1
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Yang HH, Brezovec BE, Serratosa Capdevila L, Vanderbeck QX, Adachi A, Mann RS, Wilson RI. Fine-grained descending control of steering in walking Drosophila. Cell 2024:S0092-8674(24)00962-0. [PMID: 39293446 DOI: 10.1016/j.cell.2024.08.033] [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: 10/31/2023] [Revised: 06/18/2024] [Accepted: 08/16/2024] [Indexed: 09/20/2024]
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 of 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. Our results suggest that 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 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
| | - Bella E Brezovec
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
| | | | - Quinn X Vanderbeck
- Department of Neurobiology, Harvard Medical School, Boston, MA 02115, 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.
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2
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Lochner S, Honerkamp D, Valada A, Straw AD. Reinforcement learning as a robotics-inspired framework for insect navigation: from spatial representations to neural implementation. Front Comput Neurosci 2024; 18:1460006. [PMID: 39314666 PMCID: PMC11416953 DOI: 10.3389/fncom.2024.1460006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 08/20/2024] [Indexed: 09/25/2024] Open
Abstract
Bees are among the master navigators of the insect world. Despite impressive advances in robot navigation research, the performance of these insects is still unrivaled by any artificial system in terms of training efficiency and generalization capabilities, particularly considering the limited computational capacity. On the other hand, computational principles underlying these extraordinary feats are still only partially understood. The theoretical framework of reinforcement learning (RL) provides an ideal focal point to bring the two fields together for mutual benefit. In particular, we analyze and compare representations of space in robot and insect navigation models through the lens of RL, as the efficiency of insect navigation is likely rooted in an efficient and robust internal representation, linking retinotopic (egocentric) visual input with the geometry of the environment. While RL has long been at the core of robot navigation research, current computational theories of insect navigation are not commonly formulated within this framework, but largely as an associative learning process implemented in the insect brain, especially in the mushroom body (MB). Here we propose specific hypothetical components of the MB circuit that would enable the implementation of a certain class of relatively simple RL algorithms, capable of integrating distinct components of a navigation task, reminiscent of hierarchical RL models used in robot navigation. We discuss how current models of insect and robot navigation are exploring representations beyond classical, complete map-like representations, with spatial information being embedded in the respective latent representations to varying degrees.
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Affiliation(s)
- Stephan Lochner
- Institute of Biology I, University of Freiburg, Freiburg, Germany
| | - Daniel Honerkamp
- Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Abhinav Valada
- Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Andrew D. Straw
- Institute of Biology I, University of Freiburg, Freiburg, Germany
- Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
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3
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Piantadosi ST, Gallistel CR. Formalising the role of behaviour in neuroscience. Eur J Neurosci 2024; 60:4756-4770. [PMID: 38858853 DOI: 10.1111/ejn.16372] [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: 06/12/2023] [Revised: 01/19/2024] [Accepted: 03/21/2024] [Indexed: 06/12/2024]
Abstract
We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers ℕ . We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two-dimensional coordinates under addition. We also study a system for processinga n b n strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost.
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Affiliation(s)
- Steven T Piantadosi
- Department of Psychology, Department of Neuroscience, UC Berkeley, Berkeley, California, USA
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4
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Dan C, Hulse BK, Kappagantula R, Jayaraman V, Hermundstad AM. A neural circuit architecture for rapid learning in goal-directed navigation. Neuron 2024; 112:2581-2599.e23. [PMID: 38795708 DOI: 10.1016/j.neuron.2024.04.036] [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: 01/03/2023] [Revised: 01/16/2024] [Accepted: 04/30/2024] [Indexed: 05/28/2024]
Abstract
Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.
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Affiliation(s)
- Chuntao Dan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Brad K Hulse
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Ramya Kappagantula
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Vivek Jayaraman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
| | - Ann M Hermundstad
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
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5
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Morton NJ, Grice M, Kemp S, Grace RC. Non-symbolic estimation of big and small ratios with accurate and noisy feedback. Atten Percept Psychophys 2024; 86:2169-2186. [PMID: 38992321 PMCID: PMC11410853 DOI: 10.3758/s13414-024-02914-6] [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] [Accepted: 05/31/2024] [Indexed: 07/13/2024]
Abstract
The ratio of two magnitudes can take one of two values depending on the order they are operated on: a 'big' ratio of the larger to smaller magnitude, or a 'small' ratio of the smaller to larger. Although big and small ratio scales have different metric properties and carry divergent predictions for perceptual comparison tasks, no psychophysical studies have directly compared them. Two experiments are reported in which subjects implicitly learned to compare pairs of brightnesses and line lengths by non-symbolic feedback based on the scaled big ratio, small ratio or difference of the magnitudes presented. Results of Experiment 1 showed all three operations were learned quickly and estimated with a high degree of accuracy that did not significantly differ across groups or between intensive and extensive modalities, though regressions on individual data suggested an overall predisposition towards differences. Experiment 2 tested whether subjects learned to estimate the operation trained or to associate stimulus pairs with correct responses. For each operation, Gaussian noise was added to the feedback that was constant for repetitions of each pair. For all subjects, coefficients for the added noise component were negative when entered in a regression model alongside the trained differences or ratios, and were statistically significant in 80% of individual cases. Thus, subjects learned to estimate the comparative operations and effectively ignored or suppressed the added noise. These results suggest the perceptual system is highly flexible in its capacity for non-symbolic computation, which may reflect a deeper connection between perceptual structure and mathematics.
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Affiliation(s)
- Nicola J Morton
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand.
| | - Matt Grice
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Simon Kemp
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Randolph C Grace
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand.
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6
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Frank DD, Kronauer DJC. The Budding Neuroscience of Ant Social Behavior. Annu Rev Neurosci 2024; 47:167-185. [PMID: 38603564 DOI: 10.1146/annurev-neuro-083023-102101] [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: 04/13/2024]
Abstract
Ant physiology has been fashioned by 100 million years of social evolution. Ants perform many sophisticated social and collective behaviors yet possess nervous systems similar in schematic and scale to that of the fruit fly Drosophila melanogaster, a popular solitary model organism. Ants are thus attractive complementary subjects to investigate adaptations pertaining to complex social behaviors that are absent in flies. Despite research interest in ant behavior and the neurobiological foundations of sociality more broadly, our understanding of the ant nervous system is incomplete. Recent technical advances have enabled cutting-edge investigations of the nervous system in a fashion that is less dependent on model choice, opening the door for mechanistic social insect neuroscience. In this review, we revisit important aspects of what is known about the ant nervous system and behavior, and we look forward to how functional circuit neuroscience in ants will help us understand what distinguishes solitary animals from highly social ones.
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Affiliation(s)
- Dominic D Frank
- Laboratory of Social Evolution and Behavior, The Rockefeller University, New York, NY, USA; ,
| | - Daniel J C Kronauer
- Howard Hughes Medical Institute, New York, NY, USA
- Laboratory of Social Evolution and Behavior, The Rockefeller University, New York, NY, USA; ,
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7
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Stupski SD, van Breugel F. Wind gates olfaction-driven search states in free flight. Curr Biol 2024:S0960-9822(24)00912-6. [PMID: 39067453 DOI: 10.1016/j.cub.2024.07.009] [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: 03/10/2024] [Revised: 05/08/2024] [Accepted: 07/01/2024] [Indexed: 07/30/2024]
Abstract
For organisms tracking a chemical cue to its source, the motion of their surrounding fluid provides crucial information for success. Swimming and flying animals engaged in olfaction-driven search often start by turning into the direction of an oncoming wind or water current. However, it is unclear how organisms adjust their strategies when directional cues are absent or unreliable, as is often the case in nature. Here, we use the genetic toolkit of Drosophila melanogaster to develop an optogenetic paradigm to deliver temporally precise "virtual" olfactory experiences for free-flying animals in either laminar wind or still air. We first confirm that in laminar wind flies turn upwind. Furthermore, we show that they achieve this using a rapid (∼100 ms) turn, implying that flies estimate the ambient wind direction prior to "surging" upwind. In still air, flies adopt a remarkably stereotyped "sink and circle" search state characterized by ∼60° turns at 3-4 Hz, biased in a consistent direction. Together, our results show that Drosophila melanogaster assesses the presence and direction of ambient wind prior to deploying a distinct search strategy. In both laminar wind and still air, immediately after odor onset, flies decelerate and often perform a rapid turn. Both maneuvers are consistent with predictions from recent control theoretic analyses for how insects may estimate properties of wind while in flight. We suggest that flies may use their deceleration and "anemometric" turn as active sensing maneuvers to rapidly gauge properties of their wind environment before initiating a proximal or upwind search routine.
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Affiliation(s)
- S David Stupski
- Integrative Neuroscience Program, University of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA; Ecology Evolution and Conservation Biology Program, University of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA; Department of Mechanical Engineering, University of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA
| | - Floris van Breugel
- Integrative Neuroscience Program, University of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA; Ecology Evolution and Conservation Biology Program, University of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA; Department of Mechanical Engineering, University of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA.
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8
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Patel RN, Roberts NS, Kempenaers J, Zadel A, Heinze S. Parallel vector memories in the brain of a bee as foundation for flexible navigation. Proc Natl Acad Sci U S A 2024; 121:e2402509121. [PMID: 39008670 PMCID: PMC11287249 DOI: 10.1073/pnas.2402509121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 06/03/2024] [Indexed: 07/17/2024] Open
Abstract
Insects rely on path integration (vector-based navigation) and landmark guidance to perform sophisticated navigational feats, rivaling those seen in mammals. Bees in particular exhibit complex navigation behaviors including creating optimal routes and novel shortcuts between locations, an ability historically indicative of the presence of a cognitive map. A mammalian cognitive map has been widely accepted. However, in insects, the existence of a centralized cognitive map is highly contentious. Using a controlled laboratory assay that condenses foraging behaviors to short distances in walking bumblebees, we reveal that vectors learned during path integration can be transferred to long-term memory, that multiple such vectors can be stored in parallel, and that these vectors can be recalled at a familiar location and used for homeward navigation. These findings demonstrate that bees meet the two fundamental requirements of a vector-based analog of a decentralized cognitive map: Home vectors need to be stored in long-term memory and need to be recalled from remembered locations. Thus, our data demonstrate that bees possess the foundational elements for a vector-based map. By utilizing this relatively simple strategy for spatial organization, insects may achieve high-level navigation behaviors seen in vertebrates with the limited number of neurons in their brains, circumventing the computational requirements associated with the cognitive maps of mammals.
