1
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Asinof SK, Card GM. Neural Control of Naturalistic Behavior Choices. Annu Rev Neurosci 2024; 47:369-388. [PMID: 38724026 DOI: 10.1146/annurev-neuro-111020-094019] [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] [Indexed: 08/09/2024]
Abstract
In the natural world, animals make decisions on an ongoing basis, continuously selecting which action to undertake next. In the lab, however, the neural bases of decision processes have mostly been studied using artificial trial structures. New experimental tools based on the genetic toolkit of model organisms now make it experimentally feasible to monitor and manipulate neural activity in small subsets of neurons during naturalistic behaviors. We thus propose a new approach to investigating decision processes, termed reverse neuroethology. In this approach, experimenters select animal models based on experimental accessibility and then utilize cutting-edge tools such as connectomes and genetically encoded reagents to analyze the flow of information through an animal's nervous system during naturalistic choice behaviors. We describe how the reverse neuroethology strategy has been applied to understand the neural underpinnings of innate, rapid decision making, with a focus on defensive behavioral choices in the vinegar fly Drosophila melanogaster.
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Affiliation(s)
- Samuel K Asinof
- Laboratory of Molecular Biology, National Institute of Mental Health, Bethesda, Maryland, USA
- Janelia Research Campus, Ashburn, Virginia, USA
| | - Gwyneth M Card
- Howard Hughes Medical Institute, Department of Neuroscience, and Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA;
- Janelia Research Campus, Ashburn, Virginia, USA
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2
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Stürner T, Brooks P, Capdevila LS, Morris BJ, Javier A, Fang S, Gkantia M, Cachero S, Beckett IR, Champion AS, Moitra I, Richards A, Klemm F, Kugel L, Namiki S, Cheong HS, Kovalyak J, Tenshaw E, Parekh R, Schlegel P, Phelps JS, Mark B, Dorkenwald S, Bates AS, Matsliah A, Yu SC, McKellar CE, Sterling A, Seung S, Murthy M, Tuthill J, Lee WCA, Card GM, Costa M, Jefferis GS, Eichler K. Comparative connectomics of the descending and ascending neurons of the Drosophila nervous system: stereotypy and sexual dimorphism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.04.596633. [PMID: 38895426 PMCID: PMC11185702 DOI: 10.1101/2024.06.04.596633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and information bottleneck connecting the brain and the ventral nerve cord (VNC, spinal cord analogue) and comprises diverse populations of descending (DN), ascending (AN) and sensory ascending neurons, which are crucial for sensorimotor signalling and control. Integrating three separate EM datasets, we now provide a complete connectomic description of the ascending and descending neurons of the female nervous system of Drosophila and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions have been matched across hemispheres, datasets and sexes. Crucially, we have also matched 51% of DN cell types to light level data defining specific driver lines as well as classifying all ascending populations. We use these results to reveal the general architecture, tracts, neuropil innervation and connectivity of neck connective neurons. We observe connected chains of descending and ascending neurons spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analysis of circuits implicated in sex-related behaviours, including female ovipositor extrusion (DNp13), male courtship (DNa12/aSP22) and song production (AN hemilineage 08B). Our work represents the first EM-level circuit analyses spanning the entire central nervous system of an adult animal.
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Affiliation(s)
- Tomke Stürner
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Paul Brooks
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | | | - Billy J. Morris
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Alexandre Javier
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Siqi Fang
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Marina Gkantia
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Sebastian Cachero
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | - Andrew S. Champion
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Ilina Moitra
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Alana Richards
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Finja Klemm
- Genetics Department, Leipzig University, Leipzig, Germany
| | - Leonie Kugel
- Genetics Department, Leipzig University, Leipzig, Germany
| | - Shigehiro Namiki
- Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan
| | - Han S.J. Cheong
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
- Zuckerman Institute, Columbia University, New York, United States
| | - Julie Kovalyak
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Emily Tenshaw
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Ruchi Parekh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Jasper S. Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
- Brain Mind Institute & Institute of Bioengineering, EPFL, 1015 Lausanne, Switzerland
| | - Brandon Mark
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, USA
| | - Alexander S. Bates
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
- Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK
| | - Arie Matsliah
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Szi-chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Amy Sterling
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, USA
| | - Mala Murthy
- Computer Science Department, Princeton University, USA
| | - John Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Wei-Chung A. Lee
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA
- FM Kirby Neurobiology Center, Boston Children’s Hospital, Boston, MA, USA
| | - Gwyneth M. Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
- Zuckerman Institute, Columbia University, New York, United States
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Gregory S.X.E. Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Katharina Eichler
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- Genetics Department, Leipzig University, Leipzig, Germany
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3
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Braun J, Hurtak F, Wang-Chen S, Ramdya P. Descending networks transform command signals into population motor control. Nature 2024; 630:686-694. [PMID: 38839968 PMCID: PMC11186778 DOI: 10.1038/s41586-024-07523-9] [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: 09/11/2023] [Accepted: 05/06/2024] [Indexed: 06/07/2024]
Abstract
To convert intentions into actions, movement instructions must pass from the brain to downstream motor circuits through descending neurons (DNs). These include small sets of command-like neurons that are sufficient to drive behaviours1-the circuit mechanisms for which remain unclear. Here we show that command-like DNs in Drosophila directly recruit networks of additional DNs to orchestrate behaviours that require the active control of numerous body parts. Specifically, we found that command-like DNs previously thought to drive behaviours alone2-4 in fact co-activate larger populations of DNs. Connectome analyses and experimental manipulations revealed that this functional recruitment can be explained by direct excitatory connections between command-like DNs and networks of interconnected DNs in the brain. Descending population recruitment is necessary for behavioural control: DNs with many downstream descending partners require network co-activation to drive complete behaviours and drive only simple stereotyped movements in their absence. These DN networks reside within behaviour-specific clusters that inhibit one another. These results support a mechanism for command-like descending control in which behaviours are generated through the recruitment of increasingly large DN networks that compose behaviours by combining multiple motor subroutines.
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Affiliation(s)
- Jonas Braun
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Femke Hurtak
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Sibo Wang-Chen
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Pavan Ramdya
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland.
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4
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Schretter CE, Sten TH, Klapoetke N, Shao M, Nern A, Dreher M, Bushey D, Robie AA, Taylor AL, Branson KM, Otopalik A, Ruta V, Rubin GM. Social state gates vision using three circuit mechanisms in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585289. [PMID: 38559111 PMCID: PMC10979952 DOI: 10.1101/2024.03.15.585289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Animals are often bombarded with visual information and must prioritize specific visual features based on their current needs. The neuronal circuits that detect and relay visual features have been well-studied. Yet, much less is known about how an animal adjusts its visual attention as its goals or environmental conditions change. During social behaviors, flies need to focus on nearby flies. Here, we study how the flow of visual information is altered when female Drosophila enter an aggressive state. From the connectome, we identified three state-dependent circuit motifs poised to selectively amplify the response of an aggressive female to fly-sized visual objects: convergence of excitatory inputs from neurons conveying select visual features and internal state; dendritic disinhibition of select visual feature detectors; and a switch that toggles between two visual feature detectors. Using cell-type-specific genetic tools, together with behavioral and neurophysiological analyses, we show that each of these circuit motifs function during female aggression. We reveal that features of this same switch operate in males during courtship pursuit, suggesting that disparate social behaviors may share circuit mechanisms. Our work provides a compelling example of using the connectome to infer circuit mechanisms that underlie dynamic processing of sensory signals.
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Affiliation(s)
| | - Tom Hindmarsh Sten
- Laboratory of Neurophysiology and Behavior, The Rockefeller University, New York, NY, USA
| | - Nathan Klapoetke
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Mei Shao
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Marisa Dreher
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Daniel Bushey
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Alice A Robie
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Adam L Taylor
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Kristin M Branson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Adriane Otopalik
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Vanessa Ruta
- Laboratory of Neurophysiology and Behavior, The Rockefeller University, New York, NY, USA
| | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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5
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Cheong HSJ, Boone KN, Bennett MM, Salman F, Ralston JD, Hatch K, Allen RF, Phelps AM, Cook AP, Phelps JS, Erginkaya M, Lee WCA, Card GM, Daly KC, Dacks AM. Organization of an ascending circuit that conveys flight motor state in Drosophila. Curr Biol 2024; 34:1059-1075.e5. [PMID: 38402616 PMCID: PMC10939832 DOI: 10.1016/j.cub.2024.01.071] [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: 06/08/2023] [Revised: 12/08/2023] [Accepted: 01/29/2024] [Indexed: 02/27/2024]
Abstract
Natural behaviors are a coordinated symphony of motor acts that drive reafferent (self-induced) sensory activation. Individual sensors cannot disambiguate exafferent (externally induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to carry out adaptive behaviors through corollary discharge circuits (CDCs), which provide predictive motor signals from motor pathways to sensory processing and other motor pathways. Yet, how CDCs comprehensively integrate into the nervous system remains unexplored. Here, we use connectomics, neuroanatomical, physiological, and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs) in Drosophila, which function as a predictive CDC in other insects. Both AHN pairs receive input primarily from a partially overlapping population of descending neurons, especially from DNg02, which controls wing motor output. Using Ca2+ imaging and behavioral recordings, we show that AHN activation is correlated to flight behavior and precedes wing motion. Optogenetic activation of DNg02 is sufficient to activate AHNs, indicating that AHNs are activated by descending commands in advance of behavior and not as a consequence of sensory input. Downstream, each AHN pair targets predominantly non-overlapping networks, including those that process visual, auditory, and mechanosensory information, as well as networks controlling wing, haltere, and leg sensorimotor control. These results support the conclusion that the AHNs provide a predictive motor signal about wing motor state to mostly non-overlapping sensory and motor networks. Future work will determine how AHN signaling is driven by other descending neurons and interpreted by AHN downstream targets to maintain adaptive sensorimotor performance.
