Anne-Kathrin Warzecha - Academia.edu (original) (raw)
Papers by Anne-Kathrin Warzecha
To understand the functioning of nervous systems and, in particular, how they control behaviour w... 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. The processing of retinal image motion as is experienced by freely moving animals can be understood on the basis of a model consisting of algorithmic components and components which represent a simple equivalent circuit of nerve cells. Behaviourally relevant features of the reliability of encoding of visual motion information can be understood by modelling the transformation of postsynaptic potentials into sequences of spike trains.
Journal of Neurophysiology
1. Visual interneurons tuned to the motion of small objects are found in many animal species and ... more 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. JOI JKNAL.
Journal of Neurophysiology
To understand the functioning of nervous systems and, in particular, how they control behaviour w... 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...
Frontiers in Neuroscience, 2004
Encyclopedia of Neuroscience, 2009
Motion Vision, 2001
Changes in the activity of sensory neurones carry information about a given stimulus. However, ne... more Changes in the activity of sensory neurones carry information about a given stimulus. However, neuronal activity changes may also arise from noise sources within or outside the nervous system. Here, the reliability of encoding of visual motion information is analysed in the visual motion pathway of the fly and compared to the findings obtained in other animal species. Several constraints determine and limit the reliability of encoding of visual motion information: (i) the biophysical mechanisms underlying the generation of action potentials; (ii) the computations performed in the motion vision pathway; and (iii) the dynamical properties of motion stimuli an animal encounters when moving around in its natural environment. The responses of fly motion-sensitive neurones are coupled to visual motion on a timescale of milliseconds up to several tens of milliseconds, depending on the dynamics of the motion stimuli. Only rapid velocity changes lead to a precise time-locking of spikes to the motion stimuli on a millisecond scale. Otherwise, the exact timing of spikes is mainly determined by fast stochastic membrane-potential fluctuations. It is discussed on what timescale behaviourally relevant motion information may be encoded.
Synaptic transmission is usually studied in vitro with electrical stimulation replacing the natur... more Synaptic transmission is usually studied in vitro with electrical stimulation replacing the natural input of the system. In contrast, we analyzed in vivo transfer of visual motion information from graded-potential presynaptic to spiking postsynaptic neurons in the fly. Motion in the null direction leads to hyperpolarization of the presynaptic neuron but does not much influence the postsynaptic cell, because its firing rate is already low during rest, giving only little scope for further reductions. In contrast, preferred-direction motion leads to presynaptic depolarizations and increases the postsynaptic spike rate. Signal transfer to the postsynaptic cell is linear and reliable for presynaptic graded membrane potential fluctuations of up to approximately 10 Hz. This frequency range covers the dynamic range of velocities that is encoded with a high gain by visual motion-sensitive neurons. Hence, information about preferred-direction motion is transmitted largely undistorted ensuring a consistent dependency of neuronal signals on stimulus parameters, such as motion velocity. Postsynaptic spikes are often elicited by rapid presynaptic spike-like depolarizations which superimpose the graded membrane potential. Although the timing of most of these spike-like depolarizations is set by noise and not by the motion stimulus, it is preserved at the synapse with millisecond precision.
Journal of Experimental Biology, 2010
The strength of stimulus-induced responses at the neuronal and the behavioural level often depend... more The strength of stimulus-induced responses at the neuronal and the behavioural level often depends on the internal state of an animal. Within pathways processing sensory information and eventually controlling behavioural responses, such gain changes can originate at several sites. Using motion-sensitive lobula plate tangential cells (LPTCs) of blowflies, we address whether and in which way information processing changes for two different states of motor activity. We distinguish between the two states on the basis of haltere movements. Halteres are the evolutionarily transformed hindwings of flies. They oscillate when the animals walk or fly. LPTCs mediate, amongst other behaviours, head optomotor responses. These are either of large or small amplitude depending on the state of motor activity. Here we find that LPTC responses also depend on the motor activity of flies. In particular, LPTC responses are enhanced when halteres oscillate. Nevertheless, the response changes of LPTCs do not account for the corresponding large gain changes of head movements. Moreover, haltere activity itself does not change the activity of LPTCs. Instead, we propose that a central signal associated with motor activity changes the gain of head optomotor responses and the response properties of LPTCs.
