Distributed dendritic processing facilitates object detection: a computational analysis on the visual system of the fly

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging, and so forth. A good number of motion detectors have been identified in the insects' visual pathways. Computational modeling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. These biological mechanisms through millions of years of evolutionary development will have formed solid modules for constructing dynamic vision systems for future intelligent machines. This article reviews the computational motion perception models originating from biological research on insects' visual systems in the literature. These motion perception models or neural networks consist of the looming-sensitive neuronal models of lobula giant movement detectors (LGMDs) in locusts, the translation-sensitive neural systems of direction-selective neurons (DSNs) in fruit flies, bees, and locusts, and the small-target motion detectors (STMDs) in dragonflies and hoverflies. We also review the applications of these models to robots and vehicles. Through these modeling studies, we summarize the methodologies that generate different direction and size selectivity in motion perception. Finally, we discuss multiple systems integration and hardware realization of these bio-inspired motion perception models.

Monitoring of single-cell responses in the optic tectum of adult zebrafish with dextran-coupled calcium dyes delivered via local electroporation

The zebrafish (Danio rerio) has become one of the major animal models for in vivo examination of sensory and neuronal computation. Similar to Xenopus tadpoles neural activity in the optic tectum, the major region controlling visually guided behavior, can be examined in zebrafish larvae by optical imaging. Prerequisites of these approaches are usually the transparency of larvae up to a certain age and the use of two-photon microscopy. This principle of fluorescence excitation was necessary to suppress crosstalk between signals from individual neurons, which is a critical issue when using membrane-permeant dyes. This makes the equipment to study neuronal processing costly and limits the approach to the study of larvae. Thus there is lack of knowledge about the properties of neurons in the optic tectum of adult animals. We established a procedure to circumvent these problems, enabling in vivo calcium imaging in the optic tectum of adult zebrafish. Following local application of dextran-coupled dyes single-neuron activity of adult zebrafish can be monitored with conventional widefield microscopy, because dye labeling remains restricted to tens of neurons or less. Among the neurons characterized with our technique we found neurons that were selective for a certain pattern orientation as well as neurons that responded in a direction-selective way to visual motion. These findings are consistent with previous studies and indicate that the functional integrity of neuronal circuits in the optic tectum of adult zebrafish is preserved with our staining technique. Overall, our protocol for in vivo calcium imaging provides a useful approach to monitor visual responses of individual neurons in the optic tectum of adult zebrafish even when only widefield microscopy is available. This approach will help to obtain valuable insight into the principles of visual computation in adult vertebrates and thus complement previous work on developing visual circuits.

Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action

Insects such as flies or bees, with their miniature brains, are able to control highly aerobatic flight maneuvres and to solve spatial vision tasks, such as avoiding collisions with obstacles, landing on objects, or even localizing a previously learnt inconspicuous goal on the basis of environmental cues. With regard to solving such spatial tasks, these insects still outperform man-made autonomous flying systems. To accomplish their extraordinary performance, flies and bees have been shown by their characteristic behavioral actions to actively shape the dynamics of the image flow on their eyes ("optic flow"). The neural processing of information about the spatial layout of the environment is greatly facilitated by segregating the rotational from the translational optic flow component through a saccadic flight and gaze strategy. This active vision strategy thus enables the nervous system to solve apparently complex spatial vision tasks in a particularly efficient and parsimonious way. The key idea of this review is that biological agents, such as flies or bees, acquire at least part of their strength as autonomous systems through active interactions with their environment and not by simply processing passively gained information about the world. These agent-environment interactions lead to adaptive behavior in surroundings of a wide range of complexity. Animals with even tiny brains, such as insects, are capable of performing extraordinarily well in their behavioral contexts by making optimal use of the closed action-perception loop. Model simulations and robotic implementations show that the smart biological mechanisms of motion computation and visually-guided flight control might be helpful to find technical solutions, for example, when designing micro air vehicles carrying a miniaturized, low-weight on-board processor.

Neuronal encoding of object and distance information: a model simulation study on naturalistic optic flow processing

We developed a model of the input circuitry of the FD1 cell, an identified motion-sensitive interneuron in the blowfly's visual system. The model circuit successfully reproduces the FD1 cell's most conspicuous property: its larger responses to objects than to spatially extended patterns. The model circuit also mimics the time-dependent responses of FD1 to dynamically complex naturalistic stimuli, shaped by the blowfly's saccadic flight and gaze strategy: the FD1 responses are enhanced when, as a consequence of self-motion, a nearby object crosses the receptive field during intersaccadic intervals. Moreover, the model predicts that these object-induced responses are superimposed by pronounced pattern-dependent fluctuations during movements on virtual test flights in a three-dimensional environment with systematic modifications of the environmental patterns. Hence, the FD1 cell is predicted to detect not unambiguously objects defined by the spatial layout of the environment, but to be also sensitive to objects distinguished by textural features. These ambiguous detection abilities suggest an encoding of information about objects-irrespective of the features by which the objects are defined-by a population of cells, with the FD1 cell presumably playing a prominent role in such an ensemble.

