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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:S0896-6273(24)00326-X. [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] [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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2
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van der Goes MSH, Voigts J, Newman JP, Toloza EHS, Brown NJ, Murugan P, Harnett MT. Coordinated head direction representations in mouse anterodorsal thalamic nucleus and retrosplenial cortex. eLife 2024; 13:e82952. [PMID: 38470232 PMCID: PMC10932540 DOI: 10.7554/elife.82952] [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: 08/24/2022] [Accepted: 02/23/2024] [Indexed: 03/13/2024] Open
Abstract
The sense of direction is critical for survival in changing environments and relies on flexibly integrating self-motion signals with external sensory cues. While the anatomical substrates involved in head direction (HD) coding are well known, the mechanisms by which visual information updates HD representations remain poorly understood. Retrosplenial cortex (RSC) plays a key role in forming coherent representations of space in mammals and it encodes a variety of navigational variables, including HD. Here, we use simultaneous two-area tetrode recording to show that RSC HD representation is nearly synchronous with that of the anterodorsal nucleus of thalamus (ADn), the obligatory thalamic relay of HD to cortex, during rotation of a prominent visual cue. Moreover, coordination of HD representations in the two regions is maintained during darkness. We further show that anatomical and functional connectivity are consistent with a strong feedforward drive of HD information from ADn to RSC, with anatomically restricted corticothalamic feedback. Together, our results indicate a concerted global HD reference update across cortex and thalamus.
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Affiliation(s)
- Marie-Sophie H van der Goes
- Department of Brain & Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Jakob Voigts
- Department of Brain & Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
- Open-Ephys IncAtlantaUnited States
- HHMI Janelia Research CampusAshburnUnited States
| | - Jonathan P Newman
- Open-Ephys IncAtlantaUnited States
- Department of Brain & Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Enrique HS Toloza
- Department of Brain & Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Physics, Massachusetts Institute of TechnologyCambridgeUnited States
- Harvard Medical SchoolBostonUnited States
| | - Norma J Brown
- Department of Brain & Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Pranav Murugan
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Mark T Harnett
- Department of Brain & Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
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3
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Lin A, Yang R, Dorkenwald S, Matsliah A, Sterling AR, Schlegel P, Yu SC, McKellar CE, Costa M, Eichler K, Bates AS, Eckstein N, Funke J, Jefferis GSXE, Murthy M. Network Statistics of the Whole-Brain Connectome of Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.29.551086. [PMID: 37547019 PMCID: PMC10402125 DOI: 10.1101/2023.07.29.551086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Brains comprise complex networks of neurons and connections. Network analysis applied to the wiring diagrams of brains can offer insights into how brains support computations and regulate information flow. The completion of the first whole-brain connectome of an adult Drosophila, the largest connectome to date, containing 130,000 neurons and millions of connections, offers an unprecedented opportunity to analyze its network properties and topological features. To gain insights into local connectivity, we computed the prevalence of two- and three-node network motifs, examined their strengths and neurotransmitter compositions, and compared these topological metrics with wiring diagrams of other animals. We discovered that the network of the fly brain displays rich club organization, with a large population (30% percent of the connectome) of highly connected neurons. We identified subsets of rich club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex and will serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.
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Affiliation(s)
- Albert Lin
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Center for the Physics of Biological Function, Princeton University, Princeton, NJ, USA
| | - Runzhe Yang
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - Arie Matsliah
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Amy R Sterling
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Szi-Chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Claire E McKellar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Katharina Eichler
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Alexander Shakeel Bates
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
| | - Nils Eckstein
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Jan Funke
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, 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
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
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4
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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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5
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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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6
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Beer C, Barak O. Revealing and reshaping attractor dynamics in large networks of cortical neurons. PLoS Comput Biol 2024; 20:e1011784. [PMID: 38241417 PMCID: PMC10829997 DOI: 10.1371/journal.pcbi.1011784] [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: 05/28/2023] [Revised: 01/31/2024] [Accepted: 12/22/2023] [Indexed: 01/21/2024] Open
Abstract
Attractors play a key role in a wide range of processes including learning and memory. Due to recent innovations in recording methods, there is increasing evidence for the existence of attractor dynamics in the brain. Yet, our understanding of how these attractors emerge or disappear in a biological system is lacking. By following the spontaneous network bursts of cultured cortical networks, we are able to define a vocabulary of spatiotemporal patterns and show that they function as discrete attractors in the network dynamics. We show that electrically stimulating specific attractors eliminates them from the spontaneous vocabulary, while they are still robustly evoked by the electrical stimulation. This seemingly paradoxical finding can be explained by a Hebbian-like strengthening of specific pathways into the attractors, at the expense of weakening non-evoked pathways into the same attractors. We verify this hypothesis and provide a mechanistic explanation for the underlying changes supporting this effect.
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Affiliation(s)
- Chen Beer
- Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion - Israel Institute of Technology, Haifa, Israel
- Network Biology Research Laboratories, Technion - Israel Institute of Technology, Haifa, Israel
| | - Omri Barak
- Network Biology Research Laboratories, Technion - Israel Institute of Technology, Haifa, Israel
- Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel
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7
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Brown LS, Cho JR, Bolkan SS, Nieh EH, Schottdorf M, Tank DW, Brody CD, Witten IB, Goldman MS. Neural circuit models for evidence accumulation through choice-selective sequences. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.01.555612. [PMID: 38234715 PMCID: PMC10793437 DOI: 10.1101/2023.09.01.555612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Decision making is traditionally thought to be mediated by populations of neurons whose firing rates persistently accumulate evidence across time. However, recent decision-making experiments in rodents have observed neurons across the brain that fire sequentially as a function of spatial position or time, rather than persistently, with the subset of neurons in the sequence depending on the animal's choice. We develop two new candidate circuit models, in which evidence is encoded either in the relative firing rates of two competing chains of neurons or in the network location of a stereotyped pattern ("bump") of neural activity. Encoded evidence is then faithfully transferred between neuronal populations representing different positions or times. Neural recordings from four different brain regions during a decision-making task showed that, during the evidence accumulation period, different brain regions displayed tuning curves consistent with different candidate models for evidence accumulation. This work provides mechanistic models and potential neural substrates for how graded-value information may be precisely accumulated within and transferred between neural populations, a set of computations fundamental to many cognitive operations.
