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A K Warzecha

Publications and source records attributed to A K Warzecha.

12 recordsLinked to original sources

Reliability of a fly motion-sensitive neuron depends on stimulus parameters.

The variability of responses of sensory neurons constrains how reliably animals can respond to stimuli in the outside world. We show for a motion-sensitive visual interneuron of the fly that the variability of spike trains depends on the properties of the motion stimulus, although differently for different stimulus parameters. (1) The spike count variances of responses to constant and to dynamic stimuli lie in the same range. (2) With increasing stimulus size, the variance may slightly decrease. (3) Increasing pattern contrast reduces the variance considerably. For all stimulus conditions, the spike count variance is much smaller than the mean spike count and does not depend much on the mean activity apart from very low activities. Using a model of spike generation, we analyzed how the spike count variance depends on the membrane potential noise and the deterministic membrane potential fluctuations at the spike initiation zone of the neuron. In a physiologically plausible range, the variance is affected only weakly by changes in the dynamics or the amplitude of the deterministic membrane potential fluctuations. In contrast, the amplitude and dynamics of the membrane potential noise strongly influence the spike count variance. The membrane potential noise underlying the variability of the spike responses in the motion-sensitive neuron is concluded to be affected considerably by the contrast of the stimulus but by neither its dynamics nor its size.

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Synaptic interactions increase optic flow specificity.

Representations of optic flow are encoded in fly tangential neurons by pooling the signals of many retinotopically organized local motion-sensitive inputs as well as of other tangential cells originating in the ipsi- and contralateral half of the brain. In the so called HSE cell, a neuron involved in optomotor course control, two contralateral input elements, the H1 and H2 cells, mediate distinct EPSPs. These EPSPs frequently elicit spike-like depolarizations in the HSE cell. The synaptic transmission between the H2 and the HSE cell is analysed in detail and shown to be very reliable with respect to the amplitude and time-course of the postsynaptic potential. As a consequence of its synaptic input, the HSE cell responds best to wide-field motion, such as that generated on the eyes when the animal turns about its vertical body axis. It is shown that the specificity of the HSE cell for this type of optic flow is much enhanced if rapid membrane depolarizations, such as large-amplitude EPSPs or spike-like depolarizations, are taken into account rather than the average membrane potential.

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Variability in spike trains during constant and dynamic stimulation.

In a recent study, it was concluded that natural time-varying stimuli are represented more reliably in the brain than constant stimuli are. The results presented here disagree with this conclusion, although they were obtained from the same identified neuron (H1) in the fly's visual system. For large parts of the neuron's activity range, the variability of the responses was very similar for constant and time-varying stimuli and was considerably smaller than that in many visual interneurons of vertebrates.

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Encoding of motion in real time by the fly visual system.

Direction-selective cells in the fly visual system that have large receptive fields play a decisive role in encoding the time-dependent optic flow the animal encounters during locomotion. Recent experiments on the computations performed by these cells have highlighted the significance of dendritic integration and have addressed the role of spikes versus graded membrane potential changes in encoding optic flow information. It is becoming increasingly clear that the way optic flow is encoded in real time is constrained both by the computational needs of the animal in visually guided behaviour as well as by the specific properties of the underlying neuronal hardware.

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Temporal precision of the encoding of motion information by visual interneurons.

BACKGROUND: There is much controversy about the timescale on which neurons process and transmit information. On the one hand, a vast amount of information can be processed by the nervous system if the precise timing of individual spikes on a millisecond timescale is important. On the other hand, neuronal responses to identical stimuli often vary considerably and stochastic response fluctuations can exceed the mean response amplitude. Here, we examined the timescale on which neural responses could be locked to visual motion stimuli. RESULTS: Spikes of motion-sensitive neurons in the visual system of the blowfly are time-locked to visual motion with a precision in the range of several tens of milliseconds. Nevertheless, different motion-sensitive neurons with largely overlapping receptive fields generate a large proportion of spikes almost synchronously. This precision is brought about by stochastic rather than by motion-induced membrane-potential fluctuations elicited by the common peripheral input. The stochastic membrane-potential fluctuations contain more power at frequencies above 30-40 Hz than the motion-induced potential changes. A model of spike generation indicates that such fast membrane-potential changes are a major determinant of the precise timing of spikes. CONCLUSIONS: The timing of spikes in neurons of the motion pathway of the blowfly is controlled on a millisecond timescale by fast membrane-potential fluctuations. Despite this precision, spikes do not lock to motion stimuli on this timescale because visual motion does not induce sufficiently rapid changes in the membrane potential.

