1
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Calabrese RL, Marder E. Degenerate neuronal and circuit mechanisms important for generating rhythmic motor patterns. Physiol Rev 2025; 105:95-135. [PMID: 39453990 DOI: 10.1152/physrev.00003.2024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 06/10/2024] [Accepted: 06/11/2024] [Indexed: 10/27/2024] Open
Abstract
In 1996, we published a review article (Marder E, Calabrese RL. Physiol Rev 76: 687-717, 1996) describing the state of knowledge about the structure and function of the central pattern-generating circuits important for producing rhythmic behaviors. Although many of the core questions persist, much has changed since 1996. Here, we focus on newer studies that reveal ambiguities that complicate understanding circuit dynamics, despite the enormous technical advances of the recent past. In particular, we highlight recent studies of animal-to-animal variability and our understanding that circuit rhythmicity may be supported by multiple state-dependent mechanisms within the same animal and that robustness and resilience in the face of perturbation may depend critically on the presence of modulators and degenerate circuit mechanisms. Additionally, we highlight the use of computational models to ask whether there are generalizable principles about circuit motifs that can be found across rhythmic motor systems in different animal species.
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Affiliation(s)
| | - Eve Marder
- Brandeis University, Waltham, Massachusetts, United States
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2
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Wang HY, Yu K, Yang Z, Zhang G, Guo SQ, Wang T, Liu DD, Jia RN, Zheng YT, Su YN, Lou Y, Weiss KR, Zhou HB, Liu F, Cropper EC, Yu Q, Jing J. A Single Central Pattern Generator for the Control of a Locomotor Rolling Wave in Mollusc Aplysia. RESEARCH (WASHINGTON, D.C.) 2023; 6:0060. [PMID: 36930762 PMCID: PMC10013812 DOI: 10.34133/research.0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/09/2023] [Indexed: 01/21/2023]
Abstract
Locomotion in mollusc Aplysia is implemented by a pedal rolling wave, a type of axial locomotion. Well-studied examples of axial locomotion (pedal waves in Drosophila larvae and body waves in leech, lamprey, and fish) are generated in a segmented nervous system via activation of multiple coupled central pattern generators (CPGs). Pedal waves in molluscs, however, are generated by a single pedal ganglion, and it is unknown whether there are single or multiple CPGs that generate rhythmic activity and phase shifts between different body parts. During locomotion in intact Aplysia, bursting activity in the parapedal commissural nerve (PPCN) was found to occur during tail contraction. A cluster of 20 to 30 P1 root neurons (P1Ns) on the ventral surface of the pedal ganglion, active during the pedal wave, were identified. Computational cluster analysis revealed that there are 2 phases to the motor program: phase I (centered around 168°) and phase II (centered around 357°). PPCN activity occurs during phase II. The majority of P1Ns are motoneurons. Coactive P1Ns tend to be electrically coupled. Two classes of pedal interneurons (PIs) were characterized. Class 1 (PI1 and PI2) is active during phase I. Their axons make a loop within the pedal ganglion and contribute to locomotor pattern generation. They are electrically coupled to P1Ns that fire during phase I. Class 2 (PI3) is active during phase II and innervates the contralateral pedal ganglion. PI3 may contribute to bilateral coordination. Overall, our findings support the idea that Aplysia pedal waves are generated by a single CPG.
