1
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Mancini N, Thoener J, Tafani E, Pauls D, Mayseless O, Strauch M, Eichler K, Champion A, Kobler O, Weber D, Sen E, Weiglein A, Hartenstein V, Chytoudis-Peroudis CC, Jovanic T, Thum AS, Rohwedder A, Schleyer M, Gerber B. Rewarding Capacity of Optogenetically Activating a Giant GABAergic Central-Brain Interneuron in Larval Drosophila. J Neurosci 2023; 43:7393-7428. [PMID: 37734947 PMCID: PMC10621887 DOI: 10.1523/jneurosci.2310-22.2023] [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: 12/17/2022] [Revised: 07/19/2023] [Accepted: 08/26/2023] [Indexed: 09/23/2023] Open
Abstract
Larvae of the fruit fly Drosophila melanogaster are a powerful study case for understanding the neural circuits underlying behavior. Indeed, the numerical simplicity of the larval brain has permitted the reconstruction of its synaptic connectome, and genetic tools for manipulating single, identified neurons allow neural circuit function to be investigated with relative ease and precision. We focus on one of the most complex neurons in the brain of the larva (of either sex), the GABAergic anterior paired lateral neuron (APL). Using behavioral and connectomic analyses, optogenetics, Ca2+ imaging, and pharmacology, we study how APL affects associative olfactory memory. We first provide a detailed account of the structure, regional polarity, connectivity, and metamorphic development of APL, and further confirm that optogenetic activation of APL has an inhibiting effect on its main targets, the mushroom body Kenyon cells. All these findings are consistent with the previously identified function of APL in the sparsening of sensory representations. To our surprise, however, we found that optogenetically activating APL can also have a strong rewarding effect. Specifically, APL activation together with odor presentation establishes an odor-specific, appetitive, associative short-term memory, whereas naive olfactory behavior remains unaffected. An acute, systemic inhibition of dopamine synthesis as well as an ablation of the dopaminergic pPAM neurons impair reward learning through APL activation. Our findings provide a study case of complex circuit function in a numerically simple brain, and suggest a previously unrecognized capacity of central-brain GABAergic neurons to engage in dopaminergic reinforcement.SIGNIFICANCE STATEMENT The single, identified giant anterior paired lateral (APL) neuron is one of the most complex neurons in the insect brain. It is GABAergic and contributes to the sparsening of neuronal activity in the mushroom body, the memory center of insects. We provide the most detailed account yet of the structure of APL in larval Drosophila as a neurogenetically accessible study case. We further reveal that, contrary to expectations, the experimental activation of APL can exert a rewarding effect, likely via dopaminergic reward pathways. The present study both provides an example of unexpected circuit complexity in a numerically simple brain, and reports an unexpected effect of activity in central-brain GABAergic circuits.
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Affiliation(s)
- Nino Mancini
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Juliane Thoener
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Esmeralda Tafani
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Dennis Pauls
- Department of Animal Physiology, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Oded Mayseless
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Martin Strauch
- Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, 52074, Germany
| | - Katharina Eichler
- Institute of Neurobiology, University of Puerto Rico Medical Science Campus, Old San Juan, Puerto Rico, 00901
| | - Andrew Champion
- Department of Physiology, Development and Neuroscience, Cambridge University, Cambridge, CB2 3EL, United Kingdom
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, 20147, Virginia
| | - Oliver Kobler
- Leibniz Institute for Neurobiology, Combinatorial Neuroimaging Core Facility, Magdeburg, 39118, Germany
| | - Denise Weber
- Department of Genetics, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Edanur Sen
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Aliće Weiglein
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Volker Hartenstein
- University of California, Department of Molecular, Cell and Developmental Biology, Los Angeles, California 90095-1606
| | | | - Tihana Jovanic
- Université Paris-Saclay, Centre National de la Recherche Scientifique, Institut des neurosciences Paris-Saclay, Saclay, 91400, France
| | - Andreas S Thum
