Synaptic interactions increase optic flow specificity

Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research

Polarisation vision is commonplace among invertebrates; however, most experiments focus on determining behavioural and/or neurophysiological responses to static polarised light sources rather than moving patterns of polarised light. To address the latter, we designed a polarisation stimulation device based on superimposing polarised and non-polarised images from two projectors, which can display moving patterns at frame rates exceeding invertebrate flicker fusion frequencies. A linear polariser fitted to one projector enables moving patterns of polarised light to be displayed, whilst the other projector contributes arbitrary intensities of non-polarised light to yield moving patterns with a defined polarisation and intensity contrast. To test the device, we measured receptive fields of polarisation-sensitive Argynnis paphia butterfly photoreceptors for both non-polarised and polarised light. We then measured local motion sensitivities of the optic flow-sensitive lobula plate tangential cell H1 in Calliphora vicina blowflies under both polarised and non-polarised light, finding no polarisation sensitivity in this neuron.

Summary: Design of a versatile visual stimulation device for presenting moving patterns of polarised light, and demonstration of its use to characterise polarisation sensitivity in butterfly photoreceptors and blowfly motion-sensitive interneurons.

Motion as a source of environmental information: a fresh view on biological motion computation by insect brains

Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around ("optic flow") to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and-in many behavioral contexts-less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism.

Depth information in natural environments derived from optic flow by insect motion detection system: a model analysis

Knowing the depth structure of the environment is crucial for moving animals in many behavioral contexts, such as collision avoidance, targeting objects, or spatial navigation. An important source of depth information is motion parallax. This powerful cue is generated on the eyes during translatory self-motion with the retinal images of nearby objects moving faster than those of distant ones. To investigate how the visual motion pathway represents motion-based depth information we analyzed its responses to image sequences recorded in natural cluttered environments with a wide range of depth structures. The analysis was done on the basis of an experimentally validated model of the visual motion pathway of insects, with its core elements being correlation-type elementary motion detectors (EMDs). It is the key result of our analysis that the absolute EMD responses, i.e., the motion energy profile, represent the contrast-weighted nearness of environmental structures during translatory self-motion at a roughly constant velocity. In other words, the output of the EMD array highlights contours of nearby objects. This conclusion is largely independent of the scale over which EMDs are spatially pooled and was corroborated by scrutinizing the motion energy profile after eliminating the depth structure from the natural image sequences. Hence, the well-established dependence of correlation-type EMDs on both velocity and textural properties of motion stimuli appears to be advantageous for representing behaviorally relevant information about the environment in a computationally parsimonious way.

Cooperative integration and representation underlying bilateral network of fly motion-sensitive neurons

How is binocular motion information integrated in the bilateral network of wide-field motion-sensitive neurons, called lobula plate tangential cells (LPTCs), in the visual system of flies? It is possible to construct an accurate model of this network because a complete picture of synaptic interactions has been experimentally identified. We investigated the cooperative behavior of the network of horizontal LPTCs underlying the integration of binocular motion information and the information representation in the bilateral LPTC network through numerical simulations on the network model. First, we qualitatively reproduced rotational motion-sensitive response of the H2 cell previously reported in vivo experiments and ascertained that it could be accounted for by the cooperative behavior of the bilateral network mainly via interhemispheric electrical coupling. We demonstrated that the response properties of single H1 and Hu cells, unlike H2 cells, are not influenced by motion stimuli in the contralateral visual hemi-field, but that the correlations between these cell activities are enhanced by the rotational motion stimulus. We next examined the whole population activity by performing principal component analysis (PCA) on the population activities of simulated LPTCs. We showed that the two orthogonal patterns of correlated population activities given by the first two principal components represent the rotational and translational motions, respectively, and similar to the H2 cell, rotational motion produces a stronger response in the network than does translational motion. Furthermore, we found that these population-coding properties are strongly influenced by the interhemispheric electrical coupling. Finally, to test the generality of our conclusions, we used a more simplified model and verified that the numerical results are not specific to the network model we constructed.

