Fly vision: neural mechanisms of motion computation

A wide range of novel approaches are being used to dissect the visual system of the fly, both the neural networks of motion detection and the performance of these networks under complex natural stimulus conditions.     

The neuro-ecology of resource localization in Drosophila: Behavioral components of perception and search

From the moment an adult fruit fly ecloses, its primary objective in life is to disperse and locate the source of an attractive food odor upon which to feed and reproduce. The evolution of flight has greatly enhanced the success of fruit flies specifically and insects more generally.1 Control of flight by Drosophila melanogaster is unequivocally visual. Strong optomotor reflexes towards translatory and rotational visual flow stabilize forward flight trajectory, altitude, and speed. 2, 3 The steering responses to translatory and rotational flow in particular are mediated by computationally separate neural circuits in the fly’s visual system,4 and gaze-stabilizing body saccades are elicited by threshold integration of expanding visual flow .5 However, visual information is not alone sufficient to enable a fruit fly to recognize and locate an appropriately smelly object due in part to the relatively poor resolution of its compound eyes. Rather, the animal uses an acute sense of smell to actively track odors during flight. Without a finely adapted olfactory system, the fly’s remarkable visual capabilities are for naught. The relative importance of vision is apparent in the cross-modal fusion of the two modalities for stable active odor tracking.6, 7 Olfactory processing in Drosophila is shaped by ecological and functional forces which are inextricably linked. Thus physiologists seeking the functional determinants of olfactory coding as well as ecologists seeking to understand the mechanisms of speciation do well to consider each others’ point of view. Here we synthesize a broad perspective that integrates across ultimate and proximate mechanisms of odor tracking in Drosophila.     

Neural circuitry: seeing the parts that make the picture

What are the neural correlates of vision? A recent study on Drosophila has described the incredible neuronal diversity in the fly visual system, and traced the circuits that underlie color vision.     

LIFE IN ZERO MAGNETIC FIELD. IV. INVESTIGATION OF DEVELOPMENTAL EFFECTS ON FRUITFLY VISION

The fruitfly (Drosophila melanogaster) visual system was investigated electrophysiologically in vivo after exposure to a zero magnetic field (ZMF). Electroretinographic (ERG) recording of fly eye electrical activity was performed on adult insects raised from pupae maintained for 20 hr in zero magnetic field. A flickering excitation regime was applied to excite the visual system, since in this way, a quasistable hyperpolarization component of the electroretinogram can be obtained, containing information from the neural cells, which are the most sensitive to the action of external factors during early ontogenetic stages. Results of the investigation of two D. melanogaster populations, sample and control, were statistically compared.

We found a significant statistical increase of sensitivity in neural cells from the first optic ganglion in the fly population developed from pupae exposed to ZMF.     

雄蝇追逐行为的分析

本文报告了在自由飞行条件下雄蝇追逐的行为实验及其分析的初步结果.其结果如下:1.追逐雄蝇水平方向偏转的角速度dF_1线性地依赖于目标蝇水平方位误差角T_1的大小.当目标在前视场中,即空间误差角|G|<π/4时,线性回归直线的斜率约为37**;而当空间误差角|G|>π/4时,线性回归直线的斜率约为6.7.2.追逐雄蝇俯仰方向偏转角速度dF_2在(-(π/2),π/2)的范围内线性依赖于俯仰误差角T_2的大小,其回归直线的斜率约为14.3.雄蝇追逐行为中,水平方位误差角频数分布的直方图呈现为峰值在零点的对称型分布;而俯仰误差角T_2频数分布的直方图是非对称型的,即仰角出现的频数大大超过俯角出现的频数.4.雄蝇主要利用了两蝇间距离变化dD的信息以及目标误差角来控制向前飞行的速度V.当误差角小时(即目标在前视场中),dD一般为负值,说明两蝇间的距离减小,而雄蝇追逐飞行的加速度A却与dD呈现正的线性关系.当误差角大时(即目标位于后视场中),dD一般为正值,说明两蝇间的距离增加.     