- Department of Genetics, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Astrid Rohwedder
- Department of Genetics, Institute of Biology, Leipzig University, Leipzig, 04103, Germany
| | - Michael Schleyer
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
| | - Bertram Gerber
- Leibniz Institute for Neurobiology, Department Genetics of Learning and Memory, Magdeburg, 39118, Germany
- Center for Behavioral Brain Sciences, Magdeburg, 39106, Germany
- Institute for Biology, Otto von Guericke University, Magdeburg, 39120, Germany
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2
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Mohamed A, Malekou I, Sim T, O'Kane CJ, Maait Y, Scullion B, Masuda-Nakagawa LM. Mushroom body output neurons MBON-a1/a2 define an odor intensity channel that regulates behavioral odor discrimination learning in larval Drosophila. Front Physiol 2023; 14:1111244. [PMID: 37256074 PMCID: PMC10225628 DOI: 10.3389/fphys.2023.1111244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 05/02/2023] [Indexed: 06/01/2023] Open
Abstract
The sensitivity of animals to sensory input must be regulated to ensure that signals are detected and also discriminable. However, how circuits regulate the dynamic range of sensitivity to sensory stimuli is not well understood. A given odor is represented in the insect mushroom bodies (MBs) by sparse combinatorial coding by Kenyon cells (KCs), forming an odor quality representation. To address how intensity of sensory stimuli is processed at the level of the MB input region, the calyx, we characterized a set of novel mushroom body output neurons that respond preferentially to high odor concentrations. We show that a pair of MB calyx output neurons, MBON-a1/2, are postsynaptic in the MB calyx, where they receive extensive synaptic inputs from KC dendrites, the inhibitory feedback neuron APL, and octopaminergic sVUM1 neurons, but relatively few inputs from projection neurons. This pattern is broadly consistent in the third-instar larva as well as in the first instar connectome. MBON-a1/a2 presynaptic terminals innervate a region immediately surrounding the MB medial lobe output region in the ipsilateral and contralateral brain hemispheres. By monitoring calcium activity using jRCamP1b, we find that MBON-a1/a2 responses are odor-concentration dependent, responding only to ethyl acetate (EA) concentrations higher than a 200-fold dilution, in contrast to MB neurons which are more concentration-invariant and respond to EA dilutions as low as 10-4. Optogenetic activation of the calyx-innervating sVUM1 modulatory neurons originating in the SEZ (Subesophageal zone), did not show a detectable effect on MBON-a1/a2 odor responses. Optogenetic activation of MBON-a1/a2 using CsChrimson impaired odor discrimination learning compared to controls. We propose that MBON-a1/a2 form an output channel of the calyx, summing convergent sensory and modulatory input, firing preferentially to high odor concentration, and might affect the activity of downstream MB targets.
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3
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Honda T. Optogenetic and thermogenetic manipulation of defined neural circuits and behaviors in Drosophila. Learn Mem 2022; 29:100-109. [PMID: 35332066 PMCID: PMC8973390 DOI: 10.1101/lm.053556.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 03/06/2022] [Indexed: 11/25/2022]
Abstract
Neural network dynamics underlying flexible animal behaviors remain elusive. The fruit fly Drosophila melanogaster is considered an excellent model in behavioral neuroscience because of its simple neuroanatomical architecture and the availability of various genetic methods. Moreover, Drosophila larvae's transparent body allows investigators to use optical methods on freely moving animals, broadening research directions. Activating or inhibiting well-defined events in excitable cells with a fine temporal resolution using optogenetics and thermogenetics led to the association of functions of defined neural populations with specific behavioral outputs such as the induction of associative memory. Furthermore, combining optogenetics and thermogenetics with state-of-the-art approaches, including connectome mapping and machine learning-based behavioral quantification, might provide a complete view of the experience- and time-dependent variations of behavioral responses. These methodologies allow further understanding of the functional connections between neural circuits and behaviors such as chemosensory, motivational, courtship, and feeding behaviors and sleep, learning, and memory.
