How do we learn about experiences while being removed from the experience itself? One solution involves offline learning via reactivations. Sensory reactivation involves the recurrence of a pattern of neural activity during sleep or quiet waking that previously occurred during a sensory experience. Historically, reactivations have been studied in the hippocampus. However, whether reactivations in sensory cortex depend on local activation of neurons during prior experience is not well understood. We hypothesize that such reactivations in sensory association cortex could be important for learning. To study reactivations in mouse visual cortex, we used a simple paradigm and presented two different 2-s visual cues, each followed by a 60-s inter-trial-interval to assess reactivations. We imaged calcium activity simultaneously in thousands of layer 2/3 excitatory neurons in lateral visual association cortex using jGCaMP7s. Our preliminary studies suggest that offline cue reactivations decrease across time within individual inter-trial intervals, and within each two-hour long session. Strikingly, the content of cue reactivations were 2-3 times more likely to reflect the most recently presented cue. The network responses to the two cues gradually became more distinct across trials, which correlated with the time-varying rates of cue reactivations. To determine whether activity in lateral visual association cortex is necessary to produce biased cue reactivations, we silenced cue-evoked responses unilaterally in lateral visual cortex by activating PV+ interneurons with Chrimson while concurrently imaging calcium activity. We found that both the rate of cue reactivations and the bias in reactivations to the most recent cue dramatically decreased, suggesting that lateral visual association cortex is necessary for generating the post-cue enhancement in cue reactivation rate. These results provide evidence of pronounced and widespread reactivations in visual association cortex during offline periods between cue presentations. We suggest that these reactivations provide a unique means for distributed sensory and associative learning.