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Affiliation(s)
- Rickesh N. Patel
- Lund Vision Group, Department of Biology, Lund University, Lund22362, Sweden
| | - Natalie S. Roberts
- Lund Vision Group, Department of Biology, Lund University, Lund22362, Sweden
| | - Julian Kempenaers
- Lund Vision Group, Department of Biology, Lund University, Lund22362, Sweden
| | - Ana Zadel
- Lund Vision Group, Department of Biology, Lund University, Lund22362, Sweden
| | - Stanley Heinze
- Lund Vision Group, Department of Biology, Lund University, Lund22362, Sweden
- Nano Lund, Centre for Nanoscience, Lund University, Lund22362, Sweden
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9
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Stupski SD, van Breugel F. Wind Gates Olfaction Driven Search States in Free Flight. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.30.569086. [PMID: 38076971 PMCID: PMC10705368 DOI: 10.1101/2023.11.30.569086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
For organisms tracking a chemical cue to its source, the motion of their surrounding fluid provides crucial information for success. Swimming and flying animals engaged in olfaction driven search often start by turning into the direction of an oncoming wind or water current. However, it is unclear how organisms adjust their strategies when directional cues are absent or unreliable, as is often the case in nature. Here, we use the genetic toolkit of Drosophila melanogaster to develop an optogenetic paradigm to deliver temporally precise "virtual" olfactory experiences for free-flying animals in either laminar wind or still air. We first confirm that in laminar wind flies turn upwind. Furthermore, we show that they achieve this using a rapid (∼100 ms) turn, implying that flies estimate the ambient wind direction prior to "surging" upwind. In still air, flies adopt remarkably stereotyped "sink and circle" search state characterized by ∼60°turns at 3-4 Hz, biased in a consistent direction. Together, our results show that Drosophila melanogaster assess the presence and direction of ambient wind prior to deploying a distinct search strategy. In both laminar wind and still air, immediately after odor onset, flies decelerate and often perform a rapid turn. Both maneuvers are consistent with predictions from recent control theoretic analyses for how insects may estimate properties of wind while in flight. We suggest that flies may use their deceleration and "anemometric" turn as active sensing maneuvers to rapidly gauge properties of their wind environment before initiating a proximal or upwind search routine.
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10
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Treidel LA, Deem KD, Salcedo MK, Dickinson MH, Bruce HS, Darveau CA, Dickerson BH, Ellers O, Glass JR, Gordon CM, Harrison JF, Hedrick TL, Johnson MG, Lebenzon JE, Marden JH, Niitepõld K, Sane SP, Sponberg S, Talal S, Williams CM, Wold ES. Insect Flight: State of the Field and Future Directions. Integr Comp Biol 2024; 64:icae106. [PMID: 38982327 PMCID: PMC11406162 DOI: 10.1093/icb/icae106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2024] Open
Abstract
The evolution of flight in an early winged insect ancestral lineage is recognized as a key adaptation explaining the unparalleled success and diversification of insects. Subsequent transitions and modifications to flight machinery, including secondary reductions and losses, also play a central role in shaping the impacts of insects on broadscale geographic and ecological processes and patterns in the present and future. Given the importance of insect flight, there has been a centuries-long history of research and debate on the evolutionary origins and biological mechanisms of flight. Here, we revisit this history from an interdisciplinary perspective, discussing recent discoveries regarding the developmental origins, physiology, biomechanics, and neurobiology and sensory control of flight in a diverse set of insect models. We also identify major outstanding questions yet to be addressed and provide recommendations for overcoming current methodological challenges faced when studying insect flight, which will allow the field to continue to move forward in new and exciting directions. By integrating mechanistic work into ecological and evolutionary contexts, we hope that this synthesis promotes and stimulates new interdisciplinary research efforts necessary to close the many existing gaps about the causes and consequences of insect flight evolution.
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Affiliation(s)
- Lisa A Treidel
- School of Biological Sciences, University of Nebraska, Lincoln, Lincoln NE, 68588, USA
| | - Kevin D Deem
- Department of Biology, University of Rochester, Rochester NY, 14627, USA
| | - Mary K Salcedo
- Department of Biological and Environmental Engineering, Cornell University, Ithaca NY, 14853, USA
| | - Michael H Dickinson
- Department of Bioengineering, California Institute of Technology, Pasadena CA 91125, USA
| | | | - Charles-A Darveau
- Department of Biology, University of Ottawa, Ottawa Ontario, K1N 6N5, Canada
| | - Bradley H Dickerson
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Olaf Ellers
- Biology Department, Bowdoin College, Brunswick, ME 04011, USA
| | - Jordan R Glass
- Department of Zoology & Physiology, University of Wyoming, Laramie, WY 82070, USA
| | - Caleb M Gordon
- Department of Earth and Planetary Sciences, Yale University, New Haven, CT 06520-8109, USA
| | - Jon F Harrison
- School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA
| | - Tyson L Hedrick
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Meredith G Johnson
- School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA
| | - Jacqueline E Lebenzon
- Department of Integrative Biology, University of California, Berkeley, Berkeley CA, 94720, USA
| | - James H Marden
- Department of Biology, Pennsylvania State University, University Park, PA 16803, USA
| | | | - Sanjay P Sane
- National Center for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065 India
| | - Simon Sponberg
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Stav Talal
- School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA
| | - Caroline M Williams
- Department of Integrative Biology, University of California, Berkeley, Berkeley CA, 94720, USA
| | - Ethan S Wold
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
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11
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Vilimelis Aceituno P, Dall'Osto D, Pisokas I. Theoretical principles explain the structure of the insect head direction circuit. eLife 2024; 13:e91533. [PMID: 38814703 PMCID: PMC11139481 DOI: 10.7554/elife.91533] [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: 08/02/2023] [Accepted: 03/28/2024] [Indexed: 05/31/2024] Open
Abstract
To navigate their environment, insects need to keep track of their orientation. Previous work has shown that insects encode their head direction as a sinusoidal activity pattern around a ring of neurons arranged in an eight-column structure. However, it is unclear whether this sinusoidal encoding of head direction is just an evolutionary coincidence or if it offers a particular functional advantage. To address this question, we establish the basic mathematical requirements for direction encoding and show that it can be performed by many circuits, all with different activity patterns. Among these activity patterns, we prove that the sinusoidal one is the most noise-resilient, but only when coupled with a sinusoidal connectivity pattern between the encoding neurons. We compare this predicted optimal connectivity pattern with anatomical data from the head direction circuits of the locust and the fruit fly, finding that our theory agrees with experimental evidence. Furthermore, we demonstrate that our predicted circuit can emerge using Hebbian plasticity, implying that the neural connectivity does not need to be explicitly encoded in the genetic program of the insect but rather can emerge during development. Finally, we illustrate that in our theory, the consistent presence of the eight-column organisation of head direction circuits across multiple insect species is not a chance artefact but instead can be explained by basic evolutionary principles.
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Affiliation(s)
| | - Dominic Dall'Osto
- Institute of Neuroinformatics, University of Zürich and ETH ZürichZurichSwitzerland
| | - Ioannis Pisokas
- School of Informatics, University of EdinburghEdinburghUnited Kingdom
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12
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Puri P, Wu ST, Su CY, Aljadeff J. Peripheral preprocessing in Drosophila facilitates odor classification. Proc Natl Acad Sci U S A 2024; 121:e2316799121. [PMID: 38753511 PMCID: PMC11126917 DOI: 10.1073/pnas.2316799121] [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: 10/01/2023] [Accepted: 04/16/2024] [Indexed: 05/18/2024] Open
Abstract
The mammalian brain implements sophisticated sensory processing algorithms along multilayered ("deep") neural networks. Strategies that insects use to meet similar computational demands, while relying on smaller nervous systems with shallow architectures, remain elusive. Using Drosophila as a model, we uncover the algorithmic role of odor preprocessing by a shallow network of compartmentalized olfactory receptor neurons. Each compartment operates as a ratiometric unit for specific odor-mixtures. This computation arises from a simple mechanism: electrical coupling between two differently sized neurons. We demonstrate that downstream synaptic connectivity is shaped to optimally leverage amplification of a hedonic value signal in the periphery. Furthermore, peripheral preprocessing is shown to markedly improve novel odor classification in a higher brain center. Together, our work highlights a far-reaching functional role of the sensory periphery for downstream processing. By elucidating the implementation of powerful computations by a shallow network, we provide insights into general principles of efficient sensory processing algorithms.
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Affiliation(s)
- Palka Puri
- Department of Physics, University of California, San Diego, La Jolla, CA92093
| | - Shiuan-Tze Wu
- Department of Neurobiology, University of California, San Diego, La Jolla, CA92093
| | - Chih-Ying Su
- Department of Neurobiology, University of California, San Diego, La Jolla, CA92093
| | - Johnatan Aljadeff
- Department of Neurobiology, University of California, San Diego, La Jolla, CA92093
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13
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Eckstein N, Bates AS, Champion A, Du M, Yin Y, Schlegel P, Lu AKY, Rymer T, Finley-May S, Paterson T, Parekh R, Dorkenwald S, Matsliah A, Yu SC, McKellar C, Sterling A, Eichler K, Costa M, Seung S, Murthy M, Hartenstein V, Jefferis GSXE, Funke J. Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster. Cell 2024; 187:2574-2594.e23. [PMID: 38729112 PMCID: PMC11106717 DOI: 10.1016/j.cell.2024.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 10/04/2023] [Accepted: 03/13/2024] [Indexed: 05/12/2024]
Abstract
High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.
