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Mukunda CL, Sane SP. Encoding of antennal position and velocity by the Johnston's organ in hawkmoths. J Exp Biol 2025; 228:jeb249342. [PMID: 40099381 PMCID: PMC12079665 DOI: 10.1242/jeb.249342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 03/06/2025] [Indexed: 03/19/2025]
Abstract
Insect antennae function as versatile, multimodal sensory probes in diverse behavioural contexts. In addition to their primary role as olfactory organs, they serve essential mechanosensory functions across insects, including auditory perception, vestibular feedback, airflow detection, gravity sensing and tactile sensation. These diverse functions are facilitated by the mechanosensory Johnston's organ (JO), located at the joint between the flagellum and the pedicel (second antennal segment). This joint lacks muscles, which means that JOs can perceive only passive deflections of the flagellum. Earlier work that characterized the sensitivity and short response time of the JO sensory units in hawkmoths showed that their sensitivity to a broad frequency range is range-fractionated. This vastly expands the functional repertoire of the JO. However, it is not clear what components of antennal kinematics are encoded by the JO. Here, we conducted experiments to test the hypothesis that JO neurons encode the position and velocity of angular movements of the flagellum. We recorded intracellularly from the axons of primary sensory neurons of the JO while stimulating it with ramp-and-hold stimuli in which either the antennal position or antennal angular velocity was maintained at various constant values. Our study shows that JO neurons encode angular velocity and position of the antenna in their response. We also characterized the neural adaptation of the responses to angular velocities and positions. The majority of neurons were sensitive to a movement in the ventrad direction, in the direction of gravity. The adaptation and directional response properties give rise to a nonlinear hysteresis-like response. Together, these findings highlight the neurophysiological basis underlying the functional versatility of the JO.
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Affiliation(s)
- Chinmayee L. Mukunda
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore 560065, India
| | - Sanjay P. Sane
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore 560065, India
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Lutek K, Standen EM. Increasing Viscosity Helps Explain Locomotor Control in Swimming Polypterus senegalus. Integr Org Biol 2021; 3:obab024. [PMID: 34514331 PMCID: PMC8414443 DOI: 10.1093/iob/obab024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 06/25/2021] [Accepted: 08/06/2021] [Indexed: 12/02/2022] Open
Abstract
Locomotion relies on the successful integration of sensory information to adjust brain commands and basic motor rhythms created by central pattern generators. It is not clearly understood how altering the sensory environment impacts control of locomotion. In an aquatic environment, mechanical sensory feedback to the animal can be readily altered by adjusting water viscosity. Computer modeling of fish swimming systems shows that, without sensory feedback, high viscosity systems dampen kinematic output despite similar motor control input. We recorded muscle activity and kinematics of six Polypterus senegalus in four different viscosities of water from 1 cP (normal water) to 40 cP. In high viscosity, P. senegalus exhibit increased body curvature, body wave speed, and body and pectoral fin frequency during swimming. These changes are the result of increased muscle activation intensity and maintain voluntary swimming speed. Unlike the sensory-deprived model, intact sensory feedback allows fish to adjust swimming motor control and kinematic output in high viscous water but maintain typical swimming coordination.
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Affiliation(s)
- K Lutek
- Department of Biology, University of Ottawa, 30 Marie-Curie Private, Ottawa, ON K1N 6N5, Canada
| | - E M Standen
- Department of Biology, University of Ottawa, 30 Marie-Curie Private, Ottawa, ON K1N 6N5, Canada
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Thandiackal R, Melo K, Paez L, Herault J, Kano T, Akiyama K, Boyer F, Ryczko D, Ishiguro A, Ijspeert AJ. Emergence of robust self-organized undulatory swimming based on local hydrodynamic force sensing. Sci Robot 2021; 6:6/57/eabf6354. [PMID: 34380756 DOI: 10.1126/scirobotics.abf6354] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 07/21/2021] [Indexed: 01/23/2023]
Abstract
Undulatory swimming represents an ideal behavior to investigate locomotion control and the role of the underlying central and peripheral components in the spinal cord. Many vertebrate swimmers have central pattern generators and local pressure-sensitive receptors that provide information about the surrounding fluid. However, it remains difficult to study experimentally how these sensors influence motor commands in these animals. Here, using a specifically designed robot that captures the essential components of the animal neuromechanical system and using simulations, we tested the hypothesis that sensed hydrodynamic pressure forces can entrain body actuation through local feedback loops. We found evidence that this peripheral mechanism leads to self-organized undulatory swimming by providing intersegmental coordination and body oscillations. Swimming can be redundantly induced by central mechanisms, and we show that, therefore, a combination of both central and peripheral mechanisms offers a higher robustness against neural disruptions than any of them alone, which potentially explains how some vertebrates retain locomotor capabilities after spinal cord lesions. These results broaden our understanding of animal locomotion and expand our knowledge for the design of robust and modular robots that physically interact with the environment.
