1
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Carrier Y, Rio LQ, Formicola N, de Sousa-Xavier V, Tabet M, Chen YCD, Wislez M, Orts L, Pinto-Teixeira F. Biased cell adhesion organizes a circuit for visual motion integration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.11.571076. [PMID: 38168373 PMCID: PMC10760042 DOI: 10.1101/2023.12.11.571076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Layer specific computations in the brain rely on neuronal processes establishing synaptic connections with specific partners in distinct laminae. In the Drosophila lobula plate neuropile, the axons of the four subtypes of T4 and T5 visual motion direction-selective neurons segregate into four layers, based on their directional preference, and form synapses with distinct subsets of postsynaptic neurons. Four bi-stratified inhibitory lobula plate intrinsic cells exhibit a consistent synaptic pattern, receiving excitatory T4/T5 inputs in one layer, and conveying inhibitory signals to an adjacent layer. This layered arrangement establishes motion opponency. Here, we identify layer-specific expression of different receptor-ligand pairs belonging to the Beat and Side families of Cell Adhesion Molecules (CAMs) between T4/T5 neurons and their postsynaptic partners. Genetic analysis reveals that Beat/Side mediated interactions are required to restrict T4/T5 axonal innervation to a single layer. We propose that Beat/Side contribute to synaptic specificity by biasing adhesion between synaptic partners before synaptogenesis.
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Affiliation(s)
- Yannick Carrier
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Laura Quintana Rio
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Nadia Formicola
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Vicente de Sousa-Xavier
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Maha Tabet
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | | | - Maëva Wislez
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Lisa Orts
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
| | - Filipe Pinto-Teixeira
- MCD, Centre de Biologie Intégrative (CBI), CNRS, Université de Toulouse, UT3, Toulouse, France
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2
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Ammer G, Serbe-Kamp E, Mauss AS, Richter FG, Fendl S, Borst A. Multilevel visual motion opponency in Drosophila. Nat Neurosci 2023; 26:1894-1905. [PMID: 37783895 PMCID: PMC10620086 DOI: 10.1038/s41593-023-01443-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 08/30/2023] [Indexed: 10/04/2023]
Abstract
Inhibitory interactions between opponent neuronal pathways constitute a common circuit motif across brain areas and species. However, in most cases, synaptic wiring and biophysical, cellular and network mechanisms generating opponency are unknown. Here, we combine optogenetics, voltage and calcium imaging, connectomics, electrophysiology and modeling to reveal multilevel opponent inhibition in the fly visual system. We uncover a circuit architecture in which a single cell type implements direction-selective, motion-opponent inhibition at all three network levels. This inhibition, mediated by GluClα receptors, is balanced with excitation in strength, despite tenfold fewer synapses. The different opponent network levels constitute a nested, hierarchical structure operating at increasing spatiotemporal scales. Electrophysiology and modeling suggest that distributing this computation over consecutive network levels counteracts a reduction in gain, which would result from integrating large opposing conductances at a single instance. We propose that this neural architecture provides resilience to noise while enabling high selectivity for relevant sensory information.
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Affiliation(s)
- Georg Ammer
- Max Planck Institute for Biological Intelligence, Martinsried, Germany.
| | - Etienne Serbe-Kamp
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
- Ludwig Maximilian University of Munich, Munich, Germany
| | - Alex S Mauss
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Florian G Richter
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Sandra Fendl
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Alexander Borst
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
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3
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Abstract
How neurons detect the direction of motion is a prime example of neural computation: Motion vision is found in the visual systems of virtually all sighted animals, it is important for survival, and it requires interesting computations with well-defined linear and nonlinear processing steps-yet the whole process is of moderate complexity. The genetic methods available in the fruit fly Drosophila and the charting of a connectome of its visual system have led to rapid progress and unprecedented detail in our understanding of how neurons compute the direction of motion in this organism. The picture that emerged incorporates not only the identity, morphology, and synaptic connectivity of each neuron involved but also its neurotransmitters, its receptors, and their subcellular localization. Together with the neurons' membrane potential responses to visual stimulation, this information provides the basis for a biophysically realistic model of the circuit that computes the direction of visual motion.
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Affiliation(s)
- Alexander Borst
- Max Planck Institute for Biological Intelligence, Martinsried, Germany; ,
| | - Lukas N Groschner
- Max Planck Institute for Biological Intelligence, Martinsried, Germany; ,
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4
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Zhao Y, Ke S, Cheng G, Lv X, Chang J, Zhou W. Direction Selectivity of TmY Neurites in Drosophila. Neurosci Bull 2023; 39:759-773. [PMID: 36399278 PMCID: PMC10169962 DOI: 10.1007/s12264-022-00966-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/29/2022] [Indexed: 11/19/2022] Open
Abstract
The perception of motion is an important function of vision. Neural wiring diagrams for extracting directional information have been obtained by connectome reconstruction. Direction selectivity in Drosophila is thought to originate in T4/T5 neurons through integrating inputs with different temporal filtering properties. Through genetic screening based on synaptic distribution, we isolated a new type of TmY neuron, termed TmY-ds, that form reciprocal synaptic connections with T4/T5 neurons. Its neurites responded to grating motion along the four cardinal directions and showed a variety of direction selectivity. Intriguingly, its direction selectivity originated from temporal filtering neurons rather than T4/T5. Genetic silencing and activation experiments showed that TmY-ds neurons are functionally upstream of T4/T5. Our results suggest that direction selectivity is generated in a tripartite circuit formed among these three neurons-temporal filtering, TmY-ds, and T4/T5 neurons, in which TmY-ds plays a role in the enhancement of direction selectivity in T4/T5 neurons.
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Affiliation(s)
- Yinyin Zhao
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Shanshan Ke
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Guo Cheng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Xiaohua Lv
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Jin Chang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
| | - Wei Zhou
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
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5
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Hafez OA, Escribano B, Ziegler RL, Hirtz JJ, Niebur E, Pielage J. The cellular architecture of memory modules in Drosophila supports stochastic input integration. eLife 2023; 12:e77578. [PMID: 36916672 PMCID: PMC10069864 DOI: 10.7554/elife.77578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 03/09/2023] [Indexed: 03/16/2023] Open
Abstract
The ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within the Drosophila mushroom body (MB), the fly's center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-α3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit.
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Affiliation(s)
- Omar A Hafez
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
| | - Benjamin Escribano
- Division of Neurobiology and Zoology, Department of Biology, University of KaiserslauternKaiserslauternGermany
| | - Rouven L Ziegler
- Division of Neurobiology and Zoology, Department of Biology, University of KaiserslauternKaiserslauternGermany
| | - Jan J Hirtz
- Physiology of Neuronal Networks Group, Department of Biology, University of KaiserslauternKaiserslauternGermany
| | - Ernst Niebur
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
- Solomon Snyder Department of Neuroscience, Johns Hopkins UniversityBaltimoreUnited States
| | - Jan Pielage
- Division of Neurobiology and Zoology, Department of Biology, University of KaiserslauternKaiserslauternGermany
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6
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Liessem S, Held M, Bisen RS, Haberkern H, Lacin H, Bockemühl T, Ache JM. Behavioral state-dependent modulation of insulin-producing cells in Drosophila. Curr Biol 2023; 33:449-463.e5. [PMID: 36580915 DOI: 10.1016/j.cub.2022.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 11/01/2022] [Accepted: 12/02/2022] [Indexed: 12/29/2022]
Abstract
Insulin signaling plays a pivotal role in metabolic control and aging, and insulin accordingly is a key factor in several human diseases. Despite this importance, the in vivo activity dynamics of insulin-producing cells (IPCs) are poorly understood. Here, we characterized the effects of locomotion on the activity of IPCs in Drosophila. Using in vivo electrophysiology and calcium imaging, we found that IPCs were strongly inhibited during walking and flight and that their activity rebounded and overshot after cessation of locomotion. Moreover, IPC activity changed rapidly during behavioral transitions, revealing that IPCs are modulated on fast timescales in behaving animals. Optogenetic activation of locomotor networks ex vivo, in the absence of actual locomotion or changes in hemolymph sugar levels, was sufficient to inhibit IPCs. This demonstrates that the behavioral state-dependent inhibition of IPCs is actively controlled by neuronal pathways and is independent of changes in glucose concentration. By contrast, the overshoot in IPC activity after locomotion was absent ex vivo and after starvation, indicating that it was not purely driven by feedforward signals but additionally required feedback derived from changes in hemolymph sugar concentration. We hypothesize that IPC inhibition during locomotion supports mobilization of fuel stores during metabolically demanding behaviors, while the rebound in IPC activity after locomotion contributes to replenishing muscle glycogen stores. In addition, the rapid dynamics of IPC modulation support a potential role of insulin in the state-dependent modulation of sensorimotor processing.
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Affiliation(s)
- Sander Liessem
- Neurobiology and Genetics, Theodor-Boveri-Institute, Biocenter, Julius-Maximilians-University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Martina Held
- Neurobiology and Genetics, Theodor-Boveri-Institute, Biocenter, Julius-Maximilians-University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Rituja S Bisen
- Neurobiology and Genetics, Theodor-Boveri-Institute, Biocenter, Julius-Maximilians-University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Hannah Haberkern
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Haluk Lacin
- Department of Genetics, Washington University School of Medicine, 4523 Clayton Avenue, St Louis, MO 63110, USA
| | - Till Bockemühl
- Department of Biology, Institute of Zoology, University of Cologne, Zülpicher Str. 47b, 50674 Cologne, Germany
| | - Jan M Ache
- Neurobiology and Genetics, Theodor-Boveri-Institute, Biocenter, Julius-Maximilians-University of Würzburg, Am Hubland, 97074 Würzburg, Germany.
