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Stürner T, Brooks P, Serratosa Capdevila L, 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 HSJ, 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 GSXE, 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] [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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Lee SYJ, Dallmann CJ, Cook AP, Tuthill JC, Agrawal S. Divergent neural circuits for proprioceptive and exteroceptive sensing of the Drosophila leg. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.23.590808. [PMID: 38712128 PMCID: PMC11071415 DOI: 10.1101/2024.04.23.590808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Somatosensory neurons provide the nervous system with information about mechanical forces originating inside and outside the body. Here, we use connectomics to reconstruct and analyze neural circuits downstream of the largest somatosensory organ in the Drosophila leg, the femoral chordotonal organ (FeCO). The FeCO has been proposed to support both proprioceptive sensing of the fly's femur-tibia joint and exteroceptive sensing of substrate vibrations, but it remains unknown which sensory neurons and central circuits contribute to each of these functions. We found that different subtypes of FeCO sensory neurons feed into distinct proprioceptive and exteroceptive pathways. Position- and movement-encoding FeCO neurons connect to local leg motor control circuits in the ventral nerve cord (VNC), indicating a proprioceptive function. In contrast, signals from the vibration-encoding FeCO neurons are integrated across legs and transmitted to auditory regions in the brain, indicating an exteroceptive function. Overall, our analyses reveal the structure of specialized circuits for processing proprioceptive and exteroceptive signals from the fly leg. They also demonstrate how analyzing patterns of synaptic connectivity can distill organizing principles from complex sensorimotor circuits.
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3
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Gorko B, Siwanowicz I, Close K, Christoforou C, Hibbard KL, Kabra M, Lee A, Park JY, Li SY, Chen AB, Namiki S, Chen C, Tuthill JC, Bock DD, Rouault H, Branson K, Ihrke G, Huston SJ. Motor neurons generate pose-targeted movements via proprioceptive sculpting. Nature 2024; 628:596-603. [PMID: 38509371 DOI: 10.1038/s41586-024-07222-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 02/22/2024] [Indexed: 03/22/2024]
Abstract
Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.
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Affiliation(s)
- Benjamin Gorko
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA, USA
| | - Igor Siwanowicz
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kari Close
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Karen L Hibbard
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Mayank Kabra
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Allen Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jin-Yong Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Si Ying Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | - Alex B Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Program in Neuroscience, Harvard Medical School, Boston, MA, 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
| | - Chenghao Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - John C Tuthill
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Davi D Bock
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Neurological Sciences, University of Vermont, Burlington, VT, USA
| | - Hervé Rouault
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Turing Centre for Living systems, Aix-Marseille University, Université de Toulon, CNRS, CPT (UMR 7332), Marseille, France
| | - Kristin Branson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Gudrun Ihrke
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Stephen J Huston
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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4
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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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5
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Tanaka R, Zhou B, Agrochao M, Badwan BA, Au B, Matos NCB, Clark DA. Neural mechanisms to incorporate visual counterevidence in self-movement estimation. Curr Biol 2023; 33:4960-4979.e7. [PMID: 37918398 PMCID: PMC10848174 DOI: 10.1016/j.cub.2023.10.011] [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: 07/29/2023] [Revised: 10/07/2023] [Accepted: 10/09/2023] [Indexed: 11/04/2023]
Abstract
In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can be spuriously triggered by visual motion created by objects moving in the world. Here, we show that stationary patterns on the retina, which constitute evidence against observer rotation, suppress inappropriate stabilizing rotational behavior in the fruit fly Drosophila. In silico experiments show that artificial neural networks (ANNs) that are optimized to distinguish observer movement from external object motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's local motion and optic-flow detectors. Our results show how the fly brain incorporates negative evidence to improve heading stability, exemplifying how a compact brain exploits geometrical constraints of the visual world.