Journal of Experimental Biology, 2009
Behavioural responses of an animal are variable even when the animal experiences the same sensory... more Behavioural responses of an animal are variable even when the animal experiences the same sensory input several times. This variability can arise from stochastic processes inherent to the nervous system. Also, the internal state of an animal may influence a particular behavioural response. In the present study, we analyse the variability of visually induced head pitch responses of tethered blowflies by high-speed cinematography. We found these optomotor responses to be highly variable in amplitude. Most of the variability can be attributed to two different internal states of the flies with high and low optomotor gain, respectively. Even within a given activity state, there is some variability of head optomotor responses. The amount of this variability differs for the two optomotor gain states. Moreover, these two activity states can be distinguished on a fine timescale and without visual stimulation, on the basis of the occurrence of peculiar head jitter movements. Head jitter goes along with high gain optomotor responses and haltere oscillations. Halteres are evolutionary transformed hindwings that oscillate when blowflies walk or fly. Their main function is to serve as equilibrium organs by detecting Coriolis forces and to mediate gaze stabilisation. However, their basic oscillating activity was also suggested to provide a gain-modulating signal. Our experiments demonstrate that halteres are not necessary for high gain head pitch to occur. Nevertheless, we find the halteres to be responsible for one component of head jitter movements. This component may be the inevitable consequence of their function as equilibrium and gaze-stabilising organs.
PLoS ONE, 2011
Behavioral responses of an animal vary even when they are elicited by the same stimulus. This var... more Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly's (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensorymotor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system.
German Research, 2003
... Prof. Martin Egelhaaf Dr. Roland Kern, Dr. Rafael Kurtz, PD Dr. Anne-Kathrin Warzecha Univers... 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. ...
Neuroscience Letters, 1992
Many animals use relative motion to segregate objects from their background . Nerve cells tuned t... more 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 [3, 4, 6,, amphibians [32], birds and mammals [1,. Well examined examples are the figure detection (FD) cells in the visual system of the blowfly [6,. The mechanism that tunes a particular FD-cell, the FDl-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 FDl-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.
Naturwissenschaften, 1995
Journal of Physiology-Paris, 2013
Nervous systems encode information about dynamically changing sensory input by changes in neurona... 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.
Journal of Neurophysiology, 2006
publishes original articles on the function of the nervous system. It is published 12 times a yea... more publishes original articles on the function of the nervous system. It is published 12 times a year Journal of Neurophysiology on September 14, 2006 jn.physiology.org Downloaded from M E T H O D S
Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology, 1997
Translatory movement of an animal in its environment induces optic¯ow that contains information a... more Translatory movement of an animal in its environment induces optic¯ow that contains information about the three-dimensional layout of the surroundings: as a rule, images of objects that are closer to the animal move faster across the retina than those of more distant objects. Such relative motion cues are used by¯ies to detect objects in front of a structured background. We confronted¯ying¯ies, tethered to a torque meter, with front-to-back motion of patterns displayed on two CRT screens, thereby simulating translatory motion of the background as experienced by an animal during straight¯ight. The torque meter measured the instantaneous turning responses of the¯y around its vertical body axis. During short time intervals, object motion was superimposed on background pattern motion. The average turning response towards such an object depends on both object and background velocity in a characteristic way: (1) in order to elicit signi®cant responses object motion has to be faster than background motion; (2) background motion within a certain range of velocities improves object detection. These properties can be interpreted as adaptations to situations as they occur in natural free¯ight. We con®rmed that the measured responses were mediated mainly by a control system specialized for the detection of objects rather than by the compensatory optomotor system responsible for course stabilization.
Current Opinion in Neurobiology, 1999
Direction-selective cells in the fly visual system that have large receptive fields play a decisi... more 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.