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7
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Kim H, Park H, Lee J, Kim AJ. A visuomotor circuit for evasive flight turns in Drosophila. Curr Biol 2023; 33:321-335.e6. [PMID: 36603587 DOI: 10.1016/j.cub.2022.12.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 11/14/2022] [Accepted: 12/07/2022] [Indexed: 01/06/2023]
Abstract
Visual systems extract multiple features from a scene using parallel neural circuits. Ultimately, the separate neural signals must come together to coherently influence action. Here, we characterize a circuit in Drosophila that integrates multiple visual features related to imminent threats to drive evasive locomotor turns. We identified, using genetic perturbation methods, a pair of visual projection neurons (LPLC2) and descending neurons (DNp06) that underlie evasive flight turns in response to laterally moving or approaching visual objects. Using two-photon calcium imaging or whole-cell patch clamping, we show that these cells indeed respond to both translating and approaching visual patterns. Furthermore, by measuring visual responses of LPLC2 neurons after genetically silencing presynaptic motion-sensing neurons, we show that their visual properties emerge by integrating multiple visual features across two early visual structures: the lobula and the lobula plate. This study highlights a clear example of how distinct visual signals converge on a single class of visual neurons and then activate premotor neurons to drive action, revealing a concise visuomotor pathway for evasive flight maneuvers in Drosophila.
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Affiliation(s)
- Hyosun Kim
- Department of Artificial Intelligence, Hanyang University, Seoul 04763, South Korea
| | - Hayun Park
- Department of Electronic Engineering, Hanyang University, Seoul 04763, South Korea
| | - Joowon Lee
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, South Korea
| | - Anmo J Kim
- Department of Artificial Intelligence, Hanyang University, Seoul 04763, South Korea; Department of Electronic Engineering, Hanyang University, Seoul 04763, South Korea; Department of Biomedical Engineering, Hanyang University, Seoul 04763, South Korea.
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8
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Damulewicz M, Tyszka A, Pyza E. Light exposure during development affects physiology of adults in Drosophila melanogaster. Front Physiol 2022; 13:1008154. [PMID: 36505068 PMCID: PMC9732085 DOI: 10.3389/fphys.2022.1008154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 11/14/2022] [Indexed: 11/27/2022] Open
Abstract
Light is one of most important factors synchronizing organisms to day/night cycles in the environment. In Drosophila it is received through compound eyes, Hofbauer-Buchner eyelet, ocelli, using phospholipase C-dependent phototransduction and by deep brain photoreceptors, like Cryptochrome. Even a single light pulse during early life induces larval-time memory, which synchronizes the circadian clock and maintains daily rhythms in adult flies. In this study we investigated several processes in adult flies after maintaining their embryos, larvae and pupae in constant darkness (DD) until eclosion. We found that the lack of external light during development affects sleep time, by reduction of night sleep, and in effect shift to the daytime. However, disruption of internal CRY- dependent photoreception annuls this effect. We also observed changes in the expression of genes encoding neurotransmitters and their receptors between flies kept in different light regime. In addition, the lack of light during development results in decreasing size of mushroom bodies, involved in sleep regulation. Taking together, our results show that presence of light during early life plays a key role in brain development and affects adult behavior.
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9
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Shinomiya K, Nern A, Meinertzhagen IA, Plaza SM, Reiser MB. Neuronal circuits integrating visual motion information in Drosophila melanogaster. Curr Biol 2022; 32:3529-3544.e2. [PMID: 35839763 DOI: 10.1016/j.cub.2022.06.061] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/17/2022] [Accepted: 06/20/2022] [Indexed: 11/25/2022]
Abstract
The detection of visual motion enables sophisticated animal navigation, and studies on flies have provided profound insights into the cellular and circuit bases of this neural computation. The fly's directionally selective T4 and T5 neurons encode ON and OFF motion, respectively. Their axons terminate in one of the four retinotopic layers in the lobula plate, where each layer encodes one of the four directions of motion. Although the input circuitry of the directionally selective neurons has been studied in detail, the synaptic connectivity of circuits integrating T4/T5 motion signals is largely unknown. Here, we report a 3D electron microscopy reconstruction, wherein we comprehensively identified T4/T5's synaptic partners in the lobula plate, revealing a diverse set of new cell types and attributing new connectivity patterns to the known cell types. Our reconstruction explains how the ON- and OFF-motion pathways converge. T4 and T5 cells that project to the same layer connect to common synaptic partners and comprise a core motif together with bilayer interneurons, detailing the circuit basis for computing motion opponency. We discovered pathways that likely encode new directions of motion by integrating vertical and horizontal motion signals from upstream T4/T5 neurons. Finally, we identify substantial projections into the lobula, extending the known motion pathways and suggesting that directionally selective signals shape feature detection there. The circuits we describe enrich the anatomical basis for experimental and computations analyses of motion vision and bring us closer to understanding complete sensory-motor pathways.
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Affiliation(s)
- Kazunori Shinomiya
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Ian A Meinertzhagen
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Department of Psychology and Neuroscience, Dalhousie University, 1355 Oxford Street, Halifax, NS B3H 4R2, Canada
| | - Stephen M Plaza
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Michael B Reiser
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
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10
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Ryu L, Kim SY, Kim AJ. From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila. Front Neurosci 2022; 16:883640. [PMID: 35600623 PMCID: PMC9115102 DOI: 10.3389/fnins.2022.883640] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 03/28/2022] [Indexed: 11/17/2022] Open
Abstract
Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.
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Affiliation(s)
- Leesun Ryu
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Sung Yong Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Anmo J. Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
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11
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Ammer G, Vieira RM, Fendl S, Borst A. Anatomical distribution and functional roles of electrical synapses in Drosophila. Curr Biol 2022; 32:2022-2036.e4. [DOI: 10.1016/j.cub.2022.03.040] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 02/16/2022] [Accepted: 03/14/2022] [Indexed: 10/18/2022]
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12
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Henning M, Ramos-Traslosheros G, Gür B, Silies M. Populations of local direction-selective cells encode global motion patterns generated by self-motion. SCIENCE ADVANCES 2022; 8:eabi7112. [PMID: 35044821 PMCID: PMC8769539 DOI: 10.1126/sciadv.abi7112] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Self-motion generates visual patterns on the eye that are important for navigation. These optic flow patterns are encoded by the population of local direction–selective cells in the mouse retina, whereas in flies, local direction–selective T4/T5 cells are thought to be uniformly tuned. How complex global motion patterns can be computed downstream is unclear. We show that the population of T4/T5 cells in Drosophila encodes global motion patterns. Whereas the mouse retina encodes four types of optic flow, the fly visual system encodes six. This matches the larger number of degrees of freedom and the increased complexity of translational and rotational motion patterns during flight. The four uniformly tuned T4/T5 subtypes described previously represent a local subset of the population. Thus, a population code for global motion patterns appears to be a general coding principle of visual systems that matches local motion responses to modes of the animal’s movement.
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Affiliation(s)
- Miriam Henning
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University Mainz, Mainz 55128, Germany
- Göttingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences (GGNB) and International Max Planck Research School (IMPRS) for Neurosciences at the University of Göttingen, Göttingen 37077, Germany
| | - Giordano Ramos-Traslosheros
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University Mainz, Mainz 55128, Germany
- Göttingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences (GGNB) and International Max Planck Research School (IMPRS) for Neurosciences at the University of Göttingen, Göttingen 37077, Germany
| | - Burak Gür
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University Mainz, Mainz 55128, Germany
- Göttingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences (GGNB) and International Max Planck Research School (IMPRS) for Neurosciences at the University of Göttingen, Göttingen 37077, Germany
| | - Marion Silies
- Institute of Developmental Biology and Neurobiology, Johannes-Gutenberg University Mainz, Mainz 55128, Germany
- Corresponding author.
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13
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Leonte MB, Leonhardt A, Borst A, Mauss AS. Aerial course stabilization is impaired in motion-blind flies. J Exp Biol 2021; 224:271038. [PMID: 34297111 DOI: 10.1242/jeb.242219] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 06/22/2021] [Indexed: 01/12/2023]
Abstract
Visual motion detection is among the best understood neuronal computations. As extensively investigated in tethered flies, visual motion signals are assumed to be crucial to detect and counteract involuntary course deviations. During free flight, however, course changes are also signalled by other sensory systems. Therefore, it is as yet unclear to what extent motion vision contributes to course control. To address this question, we genetically rendered flies motion-blind by blocking their primary motion-sensitive neurons and quantified their free-flight performance. We found that such flies have difficulty maintaining a straight flight trajectory, much like unimpaired flies in the dark. By unilateral wing clipping, we generated an asymmetry in propulsive force and tested the ability of flies to compensate for this perturbation. While wild-type flies showed a remarkable level of compensation, motion-blind animals exhibited pronounced circling behaviour. Our results therefore directly confirm that motion vision is necessary to fly straight under realistic conditions.