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Affiliation(s)
- Ryosuke Tanaka
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Baohua Zhou
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA; Department of Statistics and Data Science, Yale University, New Haven, CT 06511, USA
| | - Margarida Agrochao
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
| | - Bara A Badwan
- School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA
| | - Braedyn Au
- Department of Physics, Yale University, New Haven, CT 06511, USA
| | - Natalia C B Matos
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Damon A Clark
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA; Department of Physics, Yale University, New Haven, CT 06511, USA; Department of Neuroscience, Yale University, New Haven, CT 06511, USA; Wu Tsai Institute, Yale University, New Haven, CT 06511, USA; Quantitative Biology Institute, Yale University, New Haven, CT 06511, USA.
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Yang HH, Brezovec LE, Capdevila LS, Vanderbeck QX, Adachi A, Mann RS, Wilson RI. Fine-grained descending control of steering in walking Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.15.562426. [PMID: 37904997 PMCID: PMC10614758 DOI: 10.1101/2023.10.15.562426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream from distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Notably, a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from brain cells that drive specific, coordinated modulations of low-level patterns.
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Affiliation(s)
- Helen H. Yang
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115 USA
| | - Luke E. Brezovec
- Department of Neurobiology, Stanford University, Stanford, CA 94305 USA
| | | | | | - Atsuko Adachi
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | - Richard S. Mann
- Department of Biochemistry and Molecular Biophysics, Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027 USA
| | - Rachel I. Wilson
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115 USA
- Lead contact
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7
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Zhao A, Nern A, Koskela S, Dreher M, Erginkaya M, Laughland CW, Ludwigh H, Thomson A, Hoeller J, Parekh R, Romani S, Bock DD, Chiappe E, Reiser MB. A comprehensive neuroanatomical survey of the Drosophila Lobula Plate Tangential Neurons with predictions for their optic flow sensitivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.16.562634. [PMID: 37904921 PMCID: PMC10614863 DOI: 10.1101/2023.10.16.562634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of 'optic-flow' sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.
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Affiliation(s)
- Arthur Zhao
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Sanna Koskela
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Marisa Dreher
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Mert Erginkaya
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Connor W Laughland
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Henrique Ludwigh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Alex Thomson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Judith Hoeller
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Ruchi Parekh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Sandro Romani
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Davi D Bock
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
- Department of Neurological Sciences, Larner College of Medicine, University of Vermont, USA
| | - Eugenia Chiappe
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Michael B Reiser
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
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8
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Cruz TL, Chiappe ME. Multilevel visuomotor control of locomotion in Drosophila. Curr Opin Neurobiol 2023; 82:102774. [PMID: 37651855 DOI: 10.1016/j.conb.2023.102774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/26/2023] [Accepted: 08/01/2023] [Indexed: 09/02/2023]
Abstract
Vision is critical for the control of locomotion, but the underlying neural mechanisms by which visuomotor circuits contribute to the movement of the body through space are yet not well understood. Locomotion engages multiple control systems, forming distinct interacting "control levels" driven by the activity of distributed and overlapping circuits. Therefore, a comprehensive understanding of the mechanisms underlying locomotion control requires the consideration of all control levels and their necessary coordination. Due to their small size and the wide availability of experimental tools, Drosophila has become an important model system to study this coordination. Traditionally, insect locomotion has been divided into studying either the biomechanics and local control of limbs, or navigation and course control. However, recent developments in tracking techniques, and physiological and genetic tools in Drosophila have prompted researchers to examine multilevel control coordination in flight and walking.
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Affiliation(s)
- Tomás L Cruz
- Champalimaud Research, Champalimaud Centre for the Unknown, 1400-038 Lisbon, Portugal
| | - M Eugenia Chiappe
- Champalimaud Research, Champalimaud Centre for the Unknown, 1400-038 Lisbon, Portugal.
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9
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Mano O, Choi M, Tanaka R, Creamer MS, Matos NCB, Shomar JW, Badwan BA, Clandinin TR, Clark DA. Long-timescale anti-directional rotation in Drosophila optomotor behavior. eLife 2023; 12:e86076. [PMID: 37751469 PMCID: PMC10522332 DOI: 10.7554/elife.86076] [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: 01/10/2023] [Accepted: 09/12/2023] [Indexed: 09/28/2023] Open
Abstract
Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such 'anti-directional turning' is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.