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Affiliation(s)
- Nils Eckstein
- HHMI Janelia Research Campus, Ashburn, VA, USA; Institute of Neuroinformatics UZH/ETHZ, Zurich, Switzerland
| | - Alexander Shakeel Bates
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3SR, UK; Department of Neurobiology and Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Andrew Champion
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Michelle Du
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | - Yijie Yin
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | | | | | | | | | | | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Arie Matsliah
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Szi-Chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Claire McKellar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Amy Sterling
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Katharina Eichler
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Volker Hartenstein
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - 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.
| | - Jan Funke
- HHMI Janelia Research Campus, Ashburn, VA, USA.
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14
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Heinze S. Neuroethology: Decoding the waggle dance. Curr Biol 2024; 34:R313-R315. [PMID: 38653197 DOI: 10.1016/j.cub.2024.02.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
A new study combining high-speed video recordings and computational modeling has revealed an overlooked feature of the famous honeybee waggle dance, yielding the first biologically plausible neural circuit model of how the information transmitted via the waggle dance could be assimilated by the follower bees.
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Affiliation(s)
- Stanley Heinze
- Lund Vision Group and NanoLund, Lund University, Lund, Sweden.
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15
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Hadjitofi A, Webb B. Dynamic antennal positioning allows honeybee followers to decode the dance. Curr Biol 2024; 34:1772-1779.e4. [PMID: 38479387 DOI: 10.1016/j.cub.2024.02.045] [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: 01/17/2024] [Revised: 02/16/2024] [Accepted: 02/19/2024] [Indexed: 04/25/2024]
Abstract
The honeybee waggle dance has been widely studied as a communication system, yet we know little about how nestmates assimilate the information needed to navigate toward the signaled resource. They are required to detect the dancer's orientation relative to gravity and duration of the waggle phase and translate this into a flight vector with a direction relative to the sun1 and distance from the hive.2,3 Moreover, they appear capable of doing so from varied, dynamically changing positions around the dancer. Using high-speed, high-resolution video, we have uncovered a previously unremarked correlation between antennal position and the relative body axes of dancer and follower bees. Combined with new information about antennal inputs4,5 and spatial encoding in the insect central complex,6,7 we show how a neural circuit first proposed to underlie path integration could be adapted to decoding the dance and acquiring the signaled information as a flight vector that can be followed to the resource. This provides the first plausible account of how the bee brain could support the interpretation of its dance language.
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Affiliation(s)
- Anna Hadjitofi
- School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK.
| | - Barbara Webb
- School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK.
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16
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Secer G, Knierim JJ, Cowan NJ. Continuous Bump Attractor Networks Require Explicit Error Coding for Gain Recalibration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.12.579874. [PMID: 38562699 PMCID: PMC10983875 DOI: 10.1101/2024.02.12.579874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Representations of continuous variables are crucial to create internal models of the external world. A prevailing model of how the brain maintains these representations is given by continuous bump attractor networks (CBANs) in a broad range of brain functions across different areas, such as spatial navigation in hippocampal/entorhinal circuits and working memory in prefrontal cortex. Through recurrent connections, a CBAN maintains a persistent activity bump, whose peak location can vary along a neural space, corresponding to different values of a continuous variable. To track the value of a continuous variable changing over time, a CBAN updates the location of its activity bump based on inputs that encode the changes in the continuous variable (e.g., movement velocity in the case of spatial navigation)-a process akin to mathematical integration. This integration process is not perfect and accumulates error over time. For error correction, CBANs can use additional inputs providing ground-truth information about the continuous variable's correct value (e.g., visual landmarks for spatial navigation). These inputs enable the network dynamics to automatically correct any representation error. Recent experimental work on hippocampal place cells has shown that, beyond correcting errors, ground-truth inputs also fine-tune the gain of the integration process, a crucial factor that links the change in the continuous variable to the updating of the activity bump's location. However, existing CBAN models lack this plasticity, offering no insights into the neural mechanisms and representations involved in the recalibration of the integration gain. In this paper, we explore this gap by using a ring attractor network, a specific type of CBAN, to model the experimental conditions that demonstrated gain recalibration in hippocampal place cells. Our analysis reveals the necessary conditions for neural mechanisms behind gain recalibration within a CBAN. Unlike error correction, which occurs through network dynamics based on ground-truth inputs, gain recalibration requires an additional neural signal that explicitly encodes the error in the network's representation via a rate code. Finally, we propose a modified ring attractor network as an example CBAN model that verifies our theoretical findings. Combining an error-rate code with Hebbian synaptic plasticity, this model achieves recalibration of integration gain in a CBAN, ensuring accurate representation for continuous variables.
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Affiliation(s)
- Gorkem Secer
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA
| | - James J Knierim
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Noah J Cowan
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
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17
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Borzou A, Miller SN, Hommel JD, Schwarz JM. Cocaine diminishes functional network robustness and destabilizes the energy landscape of neuronal activity in the medial prefrontal cortex. PNAS NEXUS 2024; 3:pgae092. [PMID: 38476665 PMCID: PMC10929585 DOI: 10.1093/pnasnexus/pgae092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 02/13/2024] [Indexed: 03/14/2024]
Abstract
We present analysis of neuronal activity recordings from a subset of neurons in the medial prefrontal cortex of rats before and after the administration of cocaine. Using an underlying modern Hopfield model as a description for the neuronal network, combined with a machine learning approach, we compute the underlying functional connectivity of the neuronal network. We find that the functional connectivity changes after the administration of cocaine with both functional-excitatory and functional-inhibitory neurons being affected. Using conventional network analysis, we find that the diameter of the graph, or the shortest length between the two most distant nodes, increases with cocaine, suggesting that the neuronal network is less robust. We also find that the betweenness centrality scores for several of the functional-excitatory and functional-inhibitory neurons decrease significantly, while other scores remain essentially unchanged, to also suggest that the neuronal network is less robust. Finally, we study the distribution of neuronal activity and relate it to energy to find that cocaine drives the neuronal network towards destabilization in the energy landscape of neuronal activation. While this destabilization is presumably temporary given one administration of cocaine, perhaps this initial destabilization indicates a transition towards a new stable state with repeated cocaine administration. However, such analyses are useful more generally to understand how neuronal networks respond to perturbations.
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Affiliation(s)
- Ahmad Borzou
- Department of Physics and BioInspired Institute, Syracuse University, Syracuse, NY 13244, USA
- CompuFlair, Houston, TX 77064, USA
| | - Sierra N Miller
- Department of Pharmacology and Toxicology, Center for Addiction Sciences and Therapeutics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Jonathan D Hommel
- Department of Pharmacology and Toxicology, Center for Addiction Sciences and Therapeutics, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - J M Schwarz
- Department of Physics and BioInspired Institute, Syracuse University, Syracuse, NY 13244, USA
- Indian Creek Farm, Ithaca, NY 14850, USA
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18
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Brezovec BE, Berger AB, Hao YA, Chen F, Druckmann S, Clandinin TR. Mapping the neural dynamics of locomotion across the Drosophila brain. Curr Biol 2024; 34:710-726.e4. [PMID: 38242122 DOI: 10.1016/j.cub.2023.12.063] [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: 08/16/2023] [Revised: 11/13/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024]
Abstract
Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.
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Affiliation(s)
- Bella E Brezovec
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Andrew B Berger
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Yukun A Hao
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Feng Chen
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University, Fairchild D200, 299 W. Campus Drive, Stanford, CA 94305, USA.
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19
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Ding SS, Fox JL, Gordus A, Joshi A, Liao JC, Scholz M. Fantastic beasts and how to study them: rethinking experimental animal behavior. J Exp Biol 2024; 227:jeb247003. [PMID: 38372042 PMCID: PMC10911175 DOI: 10.1242/jeb.247003] [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] [Indexed: 02/20/2024]
Abstract
Humans have been trying to understand animal behavior at least since recorded history. Recent rapid development of new technologies has allowed us to make significant progress in understanding the physiological and molecular mechanisms underlying behavior, a key goal of neuroethology. However, there is a tradeoff when studying animal behavior and its underlying biological mechanisms: common behavior protocols in the laboratory are designed to be replicable and controlled, but they often fail to encompass the variability and breadth of natural behavior. This Commentary proposes a framework of 10 key questions that aim to guide researchers in incorporating a rich natural context into their experimental design or in choosing a new animal study system. The 10 questions cover overarching experimental considerations that can provide a template for interspecies comparisons, enable us to develop studies in new model organisms and unlock new experiments in our quest to understand behavior.
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Affiliation(s)
- Siyu Serena Ding
- Max Planck Institute of Animal Behavior, 78464 Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany
| | - Jessica L. Fox
- Department of Biology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Andrew Gordus
- Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Abhilasha Joshi
- Departments of Physiology and Psychiatry, University of California, San Francisco, CA 94158, USA
| | - James C. Liao
- Department of Biology, The Whitney Laboratory for Marine Bioscience, University of Florida, St. Augustine, FL 32080, USA
| | - Monika Scholz
- Max Planck Research Group Neural Information Flow, Max Planck Institute for Neurobiology of Behavior – caesar, 53175 Bonn, Germany
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20
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Hamid A, Gattuso H, Caglar AN, Pillai M, Steele T, Gonzalez A, Nagel K, Syed MH. The conserved RNA-binding protein Imp is required for the specification and function of olfactory navigation circuitry in Drosophila. Curr Biol 2024; 34:473-488.e6. [PMID: 38181792 PMCID: PMC10872534 DOI: 10.1016/j.cub.2023.12.020] [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: 05/19/2023] [Revised: 11/14/2023] [Accepted: 12/07/2023] [Indexed: 01/07/2024]
Abstract
Complex behaviors depend on the precise developmental specification of neuronal circuits, but the relationship between genetic programs for neural development, circuit structure, and behavioral output is often unclear. The central complex (CX) is a conserved sensory-motor integration center in insects, which governs many higher-order behaviors and largely derives from a small number of type II neural stem cells (NSCs). Here, we show that Imp, a conserved IGF-II mRNA-binding protein expressed in type II NSCs, plays a role in specifying essential components of CX olfactory navigation circuitry. We show the following: (1) that multiple components of olfactory navigation circuitry arise from type II NSCs. (2) Manipulating Imp expression in type II NSCs alters the number and morphology of many of these circuit elements, with the most potent effects on neurons targeting the ventral layers of the fan-shaped body (FB). (3) Imp regulates the specification of Tachykinin-expressing ventral FB input neurons. (4) Imp is required in type II NSCs for establishing proper morphology of the CX neuropil structures. (5) Loss of Imp in type II NSCs abolishes upwind orientation to attractive odor while leaving locomotion and odor-evoked regulation of movement intact. Taken together, our findings establish that a temporally expressed gene can regulate the expression of a complex behavior by developmentally regulating the specification of multiple circuit components and provides a first step toward a developmental dissection of the CX and its roles in behavior.