Intrinsic activity in the fly brain gates visual information during behavioral choices

The small insect brain is often described as an input/output system that executes reflex-like behaviors. It can also initiate neural activity and behaviors intrinsically, seen as spontaneous behaviors, different arousal states and sleep. However, less is known about how intrinsic activity in neural circuits affects sensory information processing in the insect brain and variability in behavior. Here, by simultaneously monitoring Drosophila's behavioral choices and brain activity in a flight simulator system, we identify intrinsic activity that is associated with the act of selecting between visual stimuli. We recorded neural output (multiunit action potentials and local field potentials) in the left and right optic lobes of a tethered flying Drosophila, while its attempts to follow visual motion (yaw torque) were measured by a torque meter. We show that when facing competing motion stimuli on its left and right, Drosophila typically generate large torque responses that flip from side to side. The delayed onset (0.1-1 s) and spontaneous switch-like dynamics of these responses, and the fact that the flies sometimes oppose the stimuli by flying straight, make this behavior different from the classic steering reflexes. Drosophila, thus, seem to choose one stimulus at a time and attempt to rotate toward its direction. With this behavior, the neural output of the optic lobes alternates; being augmented on the side chosen for body rotation and suppressed on the opposite side, even though the visual input to the fly eyes stays the same. Thus, the flow of information from the fly eyes is gated intrinsically. Such modulation can be noise-induced or intentional; with one possibility being that the fly brain highlights chosen information while ignoring the irrelevant, similar to what we know to occur in higher animals.     

Smelling on the fly: sensory cues and strategies for olfactory navigation in Drosophila

Navigating toward (or away from) a remote odor source is a challenging problem that requires integrating olfactory information with visual and mechanosensory cues. Drosophila melanogaster is a useful organism for studying the neural mechanisms of these navigation behaviors. There are a wealth of genetic tools in this organism, as well as a history of inventive behavioral experiments. There is also a large and growing literature in Drosophila on the neural coding of olfactory, visual, and mechanosensory stimuli. Here we review recent progress in understanding how these stimulus modalities are encoded in the Drosophila nervous system. We also discuss what strategies a fly might use to navigate in a natural olfactory landscape while making use of all these sources of sensory information. We emphasize that Drosophila are likely to switch between multiple strategies for olfactory navigation, depending on the availability of various sensory cues. Finally, we highlight future research directions that will be important in understanding the neural circuits that underlie these behaviors.     

What can we teach Drosophila? What can they teach us?

A number of single gene mutations dramatically reduce the ability of fruit flies to learn or to remember. Cloning of the affected genes implicated the adenylyl cyclase second-messenger system as key in learning and memory. The expression patterns of these genes, in combination with other data, indicates that brain structures called mushroom bodies are crucial for olfactory learning. However, the mushroom bodies are not dedicated solely to olfactory processing; they also mediate higher cognitive functions in the fly, such as visual context generalization. Molecular genetic manipulations, coupled with behavioral studies of the fly, will identify rudimentary neural circuits that underly multisensory learning and perhaps also the circuits that mediate more-complex brain functions, such as attention.     

What can we teach Drosophila? What can they teach us?

A number of single gene mutations dramatically reduce the ability of fruit flies to learn or to remember. Cloning of the affected genes implicated the adenylyl cyclase second-messenger system as key in learning and memory. The expression patterns of these genes, in combination with other data, indicates that brain structures called mushroom bodies are crucial for olfactory learning. However, the mushroom bodies are not dedicated solely to olfactory processing; they also mediate higher cognitive functions in the fly, such as visual context generalization. Molecular genetic manipulations, coupled with behavioral studies of the fly, will identify rudimentary neural circuits that underly multisensory learning and perhaps also the circuits that mediate more-complex brain functions, such as attention.     

