Direction-selective adaptation in fly visual motion-sensitive neurons is generated by an intrinsic conductance-based mechanism

Descending neurons of the hoverfly respond to pursuits of artificial targets

Many animals use motion vision information to control dynamic behaviors. Predatory animals, for example, show an exquisite ability to detect rapidly moving prey, followed by pursuit and capture. Such target detection is not only used by predators but is also important in conspecific interactions, such as for male hoverflies defending their territories against conspecific intruders. Visual target detection is believed to be subserved by specialized target-tuned neurons found in a range of species, including vertebrates and arthropods. However, how these target-tuned neurons respond to actual pursuit trajectories is currently not well understood. To redress this, we recorded extracellularly from target-selective descending neurons (TSDNs) in male Eristalis tenax hoverflies. We show that they have dorso-frontal receptive fields with a preferred direction up and away from the visual midline. We reconstructed visual flow fields as experienced during pursuits of artificial targets (black beads). We recorded TSDN responses to six reconstructed pursuits and found that each neuron responded consistently at remarkably specific time points but that these time points differed between neurons. We found that the observed spike probability was correlated with the spike probability predicted from each neuron's receptive field and size tuning. Interestingly, however, the overall response rate was low, with individual neurons responding to only a small part of each reconstructed pursuit. In contrast, the TSDN population responded to substantially larger proportions of the pursuits but with lower probability. This large variation between neurons could be useful if different neurons control different parts of the behavioral output.

Disentangling of Local and Wide-Field Motion Adaptation

Motion adaptation has been attributed in flying insects a pivotal functional role in spatial vision based on optic flow. Ongoing motion enhances in the visual pathway the representation of spatial discontinuities, which manifest themselves as velocity discontinuities in the retinal optic flow pattern during translational locomotion. There is evidence for different spatial scales of motion adaptation at the different visual processing stages. Motion adaptation is supposed to take place, on the one hand, on a retinotopic basis at the level of local motion detecting neurons and, on the other hand, at the level of wide-field neurons pooling the output of many of these local motion detectors. So far, local and wide-field adaptation could not be analyzed separately, since conventional motion stimuli jointly affect both adaptive processes. Therefore, we designed a novel stimulus paradigm based on two types of motion stimuli that had the same overall strength but differed in that one led to local motion adaptation while the other did not. We recorded intracellularly the activity of a particular wide-field motion-sensitive neuron, the horizontal system equatorial cell (HSE) in blowflies. The experimental data were interpreted based on a computational model of the visual motion pathway, which included the spatially pooling HSE-cell. By comparing the difference between the recorded and modeled HSE-cell responses induced by the two types of motion adaptation, the major characteristics of local and wide-field adaptation could be pinpointed. Wide-field adaptation could be shown to strongly depend on the activation level of the cell and, thus, on the direction of motion. In contrast, the response gain is reduced by local motion adaptation to a similar extent independent of the direction of motion. This direction-independent adaptation differs fundamentally from the well-known adaptive adjustment of response gain according to the prevailing overall stimulus level that is considered essential for an efficient signal representation by neurons with a limited operating range. Direction-independent adaptation is discussed to result from the joint activity of local motion-sensitive neurons of different preferred directions and to lead to a representation of the local motion direction that is independent of the overall direction of global motion.

Persistent Firing and Adaptation in Optic-Flow-Sensitive Descending Neurons

A general principle of sensory systems is that they adapt to prolonged stimulation by reducing their response over time. Indeed, in many visual systems, including higher-order motion sensitive neurons in the fly optic lobes and the mammalian visual cortex, a reduction in neural activity following prolonged stimulation occurs. In contrast to this phenomenon, the response of the motor system controlling flight maneuvers persists following the offset of visual motion. It has been suggested that this gap is caused by a lingering calcium signal in the output synapses of fly optic lobe neurons. However, whether this directly affects the responses of the post-synaptic descending neurons, leading to the observed behavioral output, is not known. We use extracellular electrophysiology to record from optic-flow-sensitive descending neurons in response to prolonged wide-field stimulation. We find that, as opposed to most sensory and visual neurons, and in particular to the motion vision sensitive neurons in the brains of both flies and mammals, the descending neurons show little adaption during stimulus motion. In addition, we find that the optic-flow-sensitive descending neurons display persistent firing, or an after-effect, following the cessation of visual stimulation, consistent with the lingering calcium signal hypothesis. However, if the difference in after-effect is compensated for, subsequent presentation of stimuli in a test-adapt-test paradigm reveals adaptation to visual motion. Our results thus show a combination of adaptation and persistent firing in the neurons that project to the thoracic ganglia and thereby control behavioral output.

