51
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Calabrese RL. Cider vinegar rules. eLife 2018; 7:40271. [PMID: 30141408 PMCID: PMC6108824 DOI: 10.7554/elife.40271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Accepted: 08/22/2018] [Indexed: 11/13/2022] Open
Abstract
Experiments in wind tunnels have shed light on the rules that govern how flies respond when they detect odors.
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52
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de Andres-Bragado L, Mazza C, Senn W, Sprecher SG. Statistical modelling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis. Sci Rep 2018; 8:11272. [PMID: 30050066 PMCID: PMC6062584 DOI: 10.1038/s41598-018-29533-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Accepted: 07/12/2018] [Indexed: 11/08/2022] Open
Abstract
Organisms use environmental cues for directed navigation. Understanding the basic logic behind navigational decisions critically depends on the complexity of the nervous system. Due to the comparably simple organization of the nervous system of the fruit fly larva, it stands as a powerful model to study decision-making processes that underlie directed navigation. We have quantitatively measured phototaxis in response to well-defined sensory inputs. Subsequently, we have formulated a statistical stochastic model based on biased Markov chains to characterize the behavioural basis of negative phototaxis. Our experiments show that larvae make navigational decisions depending on two independent physical variables: light intensity and its spatial gradient. Furthermore, our statistical model quantifies how larvae balance two potentially-contradictory factors: minimizing exposure to light intensity and at the same time maximizing their distance to the light source. We find that the response to the light field is manifestly non-linear, and saturates above an intensity threshold. The model has been validated against our experimental biological data yielding insight into the strategy that larvae use to achieve their goal with respect to the navigational cue of light, an important piece of information for future work to study the role of the different neuronal components in larval phototaxis.
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Affiliation(s)
| | - Christian Mazza
- Department of Mathematics, University of Fribourg, Fribourg, Switzerland.
| | - Walter Senn
- Department of Physiology, University of Bern, Bern, Switzerland.
| | - Simon G Sprecher
- Department of Biology, University of Fribourg, Fribourg, Switzerland.
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53
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Liu M, Sharma AK, Shaevitz JW, Leifer AM. Temporal processing and context dependency in Caenorhabditis elegans response to mechanosensation. eLife 2018; 7:e36419. [PMID: 29943731 PMCID: PMC6054533 DOI: 10.7554/elife.36419] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 06/10/2018] [Indexed: 11/13/2022] Open
Abstract
A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps to reveal the brain's underlying computations. We investigate how the nematode Caenorhabditis elegans responds to time-varying mechanosensory signals using a high-throughput optogenetic assay and automated behavior quantification. We find that the behavioral response is tuned to temporal properties of mechanosensory signals, such as their integral and derivative, that extend over many seconds. Mechanosensory signals, even in the same neurons, can be tailored to elicit different behavioral responses. Moreover, we find that the animal's response also depends on its behavioral context. Most dramatically, the animal ignores all tested mechanosensory stimuli during turns. Finally, we present a linear-nonlinear model that predicts the animal's behavioral response to stimulus.