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8
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Garner D, Kind E, Nern A, Houghton L, Zhao A, Sancer G, Rubin GM, Wernet MF, Kim SS. Connectomic reconstruction predicts the functional organization of visual inputs to the navigation center of the Drosophila brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.29.569241. [PMID: 38076786 PMCID: PMC10705420 DOI: 10.1101/2023.11.29.569241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
Many animals, including humans, navigate their surroundings by visual input, yet we understand little about how visual information is transformed and integrated by the navigation system. In Drosophila melanogaster, compass neurons in the donut-shaped ellipsoid body of the central complex generate a sense of direction by integrating visual input from ring neurons, a part of the anterior visual pathway (AVP). Here, we densely reconstruct all neurons in the AVP using FlyWire, an AI-assisted tool for analyzing electron-microscopy data. The AVP comprises four neuropils, sequentially linked by three major classes of neurons: MeTu neurons, which connect the medulla in the optic lobe to the small unit of anterior optic tubercle (AOTUsu) in the central brain; TuBu neurons, which connect the anterior optic tubercle to the bulb neuropil; and ring neurons, which connect the bulb to the ellipsoid body. Based on neuronal morphologies, connectivity between different neural classes, and the locations of synapses, we identified non-overlapping channels originating from four types of MeTu neurons, which we further divided into ten subtypes based on the presynaptic connections in medulla and postsynaptic connections in AOTUsu. To gain an objective measure of the natural variation within the pathway, we quantified the differences between anterior visual pathways from both hemispheres and between two electron-microscopy datasets. Furthermore, we infer potential visual features and the visual area from which any given ring neuron receives input by combining the connectivity of the entire AVP, the MeTu neurons' dendritic fields, and presynaptic connectivity in the optic lobes. These results provide a strong foundation for understanding how distinct visual features are extracted and transformed across multiple processing stages to provide critical information for computing the fly's sense of direction.
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Affiliation(s)
- Dustin Garner
- Molecular, Cellular, and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Emil Kind
- Department of Biology, Freie Universität Berlin, Berlin, Germany
| | - Aljoscha Nern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Lucy Houghton
- Molecular, Cellular, and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Arthur Zhao
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Gizem Sancer
- Department of Biology, Freie Universität Berlin, Berlin, Germany
| | - Gerald M. Rubin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Sung Soo Kim
- Molecular, Cellular, and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, USA
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9
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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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10
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Singh P, Aleman A, Omoto JJ, Nguyen BC, Kandimalla P, Hartenstein V, Donlea JM. Examining Sleep Modulation by Drosophila Ellipsoid Body Neurons. eNeuro 2023; 10:ENEURO.0281-23.2023. [PMID: 37679041 PMCID: PMC10523840 DOI: 10.1523/eneuro.0281-23.2023] [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: 08/06/2023] [Accepted: 08/10/2023] [Indexed: 09/09/2023] Open
Abstract
Recent work in Drosophila has uncovered several neighboring classes of sleep-regulatory neurons within the central complex. However, the logic of connectivity and network motifs remains limited by the incomplete examination of relevant cell types. Using a recent genetic-anatomic classification of ellipsoid body ring neurons, we conducted a thermogenetic screen in female flies to assess sleep/wake behavior and identified two wake-promoting drivers that label ER3d neurons and two sleep-promoting drivers that express in ER3m cells. We then used intersectional genetics to refine driver expression patterns. Activation of ER3d cells shortened sleep bouts, suggesting a key role in sleep maintenance. While sleep-promoting drivers from our mini-screen label overlapping ER3m neurons, intersectional strategies cannot rule out sleep regulatory roles for additional neurons in their expression patterns. Suppressing GABA synthesis in ER3m neurons prevents postinjury sleep, and GABAergic ER3d cells are required for thermogenetically induced wakefulness. Finally, we use an activity-dependent fluorescent reporter for putative synaptic contacts to embed these neurons within the known sleep-regulatory network. ER3m and ER3d neurons may receive connections from wake-active Helicon/ExR1 cells, and ER3m neurons likely inhibit ER3d neurons. Together, these data suggest a neural mechanism by which previously uncharacterized circuit elements stabilize sleep-wake states.
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Affiliation(s)
- Prabhjit Singh
- Department of Neurobiology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
| | - Abigail Aleman
- Department of Neurobiology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
- Molecular, Cellular & Integrative Physiology Interdepartmental Program, University of California-Los Angeles, Los Angeles, California 90095
| | - Jaison Jiro Omoto
- Department of Neurobiology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
| | - Bao-Chau Nguyen
- Department of Molecular, Cell, & Developmental Biology, University of California-Los Angeles, Los Angeles, California 90095
| | - Pratyush Kandimalla
- Department of Molecular, Cell, & Developmental Biology, University of California-Los Angeles, Los Angeles, California 90095
| | - Volker Hartenstein
- Department of Molecular, Cell, & Developmental Biology, University of California-Los Angeles, Los Angeles, California 90095
| | - Jeffrey M Donlea
- Department of Neurobiology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
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11
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Chiappe ME. Circuits for self-motion estimation and walking control in Drosophila. Curr Opin Neurobiol 2023; 81:102748. [PMID: 37453230 DOI: 10.1016/j.conb.2023.102748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/11/2023] [Accepted: 06/13/2023] [Indexed: 07/18/2023]
Abstract
The brain's evolution and operation are inextricably linked to animal movement, and critical functions, such as motor control, spatial perception, and navigation, rely on precise knowledge of body movement. Such internal estimates of self-motion emerge from the integration of mechanosensory and visual feedback with motor-related signals. Thus, this internal representation likely depends on the activity of circuits distributed across the central nervous system. However, the circuits responsible for self-motion estimation, and the exact mechanisms by which motor-sensory coordination occurs within these circuits remain poorly understood. Recent technological advances have positioned Drosophila melanogaster as an advantageous model for investigating the emergence, maintenance, and utilization of self-motion representations during naturalistic walking behaviors. In this review, I will illustrate how the adult fly is providing insights into the fundamental problems of self-motion computations and walking control, which have relevance for all animals.
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Affiliation(s)
- M Eugenia Chiappe
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal.
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12
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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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13
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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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14
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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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15
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Abstract
Using functional imaging and neural circuit reconstructions, a recent study reveals head direction neurons in the anterior hindbrain of zebrafish that resemble insect head-direction cells to a surprising degree.
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Affiliation(s)
- Stanley Heinze
- Lund University, Lund Vision Group and NanoLund, Lund, Sweden.
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16
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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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17
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Currier TA, Pang MM, Clandinin TR. Visual processing in the fly, from photoreceptors to behavior. Genetics 2023; 224:iyad064. [PMID: 37128740 PMCID: PMC10213501 DOI: 10.1093/genetics/iyad064] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 03/22/2023] [Indexed: 05/03/2023] Open
Abstract
Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.
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Affiliation(s)
- Timothy A Currier
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michelle M Pang
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA
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18
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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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19
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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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20
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Sit KK, Goard MJ. Coregistration of heading to visual cues in retrosplenial cortex. Nat Commun 2023; 14:1992. [PMID: 37031198 PMCID: PMC10082791 DOI: 10.1038/s41467-023-37704-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 03/28/2023] [Indexed: 04/10/2023] Open
Abstract
Spatial cognition depends on an accurate representation of orientation within an environment. Head direction cells in distributed brain regions receive a range of sensory inputs, but visual input is particularly important for aligning their responses to environmental landmarks. To investigate how population-level heading responses are aligned to visual input, we recorded from retrosplenial cortex (RSC) of head-fixed mice in a moving environment using two-photon calcium imaging. We show that RSC neurons are tuned to the animal's relative orientation in the environment, even in the absence of head movement. Next, we found that RSC receives functionally distinct projections from visual and thalamic areas and contains several functional classes of neurons. While some functional classes mirror RSC inputs, a newly discovered class coregisters visual and thalamic signals. Finally, decoding analyses reveal unique contributions to heading from each class. Our results suggest an RSC circuit for anchoring heading representations to environmental visual landmarks.