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Affiliation(s)
- Hui-Ying Wang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Ke Yu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Zhe Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Guo Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Shi-Qi Guo
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Tao Wang
- National Laboratory of Solid State Microstructures, Department of Physics, Institute for Brain Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China
| | - Dan-Dan Liu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Ruo-Nan Jia
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Yu-Tong Zheng
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Yan-Nan Su
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Yi Lou
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Klaudiusz R. Weiss
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hai-Bo Zhou
- School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu 210023, China
- Peng Cheng Laboratory, Shenzhen 518000, China
| | - Feng Liu
- National Laboratory of Solid State Microstructures, Department of Physics, Institute for Brain Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China
| | - Elizabeth C. Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Quan Yu
- Peng Cheng Laboratory, Shenzhen 518000, China
| | - Jian Jing
- State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chinese Academy of Medical Sciences Research Unit of Extracellular RNA, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, Chemistry and Biomedicine Innovation Center, School of Life Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Peng Cheng Laboratory, Shenzhen 518000, China
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3
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Gebehart C, Büschges A. Temporal differences between load and movement signal integration in the sensorimotor network of an insect leg. J Neurophysiol 2021; 126:1875-1890. [PMID: 34705575 DOI: 10.1152/jn.00399.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Nervous systems face a torrent of sensory inputs, including proprioceptive feedback. Signal integration depends on spatially and temporally coinciding signals. It is unclear how relative time delays affect multimodal signal integration from spatially distant sense organs. We measured transmission times and latencies along all processing stages of sensorimotor pathways in the stick insect leg muscle control system, using intra- and extracellular recordings. Transmission times of signals from load-sensing tibial and trochanterofemoral campaniform sensilla (tiCS, tr/fCS) to the premotor network were longer than from the movement-sensing femoral chordotonal organ (fCO). We characterized connectivity patterns from tiCS, tr/fCS, and fCO afferents to identified premotor nonspiking interneurons (NSIs) and motor neurons (MNs) by distinguishing short- and long-latency responses to sensory stimuli. Functional NSI connectivity depended on sensory context. The timeline of multisensory integration in the NSI network showed an early phase of movement signal processing and a delayed phase of load signal integration. The temporal delay of load signals relative to movement feedback persisted into MN activity and muscle force development. We demonstrate differential delays in the processing of two distinct sensory modalities generated by the sensorimotor network and affecting motor output. The reported temporal differences in sensory processing and signal integration improve our understanding of sensory network computation and function in motor control.NEW & NOTEWORTHY Networks integrating multisensory input face the challenge of not only spatial but also temporal integration. In the local network controlling insect leg movements, proprioceptive signal delays differ between sensory modalities. Specifically, signal transmission times to and neuronal connectivity within the sensorimotor network lead to delayed information about leg loading relative to movement signals. Temporal delays persist up to the level of the motor output, demonstrating its relevance for motor control.
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Affiliation(s)
- Corinna Gebehart
- Department of Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
| | - Ansgar Büschges
- Department of Animal Physiology, Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
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4
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Spardy LE, Lewis TJ. The role of long-range coupling in crayfish swimmeret phase-locking. BIOLOGICAL CYBERNETICS 2018; 112:305-321. [PMID: 29569056 DOI: 10.1007/s00422-018-0752-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Accepted: 02/23/2018] [Indexed: 06/08/2023]
Abstract
During forward swimming, crayfish and other long-tailed crustaceans rhythmically move four pairs of limbs called swimmerets to propel themselves through the water. This behavior is characterized by a particular stroke pattern in which the most posterior limb pair leads the rhythmic cycle and adjacent swimmerets paddle sequentially with a delay of roughly 25% of the period. The neural circuit underlying limb coordination consists of a chain of local modules, each of which controls a pair of limbs. All modules are directly coupled to one another, but the inter-module coupling strengths decrease with the distance of the connection. Prior modeling studies of the swimmeret neural circuit have included only the dominant nearest-neighbor coupling. Here, we investigate the potential modulatory role of long-range connections between modules. Numerical simulations and analytical arguments show that these connections cause decreases in the phase-differences between neighboring modules. Combined with previous results from a computational fluid dynamics model, we posit that this phenomenon might ensure that the resultant limb coordination lies within a range where propulsion is optimal. To further assess the effects of long-range coupling, we modify the model to reflect an experimental preparation where synaptic transmission from a middle module is blocked, and we generate predictions for the phase-locking properties in this system.
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Affiliation(s)
- Lucy E Spardy
- Department of Mathematics, Skidmore College, 815 North Broadway, Saratoga Springs, NY, 12866, USA.