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Affiliation(s)
- Omer Mano
- Department of Molecular, Cellular, and Developmental Biology, Yale UniversityNew HavenUnited States
| | - Minseung Choi
- Department of Neurobiology, Stanford UniversityStanfordUnited States
| | - Ryosuke Tanaka
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
| | - Matthew S Creamer
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
| | - Natalia CB Matos
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
| | - Joseph W Shomar
- Department of Physics, Yale UniversityNew HavenUnited States
| | - Bara A Badwan
- Department of Chemical Engineering, Yale UniversityNew HavenUnited States
| | | | - Damon A Clark
- Department of Molecular, Cellular, and Developmental Biology, Yale UniversityNew HavenUnited States
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
- Department of Physics, Yale UniversityNew HavenUnited States
- Department of Neuroscience, Yale UniversityNew HavenUnited States
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10
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Chiappe ME. Circuits for self-motion estimation and walking control in Drosophila. Curr Opin Neurobiol 2023; 81:102748. [PMID: 37453230 DOI: 10.1016/j.conb.2023.102748] [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: 04/19/2023] [Revised: 06/11/2023] [Accepted: 06/13/2023] [Indexed: 07/18/2023]
Abstract
The brain's evolution and operation are inextricably linked to animal movement, and critical functions, such as motor control, spatial perception, and navigation, rely on precise knowledge of body movement. Such internal estimates of self-motion emerge from the integration of mechanosensory and visual feedback with motor-related signals. Thus, this internal representation likely depends on the activity of circuits distributed across the central nervous system. However, the circuits responsible for self-motion estimation, and the exact mechanisms by which motor-sensory coordination occurs within these circuits remain poorly understood. Recent technological advances have positioned Drosophila melanogaster as an advantageous model for investigating the emergence, maintenance, and utilization of self-motion representations during naturalistic walking behaviors. In this review, I will illustrate how the adult fly is providing insights into the fundamental problems of self-motion computations and walking control, which have relevance for all animals.
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Affiliation(s)
- M Eugenia Chiappe
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal.
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11
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Tanaka R, Zhou B, Agrochao M, Badwan BA, Au B, Matos NCB, Clark DA. Neural mechanisms to incorporate visual counterevidence in self motion estimation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.04.522814. [PMID: 36711843 PMCID: PMC9881891 DOI: 10.1101/2023.01.04.522814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can confuse the movement of external objects with genuine self motion. Here, we show that stationary patterns on the retina, which constitute negative evidence against self rotation, are used by the fruit fly Drosophila to suppress inappropriate stabilizing rotational behavior. In silico experiments show that artificial neural networks optimized to distinguish self and world motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's motion- and optic flow-detectors. Our results exemplify how the compact brain of the fly incorporates negative evidence to improve heading stability, exploiting geometrical constraints of the visual world.
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Affiliation(s)
- Ryosuke Tanaka
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
- Present Address: Institute of Neuroscience, Technical University of Munich, Munich 80802, Germany
| | - Baohua Zhou
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06511, USA
| | - Margarida Agrochao
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
| | - Bara A. Badwan
- School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA
| | - Braedyn Au
- Department of Physics, Yale University, New Haven, CT 06511, USA
| | - Natalia C. B. Matos
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
| | - Damon A. Clark
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA
- Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
- Department of Physics, Yale University, New Haven, CT 06511, USA
- Department of Neuroscience, Yale University, New Haven, CT 06511, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
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12
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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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13
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Daly KC, Dacks A. The self as part of the sensory ecology: how behavior affects sensation from the inside out. CURRENT OPINION IN INSECT SCIENCE 2023; 58:101053. [PMID: 37290318 DOI: 10.1016/j.cois.2023.101053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/01/2023] [Accepted: 05/09/2023] [Indexed: 06/10/2023]
Abstract
Insects exhibit remarkable sensory and motor capabilities to successfully navigate their environment. As insects move, they activate sensory afferents. Hence, insects are inextricably part of their sensory ecology. Insects must correctly attribute self- versus external sources of sensory activation to make adaptive behavioral choices. This is achieved via corollary discharge circuits (CDCs), motor-to-sensory neuronal pathways providing predictive motor signals to sensory networks to coordinate sensory processing within the context of ongoing behavior. While CDCs provide predictive motor signals, their underlying mechanisms of action and functional consequences are diverse. Here, we describe inferred CDCs and identified corollary discharge interneurons (CDIs) in insects, highlighting their anatomical commonalities and our limited understanding of their synaptic integration into the nervous system. By using connectomics information, we demonstrate that the complexity with which identified CDIs integrate into the central nervous system (CNS) can be revealed.
