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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.

Typically, neurons in sensory areas are highly interconnected. Coupling two neurons can synchronize their activity and affect a variety of single-cell properties, such as their stimulus tuning, firing rate or gain. All of these factors must be considered to understand how two neurons should be coupled to optimally process stimuli. We quantified the functional effect of an interaction between two optic-flow processing neurons (Vi and H1) in the fly (Lucilia sericata). Using a generative model, we estimated a uni-directional coupling from H1 to Vi. Especially at a low signal-to-noise ratio (SNR), the coupling strongly improved the information about optic-flow in Vi. We identified two constraints confining the strength of the interaction. First, for weak couplings, Vi benefited from inputs by H1 without a concomitant shift of its stimulus tuning. Second, at both low and high SNR, the coupling strength lay in a range in which the information carried by single spikes is optimal.

In the visual system of Drosophila, photoreceptors R1-R6 relay achromatic brightness information to five parallel pathways. Two of them, the lamina monopolar cells L1 and L2, represent the major input lines to the motion detection circuitry. We devised a new method for optical recording of visually evoked changes in intracellular Ca2+ in neurons using targeted expression of a genetically encoded Ca2+ indicator. Ca2+ in single terminals of L2 neurons in the medulla carried no information about the direction of motion. However, we found that brightness decrements (light-OFF) induced a strong increase in intracellular Ca2+ but brightness increments (light-ON) induced only small changes, suggesting that half-wave rectification of the input signal occurs. Thus, L2 predominantly transmits brightness decrements to downstream circuits that then compute the direction of image motion.

In the visual system of the blowfly Calliphora vicina, neurons of the vertical system (VS cells) integrate wide-field motion information from a retinotopic array of local motion detectors. In vivo calcium imaging reveals two distinct and separate receptive fields in these cells: a narrow dendritic receptive field corresponding to feedforward input from the local motion detectors and a broad axon terminal receptive field that additionally incorporates input from neighboring cells mediated by lateral axo-axonal gap junctions. We show that the axon terminal responses are linear interpolations of the dendritic responses, resulting in a robust population coding of optic flow parameters as predicted by previous modeling studies. Compartmental modeling shows that spatially separating the axonal gap junctions from the conductive load of the dendritic synapses increases the coupling strength of the gap junctions, making this interpolation possible.

Neurons in many species have large receptive fields that are selective for specific optic flow fields. Here, we studied the neural mechanisms underlying flow field selectivity in lobula plate tangential cells (LPTCs) of the blowfly. Among these cells, the H2 cell responds preferentially to visual stimuli approximating rotational optic flow. Through double recordings from H2 and many other LPTCs, we characterized a bidirectional commissural pathway that allows visual information to be shared between the hemispheres. This pathway is mediated by axo-axonal electrical coupling of H2 and the horizontal system equatorial (HSE) cell located in the opposite hemisphere. Using single-cell ablations, we found that this pathway is sufficient to allow H2 to amplify and attenuate dendritic input during binocular visual stimuli. This is accomplished through a modulation of H2's membrane potential by input from the contralateral HSE cell, which scales the firing rate of H2 during visual stimulation but is not sufficient to induce action potentials.

At the Drosophila melanogaster larval neuromuscular junction (NMJ), a motor neuron releases glutamate from 30–100 boutons onto the muscle it innervates. How transmission strength is distributed among the boutons of the NMJ is unknown. To address this, we created synapcam, a version of the Ca2+ reporter Cameleon. Synapcam localizes to the postsynaptic terminal and selectively reports Ca2+ influx through glutamate receptors (GluRs) with single-impulse and single-bouton resolution. GluR-based Ca2+ signals were uniform within a given connection (that is, a given bouton/postsynaptic terminal pair) but differed considerably among connections of an NMJ. A steep gradient of transmission strength was observed along axonal branches, from weak proximal connections to strong distal ones. Presynaptic imaging showed a matching axonal gradient, with higher Ca2+ influx and exocytosis at distal boutons. The results suggest that transmission strength is mainly determined presynaptically at the level of individual boutons, possibly by one or more factors existing in a gradient. *Note: In the version of this article initially published online, the second author’s name was misspelled. The correct spelling should be Dierk F Reiff. The error has been corrected in the HTML version of the article. This correction has been appended to the PDF and print versions.

Motion-sensitive neurons have long been studied in both the mammalian retina and the insect optic lobe, yet striking similarities have become obvious only recently. Detailed studies at the circuit level revealed that, in both systems, (i) motion information is extracted from primary visual information in parallel ON and OFF pathways; (ii) in each pathway, the process of elementary motion detection involves the correlation of signals with different temporal dynamics; and (iii) primary motion information from both pathways converges at the next synapse, resulting in four groups of ON-OFF neurons, selective for the four cardinal directions. Given that the last common ancestor of insects and mammals lived about 550 million years ago, this general strategy seems to be a robust solution for how to compute the direction of visual motion with neural hardware.

Different visual features of an object, such as its position and direction of motion, are important elements for animal orientation, but the neural circuits extracting them are generally not well understood. We analyzed this problem in Drosophila, focusing on two well-studied behaviors known as optomotor response and fixation response. In the neural circuit controlling the optomotor response, columnar T4 and T5 cells are thought to be crucial. We found that blocking T4 and T5 cells resulted in a complete loss of the optomotor response. Nevertheless, these flies were still able to fixate a black bar, although at a reduced performance level. Further analysis revealed that flies in which T4 and T5 cells were blocked possess an intact position circuit that is implemented in parallel to the motion circuit; the optomotor response is exclusively controlled by the motion circuit, whereas the fixation response is supported by both the position and the motion circuit.

In many species, neurons responding to visual motion at higher processing stages are often specifically tuned to particular flow fields; however, the neural circuitry that leads to this selectivity is not yet understood. Here we have studied this problem in 'vertical system' (VS) cells of the blowfly lobula plate. These neurons possess distinctive local preferred directions in different parts of their receptive field. Dual recordings from pairs of VS cells show that they are electrically coupled. This coupling is responsible for the elongated horizontal extent of their receptive fields. VS cells with a lateral receptive field have additional connections to a VS cell with a frontal receptive field and to the horizontal system, tuning these cells to rotational flow fields. In summary, the receptive field of these cells consists of two components: one that they receive from local motion detectors on their dendrite, and one that they import from other large-field neurons.

Contrary to a recent finding in rabbit retina, Borg-Graham reports that inputs to retinal ganglion neurons in turtles are already directionally selective.

Information theory quantifies how much information a neural response carries about the stimulus. This can be compared to the information transferred in particular models of the stimulus-response function and to maximum possible information transfer. Such comparisons are crucial because they validate assumptions present in any neurophysiological analysis. Here we review information-theory basics before demonstrating its use in neural coding. We show how to use information theory to validate simple stimulus-response models of neural coding of dynamic stimuli. Because these models require specification of spike timing precision, they can reveal which time scales contain information in neural coding. This approach shows that dynamic stimuli can be encoded efficiently by single neurons and that each spike contributes to information transmission. We argue, however, that the data obtained so far do not suggest a temporal code, in which the placement of spikes relative to each other yields additional information.

Using calcium imaging as bees learn to associate odors with a reward, Faber and colleagues show that learning changes activity patterns at the earliest olfactory site in the brain.