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.

Octopaminergic modulation of contrast gain adaptation in fly visual motion-sensitive neurons

Locomotor activity like walking or flying has recently been shown to alter visual processing in several species. In insects, the neuromodulator octopamine is thought to play an important role in mediating state changes during locomotion of the animal [K.D. Longden & H.G. Krapp (2009) J. Neurophysiol., 102, 3606-3618; (2010) Front. Syst. Neurosci., 4, 153; S.N. Jung et al. (2011)J. Neurosci., 31, 9231-9237]. Here, we used the octopamine agonist chlordimeform (CDM) to mimic effects of behavioural state changes on visual motion processing. We recorded from identified motion-sensitive visual interneurons in the lobula plate of the blowfly Calliphora vicina. In these neurons, which are thought to be involved in visual guidance of locomotion, motion adaptation leads to a prominent attenuation of contrast sensitivity. Following CDM application, the neurons maintained high contrast sensitivity in the adapted state. This modulation of contrast gain adaptation was independent of the activity of the recorded neurons, because it was also present after stimulation with visual motion that did not result in deviations from the neurons' resting activity. We conclude that CDM affects presynaptic inputs of the recorded neurons. Accordingly, the effect of CDM was weak when adapting and test stimuli were presented in different parts of the receptive field, stimulating separate populations of local presynaptic neurons. In the peripheral visual system adaptation depends on the temporal frequency of the stimulus pattern and is therefore related to pattern velocity. Contrast gain adaptation could therefore be the basis for a shift in the velocity tuning that was previously suggested to contribute to state-dependent processing of visual motion information in the lobula plate interneurons.

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 interactions underlying the classic optomotor responses of flying flies

In response to imposed course deviations, the optomotor reactions of animals reduce motion blur and facilitate the maintenance of stable body posture. In flies, many anatomical and electrophysiological studies suggest that disparate motion cues stimulating the left and right eyes are not processed in isolation but rather are integrated in the brain to produce a cohesive panoramic percept. To investigate the strength of such inter-ocular interactions and their role in compensatory sensory–motor transformations, we utilize a virtual reality flight simulator to record wing and head optomotor reactions by tethered flying flies in response to imposed binocular rotation and monocular front-to-back and back-to-front motion. Within a narrow range of stimulus parameters that generates large contrast insensitive optomotor responses to binocular rotation, we find that responses to monocular front-to-back motion are larger than those to panoramic rotation, but are contrast sensitive. Conversely, responses to monocular back-to-front motion are slower than those to rotation and peak at the lowest tested contrast. Together our results suggest that optomotor responses to binocular rotation result from the influence of non-additive contralateral inhibitory as well as excitatory circuit interactions that serve to confer contrast insensitivity to flight behaviors influenced by rotatory optic flow.

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.

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.

Octopaminergic modulation of temporal frequency coding in an identified optic flow-processing interneuron

Flying generates predictably different patterns of optic flow compared with other locomotor states. A sensorimotor system tuned to rapid responses and a high bandwidth of optic flow would help the animal to avoid wasting energy through imprecise motor action. However, neural processing that covers a higher input bandwidth itself comes at higher energetic costs which would be a poor investment when the animal was not flying. How does the blowfly adjust the dynamic range of its optic flow-processing neurons to the locomotor state? Octopamine (OA) is a biogenic amine central to the initiation and maintenance of flight in insects. We used an OA agonist chlordimeform (CDM) to simulate the widespread OA release during flight and recorded the effects on the temporal frequency coding of the H2 cell. This cell is a visual interneuron known to be involved in flight stabilization reflexes. The application of CDM resulted in (i) an increase in the cell's spontaneous activity, expanding the inhibitory signaling range (ii) an initial response gain to moving gratings (20-60 ms post-stimulus) that depended on the temporal frequency of the grating and (iii) a reduction in the rate and magnitude of motion adaptation that was also temporal frequency-dependent. To our knowledge, this is the first demonstration that the application of a neuromodulator can induce velocity-dependent alterations in the gain of a wide-field optic flow-processing neuron. The observed changes in the cell's response properties resulted in a 33% increase of the cell's information rate when encoding random changes in temporal frequency of the stimulus. The increased signaling range and more rapid, longer lasting responses employed more spikes to encode each bit, and so consumed a greater amount of energy. It appears that for the fly investing more energy in sensory processing during flight is more efficient than wasting energy on under-performing motor control.

