The hippocampus and neocortex interact to produce adaptive behaviors and retrieve memories. Hippocampal place cell representations of spatial context are important for both of these functions and have been a useful tool for investigating neural networks dynamics (O’Keefe & Dostrovsky, 1971; O’Keefe & Nadel, 1978; Wilson & McNaughton, 1993). Recently, cells from across the neocortex have also been found to activate in position-correlated sequences (PCS) as animals traverse spatial contexts (Esteves et al., 2020; Mao, Kandler, Mcnaughton, & Bonin, 2017; Saleem, Diamanti, Fournier, Harris, & Carandini, 2018). Like hippocampal cells, these position-correlated cortical cells activate when the animal enters specific locations, or fields, in the environment. Several lines of evidence relate PCS to hippocampal place cell sequences, suggesting they are a direct cortical manifestation of hippocampal influence. Little is known, however, as to how cortical PCS change, i.e. remap, as the animal’s experience changes. Here we used PCS as a tool to assay information processing and storage in the neocortex. Using a two-photon mesoscope, PCS were imaged from the retrosplenial cortex (RSC), a cortical area involved in memory and spatial cognition (Vann, Aggleton, & Maguire, 2009), and primary visual (V1) and somatosensory (S1) cortices in mice traversed visual virtual reality (VR) environments. First, to investigate how the neocortex represents new information, animals were introduced to novel circular track VR environments while imaging hippocampal CA1 and RSC. Both regions rapidly developed PCS in the novel environment that were uncorrelated to activity in the familiar environment. Such global remapping between environments suggested that both the RSC and CA1 networks have similar capacity to encode and store information. To determine how stored representations modulate the influence of visual inputs into the RSC network, next we developed a paradigm where visual VR objects around the circular track shifted to new locations every lap. Shifting objects disrupted PCS formation in a novel environment but had less deleterious effects on PCS in a familiar environment. Finding that PCS change with significant hysteresis suggests that the RSC network exhibits a robust memory of familiar experiences. Instead, shifting the objects caused rate remapping, where the rate of activity within the fields fluctuated as a result of the different visual object configurations. Again, these RSC dynamics were similar to properties reported in the hippocampal literature and suggest that PCS may be conveying information about different experiences within spatial contexts. Finally, to test whether top-down hippocampal inputs are sufficient to drive PCS across neocortical regions in the absence of bottom-up sensory cues, the two-photon mesoscope was used to simultaneously image from RSC, V1, and S1. When mice ran through familiar visual VR environments, unlike V1 or RSC, S1 exhibited poor position decoding. Most cells only showed fields near the distinctive somatosensory cues in the environment, the hidden reward locations. These results suggest that PCS expression varies across the neocortex because top-down inputs are insufficient to drive PCS uniformly. In summary, this thesis examines how inputs into cortical regions influence the remapping, stability, and expression of PCS across and within spatial contexts. It demonstrates how association cortices, in particular RSC, exhibit key memory network dynamics in a manner similar to the hippocampus, thereby bolstering theoretical accounts that suggest the hippocampus conveys a code into the neocortex for the retrieval of memories (Teyler & Rudy, 2007). Surprisingly, although PCS are also found in primary sensory cortices, this thesis finds that PCS expression requires a conjunction of top-down and bottom-up inputs. Together, the studies in this thesis clarify the functional roles different cortical networks play in the storage of memory and guidance of adaptive behaviors.