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.     

A bio-inspired visual collision detection mechanism for cars: combining insect inspired neurons to create a robust system

The lobula giant movement detector (LGMD) of locusts is a visual interneuron that responds with an increasing spike frequency to an object approaching on a direct collision course. Recent studies involving the use of LGMD models to detect car collisions showed that it could detect collisions, but the neuron produced collision alerts to non-colliding, translating, stimuli in many cases. This study presents a modified model to address these problems. It shows how the neurons pre-synaptic to the LGMD show a remarkable ability to filter images, and only colliding and translating stimuli produce excitation in the neuron. It then integrates the LGMD network with models based on the elementary movement detector (EMD) neurons from the fly visual system, which are used to analyse directional excitation patterns in the biologically filtered images. Combining the information from the LGMD neuron and four directionally sensitive neurons produces a robust collision detection system for a wide range of automotive test situations.     

在背景干扰条件下大棕蝠对静止及移动目标的探测

采用“双选”的心理物理学方法 ,研究了训练后的大棕蝠 (Eptesicusfuscus)在背景干扰的条件下探测半圆形目标的能力。半圆形目标系以静止、旋转、摆动或不同组合的旋转与摆动呈现于蝙蝠。在测试室 ,蝙蝠-目标间距从 3 0cm开始 ,依次递增 10cm直至 110cm为止。当蝙蝠 -目标间距小于 80cm时 ,目标回声的强度总是大于背景干扰声。由旋转目标反射的回声强度则依正弦波调制。结果发现 :蝙蝠对目标的正确探测率随蝙蝠 -目标间距的增加而降低 ;在每一特定间距 ,对移动目标的正确探测率均高于对静止目标的正确探测率     

A general model for visual motion detection

We propose a general model for detection of both first-order motion and second-order motion. In this model an input stimulus is divided into a number of partially overlapping spatiotemporal local regions. Spatiotemporal frequency analysis is done for every local region using Gabor filters, then the input stimulus (original spatiotemporal signal) is replaced by the outputs of Gabor filters. Local motion is detected by applying Gabor motion detectors to each local spatiotemporal pattern depicted by each local feature value. Outputs of all the detectors are integrated to give the final output for global motion of the input stimulus. The model was simulated on a computer and was confirmed to correctly detect second-order motion as well as first-order motion.     

Identifying behavioral circuits in Drosophila melanogaster: moving targets in a flying insect

Drosophila melanogaster has historically been the premier model system for understanding the molecular and genetic bases of complex behaviors. In the last decade technical advances, in the form of new genetic tools and electrophysiological and optical methods, have allowed investigators to begin to dissect the neuronal circuits that generate behavior in the adult. The blossoming of circuit analysis in this organism has also reinforced our appreciation of the inadequacy of wiring diagrams for specifying complex behavior. Neuromodulation and neuronal plasticity act to reconfigure circuits on both short and long time scales. These processes act on the connectome, providing context by integrating external and internal cues that are relevant for behavioral choices. New approaches in the fly are providing insight into these basic principles of circuit function.     

The fundamental mechanism of motion detection in the insect visual system

The basic principle of motion detection by fibers of the optic lobes of flies were studied with a pair of small spots and a variety of paired intensity variations. These show that the process of correlation of adjacent field regions to detect motion is confined to a small area. The presence of small field units with small field adjacent inhibition in the system was detected. The optimum spot spacing for maximum reactions corresponded to the facet spacings. Selective motion detection responses from minimum information consisting of evaluating the difference between the spot intensities and the rate of change of the trailing spot relative to the motion direction was shown. However, additional properties best determined by white-noise experiments designed from this study were found.     

A model of visual detection of angular speed for bees

A fly or bee's responses to widefield image motion depend on two basic parameters: temporal frequency and angular speed. Rotational optic flow is monitored using temporal frequency analysers, whereas translational optic flow seems to be monitored in terms of angular speed. Here we present a possible model of an angular speed detector which processes input signals through two parallel channels. The output of the detector is taken as the ratio of the two channels’ outputs. This operation amplifies angular speed sensitivity and depresses temporal frequency tuning. We analyse the behaviour of two versions of this model with different filtering properties in response to a variety of input signals. We then embody the detector in a simulated agent's visual system and explore its behaviour in experiments on speed control and odometry. The latter leads us to suggest a new algorithm for optic flow driven odometry.     

视觉信号在昆虫检测植物寄主中的作用

植物为数十万种昆虫提供各种资源,如食物、交配、产卵和躲避天敌的场所。目前对昆虫检测植物寄主的研究主要关注昆虫嗅觉系统和植物寄主挥发物之间的相互作用,对昆虫视觉系统发挥的作用关注较少。近年来,对昆虫视觉器官、光行为反应及分子生物学的研究表明,昆虫具有优异的视觉能力,能够辨别植物寄主的颜色、大小和轮廓,应该将视觉纳入昆虫检测植物寄主的研究中。昆虫能够利用视觉信号准确检测寄主,远距离时,主要依靠植物寄主轮廓检测寄主,近距离时,寄主的大小、颜色和形状发挥重要作用。利用昆虫视觉识别寄主的专一性研制诱捕装置,可为害虫的监测和防治提供一定的理论基础。     

A model for neural signal-to-noise ratio improvement in the insect visual system with implications for “Anomalous resolution”