Processing of horizontal optic flow in three visual interneurons of the Drosophila brain

Motion vision is essential for navigating through the environment. Due to its genetic amenability, the fruit fly Drosophila has been serving for a lengthy period as a model organism for studying optomotor behavior as elicited by large-field horizontal motion. However, the neurons underlying the control of this behavior have not been studied in Drosophila so far. Here we report the first whole cell recordings from three cells of the horizontal system (HSN, HSE, and HSS) in the lobula plate of Drosophila. All three HS cells are tuned to large-field horizontal motion in a direction-selective way; they become excited by front-to-back motion and inhibited by back-to-front motion in the ipsilateral field of view. The response properties of HS cells such as contrast and velocity dependence are in accordance with the correlation-type model of motion detection. Neurobiotin injection suggests extensive coupling among ipsilateral HS cells and additional coupling to tangential cells that have their dendrites in the contralateral hemisphere of the brain. This connectivity scheme accounts for the complex layout of their receptive fields and explains their sensitivity both to ipsilateral and to contralateral motion. Thus the main response properties of Drosophila HS cells are strikingly similar to the responses of their counterparts in the blowfly Calliphora, although we found substantial differences with respect to their dendritic structure and connectivity. This long-awaited functional characterization of HS cells in Drosophila provides the basis for the future dissection of optomotor behavior and the underlying neural circuitry by combining genetics, physiology, and behavior.

Nonlinear integration of binocular optic flow by DNOVS2, a descending neuron of the fly

For visual orientation and course stabilization, flies rely heavily on the optic flow perceived by the animal during flight. The processing of optic flow is performed in motion-sensitive tangential cells of the lobula plate, which are well described with respect to their visual response properties and the connectivity among them. However, little is known about the postsynaptic descending neurons, which convey motion information to the motor circuits in the thoracic ganglion. Here we investigate the physiology and connectivity of an identified premotor descending neuron, called DNOVS2 (for descending neuron of the ocellar and vertical system). We find that DNOVS2 is tuned in a supralinear way to rotation around the longitudinal body axis. Experiments involving stimulation of the ipsilateral and the contralateral eye indicate that ipsilateral computation of motion information is modified nonlinearly by motion information from the contralateral eye. Performing double recordings of DNOVS2 and lobula plate tangential cells, we find that DNOVS2 is connected ipsilaterally to a subset of vertical-sensitive cells. From the contralateral eye, DNOVS2 receives input most likely from V2, a heterolateral spiking neuron. This specific neural circuit is sufficient for the tuning of DNOVS2, making it probably an important element in optomotor roll movements of the head and body around the fly's longitudinal axis.

Reciprocal inhibitory connections within a neural network for rotational optic-flow processing

Neurons in the visual system of the blowfly have large receptive fields that are selective for specific optic flow fields. Here, we studied the neural mechanisms underlying flow–field selectivity in proximal Vertical System (VS)-cells, a particular subset of tangential cells in the fly. These cells have local preferred directions that are distributed such as to match the flow field occurring during a rotation of the fly. However, the neural circuitry leading to this selectivity is not fully understood. Through dual intracellular recordings from proximal VS cells and other tangential cells, we characterized the specific wiring between VS cells themselves and between proximal VS cells and horizontal sensitive tangential cells. We discovered a spiking neuron (Vi) involved in this circuitry that has not been described before. This neuron turned out to be connected to proximal VS cells via gap junctions and, in addition, it was found to be inhibitory onto VS1.