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Affiliation(s)
- Mochi Liu
- Lewis-Sigler Institute for Integrative GenomicsPrinceton UniversityNew JerseyUnited States
| | - Anuj K Sharma
- Department of PhysicsPrinceton UniversityNew JerseyUnited States
| | - Joshua W Shaevitz
- Lewis-Sigler Institute for Integrative GenomicsPrinceton UniversityNew JerseyUnited States
- Department of PhysicsPrinceton UniversityNew JerseyUnited States
| | - Andrew M Leifer
- Department of PhysicsPrinceton UniversityNew JerseyUnited States
- Princeton Neuroscience InstitutePrinceton UniversityNew JerseyUnited States
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54
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Humberg TH, Bruegger P, Afonso B, Zlatic M, Truman JW, Gershow M, Samuel A, Sprecher SG. Dedicated photoreceptor pathways in Drosophila larvae mediate navigation by processing either spatial or temporal cues. Nat Commun 2018; 9:1260. [PMID: 29593252 PMCID: PMC5871836 DOI: 10.1038/s41467-018-03520-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 02/21/2018] [Indexed: 11/09/2022] Open
Abstract
To integrate changing environmental cues with high spatial and temporal resolution is critical for animals to orient themselves. Drosophila larvae show an effective motor program to navigate away from light sources. How the larval visual circuit processes light stimuli to control navigational decision remains unknown. The larval visual system is composed of two sensory input channels, Rhodopsin5 (Rh5) and Rhodopsin6 (Rh6) expressing photoreceptors (PRs). We here characterize how spatial and temporal information are used to control navigation. Rh6-PRs are required to perceive temporal changes of light intensity during head casts, while Rh5-PRs are required to control behaviors that allow navigation in response to spatial cues. We characterize how distinct behaviors are modulated and identify parallel acting and converging features of the visual circuit. Functional features of the larval visual circuit highlight the principle of how early in a sensory circuit distinct behaviors may be computed by partly overlapping sensory pathways.
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Affiliation(s)
| | - Pascal Bruegger
- Department of Biology, University of Fribourg, 1700, Fribourg, Switzerland
| | - Bruno Afonso
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, 20147, VA, USA
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, 20147, VA, USA.,Department of Zoology, University of Cambridge, CB2 3EJ, Cambridge, UK
| | - James W Truman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, 20147, VA, USA
| | - Marc Gershow
- Department of Physics and Center for Neural Science, New York University, New York, 10003, NY, USA
| | - Aravinthan Samuel
- Department of Physics and Center for Brain Science, Harvard University, Cambridge, 02138, MA, USA
| | - Simon G Sprecher
- Department of Biology, University of Fribourg, 1700, Fribourg, Switzerland.
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55
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Abstract
The need for high-throughput, precise, and meaningful methods for measuring behavior has been amplified by our recent successes in measuring and manipulating neural circuitry. The largest challenges associated with moving in this direction, however, are not technical but are instead conceptual: what numbers should one put on the movements an animal is performing (or not performing)? In this review, I will describe how theoretical and data analytical ideas are interfacing with recently-developed computational and experimental methodologies to answer these questions across a variety of contexts, length scales, and time scales. I will attempt to highlight commonalities between approaches and areas where further advances are necessary to place behavior on the same quantitative footing as other scientific fields.
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Affiliation(s)
- Gordon J Berman
- Department of Biology, Emory University, 1510 Clifton Road NE, Atlanta, 30322, GA, USA.
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56
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Jacob V, Monsempès C, Rospars JP, Masson JB, Lucas P. Olfactory coding in the turbulent realm. PLoS Comput Biol 2017; 13:e1005870. [PMID: 29194457 PMCID: PMC5736211 DOI: 10.1371/journal.pcbi.1005870] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2017] [Revised: 12/19/2017] [Accepted: 11/01/2017] [Indexed: 01/10/2023] Open
Abstract
Long-distance olfactory search behaviors depend on odor detection dynamics. Due to turbulence, olfactory signals travel as bursts of variable concentration and spacing and are characterized by long-tail distributions of odor/no-odor events, challenging the computing capacities of olfactory systems. How animals encode complex olfactory scenes to track the plume far from the source remains unclear. Here we focus on the coding of the plume temporal dynamics in moths. We compare responses of olfactory receptor neurons (ORNs) and antennal lobe projection neurons (PNs) to sequences of pheromone stimuli either with white-noise patterns or with realistic turbulent temporal structures simulating a large range of distances (8 to 64 m) from the odor source. For the first time, we analyze what information is extracted by the olfactory system at large distances from the source. Neuronal responses are analyzed using linear-nonlinear models fitted with white-noise stimuli and used for predicting responses to turbulent stimuli. We found that neuronal firing rate is less correlated with the dynamic odor time course when distance to the source increases because of improper coding during long odor and no-odor events that characterize large distances. Rapid adaptation during long puffs does not preclude however the detection of puff transitions in PNs. Individual PNs but not individual ORNs encode the onset and offset of odor puffs for any temporal structure of stimuli. A higher spontaneous firing rate coupled to an inhibition phase at the end of PN responses contributes to this coding property. This allows PNs to decode the temporal structure of the odor plume at any distance to the source, an essential piece of information moths can use in their tracking behavior.