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Affiliation(s)
- Kevin K Sit
- Department of Psychological and Brain Sciences University of California, Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Michael J Goard
- Department of Psychological and Brain Sciences University of California, Santa Barbara, Santa Barbara, CA, 93106, USA.
- Department of Molecular, Cellular, and Developmental Biology University of California, Santa Barbara, Santa Barbara, CA, 93106, USA.
- Neuroscience Research Institute University of California Santa Barbara, Santa Barbara, CA, 93106, USA.
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21
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Ajabi Z, Keinath AT, Wei XX, Brandon MP. Population dynamics of head-direction neurons during drift and reorientation. Nature 2023; 615:892-899. [PMID: 36949190 PMCID: PMC10060160 DOI: 10.1038/s41586-023-05813-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 02/03/2023] [Indexed: 03/24/2023]
Abstract
The head direction (HD) system functions as the brain's internal compass1,2, classically formalized as a one-dimensional ring attractor network3,4. In contrast to a globally consistent magnetic compass, the HD system does not have a universal reference frame. Instead, it anchors to local cues, maintaining a stable offset when cues rotate5-8 and drifting in the absence of referents5,8-10. However, questions about the mechanisms that underlie anchoring and drift remain unresolved and are best addressed at the population level. For example, the extent to which the one-dimensional description of population activity holds under conditions of reorientation and drift is unclear. Here we performed population recordings of thalamic HD cells using calcium imaging during controlled rotations of a visual landmark. Across experiments, population activity varied along a second dimension, which we refer to as network gain, especially under circumstances of cue conflict and ambiguity. Activity along this dimension predicted realignment and drift dynamics, including the speed of network realignment. In the dark, network gain maintained a 'memory trace' of the previously displayed landmark. Further experiments demonstrated that the HD network returned to its baseline orientation after brief, but not longer, exposures to a rotated cue. This experience dependence suggests that memory of previous associations between HD neurons and allocentric cues is maintained and influences the internal HD representation. Building on these results, we show that continuous rotation of a visual landmark induced rotation of the HD representation that persisted in darkness, demonstrating experience-dependent recalibration of the HD system. Finally, we propose a computational model to formalize how the neural compass flexibly adapts to changing environmental cues to maintain a reliable representation of HD. These results challenge classical one-dimensional interpretations of the HD system and provide insights into the interactions between this system and the cues to which it anchors.
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Affiliation(s)
- Zaki Ajabi
- Department of Psychiatry, Douglas Hospital Research Centre, McGill University, Verdun, Quebec, Canada.
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
| | - Alexandra T Keinath
- Department of Psychiatry, Douglas Hospital Research Centre, McGill University, Verdun, Quebec, Canada
| | - Xue-Xin Wei
- Department of Neuroscience, University of Texas at Austin, Austin, TX, USA
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Center for Perceptual Systems, University of Texas at Austin, Austin, TX, USA
- Center for Theoretical and Computational Neuroscience, University of Texas at Austin, Austin, TX, USA
| | - Mark P Brandon
- Department of Psychiatry, Douglas Hospital Research Centre, McGill University, Verdun, Quebec, Canada.
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
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22
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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 2023:10.1007/s00359-023-01616-y. [PMID: 36932234 DOI: 10.1007/s00359-023-01616-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 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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23
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Collett TS, Hempel de Ibarra N. An 'instinct for learning': the learning flights and walks of bees, wasps and ants from the 1850s to now. J Exp Biol 2023; 226:301237. [PMID: 37015045 PMCID: PMC10112973 DOI: 10.1242/jeb.245278] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2023]
Abstract
The learning flights and walks of bees, wasps and ants are precisely coordinated movements that enable insects to memorise the visual surroundings of their nest or other significant places such as foraging sites. These movements occur on the first few occasions that an insect leaves its nest. They are of special interest because their discovery in the middle of the 19th century provided perhaps the first evidence that insects can learn and are not solely governed by instinct. Here, we recount the history of research on learning flights from their discovery to the present day. The first studies were conducted by skilled naturalists and then, over the following 50 years, by neuroethologists examining the insects' learning behaviour in the context of experiments on insect navigation and its underlying neural mechanisms. The most important property of these movements is that insects repeatedly fixate their nest and look in other favoured directions, either in a preferred compass direction, such as North, or towards preferred objects close to the nest. Nest facing is accomplished through path integration. Memories of views along a favoured direction can later guide an insect's return to its nest. In some ant species, the favoured direction is adjusted to future foraging needs. These memories can then guide both the outward and homeward legs of a foraging trip. Current studies of central areas of the insect brain indicate what regions implement the behavioural manoeuvres underlying learning flights and the resulting visual memories.
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Affiliation(s)
- Thomas S Collett
- School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK
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24
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Global inhibition in head-direction neural circuits: a systematic comparison between connectome-based spiking neural circuit models. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023:10.1007/s00359-023-01615-z. [PMID: 36781446 DOI: 10.1007/s00359-023-01615-z] [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: 10/01/2022] [Revised: 01/16/2023] [Accepted: 01/27/2023] [Indexed: 02/15/2023]
Abstract
The recent discovery of the head-direction (HD) system in fruit flies has provided unprecedented insights into the neural mechanisms of spatial orientation. Despite the progress, the neural substance of global inhibition, an essential component of the HD circuits, remains controversial. Some studies suggested that the ring neurons provide global inhibition, while others suggested the Δ7 neurons. In the present study, we provide evaluations from the theoretical perspective by performing systematic analyses on the computational models based on the ring-neuron (R models) and Δ7-neurons (Delta models) hypotheses with modifications according to the latest connectomic data. We conducted four tests: robustness, persistency, speed, and dynamical characteristics. We discovered that the two models led to a comparable performance in general, but each excelled in different tests. The R Models were more robust, while the Delta models were better in the persistency test. We also tested a hybrid model that combines both inhibitory mechanisms. While the performances of the R and Delta models in each test are highly parameter-dependent, the Hybrid model performed well in all tests with the same set of parameters. Our results suggest the possibility of combined inhibitory mechanisms in the HD circuits of fruit flies.
