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Rind FC. Recent advances in insect vision in a 3D world: looming stimuli and escape behaviour. CURRENT OPINION IN INSECT SCIENCE 2024; 63:101180. [PMID: 38432555 DOI: 10.1016/j.cois.2024.101180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/13/2024] [Accepted: 02/19/2024] [Indexed: 03/05/2024]
Abstract
Detecting looming motion directly towards the insect is vital to its survival. Looming detection in two insects, flies and locusts, is described and contrasted. Pathways using looming detectors to trigger action and their topographical layout in the brain is explored in relation to facilitating behavioural selection. Similar visual stimuli, such as looming motion, are processed by nearby glomeruli in the brain. Insect-inspired looming motion detectors are combined to detect and avoid collision in different scenarios by robots, vehicles and unmanned aerial vehicle (UAV)s.
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Affiliation(s)
- F Claire Rind
- Newcastle University Biosciences Institute (NUBI), UK.
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2
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Moreno-Sanchez A, Vasserman AN, Jang H, Hina BW, von Reyn CR, Ausborn J. Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.591016. [PMID: 38712267 PMCID: PMC11071487 DOI: 10.1101/2024.04.24.591016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Synapses are often precisely organized on dendritic arbors, yet the role of synaptic topography in dendritic integration remains poorly understood. Utilizing electron microscopy (EM) connectomics we investigate synaptic topography in Drosophila melanogaster looming circuits, focusing on retinotopically tuned visual projection neurons (VPNs) that synapse onto descending neurons (DNs). Synapses of a given VPN type project to non-overlapping regions on DN dendrites. Within these spatially constrained clusters, synapses are not retinotopically organized, but instead adopt near random distributions. To investigate how this organization strategy impacts DN integration, we developed multicompartment models of DNs fitted to experimental data and using precise EM morphologies and synapse locations. We find that DN dendrite morphologies normalize EPSP amplitudes of individual synaptic inputs and that near random distributions of synapses ensure linear encoding of synapse numbers from individual VPNs. These findings illuminate how synaptic topography influences dendritic integration and suggest that linear encoding of synapse numbers may be a default strategy established through connectivity and passive neuron properties, upon which active properties and plasticity can then tune as needed.
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Affiliation(s)
- Anthony Moreno-Sanchez
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
| | - Alexander N. Vasserman
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
| | - HyoJong Jang
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Bryce W. Hina
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Catherine R. von Reyn
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Jessica Ausborn
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, United States
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3
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Wu H, Yue S, Hu C. Re-framing bio-plausible collision detection: identifying shared meta-properties through strategic prototyping. Front Neurorobot 2024; 18:1349498. [PMID: 38333372 PMCID: PMC10850265 DOI: 10.3389/fnbot.2024.1349498] [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: 12/04/2023] [Accepted: 01/12/2024] [Indexed: 02/10/2024] Open
Abstract
Insects exhibit remarkable abilities in navigating complex natural environments, whether it be evading predators, capturing prey, or seeking out con-specifics, all of which rely on their compact yet reliable neural systems. We explore the field of bio-inspired robotic vision systems, focusing on the locust inspired Lobula Giant Movement Detector (LGMD) models. The existing LGMD models are thoroughly evaluated, identifying their common meta-properties that are essential for their functionality. This article reveals a common framework, characterized by layered structures and computational strategies, which is crucial for enhancing the capability of bio-inspired models for diverse applications. The result of this analysis is the Strategic Prototype, which embodies the identified meta-properties. It represents a modular and more flexible method for developing more responsive and adaptable robotic visual systems. The perspective highlights the potential of the Strategic Prototype: LGMD-Universally Prototype (LGMD-UP), the key to re-framing LGMD models and advancing our understanding and implementation of bio-inspired visual systems in robotics. It might open up more flexible and adaptable avenues for research and practical applications.
