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Encoding of Motion in Real Time by the Fly Visual System Martin Egelhaaf* and Anne-Kathrin Warzecha†

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Encoding of Motion in Real Time by the Fly Visual System Martin Egelhaaf* and Anne-Kathrin Warzecha† 454 Encoding of motion in real time by the fly visual system Martin Egelhaaf* and Anne-Kathrin Warzecha† Direction-selective cells in the fly visual system that have large By what mechanisms, and how reliably, time-dependent receptive fields play a decisive role in encoding the time- stimuli are encoded by the nervous system is currently dependent optic flow the animal encounters during locomotion. being investigated intensively in the context of optic Recent experiments on the computations performed by these flow processing in the visual systems of various animals, cells have highlighted the significance of dendritic integration such as monkeys, pigeons and flies. The fly is highly and have addressed the role of spikes versus graded specialised to evaluate time-dependent optic flow to membrane potential changes in encoding optic flow information. control its often virtuosic visually guided orientation It is becoming increasingly clear that the way optic flow is behaviour. In the fly, it is possible to track motion infor- encoded in real time is constrained both by the computational mation processing physiologically from the retina to needs of the animal in visually guided behaviour as well as by visual orientation behaviour [3]. the specific properties of the underlying neuronal hardware. Optic flow is initially processed in the first and second Addresses visual areas of the fly’s brain by successive layers of retino- Lehrstuhl für Neurobiologie, Fakultät für Biologie, Universität Bielefeld, topically arranged columnar neurons. There is detailed Postfach 10 01 31, D-33501 Bielefeld, Germany knowledge on the first visual area, the lamina, both at the *e-mail: [email protected] ultrastructural and functional level. Much attention has †e-mail: [email protected] been paid in recent years to the strategies for encoding nat- Current Opinion in Neurobiology 1999, 9:454–460 ural, time-dependent input signals by lamina neurons and http://biomednet.com/elecref/0959438800900454 the functional significance of these strategies (reviewed in [4,5]). Adaptive neural filtering in the lamina is thought to © Elsevier Science Ltd ISSN 0959-4388 remove spatial and temporal redundancies from the incom- Abbreviation ing retinal signals and, thus, to maximise the transfer of TC tangential cell information about time-dependent retinal images [6]. In contrast to this understanding of information processing in Introduction the lamina, little is known about information processing in Images of the surrounding environment on the retina often the second visual area, the medulla. There is a great deal change rapidly. Retinal image changes are partly attributable of anatomical knowledge on the medulla [7–10], and elec- to changes in the outside world, such as when a moving trophysiological recordings are available from an increasing object crosses the visual field. Even if the outside world is collection of medullar neurons [11–15]. Owing to the small stationary, however, there is a continuous image flow on the size of these neurons and the difficulty of recording their retina when the observer, be it humans or other animals, activity for an adequate interval of time, their functional moves about in the environment. This so-called optic flow is characterisation is still incomplete; interpretations of their a rich source of information about both the outside world and role in motion detection must be regarded as tentative. At the path and speed of locomotion. Before this information least there is evidence that direction selectivity is first can be used to control visually guided orientating behaviour, computed on a local retinotopic basis in the most proximal it needs to be extracted from the activity profile of the array layers of the medulla [12–14,16]. of photoreceptors and processed by the nervous system. In the posterior part of the third visual area, the lobula Although humans and other animals usually seem to solve plate, the local motion information is spatially pooled by this task without much effort, the ability to process com- the large dendrites of a set of neurons, the so-called tan- plex, time-dependent sensory signals is by no means trivial gential cells (TCs) [17,18]. Two types of retinotopic input given the properties of the neuronal hardware. In particu- elements with opposite preferred direction of motion — lar, when fast reactions are required, unreliable neuronal one inhibitory and one excitatory — converge onto the computations may become a major problem. The indeter- dendritic tree of the TCs ([19]; for a review, see [20]). As minacy of neuronal responses is reflected in their often a consequence, the TCs respond selectively to the direc- large variability. When a given stimulus is presented tion of motion. Owing to the spatial properties of their repeatedly to a neuron, the responses are not identical and input