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25
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Yan W, Lin H, Yu J, Wiggin TD, Wu L, Meng Z, Liu C, Griffith LC. Subtype-Specific Roles of Ellipsoid Body Ring Neurons in Sleep Regulation in Drosophila. J Neurosci 2023; 43:764-786. [PMID: 36535771 PMCID: PMC9899086 DOI: 10.1523/jneurosci.1350-22.2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 09/22/2022] [Accepted: 10/26/2022] [Indexed: 12/23/2022] Open
Abstract
The ellipsoid body (EB) is a major structure of the central complex of the Drosophila melanogaster brain. Twenty-two subtypes of EB ring neurons have been identified based on anatomic and morphologic characteristics by light-level microscopy and EM connectomics. A few studies have associated ring neurons with the regulation of sleep homeostasis and structure. However, cell type-specific and population interactions in the regulation of sleep remain unclear. Using an unbiased thermogenetic screen of EB drivers using female flies, we found the following: (1) multiple ring neurons are involved in the modulation of amount of sleep and structure in a synergistic manner; (2) analysis of data for ΔP(doze)/ΔP(wake) using a mixed Gaussian model detected 5 clusters of GAL4 drivers which had similar effects on sleep pressure and/or depth: lines driving arousal contained R4m neurons, whereas lines that increased sleep pressure had R3m cells; (3) a GLM analysis correlating ring cell subtype and activity-dependent changes in sleep parameters across all lines identified several cell types significantly associated with specific sleep effects: R3p was daytime sleep-promoting, and R4m was nighttime wake-promoting; and (4) R3d cells present in 5HT7-GAL4 and in GAL4 lines, which exclusively affect sleep structure, were found to contribute to fragmentation of sleep during both day and night. Thus, multiple subtypes of ring neurons distinctively control sleep amount and/or structure. The unique highly interconnected structure of the EB suggests a local-network model worth future investigation; understanding EB subtype interactions may provide insight how sleep circuits in general are structured.SIGNIFICANCE STATEMENT How multiple brain regions, with many cell types, can coherently regulate sleep remains unclear, but identification of cell type-specific roles can generate opportunities for understanding the principles of integration and cooperation. The ellipsoid body (EB) of the fly brain exhibits a high level of connectivity and functional heterogeneity yet is able to tune multiple behaviors in real-time, including sleep. Leveraging the powerful genetic tools available in Drosophila and recent progress in the characterization of the morphology and connectivity of EB ring neurons, we identify several EB subtypes specifically associated with distinct aspects of sleep. Our findings will aid in revealing the rules of coding and integration in the brain.
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Affiliation(s)
- Wei Yan
- Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518000, China
| | - Hai Lin
- Central Research Institute, United Imaging Healthcare, Shanghai, 200032, China
| | - Junwei Yu
- Department of Biology, National Center for Behavioral Genomics and Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts 02453
| | - Timothy D Wiggin
- Department of Biology, National Center for Behavioral Genomics and Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts 02453
| | - Litao Wu
- Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518000, China
| | - Zhiqiang Meng
- Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518000, China
- CAS Key Laboratory of Brain Connectome and Manipulation, Shenzhen, 518000, China
- Shenzhen Key Laboratory of Drug Addiction, Shenzhen, 518000, China
| | - Chang Liu
- Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518000, China
- CAS Key Laboratory of Brain Connectome and Manipulation, Shenzhen, 518000, China
- Shenzhen Key Laboratory of Viral Vectors for Biomedicine, Shenzhen, 518000, China
| | - Leslie C Griffith
- Department of Biology, National Center for Behavioral Genomics and Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts 02453
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26
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Pfeiffer K. The neuronal building blocks of the navigational toolkit in the central complex of insects. CURRENT OPINION IN INSECT SCIENCE 2023; 55:100972. [PMID: 36126877 DOI: 10.1016/j.cois.2022.100972] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 09/03/2022] [Accepted: 09/12/2022] [Indexed: 06/15/2023]
Abstract
The central complex in the brain of insects is a group of midline-spanning neuropils at the interface between sensory and premotor tasks of the brain. It is involved in sleep control, decision-making and most prominently in goal-directed locomotion behaviors. The recently published connectome of the central complex of Drosophila melanogaster is a milestone in understanding the intricacies of the central-complex circuits and will provide inspiration for testable hypotheses for the coming years. Here, I provide a basic neuroanatomical description of the central complex of Drosophila and other species and discuss some recent advancements, some of which, such as the discovery of coordinate transformation through vector math, have been predicted from connectomics data.
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Affiliation(s)
- Keram Pfeiffer
- Behavioural Physiology and Sociobiology (Zoology II), Biocenter, University of Würzburg, 97074 Würzburg, Germany.
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27
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Alexander AS, Place R, Starrett MJ, Chrastil ER, Nitz DA. Rethinking retrosplenial cortex: Perspectives and predictions. Neuron 2023; 111:150-175. [PMID: 36460006 DOI: 10.1016/j.neuron.2022.11.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/09/2022] [Accepted: 11/06/2022] [Indexed: 12/03/2022]
Abstract
The last decade has produced exciting new ideas about retrosplenial cortex (RSC) and its role in integrating diverse inputs. Here, we review the diversity in forms of spatial and directional tuning of RSC activity, temporal organization of RSC activity, and features of RSC interconnectivity with other brain structures. We find that RSC anatomy and dynamics are more consistent with roles in multiple sensorimotor and cognitive processes than with any isolated function. However, two more generalized categories of function may best characterize roles for RSC in complex cognitive processes: (1) shifting and relating perspectives for spatial cognition and (2) prediction and error correction for current sensory states with internal representations of the environment. Both functions likely take advantage of RSC's capacity to encode conjunctions among sensory, motor, and spatial mapping information streams. Together, these functions provide the scaffold for intelligent actions, such as navigation, perspective taking, interaction with others, and error detection.
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Affiliation(s)
- Andrew S Alexander
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Ryan Place
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA
| | - Michael J Starrett
- Department of Neurobiology & Behavior, University of California, Irvine, Irvine, CA 92697, USA
| | - Elizabeth R Chrastil
- Department of Neurobiology & Behavior, University of California, Irvine, Irvine, CA 92697, USA; Department of Cognitive Sciences, University of California, Irvine, Irvine, CA 92697, USA.
| | - Douglas A Nitz
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA.
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28
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Marquis M, Wilson RI. Locomotor and olfactory responses in dopamine neurons of the Drosophila superior-lateral brain. Curr Biol 2022; 32:5406-5414.e5. [PMID: 36450284 DOI: 10.1016/j.cub.2022.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/17/2022] [Accepted: 11/03/2022] [Indexed: 12/03/2022]
Abstract
The Drosophila brain contains about 50 distinct morphological types of dopamine neurons.1,2,3,4 Physiological studies of Drosophila dopamine neurons have been largely limited to one brain region, the mushroom body,5,6,7,8,9,10,11,12,13 where they are implicated in learning.14,15,16,17,18 By comparison, we know little about the physiology of other Drosophila dopamine neurons. Interestingly, a recent whole-brain imaging study found that dopamine neuron activity in several fly brain regions is correlated with locomotion.19 This is notable because many dopamine neurons in the rodent brain are also correlated with locomotion or other movements20,21,22,23,24,25,26,27,28,29,30; however, most rodent studies have focused on learned and rewarded behaviors, and few have investigated dopamine neuron activity during spontaneous (self-timed) movements. In this study, we monitored dopamine neurons in the Drosophila brain during self-timed locomotor movements, focusing on several previously uncharacterized cell types that arborize in the superior-lateral brain, specifically the lateral horn and superior-lateral protocerebrum. We found that activity of all of these dopamine neurons correlated with spontaneous fluctuations in walking speed, with different cell types showing different speed correlations. Some dopamine neurons also responded to odors, but these responses were suppressed by repeated odor encounters. Finally, we found that the same identifiable dopamine neuron can encode different combinations of locomotion and odor in different individuals. If these dopamine neurons promote synaptic plasticity-like the dopamine neurons of the mushroom body-then, their tuning profiles would imply that plasticity depends on a flexible integration of sensory signals, motor signals, and recent experience.