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Affiliation(s)
- Aisha Hamid
- Department of Biology, University of New Mexico, 219 Yale Blvd NE, Albuquerque, NM 87131, USA
| | - Hannah Gattuso
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA
| | - Aysu Nora Caglar
- Department of Biology, University of New Mexico, 219 Yale Blvd NE, Albuquerque, NM 87131, USA
| | - Midhula Pillai
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA
| | - Theresa Steele
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA
| | - Alexa Gonzalez
- Department of Biology, University of New Mexico, 219 Yale Blvd NE, Albuquerque, NM 87131, USA
| | - Katherine Nagel
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA.
| | - Mubarak Hussain Syed
- Department of Biology, University of New Mexico, 219 Yale Blvd NE, Albuquerque, NM 87131, USA.
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21
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Westeinde EA, Kellogg E, Dawson PM, Lu J, Hamburg L, Midler B, Druckmann S, Wilson RI. Transforming a head direction signal into a goal-oriented steering command. Nature 2024; 626:819-826. [PMID: 38326621 PMCID: PMC10881397 DOI: 10.1038/s41586-024-07039-2] [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: 11/10/2022] [Accepted: 01/05/2024] [Indexed: 02/09/2024]
Abstract
To navigate, we must continuously estimate the direction we are headed in, and we must correct deviations from our goal1. Direction estimation is accomplished by ring attractor networks in the head direction system2,3. However, we do not fully understand how the sense of direction is used to guide action. Drosophila connectome analyses4,5 reveal three cell populations (PFL3R, PFL3L and PFL2) that connect the head direction system to the locomotor system. Here we use imaging, electrophysiology and chemogenetic stimulation during navigation to show how these populations function. Each population receives a shifted copy of the head direction vector, such that their three reference frames are shifted approximately 120° relative to each other. Each cell type then compares its own head direction vector with a common goal vector; specifically, it evaluates the congruence of these vectors via a nonlinear transformation. The output of all three cell populations is then combined to generate locomotor commands. PFL3R cells are recruited when the fly is oriented to the left of its goal, and their activity drives rightward turning; the reverse is true for PFL3L. Meanwhile, PFL2 cells increase steering speed, and are recruited when the fly is oriented far from its goal. PFL2 cells adaptively increase the strength of steering as directional error increases, effectively managing the tradeoff between speed and accuracy. Together, our results show how a map of space in the brain can be combined with an internal goal to generate action commands, via a transformation from world-centric coordinates to body-centric coordinates.
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Affiliation(s)
| | - Emily Kellogg
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Paul M Dawson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Jenny Lu
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Lydia Hamburg
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Benjamin Midler
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
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22
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Mussells Pires P, Zhang L, Parache V, Abbott LF, Maimon G. Converting an allocentric goal into an egocentric steering signal. Nature 2024; 626:808-818. [PMID: 38326612 PMCID: PMC10881393 DOI: 10.1038/s41586-023-07006-3] [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: 11/10/2022] [Accepted: 12/19/2023] [Indexed: 02/09/2024]
Abstract
Neuronal signals that are relevant for spatial navigation have been described in many species1-10. However, a circuit-level understanding of how such signals interact to guide navigational behaviour is lacking. Here we characterize a neuronal circuit in the Drosophila central complex that compares internally generated estimates of the heading and goal angles of the fly-both of which are encoded in world-centred (allocentric) coordinates-to generate a body-centred (egocentric) steering signal. Past work has suggested that the activity of EPG neurons represents the fly's moment-to-moment angular orientation, or heading angle, during navigation2,11. An animal's moment-to-moment heading angle, however, is not always aligned with its goal angle-that is, the allocentric direction in which it wishes to progress forward. We describe FC2 cells12, a second set of neurons in the Drosophila brain with activity that correlates with the fly's goal angle. Focal optogenetic activation of FC2 neurons induces flies to orient along experimenter-defined directions as they walk forward. EPG and FC2 neurons connect monosynaptically to a third neuronal class, PFL3 cells12,13. We found that individual PFL3 cells show conjunctive, spike-rate tuning to both the heading angle and the goal angle during goal-directed navigation. Informed by the anatomy and physiology of these three cell classes, we develop a model that explains how this circuit compares allocentric heading and goal angles to build an egocentric steering signal in the PFL3 output terminals. Quantitative analyses and optogenetic manipulations of PFL3 activity support the model. Finally, using a new navigational memory task, we show that flies expressing disruptors of synaptic transmission in subsets of PFL3 cells have a reduced ability to orient along arbitrary goal directions, with an effect size in quantitative accordance with the prediction of our model. The biological circuit described here reveals how two population-level allocentric signals are compared in the brain to produce an egocentric output signal that is appropriate for motor control.
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Affiliation(s)
- Peter Mussells Pires
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - Lingwei Zhang
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - Victoria Parache
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - L F Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY, USA
| | - Gaby Maimon
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA.
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23
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Graham JA, Dumont JR, Winter SS, Brown JE, LaChance PA, Amon CC, Farnes KB, Morris AJ, Streltzov NA, Taube JS. Angular Head Velocity Cells within Brainstem Nuclei Projecting to the Head Direction Circuit. J Neurosci 2023; 43:8403-8424. [PMID: 37871964 PMCID: PMC10711713 DOI: 10.1523/jneurosci.0581-23.2023] [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: 03/25/2023] [Revised: 09/27/2023] [Accepted: 10/17/2023] [Indexed: 10/25/2023] Open
Abstract
The sense of orientation of an animal is derived from the head direction (HD) system found in several limbic structures and depends on an intact vestibular labyrinth. However, how the vestibular system influences the generation and updating of the HD signal remains poorly understood. Anatomical and lesion studies point toward three key brainstem nuclei as key components for generating the HD signal-nucleus prepositus hypoglossi, supragenual nucleus, and dorsal paragigantocellularis reticular nuclei. Collectively, these nuclei are situated between the vestibular nuclei and the dorsal tegmental and lateral mammillary nuclei, which are thought to serve as the origin of the HD signal. To determine the types of information these brain areas convey to the HD network, we recorded neurons from these regions while female rats actively foraged in a cylindrical enclosure or were restrained and rotated passively. During foraging, a large subset of cells in all three nuclei exhibited activity that correlated with the angular head velocity (AHV) of the rat. Two fundamental types of AHV cells were observed; (1) symmetrical AHV cells increased or decreased their firing with increases in AHV regardless of the direction of rotation, and (2) asymmetrical AHV cells responded differentially to clockwise and counterclockwise head rotations. When rats were passively rotated, some AHV cells remained sensitive to AHV, whereas firing was attenuated in other cells. In addition, a large number of AHV cells were modulated by linear head velocity. These results indicate the types of information conveyed from the vestibular nuclei that are responsible for generating the HD signal.SIGNIFICANCE STATEMENT Extracellular recording of brainstem nuclei (nucleus prepositus hypoglossi, supragenual nucleus, and dorsal paragigantocellularis reticular nucleus) that project to the head direction circuit identified different types of AHV cells while rats freely foraged in a cylindrical environment. The firing of many cells was also modulated by linear velocity. When rats were restrained and passively rotated, some cells remained sensitive to AHV, whereas others had attenuated firing. These brainstem nuclei provide critical information about the rotational movement of the head of the rat in the azimuthal plane.
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Affiliation(s)
- Jalina A Graham
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Julie R Dumont
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Shawn S Winter
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Joel E Brown
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Patrick A LaChance
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Carly C Amon
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Kara B Farnes
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Ashlyn J Morris
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Nicholas A Streltzov
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
| | - Jeffrey S Taube
- Department of Psychological Brain Sciences, Dartmouth College, Dartmouth, New Hampshire 03755
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24
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Beetz MJ, El Jundi B. The neurobiology of the Monarch butterfly compass. CURRENT OPINION IN INSECT SCIENCE 2023; 60:101109. [PMID: 37660836 DOI: 10.1016/j.cois.2023.101109] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/17/2023] [Accepted: 08/28/2023] [Indexed: 09/05/2023]
Abstract
Monarch butterflies (Danaus plexippus) have become a superb model system to unravel how the tiny insect brain controls an impressive navigation behavior, such as long-distance migration. Moreover, the ability to compare the neural substrate between migratory and nonmigratory Monarch butterflies provides us with an attractive model to specifically study how the insect brain is adapted for migration. We here review our current progress on the neural substrate of spatial orientation in Monarch butterflies and how their spectacular annual migration might be controlled by their brain. We also discuss open research questions, the answers to which will provide important missing pieces to obtain a full picture of insect migration - from the perception of orientation cues to the neural control of migration.
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Affiliation(s)
- M Jerome Beetz
- Zoology II, Biocenter, University of Würzburg, Würzburg, Germany
| | - Basil El Jundi
- Animal Physiology, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway.
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25
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Goulard R, Heinze S, Webb B. Emergent spatial goals in an integrative model of the insect central complex. PLoS Comput Biol 2023; 19:e1011480. [PMID: 38109465 PMCID: PMC10760860 DOI: 10.1371/journal.pcbi.1011480] [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: 08/31/2023] [Revised: 01/02/2024] [Accepted: 12/01/2023] [Indexed: 12/20/2023] Open
Abstract
The insect central complex appears to encode and process spatial information through vector manipulation. Here, we draw on recent insights into circuit structure to fuse previous models of sensory-guided navigation, path integration and vector memory. Specifically, we propose that the allocentric encoding of location provided by path integration creates a spatially stable anchor for converging sensory signals that is relevant in multiple behavioural contexts. The allocentric reference frame given by path integration transforms a goal direction into a goal location and we demonstrate through modelling that it can enhance approach of a sensory target in noisy, cluttered environments or with temporally sparse stimuli. We further show the same circuit can improve performance in the more complex navigational task of route following. The model suggests specific functional roles for circuit elements of the central complex that helps explain their high preservation across insect species.