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Affiliation(s)
- Vincent Jacob
- Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France
- Peuplements végétaux et bioagresseurs en milieu végétal, CIRAD, Université de la Réunion, Saint Pierre, Ile de la Réunion, France
| | - Christelle Monsempès
- Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France
| | - Jean-Pierre Rospars
- Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France
| | - Jean-Baptiste Masson
- Decision and Bayesian Computation, Pasteur Institute, CNRS UMR 3571, 25-28 rue du Dr Roux, 75015 Paris, France
- Bioinformatics and Biostatistics Hub, C3BI, Pasteur Institute, CNRS USR 3756, 25-28 rue du Dr Roux, 75015 Paris, France
| | - Philippe Lucas
- Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France
- * E-mail:
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57
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Calhoun AJ, Murthy M. Quantifying behavior to solve sensorimotor transformations: advances from worms and flies. Curr Opin Neurobiol 2017; 46:90-98. [PMID: 28850885 PMCID: PMC5765764 DOI: 10.1016/j.conb.2017.08.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Revised: 08/05/2017] [Accepted: 08/08/2017] [Indexed: 02/09/2023]
Abstract
The development of new computational tools has recently opened up the study of natural behaviors at a precision that was previously unachievable. These tools permit a highly quantitative analysis of behavioral dynamics at timescales that are well matched to the timescales of neural activity. Here we examine how combining these methods with established techniques for estimating an animal's sensory experience presents exciting new opportunities for dissecting the sensorimotor transformations performed by the nervous system. We focus this review primarily on examples from Caenorhabditis elegans and Drosophila melanogaster-for these model systems, computational approaches to characterize behavior, in combination with unparalleled genetic tools for neural activation, silencing, and recording, have already proven instrumental for illuminating underlying neural mechanisms.
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Affiliation(s)
- Adam J Calhoun
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, United States
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, United States; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, United States
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58
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Sensorimotor computation underlying phototaxis in zebrafish. Nat Commun 2017; 8:651. [PMID: 28935857 PMCID: PMC5608914 DOI: 10.1038/s41467-017-00310-3] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 06/20/2017] [Indexed: 11/09/2022] Open
Abstract
Animals continuously gather sensory cues to move towards favourable environments. Efficient goal-directed navigation requires sensory perception and motor commands to be intertwined in a feedback loop, yet the neural substrate underlying this sensorimotor task in the vertebrate brain remains elusive. Here, we combine virtual-reality behavioural assays, volumetric calcium imaging, optogenetic stimulation and circuit modelling to reveal the neural mechanisms through which a zebrafish performs phototaxis, i.e. actively orients towards a light source. Key to this process is a self-oscillating hindbrain population (HBO) that acts as a pacemaker for ocular saccades and controls the orientation of successive swim-bouts. It further integrates visual stimuli in a state-dependent manner, i.e. its response to visual inputs varies with the motor context, a mechanism that manifests itself in the phase-locked entrainment of the HBO by periodic stimuli. A rate model is developed that reproduces our observations and demonstrates how this sensorimotor processing eventually biases the animal trajectory towards bright regions. Active locomotion requires closed-loop sensorimotor co ordination between perception and action. Here the authors show using behavioural, imaging and modelling approaches that gaze orientation during phototaxis behaviour in larval zebrafish is related to oscillatory dynamics of a neuronal population in the hindbrain.