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Affiliation(s)
- Michael Marquis
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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Galili DS, Jefferis GS, Costa M. Connectomics and the neural basis of behaviour. CURRENT OPINION IN INSECT SCIENCE 2022; 54:100968. [PMID: 36113710 PMCID: PMC7614087 DOI: 10.1016/j.cois.2022.100968] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/30/2022] [Accepted: 09/06/2022] [Indexed: 06/15/2023]
Abstract
Methods to acquire and process synaptic-resolution electron-microscopy datasets have progressed very rapidly, allowing production and annotation of larger, more complete connectomes. More accurate neuronal matching techniques are enriching cell type data with gene expression, neuron activity, behaviour and developmental information, providing ways to test hypotheses of circuit function. In a variety of behaviours such as learned and innate olfaction, navigation and sexual behaviour, connectomics has already revealed interconnected modules with a hierarchical structure, recurrence and integration of sensory streams. Comparing individual connectomes to determine which circuit features are robust and which are variable is one key research area; new work in comparative connectomics across development, experience, sex and species will establish strong links between neuronal connectivity and brain function.
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Affiliation(s)
- Dana S Galili
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
| | - Gregory Sxe Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK; Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
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30
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Taisz I, Jefferis GSXE. Speed of learning depends on turning. Nature 2022; 612:216-217. [PMID: 36450950 DOI: 10.1038/d41586-022-03681-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
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31
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Khona M, Fiete IR. Attractor and integrator networks in the brain. Nat Rev Neurosci 2022; 23:744-766. [DOI: 10.1038/s41583-022-00642-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/22/2022] [Indexed: 11/06/2022]
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32
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Shaverdian S, Dirlik E, Mitchell R, Tocco C, Webb B, Dacke M. Weighted cue integration for straight-line orientation. iScience 2022; 25:105207. [PMID: 36274940 PMCID: PMC9583106 DOI: 10.1016/j.isci.2022.105207] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/05/2022] [Accepted: 09/22/2022] [Indexed: 11/30/2022] Open
Abstract
Animals commonly integrate multiple sources of information to guide their behavior. Among insects, previous studies have suggested that the relative reliability of cues affects their weighting in behavior, but have not systematically explored how well alternative integration strategies can account for the observed directional choices. Here, we characterize the directional reliability of an ersatz sun at different elevations and wind at different speeds as guiding cues for a species of ball-rolling dung beetle. The relative reliability is then shown to determine which cue dominates when the cues are put in conflict. We further show through modeling that the results are best explained by continuous integration of the cues as a vector-sum (rather than switching between them) but with non-optimal weighting and small individual biases. The neural circuitry in the insect central complex appears to provide an ideal substrate for this type of vector-sum-based integration mechanism.
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Affiliation(s)
- Shahrzad Shaverdian
- Lund Vision Group, Department of Biology, Lund University, 223 62 Lund, Sweden
| | - Elin Dirlik
- Lund Vision Group, Department of Biology, Lund University, 223 62 Lund, Sweden,Corresponding author
| | - Robert Mitchell
- School of Informatics, The University of Edinburgh, Edinburgh EH8 9AB, UK
| | - Claudia Tocco
- Lund Vision Group, Department of Biology, Lund University, 223 62 Lund, Sweden
| | - Barbara Webb
- School of Informatics, The University of Edinburgh, Edinburgh EH8 9AB, UK
| | - Marie Dacke
- Lund Vision Group, Department of Biology, Lund University, 223 62 Lund, Sweden
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33
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Insect navigation: Bumblebees walk the walk. Curr Biol 2022; 32:R746-R748. [PMID: 35820386 DOI: 10.1016/j.cub.2022.05.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A new study shows that bumblebees can display path integration while walking in a small laboratory arena. This opens a new avenue for studying how insects' brains can encode direction and distance.
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34
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Nguyen TAT, Beetz MJ, Merlin C, Pfeiffer K, el Jundi B. Weighting of Celestial and Terrestrial Cues in the Monarch Butterfly Central Complex. Front Neural Circuits 2022; 16:862279. [PMID: 35847485 PMCID: PMC9285895 DOI: 10.3389/fncir.2022.862279] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 06/10/2022] [Indexed: 12/02/2022] Open
Abstract
Monarch butterflies rely on external cues for orientation during their annual long-distance migration from Northern US and Canada to Central Mexico. These external cues can be celestial cues, such as the sun or polarized light, which are processed in a brain region termed the central complex (CX). Previous research typically focused on how individual simulated celestial cues are encoded in the butterfly's CX. However, in nature, the butterflies perceive several celestial cues at the same time and need to integrate them to effectively use the compound of all cues for orientation. In addition, a recent behavioral study revealed that monarch butterflies can rely on terrestrial cues, such as the panoramic skyline, for orientation and use them in combination with the sun to maintain a directed flight course. How the CX encodes a combination of celestial and terrestrial cues and how they are weighted in the butterfly's CX is still unknown. Here, we examined how input neurons of the CX, termed TL neurons, combine celestial and terrestrial information. While recording intracellularly from the neurons, we presented a sun stimulus and polarized light to the butterflies as well as a simulated sun and a panoramic scene simultaneously. Our results show that celestial cues are integrated linearly in these cells, while the combination of the sun and a panoramic skyline did not always follow a linear integration of action potential rates. Interestingly, while the sun and polarized light were invariantly weighted between individual neurons, the sun stimulus and panoramic skyline were dynamically weighted when both stimuli were simultaneously presented. Taken together, this dynamic weighting between celestial and terrestrial cues may allow the butterflies to flexibly set their cue preference during navigation.