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Affiliation(s)
- Roman Goulard
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden
| | - Stanley Heinze
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden
| | - Barbara Webb
- Institute for Perception, Action, and Behaviour, School of Informatics, University of Edinburgh, Edinburgh, Scotland, United Kingdom
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26
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Ishida IG, Sethi S, Mohren TL, Abbott L, Maimon G. Neuronal calcium spikes enable vector inversion in the Drosophila brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.24.568537. [PMID: 38077032 PMCID: PMC10705278 DOI: 10.1101/2023.11.24.568537] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
A typical neuron signals to downstream cells when it is depolarized and firing sodium spikes. Some neurons, however, also fire calcium spikes when hyperpolarized. The function of such bidirectional signaling remains unclear in most circuits. Here we show how a neuron class that participates in vector computation in the fly central complex employs hyperpolarization-elicited calcium spikes to invert two-dimensional mathematical vectors. When cells switch from firing sodium to calcium spikes, this leads to a ~180° realignment between the vector encoded in the neuronal population and the fly's internal heading signal, thus inverting the vector. We show that the calcium spikes rely on the T-type calcium channel Ca-α1T, and argue, via analytical and experimental approaches, that these spikes enable vector computations in portions of angular space that would otherwise be inaccessible. These results reveal a seamless interaction between molecular, cellular and circuit properties for implementing vector math in the brain.
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Affiliation(s)
- Itzel G. Ishida
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
| | - Sachin Sethi
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
| | - Thomas L. Mohren
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
| | - L.F. Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York NY, USA
| | - Gaby Maimon
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York NY, USA
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27
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Castegnaro A, Ji Z, Rudzka K, Chan D, Burgess N. Overestimation in angular path integration precedes Alzheimer's dementia. Curr Biol 2023; 33:4650-4661.e7. [PMID: 37827151 PMCID: PMC10957396 DOI: 10.1016/j.cub.2023.09.047] [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: 06/09/2023] [Revised: 08/21/2023] [Accepted: 09/20/2023] [Indexed: 10/14/2023]
Abstract
Path integration (PI) is impaired early in Alzheimer's disease (AD) but reflects multiple sub-processes that may be differentially sensitive to AD. To characterize these sub-processes, we developed a novel generative linear-angular model of PI (GLAMPI) to fit the inbound paths of healthy elderly participants performing triangle completion, a popular PI task, in immersive virtual reality with real movement. The model fits seven parameters reflecting the encoding, calculation, and production errors associated with inaccuracies in PI. We compared these parameters across younger and older participants and patients with mild cognitive impairment (MCI), including those with (MCI+) and without (MCI-) cerebrospinal fluid biomarkers of AD neuropathology. MCI patients showed overestimation of the angular turn in the outbound path and more variable inbound distances and directions compared with healthy elderly. MCI+ were best distinguished from MCI- patients by overestimation of outbound turns and more variable inbound directions. Our results suggest that overestimation of turning underlies the PI errors seen in patients with early AD, indicating specific neural pathways and diagnostic behaviors for further research.
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Affiliation(s)
- Andrea Castegnaro
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK; UCL Queen Square Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK
| | - Zilong Ji
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Haidian District, Beijing 100871, China
| | - Katarzyna Rudzka
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK
| | - Dennis Chan
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK
| | - Neil Burgess
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK; UCL Queen Square Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK.
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28
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Moroz LL, Romanova DY. Chemical cognition: chemoconnectomics and convergent evolution of integrative systems in animals. Anim Cogn 2023; 26:1851-1864. [PMID: 38015282 PMCID: PMC11106658 DOI: 10.1007/s10071-023-01833-7] [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] [Accepted: 11/16/2023] [Indexed: 11/29/2023]
Abstract
Neurons underpin cognition in animals. However, the roots of animal cognition are elusive from both mechanistic and evolutionary standpoints. Two conceptual frameworks both highlight and promise to address these challenges. First, we discuss evidence that animal neural and other integrative systems evolved more than once (convergent evolution) within basal metazoan lineages, giving us unique experiments by Nature for future studies. The most remarkable examples are neural systems in ctenophores and neuroid-like systems in placozoans and sponges. Second, in addition to classical synaptic wiring, a chemical connectome mediated by hundreds of signal molecules operates in tandem with neurons and is the most information-rich source of emerging properties and adaptability. The major gap-dynamic, multifunctional chemical micro-environments in nervous systems-is not understood well. Thus, novel tools and information are needed to establish mechanistic links between orchestrated, yet cell-specific, volume transmission and behaviors. Uniting what we call chemoconnectomics and analyses of the cellular bases of behavior in basal metazoan lineages arguably would form the foundation for deciphering the origins and early evolution of elementary cognition and intelligence.
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Affiliation(s)
- Leonid L Moroz
- Department of Neuroscience, University of Florida, Gainesville, USA.
- Whitney Laboratory for Marine Bioscience, University of Florida, Saint Augustine, USA.
| | - Daria Y Romanova
- Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russia
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29
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Vargas-Vargas IL, Pérez-Hernández E, González D, Rosetti MF, Contreras-Galindo J, Roldán-Roldán G. Evidence of long-term allocentric spatial memory in the Terrestrial Hermit Crab Coenobita compressus. PLoS One 2023; 18:e0293358. [PMID: 37883496 PMCID: PMC10602228 DOI: 10.1371/journal.pone.0293358] [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: 03/14/2023] [Accepted: 10/10/2023] [Indexed: 10/28/2023] Open
Abstract
Spatial learning is a complex cognitive skill and ecologically important trait scarcely studied in crustaceans. We investigated the ability of the Pacific (Ecuadorian) hermit crab Coenobita compressus, to learn an allocentric spatial task using a palatable novel food as reward. Crabs were trained to locate the reward in a single session of eleven consecutive trials and tested subsequently, for short- (5 min) and long-term memory 1, 3 and 7 days later. Our results indicate that crabs were able to learn the location of the reward as they showed a reduction in the time required to find the food whenever it was present, suggesting a visuo-spatial and olfactory cue-guided task resolution. Moreover, crabs also remember the location of the reward up to 7 days after training using spatial cues only (without the food), as evidenced by the longer investigation time they spent in the learned food location than in any other part of the experimental arena, suggesting a visuo-spatial memory formation. This study represents the first description of allocentric spatial long-term memory in a terrestrial hermit crab.
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Affiliation(s)
- Ilse Lorena Vargas-Vargas
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Estefany Pérez-Hernández
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Daniel González
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Marcos Francisco Rosetti
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico
- Instituto National de Psiquiatría, Ramón de la Fuente Muñiz, Mexico City, Mexico
| | | | - Gabriel Roldán-Roldán
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
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30
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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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31
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Wani AR, Chowdhury B, Luong J, Chaya GM, Patel K, Isaacman-Beck J, Shafer O, Kayser MS, Syed MH. Stem cell-specific ecdysone signaling regulates the development and function of a Drosophila sleep homeostat. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.29.560022. [PMID: 37873323 PMCID: PMC10592846 DOI: 10.1101/2023.09.29.560022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Complex behaviors arise from neural circuits that are assembled from diverse cell types. Sleep is a conserved and essential behavior, yet little is known regarding how the nervous system generates neuron types of the sleep-wake circuit. Here, we focus on the specification of Drosophila sleep-promoting neurons-long-field tangential input neurons that project to the dorsal layers of the fan-shaped body neuropil in the central complex (CX). We use lineage analysis and genetic birth dating to identify two bilateral Type II neural stem cells that generate these dorsal fan-shaped body (dFB) neurons. We show that adult dFB neurons express Ecdysone-induced protein E93, and loss of Ecdysone signaling or E93 in Type II NSCs results in the misspecification of the adult dFB neurons. Finally, we show that E93 knockdown in Type II NSCs affects adult sleep behavior. Our results provide insight into how extrinsic hormonal signaling acts on NSCs to generate neuronal diversity required for adult sleep behavior. These findings suggest that some adult sleep disorders might derive from defects in stem cell-specific temporal neurodevelopmental programs.
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Affiliation(s)
- Adil R Wani
- Neural Diversity Lab, Department of Biology, University of New Mexico, 219 Yale Blvd Ne, 87131 Albuquerque, NM, USA
| | - Budhaditya Chowdhury
- The Advanced Science Research Center, City University of New York, New York, NY 10031, USA
| | - Jenny Luong
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Gonzalo Morales Chaya
- Neural Diversity Lab, Department of Biology, University of New Mexico, 219 Yale Blvd Ne, 87131 Albuquerque, NM, USA
| | - Krishna Patel
- Neural Diversity Lab, Department of Biology, University of New Mexico, 219 Yale Blvd Ne, 87131 Albuquerque, NM, USA
| | | | - Orie Shafer
- The Advanced Science Research Center, City University of New York, New York, NY 10031, USA
| | - Matthew S. Kayser
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
- Chronobiology Sleep Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Mubarak Hussain Syed
- Neural Diversity Lab, Department of Biology, University of New Mexico, 219 Yale Blvd Ne, 87131 Albuquerque, NM, USA
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32
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Parra-Barrero E, Vijayabaskaran S, Seabrook E, Wiskott L, Cheng S. A map of spatial navigation for neuroscience. Neurosci Biobehav Rev 2023; 152:105200. [PMID: 37178943 DOI: 10.1016/j.neubiorev.2023.105200] [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: 01/25/2023] [Revised: 04/13/2023] [Accepted: 04/24/2023] [Indexed: 05/15/2023]
Abstract
Spatial navigation has received much attention from neuroscientists, leading to the identification of key brain areas and the discovery of numerous spatially selective cells. Despite this progress, our understanding of how the pieces fit together to drive behavior is generally lacking. We argue that this is partly caused by insufficient communication between behavioral and neuroscientific researchers. This has led the latter to under-appreciate the relevance and complexity of spatial behavior, and to focus too narrowly on characterizing neural representations of space-disconnected from the computations these representations are meant to enable. We therefore propose a taxonomy of navigation processes in mammals that can serve as a common framework for structuring and facilitating interdisciplinary research in the field. Using the taxonomy as a guide, we review behavioral and neural studies of spatial navigation. In doing so, we validate the taxonomy and showcase its usefulness in identifying potential issues with common experimental approaches, designing experiments that adequately target particular behaviors, correctly interpreting neural activity, and pointing to new avenues of research.
