Synaptic transfer of dynamic motion information between identified neurons in the visual system of the blowfly

Warzecha, Anne-Kathrin; Kurtz, Rafael; Egelhaaf, Martin

doi:10.1016/s0306-4522(03)00204-5

Cited by 30 publications

(64 citation statements)

References 53 publications

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“…The V1 cell receives visual motion information from the four most frontal VS cells and transforms the resulting postsynaptic potentials into spike activity (Kurtz et al, 2001). This synaptic connection provides linear and robust transfer of information from VS to V1 on fluctuations in motion velocity of up to 10 Hz (Warzecha et al, 2003;Kalb et al, 2006;Beckers et al, 2007). By simultaneous recordings of presynaptic and postsynaptic activity, we were able to narrow the potential sites of adaptation-induced effects: adaptation effects that are present in the V1 cell, but not in VS cells, arise during synaptic transfer or in the postsynaptic cell itself.…”

Section: Introductionmentioning

confidence: 92%

“…For all coherence calculations, the presynaptic and postsynaptic signals were shifted according to the response latency obtained from the cross-correlation of the responses and the velocity profile of the motion stimulus. The reconstruction followed well established linear filtering procedures (Gabbiani and Koch, 1998;Warzecha et al, 2003). In brief, when reconstructing a time-dependent stimulus s(t) from a response r(t), the reverse linear filter that minimizes the mean square error between the reconstructed stimulus and s(t) is given in frequency space by the following:…”

Section: Experimental Protocolmentioning

confidence: 99%

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Adaptation of Velocity Encoding in Synaptically Coupled Neurons in the Fly Visual System

Kalb¹,

Egelhaaf²,

Kurtz³

2008

J. Neurosci.

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Although many adaptation-induced effects on neuronal response properties have been described, it is often unknown at what processing stages in the nervous system they are generated. We focused on fly visual motion-sensitive neurons to identify changes in response characteristics during prolonged visual motion stimulation. By simultaneous recordings of synaptically coupled neurons, we were able to directly compare adaptation-induced effects at two consecutive processing stages in the fly visual motion pathway. This allowed us to narrow the potential sites of adaptation effects within the visual system and to relate them to the properties of signal transfer between neurons. Motion adaptation was accompanied by a response reduction, which was somewhat stronger in postsynaptic than in presynaptic cells. We found that the linear representation of motion velocity degrades during adaptation to a white-noise velocity-modulated stimulus. This effect is caused by an increasingly nonlinear velocity representation rather than by an increase of noise and is similarly strong in presynaptic and postsynaptic neurons. In accordance with this similarity, the dynamics and the reliability of interneuronal signal transfer remained nearly constant. Thus, adaptation is mainly based on processes located in the presynaptic neuron or in more peripheral processing stages. In contrast, changes of transfer properties at the analyzed synapse or in postsynaptic spike generation contribute little to changes in velocity coding during motion adaptation.

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Section: Introductionmentioning

confidence: 92%

Section: Experimental Protocolmentioning

confidence: 99%

Adaptation of Velocity Encoding in Synaptically Coupled Neurons in the Fly Visual System

Kalb¹,

Egelhaaf²,

Kurtz³

2008

J. Neurosci.

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“…During ipsilateral upward motion their membrane potential hyperpolarizes. VS-cells are presynaptic to a spiking neuron, the V1-cell, which relays the motion information to the contralateral brain hemisphere [14,27].…”

Section: Methodsmentioning

confidence: 99%

In vivo two-photon laser-scanning microscopy of Ca2+ dynamics in visual motion-sensitive neurons

Kalb

Nielsen

Fricke

et al. 2004

Biochemical and Biophysical Research Communications

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We applied two-photon laser-scanning microscopy (TPLSM) to motion-sensitive visual interneurons of the fly to study Ca 2þ dynamics in vivo at a higher spatial and temporal resolution than possible with conventional fluorescence microscopy. Based on a custom-built two-photon microscope, we performed line scans to measure changes in presynaptic Ca 2þ concentrations elicited by visual stimulation. We used a fast avalanche photodiode (APD) with a high quantum efficiency to detect even low levels of emitted fluorescence. Our experiments show that our in vivo preparation is amenable to TPLSM: with excitation intensities low enough not to cause photodamage, activity-dependent fluorescence changes of Ca 2þ -sensitive dyes can be detected in small neuronal branches. The performance of two-photon and conventional Ca 2þ imaging carried out consecutively at the same neuron is compared and it is demonstrated that two-photon imaging allows us to detect differences in Ca 2þ dynamics between individual neurites.

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“…Thus, for a given level of membrane potential noise the frequency range of membrane potential fluctuations induced by a stimulus determines whether a neuron can use a rate code or a temporal code. Since the computations underlying motion detection inevitably require time constants of some tens of milliseconds (Borst and Egelhaaf 1989), they attenuate the neural responses to high-frequency fluctuations in pattern velocity Warzecha et al 1998Warzecha et al , 2003 (Fig. 3D).…”

Section: Precision Of Neuronal Encoding Of Visual Motion Information:mentioning

confidence: 99%

“…3D). Hence, only when the velocity changes are very rapid and large the resulting depolarisations of the motion-sensitive neuron are sufficiently pronounced to elicit spikes with a millisecond precision (Ruyter van Steveninck and Bialek 1995;Warzecha and Egelhaaf 2001;Ruyter van Steveninck et al 2001;Warzecha et al 2003). Otherwise, the exact timing of spikes is determined mostly by membrane potential noise and visual motion is most likely represented by the spike rate (Fig.…”

Section: Precision Of Neuronal Encoding Of Visual Motion Information:mentioning

confidence: 99%

Visually guided orientation in flies: case studies in computational neuroethology

Egelhaaf

Böddeker

Kern

et al. 2003

Journal of Comparative Physiology A: Sensory, Neural, and Behav

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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 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 algorithmic components and components which represent a simple equivalent circuit of nerve cells. (3) 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.

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Synaptic transfer of dynamic motion information between identified neurons in the visual system of the blowfly

Cited by 30 publications

References 53 publications

Adaptation of Velocity Encoding in Synaptically Coupled Neurons in the Fly Visual System

Adaptation of Velocity Encoding in Synaptically Coupled Neurons in the Fly Visual System

In vivo two-photon laser-scanning microscopy of Ca2+ dynamics in visual motion-sensitive neurons

Visually guided orientation in flies: case studies in computational neuroethology

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