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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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15
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Rimniceanu M, Currea JP, Frye MA. Proprioception gates visual object fixation in flying flies. Curr Biol 2023; 33:1459-1471.e3. [PMID: 37001520 PMCID: PMC10133043 DOI: 10.1016/j.cub.2023.03.018] [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: 11/08/2022] [Revised: 01/24/2023] [Accepted: 03/07/2023] [Indexed: 04/27/2023]
Abstract
Visual object tracking in animals as diverse as felines, frogs, and fish supports behaviors including predation, predator avoidance, and landscape navigation. Decades of experimental results show that a rigidly body-fixed tethered fly in a "virtual reality" visual flight simulator steers to follow the motion of a vertical bar, thereby "fixating" it on visual midline. This behavior likely reflects a desire to seek natural features such as plant stalks and has inspired algorithms for visual object tracking predicated on robust responses to bar velocity, particularly near visual midline. Using a modified flight simulator equipped with a magnetic pivot to allow frictionless turns about the yaw axis, we discovered that bar fixation as well as smooth steering responses to bar velocity are attenuated or eliminated in yaw-free conditions. Body-fixed Drosophila melanogaster respond to bar oscillation on a stationary ground with frequency-matched wing kinematics and fixate the bar on midline. Yaw-free flies respond to the same stimulus by ignoring the bar and maintaining their original heading. These differences are driven by proprioceptive signals, rather than visual signals, as artificially "clamping" a bar in the periphery of a yaw-free fly has no effect. When presented with a bar and ground oscillating at different frequencies, a yaw-free fly follows the frequency of the ground only, whereas a body-fixed fly robustly steers at the frequencies of both the bar and ground. Our findings support a model in which proprioceptive feedback promote active damping of high-gain optomotor responses to object motion.
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Affiliation(s)
- Martha Rimniceanu
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - John P Currea
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mark A Frye
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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Chen CL, Aymanns F, Minegishi R, Matsuda VDV, Talabot N, Günel S, Dickson BJ, Ramdya P. Ascending neurons convey behavioral state to integrative sensory and action selection brain regions. Nat Neurosci 2023; 26:682-695. [PMID: 36959417 PMCID: PMC10076225 DOI: 10.1038/s41593-023-01281-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 02/14/2023] [Indexed: 03/25/2023]
Abstract
Knowing one's own behavioral state has long been theorized as critical for contextualizing dynamic sensory cues and identifying appropriate future behaviors. Ascending neurons (ANs) in the motor system that project to the brain are well positioned to provide such behavioral state signals. However, what ANs encode and where they convey these signals remains largely unknown. Here, through large-scale functional imaging in behaving animals and morphological quantification, we report the behavioral encoding and brain targeting of hundreds of genetically identifiable ANs in the adult fly, Drosophila melanogaster. We reveal that ANs encode behavioral states, specifically conveying self-motion to the anterior ventrolateral protocerebrum, an integrative sensory hub, as well as discrete actions to the gnathal ganglia, a locus for action selection. Additionally, AN projection patterns within the motor system are predictive of their encoding. Thus, ascending populations are well poised to inform distinct brain hubs of self-motion and ongoing behaviors and may provide an important substrate for computations that are required for adaptive behavior.