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Affiliation(s)
- Takato Honda
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
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4
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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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5
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Gowda SBM, Salim S, Mohammad F. Anatomy and Neural Pathways Modulating Distinct Locomotor Behaviors in Drosophila Larva. BIOLOGY 2021; 10:90. [PMID: 33504061 PMCID: PMC7910854 DOI: 10.3390/biology10020090] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/07/2020] [Accepted: 12/30/2020] [Indexed: 11/17/2022]
Abstract
The control of movements is a fundamental feature shared by all animals. At the most basic level, simple movements are generated by coordinated neural activity and muscle contraction patterns that are controlled by the central nervous system. How behavioral responses to various sensory inputs are processed and integrated by the downstream neural network to produce flexible and adaptive behaviors remains an intense area of investigation in many laboratories. Due to recent advances in experimental techniques, many fundamental neural pathways underlying animal movements have now been elucidated. For example, while the role of motor neurons in locomotion has been studied in great detail, the roles of interneurons in animal movements in both basic and noxious environments have only recently been realized. However, the genetic and transmitter identities of many of these interneurons remains unclear. In this review, we provide an overview of the underlying circuitry and neural pathways required by Drosophila larvae to produce successful movements. By improving our understanding of locomotor circuitry in model systems such as Drosophila, we will have a better understanding of how neural circuits in organisms with different bodies and brains lead to distinct locomotion types at the organism level. The understanding of genetic and physiological components of these movements types also provides directions to understand movements in higher organisms.
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Affiliation(s)
| | | | - Farhan Mohammad
- Division of Biological and Biomedical Sciences (BBS), College of Health & Life Sciences (CHLS), Hamad Bin Khalifa University (HBKU), Doha 34110, Qatar; (S.B.M.G.); (S.S.)
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6
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Wong JYH, Wan BA, Bland T, Montagnese M, McLachlan AD, O'Kane CJ, Zhang SW, Masuda-Nakagawa LM. Octopaminergic neurons have multiple targets in Drosophila larval mushroom body calyx and can modulate behavioral odor discrimination. ACTA ACUST UNITED AC 2021; 28:53-71. [PMID: 33452115 PMCID: PMC7812863 DOI: 10.1101/lm.052159.120] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 10/30/2020] [Indexed: 12/17/2022]
Abstract
Discrimination of sensory signals is essential for an organism to form and retrieve memories of relevance in a given behavioral context. Sensory representations are modified dynamically by changes in behavioral state, facilitating context-dependent selection of behavior, through signals carried by noradrenergic input in mammals, or octopamine (OA) in insects. To understand the circuit mechanisms of this signaling, we characterized the function of two OA neurons, sVUM1 neurons, that originate in the subesophageal zone (SEZ) and target the input region of the memory center, the mushroom body (MB) calyx, in larval Drosophila. We found that sVUM1 neurons target multiple neurons, including olfactory projection neurons (PNs), the inhibitory neuron APL, and a pair of extrinsic output neurons, but relatively few mushroom body intrinsic neurons, Kenyon cells. PN terminals carried the OA receptor Oamb, a Drosophila α1-adrenergic receptor ortholog. Using an odor discrimination learning paradigm, we showed that optogenetic activation of OA neurons compromised discrimination of similar odors but not learning ability. Our results suggest that sVUM1 neurons modify odor representations via multiple extrinsic inputs at the sensory input area to the MB olfactory learning circuit.
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Affiliation(s)
- J Y Hilary Wong
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Bo Angela Wan
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Tom Bland
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Marcella Montagnese
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Alex D McLachlan
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Cahir J O'Kane
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Shuo Wei Zhang
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
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7
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Puñal VM, Ahmed M, Thornton-Kolbe EM, Clowney EJ. Untangling the wires: development of sparse, distributed connectivity in the mushroom body calyx. Cell Tissue Res 2021; 383:91-112. [PMID: 33404837 PMCID: PMC9835099 DOI: 10.1007/s00441-020-03386-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 12/07/2020] [Indexed: 01/16/2023]
Abstract
Appropriate perception and representation of sensory stimuli pose an everyday challenge to the brain. In order to represent the wide and unpredictable array of environmental stimuli, principle neurons of associative learning regions receive sparse, combinatorial sensory inputs. Despite the broad role of such networks in sensory neural circuits, the developmental mechanisms underlying their emergence are not well understood. As mammalian sensory coding regions are numerically complex and lack the accessibility of simpler invertebrate systems, we chose to focus this review on the numerically simpler, yet functionally similar, Drosophila mushroom body calyx. We bring together current knowledge about the cellular and molecular mechanisms orchestrating calyx development, in addition to drawing insights from literature regarding construction of sparse wiring in the mammalian cerebellum. From this, we formulate hypotheses to guide our future understanding of the development of this critical perceptual center.