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Affiliation(s)
- Maria-Bianca Leonte
- Circuits - Computation - Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Graduate School of Systemic Neurosciences, Ludwig Maximilians University, Großhadernerstr. 2, Planegg-Martinsried 82152, Germany
| | - Aljoscha Leonhardt
- Circuits - Computation - Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany
| | - Alexander Borst
- Circuits - Computation - Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany
| | - Alex S Mauss
- Circuits - Computation - Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany
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14
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Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers. PLoS Comput Biol 2021; 17:e1008965. [PMID: 34014926 PMCID: PMC8136689 DOI: 10.1371/journal.pcbi.1008965] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 04/13/2021] [Indexed: 11/20/2022] Open
Abstract
The visual system must make predictions to compensate for inherent delays in its processing. Yet little is known, mechanistically, about how prediction aids natural behaviors. Here, we show that despite a 20-30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly achieves maximally efficient prediction. This prediction enables the fly to fine-tune its complex, yet brief, evasive flight maneuvers according to its initial ego-rotation at the time of detection of the visual threat. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network has axonal gap junctions that are critical for optimal prediction. During evasive maneuvers, a VS subpopulation that directly innervates the neck motor center can convey predictive information about the fly’s future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior. Survival-critical behaviors shape neural circuits to translate sensory information into strikingly fast predictions, e.g. in escaping from a predator faster than the system’s processing delay. We show that the fly visual system implements fast and accurate prediction of its visual experience. This provides crucial information for directing fast evasive maneuvers that unfold over just 40ms. Our work shows how this fast prediction is implemented, mechanistically, and suggests the existence of a novel sensory-motor pathway from the fly visual system to a wing steering motor neuron. Echoing and amplifying previous work in the retina, our work hypothesizes that the efficient encoding of predictive information is a universal design principle supporting fast, natural behaviors.
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15
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Pagni M, Haikala V, Oberhauser V, Meyer PB, Reiff DF, Schnaitmann C. Interaction of “chromatic” and “achromatic” circuits in Drosophila color opponent processing. Curr Biol 2021; 31:1687-1698.e4. [DOI: 10.1016/j.cub.2021.01.105] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/22/2021] [Accepted: 01/28/2021] [Indexed: 02/07/2023]
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16
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Li L, Zhang Z, Lu J. Artificial fly visual joint perception neural network inspired by multiple-regional collision detection. Neural Netw 2020; 135:13-28. [PMID: 33338802 DOI: 10.1016/j.neunet.2020.11.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 11/12/2020] [Accepted: 11/30/2020] [Indexed: 10/22/2022]
Abstract
The biological visual system includes multiple types of motion sensitive neurons which preferentially respond to specific perceptual regions. However, it still keeps open how to borrow such neurons to construct bio-inspired computational models for multiple-regional collision detection. To fill this gap, this work proposes a visual joint perception neural network with two subnetworks - presynaptic and postsynaptic neural networks, inspired by the preferentialperception characteristics of three horizontal and vertical motion sensitive neurons. Related to the neural network and three hazard detection mechanisms, an artificial fly visual synthesized collision detection model for multiple-regional collision detection is originally developed to monitor possible danger occurrence in the case where one or more moving objects appear in the whole field of view. The experiments can clearly draw two conclusions: (i) the acquired neural network can effectively display the characteristics of visual movement, and (ii) the collision detection model, which outperforms the compared models, can effectively perform multiple-regional collision detection at a high success rate, and only takes about 0.24s to complete the process of collision detection for each virtual or actual image frame with resolution 110×60.
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Affiliation(s)
- Lun Li
- College of Big Data and Information Engineering, Guizhou University, Guizhou Provincial Characteristic Key Laboratory of System Optimization and Scientific Computing, Guiyang, Guizhou 550025, PR China
| | - Zhuhong Zhang
- College of Big Data and Information Engineering, Guizhou University, Guizhou Provincial Characteristic Key Laboratory of System Optimization and Scientific Computing, Guiyang, Guizhou 550025, PR China.
| | - Jiaxuan Lu
- College of Big Data and Information Engineering, Guizhou University, Guizhou Provincial Characteristic Key Laboratory of System Optimization and Scientific Computing, Guiyang, Guizhou 550025, PR China
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17
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Fendl S, Vieira RM, Borst A. Conditional protein tagging methods reveal highly specific subcellular distribution of ion channels in motion-sensing neurons. eLife 2020; 9:62953. [PMID: 33079061 PMCID: PMC7655108 DOI: 10.7554/elife.62953] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 10/14/2020] [Indexed: 11/25/2022] Open
Abstract
Neurotransmitter receptors and ion channels shape the biophysical properties of neurons, from the sign of the response mediated by neurotransmitter receptors to the dynamics shaped by voltage-gated ion channels. Therefore, knowing the localizations and types of receptors and channels present in neurons is fundamental to our understanding of neural computation. Here, we developed two approaches to visualize the subcellular localization of specific proteins in Drosophila: The flippase-dependent expression of GFP-tagged receptor subunits in single neurons and ‘FlpTag’, a versatile new tool for the conditional labelling of endogenous proteins. Using these methods, we investigated the subcellular distribution of the receptors GluClα, Rdl, and Dα7 and the ion channels para and Ih in motion-sensing T4/T5 neurons of the Drosophila visual system. We discovered a strictly segregated subcellular distribution of these proteins and a sequential spatial arrangement of glutamate, acetylcholine, and GABA receptors along the dendrite that matched the previously reported EM-reconstructed synapse distributions.
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Affiliation(s)
- Sandra Fendl
- Max Planck Institute of Neurobiology, Martinsried, Germany.,Graduate School of Systemic Neurosciences, LMU Munich, Martinsried, Germany
| | | | - Alexander Borst
- Max Planck Institute of Neurobiology, Martinsried, Germany.,Graduate School of Systemic Neurosciences, LMU Munich, Martinsried, Germany
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18
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Mazzotta GM, Damulewicz M, Cusumano P. Better Sleep at Night: How Light Influences Sleep in Drosophila. Front Physiol 2020; 11:997. [PMID: 33013437 PMCID: PMC7498665 DOI: 10.3389/fphys.2020.00997] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 07/22/2020] [Indexed: 01/25/2023] Open
Abstract
Sleep-like states have been described in Drosophila and the mechanisms and factors that generate and define sleep-wake profiles in this model organism are being thoroughly investigated. Sleep is controlled by both circadian and homeostatic mechanisms, and environmental factors such as light, temperature, and social stimuli are fundamental in shaping and confining sleep episodes into the correct time of the day. Among environmental cues, light seems to have a prominent function in modulating the timing of sleep during the 24 h and, in this review, we will discuss the role of light inputs in modulating the distribution of the fly sleep-wake cycles. This phenomenon is of growing interest in the modern society, where artificial light exposure during the night is a common trait, opening the possibility to study Drosophila as a model organism for investigating shift-work disorders.
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Affiliation(s)
| | - Milena Damulewicz
- Department of Cell Biology and Imaging, Jagiellonian University, Kraków, Poland
| | - Paola Cusumano
- Department of Biology, University of Padova, Padua, Italy
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19
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20
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Städele C, Keleş MF, Mongeau JM, Frye MA. Non-canonical Receptive Field Properties and Neuromodulation of Feature-Detecting Neurons in Flies. Curr Biol 2020; 30:2508-2519.e6. [PMID: 32442460 PMCID: PMC7343589 DOI: 10.1016/j.cub.2020.04.069] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 03/10/2020] [Accepted: 04/24/2020] [Indexed: 10/24/2022]
Abstract
Several fundamental aspects of motion vision circuitry are prevalent across flies and mice. Both taxa segregate ON and OFF signals. For any given spatial pattern, motion detectors in both taxa are tuned to speed, selective for one of four cardinal directions, and modulated by catecholamine neurotransmitters. These similarities represent conserved, canonical properties of the functional circuits and computational algorithms for motion vision. Less is known about feature detectors, including how receptive field properties differ from the motion pathway or whether they are under neuromodulatory control to impart functional plasticity for the detection of salient objects from a moving background. Here, we investigated 19 types of putative feature selective lobula columnar (LC) neurons in the optic lobe of the fruit fly Drosophila melanogaster to characterize divergent properties of feature selection. We identified LC12 and LC15 as feature detectors. LC15 encodes moving bars, whereas LC12 is selective for the motion of discrete objects, mostly independent of size. Neither is selective for contrast polarity, speed, or direction, highlighting key differences in the underlying algorithms for feature detection and motion vision. We show that the onset of background motion suppresses object responses by LC12 and LC15. Surprisingly, the application of octopamine, which is released during flight, reverses the suppressive influence of background motion, rendering both LCs able to track moving objects superimposed against background motion. Our results provide a comparative framework for the function and modulation of feature detectors and new insights into the underlying neuronal mechanisms involved in visual feature detection.
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Affiliation(s)
- Carola Städele
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA
| | - Mehmet F Keleş
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA
| | - Jean-Michel Mongeau
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA
| | - Mark A Frye
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA.
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21
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D'Angelo G, Janotte E, Schoepe T, O'Keeffe J, Milde MB, Chicca E, Bartolozzi C. Event-Based Eccentric Motion Detection Exploiting Time Difference Encoding. Front Neurosci 2020; 14:451. [PMID: 32457575 PMCID: PMC7227134 DOI: 10.3389/fnins.2020.00451] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 04/14/2020] [Indexed: 11/13/2022] Open
Abstract
Attentional selectivity tends to follow events considered as interesting stimuli. Indeed, the motion of visual stimuli present in the environment attract our attention and allow us to react and interact with our surroundings. Extracting relevant motion information from the environment presents a challenge with regards to the high information content of the visual input. In this work we propose a novel integration between an eccentric down-sampling of the visual field, taking inspiration from the varying size of receptive fields (RFs) in the mammalian retina, and the Spiking Elementary Motion Detector (sEMD) model. We characterize the system functionality with simulated data and real world data collected with bio-inspired event driven cameras, successfully implementing motion detection along the four cardinal directions and diagonally.