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Affiliation(s)
- Haotian Wu
- School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
| | - Shigang Yue
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
- School of Computing and Mathematical Sciences, University of Leicester, Leicester, United Kingdom
| | - Cheng Hu
- School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
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4
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Lei F, Peng Z, Liu M, Peng J, Cutsuridis V, Yue S. A Robust Visual System for Looming Cue Detection Against Translating Motion. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023; 34:8362-8376. [PMID: 35188895 DOI: 10.1109/tnnls.2022.3149832] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Collision detection is critical for autonomous vehicles or robots to serve human society safely. Detecting looming objects robustly and timely plays an important role in collision avoidance systems. The locust lobula giant movement detector (LGMD1) is specifically selective to looming objects which are on a direct collision course. However, the existing LGMD1 models cannot distinguish a looming object from a near and fast translatory moving object, because the latter can evoke a large amount of excitation that can lead to false LGMD1 spikes. This article presents a new visual neural system model (LGMD1) that applies a neural competition mechanism within a framework of separated ON and OFF pathways to shut off the translating response. The competition-based approach responds vigorously to monotonous ON/OFF responses resulting from a looming object. However, it does not respond to paired ON-OFF responses that result from a translating object, thereby enhancing collision selectivity. Moreover, a complementary denoising mechanism ensures reliable collision detection. To verify the effectiveness of the model, we have conducted systematic comparative experiments on synthetic and real datasets. The results show that our method exhibits more accurate discrimination between looming and translational events-the looming motion can be correctly detected. It also demonstrates that the proposed model is more robust than comparative models.
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Zheng Y, Wang Y, Wu G, Li H, Peng J. Enhancing LGMD-based model for collision prediction via binocular structure. Front Neurosci 2023; 17:1247227. [PMID: 37732308 PMCID: PMC10507862 DOI: 10.3389/fnins.2023.1247227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 08/21/2023] [Indexed: 09/22/2023] Open
Abstract
Introduction Lobular giant motion detector (LGMD) neurons, renowned for their distinctive response to looming stimuli, inspire the development of visual neural network models for collision prediction. However, the existing LGMD-based models could not yet incorporate the invaluable feature of depth distance and still suffer from the following two primary drawbacks. Firstly, they struggle to effectively distinguish the three fundamental motion patterns of approaching, receding, and translating, in contrast to the natural abilities of LGMD neurons. Secondly, due to their reliance on a general determination process employing an activation function and fixed threshold for output, these models exhibit dramatic fluctuations in prediction effectiveness across different scenarios. Methods To address these issues, we propose a novel LGMD-based model with a binocular structure (Bi-LGMD). The depth distance of the moving object is extracted by calculating the binocular disparity facilitating a clear differentiation of the motion patterns, after obtaining the moving object's contour through the basic components of the LGMD network. In addition, we introduce a self-adaptive warning depth-distance, enhancing the model's robustness in various motion scenarios. Results The effectiveness of the proposed model is verified using computer-simulated and real-world videos. Discussion Furthermore, the experimental results demonstrate that the proposed model is robust to contrast and noise.
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Affiliation(s)
- Yi Zheng
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
| | - Yusi Wang
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
| | - Guangrong Wu
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
| | - Haiyang Li
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
| | - Jigen Peng
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
- Machine Life and Intelligence Research Center, Guangzhou University, Guangzhou, China
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Wu Q, Zhang Y. Neural Circuit Mechanisms Involved in Animals' Detection of and Response to Visual Threats. Neurosci Bull 2023; 39:994-1008. [PMID: 36694085 PMCID: PMC10264346 DOI: 10.1007/s12264-023-01021-0] [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: 08/28/2022] [Accepted: 10/30/2022] [Indexed: 01/26/2023] Open
Abstract
Evading or escaping from predators is one of the most crucial issues for survival across the animal kingdom. The timely detection of predators and the initiation of appropriate fight-or-flight responses are innate capabilities of the nervous system. Here we review recent progress in our understanding of innate visually-triggered defensive behaviors and the underlying neural circuit mechanisms, and a comparison among vinegar flies, zebrafish, and mice is included. This overview covers the anatomical and functional aspects of the neural circuits involved in this process, including visual threat processing and identification, the selection of appropriate behavioral responses, and the initiation of these innate defensive behaviors. The emphasis of this review is on the early stages of this pathway, namely, threat identification from complex visual inputs and how behavioral choices are influenced by differences in visual threats. We also briefly cover how the innate defensive response is processed centrally. Based on these summaries, we discuss coding strategies for visual threats and propose a common prototypical pathway for rapid innate defensive responses.