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Affiliation(s)
- Han S J Cheong
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Zuckerman Institute, Columbia University, New York, NY 10027, USA
| | - Kaitlyn N Boone
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Marryn M Bennett
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Farzaan Salman
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Jacob D Ralston
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Kaleb Hatch
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Raven F Allen
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Alec M Phelps
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Andrew P Cook
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA
| | - Jasper S Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, USA; Swiss Federal Institute of Technology Lausanne, 1015 Lausanne, Switzerland
| | - Mert Erginkaya
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon 1400-038, Portugal
| | - Wei-Chung A Lee
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Zuckerman Institute, Columbia University, New York, NY 10027, USA
| | - Kevin C Daly
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Department of Neuroscience, West Virginia University, Morgantown, WV 26505, USA
| | - Andrew M Dacks
- Department of Biology, West Virginia University, Morgantown, WV 26505, USA; Department of Neuroscience, West Virginia University, Morgantown, WV 26505, USA.
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6
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Wagner H, Egelhaaf M, Carr C. Model organisms and systems in neuroethology: one hundred years of history and a look into the future. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2024; 210:227-242. [PMID: 38227005 PMCID: PMC10995084 DOI: 10.1007/s00359-023-01685-z] [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: 09/12/2023] [Revised: 11/27/2023] [Accepted: 11/29/2023] [Indexed: 01/17/2024]
Abstract
The Journal of Comparative Physiology lived up to its name in the last 100 years by including more than 1500 different taxa in almost 10,000 publications. Seventeen phyla of the animal kingdom were represented. The honeybee (Apis mellifera) is the taxon with most publications, followed by locust (Locusta migratoria), crayfishes (Cambarus spp.), and fruitfly (Drosophila melanogaster). The representation of species in this journal in the past, thus, differs much from the 13 model systems as named by the National Institutes of Health (USA). We mention major accomplishments of research on species with specific adaptations, specialist animals, for example, the quantitative description of the processes underlying the axon potential in squid (Loligo forbesii) and the isolation of the first receptor channel in the electric eel (Electrophorus electricus) and electric ray (Torpedo spp.). Future neuroethological work should make the recent genetic and technological developments available for specialist animals. There are many research questions left that may be answered with high yield in specialists and some questions that can only be answered in specialists. Moreover, the adaptations of animals that occupy specific ecological niches often lend themselves to biomimetic applications. We go into some depth in explaining our thoughts in the research of motion vision in insects, sound localization in barn owls, and electroreception in weakly electric fish.
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Affiliation(s)
- Hermann Wagner
- Institute of Biology II, RWTH Aachen University, 52074, Aachen, Germany.
| | - Martin Egelhaaf
- Department of Neurobiology, Bielefeld University, Bielefeld, Germany
| | - Catherine Carr
- Department of Biology, University of Maryland at College Park, College Park, USA
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7
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Ros IG, Omoto JJ, Dickinson MH. Descending control and regulation of spontaneous flight turns in Drosophila. Curr Biol 2024; 34:531-540.e5. [PMID: 38228148 PMCID: PMC10872223 DOI: 10.1016/j.cub.2023.12.047] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/12/2023] [Accepted: 12/14/2023] [Indexed: 01/18/2024]
Abstract
The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of locomotion, selecting for a common search motif in which straight movements through resource-poor regions alternate with zig-zag exploration in resource-rich domains. For example, during local search, flying flies spontaneously execute rapid flight turns, called body saccades, but suppress these maneuvers during long-distance dispersal or when surging upstream toward an attractive odor. Here, we describe the key cellular components of a neural network in flies that generate spontaneous turns as well as a specialized pair of neurons that inhibits the network and suppresses turning. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional units-one for right turns and one for left-with each unit consisting of an excitatory (DNae014) and an inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly, we identified a pair of large, distinct interneurons (VES041) that form inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As predicted by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it promotes straight flight to regulate the transition between local search and long-distance dispersal. These results thus identify the key elements of a network that may play a crucial role in foraging ecology.
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Affiliation(s)
- Ivo G Ros
- Division of Biology and Bioengineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA
| | - Jaison J Omoto
- Division of Biology and Bioengineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA
| | - Michael H Dickinson
- Division of Biology and Bioengineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA.
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8
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Simpson JH. Descending control of motor sequences in Drosophila. Curr Opin Neurobiol 2024; 84:102822. [PMID: 38096757 PMCID: PMC11215313 DOI: 10.1016/j.conb.2023.102822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 11/22/2023] [Accepted: 11/22/2023] [Indexed: 02/18/2024]
Abstract
The descending neurons connecting the fly's brain to its ventral nerve cord respond to sensory stimuli and evoke motor programs of varying complexity. Anatomical characterization of the descending neurons and their synaptic connections suggests how these circuits organize movements, while optogenetic manipulation of their activity reveals what behaviors they can induce. Monitoring their responses to sensory stimuli or during behavior performance indicates what information they may encode. Recent advances in all three approaches make the descending neurons an excellent place to better understand the sensorimotor integration and transformation required for nervous systems to govern the motor sequences that constitute animal behavior.
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Affiliation(s)
- Julie H Simpson
- Dept. Molecular Cellular and Developmental Biology and Neuroscience Research Institute, University of California Santa Barbara, USA.
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9
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Büschges A, Gorostiza EA. Neurons with names: Descending control and sensorimotor processing in insect motor control. Curr Opin Neurobiol 2023; 83:102766. [PMID: 37865029 DOI: 10.1016/j.conb.2023.102766] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 07/24/2023] [Accepted: 07/24/2023] [Indexed: 10/23/2023]
Abstract
Technical and methodological advances in recent years have brought new ways to tackle major classical questions in insect motor control. Particularly, significant advancements were achieved in comprehending brain descending control by characterizing descending neurons, their targets in the ventral nerve cord (VNC), and how local networks there integrate sensory information. While physiological experiments in larger insects brought us a better understanding of how sensory modalities are processed locally in the VNC, the development and improvement of genetic tools, principally in Drosophila, opened the door to individually characterize actors at these three levels of information flow in behavioral control. This brief review brings together the names and roles of some of those actors, by highlighting the most significant findings from our perspective.
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Affiliation(s)
- Ansgar Büschges
- Institute of Zoology, Biocenter Cologne, University of Cologne, Zülpicher Straße 47b, 50674 Cologne, Germany.
| | - E Axel Gorostiza
- Institute of Zoology, Biocenter Cologne, University of Cologne, Zülpicher Straße 47b, 50674 Cologne, Germany
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10
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Longden KD, Rogers EM, Nern A, Dionne H, Reiser MB. Different spectral sensitivities of ON- and OFF-motion pathways enhance the detection of approaching color objects in Drosophila. Nat Commun 2023; 14:7693. [PMID: 38001097 PMCID: PMC10673857 DOI: 10.1038/s41467-023-43566-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
Color and motion are used by many species to identify salient objects. They are processed largely independently, but color contributes to motion processing in humans, for example, enabling moving colored objects to be detected when their luminance matches the background. Here, we demonstrate an unexpected, additional contribution of color to motion vision in Drosophila. We show that behavioral ON-motion responses are more sensitive to UV than for OFF-motion, and we identify cellular pathways connecting UV-sensitive R7 photoreceptors to ON and OFF-motion-sensitive T4 and T5 cells, using neurogenetics and calcium imaging. Remarkably, this contribution of color circuitry to motion vision enhances the detection of approaching UV discs, but not green discs with the same chromatic contrast, and we show how this could generalize for systems with ON- and OFF-motion pathways. Our results provide a computational and circuit basis for how color enhances motion vision to favor the detection of saliently colored objects.
