Local and global motion preferences in descending neurons of the fly

For a moving animal, optic flow is an important source of information about its ego-motion. In flies, the processing of optic flow is performed by motion sensitive tangential cells in the lobula plate. Amongst them, cells of the vertical system (VS cells) have receptive fields with similarities to optic flows generated during rotations around different body axes. Their output signals are further processed by pre-motor descending neurons. Here, we investigate the local motion preferences of two descending neurons called descending neurons of the ocellar and vertical system (DNOVS1 and DNOVS2). Using an LED arena subtending 240° × 95° of visual space, we mapped the receptive fields of DNOVS1 and DNOVS2 as well as those of their presynaptic elements, i.e. VS cells 1–10 and V2. The receptive field of DNOVS1 can be predicted in detail from the receptive fields of those VS cells that are most strongly coupled to the cell. The receptive field of DNOVS2 is a combination of V2 and VS cells receptive fields. Predicting the global motion preferences from the receptive field revealed a linear spatial integration in DNOVS1 and a superlinear spatial integration in DNOVS2. In addition, the superlinear integration of V2 output is necessary for DNOVS2 to differentiate between a roll rotation and a lift translation of the fly.     

‘Vector white noise’: a technique for mapping the motion receptive fields of direction-selective visual neurons

A technique is described and tested for mapping the sensitivities and preferred directions of motion at different locations within the receptive fields of direction-selective motion-detecting visual neurons. The procedure is to record the responses to a number of visual stimuli, each stimulus presentation consisting of a set of short, randomly-oriented, moving bars arranged in a square grid. Each bar moves perpendicularly to its long axis. The vector describing the sensitivity and preferred direction of motion at each grid location is obtained as a sum of the unit vectors defining the directions of motion of the bars in each of the stimuli at that location, weighted by the strengths of the corresponding responses. The resulting vector field specifies the optimum flow field for the neuron. The advantage of this technique over the conventional approach of probing the receptive field sequentially at each grid location is that the parallel nature of the stimulus is sensitive to nonlinear interactions (such as shunting inhibition for mutual facilitation) between different regions of the visual field. The technique is used to determine accurately the motion receptive fields of direction-selective motion detecting neurons in the optic lobes of insects. It is potentially applicable to motion-sensitive neurons with highly structured receptive fields, such as those in the optic tectum of the pigeon or in area MST of the monkey.     

Subcellular mapping of dendritic activity in optic flow processing neurons

Dendritic integration is a fundamental element of neuronal information processing. So far, few studies have provided a detailed spatial picture of this process, describing the properties of local dendritic activity and its subcellular organization. Here, we used 2-photon calcium imaging in optic flow processing neurons of the fly Calliphora vicina to determine the preferred location and direction of local motion cues for small branchlets throughout the entire dendrite. We found a pronounced retinotopic mapping on both the subcellular and the cell population level. In addition, dendritic branchlets residing in different layers of the neuropil were tuned to distinct directions of motion. Summing the local receptive fields of all dendritic branchlets reproduced the characteristic properties of these neurons’ axonal output receptive fields. Our results corroborate the notion that the dendritic morphology of vertical system cells allows them to selectively collect local motion inputs with particular directional preferences from a spatially organized input repertoire, thus forming filters that match global patterns of optic flow. Furthermore, we suggest that the facet arrangement across the fly’s eye shapes the subcellular direction tuning to local motion stimuli. These data illustrate a highly structured circuit organization as an efficient way to hard-wire a complex sensory task.     

