Encoding of motion in real time by the fly visual system

Egelhaaf, Martin; Warzechat, Anne-Kathrin

doi:10.1016/s0959-4388(99)80068-3

Cited by 38 publications

(35 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is suggested by the different specificity of the HSE cell for the rotational flow component as found in responses to optic flow generated on simple artificial walking tracks, on the one hand, and to optic flow that was generated by the animal itself, on the other hand . The nonlinearities inherent in the mechanisms underlying the computation of visual motion information (for reviews see Egelhaaf and Borst 1993b, Borst et al 1995, Egelhaaf and Warzecha 1999) might be another reason why the responses of both the HSE cell and of the model cell are almost invariant with respect to the layout of the environment. This invariance is only observed if the retinal images are characterized by a broad spatial frequency spectrum rather than by only one frequency component (Kern, unpublished experimental results;see also Dror et al 2001).…”

Section: Specificity Of Neuronal Responses Under Naturalistic and Simmentioning

confidence: 99%

Neuronal processing of behaviourally generated optic flow: experiments and model simulations

Kern¹,

Lutterklas²,

Petereit³

et al. 2001

Network: Computation in Neural Systems

View full text Add to dashboard Cite

The stimuli traditionally used for analysing visual information processing are much simpler than what an animal sees when moving in its natural environment. Therefore, we analysed in a previous study the performance of an identified neuron in the optomotor system of the fly by using as visual stimuli image sequences that were experienced by the animal while walking in a structured environment. These electrophysiological experiments revealed that the fly visual system computes from behaviourally generated optic flow a rather unambiguous representation of the animal's self-motion. In contrast to conclusions based on simple stimuli, the directions of turns are represented by an interneuron, the HSE cell, quite independent of the spatial layout of the environment and its textural properties when the cell is stimulated with behaviourally generated optic flow. This conclusion is substantiated here by further experimental evidence. Moreover, it is shown that the largely unambiguous responses of the HSE cell to behaviourally generated optic flow can be replicated to a large extent by a network model of the fly's visual motion pathway. These results stress the significance of naturalistic stimuli for analysing what is encoded by neuronal circuits under natural operating conditions.

show abstract

Section: Specificity Of Neuronal Responses Under Naturalistic and Simmentioning

confidence: 99%

Neuronal processing of behaviourally generated optic flow: experiments and model simulations

Kern¹,

Lutterklas²,

Petereit³

et al. 2001

Network: Computation in Neural Systems

View full text Add to dashboard Cite

show abstract

“…Tanaka & Saito, 1989) and birds (e.g. Wylie et al, 1998), to behavioral as well as electrophysiological investigations in insects (reviews: Hausen & Egelhaaf, 1989;Egelhaaf & Warzecha, 1999;Krapp, 2000;Srinivasan & Zhang, 2000). Most electrophysiological studies have been aimed at identifying the neuronal substrate and the basic processing principles of visual self-motion estimation.…”

Section: Introductionmentioning

confidence: 99%

Early visual experience and the receptive-field organization of optic flow processing interneurons in the fly motion pathway

et al. 2001

Self Cite

View full text Add to dashboard Cite

The distribution of local preferred directions and motion sensitivities within the receptive fields of so-called tangential neurons in the fly visual system was previously found to match optic flow fields as induced by certain self-motions. The complex receptive-field organization of the tangential neurons and the recent evidence showing that the orderly development of the fly's peripheral visual system depends on visual experience led us to investigate whether or not early visual input is required to establish the functional receptive-field properties of such tangential neurons. In electrophysiological investigations of two identified tangential neurons, it turned out that dark-hatched flies which were kept in complete darkness for 2 days develop basically the same receptive-field organization as flies which were raised under seasonal light0dark conditions and were free to move in their cages. We did not find any evidence that the development of the sophisticated receptive-field organization of tangential neurons depends on sensory experience. Instead, the input to the tangential neurons seems to be "hardwired" and the specificity of these cells to optic flow induced during self-motions of the animal may have evolved on a phylogenetical time scale.

show abstract

“…In systems such as the retina of the horseshoe crab [5,6], it is now feasible to analyse the neuronal representation of visual input as it is experienced during behaviour (reviewed in Refs [7,8]). Until now, however, in most systems the underlying neuronal mechanisms have been difficult to unravel.In the fly it is possible to employ both quantitative behavioural approaches as well as in vivo electrophysiological and imaging methods to analyse how behaviourally relevant visual input is processed [9][10][11][12][13][14][15][16][17][18][19][20]. Although the latter techniques are mainly employed in the blowfly, which is relatively big, they are complemented by studies of the smaller fruitfly, Drosophila, where a broad range of genetic approaches can be applied to dissect the visual system in an increasingly specific way [21,22].…”

mentioning

confidence: 99%

Neural encoding of behaviourally relevant visual-motion information in the fly

Egelhaaf

Kern

Krapp

et al. 2002

Trends in Neurosciences

150

109

View full text Add to dashboard Cite

The goal of neuroethology is to explain behaviour in terms of the activity of nerve cells and their interactions. This can only be achieved if the experimental animal can be analysed at different levels ranging from behaviour to individual neurons. Cellular mechanisms underlying processing of neuronal information are frequently analysed using in vitro preparations where artificial stimulation replaces the natural sensory input. Although such studies provide fascinating insights into the complex computational abilities of neurons [1], the results may not be extrapolated easily to in vivo conditions, where the range of response amplitudes of neurons and their temporal activity patterns may differ considerably from artificially induced activity. In systems such as the retina of the horseshoe crab [5,6], it is now feasible to analyse the neuronal representation of visual input as it is experienced during behaviour (reviewed in Refs [7,8]). Until now, however, in most systems the underlying neuronal mechanisms have been difficult to unravel.In the fly it is possible to employ both quantitative behavioural approaches as well as in vivo electrophysiological and imaging methods to analyse how behaviourally relevant visual input is processed [9][10][11][12][13][14][15][16][17][18][19][20]. Although the latter techniques are mainly employed in the blowfly, which is relatively big, they are complemented by studies of the smaller fruitfly, Drosophila, where a broad range of genetic approaches can be applied to dissect the visual system in an increasingly specific way [21,22].We review recent progress on the encoding of optic-flow information in the blowfly. Optic flow is an important source of information about self-motion and the three-dimensional layout of the environment, not only for flies but for most moving animals including humans (Box 1, [4,[23][24][25]). Flies exploit optic flow to guide their locomotion [13] and to control compensatory head movements [26], and understanding the computational principles underlying optic-flow processing in flies could provide insights into visual-motion analysis in general.Information processing in visual systems is constrained by the spatial and temporal characteristics of the sensory input and by the biophysical properties of the neuronal circuits. Hence, to understand how visual systems encode behaviourally relevant information, we need to know about both the computational capabilities of the nervous system and the natural conditions under which animals normally operate. By combining behavioural, neurophysiological and computational approaches, it is now possible in the fly to assess adaptations that process visual-motion information under the constraints of its natural input. It is concluded that neuronal operating ranges and coding strategies appear to be closely matched to the inputs the animal encounters under behaviourally relevant conditions.

show abstract

Encoding of motion in real time by the fly visual system

Cited by 38 publications

References 39 publications

Neuronal processing of behaviourally generated optic flow: experiments and model simulations

Neuronal processing of behaviourally generated optic flow: experiments and model simulations

Early visual experience and the receptive-field organization of optic flow processing interneurons in the fly motion pathway

Neural encoding of behaviourally relevant visual-motion information in the fly

Contact Info

Product

Resources

About