| | - Timothy J Lewis
- Department of Mathematics, University of California, One Shields Ave, Davis, CA, 95616, USA
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5
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Schneider AC, Seichter HA, Neupert S, Hochhaus AM, Smarandache-Wellmann CR. Profiling neurotransmitters in a crustacean neural circuit for locomotion. PLoS One 2018; 13:e0197781. [PMID: 29787606 PMCID: PMC5963771 DOI: 10.1371/journal.pone.0197781] [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: 02/25/2018] [Accepted: 05/08/2018] [Indexed: 11/25/2022] Open
Abstract
Locomotor systems are widely used to study rhythmically active neural networks. These networks have to be coordinated in order to produce meaningful behavior. The crayfish swimmeret system is well suited to investigate such coordination of distributed neural oscillators because the neurons and their connectivity for generating and especially for coordinating the motor output are identified. The system maintains a fixed phase lag between the segmental oscillators, independent of cycle period. To further the understanding of the system’s plasticity for keeping the phase lag fixed, we profiled the neurotransmitters used by the Coordinating Neurons, which are necessary and sufficient for coordination of the segmental oscillators. We used a combination of electrophysiological, immunohistochemical, and mass spectrometric methods. This arrangement of methods ensured that we could screen for several specific neurotransmitters, since a single method is often not suitable for all neurotransmitters of interest. In a first step, to preselect neurotransmitter candidates, we investigated the effect of substances known to be present in some swimmeret system neurons on the motor output and coordination. Subsequently, we demonstrated electrophysiologically that the identified synapse between the Coordinating Neurons and their target is mainly chemical, but neither glutamate antagonist nor γ-aminobutyric acid antagonist application affected this synapse. With immunohistochemical experiments, we provide strong evidence that the Coordinating Neurons are not serotonergic. Single-cell MALDI-TOF mass spectrometry with subsequent principal component analysis identified acetylcholine as the putative neurotransmitter for both types of Coordinating Neurons.
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Affiliation(s)
- Anna C. Schneider
- Zoological Institute, Animal Physiology, Emmy Noether Group, University of Cologne, Cologne, Germany
| | - Henriette A. Seichter
- Zoological Institute, Animal Physiology, Emmy Noether Group, University of Cologne, Cologne, Germany
| | - Susanne Neupert
- Zoological Institute, Animal Physiology, University of Cologne, Cologne, Germany
| | - A. Maren Hochhaus
- Zoological Institute, Animal Physiology, Emmy Noether Group, University of Cologne, Cologne, Germany
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6
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Yoshida M, Nagayama T, Newland P. Nitric oxide-mediated intersegmental modulation of cycle frequency in the crayfish swimmeret system. Biol Open 2018; 7:bio.032789. [PMID: 29716944 PMCID: PMC5992521 DOI: 10.1242/bio.032789] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Crayfish swimmerets are paired appendages located on the ventral side of each abdominal segment that show rhythmic beating during forward swimming produced by central pattern generators in most abdominal segments. For animals with multiple body segments and limbs, intersegmental coordination of central pattern generators in each segment is crucial for the production of effective movements. Here we develop a novel pharmacological approach to analyse intersegmental modulation of swimmeret rhythm by selectively elevating nitric oxide levels and reducing them with pharmacological agents, in specific ganglia. Bath application of L-arginine, the substrate NO synthesis, increased the cyclical spike responses of the power-stroke motor neurons. By contrast the NOS inhibitor, L-NAME decreased them. To determine the role of the different local centres in producing and controlling the swimmeret rhythm, these two drugs were applied locally to two separate ganglia following bath application of carbachol. Results revealed that there was both ascending and descending intersegmental modulation of cycle frequency of the swimmeret rhythm in the abdominal ganglia and that synchrony of cyclical activity between segments of segments was maintained. We also found that there were gradients in the strength effectiveness in modulation, that ascending modulation of the swimmeret rhythm was stronger than descending modulation. Summary: We develop a novel pharmacological approach using a nitric oxide donor and a nitric oxide synthase inhibitor to analyse modulation and segmental synchrony in the swimmeret rhythm of the crayfish.
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Affiliation(s)
- Misaki Yoshida
- Division of Biology, Graduate School of Science and Engineering, Yamagata University, 990-8560, Yamagata, Japan
| | - Toshiki Nagayama
- Department of Biology, Faculty of Science, Yamagata University, 990-8560, Yamagata, Japan
| | - Philip Newland
- Center of Biological Sciences, University of Southampton, Highfield Campus, Southampton SO17 1BJ, UK
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7
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Wenning A, Norris BJ, Günay C, Kueh D, Calabrese RL. Output variability across animals and levels in a motor system. eLife 2018; 7:31123. [PMID: 29345614 PMCID: PMC5773184 DOI: 10.7554/elife.31123] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 11/22/2017] [Indexed: 01/10/2023] Open
Abstract
Rhythmic behaviors vary across individuals. We investigated the sources of this output variability across a motor system, from the central pattern generator (CPG) to the motor plant. In the bilaterally symmetric leech heartbeat system, the CPG orchestrates two coordinations in the bilateral hearts with different intersegmental phase relations (Δϕ) and periodic side-to-side switches. Population variability is large. We show that the system is precise within a coordination, that differences in repetitions of a coordination contribute little to population output variability, but that differences between bilaterally homologous cells may contribute to some of this variability. Nevertheless, much output variability is likely associated with genetic and life history differences among individuals. Variability of Δϕ were coordination-specific: similar at all levels in one, but significantly lower for the motor pattern than the CPG pattern in the other. Mechanisms that transform CPG output to motor neurons may limit output variability in the motor pattern.