Visual channels, Hebbian assemblies and the effect of Hebb's rule

 A model of sensory learning is proposed that is based upon Hebb's rule, where Hebb's rule has been generalised by introducing a stabilising function representing some feedback process within or at the adapting (cortical) neuron, preventing synaptic weights from increasing without limit. It will be shown that neurons adapting according to this stabilised Hebb rule will turn into a matched filter for that part of the stimulus pattern that covers the receptive field of a neuron. It follows that the presentation of a stimulus pattern may imply the formation of a set of neurons with overlapping receptive fields, where each neuron has adapted to a certain part of the stimulus. Making simplifying assumptions about the detection process, the model will be illustrated, fitting it to data from Meinhardt and Mortensen [Meinhardt G, Mortensen U (1998) Biol Cybern 79:413–425] which are not compatible with the classical matched filter model introduced by Hauske et al. [Hauske G, Wolf W, Lupp U (1976) Biol Cybern 22:181–188]. Received: 10 May 1999 / Accepted in revised form: 22 October 1999     

Response properties of motion-sensitive visual interneurons in the lobula plate of Drosophila melanogaster

The crystalline-like structure of the optic lobes of the fruit fly Drosophila melanogaster has made them a model system for the study of neuronal cell-fate determination, axonal path finding, and target selection. For functional studies, however, the small size of the constituting visual interneurons has so far presented a formidable barrier. We have overcome this problem by establishing in vivo whole-cell recordings from genetically targeted visual interneurons of Drosophila. Here, we describe the response properties of six motion-sensitive large-field neurons in the lobula plate that form a network consisting of individually identifiable, directionally selective cells most sensitive to vertical image motion (VS cells). Individual VS cell responses to visual motion stimuli exhibit all the characteristics that are indicative of presynaptic input from elementary motion detectors of the correlation type. Different VS cells possess distinct receptive fields that are arranged sequentially along the eye's azimuth, corresponding to their characteristic cellular morphology and position within the retinotopically organized lobula plate. In addition, lateral connections between individual VS cells cause strongly overlapping receptive fields that are wider than expected from their dendritic input. Our results suggest that motion vision in different dipteran fly species is accomplished in similar circuitries and according to common algorithmic rules. The underlying neural mechanisms of population coding within the VS cell network and of elementary motion detection, respectively, can now be analyzed by the combination of electrophysiology and genetic intervention in Drosophila.     

Organization of receptive fields of motion-senstitive neurons in the cat pulvinar

The distribution of 70 visually sensitive neurons in the cat pulvinar sensitive to motion in the receptive fields was studied. The experimental results showed that components with directional characteristics are present in the structure of these fields of both direction-selective and unselective neurons. In the receptive fields of direction-selective neurons the directional elements of the substructure have identical preferred directions, which coincide with the preferred directions of response to stimulus movement over the entire receptive field. The organization of receptive fields of direction-selective neurons of the visual association structure thus does not differ significantly from that of analogous fields of visual projection neurons. Directional elements of the receptive fields of direction-unselective neurons were found to have different preferred directions, thereby providing a basis for organization of the nondirectional response of the neuron to a stimulus moving across the entire receptive field.L. A. Orbeli Institute of Physiology, Academy of Sciences of the Armenian SSR, Erevan. Translated from Neirofiziologiya, Vol. 14, No. 4, pp. 339–346, July–August, 1982.     

Neural action fields for optic flow based navigation: a simulation study of the fly lobula plate network

Optic flow based navigation is a fundamental way of visual course control described in many different species including man. In the fly, an essential part of optic flow analysis is performed in the lobula plate, a retinotopic map of motion in the environment. There, the so-called lobula plate tangential cells possess large receptive fields with different preferred directions in different parts of the visual field. Previous studies demonstrated an extensive connectivity between different tangential cells, providing, in principle, the structural basis for their large and complex receptive fields. We present a network simulation of the tangential cells, comprising most of the neurons studied so far (22 on each hemisphere) with all the known connectivity between them. On their dendrite, model neurons receive input from a retinotopic array of Reichardt-type motion detectors. Model neurons exhibit receptive fields much like their natural counterparts, demonstrating that the connectivity between the lobula plate tangential cells indeed can account for their complex receptive field structure. We describe the tuning of a model neuron to particular types of ego-motion (rotation as well as translation around/along a given body axis) by its 'action field'. As we show for model neurons of the vertical system (VS-cells), each of them displays a different type of action field, i.e., responds maximally when the fly is rotating around a particular body axis. However, the tuning width of the rotational action fields is relatively broad, comparable to the one with dendritic input only. The additional intra-lobula-plate connectivity mainly reduces their translational action field amplitude, i.e., their sensitivity to translational movements along any body axis of the fly.     