The descending contralateral movement detector (DCMD) neurons in locusts have been used in studies of limiting spatial resolution of moving, striped objects. The results of such studies have been controversial; one group of workers claiming resolution to below a 0.3° stripe period (Burtt and Catton, 1962, 1969; Northrop, 1974; Grossman and Northrop, 1974), while another group (Palka and Pinter, 1974) not finding significant responses below a 1.5° period when an extremely precise pattern was used. The latter group has justified their experimental findings using classical optical theory which treats the receptor and its dioptic apparatus as a simple convex lens with a 33 μm pupil. It is argued in this paper that this is an oversimplification of this system, and that the best model for the dioptrics of a retinula cell is given by its directional sensitivity function (DSF) which is in effect the spatial impulse response of the in vivo system which relates effective absorbed light intensity to the angular position of a point source. A neural model is proposed in this paper which produces improved signal-to-noise ratio (SNR) at detector interneurons over the SNR in the photoreceptors. The model offers noise reduction from averaging at multisynaptic signal transmission points (Laughlin, 1973), and contrast improvement from multiplicative signal processing (MSP). A numerical example is given to illustrate the plausibility of the model, using reasonable values for known and assumed parameters. The model is compatible with known anatomy and physiology in the locust visual system. However, the existance of a presumed exponential synaptic transfer characteristic and operation of the MSP system in vivo remain to be verified experimentally.     

Separate colour-opponent mechanisms underlie the detection and discrimination of moving chromatic targets.

Current opinion holds that human colour vision is mediated primarily via a colour-opponent pathway that carries information about both wavelength and luminance contrast (type I). However, some authors argue that chromatic sensitivity may be limited by a different geniculostriate pathway, which carries information about wavelength alone (type II). We provide psychophysical evidence that both pathways may contribute to the perception of moving, chromatic targets in humans, depending on the nature of the visual discrimination. In experiment 1, we show that adaptation to drifting, red-green stimuli causes reductions in contrast sensitivity for both the detection and direction discrimination of moving chromatic targets. Importantly, the effects of adaptation are not directionally specific. In experiment 2, we show that adaptation to luminance gratings results in reduced sensitivity for the direction discrimination, but not the detection of moving chromatic targets. We suggest that sensitivity for the direction discrimination of chromatic targets is limited by a colour-opponent pathway that also conveys luminance-contrast information, whereas the detection of such targets is limited by a pathway with access to colour information alone. The properties of these pathways are consistent with the known properties of type-I and type-II neurons of the primate parvocellular lateral geniculate nucleus and their cortical projections. These findings may explain the known differences between detection and direction discrimination thresholds for chromatic targets moving at low to moderate velocities.     

A model of the human visual system in its response to certain classes of moving stimuli

The purpose of this study is to construct a functional model of the human visual system in its response to certain classes of moving stimuli.Experimental data are presented describing the interdependence of the input variables, temporal frequency, spatial period, etc., for two constant response states, viz. threshold motion response and threshold flicker response. On the basis of these data, two basic units are isolated, a vertical (V) unit and a horizontal (H) unit. The H-unit is identified with the Reichardt multiplier (Reichardt and Varju, 1959), and the V-unit with the de Lange filter (de Lange, 1954).A definition of the general motion response of the H-units is obtained, and this is then reduced to an expression which may be applied directly to the observed motion response data. By this method, Thorson's simplification of the Reichardt scheme (Thorson, 1966) is adopted for the H-unit and total and relative (population) weighting factors, associated with the H-unit output, are defined.In order to reconcile the theoretical square-wave threshold motion response with the experimental data, Thorson's simplification is modified with the introduction of a low-pass filter on the output. The amended scheme is shown to predict a (temporal) frequency-dependent phase-sensitivity. This prediction is tested experimentally, and its validity indicated.     

Segmentation of moving images by the human visual system

 New segments appearing in an image sequence or spontaneously accelerated segments are band limited by the visual system due to a nonperfect tracking of these segments by eye movements. In spite of this band limitation and acceleration of segments, a coarse segmentation (initial segmentation phase) can be performed by the visual system. This is interesting for the development of purely automatic segmentation algorithms for multimedia applications. In this paper the segmentation of the visual system is modelled and used in an automatic coarse initial segmentation. A suitable model for motion processing based on a spectral representation is presented and applied to the segmentation of synthetic and real image sequences with band limited and accelerated moving foreground and background segments. Received: 1 August 1995/Accepted in revised form: 25 February 1997     

Regulatory roles of microRNAs in insect pests: prospective targets for insect pest control

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A model for visual image-background discrimination by relative movement

Biologically plausible electronic neural network setup for real time processing motion image informa-tion was built. Using this setup the first part of the model was examined and real time discrimination of moving object image was realized from complex background in high resolution. Afterimages may play an important role in filtering moving object image and the aperture problem should be separated into two parts: the first part, i.e. the incomplete filtered moving object image, can be better resolved by parallel integration of multi-channel visual information, howev-er, the second part, i.e. the inaccurate measurement results for movement direction, may only get certain compensa-tion by visual integration.     

A visual model for object detection based on active contours and level-set method

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure–ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.This work was partially supported by Grants-in-Aid for Scientific Research (#14780254) from Japan Society of Promotion of Science.