Object representation and distance encoding in three-dimensional environments by a neural circuit in the visual system of the blowfly

Three motion-sensitive key elements of a neural circuit, presumably involved in processing object and distance information, were analyzed with optic flow sequences as experienced by blowflies in a three-dimensional environment. This optic flow is largely shaped by the blowfly's saccadic flight and gaze strategy, which separates translational flight segments from fast saccadic rotations. By modifying this naturalistic optic flow, all three analyzed neurons could be shown to respond during the intersaccadic intervals not only to nearby objects but also to changes in the distance to background structures. In the presence of strong background motion, the three types of neuron differ in their sensitivity for object motion. Object-induced response increments are largest in FD1, a neuron long known to respond better to moving objects than to spatially extended motion patterns, but weakest in VCH, a neuron that integrates wide-field motion from both eyes and, by inhibiting the FD1 cell, is responsible for its object preference. Small but significant object-induced response increments are present in HS cells, which serve both as a major input neuron of VCH and as output neurons of the visual system. In both HS and FD1, intersaccadic background responses decrease with increasing distance to the animal, although much more prominently in FD1. This strong dependence of FD1 on background distance is concluded to be the consequence of the activity of VCH that dramatically increases its activity and, thus, its inhibitory strength with increasing distance.

Binocular integration of visual information: a model study on naturalistic optic flow processing

The computation of visual information from both visual hemispheres is often of functional relevance when solving orientation and navigation tasks. The vCH-cell is a motion-sensitive wide-field neuron in the visual system of the blowfly Calliphora, a model system in the field of optic flow processing. The vCH-cell receives input from various other identified wide-field cells, the receptive fields of which are located in both the ipsilateral and the contralateral visual field. The relevance of this connectivity to the processing of naturalistic image sequences, with their peculiar dynamical characteristics, is still unresolved. To disentangle the contributions of the different input components to the cell's overall response, we used electrophysiologically determined responses of the vCH-cell and its various input elements to tune a model of the vCH-circuit. Their impact on the vCH-cell response could be distinguished by stimulating not only extended parts of the visual field of the fly, but also selected regions in the ipsi- and contralateral visual field with behaviorally generated optic flow. We show that a computational model of the vCH-circuit is able to account for the neuronal activities of the counterparts in the blowfly's visual system. Furthermore, we offer an insight into the dendritic integration of binocular visual input.

A model of visual-olfactory integration for odour localisation in free-flying fruit flies

Flying fruit flies (Drosophila melanogaster) locate a concealed appetitive odour source most accurately in environments containing vertical visual contrasts. To investigate how visuomotor and olfactory responses may be integrated, we examine the free-flight behaviour of flies in three visual conditions, with and without food odour present. While odour localisation is facilitated by uniformly distributed vertical contrast as compared with purely horizontal contrast, localised vertical contrast also facilitates odour localisation, but only if the odour source is situated close to it. We implement a model of visuomotor control consisting of three parallel subsystems: an optomotor response stabilising the model fly's yaw orientation; a collision avoidance system to saccade away from looming obstacles; and a speed regulation system. This model reproduces many of the behaviours we observe in flies, including visually mediated 'rebound' turns following saccades. Using recordings of real odour plumes, we simulate the presence of an odorant in the arena, and investigate ways in which the olfactory input could modulate visuomotor control. We reproduce the experimental results by using the change in odour intensity to regulate the sensitivity of collision avoidance, resulting in visually mediated chemokinesis. Additionally, it is necessary to amplify the optomotor response whenever odour is present, increasing the model fly's tendency to steer towards features of the visual environment. We conclude that visual and olfactory responses of Drosophila are not independent, but that relatively simple interaction between these modalities can account for the observed visual dependence of odour source localisation.

Localized direction selective responses in the dendrites of visual interneurons of the fly

BACKGROUND

The various tasks of visual systems, including course control, collision avoidance and the detection of small objects, require at the neuronal level the dendritic integration and subsequent processing of many spatially distributed visual motion inputs. While much is known about the pooled output in these systems, as in the medial superior temporal cortex of monkeys or in the lobula plate of the insect visual system, the motion tuning of the elements that provide the input has yet received little attention. In order to visualize the motion tuning of these inputs we examined the dendritic activation patterns of neurons that are selective for the characteristic patterns of wide-field motion, the lobula-plate tangential cells (LPTCs) of the blowfly. These neurons are known to sample direction-selective motion information from large parts of the visual field and combine these signals into axonal and dendro-dendritic outputs.

RESULTS

Fluorescence imaging of intracellular calcium concentration allowed us to take a direct look at the local dendritic activity and the resulting local preferred directions in LPTC dendrites during activation by wide-field motion in different directions. These 'calcium response fields' resembled a retinotopic dendritic map of local preferred directions in the receptive field, the layout of which is a distinguishing feature of different LPTCs.

CONCLUSIONS

Our study reveals how neurons acquire selectivity for distinct visual motion patterns by dendritic integration of the local inputs with different preferred directions. With their spatial layout of directional responses, the dendrites of the LPTCs we investigated thus served as matched filters for wide-field motion patterns.