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Affiliation(s)
- Eloy Parra-Barrero
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany; International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Sandhiya Vijayabaskaran
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany
| | - Eddie Seabrook
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany
| | - Laurenz Wiskott
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany; International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Sen Cheng
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Bochum, Germany; International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany.
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33
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Sizemore TR, Jonaitis J, Dacks AM. Heterogeneous receptor expression underlies non-uniform peptidergic modulation of olfaction in Drosophila. Nat Commun 2023; 14:5280. [PMID: 37644052 PMCID: PMC10465596 DOI: 10.1038/s41467-023-41012-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023] Open
Abstract
Sensory systems are dynamically adjusted according to the animal's ongoing needs by neuromodulators, such as neuropeptides. Neuropeptides are often widely-distributed throughout sensory networks, but it is unclear whether such neuropeptides uniformly modulate network activity. Here, we leverage the Drosophila antennal lobe (AL) to resolve whether myoinhibitory peptide (MIP) uniformly modulates AL processing. Despite being uniformly distributed across the AL, MIP decreases olfactory input to some glomeruli, while increasing olfactory input to other glomeruli. We reveal that a heterogeneous ensemble of local interneurons (LNs) are the sole source of AL MIP, and show that differential expression of the inhibitory MIP receptor across glomeruli allows MIP to act on distinct intraglomerular substrates. Our findings demonstrate how even a seemingly simple case of modulation can have complex consequences on network processing by acting non-uniformly within different components of the overall network.
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Affiliation(s)
- Tyler R Sizemore
- Department of Biology, Life Sciences Building, West Virginia University, Morgantown, WV, 26506, USA.
- Department of Molecular, Cellular, and Developmental Biology, Yale Science Building, Yale University, New Haven, CT, 06520-8103, USA.
| | - Julius Jonaitis
- Department of Biology, Life Sciences Building, West Virginia University, Morgantown, WV, 26506, USA
| | - Andrew M Dacks
- Department of Biology, Life Sciences Building, West Virginia University, Morgantown, WV, 26506, USA.
- Department of Neuroscience, West Virginia University, Morgantown, WV, 26506, USA.
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34
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Dallmann CJ, Dickerson BH, Simpson JH, Wyart C, Jayaram K. Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward. Integr Comp Biol 2023; 63:450-463. [PMID: 37279901 PMCID: PMC10445419 DOI: 10.1093/icb/icad057] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/10/2023] [Accepted: 05/24/2023] [Indexed: 06/08/2023] Open
Abstract
While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and outside the body-as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together.
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Affiliation(s)
- Chris J Dallmann
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Bradley H Dickerson
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Julie H Simpson
- Department of Molecular, Cellular, and Developmental Biology and Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Claire Wyart
- Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, Paris 75005, France
| | - Kaushik Jayaram
- Paul M Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO 80309, USA
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35
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Sun X, Fu Q, Peng J, Yue S. An insect-inspired model facilitating autonomous navigation by incorporating goal approaching and collision avoidance. Neural Netw 2023; 165:106-118. [PMID: 37285728 DOI: 10.1016/j.neunet.2023.05.033] [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: 05/23/2022] [Revised: 03/17/2023] [Accepted: 05/17/2023] [Indexed: 06/09/2023]
Abstract
Being one of the most fundamental and crucial capacity of robots and animals, autonomous navigation that consists of goal approaching and collision avoidance enables completion of various tasks while traversing different environments. In light of the impressive navigational abilities of insects despite their tiny brains compared to mammals, the idea of seeking solutions from insects for the two key problems of navigation, i.e., goal approaching and collision avoidance, has fascinated researchers and engineers for many years. However, previous bio-inspired studies have focused on merely one of these two problems at one time. Insect-inspired navigation algorithms that synthetically incorporate both goal approaching and collision avoidance, and studies that investigate the interactions of these two mechanisms in the context of sensory-motor closed-loop autonomous navigation are lacking. To fill this gap, we propose an insect-inspired autonomous navigation algorithm to integrate the goal approaching mechanism as the global working memory inspired by the sweat bee's path integration (PI) mechanism, and the collision avoidance model as the local immediate cue built upon the locust's lobula giant movement detector (LGMD) model. The presented algorithm is utilized to drive agents to complete navigation task in a sensory-motor closed-loop manner within a bounded static or dynamic environment. Simulation results demonstrate that the synthetic algorithm is capable of guiding the agent to complete challenging navigation tasks in a robust and efficient way. This study takes the first tentative step to integrate the insect-like navigation mechanisms with different functionalities (i.e., global goal and local interrupt) into a coordinated control system that future research avenues could build upon.
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Affiliation(s)
- Xuelong Sun
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, 510006, China; Machine Life and Intelligence Research Centre, Guangzhou University, Guangzhou, 510006, China
| | - Qinbing Fu
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, 510006, China; Machine Life and Intelligence Research Centre, Guangzhou University, Guangzhou, 510006, China
| | - Jigen Peng
- School of Mathematics and Information Science, Guangzhou University, Guangzhou, 510006, China; Machine Life and Intelligence Research Centre, Guangzhou University, Guangzhou, 510006, China.
| | - Shigang Yue
- Computational Intelligence Lab (CIL)/School of Computer Science, University of Lincoln, Lincoln, LN6 7TS, United Kingdom; School of Computing and Mathematical Sciences, University of Leicester, Leicester, LE1 7RH, United Kingdom.
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36
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Puri P, Wu ST, Su CY, Aljadeff J. Shallow networks run deep: Peripheral preprocessing facilitates odor classification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.23.550211. [PMID: 37546820 PMCID: PMC10401955 DOI: 10.1101/2023.07.23.550211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The mammalian brain implements sophisticated sensory processing algorithms along multilayered ('deep') neural-networks. Strategies that insects use to meet similar computational demands, while relying on smaller nervous systems with shallow architectures, remain elusive. Using Drosophila as a model, we uncover the algorithmic role of odor preprocessing by a shallow network of compartmentalized olfactory receptor neurons. Each compartment operates as a ratiometric unit for specific odor-mixtures. This computation arises from a simple mechanism: electrical coupling between two differently-sized neurons. We demonstrate that downstream synaptic connectivity is shaped to optimally leverage amplification of a hedonic value signal in the periphery. Furthermore, peripheral preprocessing is shown to markedly improve novel odor classification in a higher brain center. Together, our work highlights a far-reaching functional role of the sensory periphery for downstream processing. By elucidating the implementation of powerful computations by a shallow network, we provide insights into general principles of efficient sensory processing algorithms.
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Affiliation(s)
- Palka Puri
- Department of Physics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Shiuan-Tze Wu
- Department of Neurobiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Chih-Ying Su
- Department of Neurobiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Johnatan Aljadeff
- Department of Neurobiology, University of California San Diego, La Jolla, CA, 92093, USA
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37
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Wilson RI. Neural Networks for Navigation: From Connections to Computations. Annu Rev Neurosci 2023; 46:403-423. [PMID: 37428603 DOI: 10.1146/annurev-neuro-110920-032645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
Many animals can navigate toward a goal they cannot see based on an internal representation of that goal in the brain's spatial maps. These maps are organized around networks with stable fixed-point dynamics (attractors), anchored to landmarks, and reciprocally connected to motor control. This review summarizes recent progress in understanding these networks, focusing on studies in arthropods. One factor driving recent progress is the availability of the Drosophila connectome; however, it is increasingly clear that navigation depends on ongoing synaptic plasticity in these networks. Functional synapses appear to be continually reselected from the set of anatomical potential synapses based on the interaction of Hebbian learning rules, sensory feedback, attractor dynamics, and neuromodulation. This can explain how the brain's maps of space are rapidly updated; it may also explain how the brain can initialize goals as stable fixed points for navigation.
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Affiliation(s)
- Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, Cambridge, Massachusetts, USA;
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38
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Kandimalla P, Omoto JJ, Hong EJ, Hartenstein V. Lineages to circuits: the developmental and evolutionary architecture of information channels into the central complex. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023; 209:679-720. [PMID: 36932234 PMCID: PMC10354165 DOI: 10.1007/s00359-023-01616-y] [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: 10/28/2022] [Revised: 01/27/2023] [Accepted: 01/28/2023] [Indexed: 03/19/2023]
Abstract
The representation and integration of internal and external cues is crucial for any organism to execute appropriate behaviors. In insects, a highly conserved region of the brain, the central complex (CX), functions in the representation of spatial information and behavioral states, as well as the transformation of this information into desired navigational commands. How does this relatively invariant structure enable the incorporation of information from the diversity of anatomical, behavioral, and ecological niches occupied by insects? Here, we examine the input channels to the CX in the context of their development and evolution. Insect brains develop from ~ 100 neuroblasts per hemisphere that divide systematically to form "lineages" of sister neurons, that project to their target neuropils along anatomically characteristic tracts. Overlaying this developmental tract information onto the recently generated Drosophila "hemibrain" connectome and integrating this information with the anatomical and physiological recording of neurons in other species, we observe neuropil and lineage-specific innervation, connectivity, and activity profiles in CX input channels. We posit that the proliferative potential of neuroblasts and the lineage-based architecture of information channels enable the modification of neural networks across existing, novel, and deprecated modalities in a species-specific manner, thus forming the substrate for the evolution and diversification of insect navigational circuits.