organisation and to synaptic interactions with other may vary substantially. Often the variance of neuronal TCs in the ipsi- and contralateral half of the brain, the responses is on the order of the average response ampli- TCs are ideally suited to process optic flow. Some TCs tude (see e.g. [1,2]). Hence, just by looking at the activity respond best to coherent motion in large parts of the visu- of a neuron, say in a sequence of action potentials, it is al field, such as when an animal turns about one of its hardly possible to tell without additional information body axes. Other TCs are tuned to relative motion whether fluctuations in the interspike intervals are between an object and its background, such as when the induced by a sensory stimulus or result from noise. fly flies past a nearby object [3,17,18]. Encoding of motion in real time by the fly visual system Egelhaaf and Warzecha 455 Figure 1 Consequences of dendritic integration on the representation of visual motion. Schematic of a fly TC in the third visual area, with two dendritic branches, an axon and an axon terminal. The TC receives retinotopically organised, local motion-sensitive inputs: vertical lines terminating with ‘synapses’ (a) (black dots) on the dendrites. The local (a) input elements do not exhibit the same preferred direction of motion within the entire receptive field of the TC. Instead, the Local preferred directions preferred direction of motion changes in a characteristic way (indicated by arrows in the plane above the dendrites). Data courtesy of Axon Dendrite H Krapp. For the TC shown here, the (c) (ii) preferred directions correspond to the directions of motion (indicated by the arrows (i) Response High on the sphere) as experienced by the animal velocity when turning about its long axis. (b) Even (b) Local when the velocity of motion is constant, the Spatially integratedresponses ACh + - GABA Low velocity activity of the local input elements of the TCs response is modulated depending on the texture of the surround in the receptive fields of the local Pattern size elements. Traces on the right indicate the time-dependent signals of three local input Motion Motion elements of the TC. By dendritic pooling of Current Opinion in Neurobiology many local elements, this pattern dependence in the time course of the responses is (i) The enlargement illustrates that each point are activated, though to a different extent eliminated to a large extent (left trace). in the visual space is subserved by a pair of depending on the velocity of motion (black (c) Gain control in the TC makes its input elements of the TCs, one of them being and white columns). As a consequence, the responses relatively independent of the cholinergic (ACh) and excitatory, the other membrane potential approaches different number of activated input elements and, thus, GABAergic and inhibitory [19]. (ii) Even saturation levels for different velocities when of pattern size, whereas the response during motion in the local preferred direction the number of activated local input elements amplitude still depends on pattern velocity. of the TC, both types of local input elements increases. GABA, γ-aminobutyric acid. In the following sections, we concentrate on three spe- in the receptive fields of TCs are not modified by visual cific aspects of real-time motion encoding that have experience but appear to have resulted from phyloge- attracted particular attention in recent months: first, the netic adaptations [23]. role of dendritic integration by TCs in processing of optic flow; second, the performance of spiking and graded Secondly, because the local motion input elements of the potential neurons in encoding of visual motion; and TCs have only small receptive fields, their responses are third, the constraints imposed by the neuronal hardware temporally modulated even when the stimulus pattern on the temporal precision with which visual motion can moves with a constant velocity. Therefore, the signals of be encoded. these local elements, which ‘look’ at different areas of the surround, are phase-shifted with respect to each other. The role of dendritic integration in processing Spatial pooling of these local signals by the dendrites of of optic flow the TCs reduces the temporal response modulations to a Optic flow information cannot be derived by computations large extent [24,25•] (Figure 1b). Hence, dendritic integra- operating on a local basis alone. Rather, motion informa- tion produces a signal that is, to some extent, proportional tion from different areas of the visual field must be to the time course of pattern velocity. compared. Here, dendritic integration plays a prominent role. Three functional consequences of dendritic integra- Thirdly, dendritic integration of the local movement- tion will be reviewed below. sensitive elements is a highly nonlinear process. When the signals of an increasing number of input elements Firstly, the preferred directions of the local motion are pooled, saturation nonlinearities make the response inputs to the TCs are not the same across the entire largely independent of pattern size.
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