Visuomotor transformation in the fly gaze stabilization system

For sensory signals to control an animal's behavior, they must first be transformed into a format appropriate for use by its motor systems. This fundamental problem is faced by all animals, including humans. Beyond simple reflexes, little is known about how such sensorimotor transformations take place. Here we describe how the outputs of a well-characterized population of fly visual interneurons, lobula plate tangential cells (LPTCs), are used by the animal's gaze-stabilizing neck motor system. The LPTCs respond to visual input arising from both self-rotations and translations of the fly. The neck motor system however is involved in gaze stabilization and thus mainly controls compensatory head rotations. We investigated how the neck motor system is able to selectively extract rotation information from the mixed responses of the LPTCs. We recorded extracellularly from fly neck motor neurons (NMNs) and mapped the directional preferences across their extended visual receptive fields. Our results suggest that-like the tangential cells-NMNs are tuned to panoramic retinal image shifts, or optic flow fields, which occur when the fly rotates about particular body axes. In many cases, tangential cells and motor neurons appear to be tuned to similar axes of rotation, resulting in a correlation between the coordinate systems the two neural populations employ. However, in contrast to the primarily monocular receptive fields of the tangential cells, most NMNs are sensitive to visual motion presented to either eye. This results in the NMNs being more selective for rotation than the LPTCs. Thus, the neck motor system increases its rotation selectivity by a comparatively simple mechanism: the integration of binocular visual motion information.     

Neurobiological constraints and fly systematics: how different types of neural characters can contribute to a higher level dipteran phylogeny

Much uncertainty still exists regarding higher level phylogenetic relationships in the insect order Diptera, and the need for independent analyses is apparent. In this paper, I present a parsimony analysis that is based on details of the nervous system of flies. Because neural characters have received little attention in modern phylogenetic analyses and the stability of neural traits has been debated, special emphasis is given to testing the robustness of the analysis itself and to evaluating how neurobiological constraints (such as levels of neural processing) influence the phylogenetic information content. The phylogenetic study is based on 14 species in three nematoceran and nine brachyceran families. All characters used in the analysis are based on anatomical details of the neural organization of the fly visual system. For the most part they relate to uniquely identifiable neurons, which are cells or cell types that can be confidently recognized as homologues among different species and thus compared. Parsimony analysis results in a phylogenetic hypothesis that favors specific previously suggested phylogenetic relationships and suggests alternatives regarding other placements. For example, several heterodactylan families (Bombyliidae, Asilidae, and Dolichopodidae) are supported in their placement as suggested by Sinclair et al. (1993), but Tipulidae and Syrphidae are placed differently. Tipulidae are placed at a derived rather than ancestral position within the Nematocera, and Syrphidae are placed within the Schizophora. The analysis suggests that neural characters generally maintain phylogenetic information well. However, by "forcing" neural characters onto conventional phylogenetic analyses it becomes apparent that not all neural centers maintain such information equally well. For example, neurons of the second-order visual neuropil, the medulla, contain stronger phylogenetic "signal" than do characters of the deeper visual center, the lobula plate. These differences may relate to different functional constraints in the two neuropils.     

雄蝇追逐飞行的加速度分析

本文报导了采用高速摄影技术,通过分析雄蝇追逐飞行的加速度对视觉制导问题所进行的研究.我们的结果如下:1.目标蝇的角位置与追逐蝇相应的角加速度分量之间,在追逐蝇的全视场中呈现非线性的关系.追逐蝇的水平角加速度分量与水平误差角在前视场中有较好的线性关系.追逐蝇的俯仰角加速度分量与俯仰误差角之间,当目标蝇位于前上半视场中时,呈现较好的线性关系.2.目标蝇相对追逐蝇的角运动对追逐蝇的相应角加速度分量也有影响,这种影响与目标蝇位置的关系不大.3.对于目标蝇在前后视场中的两种情况,两蝇间的距离对追逐蝇加速度大小影响的规律是不同的:当目标蝇在前视场中时,只经过较短的延迟时间两蝇间的距离与追逐蝇加速度大小出现了正的相关峰,而后视场中的情况不然,它需要较长的延迟时间.两蝇间距离的变化对追逐蝇加速度大小的影响也有类似的现象.4.在追逐过程中雄蝇利用背前区的小眼来追逐带头的目标雌蝇,而组织学研究在雄蝇背前区的小眼中发现了性特化的中心小网膜细胞,与行为研究的结果相呼应.5.文中最后对蝇视觉神经系统中如何获取目标绳的位置和运动参数的问题进行了讨论.     