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Affiliation(s)
- Vanessa M. Puñal
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA,Department of Molecular & Integrative Physiology, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Maria Ahmed
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA
| | - Emma M. Thornton-Kolbe
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA,Neuroscience Graduate Program, The University of Michigan, Ann Arbor, MI 48109, USA
| | - E. Josephine Clowney
- Department of Molecular, Cellular & Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, USA
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8
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Jovanic T. Studying neural circuits of decision-making in Drosophila larva. J Neurogenet 2020; 34:162-170. [PMID: 32054384 DOI: 10.1080/01677063.2020.1719407] [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: 10/25/2022]
Abstract
To study neural circuits underlying decisions, the model organism used for that purpose has to be simple enough to be able to dissect the circuitry neuron by neuron across the nervous system and in the same time complex enough to be able to perform different types of decisions. Here, I lay out the case: (1) that Drosophila larva is an advantageous model system that balances well these two requirements and (2) the insights gained from this model, assuming that circuit principles may be shared across species, can be used to advance our knowledge of neural circuit implementation of decision-making in general, including in more complex brains.
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Affiliation(s)
- Tihana Jovanic
- Université Paris-Saclay, CNRS, Institut des Neurosciences Paris Saclay, Gif-sur-Yvette, France.,Decision and Bayesian Computation, UMR 3571 Neuroscience Department & USR 3756 (C3BI/DBC), Institut Pasteur & CNRS, Paris, France
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9
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Young BD, Escalon JA, Mathew D. Odors: from chemical structures to gaseous plumes. Neurosci Biobehav Rev 2020; 111:19-29. [PMID: 31931034 DOI: 10.1016/j.neubiorev.2020.01.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 01/07/2020] [Accepted: 01/07/2020] [Indexed: 10/25/2022]
Abstract
We are immersed within an odorous sea of chemical currents that we parse into individual odors with complex structures. Odors have been posited as determined by the structural relation between the molecules that compose the chemical compounds and their interactions with the receptor site. But, naturally occurring smells are parsed from gaseous odor plumes. To give a comprehensive account of the nature of odors the chemosciences must account for these large distributed entities as well. We offer a focused review of what is known about the perception of odor plumes for olfactory navigation and tracking, which we then connect to what is known about the role odorants play as properties of the plume in determining odor identity with respect to odor quality. We end by motivating our central claim that more research needs to be conducted on the role that odorants play within the odor plume in determining odor identity.
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Affiliation(s)
- Benjamin D Young
- Philosophy and Neuroscience, University of Nevada, 1664 N Virginia St, Reno, NV 89557, United States.
| | | | - Dennis Mathew
- Biology and Neuroscience, University of Nevada, Reno, United States.