Insect-Inspired Self-Motion Estimation with Dense Flow Fields—An Adaptive Matched Filter Approach

The control of self-motion is a basic, but complex task for both technical and biological systems. Various algorithms have been proposed that allow the estimation of self-motion from the optic flow on the eyes. We show that two apparently very different approaches to solve this task, one technically and one biologically inspired, can be transformed into each other under certain conditions. One estimator of self-motion is based on a matched filter approach; it has been developed to describe the function of motion sensitive cells in the fly brain. The other estimator, the Koenderink and van Doorn (KvD) algorithm, was derived analytically with a technical background. If the distances to the objects in the environment can be assumed to be known, the two estimators are linear and equivalent, but are expressed in different mathematical forms. However, for most situations it is unrealistic to assume that the distances are known. Therefore, the depth structure of the environment needs to be determined in parallel to the self-motion parameters and leads to a non-linear problem. It is shown that the standard least mean square approach that is used by the KvD algorithm leads to a biased estimator. We derive a modification of this algorithm in order to remove the bias and demonstrate its improved performance by means of numerical simulations. For self-motion estimation it is beneficial to have a spherical visual field, similar to many flying insects. We show that in this case the representation of the depth structure of the environment derived from the optic flow can be simplified. Based on this result, we develop an adaptive matched filter approach for systems with a nearly spherical visual field. Then only eight parameters about the environment have to be memorized and updated during self-motion.     

Responses of optokinetic neurons in the pretectum and accessory optic system of the pigeon to large-field plaids

The accessory optic system and pretectum are highly conserved brainstem visual pathways that process the visual consequences of self-motion (i.e. optic flow) and generate the optokinetic response. Neurons in these nuclei have very large receptive fields in the contalateral eye, and exhibit direction-selectivity to large-field moving stimuli. Previous research on visual motion pathways in the geniculostriate system has employed "plaids" composed of two non-parallel sine-wave gratings to investigate the visual system's ability to detect the global direction of pattern motion as opposed to the direction of motion of the components within the plaids. In this study, using standard extracellular techniques, we recorded the responses of 47 neurons in the nucleus of the basal optic root of the accessory optic system and 49 cells in the pretectal nucleus lentiformis mesencephali of pigeons to large-field gratings and plaids. We found that most neurons were classified as pattern-selective (41-49%) whereas fewer were classified as component-selective (8-17%). There were no striking differences between nucleus of the basal optic root and lentiformis mesencephali neurons in this regard. These data indicate that most of the input to the optokinetic system is orientation-insensitive but a small proportion is orientation-selective. The implications for the connectivity of the motion processing system are discussed.     

Responses of blowfly motion-sensitive neurons to reconstructed optic flow along outdoor flight paths

The retinal image flow a blowfly experiences in its daily life on the wing is determined by both the structure of the environment and the animal’s own movements. To understand the design of visual processing mechanisms, there is thus a need to analyse the performance of neurons under natural operating conditions. To this end, we recorded flight paths of flies outdoors and reconstructed what they had seen, by moving a panoramic camera along exactly the same paths. The reconstructed image sequences were later replayed on a fast, panoramic flight simulator to identified, motion sensitive neurons of the so-called horizontal system (HS) in the lobula plate of the blowfly, which are assumed to extract self-motion parameters from optic flow. We show that under real life conditions HS-cells not only encode information about self-rotation, but are also sensitive to translational optic flow and, thus, indirectly signal information about the depth structure of the environment. These properties do not require an elaboration of the known model of these neurons, because the natural optic flow sequences generate—at least qualitatively—the same depth-related response properties when used as input to a computational HS-cell model and to real neurons.     