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Affiliation(s)
- Giulia D'Angelo
- Event Driven Perception for Robotics, Italian Institute of Technology, iCub Facility, Genoa, Italy
| | - Ella Janotte
- Faculty of Technology and Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
| | - Thorben Schoepe
- Faculty of Technology and Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
| | - James O'Keeffe
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Moritz B Milde
- International Centre for Neuromorphic Systems, The MARCS Institute, Western Sydney University, Sydney, NSW, Australia
| | - Elisabetta Chicca
- Faculty of Technology and Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
| | - Chiara Bartolozzi
- Event Driven Perception for Robotics, Italian Institute of Technology, iCub Facility, Genoa, Italy
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22
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Mauss AS, Borst A. Optic flow-based course control in insects. Curr Opin Neurobiol 2020; 60:21-27. [DOI: 10.1016/j.conb.2019.10.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 10/11/2019] [Indexed: 01/31/2023]
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23
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Davis FP, Nern A, Picard S, Reiser MB, Rubin GM, Eddy SR, Henry GL. A genetic, genomic, and computational resource for exploring neural circuit function. eLife 2020; 9:e50901. [PMID: 31939737 PMCID: PMC7034979 DOI: 10.7554/elife.50901] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Accepted: 01/14/2020] [Indexed: 12/11/2022] Open
Abstract
The anatomy of many neural circuits is being characterized with increasing resolution, but their molecular properties remain mostly unknown. Here, we characterize gene expression patterns in distinct neural cell types of the Drosophila visual system using genetic lines to access individual cell types, the TAPIN-seq method to measure their transcriptomes, and a probabilistic method to interpret these measurements. We used these tools to build a resource of high-resolution transcriptomes for 100 driver lines covering 67 cell types, available at http://www.opticlobe.com. Combining these transcriptomes with recently reported connectomes helps characterize how information is transmitted and processed across a range of scales, from individual synapses to circuit pathways. We describe examples that include identifying neurotransmitters, including cases of apparent co-release, generating functional hypotheses based on receptor expression, as well as identifying strong commonalities between different cell types.
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Affiliation(s)
- Fred P Davis
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
- Molecular Immunology and Inflammation BranchNational Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of HealthBethesdaUnited States
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Serge Picard
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Michael B Reiser
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
| | - Sean R Eddy
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
- Howard Hughes Medical Institute and Department of Molecular and Cellular BiologyHarvard UniversityCambridgeUnited States
- John A. Paulson School of Engineering and Applied SciencesHarvard UniversityCambridgeUnited States
| | - Gilbert L Henry
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
- Cold Spring Harbor LaboratoryCold Spring HarborUnited States
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24
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Dynamic Signal Compression for Robust Motion Vision in Flies. Curr Biol 2020; 30:209-221.e8. [PMID: 31928873 DOI: 10.1016/j.cub.2019.10.035] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 09/17/2019] [Accepted: 10/18/2019] [Indexed: 12/16/2022]
Abstract
Sensory systems need to reliably extract information from highly variable natural signals. Flies, for instance, use optic flow to guide their course and are remarkably adept at estimating image velocity regardless of image statistics. Current circuit models, however, cannot account for this robustness. Here, we demonstrate that the Drosophila visual system reduces input variability by rapidly adjusting its sensitivity to local contrast conditions. We exhaustively map functional properties of neurons in the motion detection circuit and find that local responses are compressed by surround contrast. The compressive signal is fast, integrates spatially, and derives from neural feedback. Training convolutional neural networks on estimating the velocity of natural stimuli shows that this dynamic signal compression can close the performance gap between model and organism. Overall, our work represents a comprehensive mechanistic account of how neural systems attain the robustness to carry out survival-critical tasks in challenging real-world environments.
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25
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Wei H, Kyung HY, Kim PJ, Desplan C. The diversity of lobula plate tangential cells (LPTCs) in the Drosophila motion vision system. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2019; 206:139-148. [PMID: 31709462 DOI: 10.1007/s00359-019-01380-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 10/29/2019] [Accepted: 11/05/2019] [Indexed: 12/15/2022]
Abstract
To navigate through the environment, animals rely on visual feedback to control their movements relative to their surroundings. In dipteran flies, visual feedback is provided by the wide-field motion-sensitive neurons in the visual system called lobula plate tangential cells (LPTCs). Understanding the role of LPTCs in fly behaviors can address many fundamental questions on how sensory circuits guide behaviors. The blowfly was estimated to have ~ 60 LPTCs, but only a few have been identified in Drosophila. We conducted a Gal4 driver screen and identified five LPTC subtypes in Drosophila, based on their morphological characteristics: LPTCs have large arborizations in the lobula plate and project to the central brain. We compared their morphologies to the blowfly LPTCs and named them after the most similar blowfly cells: CH, H1, H2, FD1 and FD3, and V1. We further characterized their pre- and post-synaptic organizations, as well as their neurotransmitter profiles. These anatomical features largely agree with the anatomy and function of their likely blowfly counterparts. Nevertheless, several anatomical details indicate the Drosophila LPTCs may have more complex functions. Our characterization of these five LPTCs in Drosophila will facilitate further functional studies to understand their roles in the visual circuits that instruct fly behaviors.
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Affiliation(s)
- Huayi Wei
- Department of Biology, New York University, New York, NY, USA
| | - Ha Young Kyung
- Department of Biology, New York University, New York, NY, USA
| | - Priscilla J Kim
- Department of Biology, New York University, New York, NY, USA
| | - Claude Desplan
- Department of Biology, New York University, New York, NY, USA.
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26
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How fly neurons compute the direction of visual motion. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2019; 206:109-124. [PMID: 31691093 PMCID: PMC7069908 DOI: 10.1007/s00359-019-01375-9] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 10/16/2019] [Accepted: 10/23/2019] [Indexed: 10/25/2022]
Abstract
Detecting the direction of image motion is a fundamental component of visual computation, essential for survival of the animal. However, at the level of individual photoreceptors, the direction in which the image is shifting is not explicitly represented. Rather, directional motion information needs to be extracted from the photoreceptor array by comparing the signals of neighboring units over time. The exact nature of this process as implemented in the visual system of the fruit fly Drosophila melanogaster has been studied in great detail, and much progress has recently been made in determining the neural circuits giving rise to directional motion information. The results reveal the following: (1) motion information is computed in parallel ON and OFF pathways. (2) Within each pathway, T4 (ON) and T5 (OFF) cells are the first neurons to represent the direction of motion. Four subtypes of T4 and T5 cells exist, each sensitive to one of the four cardinal directions. (3) The core process of direction selectivity as implemented on the dendrites of T4 and T5 cells comprises both an enhancement of signals for motion along their preferred direction as well as a suppression of signals for motion along the opposite direction. This combined strategy ensures a high degree of direction selectivity right at the first stage where the direction of motion is computed. (4) At the subsequent processing stage, tangential cells spatially integrate direct excitation from ON and OFF-selective T4 and T5 cells and indirect inhibition from bi-stratified LPi cells activated by neighboring T4/T5 terminals, thus generating flow-field-selective responses.
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27
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Shinomiya K, Horne JA, McLin S, Wiederman M, Nern A, Plaza SM, Meinertzhagen IA. The Organization of the Second Optic Chiasm of the Drosophila Optic Lobe. Front Neural Circuits 2019; 13:65. [PMID: 31680879 PMCID: PMC6797552 DOI: 10.3389/fncir.2019.00065] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 09/27/2019] [Indexed: 01/03/2023] Open
Abstract
Visual pathways from the compound eye of an insect relay to four neuropils, successively the lamina, medulla, lobula, and lobula plate in the underlying optic lobe. Among these neuropils, the medulla, lobula, and lobula plate are interconnected by the complex second optic chiasm, through which the anteroposterior axis undergoes an inversion between the medulla and lobula. Given their complex structure, the projection patterns through the second optic chiasm have so far lacked critical analysis. By densely reconstructing axon trajectories using a volumetric scanning electron microscopy (SEM) technique, we reveal the three-dimensional structure of the second optic chiasm of Drosophila melanogaster, which comprises interleaving bundles and sheets of axons insulated from each other by glial sheaths. These axon bundles invert their horizontal sequence in passing between the medulla and lobula. Axons connecting the medulla and lobula plate are also bundled together with them but do not decussate the sequence of their horizontal positions. They interleave with sheets of projection neuron axons between the lobula and lobula plate, which also lack decussations. We estimate that approximately 19,500 cells per hemisphere, about two thirds of the optic lobe neurons, contribute to the second chiasm, most being Tm cells, with an estimated additional 2,780 T4 and T5 cells each. The chiasm mostly comprises axons and cell body fibers, but also a few synaptic elements. Based on our anatomical findings, we propose that a chiasmal structure between the neuropils is potentially advantageous for processing complex visual information in parallel. The EM reconstruction shows not only the structure of the chiasm in the adult brain, the previously unreported main topic of our study, but also suggest that the projection patterns of the neurons comprising the chiasm may be determined by the proliferation centers from which the neurons develop. Such a complex wiring pattern could, we suggest, only have arisen in several evolutionary steps.