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Affiliation(s)
- Angela Wenning
- Biology Department, Emory University, Atlanta, United States
| | - Brian J Norris
- Biology Department, Emory University, Atlanta, United States.,Biological Sciences, California State University, San Marcos, United States
| | - Cengiz Günay
- Biology Department, Emory University, Atlanta, United States.,School of Science and Technology, Georgia Gwinnett College, Lawrenceville, United States
| | - Daniel Kueh
- Biology Department, Emory University, Atlanta, United States
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8
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Robust phase-waves in chains of half-center oscillators. J Math Biol 2016; 74:1627-1656. [DOI: 10.1007/s00285-016-1066-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 06/16/2016] [Indexed: 10/20/2022]
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9
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Fushiki A, Zwart MF, Kohsaka H, Fetter RD, Cardona A, Nose A. A circuit mechanism for the propagation of waves of muscle contraction in Drosophila. eLife 2016; 5. [PMID: 26880545 PMCID: PMC4829418 DOI: 10.7554/elife.13253] [Citation(s) in RCA: 102] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2015] [Accepted: 02/14/2016] [Indexed: 12/20/2022] Open
Abstract
Animals move by adaptively coordinating the sequential activation of muscles. The circuit mechanisms underlying coordinated locomotion are poorly understood. Here, we report on a novel circuit for the propagation of waves of muscle contraction, using the peristaltic locomotion of Drosophila larvae as a model system. We found an intersegmental chain of synaptically connected neurons, alternating excitatory and inhibitory, necessary for wave propagation and active in phase with the wave. The excitatory neurons (A27h) are premotor and necessary only for forward locomotion, and are modulated by stretch receptors and descending inputs. The inhibitory neurons (GDL) are necessary for both forward and backward locomotion, suggestive of different yet coupled central pattern generators, and its inhibition is necessary for wave propagation. The circuit structure and functional imaging indicated that the commands to contract one segment promote the relaxation of the next segment, revealing a mechanism for wave propagation in peristaltic locomotion. DOI:http://dx.doi.org/10.7554/eLife.13253.001 Rhythmic movements such as walking and swimming require the coordinated contraction of many different muscles. Throughout the animal kingdom, from insects to mammals, animals possess specialized circuits of neurons that are responsible for producing these patterns of muscle contraction. These circuits are known as ‘central pattern generators’. Central pattern generators are made up of multiple types of neurons that exchange information. However, it is unclear how neurons controlling the movement of one part of the body relay information to neurons controlling the movement of other parts. To answer this question, Fushiki et al. used larvae from the fruit fly Drosophila melanogaster as a model, and combined techniques such as electrophysiology and electron microscopy with measures of the insect’s behavior. Fruit fly larvae have bodies that are made of segments, and they can contract and relax these segments in a sequence to propel themselves forwards or backwards. The contraction of one segment is accompanied by relaxation of the segment immediately in front. Fushiki et al. found that each body segment contains a copy of the same basic neuronal circuit. This circuit is made up of excitatory and inhibitory neurons. Both types of neurons regulate movement, but the inhibitory neurons must be suppressed for movement to occur. The experiments also showed that each circuit receives both long-range input from the brain and local sensory feedback. This combination of inputs ensures that the segments contract and relax in the correct order. Future challenges are to determine how the brain controls larval movement via its long-range projections to the body. A key step will be to map these circuits at the level of the individual neurons and the connections between them. DOI:http://dx.doi.org/10.7554/eLife.13253.002
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Affiliation(s)
- Akira Fushiki
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan.,Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Maarten F Zwart
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.,Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Hiroshi Kohsaka
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Richard D Fetter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Akinao Nose
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan.,Department of Physics, Graduate School of Science, University of Tokyo, Tokyo, Japan
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10
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Excitatory connections of nonspiking interneurones in the terminal abdominal ganglion of the crayfish. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2015; 201:773-81. [DOI: 10.1007/s00359-015-1017-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Revised: 05/14/2015] [Accepted: 05/20/2015] [Indexed: 10/23/2022]
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11