Golgi analysis of tangential neurons in the lobula plate of<Emphasis Type="Italic">Drosophila melanogaster</Emphasis>

The lobula plate (LP), which is the third order optic neuropil of flies, houses wide-field neurons which are exquisitely sensitive to motion. Among Diptera, motion-sensitive neurons of larger flies have been studied at the anatomical and physiological levels. However, the neurons ofDrosophila lobula plate are relatively less explored. AsDrosophila permits a genetic analysis of neural functions, we have analysed the organization of lobula plate ofDrosophila melanogaster. Neurons belonging to eight anatomical classes have been observed in the present study. Three neurons of the horizontal system (HS) have been visualized. The HS north (HSN) neuron, occupying the dorsal lobula plate is stunted in its geometry compared to that of larger flies. Associated with the HS neurons, thinner horizontal elements known as h-cells have also been visualized in the present study. Five of the six known neurons of the vertical system (VS) have been visualized. Three additional neurons in the proximal LP comparable in anatomy to VS system have been stained. We have termed them as additional VS AVS)-like neurons. Three thinner tangential cells that are comparable to VS neurons, which are elements of twin vertical system (tvs); and two cells with wide dendritic fields comparable to CH neurons of Diptera have been also observed. Neurons comparable to VS cells but with ‘tufted’ dendrites have been stained. The HSN and VS1-VS2 neurons are dorsally stunted. This is possibly due to the shape of the compound eye ofDrosophila which is reduced in the fronto-dorsal region as compared to larger flies     

Responses of nervous elements of the visual cortex of the chipmunk Eutamias sibiricus to moving and stationary stimuli]

The receptive field organization of cortical units has been studied in experiments with testing by moving and stationary light spots. The size of the receptive fields varied from 3 degrees to 10 degrees. Receptive fields which were tested by a stationary light spot exhibited various types of organization. Some of the neurons produced extensive excitatory on- and off-responses to stimulation by a light spot. Neuronal excitation evoked by light decreased if the stimulus was near the field boundary. Some of the neurons produced either on- or off-responses in any point of the receptive field. A small part of neurons had receptive fields with on- and off-reactions in the center, and either on- or off-responses at the peripheral zones. Most of the neurons exhibited specialization with respect to high-speed motion.     

Orientation tuning of motion-sensitive neurons shaped by vertical-horizontal network interactions

We measured the orientation tuning of two neurons of the fly lobula plate (H1 and H2 cells) sensitive to horizontal image motion. Our results show that H1 and H2 cells are sensitive to vertical motion, too. Their response depended on the position of the vertically moving stimuli within their receptive field. Stimulation within the frontal receptive field produced an asymmetric response: upward motion left the H1/H2 spike frequency nearly unaltered while downward motion increased the spike frequency to about 40% of their maximum responses to horizontal motion. In the lateral parts of their receptive fields, no such asymmetry in the responses to vertical image motion was found. Since downward motion is known to be the preferred direction of neurons of the vertical system in the lobula plate, we analyzed possible interactions between vertical system cells and H1 and H2 cells. Depolarizing current injection into the most frontal vertical system cell (VS1) led to an increased spike frequency, hyperpolarizing current injection to a decreased spike frequency in both H1 and H2 cells. Apart from VS1, no other vertical system cell (VS2-8) had any detectable influence on either H1 or H2 cells. The connectivity of VS1 and H1/H2 is also shown to influence the response properties of both centrifugal horizontal cells in the contralateral lobula plate, which are known to be postsynaptic to the H1 and H2 cells. The vCH cell receives additional input from the contralateral VS2-3 cells via the spiking interneuron V1.     