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10
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Akiba M, Sugimoto K, Aoki R, Murakami R, Miyashita T, Hashimoto R, Hiranuma A, Yamauchi J, Ueno T, Morimoto T. Dopamine modulates the optomotor response to unreliable visual stimuli in Drosophila melanogaster. Eur J Neurosci 2019; 51:822-839. [PMID: 31834948 DOI: 10.1111/ejn.14648] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 11/18/2019] [Accepted: 12/05/2019] [Indexed: 01/21/2023]
Abstract
State-dependent modulation of sensory systems has been studied in many organisms and is possibly mediated through neuromodulators such as monoamine neurotransmitters. Among these, dopamine is involved in many aspects of animal behaviour, including movement control, attention, motivation and cognition. However, the precise neural mechanism underlying dopaminergic modulation of behaviour induced by sensory stimuli remains poorly understood. Here, we used Drosophila melanogaster to show that dopamine can modulate the optomotor response to moving visual stimuli including noise. The optomotor response is the head-turning response to moving objects, which is observed in most sight-reliant animals including mammals and insects. First, the effects of the dopamine system on the optomotor response were investigated in mutant flies deficient in dopamine receptors D1R1 or D1R2, which are involved in the modulation of sleep-arousal in flies. We examined the optomotor response in D1R1 knockout (D1R1 KO) and D1R2 knockout (D1R2 KO) flies and found that it was not affected in D1R1 KO flies; however, it was significantly reduced in D1R2 KO flies compared with the wild type. Using cell-type-specific expression of an RNA interference construct of D1R2, we identified the fan-shaped body, a part of the central complex, responsible for dopamine-mediated modulation of the optomotor response. In particular, pontine cells in the fan-shaped body seemed important in the modulation of the optomotor response, and their neural activity was required for the optomotor response. These results suggest a novel role of the central complex in the modulation of a behaviour based on the processing of sensory stimulations.
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Affiliation(s)
- Masumi Akiba
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Kentaro Sugimoto
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan.,Department of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo, Japan
| | - Risa Aoki
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Ryo Murakami
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan
| | | | - Riho Hashimoto
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Anna Hiranuma
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Junji Yamauchi
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Taro Ueno
- Department of Biomolecular Science, Graduate School of Science, Toho University, Chiba, Japan
| | - Takako Morimoto
- Laboratory of Molecular Neuroscience and Neurology, School of Life Sciences, University of Pharmacy and Life Sciences, Tokyo, Japan
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11
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Jovanic T, Winding M, Cardona A, Truman JW, Gershow M, Zlatic M. Neural Substrates of Drosophila Larval Anemotaxis. Curr Biol 2019; 29:554-566.e4. [PMID: 30744969 PMCID: PMC6380933 DOI: 10.1016/j.cub.2019.01.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 11/29/2018] [Accepted: 01/04/2019] [Indexed: 01/08/2023]
Abstract
Animals use sensory information to move toward more favorable conditions. Drosophila larvae can move up or down gradients of odors (chemotax), light (phototax), and temperature (thermotax) by modulating the probability, direction, and size of turns based on sensory input. Whether larvae can anemotax in gradients of mechanosensory cues is unknown. Further, although many of the sensory neurons that mediate taxis have been described, the central circuits are not well understood. Here, we used high-throughput, quantitative behavioral assays to demonstrate Drosophila larvae anemotax in gradients of wind speeds and to characterize the behavioral strategies involved. We found that larvae modulate the probability, direction, and size of turns to move away from higher wind speeds. This suggests that similar central decision-making mechanisms underlie taxis in somatosensory and other sensory modalities. By silencing the activity of single or very few neuron types in a behavioral screen, we found two sensory (chordotonal and multidendritic class III) and six nerve cord neuron types involved in anemotaxis. We reconstructed the identified neurons in an electron microscopy volume that spans the entire larval nervous system and found they received direct input from the mechanosensory neurons or from each other. In this way, we identified local interneurons and first- and second-order subesophageal zone (SEZ) and brain projection neurons. Finally, silencing a dopaminergic brain neuron type impairs anemotaxis. These findings suggest that anemotaxis involves both nerve cord and brain circuits. The candidate neurons and circuitry identified in our study provide a basis for future detailed mechanistic understanding of the circuit principles of anemotaxis.
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Affiliation(s)
- Tihana Jovanic
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
| | - Michael Winding
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Department of Physiology, Development, and Neuroscience, Cambridge University, Cambridge, UK
| | - James W Truman
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Friday Harbor Laboratories, University of Washington, Friday Harbor, WA 98250, USA
| | - Marc Gershow
- Department of Physics, New York University, New York, NY, USA; Center for Neural Science, New York University, New York, NY, USA; Neuroscience Institute, New York University, New York, NY, USA.
