Mapping the neural dynamics of locomotion across the Drosophila brain.

Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.

BIFROST: a method for registering diverse imaging datasets.

Quantitative comparison of brain-wide neural dynamics across different experimental conditions often requires precise alignment to a common set of anatomical coordinates. While such approaches are routinely applied in functional magnetic resonance imaging (fMRI), registering in vivo fluorescence imaging data to ex vivo-derived reference atlases is challenging, given the many differences in imaging modality, microscope specification, and sample preparation. Moreover, in many systems, animal to animal variation in brain structure limits registration precision. Using the highly stereotyped architecture of the fruit fly brain as a model, we overcome these challenges by building a reference atlas based directly on in vivo multiphoton-imaged brains, called the Functional Drosophila Atlas (FDA). We then develop a novel two-step pipeline, BrIdge For Registering Over Statistical Templates (BIFROST), for transforming neural imaging data into this common space, and for importing ex vivo resources, such as connectomes. Using genetically labeled cell types to provide ground truth, we demonstrate that this method allows voxel registration with micron precision. Thus, this method provides a generalizable pipeline for registering neural activity datasets to one another, allowing quantitative comparisons across experiments, microscopes, genotypes, and anatomical atlases, including connectomes.

Glial control of sphingolipid levels sculpts diurnal remodeling in a circadian circuit.

Structural plasticity in the brain often necessitates dramatic remodeling of neuronal processes, with attendant reorganization of the cytoskeleton and membranes. Although cytoskeletal restructuring has been studied extensively, how lipids might orchestrate structural plasticity remains unclear. We show that specific glial cells in Drosophila produce glucocerebrosidase (GBA) to locally catabolize sphingolipids. Sphingolipid accumulation drives lysosomal dysfunction, causing gba1b mutants to harbor protein aggregates that cycle across circadian time and are regulated by neural activity, the circadian clock, and sleep. Although the vast majority of membrane lipids are stable across the day, a specific subset that is highly enriched in sphingolipids cycles daily in a gba1b-dependent fashion. Remarkably, both sphingolipid biosynthesis and degradation are required for the diurnal remodeling of circadian clock neurites, which grow and shrink across the day. Thus, dynamic sphingolipid regulation by glia enables diurnal circuit remodeling and proper circadian behavior.