Functional Specialization of Parallel Motion Detection Circuits in the Fly

Joesch, Maximilian; Weber, Franz; Eichner, Hubert; Borst, Alexander

doi:10.1523/jneurosci.3374-12.2013

Cited by 66 publications

(60 citation statements)

References 20 publications

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“…Intriguingly, when blocking either pathway, the SMPs are curtailed to the half-level: sieving ON pathway abolishes response elicited by ON cells leaving that of OFF cells unchanged; otherwise sieving OFF pathway gives rise to only onset response. The results adequately reconcile with related biological research [17].…”

Section: B Challenged Against Synthetic Stimulisupporting

confidence: 81%

“…In this study, an architecture of combining six-quadrant detectors demonstrates ON/OFF cells preferentially process the motion of light/dark edges respectively, which also elicited the importance of edge selectivity in motion detection. To decide between these alternatives, a case study via genetically blocking either ON/OFF pathway gave strong evidence to the functional specialized two versus six quadrants signal flows [17]. In this work, we represented the interactions of same polarity signals via the putative two-quadrant Reichardt detectors.…”

Section: Related Workmentioning

confidence: 99%

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Modeling direction selective visual neural network with ON and OFF pathways for extracting motion cues from cluttered background

Yue

2017

2017 International Joint Conference on Neural Networks (IJCNN)

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Abstract-The nature endows animals robust vision systems for extracting and recognizing different motion cues, detecting predators, chasing preys/mates in dynamic and cluttered environments. Direction selective neurons (DSNs), with preference to certain orientation visual stimulus, have been found in both vertebrates and invertebrates for decades. In this paper, with respect to recent biological research progress in motion-detecting circuitry, we propose a novel way to model DSNs for recognizing movements on four cardinal directions. It is based on an architecture of ON and OFF visual pathways underlies a theory of splitting motion signals into parallel channels, encoding brightness increments and decrements separately. To enhance the edge selectivity and speed response to moving objects, we put forth a bio-plausible spatial-temporal network structure with multiple connections of same polarity ON/OFF cells. Each pair-wised combination is filtered with dynamic delay depending on sampling distance. The proposed vision system was challenged against image streams from both synthetic and cluttered real physical scenarios. The results demonstrated three major contributions: first, the neural network fulfilled the characteristics of a postulated physiological map of conveying visual information through different neuropile layers; second, the DSNs model can extract useful directional motion cues from cluttered background robustly and timely, which hits at potential of quick implementation in visionbased micro mobile robots; moreover, it also represents better speed response compared to a state-of-the-art elementary motion detector.

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Section: B Challenged Against Synthetic Stimulisupporting

confidence: 81%

Section: Related Workmentioning

confidence: 99%

Modeling direction selective visual neural network with ON and OFF pathways for extracting motion cues from cluttered background

Yue

2017

2017 International Joint Conference on Neural Networks (IJCNN)

View full text Add to dashboard Cite

show abstract

“…More precisely, combined apparent motion and genetic silencing experiments showed that the L1 channel exclusively deals with ON--ON signals, and the L2 channel exclusively processes OFF--OFF signals [40].…”

Section: Neuronal Implementationmentioning

confidence: 99%

Subcellular mapping of dendritic activity in optic flow processing neurons

2014

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i AbstractDendritic integration is a fundamental element of neuronal information processing.So far, few studies have provided a detailed picture of this process, describing the properties of local dendritic activity and its subcellular organization.Here, I used 2--photon calcium imaging in optic flow processing neurons of the blowfly Calliphora vicina to determine the preferred location and direction of local motion cues for small branchlets throughout the entire dendrite. I found a pronounced retinotopic mapping on both the subcellular and the cell population level. In addition, dendritic branchlets residing in different layers of the neuropil were tuned to distinct directions of motion. Within one layer, local preferred directions varied according to the deflections of the ommatidial lattice. Summing the local receptive fields of all dendritic branchlets reproduced the characteristic properties of these neurons' axonal output receptive fields.These results corroborate the notion that the dendritic morphology of vertical system cells allows them to selectively collect local motion inputs with particular directional preferences from a spatially organized input repertoire, thus forming filters that match global patterns of optic flow. These data illustrate a highly structured circuit organization as an efficient way to hard--wire a complex sensory task.

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“…A number of studies found that, on the input side of the motion vision circuit, lamina monopolar cell L1 feeds into a pathway for the detection of moving light edges (ON), while L2 detects moving dark edges (OFF) (Rister et al 2007;Reiff et al 2010;Joesch et al 2010Joesch et al , 2013Clark et al 2011;Eichner et al 2011). On the output side of the circuit, electrophysiological and anatomical data point toward lobula plate neurons T4 and T5 as being the outputs that feed onto the first cell type to be truly direction-selective, the so-called lobula plate tangential cells (LPTCs) Strausfeld 2000, 2003).…”

Section: Genetic Dissection Of the Behavioral Contributions By Cell Tmentioning

confidence: 99%

So many pieces, one puzzle: cell type specification and visual circuitry in flies and mice

2014

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The visual system is a powerful model for probing the development, connectivity, and function of neural circuits. Two genetically tractable species, mice and flies, are together providing a great deal of understanding of these processes. Current efforts focus on integrating knowledge gained from three cross-fostering fields of research: (1) understanding how the fates of different cell types are specified during development, (2) revealing the synaptic connections between identified cell types (''connectomics'') by high-resolution three-dimensional circuit anatomy, and (3) causal testing of how identified circuit elements contribute to visual perception and behavior. Here we discuss representative examples from fly and mouse models to illustrate the ongoing success of this tripartite strategy, focusing on the ways it is enhancing our understanding of visual processing and other sensory systems.For many decades, the visual systems of both vertebrates and invertebrates have been a favorite arena for understanding how neural circuits are built and function. A considerable body of work has focused on the specification of cell types of the retina; for instance, the designation of different classes of photoreceptors with distinct spectral sensitivities in the Drosophila retina (Rister and Desplan 2011) and the establishment of the various cell types that comprise the vertebrate retina: photoreceptors, Muller glia, interneurons (horizontal, amacrine, and bipolar cells), and retinal ganglion cells (RGCs) (Livesey and Cepko 2001;Mu et al. 2004;Poch e and Reese 2006). With that knowledge in hand, focus in recent years has expanded to understanding how the circuits formed by these retinal cells are linked to the staggering number of diverse visual neurons in the brain, which in turn enables sophisticated and diverse computational tasks. The ultimate goal is to understand how cellular identity, function, and connectivity relate to visually guided behaviors. (Fig. 1A).

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Functional Specialization of Parallel Motion Detection Circuits in the Fly

Cited by 66 publications

References 20 publications

Modeling direction selective visual neural network with ON and OFF pathways for extracting motion cues from cluttered background

Modeling direction selective visual neural network with ON and OFF pathways for extracting motion cues from cluttered background

Subcellular mapping of dendritic activity in optic flow processing neurons

So many pieces, one puzzle: cell type specification and visual circuitry in flies and mice

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