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Affiliation(s)
- Qiwen Wu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yifeng Zhang
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
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Zhao J, Wang H, Bellotto N, Hu C, Peng J, Yue S. Enhancing LGMD's Looming Selectivity for UAV With Spatial-Temporal Distributed Presynaptic Connections. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023; 34:2539-2553. [PMID: 34495845 DOI: 10.1109/tnnls.2021.3106946] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Collision detection is one of the most challenging tasks for unmanned aerial vehicles (UAVs). This is especially true for small or micro-UAVs due to their limited computational power. In nature, flying insects with compact and simple visual systems demonstrate their remarkable ability to navigate and avoid collision in complex environments. A good example of this is provided by locusts. They can avoid collisions in a dense swarm through the activity of a motion-based visual neuron called the Lobula giant movement detector (LGMD). The defining feature of the LGMD neuron is its preference for looming. As a flying insect's visual neuron, LGMD is considered to be an ideal basis for building UAV's collision detecting system. However, existing LGMD models cannot distinguish looming clearly from other visual cues, such as complex background movements caused by UAV agile flights. To address this issue, we proposed a new model implementing distributed spatial-temporal synaptic interactions, which is inspired by recent findings in locusts' synaptic morphology. We first introduced the locally distributed excitation to enhance the excitation caused by visual motion with preferred velocities. Then, radially extending temporal latency for inhibition is incorporated to compete with the distributed excitation and selectively suppress the nonpreferred visual motions. This spatial-temporal competition between excitation and inhibition in our model is, therefore, tuned to preferred image angular velocity representing looming rather than background movements with these distributed synaptic interactions. Systematic experiments have been conducted to verify the performance of the proposed model for UAV agile flights. The results have demonstrated that this new model enhances the looming selectivity in complex flying scenes considerably and has the potential to be implemented on embedded collision detection systems for small or micro-UAVs.
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Dewell RB, Zhu Y, Eisenbrandt M, Morse R, Gabbiani F. Contrast polarity-specific mapping improves efficiency of neuronal computation for collision detection. eLife 2022; 11:e79772. [PMID: 36314775 PMCID: PMC9674337 DOI: 10.7554/elife.79772] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 10/27/2022] [Indexed: 11/29/2022] Open
Abstract
Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cell's dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. The lack of retinotopic synaptic arrangement results in the neuron's inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animal's escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.
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Affiliation(s)
| | - Ying Zhu
- Department of Neuroscience, Baylor College of MedicineHoustonUnited States
| | | | | | - Fabrizio Gabbiani
- Department of Neuroscience, Baylor College of MedicineHoustonUnited States
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Wernitznig S, Rind FC, Zankel A, Bock E, Gütl D, Hobusch U, Nikolic M, Pargger L, Pritz E, Radulović S, Sele M, Summerauer S, Pölt P, Leitinger G. The complex synaptic pathways onto a looming-detector neuron revealed using serial block-face scanning electron microscopy. J Comp Neurol 2021; 530:518-536. [PMID: 34338325 DOI: 10.1002/cne.25227] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 07/09/2021] [Accepted: 07/13/2021] [Indexed: 11/09/2022]
Abstract
The ability of locusts to detect looming stimuli and avoid collisions or predators depends on a neuronal circuit in the locust's optic lobe. Although comprehensively studied for over three decades, there are still major questions about the computational steps of this circuit. We used fourth instar larvae of Locusta migratoria to describe the connection between the lobula giant movement detector 1 (LGMD1) neuron in the lobula complex and the upstream neuropil, the medulla. Serial block-face scanning electron microscopy (SBEM) was used to characterize the morphology of the connecting neurons termed trans-medullary afferent (TmA) neurons and their synaptic connectivity. This enabled us to trace neurons over several hundred micrometers between the medulla and the lobula complex while identifying their synapses. We traced two different TmA neurons, each from a different individual, from their synapses with the LGMD in the lobula complex up into the medulla and describe their synaptic relationships. There is not a simple downstream transmission of the signal from a lamina neuron onto these TmA neurons; there is also a feedback loop in place with TmA neurons making outputs as well as receiving inputs. More than one type of neuron shapes the signal of the TmA neurons in the medulla. We found both columnar and trans-columnar neurons connected with the traced TmA neurons in the medulla. These findings indicate that there are computational steps in the medulla that have not been included in models of the neuronal pathway for looming detection.