Integration of lobula plate output signals by DNOVS1, an identified premotor descending neuron

Many motion-sensitive tangential cells of the lobula plate in blowflies are well described with respect to their visual response properties and the connectivity among them. They have large and complex receptive fields with different preferred directions in different parts of their receptive fields matching the optic flow that occurs during various flight maneuvers. However, much less is known about how tangential cells connect to postsynaptic neurons descending to the motor circuits in the thoracic ganglion and how optic flow is represented in these downstream neurons. Here we describe the physiology and the connectivity of a prominent descending neuron called DNOVS1 (for descending neurons of the ocellar and vertical system). We find that DNOVS1 is electrically coupled to a subset of vertical system cells. The specific wiring leads to a preference of DNOVS1 for rotational flow fields around a particular body axis. In addition, DNOVS1 receives input from interneurons connected to the ocelli.

Nonlinear, binocular interactions underlying flow field selectivity of a motion-sensitive neuron

Neurons in many species have large receptive fields that are selective for specific optic flow fields. Here, we studied the neural mechanisms underlying flow field selectivity in lobula plate tangential cells (LPTCs) of the blowfly. Among these cells, the H2 cell responds preferentially to visual stimuli approximating rotational optic flow. Through double recordings from H2 and many other LPTCs, we characterized a bidirectional commissural pathway that allows visual information to be shared between the hemispheres. This pathway is mediated by axo-axonal electrical coupling of H2 and the horizontal system equatorial (HSE) cell located in the opposite hemisphere. Using single-cell ablations, we found that this pathway is sufficient to allow H2 to amplify and attenuate dendritic input during binocular visual stimuli. This is accomplished through a modulation of H2's membrane potential by input from the contralateral HSE cell, which scales the firing rate of H2 during visual stimulation but is not sufficient to induce action potentials.

Encoding of Naturalistic Optic Flow by a Population of Blowfly Motion-Sensitive Neurons

In sensory systems information is encoded by the activity of populations of neurons. To analyze the coding properties of neuronal populations sensory stimuli have usually been used that were much simpler than those encountered in real life. It has been possible only recently to stimulate visual interneurons of the blowfly with naturalistic visual stimuli reconstructed from eye movements measured during free flight. Therefore we now investigate with naturalistic optic flow the coding properties of a small neuronal population of identified visual interneurons in the blowfly, the so-called VS and HS neurons. These neurons are motion sensitive and directionally selective and are assumed to extract information about the animal's self-motion from optic flow. We could show that neuronal responses of VS and HS neurons are mainly shaped by the characteristic dynamical properties of the fly's saccadic flight and gaze strategy. Individual neurons encode information about both the rotational and the translational components of the animal's self-motion. Thus the information carried by individual neurons is ambiguous. The ambiguities can be reduced by considering neuronal population activity. The joint responses of different subpopulations of VS and HS neurons can provide unambiguous information about the three rotational and the three translational components of the animal's self-motion and also, indirectly, about the three-dimensional layout of the environment.

Representation of behaviourally relevant information by blowfly motion-sensitive visual interneurons requires precise compensatory head movements