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Affiliation(s)
- Kit D Longden
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA.
| | - Edward M Rogers
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA
| | - Aljoscha Nern
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA
| | - Heather Dionne
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA
| | - Michael B Reiser
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA, 20147, USA.
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11
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Schafer SF, Croke H, Kriete A, Ayaz H, Lewin PA, von Reyn CR, Schafer ME. A Miniature Ultrasound Source for Neural Modulation. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:1544-1553. [PMID: 37812556 PMCID: PMC10751802 DOI: 10.1109/tuffc.2023.3322963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/11/2023]
Abstract
This work describes a unique ultrasound (US) exposure system designed to create very localized ( [Formula: see text]) sound fields at operating frequencies that are currently being used for preclinical US neuromodulation. This system can expose small clusters of neuronal tissue, such as cell cultures or intact brain structures in target animal models, opening up opportunities to examine possible mechanisms of action. We modified a dental descaler and drove it at a resonance frequency of 96 kHz, well above its nominal operating point of 28 kHz. A ceramic microtip from an ultrasonic wire bonder was attached to the end of the applicator, creating a 100- [Formula: see text] point source. The device was calibrated with a polyvinylidene difluoride (PVDF) membrane hydrophone, in a novel, air-backed, configuration. The experimental results were confirmed by simulation using a monopole model. The results show a consistent decaying sound field from the tip, well-suited to neural stimulation. The system was tested on an existing neurological model, Drosophila melanogaster, which has not previously been used for US neuromodulation experiments. The results show brain-directed US stimulation induces or suppresses motor actions, demonstrated through synchronized tracking of fly limb movements. These results provide the basis for ongoing and future studies of US interaction with neuronal tissue, both at the level of single neurons and intact organisms.
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12
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Ros IG, Omoto JJ, Dickinson MH. Descending control and regulation of spontaneous flight turns in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.06.555791. [PMID: 37732262 PMCID: PMC10508747 DOI: 10.1101/2023.09.06.555791] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of life, selecting for a common locomotor search motif in which straight movements through resource-poor regions alternate with zig -zag exploration in resource-rich domains. For example, flies execute rapid changes in flight heading called body saccades during local search, but suppress these turns during long-distance dispersal or when surging upwind after encountering an attractive odor plume. Here, we describe the key cellular components of a neural network in flies that generates spontaneous turns as well as a specialized neuron that inhibits the network to promote straight flight. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional couplets-one for right turns and one for left-with each couplet consisting of an excitatory (DNae014) and inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly brain, we identified a large, unique interneuron (VES041) that forms inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As suggested by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it regulates the transition between local search and long-distance dispersal. These results thus identify the critical elements of a network that not only structures the locomotor behavior of flies, but may also play a crucial role in their natural foraging ecology.
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Roemschied FA, Pacheco DA, Aragon MJ, Ireland EC, Li X, Thieringer K, Pang R, Murthy M. Flexible circuit mechanisms for context-dependent song sequencing. Nature 2023; 622:794-801. [PMID: 37821705 PMCID: PMC10600009 DOI: 10.1038/s41586-023-06632-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 09/11/2023] [Indexed: 10/13/2023]
Abstract
Sequenced behaviours, including locomotion, reaching and vocalization, are patterned differently in different contexts, enabling animals to adjust to their environments. How contextual information shapes neural activity to flexibly alter the patterning of actions is not fully understood. Previous work has indicated that this could be achieved via parallel motor circuits, with differing sensitivities to context1,2. Here we demonstrate that a single pathway operates in two regimes dependent on recent sensory history. We leverage the Drosophila song production system3 to investigate the role of several neuron types4-7 in song patterning near versus far from the female fly. Male flies sing 'simple' trains of only one mode far from the female fly but complex song sequences comprising alternations between modes when near her. We find that ventral nerve cord (VNC) circuits are shaped by mutual inhibition and rebound excitability8 between nodes driving the two song modes. Brief sensory input to a direct brain-to-VNC excitatory pathway drives simple song far from the female, whereas prolonged input enables complex song production via simultaneous recruitment of functional disinhibition of VNC circuitry. Thus, female proximity unlocks motor circuit dynamics in the correct context. We construct a compact circuit model to demonstrate that the identified mechanisms suffice to replicate natural song dynamics. These results highlight how canonical circuit motifs8,9 can be combined to enable circuit flexibility required for dynamic communication.
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Affiliation(s)
- Frederic A Roemschied
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- European Neuroscience Institute, Göttingen, Germany
| | - Diego A Pacheco
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Harvard Medical School, Boston, MA, USA
| | - Max J Aragon
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Elise C Ireland
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Xinping Li
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Kyle Thieringer
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Rich Pang
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
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14
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Evans CG, Barry MA, Perkins MH, Jing J, Weiss KR, Cropper EC. Variable task switching in the feeding network of Aplysia is a function of differential command input. J Neurophysiol 2023; 130:941-952. [PMID: 37671445 PMCID: PMC10648941 DOI: 10.1152/jn.00190.2023] [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: 05/11/2023] [Revised: 08/09/2023] [Accepted: 08/31/2023] [Indexed: 09/07/2023] Open
Abstract
Command systems integrate sensory information and then activate the interneurons and motor neurons that mediate behavior. Much research has established that the higher-order projection neurons that constitute these systems can play a key role in specifying the nature of the motor activity induced, or determining its parametric features. To a large extent, these insights have been obtained by contrasting activity induced by stimulating one neuron (or set of neurons) to activity induced by stimulating a different neuron (or set of neurons). The focus of our work differs. We study one type of motor program, ingestive feeding in the mollusc Aplysia californica, which can either be triggered when a single projection neuron (CBI-2) is repeatedly stimulated or can be triggered by projection neuron coactivation (e.g., activation of CBI-2 and CBI-3). We ask why this might be an advantageous arrangement. The cellular/molecular mechanisms that configure motor activity are different in the two situations because the released neurotransmitters differ. We focus on an important consequence of this arrangement, the fact that a persistent state can be induced with repeated CBI-2 stimulation that is not necessarily induced by CBI-2/3 coactivation. We show that this difference can have consequences for the ability of the system to switch from one type of activity to another.NEW & NOTEWORTHY We study a type of motor program that can be induced either by stimulating a higher-order projection neuron that induces a persistent state, or by coactivating projection neurons that configure activity but do not produce a state change. We show that when an activity is configured without a state change, it is possible to immediately return to an intermediate state that subsequently can be converted to any type of motor program.
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Affiliation(s)
- Colin G Evans
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Michael A Barry
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Matthew H Perkins
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Jian Jing
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chemistry and Biomedicine Innovation Center, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, China
| | - Klaudiusz R Weiss
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Elizabeth C Cropper
- Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
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15
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Schaffer ES, Mishra N, Whiteway MR, Li W, Vancura MB, Freedman J, Patel KB, Voleti V, Paninski L, Hillman EMC, Abbott LF, Axel R. The spatial and temporal structure of neural activity across the fly brain. Nat Commun 2023; 14:5572. [PMID: 37696814 PMCID: PMC10495430 DOI: 10.1038/s41467-023-41261-2] [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: 08/10/2022] [Accepted: 08/29/2023] [Indexed: 09/13/2023] Open
Abstract
What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate.
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Affiliation(s)
- Evan S Schaffer
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA.
| | - Neeli Mishra
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Matthew R Whiteway
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Statistics and the Grossman Center for the Statistics of Mind, Columbia University, New York, NY, 10027, USA
| | - Wenze Li
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Michelle B Vancura
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Jason Freedman
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Kripa B Patel
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Venkatakaushik Voleti
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Liam Paninski
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Statistics and the Grossman Center for the Statistics of Mind, Columbia University, New York, NY, 10027, USA
| | - Elizabeth M C Hillman
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
- Department of Radiology, Columbia University, New York, NY, 10027, USA
| | - L F Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, 10032, USA
| | - Richard Axel
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
- Howard Hughes Medical Institute, Columbia University, New York, NY, 10027, USA
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16
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Nicholas S, Ogawa Y, Nordström K. Dual Receptive Fields Underlying Target and Wide-Field Motion Sensitivity in Looming-Sensitive Descending Neurons. eNeuro 2023; 10:ENEURO.0188-23.2023. [PMID: 37429705 PMCID: PMC10368147 DOI: 10.1523/eneuro.0188-23.2023] [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: 05/31/2023] [Accepted: 06/16/2023] [Indexed: 07/12/2023] Open
Abstract
Responding rapidly to visual stimuli is fundamental for many animals. For example, predatory birds and insects alike have amazing target detection abilities, with incredibly short neural and behavioral delays, enabling efficient prey capture. Similarly, looming objects need to be rapidly avoided to ensure immediate survival, as these could represent approaching predators. Male Eristalis tenax hoverflies are nonpredatory, highly territorial insects that perform high-speed pursuits of conspecifics and other territorial intruders. During the initial stages of the pursuit, the retinal projection of the target is very small, but this grows to a larger object before physical interaction. Supporting such behaviors, E. tenax and other insects have both target-tuned and loom-sensitive neurons in the optic lobes and the descending pathways. We here show that these visual stimuli are not necessarily encoded in parallel. Indeed, we describe a class of descending neurons that respond to small targets, to looming and to wide-field stimuli. We show that these descending neurons have two distinct receptive fields where the dorsal receptive field is sensitive to the motion of small targets and the ventral receptive field responds to larger objects or wide-field stimuli. Our data suggest that the two receptive fields have different presynaptic input, where the inputs are not linearly summed. This novel and unique arrangement could support different behaviors, including obstacle avoidance, flower landing, and target pursuit or capture.