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Affiliation(s)
| | - M. Jerome Beetz
- Biocenter, Zoology II, University of Wuerzburg, Würzburg, Germany
| | - Christine Merlin
- Department of Biology and Center for Biological Clocks Research, Texas A&M University, College Station, TX, United States
| | - Keram Pfeiffer
- Biocenter, Zoology II, University of Wuerzburg, Würzburg, Germany
| | - Basil el Jundi
- Biocenter, Zoology II, University of Wuerzburg, Würzburg, Germany
- Department of Biology, Animal Physiology, Norwegian University of Science and Technology, Trondheim, Norway
- *Correspondence: Basil el Jundi
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35
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Vafidis P, Owald D, D'Albis T, Kempter R. Learning accurate path integration in ring attractor models of the head direction system. eLife 2022; 11:69841. [PMID: 35723252 PMCID: PMC9286743 DOI: 10.7554/elife.69841] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
Ring attractor models for angular path integration have received strong experimental support. To function as integrators, head direction circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila head direction system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading, and where the network remaps to integrate with different gains in rodents. Our model predicts that path integration requires self-supervised learning during a developmental phase, and proposes a general framework to learn to path-integrate with gain-1 even in architectures that lack the physical topography of a ring.
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Affiliation(s)
- Pantelis Vafidis
- Computation and Neural Systems, California Institute of Technology, Pasadena, United States
| | - David Owald
- NeuroCure, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Tiziano D'Albis
- Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Richard Kempter
- Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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36
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Stentiford R, Knowles TC, Pearson MJ. A Spiking Neural Network Model of Rodent Head Direction Calibrated With Landmark Free Learning. Front Neurorobot 2022; 16:867019. [PMID: 35692491 PMCID: PMC9178238 DOI: 10.3389/fnbot.2022.867019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/19/2022] [Indexed: 11/14/2022] Open
Abstract
Maintaining a stable estimate of head direction requires both self-motion (idiothetic) information and environmental (allothetic) anchoring. In unfamiliar or dark environments idiothetic drive can maintain a rough estimate of heading but is subject to inaccuracy, visual information is required to stabilize the head direction estimate. When learning to associate visual scenes with head angle, animals do not have access to the ‘ground truth' of their head direction, and must use egocentrically derived imprecise head direction estimates. We use both discriminative and generative methods of visual processing to learn these associations without extracting explicit landmarks from a natural visual scene, finding all are sufficiently capable at providing a corrective signal. Further, we present a spiking continuous attractor model of head direction (SNN), which when driven by idiothetic input is subject to drift. We show that head direction predictions made by the chosen model-free visual learning algorithms can correct for drift, even when trained on a small training set of estimated head angles self-generated by the SNN. We validate this model against experimental work by reproducing cue rotation experiments which demonstrate visual control of the head direction signal.
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37
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Xie D, Yin K, Yang ZJ, Huang H, Li X, Shu Z, Duan H, He J, Jiang J. Polarization-perceptual anisotropic two-dimensional ReS 2 neuro-transistor with reconfigurable neuromorphic vision. MATERIALS HORIZONS 2022; 9:1448-1459. [PMID: 35234765 DOI: 10.1039/d1mh02036f] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Polarization is a common and unique phenomenon in nature, which reveals more camouflage features of objects. However, current polarization-perceptual devices based on conventional physical architectures face enormous challenges for high-performance computation due to the traditional von Neumann bottleneck. In this work, a novel polarization-perceptual neuro-transistor with reconfigurable anisotropic vision is proposed based on a two-dimensional ReS2 phototransistor. The device exhibits excellent photodetection ability and superior polarization sensitivity due to its direct band gap semiconductor property and strong anisotropic crystal structure, respectively. The fascinating polarization-sensitive neuromorphic behavior, such as polarization memory consolidation and reconfigurable visual imaging, are successfully realized. In particular, the regulated polarization responsivity and dichroic ratio are successfully emulated through our artificial compound eyes. More importantly, two intriguing polarization-perceptual applications for polarized navigation with reconfigurable adaptive learning abilities and three-dimensional visual polarization imaging are also experimentally demonstrated. The proposed device may provide a promising opportunity for future polarization perception systems in intelligent humanoid robots and autonomous vehicles.
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Affiliation(s)
- Dingdong Xie
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Kai Yin
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Zhong-Jian Yang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Han Huang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Xiaohui Li
- School of Physics and Information Technology, Shanxi Normal University, Xi'an 710119, P. R. China
| | - Zhiwen Shu
- State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, P. R. China
| | - Huigao Duan
- State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, P. R. China
| | - Jun He
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Jie Jiang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
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38
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Ryu L, Kim SY, Kim AJ. From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila. Front Neurosci 2022; 16:883640. [PMID: 35600623 PMCID: PMC9115102 DOI: 10.3389/fnins.2022.883640] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 03/28/2022] [Indexed: 11/17/2022] Open
Abstract
Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.
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Affiliation(s)
- Leesun Ryu
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Sung Yong Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Anmo J. Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
- *Correspondence: Anmo J. Kim,
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39
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Frighetto G, Zordan MA, Castiello U, Megighian A, Martin JR. Dopamine Modulation of Drosophila Ellipsoid Body Neurons, a Nod to the Mammalian Basal Ganglia. Front Physiol 2022; 13:849142. [PMID: 35492587 PMCID: PMC9048027 DOI: 10.3389/fphys.2022.849142] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 03/10/2022] [Indexed: 12/04/2022] Open
Abstract
The central complex (CX) is a neural structure located on the midline of the insect brain that has been widely studied in the last few years. Its role in navigation and goal-oriented behaviors resembles those played by the basal ganglia in mammals. However, the neural mechanisms and the neurotransmitters involved in these processes remain unclear. Here, we exploited an in vivo bioluminescence Ca2+ imaging technique to record the activity in targeted neurons of the ellipsoid body (EB). We used different drugs to evoke excitatory Ca2+-responses, depending on the putative neurotransmitter released by their presynaptic inputs, while concomitant dopamine administration was employed to modulate those excitations. By using a genetic approach to knockdown the dopamine 1-like receptors, we showed that different dopamine modulatory effects are likely due to specific receptors expressed by the targeted population of neurons. Altogether, these results provide new data concerning how dopamine modulates and shapes the response of the ellipsoid body neurons. Moreover, they provide important insights regarding the similitude with mammals as far as the role played by dopamine in increasing and stabilizing the response of goal-related information.
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Affiliation(s)
- Giovanni Frighetto
- Department of General Psychology, University of Padova, Padova, Italy
- Institut des Neurosciences Paris-Saclay, Université Paris-Saclay, CNRS, Saclay, France
| | - Mauro A. Zordan
- Department of Biology, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Umberto Castiello
- Department of General Psychology, University of Padova, Padova, Italy
| | - Aram Megighian
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | - Jean-René Martin
- Institut des Neurosciences Paris-Saclay, Université Paris-Saclay, CNRS, Saclay, France
- *Correspondence: Jean-René Martin,
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40
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Flexible navigational computations in the Drosophila central complex. Curr Opin Neurobiol 2022; 73:102514. [DOI: 10.1016/j.conb.2021.12.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 12/12/2021] [Accepted: 12/22/2021] [Indexed: 12/25/2022]
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41
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Robinson BS, Norman-Tenazas R, Cervantes M, Symonette D, Johnson EC, Joyce J, Rivlin PK, Hwang GM, Zhang K, Gray-Roncal W. Online learning for orientation estimation during translation in an insect ring attractor network. Sci Rep 2022; 12:3210. [PMID: 35217679 PMCID: PMC8881593 DOI: 10.1038/s41598-022-05798-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 01/10/2022] [Indexed: 11/09/2022] Open
Abstract
Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.