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Affiliation(s)
| | - Jane Anne Horne
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
| | - Sari McLin
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
| | - Meagan Wiederman
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
| | - Aljoscha Nern
- Howard Hughes Medical Institute, Ashburn, VA, United States
| | | | - Ian A Meinertzhagen
- Howard Hughes Medical Institute, Ashburn, VA, United States.,Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
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28
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Contreras EG, Sierralta J, Oliva C. Novel Strategies for the Generation of Neuronal Diversity: Lessons From the Fly Visual System. Front Mol Neurosci 2019; 12:140. [PMID: 31213980 PMCID: PMC6554424 DOI: 10.3389/fnmol.2019.00140] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 05/13/2019] [Indexed: 12/17/2022] Open
Abstract
Among all organs of an adult animal, the central nervous system stands out because of its vast complexity and morphological diversity. During early development, the entire central nervous system develops from an apparently homogenous group of progenitors that differentiate into all neural cell types. Therefore, understanding the molecular and genetic mechanisms that give rise to the cellular and anatomical diversity of the brain is a key goal of the developmental neurobiology field. With this aim in mind, the development of the central nervous system of model organisms has been extensively studied. From more than a century, the mechanisms of neurogenesis have been studied in the fruit fly Drosophila melanogaster. The visual system comprises one of the major structures of the Drosophila brain. The visual information is collected by the eye-retina photoreceptors and then processed by the four optic lobe ganglia: the lamina, medulla, lobula and lobula plate. The molecular mechanisms that originate neuronal diversity in the optic lobe have been unveiled in the past decade. In this article, we describe the early development and differentiation of the lobula plate ganglion, from the formation of the optic placode and the inner proliferation center to the specification of motion detection neurons. We focused specifically on how the precise combination of signaling pathways and cell-specific transcription factors patterns the pool of neural stem cells that generates the different neurons of the motion detection system.
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Affiliation(s)
- Esteban G Contreras
- Department of Neuroscience and Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Jimena Sierralta
- Department of Neuroscience and Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Carlos Oliva
- Department of Cellular and Molecular Biology, Faculty of Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
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29
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Olfactory and Neuromodulatory Signals Reverse Visual Object Avoidance to Approach in Drosophila. Curr Biol 2019; 29:2058-2065.e2. [PMID: 31155354 DOI: 10.1016/j.cub.2019.05.010] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 04/01/2019] [Accepted: 05/01/2019] [Indexed: 12/15/2022]
Abstract
Behavioral reactions of animals to environmental sensory stimuli are sometimes reflexive and stereotyped but can also vary depending on contextual conditions. Engaging in active foraging or flight provokes a reversal in the valence of carbon dioxide responses from aversion to approach in Drosophila [1, 2], whereas mosquitoes encountering this same chemical cue show enhanced approach toward a small visual object [3]. Sensory plasticity in insects has been broadly attributed to the action of biogenic amines, which modulate behaviors such as olfactory learning, aggression, feeding, and egg laying [4-14]. Octopamine acts rapidly upon the onset of flight to modulate the response gain of directionally selective motion-detecting neurons in Drosophila [15]. How the action of biogenic amines might couple sensory modalities to each other or to locomotive states remains poorly understood. Here, we use a visual flight simulator [16] equipped for odor delivery [17] to confirm that flies avoid a small contrasting visual object in odorless air [18] but that the same animals reverse their preference to approach in the presence of attractive food odor. An aversive odor does not reverse object aversion. Optogenetic activation of either octopaminergic neurons or directionally selective motion-detecting neurons that express octopamine receptors elicits visual valence reversal in the absence of odor. Our results suggest a parsimonious model in which odor-activated octopamine release excites the motion detection pathway to increase the saliency of either a small object or a bar, eliciting tracking responses by both visual features.
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30
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He H, Yang X, Xu Z, Deng N, Shang Y, Liu G, Ji M, Zheng W, Zhao J, Dong L. Implementing artificial neural networks through bionic construction. PLoS One 2019; 14:e0212368. [PMID: 30794587 PMCID: PMC6386347 DOI: 10.1371/journal.pone.0212368] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 01/31/2019] [Indexed: 01/12/2023] Open
Abstract
It is evident through biology research that, biological neural network could be implemented through two means: by congenital heredity, or by posteriority learning. However, traditionally, artificial neural network, especially the Deep learning Neural Networks (DNNs) are implemented only through exhaustive training and learning. Fixed structure is built, and then parameters are trained through huge amount of data. In this way, there are a lot of redundancies in the implemented artificial neural network. This redundancy not only requires more effort to train the network, but also costs more computing resources when used. In this paper, we proposed a bionic way to implement artificial neural network through construction rather than training and learning. The hierarchy of the neural network is designed according to analysis of the required functionality, and then module design is carried out to form each hierarchy. We choose the Drosophila’s visual neural network as a test case to verify our method’s validation. The results show that the bionic artificial neural network built through our method could work as a bionic compound eye, which can achieve the detection of the object and their movement, and the results are better on some properties, compared with the Drosophila’s biological compound eyes.
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Affiliation(s)
- Hu He
- Institute of Microelectronics, Tsinghua University, Beijing, China
| | - Xu Yang
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
- * E-mail:
| | - Zhiheng Xu
- Institute of Microelectronics, Tsinghua University, Beijing, China
| | - Ning Deng
- Institute of Microelectronics, Tsinghua University, Beijing, China
| | - Yingjie Shang
- Institute of Microelectronics, Tsinghua University, Beijing, China
| | - Guo Liu
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Mengyao Ji
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Wenhao Zheng
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Jinfeng Zhao
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Liya Dong
- Institute of Microelectronics, Tsinghua University, Beijing, China
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31
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Schilling T, Ali AH, Leonhardt A, Borst A, Pujol-Martí J. Transcriptional control of morphological properties of direction-selective T4/T5 neurons in Drosophila. Development 2019; 146:dev169763. [PMID: 30642835 PMCID: PMC6361130 DOI: 10.1242/dev.169763] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 01/07/2019] [Indexed: 02/02/2023]
Abstract
In the Drosophila visual system, T4/T5 neurons represent the first stage of computation of the direction of visual motion. T4 and T5 neurons exist in four subtypes, each responding to motion in one of the four cardinal directions and projecting axons into one of the four lobula plate layers. However, all T4/T5 neurons share properties essential for sensing motion. How T4/T5 neurons acquire their properties during development is poorly understood. We reveal that the transcription factors SoxN and Sox102F control the acquisition of properties common to all T4/T5 neuron subtypes, i.e. the layer specificity of dendrites and axons. Accordingly, adult flies are motion blind after disruption of SoxN or Sox102F in maturing T4/T5 neurons. We further find that the transcription factors Ato and Dac are redundantly required in T4/T5 neuron progenitors for SoxN and Sox102F expression in T4/T5 neurons, linking the transcriptional programmes specifying progenitor identity to those regulating the acquisition of morphological properties in neurons. Our work will help to link structure, function and development in a neuronal type performing a computation that is conserved across vertebrate and invertebrate visual systems.
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Affiliation(s)
- Tabea Schilling
- Department of 'Circuits - Computation - Models', Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Aicha H Ali
- Department of 'Circuits - Computation - Models', Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Aljoscha Leonhardt
- Department of 'Circuits - Computation - Models', Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Alexander Borst
- Department of 'Circuits - Computation - Models', Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
| | - Jesús Pujol-Martí
- Department of 'Circuits - Computation - Models', Max Planck Institute of Neurobiology, 82152 Martinsried, Germany
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Busch C, Borst A, Mauss AS. Bi-directional Control of Walking Behavior by Horizontal Optic Flow Sensors. Curr Biol 2018; 28:4037-4045.e5. [PMID: 30528583 DOI: 10.1016/j.cub.2018.11.010] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 10/02/2018] [Accepted: 11/02/2018] [Indexed: 12/13/2022]
Abstract
Moving animals experience constant sensory feedback, such as panoramic image shifts on the retina, termed optic flow. Underlying neuronal signals are thought to be important for exploratory behavior by signaling unintended course deviations and by providing spatial information about the environment [1, 2]. Particularly in insects, the encoding of self-motion-related optic flow is well understood [1-5]. However, a gap remains in understanding how the associated neuronal activity controls locomotor trajectories. In flies, visual projection neurons belonging to two groups encode panoramic horizontal motion: horizontal system (HS) cells respond with depolarization to front-to-back motion and hyperpolarization to the opposite direction [6, 7], and other neurons have the mirror-symmetrical response profile [6, 8, 9]. With primarily monocular sensitivity, the neurons' responses are ambiguous for different rotational and translational self-movement components. Such ambiguities can be greatly reduced by combining signals from both eyes [10-12] to determine turning and movement speed [13-16]. Here, we explore the underlying functional logic by optogenetic HS cell manipulation in tethered walking Drosophila. We show that de- and hyperpolarization evoke opposite turning behavior, indicating that both direction-selective signals are transmitted to descending pathways for course control. Further experiments reveal a negative effect of bilaterally symmetric de- and hyperpolarization on walking velocity. Our results are therefore consistent with a functional architecture in which the HS cells' membrane potential influences walking behavior bi-directionally via two decelerating pathways.
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Affiliation(s)
- Christian Busch
- Circuits - Computation - Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany
| | - Alexander Borst
- Circuits - Computation - Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany
| | - Alex S Mauss
- Circuits - Computation - Models, Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.