Vision Research, 2010
So far, it remains largely unresolved to what extent neuronal noise affects behavioral responses.... 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.
To understand the functioning of nervous systems and, in particular, how they control behaviour w... 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. The processing of retinal image motion as is experienced by freely moving animals can be understood on the basis of a model consisting of algorithmic components and components which represent a simple equivalent circuit of nerve cells. Behaviourally relevant features of the reliability of encoding of visual motion information can be understood by modelling the transformation of postsynaptic potentials into sequences of spike trains.
Journal of Neurophysiology
1. Visual interneurons tuned to the motion of small objects are found in many animal species and ... more 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. JOI JKNAL.
Journal of Neurophysiology
To understand the functioning of nervous systems and, in particular, how they control behaviour w... 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...
Frontiers in Neuroscience, 2004
Encyclopedia of Neuroscience, 2009
Motion Vision, 2001
Changes in the activity of sensory neurones carry information about a given stimulus. However, ne... more Changes in the activity of sensory neurones carry information about a given stimulus. However, neuronal activity changes may also arise from noise sources within or outside the nervous system. Here, the reliability of encoding of visual motion information is analysed in the visual motion pathway of the fly and compared to the findings obtained in other animal species. Several constraints determine and limit the reliability of encoding of visual motion information: (i) the biophysical mechanisms underlying the generation of action potentials; (ii) the computations performed in the motion vision pathway; and (iii) the dynamical properties of motion stimuli an animal encounters when moving around in its natural environment. The responses of fly motion-sensitive neurones are coupled to visual motion on a timescale of milliseconds up to several tens of milliseconds, depending on the dynamics of the motion stimuli. Only rapid velocity changes lead to a precise time-locking of spikes to the motion stimuli on a millisecond scale. Otherwise, the exact timing of spikes is mainly determined by fast stochastic membrane-potential fluctuations. It is discussed on what timescale behaviourally relevant motion information may be encoded.
Synaptic transmission is usually studied in vitro with electrical stimulation replacing the natur... more Synaptic transmission is usually studied in vitro with electrical stimulation replacing the natural input of the system. In contrast, we analyzed in vivo transfer of visual motion information from graded-potential presynaptic to spiking postsynaptic neurons in the fly. Motion in the null direction leads to hyperpolarization of the presynaptic neuron but does not much influence the postsynaptic cell, because its firing rate is already low during rest, giving only little scope for further reductions. In contrast, preferred-direction motion leads to presynaptic depolarizations and increases the postsynaptic spike rate. Signal transfer to the postsynaptic cell is linear and reliable for presynaptic graded membrane potential fluctuations of up to approximately 10 Hz. This frequency range covers the dynamic range of velocities that is encoded with a high gain by visual motion-sensitive neurons. Hence, information about preferred-direction motion is transmitted largely undistorted ensuring a consistent dependency of neuronal signals on stimulus parameters, such as motion velocity. Postsynaptic spikes are often elicited by rapid presynaptic spike-like depolarizations which superimpose the graded membrane potential. Although the timing of most of these spike-like depolarizations is set by noise and not by the motion stimulus, it is preserved at the synapse with millisecond precision.
Journal of Experimental Biology, 2010
The strength of stimulus-induced responses at the neuronal and the behavioural level often depend... more The strength of stimulus-induced responses at the neuronal and the behavioural level often depends on the internal state of an animal. Within pathways processing sensory information and eventually controlling behavioural responses, such gain changes can originate at several sites. Using motion-sensitive lobula plate tangential cells (LPTCs) of blowflies, we address whether and in which way information processing changes for two different states of motor activity. We distinguish between the two states on the basis of haltere movements. Halteres are the evolutionarily transformed hindwings of flies. They oscillate when the animals walk or fly. LPTCs mediate, amongst other behaviours, head optomotor responses. These are either of large or small amplitude depending on the state of motor activity. Here we find that LPTC responses also depend on the motor activity of flies. In particular, LPTC responses are enhanced when halteres oscillate. Nevertheless, the response changes of LPTCs do not account for the corresponding large gain changes of head movements. Moreover, haltere activity itself does not change the activity of LPTCs. Instead, we propose that a central signal associated with motor activity changes the gain of head optomotor responses and the response properties of LPTCs.
