plasticity; Grid cell; Spatial Navigation
Simulation Environment: C or C++ program
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