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33
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Boergens KM, Kapfer C, Helmstaedter M, Denk W, Borst A. Full reconstruction of large lobula plate tangential cells in Drosophila from a 3D EM dataset. PLoS One 2018; 13:e0207828. [PMID: 30485333 PMCID: PMC6261601 DOI: 10.1371/journal.pone.0207828] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Accepted: 11/04/2018] [Indexed: 01/10/2023] Open
Abstract
With the advent of neurogenetic methods, the neural basis of behavior is presently being analyzed in more and more detail. This is particularly true for visually driven behavior of Drosophila melanogaster where cell-specific driver lines exist that, depending on the combination with appropriate effector genes, allow for targeted recording, silencing and optogenetic stimulation of individual cell-types. Together with detailed connectomic data of large parts of the fly optic lobe, this has recently led to much progress in our understanding of the neural circuits underlying local motion detection. However, how such local information is combined by optic flow sensitive large-field neurons is still incompletely understood. Here, we aim to fill this gap by a dense reconstruction of lobula plate tangential cells of the fly lobula plate. These neurons collect input from many hundreds of local motion-sensing T4/T5 neurons and connect them to descending neurons or central brain areas. We confirm all basic features of HS and VS cells as published previously from light microscopy. In addition, we identified the dorsal and the ventral centrifugal horizontal, dCH and vCH cell, as well as three VSlike cells, including their distinct dendritic and axonal projection area.
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Affiliation(s)
- Kevin M. Boergens
- Max-Planck-Institute for Brain Research, Frankfurt, Germany
- * E-mail: (KMB); (AB)
| | | | | | - Winfried Denk
- Max-Planck-Institute of Neurobiology, Martinsried, Germany
| | - Alexander Borst
- Max-Planck-Institute of Neurobiology, Martinsried, Germany
- * E-mail: (KMB); (AB)
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34
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Richter FG, Fendl S, Haag J, Drews MS, Borst A. Glutamate Signaling in the Fly Visual System. iScience 2018; 7:85-95. [PMID: 30267688 PMCID: PMC6135900 DOI: 10.1016/j.isci.2018.08.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 08/13/2018] [Accepted: 08/23/2018] [Indexed: 10/28/2022] Open
Abstract
For a proper understanding of neural circuit function, it is important to know which signals neurons relay to their downstream partners. Calcium imaging with genetically encoded calcium sensors like GCaMP has become the default approach for mapping these responses. How well such measurements represent the true neurotransmitter output of any given cell, however, remains unclear. Here, we demonstrate the viability of the glutamate sensor iGluSnFR for 2-photon in vivo imaging in Drosophila melanogaster and prove its usefulness for estimating spatiotemporal receptive fields in the visual system. We compare the results obtained with iGluSnFR with the ones obtained with GCaMP6f and find that the spatial aspects of the receptive fields are preserved between indicators. In the temporal domain, however, measurements obtained with iGluSnFR reveal the underlying response properties to be much faster than those acquired with GCaMP6f. Our approach thus offers a more accurate description of glutamatergic neurons in the fruit fly.
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Affiliation(s)
| | - Sandra Fendl
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Jürgen Haag
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Michael S Drews
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany
| | - Alexander Borst
- Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany.
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35
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Ribeiro IMA, Drews M, Bahl A, Machacek C, Borst A, Dickson BJ. Visual Projection Neurons Mediating Directed Courtship in Drosophila. Cell 2018; 174:607-621.e18. [PMID: 30033367 DOI: 10.1016/j.cell.2018.06.020] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Revised: 03/07/2018] [Accepted: 06/10/2018] [Indexed: 11/19/2022]
Abstract
Many animals rely on vision to detect, locate, and track moving objects. In Drosophila courtship, males primarily use visual cues to orient toward and follow females and to select the ipsilateral wing for courtship song. Here, we show that the LC10 visual projection neurons convey essential visual information during courtship. Males with LC10 neurons silenced are unable to orient toward or maintain proximity to the female and do not predominantly use the ipsilateral wing when singing. LC10 neurons preferentially respond to small moving objects using an antagonistic motion-based center-surround mechanism. Unilateral activation of LC10 neurons recapitulates the orienting and ipsilateral wing extension normally elicited by females, and the potency with which LC10 induces wing extension is enhanced in a state of courtship arousal controlled by male-specific P1 neurons. These data suggest that LC10 is a major pathway relaying visual input to the courtship circuits in the male brain.
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Affiliation(s)
- Inês M A Ribeiro
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Max Plank Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany; Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Michael Drews
- Max Plank Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Armin Bahl
- Max Plank Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Christian Machacek
- Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Alexander Borst
- Max Plank Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany.
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, 1030 Vienna, Austria; Queensland Brain Institute, University of Queensland, St. Lucia, QLD 4072, Australia.
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36
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Milde MB, Bertrand OJN, Ramachandran H, Egelhaaf M, Chicca E. Spiking Elementary Motion Detector in Neuromorphic Systems. Neural Comput 2018; 30:2384-2417. [PMID: 30021082 DOI: 10.1162/neco_a_01112] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Apparent motion of the surroundings on an agent's retina can be used to navigate through cluttered environments, avoid collisions with obstacles, or track targets of interest. The pattern of apparent motion of objects, (i.e., the optic flow), contains spatial information about the surrounding environment. For a small, fast-moving agent, as used in search and rescue missions, it is crucial to estimate the distance to close-by objects to avoid collisions quickly. This estimation cannot be done by conventional methods, such as frame-based optic flow estimation, given the size, power, and latency constraints of the necessary hardware. A practical alternative makes use of event-based vision sensors. Contrary to the frame-based approach, they produce so-called events only when there are changes in the visual scene. We propose a novel asynchronous circuit, the spiking elementary motion detector (sEMD), composed of a single silicon neuron and synapse, to detect elementary motion from an event-based vision sensor. The sEMD encodes the time an object's image needs to travel across the retina into a burst of spikes. The number of spikes within the burst is proportional to the speed of events across the retina. A fast but imprecise estimate of the time-to-travel can already be obtained from the first two spikes of a burst and refined by subsequent interspike intervals. The latter encoding scheme is possible due to an adaptive nonlinear synaptic efficacy scaling. We show that the sEMD can be used to compute a collision avoidance direction in the context of robotic navigation in a cluttered outdoor environment and compared the collision avoidance direction to a frame-based algorithm. The proposed computational principle constitutes a generic spiking temporal correlation detector that can be applied to other sensory modalities (e.g., sound localization), and it provides a novel perspective to gating information in spiking neural networks.
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Affiliation(s)
- M B Milde
- Institute of Neuroinformatics, University of Zurich, and ETH Zurich, 8057 Zurich, Switzerland
| | - O J N Bertrand
- Neurobiology, Faculty of Biology, Bielefeld University, 33615 Bielefeld, and Cognitive Interaction Technology, Center of Excellence, Bielefeld University, 33501 Bielefeld, Germany
| | - H Ramachandran
- Faculty of Technology, Bielefeld University, 33615 Bielefeld, and Cognitive Interaction Technology, Center of Excellence, Bielefeld University, 33501 Bielefeld, Germany
| | - M Egelhaaf
- Neurobiology, Faculty of Biology, Bielefeld University, 33615 Bielefeld, and Cognitive Interaction Technology, Center of Excellence, Bielefeld University, 33501 Bielefeld, Germany
| | - E Chicca
- Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany, and Cognitive Interaction Technology, Center of Excellence, Bielefeld University, 33501 Bielefeld, Germany
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37
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Abstract
Motion in the visual world provides critical information to guide the behavior of sighted animals. Furthermore, as visual motion estimation requires comparisons of signals across inputs and over time, it represents a paradigmatic and generalizable neural computation. Focusing on the Drosophila visual system, where an explosion of technological advances has recently accelerated experimental progress, we review our understanding of how, algorithmically and mechanistically, motion signals are first computed.
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Affiliation(s)
- Helen H Yang
- Department of Neurobiology, Stanford University, Stanford, California 94305, USA; .,Current affiliation: Department of Neurobiology, Harvard Medical School, Boston, Massachusetts 02115, USA;
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University, Stanford, California 94305, USA;
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38
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Apitz H, Salecker I. Spatio-temporal relays control layer identity of direction-selective neuron subtypes in Drosophila. Nat Commun 2018; 9:2295. [PMID: 29895891 PMCID: PMC5997761 DOI: 10.1038/s41467-018-04592-z] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 05/04/2018] [Indexed: 11/09/2022] Open
Abstract
Visual motion detection in sighted animals is essential to guide behavioral actions ensuring their survival. In Drosophila, motion direction is first detected by T4/T5 neurons. Their axons innervate one of the four lobula plate layers. How T4/T5 neurons with layer-specific representation of motion-direction preferences are specified during development is unknown. We show that diffusible Wingless (Wg) between adjacent neuroepithelia induces its own expression to form secondary signaling centers. These activate Decapentaplegic (Dpp) signaling in adjacent lateral tertiary neuroepithelial domains dedicated to producing layer 3/4-specific T4/T5 neurons. T4/T5 neurons derived from the core domain devoid of Dpp signaling adopt the default layer 1/2 fate. Dpp signaling induces the expression of the T-box transcription factor Optomotor-blind (Omb), serving as a relay to postmitotic neurons. Omb-mediated repression of Dachshund transforms layer 1/2- into layer 3/4-specific neurons. Hence, spatio-temporal relay mechanisms, bridging the distances between neuroepithelial domains and their postmitotic progeny, implement T4/T5 neuron-subtype identity.
