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To understand the functioning of nervous systems and, in particular, how they control behaviour we must bridge many levels of complexity from molecules, cells and synapses to perception behaviour. Although experimental analysis is a... more
To understand the functioning of nervous systems and, in particular, how they control behaviour we must bridge many levels of complexity from molecules, cells and synapses to perception behaviour. Although experimental analysis is a precondition for understanding by nervous systems, it is in no way sufficient. The understanding is aided at all levels of complexity by modelling. Modelling proved to be an inevitable tool to test the experimentally established hypotheses. In this review it will by exemplified by three case studies that the appropriate level of modelling needs to be adjusted to the particular computational problems that are to be solved. (1) Specific features of the highly virtuosic pursuit behaviour of male flies can be understood on the basis of a phenomenological model that relates the visual input to the motor output. (2) The processing of retinal image motion as is experienced by freely moving animals can be understood on the basis of a model consisting of algorith...
Research Interests: Neuroscience, Psychology, Electrophysiology, Motion perception, Signal Transduction, and 15 moreBrain, Synapse, Animals, Reaction Time, Reliability, Visual System, Synaptic Transmission, Neurons, Diptera, Neural Computation, Membrane Potential, Action Potentials, Visual Motion, Neurosciences, and Dynamic Range
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... Prof. Martin Egelhaaf Dr. Roland Kern, Dr. Rafael Kurtz, PD Dr. Anne-Kathrin Warzecha Universität Bielefeld The “FliMaX” panorama cinema was developed specifically for studying the brain performance of flies. The fly is located at its... more
... Prof. Martin Egelhaaf Dr. Roland Kern, Dr. Rafael Kurtz, PD Dr. Anne-Kathrin Warzecha Universität Bielefeld The “FliMaX” panorama cinema was developed specifically for studying the brain performance of flies. The fly is located at its centre and looks onto the screen. ...
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Nervous systems encode information about dynamically changing sensory input by changes in neuronal activity. Neuronal activity changes, however, also arise from noise sources within and outside the nervous system or from changes of the... more
Nervous systems encode information about dynamically changing sensory input by changes in neuronal activity. Neuronal activity changes, however, also arise from noise sources within and outside the nervous system or from changes of the animal's behavioral state. The resulting variability of neuronal responses in representing sensory stimuli limits the reliability with which animals can respond to stimuli and may thus even affect the chances for survival in certain situations. Relevant sources of noise arising at different stages along the motion vision pathway have been investigated from the sensory input to the initiation of behavioral reactions. Here, we concentrate on the reliability of processing visual motion information in flies. Flies rely on visual motion information to guide their locomotion. They are among the best established model systems for the processing of visual motion information allowing us to bridge the gap between behavioral performance and underlying neuronal computations. It has been possible to directly assess the consequences of noise at major stages of the fly's visual motion processing system on the reliability of neuronal signals. Responses of motion sensitive neurons and their variability have been related to optomotor movements as indicators for the overall performance of visual motion computation. We address whether and how noise already inherent in the stimulus, e.g. photon noise for the visual system, influences later processing stages and to what extent variability at the output level of the sensory system limits behavioral performance. Recent advances in circuit analysis and the progress in monitoring neuronal activity in behaving animals should now be applied to understand how the animal meets the requirements of fast and reliable manoeuvres in naturalistic situations.
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So far, it remains largely unresolved to what extent neuronal noise affects behavioral responses. Here, we investigate, where in the human visual motion pathway noise originates that limits the performance of the entire system. In... more
So far, it remains largely unresolved to what extent neuronal noise affects behavioral responses. Here, we investigate, where in the human visual motion pathway noise originates that limits the performance of the entire system. In particular, we ask whether perception and eye movements are limited by a common noise source, or whether processing stages after the separation into different streams limit their performance. We use the ocular following response of human subjects and a simultaneously performed psychophysical paradigm to directly compare perceptual and oculomotor system with respect to their speed discrimination ability. Our results show that on the open-loop condition the perceptual system is superior to the oculomotor system and that the responses of both systems are not correlated. Two alternative conclusions can be drawn from these findings. Either the perceptual and oculomotor pathway are effectively separate, or the amount of post-sensory (motor) noise is not negligible in comparison to the amount of sensory noise. In view of well-established experimental findings and due to plausibility considerations, we favor the latter conclusion.
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Response variability is a fundamental issue in neural coding because it limits all information processing. The reliability of neuronal coding is quantified by various approaches in different studies. In most cases it is largely unclear to... more
Response variability is a fundamental issue in neural coding because it limits all information processing. The reliability of neuronal coding is quantified by various approaches in different studies. In most cases it is largely unclear to what extent the conclusions depend on the applied reliability measure, making a comparison across studies almost impossible. We demonstrate that different reliability measures can lead to very different conclusions even if applied to the same set of data: in particular, we applied information theoretical measures (Shannon information capacity and Kullback-Leibler divergence) as well as a discrimination measure derived from signal-detection theory to the responses of blowfly photoreceptors which represent a well established model system for sensory information processing. We stimulated the photoreceptors with white noise modulated light intensity fluctuations of different contrasts. Surprisingly, the signal-detection approach leads to a safe discrimination of the photoreceptor response even when the response signal-to-noise ratio (SNR) is well below unity whereas Shannon information capacity and also Kullback-Leibler divergence indicate a very low performance. Applying different measures, can, therefore, lead to very different interpretations concerning the system's coding performance. As a consequence of the lower sensitivity compared to the signal-detection approach, the information theoretical measures overestimate internal noise sources and underestimate the importance of photon shot noise. We stress that none of the used measures and, most likely no other measure alone, allows for an unbiased estimation of a neuron's coding properties. Therefore the applied measure needs to be selected with respect to the scientific question and the analyzed neuron's functional context.