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Affiliation(s)
- Sarah Nicholas
- Flinders Health and Medical Research Institute, Flinders University, Adelaide 5001, Australia
| | - Yuri Ogawa
- Flinders Health and Medical Research Institute, Flinders University, Adelaide 5001, Australia
| | - Karin Nordström
- Flinders Health and Medical Research Institute, Flinders University, Adelaide 5001, Australia
- Department of Medical Cell Biology, Uppsala University, 75123 Uppsala, Sweden
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17
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Cheong HSJ, Boone KN, Bennett MM, Salman F, Ralston JD, Hatch K, Allen RF, Phelps AM, Cook AP, Phelps JS, Erginkaya M, Lee WCA, Card GM, Daly KC, Dacks AM. Organization of an Ascending Circuit that Conveys Flight Motor State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.544074. [PMID: 37333334 PMCID: PMC10274802 DOI: 10.1101/2023.06.07.544074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Natural behaviors are a coordinated symphony of motor acts which drive self-induced or reafferent sensory activation. Single sensors only signal presence and magnitude of a sensory cue; they cannot disambiguate exafferent (externally-induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to make appropriate decisions and initiate adaptive behavioral outcomes. This is mediated by predictive motor signaling mechanisms, which emanate from motor control pathways to sensory processing pathways, but how predictive motor signaling circuits function at the cellular and synaptic level is poorly understood. We use a variety of techniques, including connectomics from both male and female electron microscopy volumes, transcriptomics, neuroanatomical, physiological and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs), which putatively provide predictive motor signals to several sensory and motor neuropil. Both AHN pairs receive input primarily from an overlapping population of descending neurons, many of which drive wing motor output. The two AHN pairs target almost exclusively non-overlapping downstream neural networks including those that process visual, auditory and mechanosensory information as well as networks coordinating wing, haltere, and leg motor output. These results support the conclusion that the AHN pairs multi-task, integrating a large amount of common input, then tile their output in the brain, providing predictive motor signals to non-overlapping sensory networks affecting motor control both directly and indirectly.
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Affiliation(s)
- Han S. J. Cheong
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, United States of America
| | - Kaitlyn N. Boone
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Marryn M. Bennett
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Farzaan Salman
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Jacob D. Ralston
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Kaleb Hatch
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Raven F. Allen
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Alec M. Phelps
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Andrew P. Cook
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
| | - Jasper S. Phelps
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, United States of America
| | - Mert Erginkaya
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, 1400-038, Portugal
| | - Wei-Chung A. Lee
- F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, United States of America
| | - Gwyneth M. Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, United States of America
- Zuckerman Institute, Columbia University, New York, NY 10027, United States of America
| | - Kevin C. Daly
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
- Department of Neuroscience, West Virginia University, Morgantown, WV 26505, United States of America
| | - Andrew M. Dacks
- Department of Biology, West Virginia University, Morgantown, WV 26505, United States of America
- Department of Neuroscience, West Virginia University, Morgantown, WV 26505, United States of America
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18
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Ehrhardt E, Whitehead SC, Namiki S, Minegishi R, Siwanowicz I, Feng K, Otsuna H, Meissner GW, Stern D, Truman J, Shepherd D, Dickinson MH, Ito K, Dickson BJ, Cohen I, Card GM, Korff W. Single-cell type analysis of wing premotor circuits in the ventral nerve cord of Drosophila melanogaster. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.31.542897. [PMID: 37398009 PMCID: PMC10312520 DOI: 10.1101/2023.05.31.542897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their function. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse driver lines targeting 198 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neural circuits and connectivity of premotor circuits while linking them to behavioral outputs.
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Affiliation(s)
- Erica Ehrhardt
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Institute of Zoology, University of Cologne, Zülpicher Str 47b, 50674 Cologne, Germany
| | - Samuel C Whitehead
- Physics Department, Cornell University, 271 Clark Hall, Ithaca, New York 14853, USA
| | - Shigehiro Namiki
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Ryo Minegishi
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Igor Siwanowicz
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Kai Feng
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Queensland Brain Institute, University of Queensland, 79 Upland Rd, Brisbane, QLD, 4072, Australia
| | - Hideo Otsuna
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - FlyLight Project Team
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Geoffrey W Meissner
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - David Stern
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Jim Truman
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Department of Biology, University of Washington, Seattle, Washington 98195, USA
| | - David Shepherd
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Life Sciences Building, Southampton SO17 1BJ
| | - Michael H. Dickinson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- California Institute of Technology, 1200 E California Blvd, Pasadena, California 91125, USA
| | - Kei Ito
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
- Institute of Zoology, University of Cologne, Zülpicher Str 47b, 50674 Cologne, Germany
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Itai Cohen
- Physics Department, Cornell University, 271 Clark Hall, Ithaca, New York 14853, USA
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
| | - Wyatt Korff
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr, Ashburn, Virginia 20147, USA
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19
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Currier TA, Pang MM, Clandinin TR. Visual processing in the fly, from photoreceptors to behavior. Genetics 2023; 224:iyad064. [PMID: 37128740 PMCID: PMC10213501 DOI: 10.1093/genetics/iyad064] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 03/22/2023] [Indexed: 05/03/2023] Open
Abstract
Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.
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Affiliation(s)
- Timothy A Currier
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michelle M Pang
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
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20
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Blitz DM. Neural circuit regulation by identified modulatory projection neurons. Front Neurosci 2023; 17:1154769. [PMID: 37008233 PMCID: PMC10063799 DOI: 10.3389/fnins.2023.1154769] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 03/01/2023] [Indexed: 03/19/2023] Open
Abstract
Rhythmic behaviors (e.g., walking, breathing, and chewing) are produced by central pattern generator (CPG) circuits. These circuits are highly dynamic due to a multitude of input they receive from hormones, sensory neurons, and modulatory projection neurons. Such inputs not only turn CPG circuits on and off, but they adjust their synaptic and cellular properties to select behaviorally relevant outputs that last from seconds to hours. Similar to the contributions of fully identified connectomes to establishing general principles of circuit function and flexibility, identified modulatory neurons have enabled key insights into neural circuit modulation. For instance, while bath-applying neuromodulators continues to be an important approach to studying neural circuit modulation, this approach does not always mimic the neural circuit response to neuronal release of the same modulator. There is additional complexity in the actions of neuronally-released modulators due to: (1) the prevalence of co-transmitters, (2) local- and long-distance feedback regulating the timing of (co-)release, and (3) differential regulation of co-transmitter release. Identifying the physiological stimuli (e.g., identified sensory neurons) that activate modulatory projection neurons has demonstrated multiple “modulatory codes” for selecting particular circuit outputs. In some cases, population coding occurs, and in others circuit output is determined by the firing pattern and rate of the modulatory projection neurons. The ability to perform electrophysiological recordings and manipulations of small populations of identified neurons at multiple levels of rhythmic motor systems remains an important approach for determining the cellular and synaptic mechanisms underlying the rapid adaptability of rhythmic neural circuits.
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21
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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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22
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Egelhaaf M. Optic flow based spatial vision in insects. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023:10.1007/s00359-022-01610-w. [PMID: 36609568 DOI: 10.1007/s00359-022-01610-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 12/06/2022] [Accepted: 12/24/2022] [Indexed: 01/09/2023]
Abstract
The optic flow, i.e., the displacement of retinal images of objects in the environment induced by self-motion, is an important source of spatial information, especially for fast-flying insects. Spatial information over a wide range of distances, from the animal's immediate surroundings over several hundred metres to kilometres, is necessary for mediating behaviours, such as landing manoeuvres, collision avoidance in spatially complex environments, learning environmental object constellations and path integration in spatial navigation. To facilitate the processing of spatial information, the complexity of the optic flow is often reduced by active vision strategies. These result in translations and rotations being largely separated by a saccadic flight and gaze mode. Only the translational components of the optic flow contain spatial information. In the first step of optic flow processing, an array of local motion detectors provides a retinotopic spatial proximity map of the environment. This local motion information is then processed in parallel neural pathways in a task-specific manner and used to control the different components of spatial behaviour. A particular challenge here is that the distance information extracted from the optic flow does not represent the distances unambiguously, but these are scaled by the animal's speed of locomotion. Possible ways of coping with this ambiguity are discussed.