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How reliably does a neuron in the visual motion pathway of the fly encode behaviourally relevant information?

How reliably neurons convey information depends on the extent to which their activity is affected by stochastic processes which are omnipresent in the nervous system. The functional consequences of neuronal noise can only be assessed if the latter is related to the response components that are induced in a normal behavioural situation. In the present study the reliability of neural coding was investigated for an identified neuron in the pathway processing visual motion information of the fly (Lucilia cuprina). The stimuli used to investigate the neuronal performance were not exclusively defined by the experimenter. Instead, they were generated by the fly itself, i.e. by its own actions and reactions in a behavioural closed-loop experiment, and subsequently replayed to the animal while the activity of an identified motion-sensitive neuron was recorded. Although the time course of the neuronal responses is time-locked to the stimulus, individual response traces differ slightly from each other due to stochastic fluctuations in the timing and number of action potentials. Individual responses thus consist of a stimulus-induced and a stochastic response component. The stimulus-induced response component can be recovered most reliably from noisy neuronal signals if these are smoothed by intermediate-sized time windows (40-100 ms). At this time scale the best compromise is achieved between smoothing out the noise and maintaining the temporal resolution of the stimulus-induced response component. Consequently, in the visual motion pathway of the fly, behaviourally relevant motion stimuli can be resolved best at a time scale where the timing of individual spikes does not matter.

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Neural circuit tuning fly visual interneurons to motion of small objects. I. Dissection of the circuit by pharmacological and photoinactivation techniques.

1. Visual interneurons tuned to the motion of small objects are found in many animal species and are assumed to be the neuronal basis of figure-ground discrimination by relative motion. A well-examined example is the FD1-cell in the third visual neuropil of blowflies. This cell type responds best to motion of small objects. Motion of extended patterns elicits only small responses. As a neuronal mechanism that leads to such a response characteristic, it was proposed that the FD1-cell is inhibited by the two presumably GABAergic and, thus, inhibitory CH-cells, the VCH- and the DCH-cell. The CH-cells respond best to exactly that type of motion by which the activity of the FD1-cell is reduced. The hypothesis that the CH-cells inhibit the FD1-cell and, thus, mediate its selectivity to small moving objects was tested by ablating the CH-cells either pharmacologically or by photoinactivation. 2. After application of the gamma-aminobutyric acid (GABA) antagonist picrotoxinin, the FD1-cell responds more strongly to large-field than to small-field motion, i.e., it has lost its small-field selectivity. This suggests that the tuning of the FD1-cell to small moving objects relies on a GABAergic mechanism and, thus, most likely on the CH-cells. 3. The role of each CH-cell for small-field tuning was determined by inactivating them individually. They were injected with a fluorescent dye and then ablated by laser illumination. Only photoinactivation of the VCH-cell eliminated the specific selectivity of the FD1-cell for small-field motion. Ablation of the DCH-cell did not significantly change the response characteristic of the FD1-cell. This reveals the important role of the VCH-cells in mediating the characteristic sensitivity of the FD1-cell to motion of small objects. 4. The FD1-cell is most sensitive to motion of small objects in the ventral part of the ipsilateral visual field, whereas motion in the dorsal part influences the cell only weakly. This specific feature fits well to the sensitivity of the VCH-cell to ipsilateral motion that is most pronounced in the ventral part of the visual field. The spatial sensitivity distribution of the FD1-cell matches also the characteristics of figure-ground discrimination and fixation behavior.

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Neural circuit tuning fly visual neurons to motion of small objects. II. Input organization of inhibitory circuit elements revealed by electrophysiological and optical recording techniques.