Flying blowflies shift their gaze by saccadic turns of body and head, keeping their gaze basically fixed between saccades. For the head, this results in almost pure translational optic flow between saccades, enabling visual interneurons in the fly motion pathway to extract information about translation of the animal and thereby about the spatial layout of the environment. There are noticeable differences between head and body movements during flight. Head saccades are faster and shorter than body saccades, and the head orientation is more stable between saccades than the body orientation. Here, we analyse the functional importance of these differences by probing visual interneurons of the blowfly motion pathway with optic flow based on either head movements or body movements, as recorded accurately with a magnetic search coil technique. We find that the precise head-body coordination is essential for the visual system to separate the translational from the rotational optic flow. If the head were tightly coupled to the body, the resulting optic flow would not contain the behaviourally important information on translation. Since it is difficult to resolve head orientation in many experimental paradigms, even when employing state-of-the-art digital video techniques, we introduce a 'headifying algorithm', which transforms the time-dependent body orientation in free flight into an estimate of head orientation. We show that application of this algorithm leads to an estimated head orientation between saccades that is sufficiently stable to enable recovering information on translation. The algorithm may therefore be of practical use when head orientation is needed but cannot be measured.

Application of multiline two-photon microscopy to functional in vivo imaging

High spatial resolution and low risks of photodamage make two-photon laser-scanning microscopy (TPLSM) the method of choice for biological imaging. However, the study of functional dynamics such as neuronal calcium regulation often also requires a high temporal resolution. Hitherto, acquisition speed is usually increased by line scanning, which restricts spatial resolution to structures along a single axis. To overcome this gap between high spatial and high temporal resolution we performed TPLSM with a beam multiplexer to generate multiple laser foci inside the sample. By detecting the fluorescence emitted from these laser foci with an electron-multiplying camera, it was possible to perform multiple simultaneous linescans. In addition to multiline scanning, the array of up to 64 laser beams could also be used in x-y scan mode to collect entire images at high frame rates. To evaluate the applicability of multiline TPLSM to functional in vivo imaging, calcium signals were monitored in visual motion-sensitive neurons in the brain of flies. The capacity of our method to simultaneously acquire signals at different cellular locations is exemplified by measurements at branched neurites and 'spine'-like structures. Calcium dynamics depended on branch size, but 'spines' did not systematically differ from their 'parent neurites'. The spatial resolution of our setup was critically evaluated by comparing it to confocal microscopy and the negative effect of scattering of emission light during image detection was assessed directly by running the setup in both imaging and point-scanning mode.

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.

On the computations analyzing natural optic flow: quantitative model analysis of the blowfly motion vision pathway

For many animals, including humans, the optic flow generated on the eyes during locomotion is an important source of information about self-motion and the structure of the environment. The blowfly has been used frequently as a model system for experimental analysis of optic flow processing at the microcircuit level. Here, we describe a model of the computational mechanisms implemented by these circuits in the blowfly motion vision pathway. Although this model was originally proposed based on simple experimenter-designed stimuli, we show that it is also capable to quantitatively predict the responses to the complex dynamic stimuli a blowfly encounters in free flight. In particular, the model visual system exploits the active saccadic gaze and flight strategy of blowflies in a similar way, as does its neuronal counterpart. The model circuit extracts information about translation velocity in the intersaccadic intervals and thus, indirectly, about the three-dimensional layout of the environment. By stepwise dissection of the model circuit, we determine which of its components are essential for these remarkable features. When accounting for the responses to complex natural stimuli, the model is much more robust against parameter changes than when explaining the neuronal responses to simple experimenter-defined stimuli. In contrast to conclusions drawn from experiments with simple stimuli, optimization of the parameter set for different segments of natural optic flow stimuli do not indicate pronounced adaptational changes of these parameters during long-lasting stimulation.

Function of a fly motion-sensitive neuron matches eye movements during free flight

Sensing is often implicitly assumed to be the passive acquisition of information. However, part of the sensory information is generated actively when animals move. For instance, humans shift their gaze actively in a sequence of saccades towards interesting locations in a scene. Likewise, many insects shift their gaze by saccadic turns of body and head, keeping their gaze fixed between saccades. Here we employ a novel panoramic virtual reality stimulator and show that motion computation in a blowfly visual interneuron is tuned to make efficient use of the characteristic dynamics of retinal image flow. The neuron is able to extract information about the spatial layout of the environment by utilizing intervals of stable vision resulting from the saccadic viewing strategy. The extraction is possible because the retinal image flow evoked by translation, containing information about object distances, is confined to low frequencies. This flow component can be derived from the total optic flow between saccades because the residual intersaccadic head rotations are small and encoded at higher frequencies. Information about the spatial layout of the environment can thus be extracted by the neuron in a computationally parsimonious way. These results on neuronal function based on naturalistic, behaviourally generated optic flow are in stark contrast to conclusions based on conventional visual stimuli that the neuron primarily represents a detector for yaw rotations of the animal.