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Affiliation(s)
- Martin Egelhaaf
- Neurobiology and Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Universitätsstraße 25, 33615, Bielefeld, Germany.
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23
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Dombrovski M, Peek MY, Park JY, Vaccari A, Sumathipala M, Morrow C, Breads P, Zhao A, Kurmangaliyev YZ, Sanfilippo P, Rehan A, Polsky J, Alghailani S, Tenshaw E, Namiki S, Zipursky SL, Card GM. Synaptic gradients transform object location to action. Nature 2023; 613:534-542. [PMID: 36599984 PMCID: PMC9849133 DOI: 10.1038/s41586-022-05562-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 11/11/2022] [Indexed: 01/06/2023]
Abstract
To survive, animals must convert sensory information into appropriate behaviours1,2. Vision is a common sense for locating ethologically relevant stimuli and guiding motor responses3-5. How circuitry converts object location in retinal coordinates to movement direction in body coordinates remains largely unknown. Here we show through behaviour, physiology, anatomy and connectomics in Drosophila that visuomotor transformation occurs by conversion of topographic maps formed by the dendrites of feature-detecting visual projection neurons (VPNs)6,7 into synaptic weight gradients of VPN outputs onto central brain neurons. We demonstrate how this gradient motif transforms the anteroposterior location of a visual looming stimulus into the fly's directional escape. Specifically, we discover that two neurons postsynaptic to a looming-responsive VPN type promote opposite takeoff directions. Opposite synaptic weight gradients onto these neurons from looming VPNs in different visual field regions convert localized looming threats into correctly oriented escapes. For a second looming-responsive VPN type, we demonstrate graded responses along the dorsoventral axis. We show that this synaptic gradient motif generalizes across all 20 primary VPN cell types and most often arises without VPN axon topography. Synaptic gradients may thus be a general mechanism for conveying spatial features of sensory information into directed motor outputs.
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Affiliation(s)
- Mark Dombrovski
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Martin Y Peek
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jin-Yong Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Andrea Vaccari
- Department of Computer Science, Middlebury College, Middlebury, VT, USA
| | | | - Carmen Morrow
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Patrick Breads
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Arthur Zhao
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yerbol Z Kurmangaliyev
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Piero Sanfilippo
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Aadil Rehan
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jason Polsky
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Shada Alghailani
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Emily Tenshaw
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Shigehiro Namiki
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.,Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan
| | - S Lawrence Zipursky
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Gwyneth M Card
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA. .,Department of Neuroscience, Howard Hughes Medical Institute, The Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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24
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Shoenhard H, Jain RA, Granato M. The calcium-sensing receptor (CaSR) regulates zebrafish sensorimotor decision making via a genetically defined cluster of hindbrain neurons. Cell Rep 2022; 41:111790. [PMID: 36476852 PMCID: PMC9813870 DOI: 10.1016/j.celrep.2022.111790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 09/21/2022] [Accepted: 11/15/2022] [Indexed: 12/12/2022] Open
Abstract
Decision making is a fundamental nervous system function that ranges widely in complexity and speed of execution. We previously established larval zebrafish as a model for sensorimotor decision making and identified the G-protein-coupled calcium-sensing receptor (CaSR) to be critical for this process. Here, we report that CaSR functions in neurons to dynamically regulate the bias between two behavioral outcomes: escapes and reorientations. By employing a computational guided transgenic strategy, we identify a genetically defined neuronal cluster in the hindbrain as a key candidate site for CaSR function. Finally, we demonstrate that transgenic CaSR expression targeting this cluster consisting of a few hundred neurons shifts behavioral bias in wild-type animals and restores decision making deficits in CaSR mutants. Combined, our data provide a rare example of a G-protein-coupled receptor that biases vertebrate sensorimotor decision making via a defined neuronal cluster.
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Affiliation(s)
- Hannah Shoenhard
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Roshan A. Jain
- Department of Biology, Haverford College, Haverford, PA 19041, USA
| | - Michael Granato
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Lead contact,Correspondence:
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25
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Devineni AV. Sensory biology: Olfactory crosstalk reshapes odor coding. Curr Biol 2022; 32:R1002-R1005. [PMID: 36220084 DOI: 10.1016/j.cub.2022.08.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
New research uncovers a novel form of crosstalk between olfactory pathways in the antennal lobe, the first olfactory center of the fly brain. This crosstalk reshapes odor coding and may explain how carbon dioxide can elicit either attraction or aversion.
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Affiliation(s)
- Anita V Devineni
- Department of Biology, Emory University, Atlanta, GA 30322, USA.
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26
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Fischer PJ, Schnell B. Multiple mechanisms mediate the suppression of motion vision during escape maneuvers in flying Drosophila. iScience 2022; 25:105143. [PMID: 36185378 PMCID: PMC9523382 DOI: 10.1016/j.isci.2022.105143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/15/2022] [Accepted: 09/12/2022] [Indexed: 11/17/2022] Open
Affiliation(s)
- Philippe Jules Fischer
- Emmy Noether Group Neurobiology of Flight Control, Max Planck Institute for Neurobiology of Behavior – caesar, 53175 Bonn, Germany
| | - Bettina Schnell
- Emmy Noether Group Neurobiology of Flight Control, Max Planck Institute for Neurobiology of Behavior – caesar, 53175 Bonn, Germany
- Corresponding author
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27
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Flavell SW, Gogolla N, Lovett-Barron M, Zelikowsky M. The emergence and influence of internal states. Neuron 2022; 110:2545-2570. [PMID: 35643077 PMCID: PMC9391310 DOI: 10.1016/j.neuron.2022.04.030] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 02/11/2022] [Accepted: 04/27/2022] [Indexed: 01/09/2023]
Abstract
Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.
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Affiliation(s)
- Steven W Flavell
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Nadine Gogolla
- Emotion Research Department, Max Planck Institute of Psychiatry, 80804 Munich, Germany; Circuits for Emotion Research Group, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany.
| | - Matthew Lovett-Barron
- Division of Biological Sciences-Neurobiology Section, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Moriel Zelikowsky
- Department of Neurobiology, University of Utah, Salt Lake City, UT 84112, USA.
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28
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Impact of walking speed and motion adaptation on optokinetic nystagmus-like head movements in the blowfly Calliphora. Sci Rep 2022; 12:11540. [PMID: 35799051 PMCID: PMC9262929 DOI: 10.1038/s41598-022-15740-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 04/25/2022] [Indexed: 11/30/2022] Open
Abstract
The optokinetic nystagmus is a gaze-stabilizing mechanism reducing motion blur by rapid eye rotations against the direction of visual motion, followed by slower syndirectional eye movements minimizing retinal slip speed. Flies control their gaze through head turns controlled by neck motor neurons receiving input directly, or via descending neurons, from well-characterized directional-selective interneurons sensitive to visual wide-field motion. Locomotion increases the gain and speed sensitivity of these interneurons, while visual motion adaptation in walking animals has the opposite effects. To find out whether flies perform an optokinetic nystagmus, and how it may be affected by locomotion and visual motion adaptation, we recorded head movements of blowflies on a trackball stimulated by progressive and rotational visual motion. Flies flexibly responded to rotational stimuli with optokinetic nystagmus-like head movements, independent of their locomotor state. The temporal frequency tuning of these movements, though matching that of the upstream directional-selective interneurons, was only mildly modulated by walking speed or visual motion adaptation. Our results suggest flies flexibly control their gaze to compensate for rotational wide-field motion by a mechanism similar to an optokinetic nystagmus. Surprisingly, the mechanism is less state-dependent than the response properties of directional-selective interneurons providing input to the neck motor system.
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29
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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] [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
- *Correspondence: Anmo J. Kim,
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30
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Nande A, Dubinkina V, Ravasio R, Zhang GH, Berman GJ. Bottlenecks, Modularity, and the Neural Control of Behavior. Front Behav Neurosci 2022; 16:835753. [PMID: 35464140 PMCID: PMC9020368 DOI: 10.3389/fnbeh.2022.835753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
In almost all animals, the transfer of information from the brain to the motor circuitry is facilitated by a relatively small number of neurons, leading to a constraint on the amount of information that can be transmitted. Our knowledge of how animals encode information through this pathway, and the consequences of this encoding, however, is limited. In this study, we use a simple feed-forward neural network to investigate the consequences of having such a bottleneck and identify aspects of the network architecture that enable robust information transfer. We are able to explain some recently observed properties of descending neurons—that they exhibit a modular pattern of connectivity and that their excitation leads to consistent alterations in behavior that are often dependent upon the desired behavioral state of the animal. Our model predicts that in the presence of an information bottleneck, such a modular structure is needed to increase the efficiency of the network and to make it more robust to perturbations. However, it does so at the cost of an increase in state-dependent effects. Despite its simplicity, our model is able to provide intuition for the trade-offs faced by the nervous system in the presence of an information processing constraint and makes predictions for future experiments.
