Persistent Firing and Adaptation in Optic-Flow-Sensitive Descending Neurons

Descending neurons of the hoverfly respond to pursuits of artificial targets

Many animals use motion vision information to control dynamic behaviors. Predatory animals, for example, show an exquisite ability to detect rapidly moving prey, followed by pursuit and capture. Such target detection is not only used by predators but is also important in conspecific interactions, such as for male hoverflies defending their territories against conspecific intruders. Visual target detection is believed to be subserved by specialized target-tuned neurons found in a range of species, including vertebrates and arthropods. However, how these target-tuned neurons respond to actual pursuit trajectories is currently not well understood. To redress this, we recorded extracellularly from target-selective descending neurons (TSDNs) in male Eristalis tenax hoverflies. We show that they have dorso-frontal receptive fields with a preferred direction up and away from the visual midline. We reconstructed visual flow fields as experienced during pursuits of artificial targets (black beads). We recorded TSDN responses to six reconstructed pursuits and found that each neuron responded consistently at remarkably specific time points but that these time points differed between neurons. We found that the observed spike probability was correlated with the spike probability predicted from each neuron's receptive field and size tuning. Interestingly, however, the overall response rate was low, with individual neurons responding to only a small part of each reconstructed pursuit. In contrast, the TSDN population responded to substantially larger proportions of the pursuits but with lower probability. This large variation between neurons could be useful if different neurons control different parts of the behavioral output.

Impact of walking speed and motion adaptation on optokinetic nystagmus-like head movements in the blowfly Calliphora

The optokinetic nystagmus is a gaze-stabilizing mechanism reducing motion blur by rapid eye rotations against the direction of visual motion, followed by slower syndirectional eye movements minimizing retinal slip speed. Flies control their gaze through head turns controlled by neck motor neurons receiving input directly, or via descending neurons, from well-characterized directional-selective interneurons sensitive to visual wide-field motion. Locomotion increases the gain and speed sensitivity of these interneurons, while visual motion adaptation in walking animals has the opposite effects. To find out whether flies perform an optokinetic nystagmus, and how it may be affected by locomotion and visual motion adaptation, we recorded head movements of blowflies on a trackball stimulated by progressive and rotational visual motion. Flies flexibly responded to rotational stimuli with optokinetic nystagmus-like head movements, independent of their locomotor state. The temporal frequency tuning of these movements, though matching that of the upstream directional-selective interneurons, was only mildly modulated by walking speed or visual motion adaptation. Our results suggest flies flexibly control their gaze to compensate for rotational wide-field motion by a mechanism similar to an optokinetic nystagmus. Surprisingly, the mechanism is less state-dependent than the response properties of directional-selective interneurons providing input to the neck motor system.

The impulse response of optic flow-sensitive descending neurons to roll m-sequences

When animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow-sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensorimotor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. Therefore, here we used m-sequences to quantify the impulse responses of optic flow-sensitive descending neurons in male Eristalis tenax hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5–18.0 ms. This is similar to the impulse response time to peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift.

Summary: The impulse response of hoverfly optic flow-sensitive descending neurons to roll m-sequences reaches its time to peak within 20 ms and slowly returns to baseline over the next 100 ms.

Facilitation of neural responses to targets moving against optic flow

Target detection in visual clutter is a difficult computational task that insects, with their poor spatial resolution compound eyes and small brains, do successfully and with extremely short behavioral delays. We here show that the responses of target selective descending neurons are attenuated by background motion in the same direction as target motion but facilitated by background motion in the opposite direction. This finding is important for understanding how target pursuit can occur in tandem with gaze stabilization. Indeed, the neural facilitation would come into effect if the hoverfly is subjected to background motion in one direction but the target it is pursuing moves in the opposite direction and could therefore be used to override gaze stabilizing corrective turns.

For the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. In contrast, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. We here recorded from target selective descending neurons (TSDNs), which likely subserve these impressive behaviors. To simulate the type of optic flow that would be generated by the pursuer’s own movements through the world, we used the motion of a perspective corrected sparse dot field. We show that hoverfly TSDN responses to target motion are suppressed when such optic flow moves syn-directional to the target. Indeed, neural responses are strongly suppressed when targets move over either translational sideslip or rotational yaw. More strikingly, we show that TSDNs are facilitated by optic flow moving counterdirectional to the target, if the target moves horizontally. Furthermore, we show that a small, frontal spatial window of optic flow is enough to fully facilitate or suppress TSDN responses to target motion. We argue that such TSDN response facilitation could be beneficial in modulating corrective turns during target pursuit.