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Affiliation(s)
- Stefan Wernitznig
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - F Claire Rind
- Newcastle University, Biosciences Institute, Newcastle upon Tyne, UK
| | - Armin Zankel
- Institute of Electron Microscopy and Nanoanalysis, NAWI Graz, Graz University of Technology, Graz, Austria.,Centre for Electron Microscopy, Graz, Austria
| | - Elisabeth Bock
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Daniel Gütl
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Ulrich Hobusch
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Manuela Nikolic
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Lukas Pargger
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Elisabeth Pritz
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Snježana Radulović
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Mariella Sele
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Susanne Summerauer
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Peter Pölt
- Institute of Electron Microscopy and Nanoanalysis, NAWI Graz, Graz University of Technology, Graz, Austria.,Centre for Electron Microscopy, Graz, Austria
| | - Gerd Leitinger
- Research Unit Electron Microscopic Techniques, Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria.,BioTechMed Graz, Graz, Austria
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Olson EGN, Wiens TK, Gray JR. A model of feedforward, global, and lateral inhibition in the locust visual system predicts responses to looming stimuli. BIOLOGICAL CYBERNETICS 2021; 115:245-265. [PMID: 33997912 DOI: 10.1007/s00422-021-00876-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Accepted: 04/27/2021] [Indexed: 06/12/2023]
Abstract
Detection of looming obstacles is a vital task for both natural and artificial systems. Locusts possess a visual nervous system with an extensively studied obstacle detection pathway, culminating in the lobula giant movement detector (LGMD) neuron. While numerous models of this system exist, none to date have incorporated recent data on the anatomy and function of feedforward and global inhibitory systems in the input network of the LGMD. Moreover, the possibility that global and lateral inhibition shape the feedforward inhibitory signals to the LGMD has not been investigated. To address these points, a novel model of feedforward inhibitory neurons in the locust optic lobe was developed based on the recent literature. This model also incorporated global and lateral inhibition into the afferent network of these neurons, based on their observed behaviour in existing data and the posited role of these mechanisms in the inputs to the LGMD. Tests with the model showed that it accurately replicates the behaviour of feedforward inhibitory neurons in locusts; the model accurately coded for stimulus angular size in an overall linear fashion, with decreasing response saturation and increasing linearity as stimulus size increased or approach velocity decreased. The model also exhibited only phasic responses to the appearance of a grating, along with sustained movement by it at constant speed. By observing the effects of altering inhibition schemes on these responses, it was determined that global inhibition serves primarily to normalize growing excitation as collision approaches, and keeps coding for subtense angle linear. Lateral inhibition was determined to suppress tonic responses to wide-field stimuli translating at constant speed. Based on these features being shared with characterizations of the LGMD input network, it was hypothesized that the feedforward inhibitory neurons and the LGMD share the same excitatory afferents; this necessitates further investigation.
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Affiliation(s)
- Erik G N Olson
- University of Saskatchewan, 112 Science Pl, Saskatoon, SK, S7N 5C8, Canada.
| | - Travis K Wiens
- University of Saskatchewan, 57 Campus Dr, Saskatoon, SK, S7N 5A9, Canada
| | - John R Gray
- University of Saskatchewan, 112 Science Pl, Saskatoon, SK, S7N 5C8, Canada
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11
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Study on Collision Detection and Force Feedback Algorithm in Virtual Surgery. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:6611196. [PMID: 33628402 PMCID: PMC7889397 DOI: 10.1155/2021/6611196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/18/2021] [Accepted: 01/29/2021] [Indexed: 11/22/2022]
Abstract
The development of virtual reality technology is expected to solve traditional surgical training. The lack of methods has brought revolutionary advances in technology. The virtual surgery system based on collision detection and force feedback can enable the operator to have stronger interaction, which is an exploration of the feature of touch in virtual reality technology. Reality is an important indicator of the virtual surgical system. This article improves the realism of the system from the visual and tactile senses and uses the surrounding ball collision detection and force feedback algorithms to build a realistic surgical platform. In the virtual surgery training system, the introduction of force feedback greatly improves the sense of presence during virtual surgery interaction. The operator can feel the softness and hardness of different tissues and organs through the force feedback device. Virtual reality is an interdisciplinary comprehensive technology that has been widely used in military, film, medical, and gaming fields. Virtual reality can simulate the objective world and display it visually, making people feel immersive. Virtual surgery provides surgeons with a recyclable surgical practice platform and can help doctors perform preoperative rehearsals and predict the results of surgery. The design of collision detection and force feedback algorithms is a prerequisite to ensure the immersion and transparency of the virtual surgical training system. This article mainly introduces the collision detection and force feedback algorithm research in virtual surgery, with the intention of providing some ideas and directions for the development of virtual surgery. This paper proposes two collision detection algorithms, space decomposition method and hierarchical bounding box method, and three force feedback algorithms including spring mass point algorithm, Runge–Kutta method, and Euler method to construct virtual surgery collision detection and force feedback. Experiment with the Overall System Architecture. This paper proves through experimental results that the average collision detection time after the application of the improved collision detection and force feedback algorithm in the virtual surgery system is more than 80.7% less than the traditional method, which greatly improves the detection speed.