Pattern-dependent response modulations in motion-sensitive visual interneurons--a model study

Even if a stimulus pattern moves at a constant velocity across the receptive field of motion-sensitive neurons, such as lobula plate tangential cells (LPTCs) of flies, the response amplitude modulates over time. The amplitude of these response modulations is related to local pattern properties of the moving retinal image. On the one hand, pattern-dependent response modulations have previously been interpreted as 'pattern-noise', because they deteriorate the neuron's ability to provide unambiguous velocity information. On the other hand, these modulations might also provide the system with valuable information about the textural properties of the environment. We analyzed the influence of the size and shape of receptive fields by simulations of four versions of LPTC models consisting of arrays of elementary motion detectors of the correlation type (EMDs). These models have previously been suggested to account for many aspects of LPTC response properties. Pattern-dependent response modulations decrease with an increasing number of EMDs included in the receptive field of the LPTC models, since spatial changes within the visual field are smoothed out by the summation of spatially displaced EMD responses. This effect depends on the shape of the receptive field, being the more pronounced--for a given total size--the more elongated the receptive field is along the direction of motion. Large elongated receptive fields improve the quality of velocity signals. However, if motion signals need to be localized the velocity coding is only poor but the signal provides--potentially useful--local pattern information. These modelling results suggest that motion vision by correlation type movement detectors is subject to uncertainty: you cannot obtain both an unambiguous and a localized velocity signal from the output of a single cell. Hence, the size and shape of receptive fields of motion sensitive neurons should be matched to their potential computational task.     

Object segmentation model: analytical results and biological implications

 A simple, biologically motivated neural network for segmentation of a moving object from a visual scene is presented. The model consists of two parts: an object selection model which employs a scaling approach for receptive field sizes, and a subsequent network implementing a spotlight by means of multiplicative synapses. The network selects one object out of several, segments the rough contour of the object, and encodes the winner object's position with high accuracy. Analytical equations for the performance level of the network, e.g., for the critical distance of two objects above which they are perceived as separate, are derived. The network preferentially chooses the object with the largest angular velocity and the largest angular width. An equation for the velocity and width preferences is presented. Additionally it is shown that for certain neurons of the model, flat receptive fields are more favourable than Gaussian ones. The network exhibits performances similar to those known from amphibians. Various electrophysiological and behavioral results – e.g., the distribution of the diameters of the receptive fields of tectal neurons, of the tongue-projecting salamander Hydromantes italicus and the range of optimal prey velocities for prey catching – can be understood on the basis of the model. Received: 7 December 2000 / Accepted: 13 February 2001     

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.     

Saccadic flight strategy facilitates collision avoidance: closed-loop performance of a cyberfly

Behavioural and electrophysiological experiments suggest that blowflies employ an active saccadic strategy of flight and gaze control to separate the rotational from the translational optic flow components. As a consequence, this allows motion sensitive neurons to encode during translatory intersaccadic phases of locomotion information about the spatial layout of the environment. So far, it has not been clear whether and how a motor controller could decode the responses of these neurons to prevent a blowfly from colliding with obstacles. Here we propose a simple model of the blowfly visual course control system, named cyberfly, and investigate its performance and limitations. The sensory input module of the cyberfly emulates a pair of output neurons subserving the two eyes of the blowfly visual motion pathway. We analyse two sensory–motor interfaces (SMI). An SMI coupling the differential signal of the sensory neurons proportionally to the yaw rotation fails to avoid obstacles. A more plausible SMI is based on a saccadic controller. Even with sideward drift after saccades as is characteristic of real blowflies, the cyberfly is able to successfully avoid collisions with obstacles. The relative distance information contained in the optic flow during translatory movements between saccades is provided to the SMI by the responses of the visual output neurons. An obvious limitation of this simple mechanism is its strong dependence on the textural properties of the environment.     

