Stereotyped spatiotemporal dynamics of spontaneous activity in visual cortex prior to eye-opening

Abstract

AbstractOver the course of development, functional sensory representations emerge in the visual cortex. Prior to eye-opening, modular patterns of spontaneous activity form long-range networks that may serve as a precursor for mature network organization. Although the spatial structure of these networks has been well studied, their temporal features, which may contribute to their continued plasticity and development, remain largely uncharacterized. To address this, we imaged hours of spontaneous network activity in the visual cortex of developing ferrets of both sexes utilizing a fast calcium indicator (GCaMP8m) and widefield imaging at high temporal resolution (50Hz), then segmented out spatiotemporal events. The spatial structure of this activity was highly modular, exhibiting spatially segregated active domains consistent with prior work. We found that the vast majority of events showed a clear dynamic component in which modules activated sequentially across the field of view, but only a minority of events were well-fit with a linear traveling wave. We found that spatiotemporal events occur in repeated and stereotyped motifs, reoccurring across hours of imaging. Finally, we found that the most frequently occurring single-frame spatial activity patterns were predictive of future activity patterns over hundreds of milliseconds. Together, our results demonstrate that spontaneous activity in the early developing cortex exhibits a rich spatiotemporal structure, suggesting a potential role in the maturation and refinement of future functional representations.Significance statementUnderstanding the temporal dynamics underlying the network structure in early development is critical for understanding network function and plasticity. By imaging hours of spontaneous cortical activity, we show strong evidence that the vast majority of spontaneous neural activity is dynamic with repeated and complex spatiotemporal patterns with stereotyped structure across hours. This suggests the potential for Hebbian learning in the development and refinement of functional visual representations. We also find that frequently occurring spatial activity patterns are predictive of subsequent activity for up to one second, which may indicate attractor dynamics in spontaneous activity. Our findings characterize key features of the temporal structure of spontaneous activity in visual cortex early in development and deepen our understanding of developing neural networks.