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA; Department of Zoology, Cambridge University, Cambridge, UK.
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12
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Marescotti M, Lagogiannis K, Webb B, Davies RW, Armstrong JD. Monitoring brain activity and behaviour in freely moving Drosophila larvae using bioluminescence. Sci Rep 2018; 8:9246. [PMID: 29915372 PMCID: PMC6006295 DOI: 10.1038/s41598-018-27043-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 05/09/2018] [Indexed: 12/18/2022] Open
Abstract
We present a bioluminescence method, based on the calcium-reporter Aequorin (AEQ), that exploits targeted transgenic expression patterns to identify activity of specific neural groups in the larval Drosophila nervous system. We first refine, for intact but constrained larva, the choice of Aequorin transgene and method of delivery of the co-factor coelenterazine and assay the luminescence signal produced for different neural expression patterns and concentrations of co-factor, using standard photo-counting techniques. We then develop an apparatus that allows simultaneous measurement of this neural signal while video recording the crawling path of an unconstrained animal. The setup also enables delivery and measurement of an olfactory cue (CO2) and we demonstrate the ability to record synchronized changes in Kenyon cell activity and crawling speed caused by the stimulus. Our approach is thus shown to be an effective and affordable method for studying the neural basis of behavior in Drosophila larvae.
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Affiliation(s)
- Manuela Marescotti
- Brainwave-Discovery Ltd., Edinburgh, Scotland, UK. .,The University of Edinburgh, Edinburgh, Scotland, UK.
| | - Konstantinos Lagogiannis
- The University of Edinburgh, Edinburgh, Scotland, UK.,Centre Of Developmental Neuroscience, King's College London, London, UK
| | - Barbara Webb
- The University of Edinburgh, Edinburgh, Scotland, UK
| | - R Wayne Davies
- Brainwave-Discovery Ltd., Edinburgh, Scotland, UK.,The University of Edinburgh, Edinburgh, Scotland, UK
| | - J Douglas Armstrong
- Brainwave-Discovery Ltd., Edinburgh, Scotland, UK.,The University of Edinburgh, Edinburgh, Scotland, UK
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13
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Eichler K, Li F, Litwin-Kumar A, Park Y, Andrade I, Schneider-Mizell CM, Saumweber T, Huser A, Eschbach C, Gerber B, Fetter RD, Truman JW, Priebe CE, Abbott LF, Thum AS, Zlatic M, Cardona A. The complete connectome of a learning and memory centre in an insect brain. Nature 2017; 548:175-182. [PMID: 28796202 PMCID: PMC5806122 DOI: 10.1038/nature23455] [Citation(s) in RCA: 275] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 07/04/2017] [Indexed: 12/19/2022]
Abstract
Associating stimuli with positive or negative reinforcement is essential for survival, but a complete wiring diagram of a higher-order circuit supporting associative memory has not been previously available. Here we reconstruct one such circuit at synaptic resolution, the Drosophila larval mushroom body. We find that most Kenyon cells integrate random combinations of inputs but that a subset receives stereotyped inputs from single projection neurons. This organization maximizes performance of a model output neuron on a stimulus discrimination task. We also report a novel canonical circuit in each mushroom body compartment with previously unidentified connections: reciprocal Kenyon cell to modulatory neuron connections, modulatory neuron to output neuron connections, and a surprisingly high number of recurrent connections between Kenyon cells. Stereotyped connections found between output neurons could enhance the selection of learned behaviours. The complete circuit map of the mushroom body should guide future functional studies of this learning and memory centre.