A Unified Model of Heading and Path Perception in Primate MSTd

Self-motion, steering, and obstacle avoidance during navigation in the real world require humans to travel along curved paths. Many perceptual models have been proposed that focus on heading, which specifies the direction of travel along straight paths, but not on path curvature, which humans accurately perceive and is critical to everyday locomotion. In primates, including humans, dorsal medial superior temporal area (MSTd) has been implicated in heading perception. However, the majority of MSTd neurons respond optimally to spiral patterns, rather than to the radial expansion patterns associated with heading. No existing theory of curved path perception explains the neural mechanisms by which humans accurately assess path and no functional role for spiral-tuned cells has yet been proposed. Here we present a computational model that demonstrates how the continuum of observed cells (radial to circular) in MSTd can simultaneously code curvature and heading across the neural population. Curvature is encoded through the spirality of the most active cell, and heading is encoded through the visuotopic location of the center of the most active cell''s receptive field. Model curvature and heading errors fit those made by humans. Our model challenges the view that the function of MSTd is heading estimation, based on our analysis we claim that it is primarily concerned with trajectory estimation and the simultaneous representation of both curvature and heading. In our model, temporal dynamics afford time-history in the neural representation of optic flow, which may modulate its structure. This has far-reaching implications for the interpretation of studies that assume that optic flow is, and should be, represented as an instantaneous vector field. Our results suggest that spiral motion patterns that emerge in spatio-temporal optic flow are essential for guiding self-motion along complex trajectories, and that cells in MSTd are specifically tuned to extract complex trajectory estimation from flow.     

Tuned solutions in dynamic neural fields as building blocks for extended EEG models

The most prominent functional property of cortical neurons in sensory areas are their tuned receptive fields which provide specific responses of the neurons to external stimuli. Tuned neural firing indeed reflects the most basic and best worked out level of cognitive representations. Tuning properties can be dynamic on a short time-scale of fractions of a second. Such dynamic effects have been modeled by localised solutions (also called “bumps” or “peaks”) in dynamic neural fields. In the present work we develop an approximation method to reduce the dynamics of localised activation peaks in systems of n coupled nonlinear d-dimensional neural fields with transmission delays to a small set of delay differential equations for the peak amplitudes and widths only. The method considerably simplifies the analysis of peaked solutions as demonstrated for a two-dimensional example model of neural feature selectivity in the brain. The reduced equations describe the effective interaction between pools of local neurons of several (n) classes that participate in shaping the dynamic receptive field responses. To lowest order they resemble neural mass models as they often form the base of EEG-models. Thereby they provide a link between functional small-scale receptive field models and more coarse-grained EEG-models. More specifically, they connect the dynamics in feature-selective cortical microcircuits to the more abstract local elements used in coarse-grained models. However, beside amplitudes the reduced equations also reflect the sharpness of tuning of the activity in a d-dimensional feature space in response to localised stimuli.     

Distribution of auditory motion-direction sensitive neurons in the barn owl's midbrain

Barn owls have neurons sensitive to acoustic motion-direction in the midbrain. We report here that acoustic motion-direction sensitive neurons with receptive-field centres in frontal auditory space are not randomly distributed. In the inferior colliculus and optic tectum in the left (right) brain, the responses of about two-thirds of the motion-direction sensitive neurons were sensitive to clockwise (counter-clockwise) motion. The midbrain contains maps of auditory space that represent about 15 degrees of ipsilateral and all of contralateral space. Since a similar bias in motion-direction sensitivity was observed for neurons with receptive-field centres in ipsilateral as well as for neurons with receptive fields centres in contralateral auditory space, the brain side at which a motion-direction sensitive neuron was recorded was a more important predictor for the preferred direction of a cell than the spatial direction of the centre of the receptive field. Within one dorso-ventral electrode pass motion-direction sensitivity typically stayed constant suggesting a clustered or even a columnar-like organization. We hypothesize from these distributions that the right brain is important for orientating movements to the left hemisphere and vice versa.