Dendritic hotspots support switching between competing rules without expanding the cortical engram
Adaptive behavior requires updating responses when contingencies change while preserving prior associations and the capacity to learn a new. How this trade-off is resolved remains unknown. Here, we combined in vivo imaging of apical tuft spines in the secondary motor cortex (M2) with biologically constrained network modeling in mice performing a cross-modal rule-switch task. M2 inactivation impaired rule-switching but not learning or maintenance, identifying it as a conflict resolution substrate. Adaptation was accompanied by elevated spine turnover concentrated within stable dendritic hotspots, in which the formation, elimination and clustering of new spines were coupled and pre-existing spines were lost early. A network model reproduces these dynamics and predicts that dendritic hotspots are critical for resource-efficient adaptation. Within these reusable domains, spines encoding the prior rule are replaced by newly-relevant ones via sharing of plasticity-related resources. Preventing reuse increases both the plasticity and the engram size requirements to encode the two rules. We propose that dendritic hotspots provide a mechanistic substrate for efficient adaptive learning.