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Affiliation(s)
- Anjalika Nande
- Department of Physics, Harvard University, Cambridge, MA, United States
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Veronika Dubinkina
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Riccardo Ravasio
- Institute of Physics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- The James Franck Institute, University of Chicago, Chicago, IL, United States
| | - Grace H. Zhang
- Department of Physics, Harvard University, Cambridge, MA, United States
| | - Gordon J. Berman
- Departments of Biology and Physics, Emory University, Atlanta, GA, United States
- *Correspondence: Gordon J. Berman
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31
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Context-dependent control of behavior in Drosophila. Curr Opin Neurobiol 2022; 73:102523. [DOI: 10.1016/j.conb.2022.02.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 01/30/2022] [Accepted: 02/02/2022] [Indexed: 12/16/2022]
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32
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Devineni AV, Scaplen KM. Neural Circuits Underlying Behavioral Flexibility: Insights From Drosophila. Front Behav Neurosci 2022; 15:821680. [PMID: 35069145 PMCID: PMC8770416 DOI: 10.3389/fnbeh.2021.821680] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 12/14/2021] [Indexed: 11/16/2022] Open
Abstract
Behavioral flexibility is critical to survival. Animals must adapt their behavioral responses based on changes in the environmental context, internal state, or experience. Studies in Drosophila melanogaster have provided insight into the neural circuit mechanisms underlying behavioral flexibility. Here we discuss how Drosophila behavior is modulated by internal and behavioral state, environmental context, and learning. We describe general principles of neural circuit organization and modulation that underlie behavioral flexibility, principles that are likely to extend to other species.
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Affiliation(s)
- Anita V. Devineni
- Department of Biology, Emory University, Atlanta, GA, United States
- Zuckerman Mind Brain Institute, Columbia University, New York, NY, United States
| | - Kristin M. Scaplen
- Department of Psychology, Bryant University, Smithfield, RI, United States
- Center for Health and Behavioral Studies, Bryant University, Smithfield, RI, United States
- Department of Neuroscience, Brown University, Providence, RI, United States
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33
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Aymanns F, Chen CL, Ramdya P. Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors. eLife 2022; 11:81527. [PMID: 36286408 PMCID: PMC9605690 DOI: 10.7554/elife.81527] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/13/2022] [Indexed: 11/21/2022] Open
Abstract
Deciphering how the brain regulates motor circuits to control complex behaviors is an important, long-standing challenge in neuroscience. In the fly, Drosophila melanogaster, this is coordinated by a population of ~ 1100 descending neurons (DNs). Activating only a few DNs is known to be sufficient to drive complex behaviors like walking and grooming. However, what additional role the larger population of DNs plays during natural behaviors remains largely unknown. For example, they may modulate core behavioral commands or comprise parallel pathways that are engaged depending on sensory context. We evaluated these possibilities by recording populations of nearly 100 DNs in individual tethered flies while they generated limb-dependent behaviors, including walking and grooming. We found that the largest fraction of recorded DNs encode walking while fewer are active during head grooming and resting. A large fraction of walk-encoding DNs encode turning and far fewer weakly encode speed. Although odor context does not determine which behavior-encoding DNs are recruited, a few DNs encode odors rather than behaviors. Lastly, we illustrate how one can identify individual neurons from DN population recordings by using their spatial, functional, and morphological properties. These results set the stage for a comprehensive, population-level understanding of how the brain’s descending signals regulate complex motor actions.
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Affiliation(s)
- Florian Aymanns
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFLLausanneSwitzerland
| | - Chin-Lin Chen
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFLLausanneSwitzerland
| | - Pavan Ramdya
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFLLausanneSwitzerland
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34
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Leibbrandt R, Nicholas S, Nordström K. The impulse response of optic flow-sensitive descending neurons to roll m-sequences. J Exp Biol 2021; 224:273641. [PMID: 34870706 PMCID: PMC8714074 DOI: 10.1242/jeb.242833] [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: 05/05/2021] [Accepted: 11/05/2021] [Indexed: 11/23/2022]
Abstract
When animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow-sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensorimotor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. Therefore, here we used m-sequences to quantify the impulse responses of optic flow-sensitive descending neurons in male Eristalis tenax hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5–18.0 ms. This is similar to the impulse response time to peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift. Summary: The impulse response of hoverfly optic flow-sensitive descending neurons to roll m-sequences reaches its time to peak within 20 ms and slowly returns to baseline over the next 100 ms.
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Affiliation(s)
- Richard Leibbrandt
- Neuroscience, Flinders Health and Medical Research Institute, Flinders University, GPO Box 2100, 5001 Adelaide, SA, Australia
| | - Sarah Nicholas
- Neuroscience, Flinders Health and Medical Research Institute, Flinders University, GPO Box 2100, 5001 Adelaide, SA, Australia
| | - Karin Nordström
- Neuroscience, Flinders Health and Medical Research Institute, Flinders University, GPO Box 2100, 5001 Adelaide, SA, Australia.,Department of Neuroscience, Uppsala University, Box 593, 751 24 Uppsala, Sweden
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35
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Beetz MJ, Kraus C, Franzke M, Dreyer D, Strube-Bloss MF, Rössler W, Warrant EJ, Merlin C, El Jundi B. Flight-induced compass representation in the monarch butterfly heading network. Curr Biol 2021; 32:338-349.e5. [PMID: 34822766 DOI: 10.1016/j.cub.2021.11.009] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/27/2021] [Accepted: 11/03/2021] [Indexed: 10/19/2022]
Abstract
For navigation, animals use a robust internal compass. Compass navigation is crucial for long-distance migrating animals like monarch butterflies, which use the sun to navigate over 4,000 km to their overwintering sites every fall. Sun-compass neurons of the central complex have only been recorded in immobile butterflies, and experimental evidence for encoding the animal's heading in these neurons is still missing. Although the activity of central-complex neurons exhibits a locomotor-dependent modulation in many insects, the function of such modulations remains unexplored. Here, we developed tetrode recordings from tethered flying monarch butterflies to reveal how flight modulates heading representation. We found that, during flight, heading-direction neurons change their tuning, transforming the central-complex network to function as a global compass. This compass is characterized by the dominance of processing steering feedback and allows for robust heading representation even under unreliable visual scenarios, an ideal strategy for maintaining a migratory heading over enormous distances.
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Affiliation(s)
- M Jerome Beetz
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany.
| | - Christian Kraus
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany
| | - Myriam Franzke
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany
| | - David Dreyer
- Lund Vision Group, Department of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
| | - Martin F Strube-Bloss
- Department of Biological Cybernetics, University of Bielefeld, Universitätsstraße 25, 33615 Bielefeld, Germany
| | - Wolfgang Rössler
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany
| | - Eric J Warrant
- Lund Vision Group, Department of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
| | - Christine Merlin
- Department of Biology and Center for Biological Clocks Research, Texas A&M University, College Station, TX 77843, USA
| | - Basil El Jundi
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany.
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36
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Cellini B, Salem W, Mongeau JM. Mechanisms of punctuated vision in fly flight. Curr Biol 2021; 31:4009-4024.e3. [PMID: 34329590 DOI: 10.1016/j.cub.2021.06.080] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 06/02/2021] [Accepted: 06/25/2021] [Indexed: 11/26/2022]
Abstract
To guide locomotion, animals control gaze via movements of their eyes, head, and/or body, but how the nervous system controls gaze during complex motor tasks remains elusive. In many animals, shifts in gaze consist of periods of smooth movement punctuated by rapid eye saccades. Notably, eye movements are constrained by anatomical limits, which requires resetting eye position. By studying tethered, flying fruit flies (Drosophila), we show that flies perform stereotyped head saccades to reset gaze, analogous to optokinetic nystagmus in primates. Head-reset saccades interrupted head smooth movement for as little as 50 ms-representing less than 5% of the total flight time-thereby enabling punctuated gaze stabilization. By revealing the passive mechanics of the neck joint, we show that head-reset saccades leverage the neck's natural elastic recoil, enabling mechanically assisted redirection of gaze. The consistent head orientation at saccade initiation, the influence of the head's angular position on saccade rate, the decrease in wing saccade frequency in head-fixed flies, and the decrease in head-reset saccade rate in flies with their head range of motion restricted together implicate proprioception as the primary trigger of head-reset saccades. Wing-reset saccades were influenced by head orientation, establishing a causal link between neck sensory signals and the execution of body saccades. Head-reset saccades were abolished when flies switched to a landing state, demonstrating that head movements are gated by behavioral state. We propose a control architecture for active vision systems with limits in sensor range of motion. VIDEO ABSTRACT.
