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Microcircuitry of the Drosophila visual system

Periodic Reporting for period 4 - MicroCyFly (Microcircuitry of the Drosophila visual system)

Reporting period: 2022-01-01 to 2023-03-31

To turn sensory inputs of the outside world into appropriate actions, our brains as well as the brain of all animals must perform specific computations. These computations can be simple or complex, but often involve intricate circuit architecture. It is our major goal to understand how neural computations are implemented in the neuronal networks for the brain. We chose to study a basic, paradigmatic computation, the extraction of direction-selective signals, which is a hallmark of motion detection. While recent years have mapped out core circuits of visual motion detection in the model organism Drosophila, and highlighted many parallels to vertebrate vision, we now aim to understand circuit computations at a new level of detail. Within the “MicroCyFly” project, we develop novel genetic tools to dissect visual circuitry at the level of individual neuronal connections, or synapses, rather at the cell type level. To understand how microcircuits in the brain are generally organized to perform certain tasks is key to target many neurological and psychiatric diseases.
We have carefully characterized neurons of motion detection circuits. We found physiological properties that are essential to implement theoretical models of motion detection, using linear summation mechanisms. In parallel, we have used a forward genetic screen to also identify novel neurons of motion-detection circuitry. This led to the identification of novel, inhibitory cell types of motion-detection circuits, the roles of which we have extensively characterized using physiology, especially in vivo calcium imaging experiments of neural activity, as well as behavioral analysis. Most central to the “MicroCyFly” project, we have developed novel genetic tools for the synapse-specific analysis of circuit function. In vitro and in vivo validation of individual components of this tool called STAB (synapse-targeted activity block) has been successful, and STAB will be made available to the scientific community soon. Building on our analysis of the fly eye microcircuitry, as well as on recent advances in connectomics that have allowed the community to map an entire fly brain at synaptic resolution, we have investigated neuronal wiring variability in the fly eye with synaptic resolution. Our work has shown that some visual neurons have diverse properties across the population of neurons that cover the eye, and thus within a structure that has been considered to be highly homogenous, shedding new insights into coding properties of the visual system. Lastly, also at the population level, we have shown that local direction-selective cells encode global motion at the population level. This reveled a novel coding principle of motion detection circuits in the fly, and highlighted a novel interesting parallel to vision in vertebrates.
Besides achieving the aims of the MicroCyFly projects, two findings were unexpected: We were looking for micro-circuit motifs within the visual system in order to understand how motion is computed and how this information is used to guide animal behavior. Interestingly, our characterization of microcircuit-motifs has shown that the fly eye isn’t fully homogenous, as written in text books, but that some cell types show functional variability, manifested in wiring variability to their presynaptic inputs. Variability also exists in the tuning properties of direction-selective cells. These cells have served as a model to understand how motion is computed, and were long thought to be tuned to upward, downward, rightward and leftward motion. We thought that they in fact fall into subtypes that, as a population are tuned to all direction of motion. Each subtypes uses its diverse tuning properties to encode of pattern of motion that matches the visual experience encountered during self-motion of the fly.
Four neurons of the fly brain with broad arborizations in the visual system (flywire.ai data)
Direction-selective cells encode global motion patterns generated by self-motion