Neural mechanism of spatio-chromatic opponency in the Drosophila amacrine neurons.

Visual animals detect spatial variations of light intensity and wavelength composition. Opponent coding is a common strategy for reducing information redundancy. Neurons equipped with both spatial and spectral opponency have been identified in vertebrates but not yet in insects. The Drosophila amacrine neuron Dm8 was recently reported to show color opponency. Here, we demonstrate Dm8 exhibits spatio-chromatic opponency. Antagonistic convergence of the direct input from the UV-sensing R7s and indirect input from the broadband receptors R1-R6 through Tm3 and Mi1 is sufficient to confer Dm8's UV/Vis (ultraviolet/visible light) opponency. Using high resolution monochromatic stimuli, we show the pale and yellow subtypes of Dm8s, inheriting retinal mosaic characteristics, have distinct spectral tuning properties. Using 2D white-noise stimulus and reverse correlation analysis, we found that the UV receptive field (RF) of Dm8 has a center-inhibition/surround-excitation structure. In the absence of UV-sensing R7 inputs, the polarity of the RF is inverted owing to the excitatory input from the broadband photoreceptors R1-R6. Using a new synGRASP method based on endogenous neurotransmitter receptors, we show that neighboring Dm8s form mutual inhibitory connections mediated by the glutamate-gated chloride channel GluClα, which is essential for both Dm8's spatial opponency and animals' phototactic behavior. Our study shows spatio-chromatic opponency could arise in the early visual stage, suggesting a common information processing strategy in both invertebrates and vertebrates.

Dynamic Signal Compression for Robust Motion Vision in Flies.

Sensory systems need to reliably extract information from highly variable natural signals. Flies, for instance, use optic flow to guide their course and are remarkably adept at estimating image velocity regardless of image statistics. Current circuit models, however, cannot account for this robustness. Here, we demonstrate that the Drosophila visual system reduces input variability by rapidly adjusting its sensitivity to local contrast conditions. We exhaustively map functional properties of neurons in the motion detection circuit and find that local responses are compressed by surround contrast. The compressive signal is fast, integrates spatially, and derives from neural feedback. Training convolutional neural networks on estimating the velocity of natural stimuli shows that this dynamic signal compression can close the performance gap between model and organism. Overall, our work represents a comprehensive mechanistic account of how neural systems attain the robustness to carry out survival-critical tasks in challenging real-world environments.

Glutamate Signaling in the Fly Visual System.

For a proper understanding of neural circuit function, it is important to know which signals neurons relay to their downstream partners. Calcium imaging with genetically encoded calcium sensors like GCaMP has become the default approach for mapping these responses. How well such measurements represent the true neurotransmitter output of any given cell, however, remains unclear. Here, we demonstrate the viability of the glutamate sensor iGluSnFR for 2-photon in vivo imaging in Drosophila melanogaster and prove its usefulness for estimating spatiotemporal receptive fields in the visual system. We compare the results obtained with iGluSnFR with the ones obtained with GCaMP6f and find that the spatial aspects of the receptive fields are preserved between indicators. In the temporal domain, however, measurements obtained with iGluSnFR reveal the underlying response properties to be much faster than those acquired with GCaMP6f. Our approach thus offers a more accurate description of glutamatergic neurons in the fruit fly.

The Temporal Tuning of the Drosophila Motion Detectors Is Determined by the Dynamics of Their Input Elements.

Detecting the direction of motion contained in the visual scene is crucial for many behaviors. However, because single photoreceptors only signal local luminance changes, motion detection requires a comparison of signals from neighboring photoreceptors across time in downstream neuronal circuits. For signals to coincide on readout neurons that thus become motion and direction selective, different input lines need to be delayed with respect to each other. Classical models of motion detection rely on non-linear interactions between two inputs after different temporal filtering. However, recent studies have suggested the requirement for at least three, not only two, input signals. Here, we comprehensively characterize the spatiotemporal response properties of all columnar input elements to the elementary motion detectors in the fruit fly, T4 and T5 cells, via two-photon calcium imaging. Between these input neurons, we find large differences in temporal dynamics. Based on this, computer simulations show that only a small subset of possible arrangements of these input elements maps onto a recently proposed algorithmic three-input model in a way that generates a highly direction-selective motion detector, suggesting plausible network architectures. Moreover, modulating the motion detection system by octopamine-receptor activation, we find the temporal tuning of T4 and T5 cells to be shifted toward higher frequencies, and this shift can be fully explained by the concomitant speeding of the input elements.