A combinatorial code of transcription factors specifies subtypes of visual motion-sensing neurons in Drosophila.

Direction-selective T4/T5 neurons exist in four subtypes, each tuned to visual motion along one of the four cardinal directions. Along with their directional tuning, neurons of each T4/T5 subtype orient their dendrites and project their axons in a subtype-specific manner. Directional tuning, thus, appears strictly linked to morphology in T4/T5 neurons. How the four T4/T5 subtypes acquire their distinct morphologies during development remains largely unknown. Here, we investigated when and how the dendrites of the four T4/T5 subtypes acquire their specific orientations, and profiled the transcriptomes of all T4/T5 neurons during this process. This revealed a simple and stable combinatorial code of transcription factors defining the four T4/T5 subtypes during their development. Changing the combination of transcription factors of specific T4/T5 subtypes resulted in predictable and complete conversions of subtype-specific properties, i.e. dendrite orientation and matching axon projection pattern. Therefore, a combinatorial code of transcription factors coordinates the development of dendrite and axon morphologies to generate anatomical specializations that differentiate subtypes of T4/T5 motion-sensing neurons.

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.

An Electrophysiological Investigation of Power-Amplification in the Ballistic Mantis Shrimp Punch.

Mantis shrimp are aggressive, burrowing crustaceans that hunt using one the fastest movements in the natural world. These stomatopods can crack the calcified shells of prey or spear down unsuspecting fish with lighting speed. Their strike makes use of power-amplification mechanisms to move their limbs much faster than is possible by muscles alone. Other arthropods such as crickets and grasshoppers also use power-amplified kicks that allow these animals to rapidly jump away from predator threats. Here we present a template laboratory exercise for studying the electrophysiology of power-amplified limb movement in arthropods, with a specific focus on mantis shrimp strikes. The exercise is designed in such a way that it can be applied to other species that perform power-amplified limb movements (e.g., house crickets, Acheta domesticus) and species that do not (e.g., cockroaches, Blaberus discoidalis). Students learn to handle the animals, make and implant electromyogram (EMG) probes, and finally perform experiments. This integrative approach introduces the concept of power-amplified neuromuscular control; allows students to develop scientific methods, and conveys high-level insights into behavior, and convergent evolution, the process by which different species evolve similar traits. Our power-amplification laboratory exercise involves a non-terminal preparation which allows electrophysiological recordings across multiple days from arthropods using a low-cost EMG amplifier. Students learn the principles of electrophysiology by fabricating their own electrode system and performing implant surgeries. Students then present behaviorally-relevant stimuli that generate attack strikes in the animals during the electrophysiology experiments to get insight into the underlying mechanisms of power amplification. Analyses of the EMG data (spike train burst duration, firing rate, and spike amplitude) allow students to compare mantis shrimp with other power-amplifying species, as well as a non-power-amplifying one. The major learning goal of this exercise is to empower students by providing an experience to develop their own setup to examine a complex biological principle. By contrasting power-amplifiers with non-power-amplifiers, these analyses highlight the peculiarity of power amplification at multiple levels of analysis, from behavior to physiology. Our comparative design requires students to consider the behavioral function of the movement in different species alongside the neuromuscular underpinnings of each movement. This laboratory exercise allows students to develop methodology, problem-solving and inquisitive skills crucial for pursuing science.

Neural mechanisms underlying sensitivity to reverse-phi motion in the fly.

Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics.

Complementary mechanisms create direction selectivity in the fly.

How neurons become sensitive to the direction of visual motion represents a classic example of neural computation. Two alternative mechanisms have been discussed in the literature so far: preferred direction enhancement, by which responses are amplified when stimuli move along the preferred direction of the cell, and null direction suppression, where one signal inhibits the response to the subsequent one when stimuli move along the opposite, i.e. null direction. Along the processing chain in the Drosophila optic lobe, directional responses first appear in T4 and T5 cells. Visually stimulating sequences of individual columns in the optic lobe with a telescope while recording from single T4 neurons, we find both mechanisms at work implemented in different sub-regions of the receptive field. This finding explains the high degree of directional selectivity found already in the fly's primary motion-sensing neurons and marks an important step in our understanding of elementary motion detection.

Asymmetry of Drosophila ON and OFF motion detectors enhances real-world velocity estimation.

The reliable estimation of motion across varied surroundings represents a survival-critical task for sighted animals. How neural circuits have adapted to the particular demands of natural environments, however, is not well understood. We explored this question in the visual system of Drosophila melanogaster. Here, as in many mammalian retinas, motion is computed in parallel streams for brightness increments (ON) and decrements (OFF). When genetically isolated, ON and OFF pathways proved equally capable of accurately matching walking responses to realistic motion. To our surprise, detailed characterization of their functional tuning properties through in vivo calcium imaging and electrophysiology revealed stark differences in temporal tuning between ON and OFF channels. We trained an in silico motion estimation model on natural scenes and discovered that our optimized detector exhibited differences similar to those of the biological system. Thus, functional ON-OFF asymmetries in fly visual circuitry may reflect ON-OFF asymmetries in natural environments.

Comprehensive Characterization of the Major Presynaptic Elements to the Drosophila OFF Motion Detector.