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59
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Larderet I, Fritsch PM, Gendre N, Neagu-Maier GL, Fetter RD, Schneider-Mizell CM, Truman JW, Zlatic M, Cardona A, Sprecher SG. Organization of the Drosophila larval visual circuit. eLife 2017; 6:28387. [PMID: 30726702 PMCID: PMC5577918 DOI: 10.7554/elife.28387] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 08/07/2017] [Indexed: 11/20/2022] Open
Abstract
Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on photoreceptor neuron types (PR) present, organization of the eye and wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create two converging pathways potentially underlying the computation of ambient light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the larval optic neuropil (LON) suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors.
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Affiliation(s)
- Ivan Larderet
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | | | - Nanae Gendre
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | | | - Richard D Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | - James W Truman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Marta Zlatic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Simon G Sprecher
- Department of Biology, University of Fribourg, Fribourg, Switzerland
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60
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Gorur-Shandilya S, Demir M, Long J, Clark DA, Emonet T. Olfactory receptor neurons use gain control and complementary kinetics to encode intermittent odorant stimuli. eLife 2017; 6:e27670. [PMID: 28653907 PMCID: PMC5524537 DOI: 10.7554/elife.27670] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 06/26/2017] [Indexed: 11/13/2022] Open
Abstract
Insects find food and mates by navigating odorant plumes that can be highly intermittent, with intensities and durations that vary rapidly over orders of magnitude. Much is known about olfactory responses to pulses and steps, but it remains unclear how olfactory receptor neurons (ORNs) detect the intensity and timing of natural stimuli, where the absence of scale in the signal makes detection a formidable olfactory task. By stimulating Drosophila ORNs in vivo with naturalistic and Gaussian stimuli, we show that ORNs adapt to stimulus mean and variance, and that adaptation and saturation contribute to naturalistic sensing. Mean-dependent gain control followed the Weber-Fechner relation and occurred primarily at odor transduction, while variance-dependent gain control occurred at both transduction and spiking. Transduction and spike generation possessed complementary kinetic properties, that together preserved the timing of odorant encounters in ORN spiking, regardless of intensity. Such scale-invariance could be critical during odor plume navigation.
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Affiliation(s)
- Srinivas Gorur-Shandilya
- Interdepartmental Neuroscience Program, Yale University, New Haven, United States
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, United States
| | - Mahmut Demir
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, United States
| | - Junjiajia Long
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, United States
- Department of Physics, Yale University, New Haven, United States
| | - Damon A Clark
- Interdepartmental Neuroscience Program, Yale University, New Haven, United States
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, United States
- Department of Physics, Yale University, New Haven, United States
| | - Thierry Emonet
- Interdepartmental Neuroscience Program, Yale University, New Haven, United States
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, United States
- Department of Physics, Yale University, New Haven, United States
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61
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Ehrlich DE, Schoppik D. Control of Movement Initiation Underlies the Development of Balance. Curr Biol 2017; 27:334-344. [PMID: 28111151 DOI: 10.1016/j.cub.2016.12.003] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Revised: 10/13/2016] [Accepted: 12/05/2016] [Indexed: 11/29/2022]
Abstract
Balance arises from the interplay of external forces acting on the body and internally generated movements. Many animal bodies are inherently unstable, necessitating corrective locomotion to maintain stability. Understanding how developing animals come to balance remains a challenge. Here we study the interplay among environment, sensation, and action as balance develops in larval zebrafish. We first model the physical forces that challenge underwater balance and experimentally confirm that larvae are subject to constant destabilization. Larvae propel in swim bouts that, we find, tend to stabilize the body. We confirm the relationship between locomotion and balance by changing larval body composition, exacerbating instability and eliciting more frequent swimming. Intriguingly, developing zebrafish come to control the initiation of locomotion, swimming preferentially when unstable, thus restoring preferred postures. To test the sufficiency of locomotor-driven stabilization and the developing control of movement timing, we incorporate both into a generative model of swimming. Simulated larvae recapitulate observed postures and movement timing across early development, but only when locomotor-driven stabilization and control of movement initiation are both utilized. We conclude the ability to move when unstable is the key developmental improvement to balance in larval zebrafish. Our work informs how emerging sensorimotor ability comes to impact how and why animals move when they do.