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Affiliation(s)
- Benjamin Cellini
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Wael Salem
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Jean-Michel Mongeau
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
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37
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38
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Yarger AM, Jordan KA, Smith AJ, Fox JL. Takeoff diversity in Diptera. Proc Biol Sci 2021; 288:20202375. [PMID: 33434467 PMCID: PMC7892408 DOI: 10.1098/rspb.2020.2375] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 12/07/2020] [Indexed: 11/12/2022] Open
Abstract
The order Diptera (true flies) are named for their two wings because their hindwings have evolved into specialized mechanosensory organs called halteres. Flies use halteres to detect body rotations and maintain stability during flight and other behaviours. The most recently diverged dipteran monophyletic subsection, the Calyptratae, is highly successful, accounting for approximately 12% of dipteran diversity, and includes common families like house flies. These flies move their halteres independently from their wings and oscillate their halteres during walking. Here, we demonstrate that this subsection of flies uses their halteres to stabilize their bodies during takeoff, whereas non-Calyptratae flies do not. We find that flies of the Calyptratae are able to take off more rapidly than non-Calyptratae flies without sacrificing stability. Haltere removal decreased both velocity and stability in the takeoffs of Calyptratae, but not other flies. The loss of takeoff velocity following haltere removal in Calyptratae (but not other flies) is a direct result of a decrease in leg extension speed. A closely related non-Calyptratae species (D. melanogaster) also has a rapid takeoff, but takeoff duration and stability are unaffected by haltere removal. Haltere use thus allows for greater speed and stability during fast escapes, but only in the Calyptratae clade.
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Affiliation(s)
| | | | | | - Jessica L. Fox
- Department of Biology, Case Western Reserve University, Cleveland, OH 44106-7080, USA
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Bogovic JA, Otsuna H, Heinrich L, Ito M, Jeter J, Meissner G, Nern A, Colonell J, Malkesman O, Ito K, Saalfeld S. An unbiased template of the Drosophila brain and ventral nerve cord. PLoS One 2020; 15:e0236495. [PMID: 33382698 PMCID: PMC7774840 DOI: 10.1371/journal.pone.0236495] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 07/07/2020] [Indexed: 12/03/2022] Open
Abstract
The fruit fly Drosophila melanogaster is an important model organism for neuroscience with a wide array of genetic tools that enable the mapping of individual neurons and neural subtypes. Brain templates are essential for comparative biological studies because they enable analyzing many individuals in a common reference space. Several central brain templates exist for Drosophila, but every one is either biased, uses sub-optimal tissue preparation, is imaged at low resolution, or does not account for artifacts. No publicly available Drosophila ventral nerve cord template currently exists. In this work, we created high-resolution templates of the Drosophila brain and ventral nerve cord using the best-available technologies for imaging, artifact correction, stitching, and template construction using groupwise registration. We evaluated our central brain template against the four most competitive, publicly available brain templates and demonstrate that ours enables more accurate registration with fewer local deformations in shorter time.
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Affiliation(s)
- John A. Bogovic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Hideo Otsuna
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Larissa Heinrich
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Masayoshi Ito
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Jennifer Jeter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Geoffrey Meissner
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Oz Malkesman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Kei Ito
- Institute of Zoology, University of Cologne, Germany
| | - Stephan Saalfeld
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
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40
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Cheong HS, Siwanowicz I, Card GM. Multi-regional circuits underlying visually guided decision-making in Drosophila. Curr Opin Neurobiol 2020; 65:77-87. [PMID: 33217639 DOI: 10.1016/j.conb.2020.10.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/30/2020] [Accepted: 10/02/2020] [Indexed: 12/26/2022]
Abstract
Visually guided decision-making requires integration of information from distributed brain areas, necessitating a brain-wide approach to examine its neural mechanisms. New tools in Drosophila melanogaster enable circuits spanning the brain to be charted with single cell-type resolution. Here, we highlight recent advances uncovering the computations and circuits that transform and integrate visual information across the brain to make behavioral choices. Visual information flows from the optic lobes to three primary central brain regions: a sensorimotor mapping area and two 'higher' centers for memory or spatial orientation. Rapid decision-making during predator evasion emerges from the spike timing dynamics in parallel sensorimotor cascades. Goal-directed decisions may occur through memory, navigation and valence processing in the central complex and mushroom bodies.
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Affiliation(s)
- Han Sj Cheong
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, United States
| | - Igor Siwanowicz
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, United States
| | - Gwyneth M Card
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, United States.
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41
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Mezzera C, Brotas M, Gaspar M, Pavlou HJ, Goodwin SF, Vasconcelos ML. Ovipositor Extrusion Promotes the Transition from Courtship to Copulation and Signals Female Acceptance in Drosophila melanogaster. Curr Biol 2020; 30:3736-3748.e5. [PMID: 32795437 DOI: 10.1016/j.cub.2020.06.071] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 05/05/2020] [Accepted: 06/22/2020] [Indexed: 10/23/2022]
Abstract
Communication between male and female fruit flies during courtship is essential for successful mating, but, as with many other species, it is the female who decides whether to mate. Here, we show a novel role for ovipositor extrusion in promoting male copulation attempts in virgin and mated females and signaling acceptance in virgins. We first show that ovipositor extrusion is only displayed by sexually mature females, exclusively during courtship and in response to the male song. We identified a pair of descending neurons that controls ovipositor extrusion in mated females. Genetic silencing of the descending neurons shows that ovipositor extrusion stimulates the male to attempt copulation. A detailed behavioral analysis revealed that during courtship, the male repeatedly licks the female genitalia, independently of ovipositor extrusion, and that licking an extruded ovipositor prompts a copulation attempt. However, if the ovipositor is not subsequently retracted, copulation is prevented, as it happens with mated females. In this study, we reveal a dual function of the ovipositor: while its extrusion is necessary for initiating copulation by the male, its retraction signals female acceptance. We thus uncover the significance of the communication between male and female that initiates the transition from courtship to copulation.
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Affiliation(s)
- Cecilia Mezzera
- Champalimaud Center for the Unknown, Lisbon 1400-038, Portugal
| | | | - Miguel Gaspar
- Champalimaud Center for the Unknown, Lisbon 1400-038, Portugal
| | - Hania J Pavlou
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford OX1 3SR, UK
| | - Stephen F Goodwin
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford OX1 3SR, UK
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42
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Bidaye SS, Laturney M, Chang AK, Liu Y, Bockemühl T, Büschges A, Scott K. Two Brain Pathways Initiate Distinct Forward Walking Programs in Drosophila. Neuron 2020; 108:469-485.e8. [PMID: 32822613 DOI: 10.1016/j.neuron.2020.07.032] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 06/08/2020] [Accepted: 07/24/2020] [Indexed: 12/12/2022]
Abstract
An animal at rest or engaged in stationary behaviors can instantaneously initiate goal-directed walking. How descending brain inputs trigger rapid transitions from a non-walking state to an appropriate walking state is unclear. Here, we identify two neuronal types, P9 and BPN, in the Drosophila brain that, upon activation, initiate and maintain two distinct coordinated walking patterns. P9 drives forward walking with ipsilateral turning, receives inputs from central courtship-promoting neurons and visual projection neurons, and is necessary for a male to pursue a female during courtship. In contrast, BPN drives straight, forward walking and is not required during courtship. BPN is instead recruited during and required for fast, straight, forward walking bouts. Thus, this study reveals separate brain pathways for object-directed walking and fast, straight, forward walking, providing insight into how the brain initiates context-appropriate walking programs.
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Affiliation(s)
- Salil S Bidaye
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
| | - Meghan Laturney
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Amy K Chang
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Yuejiang Liu
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Till Bockemühl
- Department of Animal Physiology, Institute of Zoology, University of Cologne, 50674 Cologne, Germany
| | - Ansgar Büschges
- Department of Animal Physiology, Institute of Zoology, University of Cologne, 50674 Cologne, Germany
| | - Kristin Scott
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
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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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44
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Azevedo AW, Dickinson ES, Gurung P, Venkatasubramanian L, Mann RS, Tuthill JC. A size principle for recruitment of Drosophila leg motor neurons. eLife 2020; 9:e56754. [PMID: 32490810 PMCID: PMC7347388 DOI: 10.7554/elife.56754] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 06/01/2020] [Indexed: 11/28/2022] Open
Abstract
To move the body, the brain must precisely coordinate patterns of activity among diverse populations of motor neurons. Here, we use in vivo calcium imaging, electrophysiology, and behavior to understand how genetically-identified motor neurons control flexion of the fruit fly tibia. We find that leg motor neurons exhibit a coordinated gradient of anatomical, physiological, and functional properties. Large, fast motor neurons control high force, ballistic movements while small, slow motor neurons control low force, postural movements. Intermediate neurons fall between these two extremes. This hierarchical organization resembles the size principle, first proposed as a mechanism for establishing recruitment order among vertebrate motor neurons. Recordings in behaving flies confirmed that motor neurons are typically recruited in order from slow to fast. However, we also find that fast, intermediate, and slow motor neurons receive distinct proprioceptive feedback signals, suggesting that the size principle is not the only mechanism that dictates motor neuron recruitment. Overall, this work reveals the functional organization of the fly leg motor system and establishes Drosophila as a tractable system for investigating neural mechanisms of limb motor control.