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Compensatory eye, head or body movements are essential to stabilize the gaze or the path of locomotion. Because such compensatory responses usually lag the sensory input by a time delay, the underlying control system is prone to... more
Compensatory eye, head or body movements are essential to stabilize the gaze or the path of locomotion. Because such compensatory responses usually lag the sensory input by a time delay, the underlying control system is prone to instability, at least if it operates with a high gain in order to compensate disturbances efficiently. In behavioural experiments it could be shown that the optomotor system of the fly does not get unstable even when its overall gain is so high that, on average, imposed disturbances are compensated to a large extent. Fluctuations of the animal's torque signal do not build up. Rather they are accompanied by only small-amplitude jittery retinal image displacements that rarely slip over more than a few neighbouring photoreceptors. Combined electrophysiological experiments on a pair of neurons in the fly's optomotor pathway and model simulations of the optomotor control system suggest that this relative stability of the optomotor system is the consequence of the specific velocity dependence of biological movement detectors. The response of the movement detectors first increases with increasing velocity, reaches a maximum and then decreases again. As a consequence, large-amplitude fluctuations in pattern velocity, as are generated when the optomotor system tends to get unstable, are transmitted with a small gain leading to only relatively small torque fluctuations and, thus, small-amplitude image displacements.
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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... more
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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Response variability is a fundamental issue in neural coding because it limits all information processing. The reliability of neuronal coding is quantified by various approaches in different studies. In most cases it is largely unclear to... more
Response variability is a fundamental issue in neural coding because it limits all information processing. The reliability of neuronal coding is quantified by various approaches in different studies. In most cases it is largely unclear to what extent the conclusions depend on the applied reliability measure, making a comparison across studies almost impossible. We demonstrate that different reliability measures can lead to very different conclusions even if applied to the same set of data: in particular, we applied information theoretical measures (Shannon information capacity and Kullback-Leibler divergence) as well as a discrimination measure derived from signal-detection theory to the responses of blowfly photoreceptors which represent a well established model system for sensory information processing. We stimulated the photoreceptors with white noise modulated light intensity fluctuations of different contrasts. Surprisingly, the signal-detection approach leads to a safe discrimination of the photoreceptor response even when the response signal-to-noise ratio (SNR) is well below unity whereas Shannon information capacity and also Kullback-Leibler divergence indicate a very low performance. Applying different measures, can, therefore, lead to very different interpretations concerning the system's coding performance. As a consequence of the lower sensitivity compared to the signal-detection approach, the information theoretical measures overestimate internal noise sources and underestimate the importance of photon shot noise. We stress that none of the used measures and, most likely no other measure alone, allows for an unbiased estimation of a neuron's coding properties. Therefore the applied measure needs to be selected with respect to the scientific question and the analyzed neuron's functional context.
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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... more
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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Kleine Gehirne können große Gehirne an Leistung bei weitem übertreffen. So hat sich die Fliege als hervorragendes Modellsystem für die Bildverarbeitung im Gehirn erwiesen
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Raising the head temperature within a behaviourally relevant range has strong effects on the performance of an identified neuron, the H1 neuron, in the visual motion pathway of blowflies. The effect is seen as an increase in the mean... more
Raising the head temperature within a behaviourally relevant range has strong effects on the performance of an identified neuron, the H1 neuron, in the visual motion pathway of blowflies. The effect is seen as an increase in the mean amplitude of the responses to motion under both transient and steady-state conditions, a considerable decrease in the response latency and an improvement in the reliability of the responses to motion. These temperature-dependent effects are independent of whether the animal is exposed to transient temperature changes or is maintained continuously at the same temperature for its entire life. The changes in the neuronal response properties with temperature may be of immediate functional significance for the animal under its normal operating conditions. In particular, the decrease in latency and the improvement in the reliability with increasing temperature may be relevant for the fly when executing its extremely virtuosic flight manoeuvres.
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The neural encoding of sensory stimuli is usually investigated for spike responses, although many neurons are known to convey information by graded membrane potential changes. We compare by model simulations how well different dynamical... more
The neural encoding of sensory stimuli is usually investigated for spike responses, although many neurons are known to convey information by graded membrane potential changes. We compare by model simulations how well different dynamical stimuli can be discriminated on the basis of spiking or graded responses. Although a continuously varying membrane potential contains more information than binary spike trains, we find situations where different stimuli can be better discriminated on the basis of spike responses than on the basis of graded responses. Spikes can be superior to graded membrane potential fluctuations if spikes sharpen the temporal structure of neuronal responses by amplifying fast transients of the membrane potential. Such fast membrane potential changes can be induced deterministically by the stimulus or can be due to membrane potential noise that is influenced in its statistical properties by the stimulus. The graded response mode is superior for discrimination between stimuli on a fine time scale.
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In tethered flying houseflies (Musca domestica), the yaw torque produced by the wings is accompanied by postural changes of the abdomen and hindlegs. In free flight, these body movements would jointly lead to turning manoeuvres of the... more
In tethered flying houseflies (Musca domestica), the yaw torque produced by the wings is accompanied by postural changes of the abdomen and hindlegs. In free flight, these body movements would jointly lead to turning manoeuvres of the animal. By recording the yaw torque together with the lateral deflections of either the abdomen or the hindlegs, it is shown that these motor output systems act in a highly synergistic way during two types of visual orientation behavior, compensatory optomotor turning reactions and orientation turns elicited by moving objects. This high degree of coordination is particularly conspicuous for the pathway activated by moving objects. Here, orientation responses either may be induced or may fail to be generated always simultaneously in all three motor output systems. This suggests that the pathway mediating orientation turns towards objects is gated before it segregates into the respective motor control systems of the wings, the abdomen and the hindlegs.