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12
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Neonicotinoid and sulfoximine pesticides differentially impair insect escape behavior and motion detection. Proc Natl Acad Sci U S A 2020; 117:5510-5515. [PMID: 32094166 PMCID: PMC7071913 DOI: 10.1073/pnas.1916432117] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Novel insecticides are developed and implemented in agriculture without a broad understanding of their sublethal effects. Although all act via nicotinic acetylcholine receptors, neonicotinoids and the novel sulfoxaflor insecticide exhibit differences in relative toxicity. In this study comparing the effects of these insecticides on visual motion detection and escape behavior, we show that sulfoxaflor displays decreased sublethal toxicity despite similar lethal endpoints of these insecticides. Imidacloprid reduces putative neural population code variability when responding to approaching objects, suggesting that neonics may constrain the tuning of visual sensory circuits. We suggest that neuroethologic methods are powerful tools to link toxic effects across levels of biological organization and further our understanding of how neural populations operate in complex sensory environments. Insect nervous systems offer unique advantages for studying interactions between sensory systems and behavior, given their complexity with high tractability. By examining the neural coding of salient environmental stimuli and resulting behavioral output in the context of environmental stressors, we gain an understanding of the effects of these stressors on brain and behavior and provide insight into normal function. The implication of neonicotinoid (neonic) pesticides in contributing to declines of nontarget species, such as bees, has motivated the development of new compounds that can potentially mitigate putative resistance in target species and declines of nontarget species. We used a neuroethologic approach, including behavioral assays and multineuronal recording techniques, to investigate effects of imidacloprid (IMD) and the novel insecticide sulfoxaflor (SFX) on visual motion-detection circuits and related escape behavior in the tractable locust system. Despite similar LD50 values, IMD and SFX evoked different behavioral and physiological effects. IMD significantly attenuated collision avoidance behaviors and impaired responses of neural populations, including decreases in spontaneous firing and neural habituation. In contrast, SFX displayed no effect at a comparable sublethal dose. These results show that neonics affect population responses and habituation of a visual motion detection system. We propose that differences in the sublethal effects of SFX reflect a different mode of action than that of IMD. More broadly, we suggest that neuroethologic assays for comparative neurotoxicology are valuable tools for fully addressing current issues regarding the proximal effects of environmental toxicity in nontarget species.
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13
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Parkinson RH, Gray JR. Neural conduction, visual motion detection, and insect flight behaviour are disrupted by low doses of imidacloprid and its metabolites. Neurotoxicology 2019; 72:107-113. [PMID: 30790592 DOI: 10.1016/j.neuro.2019.02.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 01/14/2019] [Accepted: 02/16/2019] [Indexed: 01/06/2023]
Abstract
While neonicotinoid insecticides impair visually guided behaviours, the effects of their metabolites are unknown and measurements of environmental concentrations of neonicotinoids, typically lower than those required to elicit toxic effects, tend to exclude metabolites. Here we examined the contributions of imidacloprid and two of its metabolites, imidacloprid-olefin and 5-hydroxy-imidacloprid, on neural conduction velocity, visual motion detection and flight in the locust (Locusta migratoria) using a combination of electrophysiological and behavioural assays. We show reduced visual motion detection and impaired flight behaviour following treatment of metabolite concentrations equal to sublethal doses of the parent compound. Additionally, we show for the first time that imidacloprid and its metabolites result in a decrease in conduction velocity along an unmyelinated axon. We suggest that secondary effects of the insecticide on the biophysical properties of the axon may result in decreased neural conduction. As these metabolites display neurotoxicity similar to the parent compound they should be considered when quantifying environmental concentrations.
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Affiliation(s)
| | - John R Gray
- Department of Biology, University of Saskatchewan, Canada.
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14
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Stott TP, Olson EGN, Parkinson RH, Gray JR. Three-dimensional shape and velocity changes affect responses of a locust visual interneuron to approaching objects. ACTA ACUST UNITED AC 2018; 221:jeb.191320. [PMID: 30341087 DOI: 10.1242/jeb.191320] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2018] [Accepted: 10/12/2018] [Indexed: 11/20/2022]
Abstract
Adaptive collision avoidance behaviours require accurate detection of complex spatiotemporal properties of an object approaching in an animal's natural, three-dimensional environment. Within the locust, the lobula giant movement detector and its postsynaptic partner, the descending contralateral movement detector (DCMD), respond robustly to images that emulate an approaching two-dimensional object and exhibit firing rate modulation correlated with changes in object trajectory. It is not known how this pathway responds to visual expansion of a three-dimensional object or an approaching object that changes velocity, both of which represent natural stimuli. We compared DCMD responses with images that emulate the approach of a sphere with those elicited by a two-dimensional disc. A sphere evoked later peak firing and decreased sensitivity to the ratio of the half size of the object to the approach velocity, resulting in an increased threshold subtense angle required to generate peak firing. We also presented locusts with an approaching sphere that decreased or increased in velocity. A velocity decrease resulted in transition-associated peak firing followed by a firing rate increase that resembled the response to a constant, slower velocity. A velocity increase resulted in an earlier increase in the firing rate that was more pronounced with an earlier transition. These results further demonstrate that this pathway can provide motor circuits for behaviour with salient information about complex stimulus dynamics.