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Affiliation(s)
- Holger Apitz
- The Francis Crick Institute, Visual Circuit Assembly Laboratory, 1 Midland Road, London, NW1 1AT, UK
| | - Iris Salecker
- The Francis Crick Institute, Visual Circuit Assembly Laboratory, 1 Midland Road, London, NW1 1AT, UK.
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39
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Borst A. A biophysical mechanism for preferred direction enhancement in fly motion vision. PLoS Comput Biol 2018; 14:e1006240. [PMID: 29897917 PMCID: PMC6016951 DOI: 10.1371/journal.pcbi.1006240] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 06/25/2018] [Accepted: 05/29/2018] [Indexed: 11/18/2022] Open
Abstract
Seeing the direction of motion is essential for survival of all sighted animals. Consequently, nerve cells that respond to visual stimuli moving in one but not in the opposite direction, so-called 'direction-selective' neurons, are found abundantly. In general, direction selectivity can arise by either signal amplification for stimuli moving in the cell's preferred direction ('preferred direction enhancement'), signal suppression for stimuli moving along the opposite direction ('null direction suppression'), or a combination of both. While signal suppression can be readily implemented in biophysical terms by a hyperpolarization followed by a rectification corresponding to the nonlinear voltage-dependence of the Calcium channel, the biophysical mechanism for signal amplification has remained unclear so far. Taking inspiration from the fly, I analyze a neural circuit where a direction-selective ON-cell receives inhibitory input from an OFF cell on the preferred side of the dendrite, while excitatory ON-cells contact the dendrite centrally. This way, an ON edge moving along the cell's preferred direction suppresses the inhibitory input, leading to a release from inhibition in the postsynaptic cell. The benefit of such a two-fold signal inversion lies in the resulting increase of the postsynaptic cell's input resistance, amplifying its response to a subsequent excitatory input signal even with a passive dendrite, i.e. without voltage-gated ion channels. A motion detector implementing this mechanism together with null direction suppression shows a high degree of direction selectivity over a large range of temporal frequency, narrow directional tuning, and a large signal-to-noise ratio.
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40
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Wang H, Dewell RB, Zhu Y, Gabbiani F. Feedforward Inhibition Conveys Time-Varying Stimulus Information in a Collision Detection Circuit. Curr Biol 2018; 28:1509-1521.e3. [PMID: 29754904 DOI: 10.1016/j.cub.2018.04.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Revised: 03/06/2018] [Accepted: 04/03/2018] [Indexed: 10/16/2022]
Abstract
Feedforward inhibition is ubiquitous as a motif in the organization of neuronal circuits. During sensory information processing, it is traditionally thought to sharpen the responses and temporal tuning of feedforward excitation onto principal neurons. As it often exhibits complex time-varying activation properties, feedforward inhibition could also convey information used by single neurons to implement dendritic computations on sensory stimulus variables. We investigated this possibility in a collision-detecting neuron of the locust optic lobe that receives both feedforward excitation and inhibition. We identified a small population of neurons mediating feedforward inhibition, with wide visual receptive fields and whose responses depend both on the size and speed of moving stimuli. By studying responses to simulated objects approaching on a collision course, we determined that they jointly encode the angular size of expansion of the stimulus. Feedforward excitation, on the other hand, encodes a function of the angular velocity of expansion and the targeted collision-detecting neuron combines these two variables non-linearly in its firing output. Thus, feedforward inhibition actively contributes to the detailed firing-rate time course of this collision-detecting neuron, a feature critical to the appropriate execution of escape behaviors. These results suggest that feedforward inhibition could similarly convey time-varying stimulus information in other neuronal circuits.
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Affiliation(s)
- Hongxia Wang
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Richard B Dewell
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ying Zhu
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA; Quantitative and Computational Biosciences, Graduate Program, Baylor College of Medicine, Houston, TX 77030, USA
| | - Fabrizio Gabbiani
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA; Quantitative and Computational Biosciences, Graduate Program, Baylor College of Medicine, Houston, TX 77030, USA; Electrical and Computer Engineering Department, Rice University, Houston, TX 77005, USA.
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41
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Development of Concurrent Retinotopic Maps in the Fly Motion Detection Circuit. Cell 2018; 173:485-498.e11. [PMID: 29576455 DOI: 10.1016/j.cell.2018.02.053] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 12/24/2017] [Accepted: 02/21/2018] [Indexed: 11/22/2022]
Abstract
Understanding how complex brain wiring is produced during development is a daunting challenge. In Drosophila, information from 800 retinal ommatidia is processed in distinct brain neuropiles, each subdivided into 800 matching retinotopic columns. The lobula plate comprises four T4 and four T5 neuronal subtypes. T4 neurons respond to bright edge motion, whereas T5 neurons respond to dark edge motion. Each is tuned to motion in one of the four cardinal directions, effectively establishing eight concurrent retinotopic maps to support wide-field motion. We discovered a mode of neurogenesis where two sequential Notch-dependent divisions of either a horizontal or a vertical progenitor produce matching sets of two T4 and two T5 neurons retinotopically coincident with pairwise opposite direction selectivity. We show that retinotopy is an emergent characteristic of this neurogenic program and derives directly from neuronal birth order. Our work illustrates how simple developmental rules can implement complex neural organization.
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42
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Li J, Lindemann JP, Egelhaaf M. Local motion adaptation enhances the representation of spatial structure at EMD arrays. PLoS Comput Biol 2017; 13:e1005919. [PMID: 29281631 PMCID: PMC5760083 DOI: 10.1371/journal.pcbi.1005919] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Revised: 01/09/2018] [Accepted: 11/13/2017] [Indexed: 11/18/2022] Open
Abstract
Neuronal representation and extraction of spatial information are essential for behavioral control. For flying insects, a plausible way to gain spatial information is to exploit distance-dependent optic flow that is generated during translational self-motion. Optic flow is computed by arrays of local motion detectors retinotopically arranged in the second neuropile layer of the insect visual system. These motion detectors have adaptive response characteristics, i.e. their responses to motion with a constant or only slowly changing velocity decrease, while their sensitivity to rapid velocity changes is maintained or even increases. We analyzed by a modeling approach how motion adaptation affects signal representation at the output of arrays of motion detectors during simulated flight in artificial and natural 3D environments. We focused on translational flight, because spatial information is only contained in the optic flow induced by translational locomotion. Indeed, flies, bees and other insects segregate their flight into relatively long intersaccadic translational flight sections interspersed with brief and rapid saccadic turns, presumably to maximize periods of translation (80% of the flight). With a novel adaptive model of the insect visual motion pathway we could show that the motion detector responses to background structures of cluttered environments are largely attenuated as a consequence of motion adaptation, while responses to foreground objects stay constant or even increase. This conclusion even holds under the dynamic flight conditions of insects.
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Affiliation(s)
- Jinglin Li
- Department of Neurobiology and Cluster of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
- * E-mail:
| | - Jens P. Lindemann
- Department of Neurobiology and Cluster of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
| | - Martin Egelhaaf
- Department of Neurobiology and Cluster of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
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43
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Neural mechanisms underlying sensitivity to reverse-phi motion in the fly. PLoS One 2017; 12:e0189019. [PMID: 29261684 PMCID: PMC5737883 DOI: 10.1371/journal.pone.0189019] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 11/18/2017] [Indexed: 01/18/2023] Open
Abstract
Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics.
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44
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Wang S, Borst A, Zaslavsky N, Tishby N, Segev I. Efficient encoding of motion is mediated by gap junctions in the fly visual system. PLoS Comput Biol 2017; 13:e1005846. [PMID: 29206224 PMCID: PMC5730180 DOI: 10.1371/journal.pcbi.1005846] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Revised: 12/14/2017] [Accepted: 10/16/2017] [Indexed: 01/10/2023] Open
Abstract
Understanding the computational implications of specific synaptic connectivity patterns is a fundamental goal in neuroscience. In particular, the computational role of ubiquitous electrical synapses operating via gap junctions remains elusive. In the fly visual system, the cells in the vertical-system network, which play a key role in visual processing, primarily connect to each other via axonal gap junctions. This network therefore provides a unique opportunity to explore the functional role of gap junctions in sensory information processing. Our information theoretical analysis of a realistic VS network model shows that within 10 ms following the onset of the visual input, the presence of axonal gap junctions enables the VS system to efficiently encode the axis of rotation, θ, of the fly’s ego motion. This encoding efficiency, measured in bits, is near-optimal with respect to the physical limits of performance determined by the statistical structure of the visual input itself. The VS network is known to be connected to downstream pathways via a subset of triplets of the vertical system cells; we found that because of the axonal gap junctions, the efficiency of this subpopulation in encoding θ is superior to that of the whole vertical system network and is robust to a wide range of signal to noise ratios. We further demonstrate that this efficient encoding of motion by this subpopulation is necessary for the fly's visually guided behavior, such as banked turns in evasive maneuvers. Because gap junctions are formed among the axons of the vertical system cells, they only impact the system’s readout, while maintaining the dendritic input intact, suggesting that the computational principles implemented by neural circuitries may be much richer than previously appreciated based on point neuron models. Our study provides new insights as to how specific network connectivity leads to efficient encoding of sensory stimuli. Understanding sensory stimuli from the environment and deciding how best to respond to it behaviorally is essential for survival. What makes organisms efficient in encoding these sensory stimuli? This study provides a novel view on this unresolved issue using the visual system of the fly. We show that a specific synaptic connectivity manifested via gap junctions (GJs) among axons in the Vertical System (VS) network leads to particularly high encoding efficiency of the axis of rotation of the fly’s ego motion. Due to these GJs, triplets of VS neurons (the VS5-6-7 triplet), which connect to a downstream motor system, encode motion stimuli at an efficiency close to the physical limit; this efficient encoding is necessary for evasive maneuvers that are critical for the fly to escape predators. We then suggest why GJs in the VS network enable such high encoding efficiency.