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Affiliation(s)
- David E Ehrlich
- Department of Otolaryngology, Department of Neuroscience and Physiology, and the Neuroscience Institute, New York University Langone School of Medicine, New York, NY 10016, USA
| | - David Schoppik
- Department of Otolaryngology, Department of Neuroscience and Physiology, and the Neuroscience Institute, New York University Langone School of Medicine, New York, NY 10016, USA.
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62
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Kohsaka H, Guertin PA, Nose A. Neural Circuits Underlying Fly Larval Locomotion. Curr Pharm Des 2017; 23:1722-1733. [PMID: 27928962 PMCID: PMC5470056 DOI: 10.2174/1381612822666161208120835] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 12/01/2016] [Indexed: 12/17/2022]
Abstract
Locomotion is a complex motor behavior that may be expressed in different ways using a variety of strategies depending upon species and pathological or environmental conditions. Quadrupedal or bipedal walking, running, swimming, flying and gliding constitute some of the locomotor modes enabling the body, in all cases, to move from one place to another. Despite these apparent differences in modes of locomotion, both vertebrate and invertebrate species share, at least in part, comparable neural control mechanisms for locomotor rhythm and pattern generation and modulation. Significant advances have been made in recent years in studies of the genetic aspects of these control systems. Findings made specifically using Drosophila (fruit fly) models and preparations have contributed to further understanding of the key role of genes in locomotion. This review focuses on some of the main findings made in larval fruit flies while briefly summarizing the basic advantages of using this powerful animal model for studying the neural locomotor system.
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Affiliation(s)
- Hiroshi Kohsaka
- Department of Complexity Science and Engineering, University of Tokyo, Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
| | - Pierre A. Guertin
- Department of Psychiatry & Neurosciences, Laval University, Québec City, QC, Canada
| | - Akinao Nose
- Department of Complexity Science and Engineering, University of Tokyo, Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
- Department of Physics, Graduate School of Science, University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
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63
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Wystrach A, Lagogiannis K, Webb B. Continuous lateral oscillations as a core mechanism for taxis in Drosophila larvae. eLife 2016; 5. [PMID: 27751233 PMCID: PMC5117870 DOI: 10.7554/elife.15504] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Accepted: 10/17/2016] [Indexed: 12/19/2022] Open
Abstract
Taxis behaviour in Drosophila larva is thought to consist of distinct control mechanisms triggering specific actions. Here, we support a simpler hypothesis: that taxis results from direct sensory modulation of continuous lateral oscillations of the anterior body, sparing the need for ‘action selection’. Our analysis of larvae motion reveals a rhythmic, continuous lateral oscillation of the anterior body, encompassing all head-sweeps, small or large, without breaking the oscillatory rhythm. Further, we show that an agent-model that embeds this hypothesis reproduces a surprising number of taxis signatures observed in larvae. Also, by coupling the sensory input to a neural oscillator in continuous time, we show that the mechanism is robust and biologically plausible. The mechanism provides a simple architecture for combining information across modalities, and explaining how learnt associations modulate taxis. We discuss the results in the light of larval neural circuitry and make testable predictions. DOI:http://dx.doi.org/10.7554/eLife.15504.001
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Affiliation(s)
- Antoine Wystrach
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.,Centre de recherche sur la cognition animal, CNRS, Universite de Toulouse, Toulouse, United Kingdom
| | | | - Barbara Webb
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
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64
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Grimaud J, Lledo PM. Illuminating odors: when optogenetics brings to light unexpected olfactory abilities. ACTA ACUST UNITED AC 2016; 23:249-54. [PMID: 27194792 PMCID: PMC4880145 DOI: 10.1101/lm.041269.115] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Accepted: 03/17/2016] [Indexed: 11/25/2022]
Abstract