1. The FD1-cell in the visual system of the fly is an identified visual interneuron that is specifically tuned to motion of small objects. In the companion paper it was shown that this response property is mediated by one of the two CH-cells, the VCH-cell, that inhibits the FD1-cell by GABAergic synapses. Here the input organization of the two CH-cells is analyzed by both electrophysiological and optical recording techniques. 2. Both CH-cells are excited by front-to-back motion in the ipsilateral and by back-to-front motion in the contralateral visual field. They respond maximally to binocular rotatory motion about the vertical axis of the animal. The latter response is only slightly less than the sum of the corresponding monocular response components. The relative contribution of the ipsi-and contralateral eye to the binocular response varies considerably between flies. In extreme cases it is dominated by either the ipsi- or the contralateral eye. The two CH-cells are not equally sensitive along the vertical axis of the eye. The DCH-cell has its sensitivity maximum in the dorsal part, the VCH-cell in the ventral part of the visual field. 3. The CH-cells have two arborizations, a large one in the posterior part of the third visual neuropil, the lobula plate, and a smaller one in the ipsilateral ventrolateral brain. With the calcium-sensitive dye fura-2 as an activity marker, it is analyzed which of these branches of the CH-cells receive the ipsi- and contralateral motion input, respectively. During motion in the preferred direction within the ipsilateral visual field, calcium accumulates only in the CH-cells' main arborization in the lobula plate but not in their branches in the ventrolateral brain, indicating that the arborization in the lobula plate is postsynaptic to the ipsilateral input. In contrast, contralateral motion in the preferred direction leads to calcium accumulation in both arborizations, suggesting that both are postsynaptic to contralateral input elements. During preferred direction motion in the upper or lower part of the ipsilateral visual field, calcium accumulates in only dorsal or ventral branches of the CH-cells' arborization in the lobula plate, respectively, revealing that their ipsilateral motion input is organized retinotopically. Because this arborization, most likely, is also the main output terminal of the CH-cells, it is both pre- and postsynaptic. This specific neuronal design is discussed with respect to its consequences for the mechanism of tuning the FD1-cell to motion of small objects.

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Photo-ablation of single neurons in the fly visual system reveals neural circuit for the detection of small moving objects.

Many animals use relative motion to segregate objects from their background. Nerve cells tuned to this visual cue have been found in various animal groups, such as insects, amphibians, birds and mammals. Well examined examples are the figure detection (FD) cells in the visual system of the blowfly. The mechanism that tunes a particular FD-cell, the FD1-cell, to small-field motion is analyzed by injecting individual visual interneurons with a fluorescent dye and ablating them by illumination with a laser beam. In this way, it is shown that the FD1-cell acquires its specific spatial tuning by inhibitory input from an identified GABAergic cell, the ventral centrifugal horizontal (VCH)-cell which is most sensitive to coherent large-field motion in front of both eyes. For the first time, the detection of small objects by evaluation of their motion parallax, thus, can be attributed to synaptic interactions between identified neurons.

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On the performance of biological movement detectors and ideal velocity sensors in the context of optomotor course stabilization.

It is often assumed that the ultimate goal of a motion-detection system is to faithfully represent the time-dependent velocity of a moving stimulus. This assumption, however, may be an arbitrary standard since the requirements for a motion-detection system depend on the task that is to be solved. In the context of optomotor course stabilization, the performance of a motion-sensitive neuron in the fly's optomotor pathway and of a hypothetical velocity sensor are compared for stimuli as are characteristic of a normal behavioral situation in which the actions and reactions of the animal directly affect its visual input. On average, tethered flies flying in a flight simulator are able to compensate to a large extent the retinal image displacements as are induced by an external disturbance of their flight course. The retinal image motion experienced by the fly under these behavioral closed-loop conditions was replayed in subsequent electrophysiological experiments to the animal while the activity of an identified neuron in the motion pathway was recorded. The velocity fluctuations as well as the corresponding neuronal signals were analyzed with a statistical approach taken from signal-detection theory. An observer scrutinizing either signal performs almost equally well in detecting the external disturbance.

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Membrane potential fluctuations determine the precision of spike timing and synchronous activity: a model study.

It is much debated on what time scale information is encoded by neuronal spike activity. With a phenomenological model that transforms time-dependent membrane potential fluctuations into spike trains, we investigate constraints for the timing of spikes and for synchronous activity of neurons with common input. The model of spike generation has a variable threshold that depends on the time elapsed since the previous action potential and on the preceding membrane potential changes. To ensure that the model operates in a biologically meaningful range, the model was adjusted to fit the responses of a fly visual interneuron to motion stimuli. The dependence of spike timing on the membrane potential dynamics was analyzed. Fast membrane potential fluctuations are needed to trigger spikes with a high temporal precision. Slow fluctuations lead to spike activity with a rate about proportional to the membrane potential. Thus, for a given level of stochastic input, the frequency range of membrane potential fluctuations induced by a stimulus determines whether a neuron can use a rate code or a temporal code. The relationship between the steepness of membrane potential fluctuations and the timing of spikes has also implications for synchronous activity in neurons with common input. Fast membrane potential changes must be shared by the neurons to produce synchronous activity.

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