Activity-dependent organization of prefrontal hub-networks for associative learning and signal transformation

Associative learning is crucial for adapting to environmental changes. The encoding of associative learning involves the dorso-medial prefrontal cortex (dmPFC), and is underpinned by interactions within the resident neuronal population. However, the nature of this population coding is poorly understood. Here we developed a pipeline for computational dissection and longitudinal two-photon imaging of neural population activities in the mouse dmPFC during fear-conditioning procedures, enabling us to detect learning-dependent changes in the dmPFC topology. Through regularized regression methods and graphical modeling, we found fear conditioning organized neuronal ensembles encoding conditioned responses (CR), with enhancing their coactivity, functional connectivity, and association with conditioned stimuli (CS). This suggests that fear conditioning drives dmPFC reorganization to generate novel associative circuits for CS-to-CR transformation. Importantly, neurons strongly responding to unconditioned stimuli (US) during conditioning anterogradely became a hub of the CR ensemble. Altogether, we demonstrate learning-dependent dynamic modulation of population coding structured on an activity-dependent hub-network formation within the dmPFC.