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Affiliation(s)
- Siwei Wang
- Department of Neurobiology, Hebrew University Jerusalem, Jerusalem, Israel
- * E-mail:
| | - Alexander Borst
- Max Planck Institute of Neurobiology, Martinstried, Munich, Germany
| | - Noga Zaslavsky
- The Edmond and Lily Safra Center for Brain Sciences, Hebrew University Jerusalem, Jerusalem, Israel
| | - Naftali Tishby
- The Edmond and Lily Safra Center for Brain Sciences, Hebrew University Jerusalem, Jerusalem, Israel
- Department of Computer Science, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Idan Segev
- Department of Neurobiology, Hebrew University Jerusalem, Jerusalem, Israel
- Max Planck Institute of Neurobiology, Martinstried, Munich, Germany
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45
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Optogenetic Neuronal Silencing in Drosophila during Visual Processing. Sci Rep 2017; 7:13823. [PMID: 29061981 PMCID: PMC5653863 DOI: 10.1038/s41598-017-14076-7] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 10/06/2017] [Indexed: 02/04/2023] Open
Abstract
Optogenetic channels and ion pumps have become indispensable tools in neuroscience to manipulate neuronal activity and thus to establish synaptic connectivity and behavioral causality. Inhibitory channels are particularly advantageous to explore signal processing in neural circuits since they permit the functional removal of selected neurons on a trial-by-trial basis. However, applying these tools to study the visual system poses a considerable challenge because the illumination required for their activation usually also stimulates photoreceptors substantially, precluding the simultaneous probing of visual responses. Here, we explore the utility of the recently discovered anion channelrhodopsins GtACR1 and GtACR2 for application in the visual system of Drosophila. We first characterized their properties using a larval crawling assay. We further obtained whole-cell recordings from cells expressing GtACR1, which mediated strong and light-sensitive photocurrents. Finally, using physiological recordings and a behavioral readout, we demonstrate that GtACR1 enables the fast and reversible silencing of genetically targeted neurons within circuits engaged in visual processing.
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46
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Perry M, Konstantinides N, Pinto-Teixeira F, Desplan C. Generation and Evolution of Neural Cell Types and Circuits: Insights from the Drosophila Visual System. Annu Rev Genet 2017; 51:501-527. [PMID: 28961025 DOI: 10.1146/annurev-genet-120215-035312] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The Drosophila visual system has become a premier model for probing how neural diversity is generated during development. Recent work has provided deeper insight into the elaborate mechanisms that control the range of types and numbers of neurons produced, which neurons survive, and how they interact. These processes drive visual function and influence behavioral preferences. Other studies are beginning to provide insight into how neuronal diversity evolved in insects by adding new cell types and modifying neural circuits. Some of the most powerful comparisons have been those made to the Drosophila visual system, where a deeper understanding of molecular mechanisms allows for the generation of hypotheses about the evolution of neural anatomy and function. The evolution of new neural types contributes additional complexity to the brain and poses intriguing questions about how new neurons interact with existing circuitry. We explore how such individual changes in a variety of species might play a role over evolutionary timescales. Lessons learned from the fly visual system apply to other neural systems, including the fly central brain, where decisions are made and memories are stored.
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Affiliation(s)
- Michael Perry
- Department of Biology, New York University, New York, NY 10003, USA;
| | | | - Filipe Pinto-Teixeira
- Department of Biology, New York University, New York, NY 10003, USA; .,Center for Genomics and Systems Biology, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
| | - Claude Desplan
- Department of Biology, New York University, New York, NY 10003, USA; .,Center for Genomics and Systems Biology, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates
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47
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Azevedo AW, Wilson RI. Active Mechanisms of Vibration Encoding and Frequency Filtering in Central Mechanosensory Neurons. Neuron 2017; 96:446-460.e9. [PMID: 28943231 DOI: 10.1016/j.neuron.2017.09.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 07/26/2017] [Accepted: 09/05/2017] [Indexed: 12/11/2022]
Abstract
To better understand biophysical mechanisms of mechanosensory processing, we investigated two cell types in the Drosophila brain (A2 and B1 cells) that are postsynaptic to antennal vibration receptors. A2 cells receive excitatory synaptic currents in response to both directions of movement: thus, twice per vibration cycle. The membrane acts as a low-pass filter, so that voltage and spiking mainly track the vibration envelope rather than individual cycles. By contrast, B1 cells are excited by only forward or backward movement, meaning they are sensitive to vibration phase. They receive oscillatory synaptic currents at the stimulus frequency, and they bandpass filter these inputs to favor specific frequencies. Different cells prefer different frequencies, due to differences in their voltage-gated conductances. Both Na+ and K+ conductances suppress low-frequency synaptic inputs, so cells with larger voltage-gated conductances prefer higher frequencies. These results illustrate how membrane properties and voltage-gated conductances can extract distinct stimulus features into parallel channels.
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Affiliation(s)
- Anthony W Azevedo
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA.
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48
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Bengochea M, Berón de Astrada M, Tomsic D, Sztarker J. A crustacean lobula plate: Morphology, connections, and retinotopic organization. J Comp Neurol 2017; 526:109-119. [PMID: 28884472 DOI: 10.1002/cne.24322] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Revised: 08/25/2017] [Accepted: 08/28/2017] [Indexed: 02/03/2023]
Abstract
The lobula plate is part of the lobula complex, the third optic neuropil, in the optic lobes of insects. It has been extensively studied in dipterous insects, where its role in processing flow-field motion information used for controlling optomotor responses was discovered early. Recently, a lobula plate was also found in malacostracan crustaceans. Here, we provide the first detailed description of the neuroarchitecture, the input and output connections and the retinotopic organization of the lobula plate in a crustacean, the crab Neohelice granulata using a variety of histological methods that include silver reduced staining and mass staining with dextran-conjugated dyes. The lobula plate of this crab is a small elongated neuropil. It receives separated retinotopic inputs from columnar neurons of the medulla and the lobula. In the anteroposterior plane, the neuropil possesses four layers defined by the arborizations of such columnar inputs. Medulla projecting neurons arborize mainly in two of these layers, one on each side, while input neurons arriving from the lobula branch only in one. The neuropil contains at least two classes of tangential elements, one connecting with the lateral protocerebrum and the other that exits the optic lobes toward the supraesophageal ganglion. The number of layers in the crab's lobula plate, the retinotopic connections received from the medulla and from the lobula, and the presence of large tangential neurons exiting the neuropil, reflect the general structure of the insect lobula plate and, hence, provide support to the notion of an evolutionary conserved function for this neuropil.
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Affiliation(s)
- Mercedes Bengochea
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular. CONICET-Universidad de Buenos Aires, Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE), Buenos Aires, Argentina
| | - Martín Berón de Astrada
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular. CONICET-Universidad de Buenos Aires, Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE), Buenos Aires, Argentina
| | - Daniel Tomsic
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular. CONICET-Universidad de Buenos Aires, Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE), Buenos Aires, Argentina
| | - Julieta Sztarker
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular. CONICET-Universidad de Buenos Aires, Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE), Buenos Aires, Argentina
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49
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Haag J, Mishra A, Borst A. A common directional tuning mechanism of Drosophila motion-sensing neurons in the ON and in the OFF pathway. eLife 2017; 6:29044. [PMID: 28829040 PMCID: PMC5582866 DOI: 10.7554/elife.29044] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 08/21/2017] [Indexed: 01/19/2023] Open
Abstract
In the fruit fly optic lobe, T4 and T5 cells represent the first direction-selective neurons, with T4 cells responding selectively to moving brightness increments (ON) and T5 cells to brightness decrements (OFF). Both T4 and T5 cells comprise four subtypes with directional tuning to one of the four cardinal directions. We had previously found that upward-sensitive T4 cells implement both preferred direction enhancement and null direction suppression (Haag et al., 2016). Here, we asked whether this mechanism generalizes to OFF-selective T5 cells and to all four subtypes of both cell classes. We found that all four subtypes of both T4 and T5 cells implement both mechanisms, that is preferred direction enhancement and null direction inhibition, on opposing sides of their receptive fields. This gives rise to the high degree of direction selectivity observed in both T4 and T5 cells within each subpopulation.
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Affiliation(s)
- Juergen Haag
- Max-Planck-Institute of Neurobiology, Martinsried, Germany
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50
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Larderet I, Fritsch PM, Gendre N, Neagu-Maier GL, Fetter RD, Schneider-Mizell CM, Truman JW, Zlatic M, Cardona A, Sprecher SG. Organization of the Drosophila larval visual circuit. eLife 2017; 6:28387. [PMID: 30726702 PMCID: PMC5577918 DOI: 10.7554/elife.28387] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 08/07/2017] [Indexed: 11/20/2022] Open
Abstract
Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on photoreceptor neuron types (PR) present, organization of the eye and wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create two converging pathways potentially underlying the computation of ambient light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the larval optic neuropil (LON) suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors.
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Affiliation(s)
- Ivan Larderet
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | | | - Nanae Gendre
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | | | - Richard D Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | - James W Truman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Simon G Sprecher
- Department of Biology, University of Fribourg, Fribourg, Switzerland
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