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 sensitivity

Sensory systems adapt to prolonged stimulation by decreasing their response to continuous stimuli. Whereas visual motion adaptation has traditionally been studied in immobilized animals, recent work indicates that the animal's behavioral state influences the response properties of higher-order motion vision-sensitive neurons. During insect flight octopamine is released, and pharmacological octopaminergic activation can induce a fictive locomotor state. In the insect optic ganglia, lobula plate tangential cells (LPTCs) spatially pool input from local elementary motion detectors (EMDs) that correlate luminosity changes from two spatially discrete inputs after delaying the signal from one. The LPTC velocity optimum thereby depends on the spatial separation of the inputs and on the EMD's delay properties. Recently it was shown that behavioral activity increases the LPTC velocity optimum, with modeling suggesting this to originate in the EMD's temporal delay filters. However, behavior induces an additional post-EMD effect: the LPTC membrane conductance increases in flying flies. To physiologically investigate the degree to which activity causes presynaptic and postsynaptic effects, we conducted intracellular recordings of Eristalis horizontal system (HS) neurons. We constructed contrast response functions before and after adaptation at different temporal frequencies, with and without the octopamine receptor agonist chlordimeform (CDM). We extracted three motion adaptation components, where two are likely to be generated presynaptically of the LPTCs, and one within them. We found that CDM affected the early, EMD-associated contrast gain reduction, temporal frequency dependently. However, a CDM-induced change of the HS membrane conductance disappeared during and after visual stimulation. This suggests that physical activity mainly affects motion adaptation presynaptically of LPTCs, whereas post-EMD effects have a minimal effect.

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.

Species-Specific Flight Styles of Flies are Reflected in the Response Dynamics of a Homolog Motion-Sensitive Neuron

Hoverflies and blowflies have distinctly different flight styles. Yet, both species have been shown to structure their flight behavior in a way that facilitates extraction of 3D information from the image flow on the retina (optic flow). Neuronal candidates to analyze the optic flow are the tangential cells in the third optical ganglion - the lobula complex. These neurons are directionally selective and integrate the optic flow over large parts of the visual field. Homolog tangential cells in hoverflies and blowflies have a similar morphology. Because blowflies and hoverflies have similar neuronal layout but distinctly different flight behaviors, they are an ideal substrate to pinpoint potential neuronal adaptations to the different flight styles. In this article we describe the relationship between locomotion behavior and motion vision on three different levels: (1) We compare the different flight styles based on the categorization of flight behavior into prototypical movements. (2) We measure the species-specific dynamics of the optic flow under naturalistic flight conditions. We found the translational optic flow of both species to be very different. (3) We describe possible adaptations of a homolog motion-sensitive neuron. We stimulate this cell in blowflies (Calliphora) and hoverflies (Eristalis) with naturalistic optic flow generated by both species during free flight. The characterized hoverfly tangential cell responds faster to transient changes in the optic flow than its blowfly homolog. It is discussed whether and how the different dynamical response properties aid optic flow analysis.