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Ryczko D, Knüsel J, Crespi A, Lamarque S, Mathou A, Ijspeert AJ, Cabelguen JM. Flexibility of the axial central pattern generator network for locomotion in the salamander. J Neurophysiol 2014; 113:1921-40. [PMID: 25540227 DOI: 10.1152/jn.00894.2014] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
In tetrapods, limb and axial movements are coordinated during locomotion. It is well established that inter- and intralimb coordination show considerable variations during ongoing locomotion. Much less is known about the flexibility of the axial musculoskeletal system during locomotion and the neural mechanisms involved. Here we examined this issue in the salamander Pleurodeles waltlii, which is capable of locomotion in both aquatic and terrestrial environments. Kinematics of the trunk and electromyograms from the mid-trunk epaxial myotomes were recorded during four locomotor behaviors in freely moving animals. A similar approach was used during rhythmic struggling movements since this would give some insight into the flexibility of the axial motor system. Our results show that each of the forms of locomotion and the struggling behavior is characterized by a distinct combination of mid-trunk motor patterns and cycle durations. Using in vitro electrophysiological recordings in isolated spinal cords, we observed that the spinal networks activated with bath-applied N-methyl-d-aspartate could generate these axial motor patterns. In these isolated spinal cord preparations, the limb motor nerve activities were coordinated with each mid-trunk motor pattern. Furthermore, isolated mid-trunk spinal cords and hemicords could generate the mid-trunk motor patterns. This indicates that each side of the cord comprises a network able to generate coordinated axial motor activity. The roles of descending and sensory inputs in the behavior-related changes in axial motor coordination are discussed.
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Affiliation(s)
- D Ryczko
- Institut National de la Santé et de la Recherche Médicale (INSERM) U 862-Neurocentre Magendie, Université de Bordeaux, Bordeaux Cedex, France; and
| | - J Knüsel
- Biorobotics Laboratory (BIOROB), Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - A Crespi
- Biorobotics Laboratory (BIOROB), Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - S Lamarque
- Institut National de la Santé et de la Recherche Médicale (INSERM) U 862-Neurocentre Magendie, Université de Bordeaux, Bordeaux Cedex, France; and
| | - A Mathou
- Institut National de la Santé et de la Recherche Médicale (INSERM) U 862-Neurocentre Magendie, Université de Bordeaux, Bordeaux Cedex, France; and
| | - A J Ijspeert
- Biorobotics Laboratory (BIOROB), Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - J M Cabelguen
- Institut National de la Santé et de la Recherche Médicale (INSERM) U 862-Neurocentre Magendie, Université de Bordeaux, Bordeaux Cedex, France; and
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12
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Mita A, Yoshida M, Nagayama T. Nitric oxide modulates a swimmeret beating rhythm in the crayfish. ACTA ACUST UNITED AC 2014; 217:4423-31. [PMID: 25452502 DOI: 10.1242/jeb.110551] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The modulatory effects of nitric oxide (NO) and cAMP on the rhythmic beating activity of the swimmeret motor neurones in the crayfish were examined. Swimmerets are paired appendages located on the ventral side of each abdominal segment that show rhythmic beating activity during forward swimming, postural righting behaviour and egg ventilation in gravid females. In isolated abdominal nerve cord preparations, swimmeret motor neurones are usually silent or show a continuous low-frequency spiking activity. Application of carbachol, a cholinergic agonist, elicited rhythmic bursts of motor neurone spikes. The co-application of L-arginine, the substrate for NO synthesis with carbachol increased the burst frequency of the motor neurones. The co-application of the NO donor SNAP with carbachol also increased the burst frequency of the motor neurones. By contrast, co-application of a NOS inhibitor, L-NAME, with carbachol decreased beating frequency of the motor neurones. These results indicate that NO may act as a neuromodulator to facilitate swimmeret beating activity. The facilitatory effect of L-arginine was cancelled by co-application of the soluble guanylate cyclase (sGC) inhibitor ODQ suggesting that NO acts by activating sGC to promote the production of cGMP. Application of L-arginine alone or membrane-permeable cGMP analogue 8-Br-cGMP alone did not elicit rhythmic activity of motor neurones, but co-application of 8-Br-cGMP with carbachol increased bursting frequency of the motor neurones. Furthermore, application of the membrane-permeable cAMP analogue CPT-cAMP alone produced rhythmic bursting of swimmeret motor neurones, and the bursting frequency elicited by CPT-cAMP was increased by co-application with L-arginine. Co-application of the adenylate cyclase inhibitor SQ22536 ceased rhythmic bursts of motor neurone spikes elicited by carbachol. These results suggest that a cAMP system enables the rhythmic bursts of motor neurone spikes and that a NO-cGMP signaling pathway increases cAMP activity to facilitate swimmeret beating.