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Affiliation(s)
- Katharina Eichler
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
- Department of Biology, University of Konstanz, Universitätsstrasse 10, 78464 Konstanz, Germany
| | - Feng Li
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Ashok Litwin-Kumar
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, New York 10027, USA
| | - Youngser Park
- Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, 100 Whitehead Hall, 3400 North Charles Street, Baltimore, Maryland 21218, USA
| | - Ingrid Andrade
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Casey M Schneider-Mizell
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Timo Saumweber
- Abteilung Genetik von Lernen und Gedächtnis, Leibniz Institut für Neurobiologie, 39118 Magdeburg, Germany
| | - Annina Huser
- Department of Biology, University of Konstanz, Universitätsstrasse 10, 78464 Konstanz, Germany
| | - Claire Eschbach
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Bertram Gerber
- Abteilung Genetik von Lernen und Gedächtnis, Leibniz Institut für Neurobiologie, 39118 Magdeburg, Germany
- Otto von Guericke Universität Magdeburg, Institut für Biologie, Verhaltensgenetik, Universitätsplatz 2, D-39106 Magdeburg, Germany
- Otto-von-Guericke University Magdeburg, Center for Behavioral Brain Sciences, Universitätsplatz 2, D-39106 Magdeburg, Germany
| | - Richard D Fetter
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - James W Truman
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
| | - Carey E Priebe
- Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, 100 Whitehead Hall, 3400 North Charles Street, Baltimore, Maryland 21218, USA
| | - L F Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, 3227 Broadway, New York, New York 10027, USA
- Department of Physiology and Cellular Biophysics, Columbia University, Russ Berrie Pavilion, 1150 St Nicholas Avenue, New York, New York 10032, USA
| | - Andreas S Thum
- Department of Biology, University of Konstanz, Universitätsstrasse 10, 78464 Konstanz, Germany
| | - Marta Zlatic
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Albert Cardona
- Howard Hughes Medical Institute Janelia Research Campus, 19700 Helix Drive, Ashburn, Virginia 20147, USA
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
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14
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Risse B, Berh D, Otto N, Klämbt C, Jiang X. FIMTrack: An open source tracking and locomotion analysis software for small animals. PLoS Comput Biol 2017; 13:e1005530. [PMID: 28493862 PMCID: PMC5444858 DOI: 10.1371/journal.pcbi.1005530] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Revised: 05/25/2017] [Accepted: 04/20/2017] [Indexed: 11/18/2022] Open
Abstract
Imaging and analyzing the locomotion behavior of small animals such as Drosophila larvae or C. elegans worms has become an integral subject of biological research. In the past we have introduced FIM, a novel imaging system feasible to extract high contrast images. This system in combination with the associated tracking software FIMTrack is already used by many groups all over the world. However, so far there has not been an in-depth discussion of the technical aspects. Here we elaborate on the implementation details of FIMTrack and give an in-depth explanation of the used algorithms. Among others, the software offers several tracking strategies to cover a wide range of different model organisms, locomotion types, and camera properties. Furthermore, the software facilitates stimuli-based analysis in combination with built-in manual tracking and correction functionalities. All features are integrated in an easy-to-use graphical user interface. To demonstrate the potential of FIMTrack we provide an evaluation of its accuracy using manually labeled data. The source code is available under the GNU GPLv3 at https://github.com/i-git/FIMTrack and pre-compiled binaries for Windows and Mac are available at http://fim.uni-muenster.de.
