Goal location beta oscillations and sharp wave ripples are complementary markers of learning-related changes in...

The hippocampus and neocortex are thought to undergo reorganization to incorporate new information during learning. How can we identify network states that indicate learning is occurring? In the hippocampus, one network signature with these properties is the sharp wave ripple (SWR), which occurs more frequently during initial learning. However, it remains unclear which neural signatures track changes in neocortical networks during learning. We therefore recorded local field potentials simultaneously from dorsal hippocampus (CA1) and prefrontal cortex (PFC) as male rats learned spatial navigation tasks. After animals reached goal locations, we found beta frequency (∼20Hz) oscillations in PFC that increased in power with improvements in performance across days of training. In contrast, the rate and size of hippocampal sharp wave ripples decreased over the same period. Further, goal-entry beta was correlated with reward likelihood in PFC but not in CA1. Our results suggest that neocortical beta oscillations develop gradually as learning occurs, which stands in contrast to the reduction in hippocampal SWRs as the task becomes familiar. We hypothesize that PFC beta oscillations and hippocampal SWRs are complementary markers of experience-dependent change in hippocampal-neocortical networks during learning.Significance statement Hippocampal and neocortical circuits are crucial for learning. The network states associated with the learning process remain challenging to identify. It remains unclear how to distinguish states associated with active reorganization during learning versus states of stability after learning has taken place. We report that properties of neocortical beta oscillations and hippocampal sharp wave ripples show an inverse relationship across training. Our results support the hypothesis that these network signatures are complementary learning- and experience-related markers in hippocampal-neocortical networks.