Heterogeneity of synaptic connectivity in the fly visual system

Toward a probabilistic definition of neural cell types

A classical view of cell type relies on a definite set of stable properties that are critical for brain functions. Single-cell technologies led to an extensive multimodal characterization of nervous systems and perhaps achieved one of Santiago Ramón y Cajal's dreams: to unveil a comprehensive view of the brain composition. While global analyses of brain structures highlight a degree of mesoscale stereotypy, a finer-scale resolution of brain composition shows significant variance in essential neural cellular phenotypes, including morphology, gene expression, electrophysiology, and connectivity. This highlights the need for novel conceptualization of the definition of a neural "cell type." The challenge of modern neural classification is thus to integrate various distinct cellular properties into a unifying descriptor.

Connectome-driven neural inventory of a complete visual system

Vision provides animals with detailed information about their surroundings and conveys diverse features such as colour, form and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons. Consequently, from flies to humans, visual regions in the brain constitute half its volume. These visual regions often have marked structure-function relationships, with neurons organized along spatial maps and with shapes that directly relate to their roles in visual processing. More than a century of anatomical studies have catalogued in detail cell types in fly visual systems1-3, and parallel behavioural and physiological experiments have examined the visual capabilities of flies. To unravel the diversity of a complex visual system, careful mapping of the neural architecture matched to tools for targeted exploration of this circuitry is essential. Here we present a connectome of the right optic lobe from a male Drosophila melanogaster acquired using focused ion beam milling and scanning electron microscopy. We established a comprehensive inventory of the visual neurons and developed a computational framework to quantify their anatomy. Together, these data establish a basis for interpreting how the shapes of visual neurons relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity and expert curation, we classified the approximately 53,000 neurons into 732 types. These types are systematically described and about half are newly named. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron-type catalogue. Overall, this comprehensive set of tools and data unlocks new possibilities for systematic investigations of vision in Drosophila and provides a foundation for a deeper understanding of sensory processing.

Neural pathways and computations that achieve stable contrast processing tuned to natural scenes

Natural scenes are highly dynamic, challenging the reliability of visual processing. Yet, humans and many animals perform accurate visual behaviors, whereas computer vision devices struggle with rapidly changing background luminance. How does animal vision achieve this? Here, we reveal the algorithms and mechanisms of rapid luminance gain control in Drosophila, resulting in stable visual processing. We identify specific transmedullary neurons as the site of luminance gain control, which pass this property to direction-selective cells. The circuitry further involves wide-field neurons, matching computational predictions that local spatial pooling drive optimal contrast processing in natural scenes when light conditions change rapidly. Experiments and theory argue that a spatially pooled luminance signal achieves luminance gain control via divisive normalization. This process relies on shunting inhibition using the glutamate-gated chloride channel GluClα. Our work describes how the fly robustly processes visual information in dynamically changing natural scenes, a common challenge of all visual systems.

Neuronal wiring diagram of an adult brain

Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative1-6, but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 × 107 chemical synapses7 between 139,255 neurons reconstructed from an adult female Drosophila melanogaster8,9. The resource also incorporates annotations of cell classes and types, nerves, hemilineages and predictions of neurotransmitter identities10-12. Data products are available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources. We derive a projectome-a map of projections between regions-from the connectome and report on tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine and descending neurons) across both hemispheres and between the central brain and the optic lobes. Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours. The technologies and open ecosystem reported here set the stage for future large-scale connectome projects in other species.

Wiring up for controlled flight

A map showing how neurons that process motion are wired together in the visual system of fruit flies provides new insights into how animals navigate and remain stable when flying.