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Affiliation(s)
- Atsuki Mita
- Division of Biology, Graduate School of Science and Engineering, Yamagata University, 990-8560 Yamagata, Japan
| | - Misaki Yoshida
- Division of Biology, Graduate School of Science and Engineering, Yamagata University, 990-8560 Yamagata, Japan
| | - Toshiki Nagayama
- Department of Biology, Faculty of Science, Yamagata University, 990-8560 Yamagata, Japan.
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13
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Seichter HA, Blumenthal F, Smarandache-Wellmann CR. The swimmeret system of crayfish: a practical guide for the dissection of the nerve cord and extracellular recordings of the motor pattern. J Vis Exp 2014:e52109. [PMID: 25490730 DOI: 10.3791/52109] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
Here we demonstrate the dissection of the crayfish abdominal nerve cord. The preparation comprises the last two thoracic ganglia (T4, T5) and the chain of abdominal ganglia (A1 to A6). This chain of ganglia includes the part of the central nervous system (CNS) that drives coordinated locomotion of the pleopods (swimmerets): the swimmeret system. It is known for over five decades that in crayfish each swimmeret is driven by its own independent pattern generating kernel that generates rhythmic alternating activity . The motor neurons innervating the musculature of each swimmeret comprise two anatomically and functionally distinct populations. One is responsible for the retraction (power stroke, PS) of the swimmeret. The other drives the protraction (return stroke, RS) of the swimmeret. Motor neurons of the swimmeret system are able to produce spontaneously a fictive motor pattern, which is identical to the pattern recorded in vivo. The aim of this report is to introduce an interesting and convenient model system for studying rhythm generating networks and coordination of independent microcircuits for students' practical laboratory courses. The protocol provided includes step-by-step instructions for the dissection of the crayfish's abdominal nerve cord, pinning of the isolated chain of ganglia, desheathing the ganglia and recording the swimmerets fictive motor pattern extracellularly from the isolated nervous system. Additionally, we can monitor the activity of swimmeret neurons recorded intracellularly from dendrites. Here we also describe briefly these techniques and provide some examples. Furthermore, the morphology of swimmeret neurons can be assessed using various staining techniques. Here we provide examples of intracellular (by iontophoresis) dye filled neurons and backfills of pools of swimmeret motor neurons. In our lab we use this preparation to study basic functions of fictive locomotion, the effect of sensory feedback on the activity of the CNS, and coordination between microcircuits on a cellular level.
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Robust circuit rhythms in small circuits arise from variable circuit components and mechanisms. Curr Opin Neurobiol 2014; 31:156-63. [PMID: 25460072 DOI: 10.1016/j.conb.2014.10.012] [Citation(s) in RCA: 106] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 10/20/2014] [Accepted: 10/21/2014] [Indexed: 11/22/2022]
Abstract
Small central pattern generating circuits found in invertebrates have significant advantages for the study of the circuit mechanisms that generate brain rhythms. Experimental and computational studies of small oscillatory circuits reveal that similar rhythms can arise from disparate mechanisms. Animal-to-animal variation in the properties of single neurons and synapses may underly robust circuit performance, and can be revealed by perturbations. Neuromodulation can produce altered circuit performance but also ensure reliable circuit function.