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Affiliation(s)
- Brian S Robinson
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA.
| | | | - Martha Cervantes
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA
| | - Danilo Symonette
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA
| | - Erik C Johnson
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA
| | - Justin Joyce
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA
| | - Patricia K Rivlin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20147, USA
| | - Grace M Hwang
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Kechen Zhang
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - William Gray-Roncal
- The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
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42
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Ning J, Li Z, Zhang X, Wang J, Chen D, Liu Q, Sun Y. Behavioral signatures of structured feature detection during courtship in Drosophila. Curr Biol 2022; 32:1211-1231.e7. [DOI: 10.1016/j.cub.2022.01.024] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 11/27/2021] [Accepted: 01/10/2022] [Indexed: 11/27/2022]
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43
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Takahashi N, Zittrell F, Hensgen R, Homberg U. Receptive field structures for two celestial compass cues at the input stage of the central complex in the locust brain. J Exp Biol 2022; 225:274503. [DOI: 10.1242/jeb.243858] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/14/2022] [Indexed: 11/20/2022]
Abstract
Successful navigation depends on an animal's ability to perceive its spatial orientation relative to visual surroundings. Heading direction in insects is represented in the central complex (CX), a navigation center in the brain, to generate steering commands. In insects that navigate relative to sky compass signals, CX neurons are tuned to celestial cues indicating the location of the sun. The desert locust CX contains a compass-like representation of two related celestial cues: the direction of unpolarized direct sunlight and the pattern of polarized light, which depends on the sun position. Whether congruent tuning to these two compass cues emerges within the CX network or is inherited from CX input neurons is unclear. To address this question, we intracellularly recorded from GABA-immunoreactive TL neurons, input elements to the locust CX (corresponding to R neurons in Drosophila), while applying visual stimuli simulating unpolarized sunlight and polarized light across the hemisphere above the animal. We show that TL neurons have large receptive fields for both types of stimuli. However, faithful integration of polarization angles across the dorsal hemisphere, or matched-filter ability to encode particular sun positions, was found in only two out of 22 recordings. Those two neurons also showed a good match in sun position coding through polarized and unpolarized light signaling, whereas 20 neurons showed substantial mismatch in signaling of the two compass cues. The data, therefore, suggest that considerable refinement of azimuth coding based on sky compass signals occurs at the synapses from TL neurons to postsynaptic CX compass neurons.
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Affiliation(s)
- Naomi Takahashi
- Department of Biology, Animal Physiology, Philipps-Universität Marburg, D-35032 Marburg, Germany
| | - Frederick Zittrell
- Department of Biology, Animal Physiology, Philipps-Universität Marburg, D-35032 Marburg, Germany
| | - Ronja Hensgen
- Department of Biology, Animal Physiology, Philipps-Universität Marburg, D-35032 Marburg, Germany
| | - Uwe Homberg
- Department of Biology, Animal Physiology, Philipps-Universität Marburg, D-35032 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Germany
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44
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Fisher YE, Marquis M, D’Alessandro I, Wilson RI. Dopamine promotes head direction plasticity during orienting movements. Nature 2022; 612:316-322. [PMID: 36450986 PMCID: PMC9729112 DOI: 10.1038/s41586-022-05485-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 10/25/2022] [Indexed: 12/05/2022]
Abstract
In neural networks that store information in their connection weights, there is a tradeoff between sensitivity and stability1,2. Connections must be plastic to incorporate new information, but if they are too plastic, stored information can be corrupted. A potential solution is to allow plasticity only during epochs when task-specific information is rich, on the basis of a 'when-to-learn' signal3. We reasoned that dopamine provides a when-to-learn signal that allows the brain's spatial maps to update when new spatial information is available-that is, when an animal is moving. Here we show that the dopamine neurons innervating the Drosophila head direction network are specifically active when the fly turns to change its head direction. Moreover, their activity scales with moment-to-moment fluctuations in rotational speed. Pairing dopamine release with a visual cue persistently strengthens the cue's influence on head direction cells. Conversely, inhibiting these dopamine neurons decreases the influence of the cue. This mechanism should accelerate learning during moments when orienting movements are providing a rich stream of head direction information, allowing learning rates to be low at other times to protect stored information. Our results show how spatial learning in the brain can be compressed into discrete epochs in which high learning rates are matched to high rates of information intake.
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Affiliation(s)
- Yvette E. Fisher
- grid.38142.3c000000041936754XDepartment of Neurobiology, Harvard Medical School, Boston, MA USA ,grid.47840.3f0000 0001 2181 7878Present Address: Department of Molecular and Cellular Biology, University of California Berkeley, Berkeley, CA USA ,grid.499295.a0000 0004 9234 0175Present Address: Chan Zuckerberg Biohub, San Francisco, CA USA
| | - Michael Marquis
- grid.38142.3c000000041936754XDepartment of Neurobiology, Harvard Medical School, Boston, MA USA
| | - Isabel D’Alessandro
- grid.38142.3c000000041936754XDepartment of Neurobiology, Harvard Medical School, Boston, MA USA
| | - Rachel I. Wilson
- grid.38142.3c000000041936754XDepartment of Neurobiology, Harvard Medical School, Boston, MA USA
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45
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Sun X, Yue S, Mangan M. How the insect central complex could coordinate multimodal navigation. eLife 2021; 10:e73077. [PMID: 34882094 PMCID: PMC8741217 DOI: 10.7554/elife.73077] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 12/08/2021] [Indexed: 11/13/2022] Open
Abstract
The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours, but their applicability across sensory and task domains remains untested. Here, we assess the capacity of our previous model (Sun et al. 2020) of visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically plausible neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to allow the transfer cues from unstable/egocentric to stable/geocentric frames of reference, providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.
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Affiliation(s)
- Xuelong Sun
- Machine Life and Intelligence Research Centre, School of Mathematics and Information Science, Guangzhou UniversityGuangzhouChina
- Computational Intelligence Lab and L-CAS, School of Computer Science, University of LincolnLincolnUnited Kingdom
| | - Shigang Yue
- Machine Life and Intelligence Research Centre, School of Mathematics and Information Science, Guangzhou UniversityGuangzhouChina
- Computational Intelligence Lab and L-CAS, School of Computer Science, University of LincolnLincolnUnited Kingdom
| | - Michael Mangan
- Sheffield Robotics, Department of Computer Science, University of SheffieldSheffieldUnited Kingdom
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46
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Beetz MJ, Kraus C, Franzke M, Dreyer D, Strube-Bloss MF, Rössler W, Warrant EJ, Merlin C, El Jundi B. Flight-induced compass representation in the monarch butterfly heading network. Curr Biol 2021; 32:338-349.e5. [PMID: 34822766 DOI: 10.1016/j.cub.2021.11.009] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/27/2021] [Accepted: 11/03/2021] [Indexed: 10/19/2022]
Abstract
For navigation, animals use a robust internal compass. Compass navigation is crucial for long-distance migrating animals like monarch butterflies, which use the sun to navigate over 4,000 km to their overwintering sites every fall. Sun-compass neurons of the central complex have only been recorded in immobile butterflies, and experimental evidence for encoding the animal's heading in these neurons is still missing. Although the activity of central-complex neurons exhibits a locomotor-dependent modulation in many insects, the function of such modulations remains unexplored. Here, we developed tetrode recordings from tethered flying monarch butterflies to reveal how flight modulates heading representation. We found that, during flight, heading-direction neurons change their tuning, transforming the central-complex network to function as a global compass. This compass is characterized by the dominance of processing steering feedback and allows for robust heading representation even under unreliable visual scenarios, an ideal strategy for maintaining a migratory heading over enormous distances.