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Affiliation(s)
- Pratyush Kandimalla
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, CA, USA.
| | - Jaison Jiro Omoto
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, CA, USA
| | - Elizabeth J Hong
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Volker Hartenstein
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, CA, USA
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39
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Steele TJ, Lanz AJ, Nagel KI. Olfactory navigation in arthropods. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023; 209:467-488. [PMID: 36658447 PMCID: PMC10354148 DOI: 10.1007/s00359-022-01611-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 12/26/2022] [Accepted: 12/31/2022] [Indexed: 01/21/2023]
Abstract
Using odors to find food and mates is one of the most ancient and highly conserved behaviors. Arthropods from flies to moths to crabs use broadly similar strategies to navigate toward odor sources-such as integrating flow information with odor information, comparing odor concentration across sensors, and integrating odor information over time. Because arthropods share many homologous brain structures-antennal lobes for processing olfactory information, mechanosensors for processing flow, mushroom bodies (or hemi-ellipsoid bodies) for associative learning, and central complexes for navigation, it is likely that these closely related behaviors are mediated by conserved neural circuits. However, differences in the types of odors they seek, the physics of odor dispersal, and the physics of locomotion in water, air, and on substrates mean that these circuits must have adapted to generate a wide diversity of odor-seeking behaviors. In this review, we discuss common strategies and specializations observed in olfactory navigation behavior across arthropods, and review our current knowledge about the neural circuits subserving this behavior. We propose that a comparative study of arthropod nervous systems may provide insight into how a set of basic circuit structures has diversified to generate behavior adapted to different environments.
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Affiliation(s)
- Theresa J Steele
- Neuroscience Institute, NYU School of Medicine, 435 E 30th St., New York, NY, 10016, USA
| | - Aaron J Lanz
- Neuroscience Institute, NYU School of Medicine, 435 E 30th St., New York, NY, 10016, USA
| | - Katherine I Nagel
- Neuroscience Institute, NYU School of Medicine, 435 E 30th St., New York, NY, 10016, USA.
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40
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Vijayan V, Wang F, Wang K, Chakravorty A, Adachi A, Akhlaghpour H, Dickson BJ, Maimon G. A rise-to-threshold process for a relative-value decision. Nature 2023; 619:563-571. [PMID: 37407812 PMCID: PMC10356611 DOI: 10.1038/s41586-023-06271-6] [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: 10/18/2021] [Accepted: 05/26/2023] [Indexed: 07/07/2023]
Abstract
Whereas progress has been made in the identification of neural signals related to rapid, cued decisions1-3, less is known about how brains guide and terminate more ethologically relevant decisions in which an animal's own behaviour governs the options experienced over minutes4-6. Drosophila search for many seconds to minutes for egg-laying sites with high relative value7,8 and have neurons, called oviDNs, whose activity fulfills necessity and sufficiency criteria for initiating the egg-deposition motor programme9. Here we show that oviDNs express a calcium signal that (1) dips when an egg is internally prepared (ovulated), (2) drifts up and down over seconds to minutes-in a manner influenced by the relative value of substrates-as a fly determines whether to lay an egg and (3) reaches a consistent peak level just before the abdomen bend for egg deposition. This signal is apparent in the cell bodies of oviDNs in the brain and it probably reflects a behaviourally relevant rise-to-threshold process in the ventral nerve cord, where the synaptic terminals of oviDNs are located and where their output can influence behaviour. We provide perturbational evidence that the egg-deposition motor programme is initiated once this process hits a threshold and that subthreshold variation in this process regulates the time spent considering options and, ultimately, the choice taken. Finally, we identify a small recurrent circuit that feeds into oviDNs and show that activity in each of its constituent cell types is required for laying an egg. These results argue that a rise-to-threshold process regulates a relative-value, self-paced decision and provide initial insight into the underlying circuit mechanism for building this process.
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Affiliation(s)
- Vikram Vijayan
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA.
| | - Fei Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Kaiyu Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Lingang Laboratory, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Arun Chakravorty
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Atsuko Adachi
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Hessameddin Akhlaghpour
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia
| | - Gaby Maimon
- Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA.
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41
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Mitchell R, Shaverdian S, Dacke M, Webb B. A model of cue integration as vector summation in the insect brain. Proc Biol Sci 2023; 290:20230767. [PMID: 37357865 PMCID: PMC10291719 DOI: 10.1098/rspb.2023.0767] [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: 03/31/2023] [Accepted: 05/30/2023] [Indexed: 06/27/2023] Open
Abstract
Ball-rolling dung beetles are known to integrate multiple cues in order to facilitate their straight-line orientation behaviour. Recent work has suggested that orientation cues are integrated according to a vector sum, that is, compass cues are represented by vectors and summed to give a combined orientation estimate. Further, cue weight (vector magnitude) appears to be set according to cue reliability. This is consistent with the popular Bayesian view of cue integration: cues are integrated to reduce or minimize an agent's uncertainty about the external world. Integration of orientation cues is believed to occur at the input to the insect central complex. Here, we demonstrate that a model of the head direction circuit of the central complex, including plasticity in input synapses, can act as a substrate for cue integration as vector summation. Further, we show that cue influence is not necessarily driven by cue reliability. Finally, we present a dung beetle behavioural experiment which, in combination with simulation, strongly suggests that these beetles do not weight cues according to reliability. We suggest an alternative strategy whereby cues are weighted according to relative contrast, which can also explain previous results.
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Affiliation(s)
- Robert Mitchell
- Institute for Perception, Action, and Behaviour, The University of Edinburgh School of Informatics, Edinburgh, Edinburgh EH8 9AB, UK
| | - Shahrzad Shaverdian
- Lund Vision Group, Department of Biology, Lund University, Lund SE-223 62, Sweden
| | - Marie Dacke
- Lund Vision Group, Department of Biology, Lund University, Lund SE-223 62, Sweden
| | - Barbara Webb
- Institute for Perception, Action, and Behaviour, The University of Edinburgh School of Informatics, Edinburgh, Edinburgh EH8 9AB, UK
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42
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Ambrosio B, Aziz-Alaoui MA, Mondal A, Mondal A, Sharma SK, Upadhyay RK. Non-Trivial Dynamics in the FizHugh-Rinzel Model and Non-Homogeneous Oscillatory-Excitable Reaction-Diffusions Systems. BIOLOGY 2023; 12:918. [PMID: 37508349 PMCID: PMC10376066 DOI: 10.3390/biology12070918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/16/2023] [Accepted: 06/19/2023] [Indexed: 07/30/2023]
Abstract
This article focuses on the qualitative analysis of complex dynamics arising in a few mathematical models in neuroscience context. We first discuss the dynamics arising in the three-dimensional FitzHugh-Rinzel (FHR) model and then illustrate those arising in a class of non-homogeneous FitzHugh-Nagumo (Nh-FHN) reaction-diffusion systems. FHR and Nh-FHN models can be used to generate relevant complex dynamics and wave-propagation phenomena in neuroscience context. Such complex dynamics include canards, mixed-mode oscillations (MMOs), Hopf-bifurcations and their spatially extended counterpart. Our article highlights original methods to characterize these complex dynamics and how they emerge in ordinary differential equations and spatially extended models.
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Affiliation(s)
- Benjamin Ambrosio
- UNIHAVRE, LMAH, FR-CNRS-3335, ISCN, Normandie University, 76600 Le Havre, France
- The Hudson School of Mathematics, New York, NY 10001, USA
| | - M A Aziz-Alaoui
- UNIHAVRE, LMAH, FR-CNRS-3335, ISCN, Normandie University, 76600 Le Havre, France
| | - Argha Mondal
- Department of Mathematics, Sidho-Kanho-Birsha University, Purulia 723104, India
- Department of Mathematical Sciences, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK
| | - Arnab Mondal
- Department of Mathematics and Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India
| | - Sanjeev K Sharma
- Department of Mathematics and Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India
| | - Ranjit Kumar Upadhyay
- Department of Mathematics and Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India
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43
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Langdon C, Genkin M, Engel TA. A unifying perspective on neural manifolds and circuits for cognition. Nat Rev Neurosci 2023; 24:363-377. [PMID: 37055616 PMCID: PMC11058347 DOI: 10.1038/s41583-023-00693-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/06/2023] [Indexed: 04/15/2023]
Abstract
Two different perspectives have informed efforts to explain the link between the brain and behaviour. One approach seeks to identify neural circuit elements that carry out specific functions, emphasizing connectivity between neurons as a substrate for neural computations. Another approach centres on neural manifolds - low-dimensional representations of behavioural signals in neural population activity - and suggests that neural computations are realized by emergent dynamics. Although manifolds reveal an interpretable structure in heterogeneous neuronal activity, finding the corresponding structure in connectivity remains a challenge. We highlight examples in which establishing the correspondence between low-dimensional activity and connectivity has been possible, unifying the neural manifold and circuit perspectives. This relationship is conspicuous in systems in which the geometry of neural responses mirrors their spatial layout in the brain, such as the fly navigational system. Furthermore, we describe evidence that, in systems in which neural responses are heterogeneous, the circuit comprises interactions between activity patterns on the manifold via low-rank connectivity. We suggest that unifying the manifold and circuit approaches is important if we are to be able to causally test theories about the neural computations that underlie behaviour.
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Affiliation(s)
- Christopher Langdon
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Mikhail Genkin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Tatiana A Engel
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
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44
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Hamid A, Gattuso H, Caglar AN, Pillai M, Steele T, Gonzalez A, Nagel K, Syed MH. The RNA-binding protein, Imp specifies olfactory navigation circuitry and behavior in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.26.542522. [PMID: 37398350 PMCID: PMC10312496 DOI: 10.1101/2023.05.26.542522] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Complex behaviors depend on the precise developmental specification of neuronal circuits, but the relationship between genetic prograssms for neural development, circuit structure, and behavioral output is often unclear. The central complex (CX) is a conserved sensory-motor integration center in insects that governs many higher order behaviors and largely derives from a small number of Type II neural stem cells. Here, we show that Imp, a conserved IGF-II mRNA-binding protein expressed in Type II neural stem cells, specifies components of CX olfactory navigation circuitry. We show: (1) that multiple components of olfactory navigation circuitry arise from Type II neural stem cells and manipulating Imp expression in Type II neural stem cells alters the number and morphology of many of these circuit elements, with the most potent effects on neurons targeting the ventral layers of the fan-shaped body. (2) Imp regulates the specification of Tachykinin expressing ventral fan-shaped body input neurons. (3) Imp in Type II neural stem cells alters the morphology of the CX neuropil structures. (4) Loss of Imp in Type II neural stem cells abolishes upwind orientation to attractive odor while leaving locomotion and odor-evoked regulation of movement intact. Taken together, our work establishes that a single temporally expressed gene can regulate the expression of a complex behavior through the developmental specification of multiple circuit components and provides a first step towards a developmental dissection of the CX and its roles in behavior.