Associative learning and memory in Drosophila: beyond olfactory conditioning

The associative learning abilities of the fruit fly, Drosophila melanogaster, have been demonstrated in both classical and operant conditioning paradigms. Efforts to identify the neural pathways and cellular mechanisms of learning have focused largely on olfactory classical conditioning. Results derived from various genetic and molecular manipulations provide considerable evidence that this form of associative learning depends critically on neural activity and cAMP signaling in brain neuropil structures called mushroom bodies. Three other behavioral learning paradigms in Drosophila serve as the main subject of this review. These are (1) visual and motor learning of flies tethered in a flight simulator, (2) a form of spatial learning that is independent of visual and olfactory cues, and (3) experience-dependent changes in male courtship behavior. The present evidence suggests that at least some of these modes of learning are independent of mushroom bodies. Applying targeted genetic manipulations to these behavioral paradigms should allow for a more comprehensive understanding of neural mechanisms responsible for diverse forms of associative learning and memory.     

Building a projection map for photoreceptor neurons in the Drosophila optic lobes

The sensory tasks performed by the eye are diverse and complex. In Drosophila, the eye performs motion detection for navigation as well as detection of the quality of light (color and polarized light). Both types of inputs are processed separately, as different photoreceptors are specialized in these tasks and contact different target cell layers in the optic lobe. However, their respective outputs are likely to be integrated in higher brain centers. Here, we discuss the cell diversity and potential role of the several ganglia that form the fly optic lobe. We also discuss the power of modern genetic tools to provide the potential to trace the visual neural networks.     

Visually induced height orientation of the fly Musca domestica

The visually controlled height orientation of fixed flying flies (Musca domestica) was investigated. The flight lift force measured by a transducer drives the vertical motion of a panorama. The dynamical conditions of the free flight are electronically simulated for the fly with respect to this degree of freedom of motion. In most of the experimentally investigated cases the panorama consists of a horizontally oriented narrow dark stripe on a bright background. The fly orientates with respect to the stripe, transporting it into a stable fixation position just below the equatorial plane of its compound eyes. It is experimentally demonstrated that the formalism of the linearized theory of the pattern induced flight orientation — Poggio and Reichardt (1973a) — can be applied to describe the height orientation of the fly. The experimental evidence concerning the simultaneous perception of stripes moving in a well defined manner in front of each of the two compound eyes is consistent with the hypothesis that the two halves of the visual system are perceptually additive.     

Reading spike timing without a clock: intrinsic decoding of spike trains

The precise timing of action potentials of sensory neurons relative to the time of stimulus presentation carries substantial sensory information that is lost or degraded when these responses are summed over longer time windows. However, it is unclear whether and how downstream networks can access information in precise time-varying neural responses. Here, we review approaches to test the hypothesis that the activity of neural populations provides the temporal reference frames needed to decode temporal spike patterns. These approaches are based on comparing the single-trial stimulus discriminability obtained from neural codes defined with respect to network-intrinsic reference frames to the discriminability obtained from codes defined relative to the experimenter''s computer clock. Application of this formalism to auditory, visual and somatosensory data shows that information carried by millisecond-scale spike times can be decoded robustly even with little or no independent external knowledge of stimulus time. In cortex, key components of such intrinsic temporal reference frames include dedicated neural populations that signal stimulus onset with reliable and precise latencies, and low-frequency oscillations that can serve as reference for partitioning extended neuronal responses into informative spike patterns.     