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Affiliation(s)
- M Jerome Beetz
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany.
| | - Christian Kraus
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany
| | - Myriam Franzke
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany
| | - David Dreyer
- Lund Vision Group, Department of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
| | - Martin F Strube-Bloss
- Department of Biological Cybernetics, University of Bielefeld, Universitätsstraße 25, 33615 Bielefeld, Germany
| | - Wolfgang Rössler
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany
| | - Eric J Warrant
- Lund Vision Group, Department of Biology, Lund University, Sölvegatan 35, 22362 Lund, Sweden
| | - Christine Merlin
- Department of Biology and Center for Biological Clocks Research, Texas A&M University, College Station, TX 77843, USA
| | - Basil El Jundi
- Zoology II, Biocenter, University of Würzburg, Am Hubland 1, 97074 Würzburg, Germany.
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47
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Hulse BK, Haberkern H, Franconville R, Turner-Evans DB, Takemura SY, Wolff T, Noorman M, Dreher M, Dan C, Parekh R, Hermundstad AM, Rubin GM, Jayaraman V. A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection. eLife 2021; 10:66039. [PMID: 34696823 PMCID: PMC9477501 DOI: 10.7554/elife.66039] [Citation(s) in RCA: 118] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 09/07/2021] [Indexed: 11/13/2022] Open
Abstract
Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly's head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.
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Affiliation(s)
- Brad K Hulse
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Hannah Haberkern
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Romain Franconville
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | | | - Tanya Wolff
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Marcella Noorman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Marisa Dreher
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Chuntao Dan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Ruchi Parekh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Vivek Jayaraman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
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48
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Plasticity between visual input pathways and the head direction system. Curr Opin Neurobiol 2021; 71:60-68. [PMID: 34619578 DOI: 10.1016/j.conb.2021.08.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 08/26/2021] [Indexed: 11/21/2022]
Abstract
Animals can maintain a stable sense of direction even when they navigate in novel environments, but how the animal's brain interprets and encodes unfamiliar sensory information in its navigation system to maintain a stable sense of direction is a mystery. Recent studies have suggested that distinct brain structures of mammals and insects have evolved to solve this common problem with strategies that share computational principles; specifically, a network structure called a ring attractor maintains the sense of direction. Initially, in a novel environment, the animal's sense of direction relies on self-motion cues. Over time, the mapping from visual inputs to head direction cells, responsible for the sense of direction, is established via experience-dependent plasticity. Yet the mechanisms that facilitate acquiring a world-centered sense of direction, how many environments can be stored in memory, and what visual features are selected, all remain unknown. Thanks to recent advances in large scale physiological recording, genetic tools, and theory, these mechanisms may soon be revealed.
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49
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Sayre ME, Templin R, Chavez J, Kempenaers J, Heinze S. A projectome of the bumblebee central complex. eLife 2021; 10:e68911. [PMID: 34523418 PMCID: PMC8504972 DOI: 10.7554/elife.68911] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 09/14/2021] [Indexed: 12/29/2022] Open
Abstract
Insects have evolved diverse and remarkable strategies for navigating in various ecologies all over the world. Regardless of species, insects share the presence of a group of morphologically conserved neuropils known collectively as the central complex (CX). The CX is a navigational center, involved in sensory integration and coordinated motor activity. Despite the fact that our understanding of navigational behavior comes predominantly from ants and bees, most of what we know about the underlying neural circuitry of such behavior comes from work in fruit flies. Here, we aim to close this gap, by providing the first comprehensive map of all major columnar neurons and their projection patterns in the CX of a bee. We find numerous components of the circuit that appear to be highly conserved between the fly and the bee, but also highlight several key differences which are likely to have important functional ramifications.
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Affiliation(s)
- Marcel Ethan Sayre
- Lund University, Lund Vision Group, Department of BiologyLundSweden
- Macquarie University, Department of Biological SciencesSydneyAustralia
| | - Rachel Templin
- Queensland Brain Institute, University of QueenslandBrisbaneSweden
| | - Johanna Chavez
- Lund University, Lund Vision Group, Department of BiologyLundSweden
| | | | - Stanley Heinze
- Lund University, Lund Vision Group, Department of BiologyLundSweden
- Lund University, NanoLundLundSweden
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50
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Yan Y, Burgess N, Bicanski A. A model of head direction and landmark coding in complex environments. PLoS Comput Biol 2021; 17:e1009434. [PMID: 34570749 PMCID: PMC8496825 DOI: 10.1371/journal.pcbi.1009434] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 10/07/2021] [Accepted: 09/08/2021] [Indexed: 01/27/2023] Open
Abstract
Environmental information is required to stabilize estimates of head direction (HD) based on angular path integration. However, it is unclear how this happens in real-world (visually complex) environments. We present a computational model of how visual feedback can stabilize HD information in environments that contain multiple cues of varying stability and directional specificity. We show how combinations of feature-specific visual inputs can generate a stable unimodal landmark bearing signal, even in the presence of multiple cues and ambiguous directional specificity. This signal is associated with the retrosplenial HD signal (inherited from thalamic HD cells) and conveys feedback to the subcortical HD circuitry. The model predicts neurons with a unimodal encoding of the egocentric orientation of the array of landmarks, rather than any one particular landmark. The relationship between these abstract landmark bearing neurons and head direction cells is reminiscent of the relationship between place cells and grid cells. Their unimodal encoding is formed from visual inputs via a modified version of Oja's Subspace Algorithm. The rule allows the landmark bearing signal to disconnect from directionally unstable or ephemeral cues, incorporate newly added stable cues, support orientation across many different environments (high memory capacity), and is consistent with recent empirical findings on bidirectional HD firing reported in the retrosplenial cortex. Our account of visual feedback for HD stabilization provides a novel perspective on neural mechanisms of spatial navigation within richer sensory environments, and makes experimentally testable predictions.
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Affiliation(s)
- Yijia Yan
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Neil Burgess
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Andrej Bicanski
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
- School of Psychology, Newcastle University, Newcastle upon Tyne, United Kingdom
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