Journal of Experimental Biology, 2009
Behavioural responses of an animal are variable even when the animal experiences the same sensory... more Behavioural responses of an animal are variable even when the animal experiences the same sensory input several times. This variability can arise from stochastic processes inherent to the nervous system. Also, the internal state of an animal may influence a particular behavioural response. In the present study, we analyse the variability of visually induced head pitch responses of tethered blowflies by high-speed cinematography. We found these optomotor responses to be highly variable in amplitude. Most of the variability can be attributed to two different internal states of the flies with high and low optomotor gain, respectively. Even within a given activity state, there is some variability of head optomotor responses. The amount of this variability differs for the two optomotor gain states. Moreover, these two activity states can be distinguished on a fine timescale and without visual stimulation, on the basis of the occurrence of peculiar head jitter movements. Head jitter goes along with high gain optomotor responses and haltere oscillations. Halteres are evolutionary transformed hindwings that oscillate when blowflies walk or fly. Their main function is to serve as equilibrium organs by detecting Coriolis forces and to mediate gaze stabilisation. However, their basic oscillating activity was also suggested to provide a gain-modulating signal. Our experiments demonstrate that halteres are not necessary for high gain head pitch to occur. Nevertheless, we find the halteres to be responsible for one component of head jitter movements. This component may be the inevitable consequence of their function as equilibrium and gaze-stabilising organs.
PLoS ONE, 2011
Behavioral responses of an animal vary even when they are elicited by the same stimulus. This var... more Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly's (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensorymotor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system.
German Research, 2003
... Prof. Martin Egelhaaf Dr. Roland Kern, Dr. Rafael Kurtz, PD Dr. Anne-Kathrin Warzecha Univers... 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. ...
Neuroscience Letters, 1992
Many animals use relative motion to segregate objects from their background . Nerve cells tuned t... more 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 [3, 4, 6,, amphibians [32], birds and mammals [1,. Well examined examples are the figure detection (FD) cells in the visual system of the blowfly [6,. The mechanism that tunes a particular FD-cell, the FDl-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 FDl-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.
Naturwissenschaften, 1995
Journal of Physiology-Paris, 2013
Nervous systems encode information about dynamically changing sensory input by changes in neurona... 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.
Journal of Neurophysiology, 2006
publishes original articles on the function of the nervous system. It is published 12 times a yea... more publishes original articles on the function of the nervous system. It is published 12 times a year Journal of Neurophysiology on September 14, 2006 jn.physiology.org Downloaded from M E T H O D S
Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology, 1997
Translatory movement of an animal in its environment induces optic¯ow that contains information a... more Translatory movement of an animal in its environment induces optic¯ow that contains information about the three-dimensional layout of the surroundings: as a rule, images of objects that are closer to the animal move faster across the retina than those of more distant objects. Such relative motion cues are used by¯ies to detect objects in front of a structured background. We confronted¯ying¯ies, tethered to a torque meter, with front-to-back motion of patterns displayed on two CRT screens, thereby simulating translatory motion of the background as experienced by an animal during straight¯ight. The torque meter measured the instantaneous turning responses of the¯y around its vertical body axis. During short time intervals, object motion was superimposed on background pattern motion. The average turning response towards such an object depends on both object and background velocity in a characteristic way: (1) in order to elicit signi®cant responses object motion has to be faster than background motion; (2) background motion within a certain range of velocities improves object detection. These properties can be interpreted as adaptations to situations as they occur in natural free¯ight. We con®rmed that the measured responses were mediated mainly by a control system specialized for the detection of objects rather than by the compensatory optomotor system responsible for course stabilization.
Current Opinion in Neurobiology, 1999
Direction-selective cells in the fly visual system that have large receptive fields play a decisi... more 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.
Vision Research, 2010
So far, it remains largely unresolved to what extent neuronal noise affects behavioral responses.... 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.