Neuronal Encoding of Visual Motion in Real-Time

Warzecha, Anne-Kathrin; Egelhaaf, Martin

doi:10.1007/978-3-642-56550-2_14

Cited by 19 publications

(20 citation statements)

References 99 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore all six cardinal axes of self-motion can be read out in a relatively simple way from the population response of VS and HS neurons. Furthermore, combining responses of different neurons may reduce ambiguities arising from the neuronal variability in the responses of VS and HS neurons (e.g., Haag and Borst 2004;Warzecha and Egelhaaf 2001;Warzecha et al 2003;Zohary et al 1994).…”

Section: Discussionmentioning

confidence: 99%

Encoding of Naturalistic Optic Flow by a Population of Blowfly Motion-Sensitive Neurons

Karmeier

Hateren²,

Kern³

et al. 2006

Journal of Neurophysiology

View full text Add to dashboard Cite

To analyze the coding properties of neuronal populations sensory stimuli have usually been used that were much simpler than those encountered in real life. It has been possible only recently to stimulate visual interneurons of the blowfly with naturalistic visual stimuli reconstructed from eye movements measured during free flight. Therefore we now investigate with naturalistic optic flow the coding properties of a small neuronal population of identified visual interneurons in the blowfly, the so-called VS and HS neurons. These neurons are motion sensitive and directionally selective and are assumed to extract information about the animal's self-motion from optic flow. We could show that neuronal responses of VS and HS neurons are mainly shaped by the characteristic dynamical properties of the fly's saccadic flight and gaze strategy. Individual neurons encode information about both the rotational and the translational components of the animal's self-motion. Thus the information carried by individual neurons is ambiguous. The ambiguities can be reduced by considering neuronal population activity. The joint responses of different subpopulations of VS and HS neurons can provide unambiguous information about the three rotational and the three translational components of the animal's self-motion and also, indirectly, about the three-dimensional layout of the environment. I N T R O D U C T I O NEven single aspects of the world, such as the orientation of contours or the frequency of a tone, induce an activity pattern spread over multiple neurons. A given environmental situation, such as the movements of an animal in its environment, is reflected in this neuronal population activity rather than in the responses of single neurons. Population coding of sensory information has been analyzed in many studies (e.g., Averbeck and Lee 2004;Deadwyler and Hampson 1997;Nirenberg and Latham 1998;Pouget et al. 2000). The sensory input an animal encounters in real life, however, may have much more complex properties than the experimenter-defined stimuli usually used in these studies (for review see Reinagel 2001).We analyze the coding properties of a population of motionsensitive visual interneurons in the blowfly with naturalistic stimuli generated actively by the animal during nearly unrestrained behavior. This neuronal population consists of two classes of neurons, the 10 VS (vertical system) neurons (Hengstenberg 1982;Hengstenberg et al. 1982;Krapp et al. 1998) and the three HS (horizontal system) neurons (Hausen 1982a,b) whose response properties and function in visually guided behavior have been characterized in great detail (for reviews see Borst and Haag 2002;Egelhaaf et al. 2002Egelhaaf et al. , 2004. HS neurons are excited primarily by front-to-back motion and their receptive fields jointly cover one visual hemisphere. The latter is also true for VS neurons, which are most sensitive to downward motion within a vertical stripe of the visual field (Fig. 1A). Based on their receptive field properties (Krapp et al. 1998(Krap...

show abstract

Section: Discussionmentioning

confidence: 99%

Encoding of Naturalistic Optic Flow by a Population of Blowfly Motion-Sensitive Neurons

Karmeier

Hateren²,

Kern³

et al. 2006

Journal of Neurophysiology

View full text Add to dashboard Cite

show abstract

“…Because during saccades the motion vision system operates beyond its linear range, it can resolve the much smaller translational optic flow component between saccades and thus provide information about the spatial layout of the environment. If the motion vision system would encode the entire angular velocity range in a linear way, the translational responses would be negligible and could hardly be resolved given the limited operating range of neurons and the noisiness of neuronal signals (for review, see Warzecha and Egelhaaf, 2001). Surprisingly, the performance of the model is much less sensitive to parameter changes when confronted with complex behaviorally generated optic flow than when much simpler experimenter-designed stimuli are used.…”

Section: Discussionmentioning

confidence: 99%

On the Computations Analyzing Natural Optic Flow: Quantitative Model Analysis of the Blowfly Motion Vision Pathway

Lindemann¹,

Kern²,

Hateren³

et al. 2005

J. Neurosci.

View full text Add to dashboard Cite

For many animals, including humans, the optic flow generated on the eyes during locomotion is an important source of information about self-motion and the structure of the environment. The blowfly has been used frequently as a model system for experimental analysis of optic flow processing at the microcircuit level. Here, we describe a model of the computational mechanisms implemented by these circuits in the blowfly motion vision pathway. Although this model was originally proposed based on simple experimenter-designed stimuli, we show that it is also capable to quantitatively predict the responses to the complex dynamic stimuli a blowfly encounters in free flight. In particular, the model visual system exploits the active saccadic gaze and flight strategy of blowflies in a similar way, as does its neuronal counterpart. The model circuit extracts information about translation velocity in the intersaccadic intervals and thus, indirectly, about the three-dimensional layout of the environment. By stepwise dissection of the model circuit, we determine which of its components are essential for these remarkable features. When accounting for the responses to complex natural stimuli, the model is much more robust against parameter changes than when explaining the neuronal responses to simple experimenter-defined stimuli. In contrast to conclusions drawn from experiments with simple stimuli, optimization of the parameter set for different segments of natural optic flow stimuli do not indicate pronounced adaptational changes of these parameters during long-lasting stimulation.

show abstract

“…4A, B; see also Warzecha et al, 1998). Precise time locking of neuronal signals to motion stimuli occurs in fly TCs only after very rapid velocity changes (de Ruyter van Steveninck et al, 2001;Bialek, 1988, 1995;Warzecha and Egelhaaf, 2001). This To account for the rectification nonlinearity due to spike generation and the low spontaneous activity of V1, the presynaptic membrane potential traces and the velocity traces were rectified.…”

Section: Discussionmentioning

confidence: 99%

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

2003

View full text Add to dashboard Cite

Abstract-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 motionsensitive 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.

show abstract

Neuronal Encoding of Visual Motion in Real-Time

Cited by 19 publications

References 99 publications

Encoding of Naturalistic Optic Flow by a Population of Blowfly Motion-Sensitive Neurons

Encoding of Naturalistic Optic Flow by a Population of Blowfly Motion-Sensitive Neurons

On the Computations Analyzing Natural Optic Flow: Quantitative Model Analysis of the Blowfly Motion Vision Pathway

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

Contact Info

Product

Resources

About