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Wiggin TD, Peck JH, Masino MA. Coordination of fictive motor activity in the larval zebrafish is generated by non-segmental mechanisms. PLoS One 2014; 9:e109117. [PMID: 25275377 PMCID: PMC4183566 DOI: 10.1371/journal.pone.0109117] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Accepted: 08/25/2014] [Indexed: 01/15/2023] Open
Abstract
The cellular and network basis for most vertebrate locomotor central pattern generators (CPGs) is incompletely characterized, but organizational models based on known CPG architectures have been proposed. Segmental models propose that each spinal segment contains a circuit that controls local coordination and sends longer projections to coordinate activity between segments. Unsegmented/continuous models propose that patterned motor output is driven by gradients of neurons and synapses that do not have segmental boundaries. We tested these ideas in the larval zebrafish, an animal that swims in discrete episodes, each of which is composed of coordinated motor bursts that progress rostrocaudally and alternate from side to side. We perturbed the spinal cord using spinal transections or strychnine application and measured the effect on fictive motor output. Spinal transections eliminated episode structure, and reduced both rostrocaudal and side-to-side coordination. Preparations with fewer intact segments were more severely affected, and preparations consisting of midbody and caudal segments were more severely affected than those consisting of rostral segments. In reduced preparations with the same number of intact spinal segments, side-to-side coordination was more severely disrupted than rostrocaudal coordination. Reducing glycine receptor signaling with strychnine reversibly disrupted both rostrocaudal and side-to-side coordination in spinalized larvae without disrupting episodic structure. Both spinal transection and strychnine decreased the stability of the motor rhythm, but this effect was not causal in reducing coordination. These results are inconsistent with a segmented model of the spinal cord and are better explained by a continuous model in which motor neuron coordination is controlled by segment-spanning microcircuits.
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Affiliation(s)
- Timothy D. Wiggin
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Jack H. Peck
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Mark A. Masino
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America
- * E-mail:
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Abstract
A fundamental challenge in neuroscience is to understand how biologically salient motor behaviors emerge from properties of the underlying neural circuits. Crayfish, krill, prawns, lobsters, and other long-tailed crustaceans swim by rhythmically moving limbs called swimmerets. Over the entire biological range of animal size and paddling frequency, movements of adjacent swimmerets maintain an approximate quarter-period phase difference with the more posterior limbs leading the cycle. We use a computational fluid dynamics model to show that this frequency-invariant stroke pattern is the most effective and mechanically efficient paddling rhythm across the full range of biologically relevant Reynolds numbers in crustacean swimming. We then show that the organization of the neural circuit underlying swimmeret coordination provides a robust mechanism for generating this stroke pattern. Specifically, the wave-like limb coordination emerges robustly from a combination of the half-center structure of the local central pattern generating circuits (CPGs) that drive the movements of each limb, the asymmetric network topology of the connections between local CPGs, and the phase response properties of the local CPGs, which we measure experimentally. Thus, the crustacean swimmeret system serves as a concrete example in which the architecture of a neural circuit leads to optimal behavior in a robust manner. Furthermore, we consider all possible connection topologies between local CPGs and show that the natural connectivity pattern generates the biomechanically optimal stroke pattern most robustly. Given the high metabolic cost of crustacean swimming, our results suggest that natural selection has pushed the swimmeret neural circuit toward a connection topology that produces optimal behavior.
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Mulloney B, Smarandache-Wellmann C, Weller C, Hall WM, DiCaprio RA. Proprioceptive feedback modulates coordinating information in a system of segmentally distributed microcircuits. J Neurophysiol 2014; 112:2799-809. [PMID: 25185816 PMCID: PMC4254881 DOI: 10.1152/jn.00321.2014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The system of modular neural circuits that controls crustacean swimmerets drives a metachronal sequence of power-stroke (PS, retraction) and return-stroke (RS, protraction) movements that propels the animal forward efficiently. These neural modules are synchronized by an intersegmental coordinating circuit that imposes characteristic phase differences between these modules. Using a semi-intact preparation that left one swimmeret attached to an otherwise isolated central nervous system (CNS) of the crayfish, Pacifastacus leniusculus, we investigated how the rhythmic activity of this system responded to imposed movements. We recorded extracellularly from the PS and RS nerves that innervated the attached limb and from coordinating axons that encode efference copies of the periodic bursts in PS and RS axons. Simultaneously, we recorded from homologous nerves in more anterior and posterior segments. Maintained retractions did not affect cycle period but promptly weakened PS bursts, strengthened RS bursts, and caused corresponding changes in the strength and timing of efference copies in the module's coordinating axons. Changes in these efference copies then caused changes in the phase and duration, but not the strength, of PS bursts in modules controlling neighboring swimmerets. These changes were promptly reversed when the limb was released. Each swimmeret is innervated by two nonspiking stretch receptors (NSSRs) that depolarize when the limb is retracted. Voltage clamp of an NSSR changed the durations and strengths of bursts in PS and RS axons innervating the same limb and caused corresponding changes in the efference copies of this motor output.