For hundreds of years, the sense of smell has generated great interest in the world literature, oenologists, and perfume makers but less of scientists. Only recently this sensory modality has gained new attraction in neuroscience when original tools issued from physiology, anatomy, or molecular biology were available to decipher how the brain makes sense of olfactory cues. However, this move was promptly dampened by the difficulties of developing quantitative approaches to study the relationship between the physical characteristics of stimuli and the sensations they create. An upswing of olfactory investigations occurred when genetic tools could be used in combination with devices borrowed from the physics of light (a hybrid technique called optogenetics) to scrutinize the olfactory system and to provide greater physiological precision for studying olfactory-driven behaviors. This review aims to present the most recent studies that have used light to activate components of the olfactory pathway, such as olfactory receptor neurons, or neurons located further downstream, while leaving intact others brain circuits. With the use of optogenetics to unravel the mystery of olfaction, scientists have begun to disentangle how the brain makes sense of smells. In this review, we shall discuss how the brain recognizes odors, how it memorizes them, and how animals make decisions based on odorants they are capable of sensing. Although this review deals with olfaction, the role of light will be central throughout.
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Affiliation(s)
- Julien Grimaud
- Institut Pasteur, Laboratory for Perception and Memory, F-75015 Paris, France Centre National de la Recherche Scientifique (CNRS), Unité Mixte de Recherche (UMR) 3571, F-75015 Paris, France
| | - Pierre-Marie Lledo
- Institut Pasteur, Laboratory for Perception and Memory, F-75015 Paris, France Centre National de la Recherche Scientifique (CNRS), Unité Mixte de Recherche (UMR) 3571, F-75015 Paris, France
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65
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Berck ME, Khandelwal A, Claus L, Hernandez-Nunez L, Si G, Tabone CJ, Li F, Truman JW, Fetter RD, Louis M, Samuel AD, Cardona A. The wiring diagram of a glomerular olfactory system. eLife 2016; 5. [PMID: 27177418 PMCID: PMC4930330 DOI: 10.7554/elife.14859] [Citation(s) in RCA: 123] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2016] [Accepted: 05/06/2016] [Indexed: 12/12/2022] Open
Abstract
The sense of smell enables animals to react to long-distance cues according to learned and innate valences. Here, we have mapped with electron microscopy the complete wiring diagram of the Drosophila larval antennal lobe, an olfactory neuropil similar to the vertebrate olfactory bulb. We found a canonical circuit with uniglomerular projection neurons (uPNs) relaying gain-controlled ORN activity to the mushroom body and the lateral horn. A second, parallel circuit with multiglomerular projection neurons (mPNs) and hierarchically connected local neurons (LNs) selectively integrates multiple ORN signals already at the first synapse. LN-LN synaptic connections putatively implement a bistable gain control mechanism that either computes odor saliency through panglomerular inhibition, or allows some glomeruli to respond to faint aversive odors in the presence of strong appetitive odors. This complete wiring diagram will support experimental and theoretical studies towards bridging the gap between circuits and behavior. DOI:http://dx.doi.org/10.7554/eLife.14859.001 Our sense of smell can tell us about bread being baked faraway in the kitchen, or whether a leftover piece finally went bad. Similarly to the eyes, the nose enables us to make up a mental image of what lies at a distance. In mammals, the surface of the nose hosts a huge number of olfactory sensory cells, each of which is tuned to respond to a small set of scent molecules. The olfactory sensory cells communicate with a region of the brain called the olfactory bulb. Olfactory sensory cells of the same type converge onto the same small pocket of the olfactory bulb, forming a structure called a glomerulus. Similarly to how the retina generates an image, the combined activity of multiple glomeruli defines an odor. A particular smell is the combination of many volatile compounds, the odorants. Therefore the interactions between different olfactory glomeruli are important for defining the nature of the perceived odor. Although the types of neurons involved in these interactions were known in insects, fish and mice, a precise wiring diagram of a complete set of glomeruli had not been