Associative learning is crucial for adapting to environmental changes. Interactions among neuronal populations involving the dorso-medial prefrontal cortex (dmPFC) in rodents are proposed to regulate associative memory. However, how these neuronal populations store and process information about the association remains unclear. Here we developed a pipeline for longitudinal two-photon imaging and computational dissection of neural population activities in male mouse dmPFC during fear-conditioning procedures, enabling us to detect learning-dependent changes in the dmPFC network topology. After confirming that the dmPFC contributes to the expression of the conditioned responses (CR) by chemogenetic silencing, we analyzed neural population activities by regularized regression methods and graphical modeling. We found that fear conditioning drove dmPFC reorganization to generate a neuronal ensemble encoding CR, which was characterized by enhanced internal coactivity and functional connectivity. Importantly, neurons strongly responding to unconditioned stimuli during fear conditioning subsequently became hubs of this novel network and revealed enhanced association with conditioned stimuli (CS), which may work as an information-processing neural network implementing CS-triggered CR (i.e., a neural network for the CS-to-CR transformation). Altogether, we demonstrate learning-dependent dynamic modulation of population coding structured on the activity-dependent formation of the hub network within the dmPFC.