The remote roots of consciousness in fruit‐fly selective attention?

A mechanistic study of consciousness need not be confined to human complexity. Other animals also display key behaviors and responses that have long been intimately tied to the measure of consciousness in humans. Among them are some very well-defined and measurable endpoints: selective attention, sleep and general anesthesia. That these three variables associated with changes in consciousness might exist even in a fruit-fly does not necessarily imply that a fly is "conscious", but it does suggest that some of the problems central to the field of consciousness studies could be investigated in a model organism such as Drosophila melanogaster. Demonstrating suppression of unattended stimuli, which is central to attention studies in humans, is now possible in Drosophila by measuring neural correlates of visual selection. By combining such studies with an eventual understanding of suppression in other arousal states in the fly, such as sleep and general anesthesia, we might be unraveling mechanisms relevant to consciousness as well.     

Neural coding of natural stimuli: information at sub-millisecond resolution

Sensory information about the outside world is encoded by neurons in sequences of discrete, identical pulses termed action potentials or spikes. There is persistent controversy about the extent to which the precise timing of these spikes is relevant to the function of the brain. We revisit this issue, using the motion-sensitive neurons of the fly visual system as a test case. Our experimental methods allow us to deliver more nearly natural visual stimuli, comparable to those which flies encounter in free, acrobatic flight. New mathematical methods allow us to draw more reliable conclusions about the information content of neural responses even when the set of possible responses is very large. We find that significant amounts of visual information are represented by details of the spike train at millisecond and sub-millisecond precision, even though the sensory input has a correlation time of ~55 ms; different patterns of spike timing represent distinct motion trajectories, and the absolute timing of spikes points to particular features of these trajectories with high precision. Finally, the efficiency of our entropy estimator makes it possible to uncover features of neural coding relevant for natural visual stimuli: first, the system's information transmission rate varies with natural fluctuations in light intensity, resulting from varying cloud cover, such that marginal increases in information rate thus occur even when the individual photoreceptors are counting on the order of one million photons per second. Secondly, we see that the system exploits the relatively slow dynamics of the stimulus to remove coding redundancy and so generate a more efficient neural code.     

Neurogenetics and the "fly-stampede": dissecting neural circuits involved in visual behaviors

A central goal of systems neuroscience is to understand how neural circuits represent quantitative aspects of the outside world and transform these signals into the motor code for behavior. By contrast to olfactory perception in which odors are encoded by a population of ligand-binding receptors at the input stage, the visual system extracts complex information about color, form and movement from just a few types of photoreceptor inputs. The algorithms for many of these transformations are poorly understood. We designed a high throughput real-time quantitative testing system, the "fly-stampede", to evaluate behavioral responses to light and motion cues in Drosophila. With this system, we identified a neural circuit that does not participate in sensing light but is crucial for computing visual motion. When neurons of this circuit are genetically inactivated, the flies show normal walking phototaxis, but are completely motion blind. Using neurogenetics to study the circuits mediating sophisticated animal behaviors is currently a field of intense study. This extra view attempts to summarize our work within historical background of fly biocybernetics and other recent advances.     

Nitric oxide and Drosophila development

Mechanisms controlling the transition of precursor cells from proliferation to differentiation during organism development determine the distinct anatomical features of tissues and organs. NO may mediate such a transition since it can suppress DNA synthesis and cell proliferation. Inhibition of NOS activity in the imaginal discs of Drosophila larvae results in hypertrophy of tissues and organs of the adult fly, whereas ectopic overexpression of NOS has the reciprocal, hypotrophic, effect. Furthermore, NO production is crucial for the establishment of ordered neuronal connections in the visual system of the fly, indicating that NO affects the acquisition of the differentiated phenotype by the neural tissue. Increasing evidence points to a broad role that NO may play in animal development by acting as an essential negative regulator of precursor cell proliferation during tissue and organ morphogenesis.