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Affiliation(s)
- Brian Mulloney
- Department of Neurobiology, Physiology, and Behavior, University of California, Davis, California;
| | | | - Cynthia Weller
- Department of Neurobiology, Physiology, and Behavior, University of California, Davis, California
| | - Wendy M Hall
- Department of Neurobiology, Physiology, and Behavior, University of California, Davis, California
| | - Ralph A DiCaprio
- Department of Biological Sciences, Ohio University, Athens, Ohio
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Abstract
We describe synaptic connections through which information essential for encoding efference copies reaches two coordinating neurons in each of the microcircuits that controls limbs on abdominal segments of the crayfish, Pacifastacus leniusculus. In each microcircuit, these coordinating neurons fire bursts of spikes simultaneously with motor neurons. These bursts encode timing, duration, and strength of each motor burst. Using paired microelectrode recordings, we demonstrate that one class of nonspiking neurons in each microcircuit's pattern-generating kernel--IPS--directly inhibits the ASCE coordinating neuron that copies each burst in power-stroke (PS) motor neurons. This inhibitory synapse parallels IPS's inhibition of the same PS motor neurons. Using a disynaptic pathway to control its membrane potential, we demonstrate that a second type of nonspiking interneuron in the pattern-generating kernel--IRSh--inhibits the DSC coordinating neuron that copies each burst in return-stroke (RS) motor neurons. This inhibitory synapse parallels IRS's inhibition of the microcircuit's RS motor neurons. Experimental changes in the membrane potential of one IPS or one IRSh neuron simultaneously changed the strengths of motor bursts, durations, numbers of spikes, and spike frequency in the simultaneous ASCE and DSC bursts. ASCE and DSC coordinating neurons link the segmentally distributed microcircuits into a coordinated system that oscillates with the same period and with stable phase differences. The inhibitory synapses from different pattern-generating neurons that parallel their inhibition of different sets of motor neurons enable ASCE and DSC to encode details of each oscillation that are necessary for stable, adaptive synchronization of the system.
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Stanek E, Cheng S, Takatoh J, Han BX, Wang F. Monosynaptic premotor circuit tracing reveals neural substrates for oro-motor coordination. eLife 2014; 3:e02511. [PMID: 24843003 PMCID: PMC4041139 DOI: 10.7554/elife.02511] [Citation(s) in RCA: 81] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2014] [Accepted: 04/24/2014] [Indexed: 11/21/2022] Open
Abstract
Feeding behaviors require intricately coordinated activation among the muscles of the jaw, tongue, and face, but the neural anatomical substrates underlying such coordination remain unclear. In this study, we investigate whether the premotor circuitry of jaw and tongue motoneurons contain elements for coordination. Using a modified monosynaptic rabies virus-based transsynaptic tracing strategy, we systematically mapped premotor neurons for the jaw-closing masseter muscle and the tongue-protruding genioglossus muscle. The maps revealed that the two groups of premotor neurons are distributed in regions implicated in rhythmogenesis, descending motor control, and sensory feedback. Importantly, we discovered several premotor connection configurations that are ideally suited for coordinating bilaterally symmetric jaw movements, and for enabling co-activation of specific jaw, tongue, and facial muscles. Our findings suggest that shared premotor neurons that form specific multi-target connections with selected motoneurons are a simple and general solution to the problem of orofacial coordination.DOI: http://dx.doi.org/10.7554/eLife.02511.001.
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Affiliation(s)
- Edward Stanek
- Department of Neurobiology, Duke University Medical Center, Durham, United States
| | - Steven Cheng
- Department of Neurobiology, Duke University Medical Center, Durham, United States
| | - Jun Takatoh
- Department of Neurobiology, Duke University Medical Center, Durham, United States
| | - Bao-Xia Han
- Department of Neurobiology, Duke University Medical Center, Durham, United States
| | - Fan Wang
- Department of Neurobiology, Duke University Medical Center, Durham, United States Department of Cell Biology, Duke University Medical Center, Durham, United States
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Calabrese RL. Motor coordination: a local hub for coordination. Curr Biol 2014; 24:R274-5. [PMID: 24698375 DOI: 10.1016/j.cub.2014.02.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
A local interneuron of a crayfish central pattern generator serves as a hub that integrates ascending and descending coordinating information and passes it on to a local oscillatory microcircuit to coordinate a series of segmental appendages known as swimmerets.
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Affiliation(s)
- Ronald L Calabrese
- Department of Biology, Emory University, 1510 Clifton Road, Atlanta, GA 30322, USA.
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