With the aid of virtual reality, the authors study the neuronal responses to visual motion associated with natural behavior.

Function and coding in the blowfly H1 neuron during naturalistic optic flow

Naturalistic stimuli, reconstructed from measured eye movements of flying blowflies, were replayed on a panoramic stimulus device. The directional movement-sensitive H1 neuron was recorded from blowflies watching these stimuli. The response of the H1 neuron is dominated by the response to fast saccadic turns into one direction. The response between saccades is mostly inhibited by the front-to-back optic flow caused by the forward translation during flight. To unravel the functional significance of the H1 neuron, we replayed, in addition to the original behaviorally generated stimulus, two targeted stimulus modifications: (1) a stimulus in which flow resulting from translation was removed (this stimulus produced strong intersaccadic responses); and (2) a stimulus in which the saccades were removed by assuming that the head follows the smooth flight trajectory (this stimulus produced alternating zero or nearly saturating spike rates). The responses to the two modified stimuli are strongly different from the response to the original stimulus, showing the importance of translation and saccades for the H1 response to natural optic flow. The response to the original stimulus thus suggests a double function for the H1 neuron, assisting two major classes of movement-sensitive output neurons targeted by H1. First, its strong response to saccades may function as a saccadic suppressor (via one of its target neurons) for cells involved in figure-ground discrimination. Second, its intersaccadic response may increase the signal-to-noise ratio (SNR) of wide-field neurons involved in detecting translational optic flow between saccades, in particular when flying speeds are low or when object distances are large.

Dye-coupling visualizes networks of large-field motion-sensitive neurons in the fly

In the fly, visually guided course control is accomplished by a set of 60 large-field motion-sensitive neurons in each brain hemisphere. These neurons have been shown to receive retinotopic motion information from local motion detectors on their dendrites. In addition, recent experiments revealed extensive coupling between the large-field neurons through electrical synapses. These two processes together give rise to their broad and elaborate receptive fields significantly surpassing the extent of their dendritic fields. Here, we demonstrate that the electrical connections between different large-field neurons can be visualized using Neurobiotin dye injection into a single one of them. When combined with a fluorescent dye which does not cross electrical synapses, the injected cell can be identified unambiguously. The Neurobiotin staining corroborates the electrical coupling postulated amongst the cells of the vertical system (VS-cells) and between cells of the horizontal system (HS-cells and CH-cells). In addition, connections between some cells are revealed that have so far not been considered as electrically coupled.

Ca2+ Clearance in Visual Motion-Sensitive Neurons of the Fly Studied In Vivo by Sensory Stimulation and UV Photolysis of Caged Ca2+

In motion-sensitive visual neurons of the fly, excitatory visual stimulation elicits Ca2+ accumulation in dendrites and presynaptic arborizations. Following the cessation of motion stimuli, decay time courses of the cytosolic Ca2+ concentration signals measured with fluorescent dyes were faster in fine arborizations compared with the main branches. When indicators with low Ca2+ affinity were used, the decay of the Ca2+ signals appeared slightly faster than with high affinity dyes, but the dependence of decay kinetics on branch size was preserved. The most parsimonious explanation for faster Ca2+ concentration decline in thin branches compared with thick ones is that the velocity of Ca2+ clearance is limited by transport mechanisms located in the outer membrane and is thus dependent on the neurite's surface-to-volume ratio. This interpretation was corroborated by UV flash photolysis of caged Ca2+ to systematically elicit spatially homogeneous step-like Ca2+ concentration increases of varying amplitude. Clearance of Ca2+ liberated by this method depended on branch size in the same way as Ca2+ accumulated during visual stimulation. Furthermore, the decay time courses of Ca2+ signals were only little affected by the amount of Ca2+ released by photolysis. Thus Ca2+ efflux via the outer membrane is likely to be the main reason for the spatial differences in Ca2+ clearance in visual motion-sensitive neurons of the fly.