Rapid contrast gain reduction following motion adaptation

Neural and sensory systems adapt to prolonged stimulation to allow signaling across broader input ranges than otherwise possible with the limited bandwidth of single neurons and receptors. In the visual system, adaptation takes place at every stage of processing, from the photoreceptors that adapt to prevailing luminance conditions, to higher-order motion-sensitive neurons that adapt to prolonged exposure to motion. Recent experiments using dynamic, fluctuating visual stimuli indicate that adaptation operates on a time scale similar to that of the response itself. Further work from our own laboratory has highlighted the role for rapid motion adaptation in reliable encoding of natural image motion. Physiologically, motion adaptation can be broken down into four separate components. It is not clear from the previous studies which of these motion adaptation components are involved in the fast and dynamic response changes. To investigate the adapted response in more detail, we therefore analyzed the effect of motion adaptation using a test-adapt-test protocol with adapting durations ranging from 20 ms to 20 s. Our results underscore the very rapid rate of motion adaptation, suggesting that under free flight, visual motion-sensitive neurons continuously adapt to the changing scenery. This might help explain recent observations of strong invariance in the response to natural scenes with highly variable contrast and image structure.

A neuronally based model of contrast gain adaptation in fly motion vision

Motion-sensitive neurons in the visual systems of many species, including humans, exhibit a depression of motion responses immediately after being exposed to rapidly moving images. This motion adaptation has been extensively studied in flies, but a neuronal mechanism that explains the most prominent component of adaptation, which occurs regardless of the direction of motion of the visual stimulus, has yet to be proposed. We identify a neuronal mechanism, namely frequency-dependent synaptic depression, which explains a number of the features of adaptation in mammalian motion-sensitive neurons and use it to model fly motion adaptation. While synaptic depression has been studied mainly in spiking cells, we use the same principles to develop a simple model for depression in a graded synapse. By incorporating this synaptic model into a neuronally based model for elementary motion detection, along with the implementation of a center-surround spatial band-pass filtering stage that mimics the interactions among a subset of visual neurons, we show that we can predict with remarkable success most of the qualitative features of adaptation observed in electrophysiological experiments. Our results support the idea that diverse species share common computational principles for processing visual motion and suggest that such principles could be neuronally implemented in very similar ways.

The many facets of adaptation in fly visual motion processing

Neuronal adaptation has been studied extensively in visual motion-sensitive neurons of the fly Calliphora vicina, a model system in which the computational principles of visual motion processing are amenable on a single-cell level. Evidenced by several recent papers, the original idea had to be dismissed that motion adaptation adjusts velocity coding to the current stimulus range by a simple parameter change in the motion detection scheme. In contrast, linear encoding of velocity modulations and total information rates might even go down in the course of adaptation. Thus it seems that rather than improving absolute velocity encoding motion adaptation might bring forward an efficient extraction of those features in the visual input signal that are most relevant for visually guided course control and obstacle avoidance.

Impact of visual motion adaptation on neural responses to objects and its dependence on the temporal characteristics of optic flow

It is still unclear how sensory systems efficiently encode signals with statistics as experienced by animals in the real world and what role adaptation plays during normal behavior. Therefore, we studied the performance of visual motion-sensitive neurons of blowflies, the horizontal system neurons, with optic flow that was reconstructed from the head trajectories of semi-free-flying flies. To test how motion adaptation is affected by optic flow dynamics, we manipulated the seminatural optic flow by targeted modifications of the flight trajectories and assessed to what extent neuronal responses to an object located close to the flight trajectory depend on adaptation dynamics. For all types of adapting optic flow object-induced response increments were stronger in the adapted compared with the nonadapted state. Adaptation with optic flow characterized by the typical alternation between translational and rotational segments produced this effect but also adaptation with optic flow that lacked these distinguishing features and even pure rotation at a constant angular velocity. The enhancement of object-induced response increments had a direction-selective component because preferred-direction rotation and natural optic flow were more efficient adaptors than null-direction rotation. These results indicate that natural dynamics of optic flow is not a basic requirement to adapt neurons in a specific, presumably functionally beneficial way. Our findings are discussed in the light of adaptation mechanisms proposed on the basis of experiments previously done with conventional experimenter-defined stimuli.

