Temporal and spatial adaptation of transient responses to local features.

Interpreting visual motion within the natural environment is a challenging task, particularly considering that natural scenes vary enormously in brightness, contrast and spatial structure. The performance of current models for the detection of self-generated optic flow depends critically on these very parameters, but despite this, animals manage to successfully navigate within a broad range of scenes. Within global scenes local areas with more salient features are common. Recent work has highlighted the influence that local, salient features have on the encoding of optic flow, but it has been difficult to quantify how local transient responses affect responses to subsequent features and thus contribute to the global neural response. To investigate this in more detail we used experimenter-designed stimuli and recorded intracellularly from motion-sensitive neurons. We limited the stimulus to a small vertically elongated strip, to investigate local and global neural responses to pairs of local "doublet" features that were designed to interact with each other in the temporal and spatial domain. We show that the passage of a high-contrast doublet feature produces a complex transient response from local motion detectors consistent with predictions of a simple computational model. In the neuron, the passage of a high-contrast feature induces a local reduction in responses to subsequent low-contrast features. However, this neural contrast gain reduction appears to be recruited only when features stretch vertically (i.e., orthogonal to the direction of motion) across at least several aligned neighboring ommatidia. Horizontal displacement of the components of elongated features abolishes the local adaptation effect. It is thus likely that features in natural scenes with vertically aligned edges, such as tree trunks, recruit the greatest amount of response suppression. This property could emphasize the local responses to such features vs. those in nearby texture within the scene.

Local and global responses of insect motion detectors to the spatial structure of natural scenes.

As a consequence of the non-linear correlation mechanism underlying motion detection, the variability in local pattern structure and contrast inherent within natural scenes profoundly influences local motion responses. To accurately interpret optic flow induced by self-motion, neurons in many dipteran flies smooth this "pattern noise" by wide-field spatial integration. We investigated the role that size and shape of the receptive field plays in smoothing out pattern noise in two unusual hoverfly optic flow neurons: one (HSN) with an exceptionally small receptive field and one (HSNE) with a larger receptive field. We compared the local and global responses to a sequence of panoramic natural images in these two neurons with a parsimonious model for elementary motion detection weighted for their spatial receptive fields. Combined with manipulation of size and contrast of the stimulus images, this allowed us to separate spatial integration properties arising from the receptive field, from other local and global non-linearities, such as motion adaptation and dendritic gain control. We show that receptive field properties alone are poor predictors of the response to natural scenes. If anything, additional non-linearity enhances the pattern dependence of HSN's response, particularly to vertically elongated features, suggesting that it may serve a role in forward fixation during hovering.

Motion adaptation and the velocity coding of natural scenes.

Estimating relative velocity in the natural environment is challenging because natural scenes vary greatly in contrast and spatial structure. Widely accepted correlation-based models for elementary motion detectors (EMDs) are sensitive to contrast and spatial structure and consequently generate ambiguous estimates of velocity. Identified neurons in the third optic lobe of the hoverfly can reliably encode the velocity of natural images largely independent of contrast, despite receiving inputs directly from arrays of such EMDs. This contrast invariance suggests an important role for additional neural processes in robust encoding of image motion. However, it remains unclear which neural processes are contributing to contrast invariance. By recording from horizontal system neurons in the hoverfly lobula, we show two activity-dependent adaptation mechanisms acting as near-ideal normalizers for images of different contrasts that would otherwise produce highly variable response magnitudes. Responses to images that are initially weak neural drivers are boosted over several hundred milliseconds. Responses to images that are initially strong neural drivers are reduced over longer time scales. These adaptation mechanisms appear to be matched to higher-order natural image statistics reconciling the neurons' accurate encoding of image velocity with the inherent ambiguity of correlation-based motion detectors.

Sexual dimorphism in the hoverfly motion vision pathway.

Many insects perform high-speed aerial maneuvers in which they navigate through visually complex surrounds. Among insects, hoverflies stand out, with males switching from stationary hovering to high-speed pursuit at extreme angular velocities [1]. In dipterans, 50-60 large interneurons -- the lobula-plate tangential cells (LPTCs) -- detect changes in optic flow experienced during flight [2-5]. It has been predicted that large LPTC receptive fields are a requirement of accurate "matched filters" of optic flow [6]. Whereas many fly taxa have three horizontal system (HS) LPTC neurons in each hemisphere, hoverflies have four [7], possibly reflecting the more sophisticated flight behavior. We here show that the most dorsal hoverfly neuron (HS north [HSN]) is sexually dimorphic, with the male receptive field substantially smaller than in females or in either sex of blowflies. The (hoverfly-specific) HSN equatorial (HSNE) is, however, sexually isomorphic. Using complex optic flow, we show that HSN, despite its smaller receptive field, codes yaw velocity as well as HSNE. Responses to a target moving against a plain or textured background suggest that the male HSN could potentially play a role in target pursuit under some conditions.

Retinotopic organization of small-field-target-detecting neurons in the insect visual system.

BACKGROUND: Despite having tiny brains and relatively low-resolution compound eyes, many fly species frequently engage in precisely controlled aerobatic pursuits of conspecifics. Recent investigations into high-order processing in the fly visual system have revealed a class of neurons, coined small-target-motion detectors (STMDs), capable of responding robustly to target motion against the motion of background clutter. Despite limited spatial acuity in the insect eye, these neurons display exquisite sensitivity to small targets. RESULTS: We recorded intracellularly from morphologically identified columnar neurons in the lobula complex of the hoverfly Eristalis tenax. We show that these columnar neurons with exquisitely small receptive fields, like their large-field counterparts recently described from both male and female flies, have an extreme selectivity for the motion of small targets. In doing so, we provide the first physiological characterization of small-field neurons in female flies. These retinotopically organized columnar neurons include both direction-selective and nondirection-selective classes covering a large area of visual space. CONCLUSIONS: The retinotopic arrangement of lobula columnar neurons sensitive to the motion of small targets makes a strong case for these neurons as important precursors in the local processing of target motion. Furthermore, the continued response of STMDs with such small receptive fields to the motion of small targets in the presence of moving background clutter places further constraints on the potential mechanisms underlying their small-target tuning.

Insect detection of small targets moving in visual clutter.

Detection of targets that move within visual clutter is a common task for animals searching for prey or conspecifics, a task made even more difficult when a moving pursuer needs to analyze targets against the motion of background texture (clutter). Despite the limited optical acuity of the compound eye of insects, this challenging task seems to have been solved by their tiny visual system. Here we describe neurons found in the male hoverfly, Eristalis tenax, that respond selectively to small moving targets. Although many of these target neurons are inhibited by the motion of a background pattern, others respond to target motion within the receptive field under a surprisingly large range of background motion stimuli. Some neurons respond whether or not there is a speed differential between target and background. Analysis of responses to very small targets (smaller than the size of the visual field of single photoreceptors) or those targets with reduced contrast shows that these neurons have extraordinarily high contrast sensitivity. Our data suggest that rejection of background motion may result from extreme selectivity for small targets contrasting against local patches of the background, combined with this high sensitivity, such that background patterns rarely contain features that satisfactorily drive the neuron.