Synaptic transfer of dynamic motion information between identified neurons in the visual system of the blowfly

Synaptic transmission is usually studied in vitro with electrical stimulation replacing the natural input of the system. In contrast, we analyzed in vivo transfer of visual motion information from graded-potential presynaptic to spiking postsynaptic neurons in the fly. Motion in the null direction leads to hyperpolarization of the presynaptic neuron but does not much influence the postsynaptic cell, because its firing rate is already low during rest, giving only little scope for further reductions. In contrast, preferred-direction motion leads to presynaptic depolarizations and increases the postsynaptic spike rate. Signal transfer to the postsynaptic cell is linear and reliable for presynaptic graded membrane potential fluctuations of up to approximately 10 Hz. This frequency range covers the dynamic range of velocities that is encoded with a high gain by visual motion-sensitive neurons. Hence, information about preferred-direction motion is transmitted largely undistorted ensuring a consistent dependency of neuronal signals on stimulus parameters, such as motion velocity. Postsynaptic spikes are often elicited by rapid presynaptic spike-like depolarizations which superimpose the graded membrane potential. Although the timing of most of these spike-like depolarizations is set by noise and not by the motion stimulus, it is preserved at the synapse with millisecond precision.

Robustness of the tuning of fly visual interneurons to rotatory optic flow

The sophisticated receptive field organization of motion-sensitive tangential cells in the visual system of the blowfly Calliphora vicina matches the structure of particular optic flow fields. Hypotheses on the tuning of particular tangential cells to rotatory self-motion are based on local motion measurements. So far, tangential cells have never been tested with global optic flow stimuli. Therefore we measured the responses of an identifiable neuron, the V1 tangential cell, to wide-field motion stimuli mimicking optic flow fields similar to those the fly encounters during particular self-motions. The stimuli were generated by a "planetarium-projector," casting a pattern of moving light dots on a large spherical projection screen. We determined the tuning curves of the V1-cell to optic flow fields as induced by the animal during 1) rotation about horizontally aligned body axes, 2) upward/downward translation, and 3) a combination of both components. We found that the V1-cell does not respond as specifically to self-rotations, as had been concluded from its receptive field organization. The neuron responds strongly to upward translation and its tuning to rotations is much coarser than expected. The discrepancies between the responses to global optic flow and the predictions based on the receptive field organization are likely due to nonlinear integration properties of tangential neurons. Response parameters like orientation, shape, and width of the tuning curve are largely unaffected by changes in rotation velocity or a superposition of rotational and translational optic flow.

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.

FliMax, a novel stimulus device for panoramic and highspeed presentation of behaviourally generated optic flow

A high-speed panoramic visual stimulation device is introduced which is suitable to analyse visual interneurons during stimulation with rapid image displacements as experienced by fast moving animals. The responses of an identified motion sensitive neuron in the visual system of the blowfly to behaviourally generated image sequences are very complex and hard to predict from the established input circuitry of the neuron. This finding suggests that the computational significance of visual interneurons can only be assessed if they are characterised not only by conventional stimuli as are often used for systems analysis, but also by behaviourally relevant input.

Vision in flying insects

Vision guides flight behaviour in numerous insects. Despite their small brain, insects easily outperform current man-made autonomous vehicles in many respects. Examples are the virtuosic chasing manoeuvres male flies perform as part of their mating behaviour and the ability of bees to assess, on the basis of visual motion cues, the distance travelled in a novel environment. Analyses at both the behavioural and neuronal levels are beginning to unveil reasons for such extraordinary capabilities of insects. One recipe for their success is the adaptation of visual information processing to the specific requirements of the behavioural tasks and to the specific spatiotemporal properties of the natural input.