Motion adaptation and the velocity coding of natural scenes

Estimating relative velocity in the natural environment is challenging because natural scenes vary greatly in contrast and spatial structure. Widely accepted correlation-based models for elementary motion detectors (EMDs) are sensitive to contrast and spatial structure and consequently generate ambiguous estimates of velocity. Identified neurons in the third optic lobe of the hoverfly can reliably encode the velocity of natural images largely independent of contrast, despite receiving inputs directly from arrays of such EMDs. This contrast invariance suggests an important role for additional neural processes in robust encoding of image motion. However, it remains unclear which neural processes are contributing to contrast invariance. By recording from horizontal system neurons in the hoverfly lobula, we show two activity-dependent adaptation mechanisms acting as near-ideal normalizers for images of different contrasts that would otherwise produce highly variable response magnitudes. Responses to images that are initially weak neural drivers are boosted over several hundred milliseconds. Responses to images that are initially strong neural drivers are reduced over longer time scales. These adaptation mechanisms appear to be matched to higher-order natural image statistics reconciling the neurons' accurate encoding of image velocity with the inherent ambiguity of correlation-based motion detectors.

Adaptation accentuates responses of fly motion-sensitive visual neurons to sudden stimulus changes

Adaptation in sensory and neuronal systems usually leads to reduced responses to persistent or frequently presented stimuli. In contrast to simple fatigue, adapted neurons often retain their ability to encode changes in stimulus intensity and to respond when novel stimuli appear. We investigated how the level of adaptation of a fly visual motion-sensitive neuron affects its responses to discontinuities in the stimulus, i.e. sudden brief changes in one of the stimulus parameters (velocity, contrast, grating orientation and spatial frequency). Although the neuron's overall response decreased gradually during ongoing motion stimulation, the response transients elicited by stimulus discontinuities were preserved or even enhanced with adaptation. Moreover, the enhanced sensitivity to velocity changes by adaptation was not restricted to a certain velocity range, but was present regardless of whether the neuron was adapted to a baseline velocity below or above its steady-state velocity optimum. Our results suggest that motion adaptation helps motion-sensitive neurons to preserve their sensitivity to novel stimuli even in the presence of strong tonic stimulation, for example during self-motion.

The motion after-effect: local and global contributions to contrast sensitivity

Motion adaptation is a widespread phenomenon analogous to peripheral sensory adaptation, presumed to play a role in matching responses to prevailing current stimulus parameters and thus to maximize efficiency of motion coding. While several components of motion adaptation (contrast gain reduction, output range reduction and motion after-effect) have been described, previous work is inconclusive as to whether these are separable phenomena and whether they are locally generated. We used intracellular recordings from single horizontal system neurons in the fly to test the effect of local adaptation on the full contrast-response function for stimuli at an unadapted location. We show that contrast gain and output range reductions are primarily local phenomena and are probably associated with spatially distinct synaptic changes, while the antagonistic after-potential operates globally by transferring to previously unadapted locations. Using noise analysis and signal processing techniques to remove 'spikelets', we also characterize a previously undescribed alternating current component of adaptation that can explain several phenomena observed in earlier studies.

Adaptation of velocity encoding in synaptically coupled neurons in the fly visual system

Although many adaptation-induced effects on neuronal response properties have been described, it is often unknown at what processing stages in the nervous system they are generated. We focused on fly visual motion-sensitive neurons to identify changes in response characteristics during prolonged visual motion stimulation. By simultaneous recordings of synaptically coupled neurons, we were able to directly compare adaptation-induced effects at two consecutive processing stages in the fly visual motion pathway. This allowed us to narrow the potential sites of adaptation effects within the visual system and to relate them to the properties of signal transfer between neurons. Motion adaptation was accompanied by a response reduction, which was somewhat stronger in postsynaptic than in presynaptic cells. We found that the linear representation of motion velocity degrades during adaptation to a white-noise velocity-modulated stimulus. This effect is caused by an increasingly nonlinear velocity representation rather than by an increase of noise and is similarly strong in presynaptic and postsynaptic neurons. In accordance with this similarity, the dynamics and the reliability of interneuronal signal transfer remained nearly constant. Thus, adaptation is mainly based on processes located in the presynaptic neuron or in more peripheral processing stages. In contrast, changes of transfer properties at the analyzed synapse or in postsynaptic spike generation contribute little to changes in velocity coding during motion adaptation.