The sensory cortices of the brain are highly complex systems that are uniquely adapted to reliably process any encountered sensory stimulus. Sensory stimuli such as sound are encoded in large populations of neurons that exhibit some functional organization in the cortex. For example, the auditory cortex has a characteristic organization of sound frequency by which neuronal responses are organized. However, this organization is a broad approximation of more complex and diverse functional properties of individual neurons. Furthermore, on a finer temporal scale, the moment-to-moment activity dynamics of populations of neurons are incredibly complex. Numerous studies have shown that spatiotemporal cascades of co-active neurons organize as neuronal avalanches possessing certain characteristics such as size, duration, and shape that fit the parameters of a critical system. Nevertheless, it remains that the exact manner in which neuronal populations encode information is still not fully understood. This dissertation makes use of neuroimaging data acquired with 2-photon calcium imaging of the auditory cortex in awake mice to investigate the spatiotemporal and functional organization of active neuronal populations in auditory cortex at a range of temporal and spatial scales. I aimed to gain a deeper understanding into how neuronal population dynamics and the underlying network organization contribute to sound encoding in auditory cortex. I studied input and associative layers of auditory cortex (L4 and L2/3) in a mouse model with normal hearing and another with age-related hearing loss due to loss of proper cochlear function to high-frequency sound. L4 and L2/3 contained populations of neurons with a large diversity in functional properties, though diversity was reduced in the hearing loss model due to paucity of high frequency tuned neurons. Despite the diverse tuning in both, similarly responding neurons tended to be co-localized in cortical space. I found that this result extended to volumetric samples of L2/3 where large populations of neurons contained a functional network architecture indicative of small-world topology. Furthermore, I demonstrated that L4 and L2/3 contain ensembles of co-active neurons indicative of critical dynamics in both the absence and presence of a stimulus. Finally, I developed software that facilitates real-time quantification of neuronal populations during an experiment which opens the door for novel closed-loop experiment design. This dissertation provides several avenues for further investigation into neuronal population coding and dynamics, functional network topology, and provides the groundwork for closed-loop experimental design.