Progress in the use of genetic methods to study insect behavior outside Drosophila

In the span of a decade we have seen a rapid progress in the application of genetic tools and genome editing approaches in ‘non-model’ insects. It is now possible to target sensory receptor genes and neurons, explore their functional roles and manipulate behavioral responses in these insects. In this review, we focus on the latest examples from Diptera, Lepidoptera and Hymenoptera of how applications of genetic tools advanced our understanding of diverse behavioral phenomena. We further discuss genetic methods that could be applied to study insect behavior in the future

Head movements and the optic flow generated during the learning flights of bumblebees.

This is the final version of the article. Available from the publisher via the DOI in this recordInsects inform themselves about the 3D structure of their surroundings through motion parallax. During flight, they often simplify this task by minimising rotational image movement. Coordinated head and body movements generate rapid shifts of gaze separated by periods of almost zero rotational movement, during which the distance of objects from the insect can be estimated through pure translational optic flow. This saccadic strategy is less appropriate for assessing the distance between objects. Bees and wasps face this problem when learning the position of their nest-hole relative to objects close to it. They acquire the necessary information during specialised flights performed on leaving the nest. Here, we show that the bumblebee's saccadic strategy differs from other reported cases. In the fixations between saccades, a bumblebee's head continues to turn slowly, generating rotational flow. At specific points in learning flights these imperfect fixations generate a form of 'pivoting parallax', which is centred on the nest and enhances the visibility of features near the nest. Bumblebees may thus utilize an alternative form of motion parallax to that delivered by the standard 'saccade and fixate' strategy in which residual rotational flow plays a role in assessing the distances of objects from a focal point of interest.Financial support came from the EPSRC, Biotechnology and Biological Sciences Research Council (BBSRC) and The Leverhulme Trust. O.R. was supported by the Overseas Researc

A Model for Detection of Angular Velocity of Image Motion Based on the Temporal Tuning of the Drosophila

We propose a new bio-plausible model based on the visual systems of Drosophila for estimating angular velocity of image motion in insects’ eyes. The model implements both preferred direction motion enhancement and non-preferred direction motion suppression which is discovered in Drosophila’s visual neural circuits recently to give a stronger directional selectivity. In addition, the angular velocity detecting model (AVDM) produces a response largely independent of the spatial frequency in grating experiments which enables insects to estimate the flight speed in cluttered environments. This also coincides with the behaviour experiments of honeybee flying through tunnels with stripes of different spatial frequencies

Constant Angular Velocity Regulation for Visually Guided Terrain Following

Insects use visual cues to control their flight behaviours. By estimating the angular velocity of the visual stimuli and regulating it to a constant value, honeybees can perform a terrain following task which keeps the certain height above the undulated ground. For mimicking this behaviour in a bio-plausible computation structure, this paper presents a new angular velocity decoding model based on the honeybee's behavioural experiments. The model consists of three parts, the texture estimation layer for spatial information extraction, the motion detection layer for temporal information extraction and the decoding layer combining information from pervious layers to estimate the angular velocity. Compared to previous methods on this field, the proposed model produces responses largely independent of the spatial frequency and contrast in grating experiments. The angular velocity based control scheme is proposed to implement the model into a bee simulated by the game engine Unity. The perfect terrain following above patterned ground and successfully flying over irregular textured terrain show its potential for micro unmanned aerial vehicles' terrain following

Strategies of the honeybee Apis mellifera during visual search for vertical targets presented at various heights: a role for spatial attention?

When honeybees are presented with a colour discrimination task, they tend to choose swiftly and accurately when objects are presented in the ventral part of their frontal visual field. In contrast, poor performance is observed when objects appear in the dorsal part. Here we investigate if this asymmetry is caused by fixed search patterns or if bees can use alternative search mechanisms such as spatial attention, which allows flexible focusing on different areas of the visual field. We asked individual honeybees to choose an orange rewarded target among blue distractors. Target and distractors were presented in the ventral visual field, the dorsal field or both. Bees presented with targets in the ventral visual field consistently had the highest search efficiency, with rapid decisions, high accuracy and direct flight paths. In contrast, search performance for dorsally located targets was inaccurate and slow at the beginning of the test phase, but bees increased their search performance significantly after a few learning trials: they found the target faster, made fewer errors and flew in a straight line towards the target. However, bees needed thrice as long to improve the search for a dorsally located target when the target's position changed randomly between the ventral and the dorsal visual field. We propose that honeybees form expectations of the location of the target's appearance and adapt their search strategy accordingly. Different possible mechanisms of this behavioural adaptation are discussed.L.M. was recipient of a DOC-fFORTE fellowship of the Austrian Academy of Science at the Department of Integrative Zoology, University of Vienna. L.C. is supported by an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award

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