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Affiliation(s)
- Aisha Hamid
- Department of Biology, 219 Yale Blvd NE, University of New Mexico, Albuquerque, NM 87131, USA
| | - Hannah Gattuso
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA
| | - Aysu Nora Caglar
- Current address: Biochemistry & Molecular Biology, 915 Camino De Salud NE, Albuquerque, NM 87132, USA
| | - Midhula Pillai
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA
| | - Theresa Steele
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA
| | - Alexa Gonzalez
- Department of Biology, 219 Yale Blvd NE, University of New Mexico, Albuquerque, NM 87131, USA
| | - Katherine Nagel
- Neuroscience Institute, NYU Medical Center, 435 E 30th St., New York, NY 10016, USA
| | - Mubarak Hussain Syed
- Department of Biology, 219 Yale Blvd NE, University of New Mexico, Albuquerque, NM 87131, USA
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45
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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: 13] [Impact Index Per Article: 13.0] [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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46
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Homberg U, Pfeiffer K. Unraveling the neural basis of spatial orientation in arthropods. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023:10.1007/s00359-023-01635-9. [PMID: 37198448 DOI: 10.1007/s00359-023-01635-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/19/2023]
Abstract
The neural basis underlying spatial orientation in arthropods, in particular insects, has received considerable interest in recent years. This special issue of the Journal of Comparative Physiology A seeks to take account of these developments by presenting a collection of eight review articles and eight original research articles highlighting hotspots of research on spatial orientation in arthropods ranging from flies to spiders and the underlying neural circuits. The contributions impressively illustrate the wide range of tools available to arthropods extending from specific sensory channels to highly sophisticated neural computations for mastering complex navigational challenges.
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Affiliation(s)
- Uwe Homberg
- Department of Biology, Animal Physiology, Philipps University Marburg, 35032, Marburg, Germany.
- Center for Mind Brain and Behavior (CMBB), Philipps-University Marburg and Justus Liebig University Giessen, 35032, Marburg, Germany.
| | - Keram Pfeiffer
- Behavioral Physiology and Sociobiology (Zoology II), Biocenter, University of Würzburg, 97074, Würzburg, Germany
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47
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Petrucco L, Lavian H, Wu YK, Svara F, Štih V, Portugues R. Neural dynamics and architecture of the heading direction circuit in zebrafish. Nat Neurosci 2023; 26:765-773. [PMID: 37095397 PMCID: PMC10166860 DOI: 10.1038/s41593-023-01308-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 03/16/2023] [Indexed: 04/26/2023]
Abstract
Animals generate neural representations of their heading direction. Notably, in insects, heading direction is topographically represented by the activity of neurons in the central complex. Although head direction cells have been found in vertebrates, the connectivity that endows them with their properties is unknown. Using volumetric lightsheet imaging, we find a topographical representation of heading direction in a neuronal network in the zebrafish anterior hindbrain, where a sinusoidal bump of activity rotates following directional swims of the fish and is otherwise stable over many seconds. Electron microscopy reconstructions show that, although the cell bodies are located in a dorsal region, these neurons arborize in the interpeduncular nucleus, where reciprocal inhibitory connectivity stabilizes the ring attractor network that encodes heading. These neurons resemble those found in the fly central complex, showing that similar circuit architecture principles may underlie the representation of heading direction across the animal kingdom and paving the way to an unprecedented mechanistic understanding of these networks in vertebrates.
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Affiliation(s)
- Luigi Petrucco
- Institute of Neuroscience, Technical University of Munich, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilian University, Munich, Germany
| | - Hagar Lavian
- Institute of Neuroscience, Technical University of Munich, Munich, Germany
| | - You Kure Wu
- Institute of Neuroscience, Technical University of Munich, Munich, Germany
| | - Fabian Svara
- Department of Computational Neuroethology, Max Planck Institute for Neurobiology of Behavior - caesar, Bonn, Germany
| | | | - Ruben Portugues
- Institute of Neuroscience, Technical University of Munich, Munich, Germany.
- Munich Cluster of Systems Neurology (SyNergy), Munich, Germany.
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48
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Beetz MJ, El Jundi B. The influence of stimulus history on directional coding in the monarch butterfly brain. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023:10.1007/s00359-023-01633-x. [PMID: 37095358 DOI: 10.1007/s00359-023-01633-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 04/05/2023] [Accepted: 04/12/2023] [Indexed: 04/26/2023]
Abstract
The central complex is a brain region in the insect brain that houses a neural network specialized to encode directional information. Directional coding has traditionally been investigated with compass cues that revolve in full rotations and at constant angular velocities around the insect's head. However, these stimulus conditions do not fully simulate an insect's sensory perception of compass cues during navigation. In nature, an insect flight is characterized by abrupt changes in moving direction as well as constant changes in velocity. The influence of such varying cue dynamics on compass coding remains unclear. We performed long-term tetrode recordings from the brain of monarch butterflies to study how central complex neurons respond to different stimulus velocities and directions. As these butterflies derive directional information from the sun during migration, we measured the neural response to a virtual sun. The virtual sun was either presented as a spot that appeared at random angular positions or was rotated around the butterfly at different angular velocities and directions. By specifically manipulating the stimulus velocity and trajectory, we dissociated the influence of angular velocity and direction on compass coding. While the angular velocity substantially affected the tuning directedness, the stimulus trajectory influenced the shape of the angular tuning curve. Taken together, our results suggest that the central complex flexibly adjusts its directional coding to the current stimulus dynamics ensuring a precise compass even under highly demanding conditions such as during rapid flight maneuvers.
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Affiliation(s)
- M Jerome Beetz
- Zoology II, Biocenter, University of Würzburg, Würzburg, Germany.
| | - Basil El Jundi
- Zoology II, Biocenter, University of Würzburg, Würzburg, Germany
- Animal Physiology, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
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49
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Aimon S, Cheng KY, Gjorgjieva J, Grunwald Kadow IC. Global change in brain state during spontaneous and forced walk in Drosophila is composed of combined activity patterns of different neuron classes. eLife 2023; 12:e85202. [PMID: 37067152 PMCID: PMC10168698 DOI: 10.7554/elife.85202] [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: 11/27/2022] [Accepted: 04/13/2023] [Indexed: 04/18/2023] Open
Abstract
Movement-correlated brain activity has been found across species and brain regions. Here, we used fast whole brain lightfield imaging in adult Drosophila to investigate the relationship between walk and brain-wide neuronal activity. We observed a global change in activity that tightly correlated with spontaneous bouts of walk. While imaging specific sets of excitatory, inhibitory, and neuromodulatory neurons highlighted their joint contribution, spatial heterogeneity in walk- and turning-induced activity allowed parsing unique responses from subregions and sometimes individual candidate neurons. For example, previously uncharacterized serotonergic neurons were inhibited during walk. While activity onset in some areas preceded walk onset exclusively in spontaneously walking animals, spontaneous and forced walk elicited similar activity in most brain regions. These data suggest a major contribution of walk and walk-related sensory or proprioceptive information to global activity of all major neuronal classes.
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Affiliation(s)
- Sophie Aimon
- School of Life Sciences, Technical University of MunichFreisingGermany
| | - Karen Y Cheng
- School of Life Sciences, Technical University of MunichFreisingGermany
- University of Bonn, Medical Faculty (UKB), Institute of Physiology IIBonnGermany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of MunichFreisingGermany
- Max Planck Institute for Brain Research, Computation in Neural CircuitsFrankfurtGermany
| | - Ilona C Grunwald Kadow
- School of Life Sciences, Technical University of MunichFreisingGermany
- University of Bonn, Medical Faculty (UKB), Institute of Physiology IIBonnGermany
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50
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Honkanen A, Hensgen R, Kannan K, Adden A, Warrant E, Wcislo W, Heinze S. Parallel motion vision pathways in the brain of a tropical bee. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023:10.1007/s00359-023-01625-x. [PMID: 37017717 DOI: 10.1007/s00359-023-01625-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 03/01/2023] [Accepted: 03/09/2023] [Indexed: 04/06/2023]
Abstract
Spatial orientation is a prerequisite for most behaviors. In insects, the underlying neural computations take place in the central complex (CX), the brain's navigational center. In this region different streams of sensory information converge to enable context-dependent navigational decisions. Accordingly, a variety of CX input neurons deliver information about different navigation-relevant cues. In bees, direction encoding polarized light signals converge with translational optic flow signals that are suited to encode the flight speed of the animals. The continuous integration of speed and directions in the CX can be used to generate a vector memory of the bee's current position in space in relation to its nest, i.e., perform path integration. This process depends on specific, complex features of the optic flow encoding CX input neurons, but it is unknown how this information is derived from the visual periphery. Here, we thus aimed at gaining insight into how simple motion signals are reshaped upstream of the speed encoding CX input neurons to generate their complex features. Using electrophysiology and anatomical analyses of the halictic bees Megalopta genalis and Megalopta centralis, we identified a wide range of motion-sensitive neurons connecting the optic lobes with the central brain. While most neurons formed pathways with characteristics incompatible with CX speed neurons, we showed that one group of lobula projection neurons possess some physiological and anatomical features required to generate the visual responses of CX optic-flow encoding neurons. However, as these neurons cannot explain all features of CX speed cells, local interneurons of the central brain or alternative input cells from the optic lobe are additionally required to construct inputs with sufficient complexity to deliver speed signals suited for path integration in bees.
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Affiliation(s)
- Anna Honkanen
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden
| | - Ronja Hensgen
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden
| | - Kavitha Kannan
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden
| | - Andrea Adden
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden
- Neural Circuits and Evolution Lab, The Francis Crick Institute, London, UK
| | - Eric Warrant
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden
| | - William Wcislo
- Smithsonian Tropical Research Institute, Panama City, República de Panamá
| | - Stanley Heinze
- Lund Vision Group, Department of Biology, Lund University, Lund, Sweden.
- NanoLund, Lund University, Lund, Sweden.
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