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Affiliation(s)
- Robin Thandiackal
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. .,Harvard University, Cambridge MA, USA
| | - Kamilo Melo
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. .,KM-RoBoTa Sàrl, Renens, Switzerland
| | - Laura Paez
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | | | | | | | | | | | - Auke J Ijspeert
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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Chandrasekaran S, Danos N, George UZ, Han JP, Quon G, Müller R, Tsang Y, Wolgemuth C. The Axes of Life: A roadmap for understanding dynamic multiscale systems. Integr Comp Biol 2021; 61:2011-2019. [PMID: 34048574 DOI: 10.1093/icb/icab114] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The biological challenges facing humanity are complex, multi-factorial, and are intimately tied to the future of our health, welfare, and stewardship of the Earth. Tackling problems in diverse areas, such as agriculture, ecology, and health care require linking vast data sets that encompass numerous components and spatio-temporal scales. Here, we provide a new framework and a road map for using experiments and computation to understand dynamic biological systems that span multiple scales. We discuss theories that can help understand complex biological systems and highlight the limitations of existing methodologies and recommend data generation practices. The advent of new technologies such as big data analytics and artificial intelligence can help bridge different scales and data types. We recommend ways to make such models transparent, compatible with existing theories of biological function, and to make biological data sets readable by advanced machine learning algorithms. Overall, the barriers for tackling pressing biological challenges are not only technological, but also sociological. Hence, we also provide recommendations for promoting interdisciplinary interactions between scientists.
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Affiliation(s)
| | - Nicole Danos
- Department of Biology, University of San Diego, San Diego, CA, USA
| | - Uduak Z George
- Department of Mathematics & Statistics, San Diego State University, San Diego, CA, USA
| | - Jin-Ping Han
- IBM TJ Watson Research Center, Ossining, NY, USA
| | - Gerald Quon
- Department of Molecular and Cellular Biology, University of California-Davis, Davis, CA,USA
| | - Rolf Müller
- Department of Mechanical Engineering, Virginia Tech, Blacksburg, VI, USA
| | - Yinphan Tsang
- Department of Natural Resources and Environmental Management, University of Hawai'i at Mānoa, Honolulu, HI, USA
| | - Charles Wolgemuth
- Departments of Physics and Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA
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Tytell ED, Carr JA, Danos N, Wagenbach C, Sullivan CM, Kiemel T, Cowan NJ, Ankarali MM. Body stiffness and damping depend sensitively on the timing of muscle activation in lampreys. Integr Comp Biol 2019; 58:860-873. [PMID: 29873726 DOI: 10.1093/icb/icy042] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Unlike most manmade machines, animals move through their world using flexible bodies and appendages, which bend due to internal muscle and body forces, and also due to forces from the environment. Fishes in particular must cope with fluid dynamic forces that not only resist their overall swimming movements but also may have unsteady flow patterns, vortices, and turbulence, many of which occur more rapidly than what the nervous system can process. Has natural selection led to mechanical properties of fish bodies and their component tissues that can respond very quickly to environmental perturbations? Here, we focus on the mechanical properties of isolated muscle tissue and of the entire intact body in the silver lamprey, Ichthyomyzon unicuspis. We developed two modified work loop protocols to determine the effect of small perturbations on the whole body and on isolated segments of muscle as a function of muscle activation and phase within the swimming cycle. First, we examined how the mechanical properties of the whole lamprey body change depending on the timing of muscle activity. Relative to passive muscle, muscle activation can modulate the effective stiffness by about two-fold and modulate the effective damping by >10-fold depending on the activation phase. Next, we performed a standard work loop test on small sections of axial musculature while adding low-amplitude sinusoidal perturbations at specific frequencies. We modeled the data using a new system identification technique based on time-periodic system analysis and harmonic transfer functions (HTFs) and used the resulting models to predict muscle function under novel conditions. We found that the effective stiffness and damping of muscle varies during the swimming cycle, and that the timing of activation can alter both the magnitude and timing of peak stiffness and damping. Moreover, the response of the isolated muscle was highly nonlinear and length dependent, but the body's response was much more linear. We applied the resulting HTFs from our experiments to explore the effect of pairs of antagonistic muscles. The results suggest that when muscles work against each other as antagonists, the combined system has weaker nonlinearities than either muscle segment alone. Together, these results begin to provide an integrative understanding of how activation timing can tune the mechanical response properties of muscles, enabling fish to swim effectively in their complex and unpredictable environment.