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Affiliation(s)
- Chin-Lin Chen
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Florian Aymanns
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Ryo Minegishi
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Victor D V Matsuda
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Nicolas Talabot
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
- Computer Vision Laboratory, EPFL, Lausanne, Switzerland
| | - Semih Günel
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland
- Computer Vision Laboratory, EPFL, Lausanne, Switzerland
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Pavan Ramdya
- Neuroengineering Laboratory, Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne, Switzerland.
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Marquis M, Wilson RI. Locomotor and olfactory responses in dopamine neurons of the Drosophila superior-lateral brain. Curr Biol 2022; 32:5406-5414.e5. [PMID: 36450284 DOI: 10.1016/j.cub.2022.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/17/2022] [Accepted: 11/03/2022] [Indexed: 12/03/2022]
Abstract
The Drosophila brain contains about 50 distinct morphological types of dopamine neurons.1,2,3,4 Physiological studies of Drosophila dopamine neurons have been largely limited to one brain region, the mushroom body,5,6,7,8,9,10,11,12,13 where they are implicated in learning.14,15,16,17,18 By comparison, we know little about the physiology of other Drosophila dopamine neurons. Interestingly, a recent whole-brain imaging study found that dopamine neuron activity in several fly brain regions is correlated with locomotion.19 This is notable because many dopamine neurons in the rodent brain are also correlated with locomotion or other movements20,21,22,23,24,25,26,27,28,29,30; however, most rodent studies have focused on learned and rewarded behaviors, and few have investigated dopamine neuron activity during spontaneous (self-timed) movements. In this study, we monitored dopamine neurons in the Drosophila brain during self-timed locomotor movements, focusing on several previously uncharacterized cell types that arborize in the superior-lateral brain, specifically the lateral horn and superior-lateral protocerebrum. We found that activity of all of these dopamine neurons correlated with spontaneous fluctuations in walking speed, with different cell types showing different speed correlations. Some dopamine neurons also responded to odors, but these responses were suppressed by repeated odor encounters. Finally, we found that the same identifiable dopamine neuron can encode different combinations of locomotion and odor in different individuals. If these dopamine neurons promote synaptic plasticity-like the dopamine neurons of the mushroom body-then, their tuning profiles would imply that plasticity depends on a flexible integration of sensory signals, motor signals, and recent experience.
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Affiliation(s)
- Michael Marquis
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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Turner MH, Krieger A, Pang MM, Clandinin TR. Visual and motor signatures of locomotion dynamically shape a population code for feature detection in Drosophila. eLife 2022; 11:e82587. [PMID: 36300621 PMCID: PMC9651947 DOI: 10.7554/elife.82587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 10/25/2022] [Indexed: 01/07/2023] Open
Abstract
Natural vision is dynamic: as an animal moves, its visual input changes dramatically. How can the visual system reliably extract local features from an input dominated by self-generated signals? In Drosophila, diverse local visual features are represented by a group of projection neurons with distinct tuning properties. Here, we describe a connectome-based volumetric imaging strategy to measure visually evoked neural activity across this population. We show that local visual features are jointly represented across the population, and a shared gain factor improves trial-to-trial coding fidelity. A subset of these neurons, tuned to small objects, is modulated by two independent signals associated with self-movement, a motor-related signal, and a visual motion signal associated with rotation of the animal. These two inputs adjust the sensitivity of these feature detectors across the locomotor cycle, selectively reducing their gain during saccades and restoring it during intersaccadic intervals. This work reveals a strategy for reliable feature detection during locomotion.
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Affiliation(s)
- Maxwell H Turner
- Department of Neurobiology, Stanford UniversityStanfordUnited States
| | - Avery Krieger
- Department of Neurobiology, Stanford UniversityStanfordUnited States
| | - Michelle M Pang
- Department of Neurobiology, Stanford UniversityStanfordUnited States
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19
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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: 7] [Impact Index Per Article: 3.5] [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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