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Affiliation(s)
- Anthony W Azevedo
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Evyn S Dickinson
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Pralaksha Gurung
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
| | - Lalanti Venkatasubramanian
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkUnited States
| | - Richard S Mann
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkUnited States
| | - John C Tuthill
- Department of Physiology and Biophysics, University of WashingtonSeattleUnited States
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45
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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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46
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Nicholas S, Leibbrandt R, Nordström K. Visual motion sensitivity in descending neurons in the hoverfly. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2020; 206:149-163. [PMID: 31989217 PMCID: PMC7069906 DOI: 10.1007/s00359-020-01402-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 12/06/2019] [Indexed: 01/11/2023]
Abstract
Many animals use motion vision information to control dynamic behaviors. For example, flying insects must decide whether to pursue a prey or not, to avoid a predator, to maintain their current flight trajectory, or to land. The neural mechanisms underlying the computation of visual motion have been particularly well investigated in the fly optic lobes. However, the descending neurons, which connect the optic lobes with the motor command centers of the ventral nerve cord, remain less studied. To address this deficiency, we describe motion vision sensitive descending neurons in the hoverfly Eristalis tenax. We describe how the neurons can be identified based on their receptive field properties, and how they respond to moving targets, looming stimuli and to widefield optic flow. We discuss their similarities with previously published visual neurons, in the optic lobes and ventral nerve cord, and suggest that they can be classified as target-selective, looming sensitive and optic flow sensitive, based on these similarities. Our results highlight the importance of using several visual stimuli as the neurons can rarely be identified based on only one response characteristic. In addition, they provide an understanding of the neurophysiology of visual neurons that are likely to affect behavior.
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Affiliation(s)
- Sarah Nicholas
- Centre for Neuroscience, Flinders University, GPO Box 2100, Adelaide, SA, 5001, Australia
| | - Richard Leibbrandt
- Centre for Neuroscience, Flinders University, GPO Box 2100, Adelaide, SA, 5001, Australia
| | - Karin Nordström
- Centre for Neuroscience, Flinders University, GPO Box 2100, Adelaide, SA, 5001, Australia. .,Department of Neuroscience, Uppsala University, Box 593, 751 24 , Uppsala, Sweden.
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47
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Abstract
The full functionality of the brain is determined by its molecular, cellular and circuit structure. Modern neuroscience now prioritizes the mapping of whole brain connectomes by detecting all direct neuron to neuron synaptic connections, a feat first accomplished for C. elegans, a full reconstruction of a 302-neuron nervous system. Efforts at Janelia Research Campus will soon reconstruct the whole brain connectomes of a larval and an adult Drosophila. These connectomes will provide a framework for incorporating detailed neural circuit information that Drosophila neuroscientists have gathered over decades. But when viewed in the context of a whole brain, it becomes difficult to isolate the contributions of distinct circuits, whether sensory systems or higher brain regions. The complete wiring diagram tells us that sensory information is not only processed in separate channels, but that even the earliest sensory layers are strongly synaptically interconnected. In the higher brain, long-range projections densely interconnect major brain regions and convergence centers that integrate input from different sensory systems. Furthermore, we also need to understand the impact of neuronal communication beyond direct synaptic modulation. Nevertheless, all of this can be pursued with Drosophila, combining connectomics with a diverse array of genetic tools and behavioral paradigms that provide effective approaches to entire brain function.
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Affiliation(s)
- Katrin Vogt
- Department of Physics, Harvard University, Cambridge, MA, USA.,Center for Brain Science, Harvard University, Cambridge, MA, USA
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48
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Currier TA, Nagel KI. Multisensory control of navigation in the fruit fly. Curr Opin Neurobiol 2019; 64:10-16. [PMID: 31841944 DOI: 10.1016/j.conb.2019.11.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 11/23/2019] [Accepted: 11/25/2019] [Indexed: 01/16/2023]
Abstract
Spatial navigation is influenced by cues from nearly every sensory modality and thus provides an excellent model for understanding how different sensory streams are integrated to drive behavior. Here we review recent work on multisensory control of navigation in the model organism Drosophila melanogaster, which allows for detailed circuit dissection. We identify four modes of integration that have been described in the literature-suppression, gating, summation, and association-and describe regions of the larval and adult brain that have been implicated in sensory integration. Finally we discuss what circuit architectures might support these different forms of integration. We argue that Drosophila is an excellent model to discover these circuit and biophysical motifs.
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Affiliation(s)
- Timothy A Currier
- Neuroscience Institute, New York University Medical Center, 435 E 30th St., New York, NY 10016, USA; Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003, USA
| | - Katherine I Nagel
- Neuroscience Institute, New York University Medical Center, 435 E 30th St., New York, NY 10016, USA; Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003, USA.
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49
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Neuromodulation of insect motion vision. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2019; 206:125-137. [DOI: 10.1007/s00359-019-01383-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 11/11/2019] [Accepted: 11/19/2019] [Indexed: 10/25/2022]
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50
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Dürr V, Arena PP, Cruse H, Dallmann CJ, Drimus A, Hoinville T, Krause T, Mátéfi-Tempfli S, Paskarbeit J, Patanè L, Schäffersmann M, Schilling M, Schmitz J, Strauss R, Theunissen L, Vitanza A, Schneider A. Integrative Biomimetics of Autonomous Hexapedal Locomotion. Front Neurorobot 2019; 13:88. [PMID: 31708765 PMCID: PMC6819508 DOI: 10.3389/fnbot.2019.00088] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 10/07/2019] [Indexed: 01/31/2023] Open
Abstract
Despite substantial advances in many different fields of neurorobotics in general, and biomimetic robots in particular, a key challenge is the integration of concepts: to collate and combine research on disparate and conceptually disjunct research areas in the neurosciences and engineering sciences. We claim that the development of suitable robotic integration platforms is of particular relevance to make such integration of concepts work in practice. Here, we provide an example for a hexapod robotic integration platform for autonomous locomotion. In a sequence of six focus sections dealing with aspects of intelligent, embodied motor control in insects and multipedal robots-ranging from compliant actuation, distributed proprioception and control of multiple legs, the formation of internal representations to the use of an internal body model-we introduce the walking robot HECTOR as a research platform for integrative biomimetics of hexapedal locomotion. Owing to its 18 highly sensorized, compliant actuators, light-weight exoskeleton, distributed and expandable hardware architecture, and an appropriate dynamic simulation framework, HECTOR offers many opportunities to integrate research effort across biomimetics research on actuation, sensory-motor feedback, inter-leg coordination, and cognitive abilities such as motion planning and learning of its own body size.
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Affiliation(s)
- Volker Dürr
- Department of Biological Cybernetics, Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Paolo P. Arena
- DIEEI: Dipartimento di Ingegneria Elettrica Elettronica e Informatica, Università degli Studi di Catania, Catania, Italy
| | - Holk Cruse
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Chris J. Dallmann
- Department of Biological Cybernetics, Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Alin Drimus
- Mads Clausen Institute, University of Southern Denmark, Sønderborg, Denmark
| | - Thierry Hoinville
- Department of Biological Cybernetics, Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Tammo Krause
- Institut für Entwicklungsbiologie und Neurobiologie, Johannes Gutenberg-Universität, Mainz, Germany
| | | | - Jan Paskarbeit
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Luca Patanè
- DIEEI: Dipartimento di Ingegneria Elettrica Elettronica e Informatica, Università degli Studi di Catania, Catania, Italy
| | - Mattias Schäffersmann
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Malte Schilling
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Josef Schmitz
- Department of Biological Cybernetics, Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Roland Strauss
- Institut für Entwicklungsbiologie und Neurobiologie, Johannes Gutenberg-Universität, Mainz, Germany
| | - Leslie Theunissen
- Department of Biological Cybernetics, Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
| | - Alessandra Vitanza
- DIEEI: Dipartimento di Ingegneria Elettrica Elettronica e Informatica, Università degli Studi di Catania, Catania, Italy
| | - Axel Schneider
- Cognitive Interaction Technology: Center of Excellence, Bielefeld University, Bielefeld, Germany
- Institute of System Dynamics and Mechatronics, Bielefeld University of Applied Sciences, Bielefeld, Germany
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