Recurrent network interactions underlying flow-field selectivity of visual interneurons

Motion-sensitive large-field neurons found at higher processing stages in many species often exhibit a remarkable selectivity for particular flow fields. However, the underlying neural mechanisms are not yet understood. We studied this problem in the so-called lobula plate tangential cells (LPTCs) of the fly. Investigating the connectivity between LPTCs by means of dual recordings, we find two types of connections: (1) heterolateral connections between LPTCs of both hemispheres and (2) ipsilateral connections between LPTCs within one lobula plate. The circuit is suitable to amplify incoming, dendritic signals in the case of rotatory flow fields and to reduce them in the case of other flow-field structures. In addition to feedforward connectivity, thus, the flow-field selectivity of LPTCs may be significantly attributable to recurrent excitation involving the network of large-field neurons in both brain hemispheres.

Binocular contributions to optic flow processing in the fly visual system

Integrating binocular motion information tunes wide-field direction-selective neurons in the fly optic lobe to respond preferentially to specific optic flow fields. This is shown by measuring the local preferred directions (LPDs) and local motion sensitivities (LMSs) at many positions within the receptive fields of three types of anatomically identifiable lobula plate tangential neurons: the three horizontal system (HS) neurons, the two centrifugal horizontal (CH) neurons, and three heterolateral connecting elements. The latter impart to two of the HS and to both CH neurons a sensitivity to motion from the contralateral visual field. Thus in two HS neurons and both CH neurons, the response field comprises part of the ipsi- and contralateral visual hemispheres. The distributions of LPDs within the binocular response fields of each neuron show marked similarities to the optic flow fields created by particular types of self-movements of the fly. Based on the characteristic distributions of local preferred directions and motion sensitivities within the response fields, the functional role of the respective neurons in the context of behaviorally relevant processing of visual wide-field motion is discussed.

Response latency of a motion-sensitive neuron in the fly visual system: dependence on stimulus parameters and physiological conditions

The response latency of an identified motion-sensitive neuron in the blowfly visual system strongly depends on stimulus parameters. The latency decreases with increasing contrast and temporal frequency of a moving pattern, but changes only little when the pattern size and thus the number of activated inputs is increased. The latency does not only depend on visual stimuli, but is also affected by temperature changes and the age of the fly. Since response latencies cover a range of one order of magnitude, the latency changes are expected to be of relevance in visually guided orientation behaviour.

Performance of fly visual interneurons during object fixation

Neurons involved in the processing of optic flow are usually analyzed using stimuli designed by the experimenter. However, in real life optic flow depends on locomotive behavior. We characterized the performance of motion-sensitive neurons in the visual system of the fly using optic flow as occurring in behavioral situations during object fixation. Optic flow generated by tethered flying flies in a flight simulator was subsequently replayed while recording the responses of two cell types in the fly's motion pathway presumably involved in the detection of objects and of deviations from a straight flight course, respectively. FD1b cells, which are representatives of the so-called figure-detection cells, responded very specifically to object motion. Although object selectivity of these cells is attributable to inhibition during large-field motion, the influence of background motion during object fixation was almost negligible. In contrast, the cells of the so-called horizontal system (HS cells) are most sensitive to background motion, as elicited during deviations of the animal from its course. During object fixation, the responses of HS cells depended on both object and background motion. The simulated distance of the background to the fly did not have a strong influence on the responses of either cell type. The specificity for detecting deviations from a straight course is enhanced by subtraction of the signals of HS cells in both halves of the brain. In contrast, the FD1b cells in the two halves of the brain need to interact in a nonlinear way to ensure efficient detection of objects.