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Affiliation(s)
- Benjamin Risse
- School of Informatics, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Dimitri Berh
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Nils Otto
- Department of Behaviour and Neuronal Biology, University of Münster, Münster, Germany
| | - Christian Klämbt
- Department of Behaviour and Neuronal Biology, University of Münster, Münster, Germany
| | - Xiaoyi Jiang
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
- * E-mail:
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15
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Berh D, Risse B, Michels T, Otto N, Klambt C. An FIM-Based Long-Term In-Vial Monitoring System for Drosophila Larvae. IEEE Trans Biomed Eng 2016; 64:1862-1874. [PMID: 28113288 DOI: 10.1109/tbme.2016.2628203] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Drosophila larvae are an insightful model and the automated analysis of their behavior is an integral readout in behavioral biology. Current tracking systems, however, entail a disturbance of the animals, are labor-intensive, and cannot be easily used for long-term monitoring purposes. Here, we present a novel monitoring system for Drosophila larvae, which allows us to analyze the animals in cylindrical culture vials. By utilizing the frustrated total internal reflection in combination with a multi-camera/microcomputer setup, we image the complete housing vial surface and, thus, the larvae for days. We introduce a calibration scheme to stitch the images from the multi-camera system and unfold arbitrary cylindrical surfaces to support different vials. As a result, imaging and analysis of a whole population can be done implicitly. For the first time, this allows us to extract long-term activity quantities of larvae without disturbing the animals. We demonstrate the capabilities of this new setup by automatically quantifying the activity of multiple larvae moving in a vial. The accuracy of the system and the spatio-temporal resolution are sufficient to obtain motion trajectories and higher level features, such as body bending. This new setup can be used for in-vial activity monitoring and behavioral analysis and is capable of gathering millions of data points without both disturbing the animals and increasing labor time. In total, we have analyzed 107 671 frames resulting in 8650 trajectories, which are longer than 30 s, and obtained more than 4.2 × 106 measurements.
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16
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Tastekin I, Riedl J, Schilling-Kurz V, Gomez-Marin A, Truman J, Louis M. Role of the Subesophageal Zone in Sensorimotor Control of Orientation in Drosophila Larva. Curr Biol 2015; 25:1448-60. [DOI: 10.1016/j.cub.2015.04.016] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Revised: 04/02/2015] [Accepted: 04/08/2015] [Indexed: 01/14/2023]
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17
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Nehrkorn J, Tanimoto H, Herz AVM, Yarali A. A model for non-monotonic intensity coding. ROYAL SOCIETY OPEN SCIENCE 2015; 2:150120. [PMID: 26064666 PMCID: PMC4453257 DOI: 10.1098/rsos.150120] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2015] [Accepted: 04/09/2015] [Indexed: 05/12/2023]
Abstract
Peripheral neurons of most sensory systems increase their response with increasing stimulus intensity. Behavioural responses, however, can be specific to some intermediate intensity level whose particular value might be innate or associatively learned. Learning such a preference requires an adjustable trans- formation from a monotonic stimulus representation at the sensory periphery to a non-monotonic representation for the motor command. How do neural systems accomplish this task? We tackle this general question focusing on odour-intensity learning in the fruit fly, whose first- and second-order olfactory neurons show monotonic stimulus-response curves. Nevertheless, flies form associative memories specific to particular trained odour intensities. Thus, downstream of the first two olfactory processing layers, odour intensity must be re-coded to enable intensity-specific associative learning. We present a minimal, feed-forward, three-layer circuit, which implements the required transformation by combining excitation, inhibition, and, as a decisive third element, homeostatic plasticity. Key features of this circuit motif are consistent with the known architecture and physiology of the fly olfactory system, whereas alternative mechanisms are either not composed of simple, scalable building blocks or not compatible with physiological observations. The simplicity of the circuit and the robustness of its function under parameter changes make this computational motif an attractive candidate for tuneable non-monotonic intensity coding.
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Affiliation(s)
- Johannes Nehrkorn
- Department of Biology II, Bernstein Center for Computational Neuroscience Munich and Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Martinsried 82152, Germany
- Max Planck Institute of Neurobiology, Martinsried 82152, Germany
| | - Hiromu Tanimoto
- Max Planck Institute of Neurobiology, Martinsried 82152, Germany
- Tohoku University Graduate School of Life Sciences, Sendai 980-8577, Japan
| | - Andreas V. M. Herz
- Department of Biology II, Bernstein Center for Computational Neuroscience Munich and Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Martinsried 82152, Germany
- Authors for correspondence: Andreas V. M. Herz e-mail:
| | - Ayse Yarali
- Max Planck Institute of Neurobiology, Martinsried 82152, Germany
- Research Group Molecular Systems Biology of Learning, Leibniz Institute for Neurobiology, Magdeburg 39118, Germany
- Center for Brain and Behavioural Sciences, Magdeburg, Germany
- Authors for correspondence: Ayse Yarali e-mail:
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