described. In particular, the points of contact through which neurons communicate with each other – known as synapses – among all the neurons participating in an olfactory system were not known. Berck, Khandelwal et al. have now taken advantage of the small size of the olfactory system of the larvae of Drosophila fruit flies to fully describe, using high-resolution imaging, all its neurons and their synapses. The results define the complete wiring diagram of the neural circuit that processes the signals sent by olfactory sensory neurons in the larva’s olfactory circuits. In addition to the neurons that read out the activity of a single glomerulus and send it to higher areas of the brain for further processing, there are also numerous neurons that read out activity from multiple glomeruli. These neurons represent a system, encoded in the genome, for quickly extracting valuable olfactory information and then relaying it to other areas of the brain. An essential aspect of sensation is the ability to stop noticing a stimulus if it doesn't change. This allows an animal to, for example, find food by moving in a direction that increases the intensity of an odor. Inhibition mediates some aspects of this capability. The discovery of structure in the inhibitory connections among glomeruli, together with prior findings on the inner workings of the olfactory system, enabled Berck, Khandelwal et al. to hypothesize how the olfactory circuits enable odor gradients to be navigated. Further investigation revealed more about how the circuits could detect slight changes in odor concentration regardless of whether the overall odor intensity is strong or faint. And, crucially, it revealed how the worst odors – which can signal danger – can still be perceived in the presence of very strong pleasant odors. With the wiring diagram, theories about the sense of smell can now be tested using the genetic tools available for Drosophila, leading to an understanding of how neural circuits work. DOI:http://dx.doi.org/10.7554/eLife.14859.002
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Affiliation(s)
- Matthew E Berck
- Department of Physics, Harvard University, Cambridge, United States.,Center for Brain Science, Harvard University, Cambridge, United States
| | - Avinash Khandelwal
- EMBL-CRG Systems Biology Program, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Lindsey Claus
- Department of Physics, Harvard University, Cambridge, United States.,Center for Brain Science, Harvard University, Cambridge, United States
| | - Luis Hernandez-Nunez
- Department of Physics, Harvard University, Cambridge, United States.,Center for Brain Science, Harvard University, Cambridge, United States
| | - Guangwei Si
- Department of Physics, Harvard University, Cambridge, United States.,Center for Brain Science, Harvard University, Cambridge, United States
| | | | - Feng Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - James W Truman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Rick D Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Matthieu Louis
- EMBL-CRG Systems Biology Program, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Aravinthan Dt Samuel
- Department of Physics, Harvard University, Cambridge, United States.,Center for Brain Science, Harvard University, Cambridge, United States
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
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Blanke O, Slater M, Serino A. Behavioral, Neural, and Computational Principles of Bodily Self-Consciousness. Neuron 2015; 88:145-66. [PMID: 26447578 DOI: 10.1016/j.neuron.2015.09.029] [Citation(s) in RCA: 417] [Impact Index Per Article: 41.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Olaf Blanke
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics and Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 9 Chemin des Mines, 1202 Geneva, Switzerland; Department of Neurology, University of Geneva, 24 rue Micheli-du-Crest, 1211 Geneva, Switzerland.
| | - Mel Slater
- ICREA-University of Barcelona, Campus de Mundet, 08035 Barcelona, Spain; Department of Computer Science, University College London, Malet Place Engineering Building, Gower Street, London, WC1E 6BT, UK
| | - Andrea Serino
- Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics and Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), 9 Chemin des Mines, 1202 Geneva, Switzerland.
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Abstract
Three recent studies use optogenetics, virtual ‘odor-scapes’ and mathematical modeling to study how the nervous system of fruit fly larvae processes sensory information to control navigation.
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