Information theoretical evaluation of parametric models of gain control in blowfly photoreceptor cells

Hateren, van Johannes; Snippe, H.P.

doi:10.1016/s0042-6989(01)00052-9

Cited by 94 publications

(105 citation statements)

References 21 publications

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“…Phototransduction is nonlinear, with receptor membrane potential dependent on luminance in a roughly logarithmic manner. This dependence holds about an operating point that is adapted as a functional of the luminance history (van Hateren and Snippe, 2001;van Hateren, 1997). Fly photoreceptors are much faster in their temporal response properties than vertebrate receptors, but nonetheless have a lowpass characteristic with corner frequencies in the range 40Hz-70Hz in diurnal insects (Laughlin and Weckström, 1993).…”

Section: Early Visionmentioning

confidence: 99%

Velocity constancy and models for wide-field visual motion detection in insects

2005

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Abstract. The tangential neurons in the lobula plate region of the flies are known to respond to visual motion across broad receptive fields in visual space. When intracellular recordings are made from t angential neurons while the intact animal is stimulated visually with moving natural imagery, we find that neural response depends upon speed of motion but is nearly invariant with respect to variations in natural scenery. We refer to this invariance as velocity constancy. It is remarkable because natural scenes, in spite of similarities in spatial structure, vary considerably in contrast, and contrast dependence is a feature of neurons in the early visual pathway as well as of most models for the elementary operations of visual motion detection. Thus, we expect that operations must be present in the processing pathway that reduce contrast dependence in order to approximate velocity constancy. We consider models for such operations, including spatial filtering, motion adaptation, saturating nonlinearities, and nonlinear spatial integration by the tangential neurons themselves, and evaluate their effects in simulations of a tangential neuron and precursor processing in response to animated natural imagery. We conclude that all such features reduce interscene variance in response, but that the model system does not approach velocity constancy as closely as the biological tangential cell.

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Section: Early Visionmentioning

confidence: 99%

Velocity constancy and models for wide-field visual motion detection in insects

2005

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“…Therefore we quantify the Signal to Noise Ratio (SNR) of the output for each input light level. Because the number of repetitions is limited, we apply an bias corrected SNR estimation procedure [20,13]. We estimate the signal y raw = y by the ensamble average as y = J repeated stimuli.…”

Section: Signal To Noise Ratiomentioning

confidence: 99%

“…We estimate the signal y raw = y by the ensamble average as y = J repeated stimuli. Adopting the notation in [13], we obtain the raw signal and noise power in the voltage output by…”

Section: Signal To Noise Ratiomentioning

confidence: 99%

“…The latter has been shown to linearise fly photoreceptor outputs and does not excite its nonlinear dynamics as natural scenes do [12,5]. Motivated by this observation, van Hateren developed a model that is able to simulate fly photoreceptor responses to natural light statistics [13]. However, in this study, the light stimuli was limited to a 2-3 log unit range and the model itself had a fixed structure.…”

Section: Introductionmentioning

confidence: 99%

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Data Modelling for Analysis of Adaptive Changes in Fly Photoreceptors

Friederich

Coca

Billings

et al. 2009

Lecture Notes in Computer Science

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Monograph ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. Abstract. Adaptation is a hallmark of sensory processing. We studied neural adaptation in intracellular voltage responses of the R1-R6 photoreceptors, of the fruit fly Drosophila, subjected to light patterns of naturalistic distribution at varying intensity levels. We use experimental data in a stepwise empirical modeling procedure to estimate a non-linear dynamical model (NARMAX) with variable gain. This model can describe accurately the observed adaptation process at each new level of changing light inputs. Generalized frequency response functions were used to visualize and quantify adaptation in the frequency domain.

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“…An integral part of the coherence analysis is the reverse reconstruction technique (Haag and Borst 1998;van Hateren and Snippe 2001): To obtain an estimated (reconstructed) time-dependent stimulus from the measured response, the time-dependent neuronal response is convolved with the linear temporal Wlter that minimises the diVerence between the real stimulus and the reconstructed stimulus. The coherence function gives a measure of the similarity between the real and the reconstructed stimulus for diVerent frequencies.…”

Section: Visual Stimulationmentioning

confidence: 99%

Characterisation of a blowfly male-specific neuron using behaviourally generated visual stimuli

2007

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The pursuit system controlling chasing behaviour in male blowXies has to cope with extremely fast and dynamically changing visual input. An identiWed male-speciWc visual neuron called Male Lobula Giant 1 (MLG1) is presumably one major element of this pursuit system. Previous behavioural and modelling analyses have indicated that angular target size, retinal target position and target velocity are relevant input variables of the pursuit system. To investigate whether MLG1 speciWcally represents any of these visual parameters we obtained in vivo intracellular recordings while replaying optical stimuli that simulate the visual signals received by a male Xy during chasing manoeuvres. On the basis of these naturalistic stimuli we Wnd that MLG1 shows distinct direction sensitivity and is depolarised if the target motion contains an upward component. The responses of MLG1 are jointly determined by the retinal position, the speed and direction, and the duration of target motimotion. Coherence analysis reveals that although retinal target size and position are in some way inherent in the responses of MLG1, we Wnd no conWrmation of the hypothesis that MLG1 encodes any of these parameters exclusively.

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Information theoretical evaluation of parametric models of gain control in blowfly photoreceptor cells

Cited by 94 publications

References 21 publications

Velocity constancy and models for wide-field visual motion detection in insects

Velocity constancy and models for wide-field visual motion detection in insects

Data Modelling for Analysis of Adaptive Changes in Fly Photoreceptors

Characterisation of a blowfly male-specific neuron using behaviourally generated visual stimuli

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