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Affiliation(s)
- Eric D Tytell
- Department of Biology, Tufts University, Medford, MA 02155, USA
| | - Jennifer A Carr
- Department of Biology, Tufts University, Medford, MA 02155, USA.,Department of Biology, Salem State University, Salem, MA 01970, USA
| | - Nicole Danos
- Department of Biology, Tufts University, Medford, MA 02155, USA.,Department of Biology, University of San Diego, San Diego, CA 92110, USA
| | | | | | - Tim Kiemel
- Department of Kinesiology, University of Maryland, College Park, MD 20742, USA
| | - Noah J Cowan
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - M Mert Ankarali
- Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey
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Hamlet CL, Hoffman KA, Tytell ED, Fauci LJ. The role of curvature feedback in the energetics and dynamics of lamprey swimming: A closed-loop model. PLoS Comput Biol 2018; 14:e1006324. [PMID: 30118476 PMCID: PMC6114910 DOI: 10.1371/journal.pcbi.1006324] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Revised: 08/29/2018] [Accepted: 06/24/2018] [Indexed: 12/02/2022] Open
Abstract
Like other animals, lampreys have a central pattern generator (CPG) circuit that activates muscles for locomotion and also adjusts the activity to respond to sensory inputs from the environment. Such a feedback system is crucial for responding appropriately to unexpected perturbations, but it is also active during normal unperturbed steady swimming and influences the baseline swimming pattern. In this study, we investigate different functional forms of body curvature-based sensory feedback and evaluate their effects on steady swimming energetics and kinematics, since little is known experimentally about the functional form of curvature feedback. The distributed CPG is modeled as chains of coupled oscillators. Pairs of phase oscillators represent the left and right sides of segments along the lamprey body. These activate muscles that flex the body and move the lamprey through a fluid environment, which is simulated using a full Navier-Stokes model. The emergent curvature of the body then serves as an input to the CPG oscillators, closing the loop. We consider two forms of feedback, each consistent with experimental results on lamprey proprioceptive sensory receptors. The first, referred to as directional feedback, excites or inhibits the oscillators on the same side, depending on the sign of a chosen gain parameter, and has the opposite effect on oscillators on the opposite side. We find that directional feedback does not affect beat frequency, but does change the duration of muscle activity. The second feedback model, referred to as magnitude feedback, provides a symmetric excitatory or inhibitory effect to oscillators on both sides. This model tends to increase beat frequency and reduces the energetic cost to the lamprey when the gain is high and positive. With both types of feedback, the body curvature has a similar magnitude. Thus, these results indicate that the same magnitude of curvature-based feedback on the CPG with different functional forms can cause distinct differences in swimming performance. When animals move, they receive sensory inputs, which in turn are used to modulate the movement. Relatively little is known about how these inputs affect performance during steady locomotion. Using a computational model of a swimming lamprey, we investigated two different types of feedback, both consistent with experimental data. Both have strong, but different, effects on swimming speed and energy consumption, suggesting that sensory feedback is crucial not just for responding to perturbations, but also for high performance steady locomotion.
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Affiliation(s)
- Christina L. Hamlet
- Department of Mathematics, Bucknell University, Lewisburg, Pennsylvania, United States of America
- * E-mail:
| | - Kathleen A. Hoffman
- Department of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, Maryland, United States of America
| | - Eric D. Tytell
- Department of Biology, Tufts University, Medford, Massachusetts, United States of America
| | - Lisa J. Fauci
- Department of Mathematics, Tulane University, New Orleans, Louisiana, United States of America
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