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Affiliation(s)
- Tarquin P Stott
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5E2
| | - Erik G N Olson
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5E2
| | - Rachel H Parkinson
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5E2
| | - John R Gray
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5E2
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15
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Wang H, Dewell RB, Ehrengruber MU, Segev E, Reimer J, Roukes ML, Gabbiani F. Optogenetic manipulation of medullary neurons in the locust optic lobe. J Neurophysiol 2018; 120:2049-2058. [PMID: 30110231 PMCID: PMC6230808 DOI: 10.1152/jn.00356.2018] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 08/09/2018] [Accepted: 08/09/2018] [Indexed: 11/22/2022] Open
Abstract
The locust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts ( Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered excitatory postsynaptic potentials and firing of a postsynaptic, looming-sensitive neuron, the lobula giant movement detector. These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects. NEW & NOTEWORTHY Using Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and elicits excitatory postsynaptic potentials and spiking in an identified postsynaptic target neuron, the lobula giant movement detector neuron. This technique allows the manipulation of neuronal activity in locust neural circuits using optogenetics.
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Affiliation(s)
- Hongxia Wang
- Department of Neuroscience, Baylor College of Medicine , Houston, Texas
| | - Richard B Dewell
- Department of Neuroscience, Baylor College of Medicine , Houston, Texas
| | | | - Eran Segev
- Department of Applied Physics and Material Science, California Institute of Technology , Pasadena, California
| | - Jacob Reimer
- Department of Neuroscience, Baylor College of Medicine , Houston, Texas
| | - Michael L Roukes
- Department of Applied Physics and Material Science, California Institute of Technology , Pasadena, California
| | - Fabrizio Gabbiani
- Department of Neuroscience, Baylor College of Medicine , Houston, Texas
- Electrical and Computer Engineering Department, Rice University , Houston, Texas
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16
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Dewell RB, Gabbiani F. M current regulates firing mode and spike reliability in a collision-detecting neuron. J Neurophysiol 2018; 120:1753-1764. [PMID: 30044671 DOI: 10.1152/jn.00363.2018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
All animals must detect impending collisions to escape and reliably discriminate them from nonthreatening stimuli, thus preventing false alarms. Therefore, it is no surprise that animals have evolved highly selective and sensitive neurons dedicated to such tasks. We examined a well-studied collision-detection neuron in the grasshopper ( Schistocerca americana) using in vivo electrophysiology, pharmacology, and computational modeling. This lobula giant movement detector (LGMD) neuron is excitable by inputs originating from each ommatidia of the compound eye. It possesses many intrinsic properties that increase its selectivity to objects approaching on a collision course, including switching between burst and nonburst firing. In this study, we demonstrate that the LGMD neuron exhibits a large M current, generated by noninactivating K+ channels, that shortens the temporal window of dendritic integration, regulates a firing mode switch between burst and isolated spiking, increases the precision of spike timing, and increases the reliability of spike propagation to downstream motor centers. By revealing how the M current increases the LGMD's ability to detect impending collisions, our results suggest that similar channels may play an analogous role in other collision detection circuits. NEW & NOTEWORTHY The ability to reliably detect impending collisions is a critical survival skill. The nervous systems of many animals have developed dedicated neurons for accomplishing this task. We used a mix of in vivo electrophysiology and computational modeling to investigate the role of M potassium channels within one such collision-detecting neuron and show that through regulation of burst firing and enhancement of spiking reliability, the M current increases the ability to detect impending collisions.
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Affiliation(s)
- Richard B Dewell
- Department of Neuroscience, Baylor College of Medicine , Houston, Texas
| | - Fabrizio Gabbiani
- Department of Neuroscience, Baylor College of Medicine , Houston, Texas.,Department of Electrical and Computer Engineering, Rice University , Houston, Texas
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17
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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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