Estimating motion is a fundamental task for the visual system of sighted animals. In Drosophila, direction-selective T4 and T5 cells respond to moving brightness increments (ON) and decrements (OFF), respectively. Current algorithmic models of the circuit are based on the interaction of two differentially filtered signals. However, electron microscopy studies have shown that T5 cells receive their major input from four classes of neurons: Tm1, Tm2, Tm4, and Tm9. Using two-photon calcium imaging, we demonstrate that T5 is the first direction-selective stage within the OFF pathway. The four cells provide an array of spatiotemporal filters to T5. Silencing their synaptic output in various combinations, we find that all input elements are involved in OFF motion detection to varying degrees. Our comprehensive survey challenges the simplified view of how neural systems compute the direction of motion and suggests that an intricate interplay of many signals results in direction selectivity.

Neural Mechanisms for Drosophila Contrast Vision.

Spatial contrast, the difference in adjacent luminance values, provides information about objects, textures, and motion and supports diverse visual behaviors. Contrast computation is therefore an essential element of visual processing. The underlying mechanisms, however, are poorly understood. In human psychophysics, contrast illusions are means to explore such computations, but humans offer limited experimental access. Via behavioral experiments in Drosophila, we find that flies are also susceptible to contrast illusions. Using genetic silencing techniques, electrophysiology, and modeling, we systematically dissect the mechanisms and neuronal correlates underlying the behavior. Our results indicate that spatial contrast computation involves lateral inhibition within the same pathway that computes motion of luminance increments (ON pathway). Yet motion-blind flies, in which we silenced downstream motion-sensitive neurons needed for optomotor behavior, have fully intact contrast responses. In conclusion, spatial contrast and motion cues are first computed by overlapping neuronal circuits which subsequently feed into parallel visual processing streams.

Neural circuit components of the Drosophila OFF motion vision pathway.

BACKGROUND: Detecting the direction of visual motion is an essential task of the early visual system. The Reichardt detector has been proven to be a faithful description of the underlying computation in insects. A series of recent studies addressed the neural implementation of the Reichardt detector in Drosophila revealing the overall layout in parallel ON and OFF channels, its input neurons from the lamina (L1→ON, and L2→OFF), and the respective output neurons to the lobula plate (ON→T4, and OFF→T5). While anatomical studies showed that T4 cells receive input from L1 via Mi1 and Tm3 cells, the neurons connecting L2 to T5 cells have not been identified so far. It is, however, known that L2 contacts, among others, two neurons, called Tm2 and L4, which show a pronounced directionality in their wiring. RESULTS: We characterized the visual response properties of both Tm2 and L4 neurons via Ca(2+) imaging. We found that Tm2 and L4 cells respond with an increase in activity to moving OFF edges in a direction-unselective manner. To investigate their participation in motion vision, we blocked their output while recording from downstream tangential cells in the lobula plate. Silencing of Tm2 and L4 completely abolishes the response to moving OFF edges. CONCLUSIONS: Our results demonstrate that both cell types are essential components of the Drosophila OFF motion vision pathway, prior to the computation of directionality in the dendrites of T5 cells.

Optogenetic and pharmacologic dissection of feedforward inhibition in Drosophila motion vision.

Visual systems extract directional motion information from spatiotemporal luminance changes on the retina. An algorithmic model, the Reichardt detector, accounts for this by multiplying adjacent inputs after asymmetric temporal filtering. The outputs of two mirror-symmetrical units tuned to opposite directions are thought to be subtracted on the dendrites of wide-field motion-sensitive lobula plate tangential cells by antagonistic transmitter systems. In Drosophila, small-field T4/T5 cells carry visual motion information to the tangential cells that are depolarized during preferred and hyperpolarized during null direction motion. While preferred direction input is likely provided by excitation from T4/T5 terminals, the origin of null direction inhibition is unclear. Probing the connectivity between T4/T5 and tangential cells in Drosophila using a combination of optogenetics, electrophysiology, and pharmacology, we found a direct excitatory as well as an indirect inhibitory component. This suggests that the null direction response is caused by feedforward inhibition via yet unidentified neurons.

A directional tuning map of Drosophila elementary motion detectors.

The extraction of directional motion information from changing retinal images is one of the earliest and most important processing steps in any visual system. In the fly optic lobe, two parallel processing streams have been anatomically described, leading from two first-order interneurons, L1 and L2, via T4 and T5 cells onto large, wide-field motion-sensitive interneurons of the lobula plate. Therefore, T4 and T5 cells are thought to have a pivotal role in motion processing; however, owing to their small size, it is difficult to obtain electrical recordings of T4 and T5 cells, leaving their visual response properties largely unknown. We circumvent this problem by means of optical recording from these cells in Drosophila, using the genetically encoded calcium indicator GCaMP5 (ref. 2). Here we find that specific subpopulations of T4 and T5 cells are directionally tuned to one of the four cardinal directions; that is, front-to-back, back-to-front, upwards and downwards. Depending on their preferred direction, T4 and T5 cells terminate in specific sublayers of the lobula plate. T4 and T5 functionally segregate with respect to contrast polarity: whereas T4 cells selectively respond to moving brightness increments (ON edges), T5 cells only respond to moving brightness decrements (OFF edges). When the output from T4 or T5 cells is blocked, the responses of postsynaptic lobula plate neurons to moving ON (T4 block) or OFF edges (T5 block) are selectively compromised. The same effects are seen in turning responses of tethered walking flies. Thus, starting with L1 and L2, the visual input is split into separate ON and OFF pathways, and motion along all four cardinal directions is computed separately within each pathway. The output of these eight different motion detectors is then sorted such that ON (T4) and OFF (T5) motion detectors with the same directional tuning converge in the same layer of the lobula plate, jointly providing the input to downstream circuits and motion-driven behaviours.