Place Cells (PCs), are neurons that exhibit localized firing when an animal enters specific areas within an environment. Despite extensive experimental study revealing their link to cognitive functions, the precise cellular mechanisms underlying the transformation of a hippocampal neuron into a Place Cell remain incompletely understood. In our research, we employed a detailed computational model of a CA1 pyramidal neuron, considering both its morphology and biophysics. We aimed to elucidate how, and under what circumstances, such a neuron could encode a specific location based on the self-organization of its synaptic inputs in response to external signals targeting various dendritic layers. Our findings demonstrate that our model aligns with experimental observations, showing the stability of PCs within the same spatial context across different trajectories, environmental rotations, and place field remapping to accommodate changes in the surroundings. Our model accurately captures both the biophysical and morphological aspects of PCs formation, offering a tool for investigating cognitive functions and dysfunctions at the cellular level within physiologically accurate microcircuits and large-scale model networks.PC's formation and operation (Fig.5 from Ref.1).(a) Typical mouse trajectory; The red dots indicate the positions where the neuron generated an action potential;(b) Synaptic weights evolution (top); Somatic membrane potential during an entire 10 min simulation (middle); the inset (bottom plot) shows 10s of somatic potential during the activation of the plateau potential.References1.Mazzara, C. & Migliore, M. A realistic computational model for the formation of a Place Cell. Scientific Reports 2023 13:1 13, 1–11 (2023).