首页|A Synthetic Nervous System Controls a Biomechanical Model of Aplysia Feeding
A Synthetic Nervous System Controls a Biomechanical Model of Aplysia Feeding
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NETL
Springer Nature
Building an accurate computational model can clarify the basis of feeding behaviors in Aplysia californica。 We introduce a specific circuitry model that emphasizes feedback integration。 The circuitry uses a Synthetic Nervous System， a biologically plausible neural model， with motor neurons and buccal ganglion interneurons organized into 9 subnetworks realizing functions essential to feeding control during the protraction and retraction phases of feeding。 These subnetworks are combined with a cerebral ganglion layer that controls transitions between feeding behaviors。 This Synthetic Nervous System is connected to a simplified biomechanical model of Aplysia and afferent pathways provide proprioceptive and exteroceptive feedback to the controller。 The feedback allows the model to coordinate and control its behaviors in response to the external environment。 We find that the model can qualitatively reproduce multifunctional feeding behaviors。 The kinematic and dynamic responses of the model also share similar features with experimental data。 The results suggest that this neuromechanical model has predictive ability and could be used for generating or testing hypotheses about Aplysia feeding control。
MultifunctionalityComputational neuroscienceAplysiaControlSynthetic nervous systems
Yanjun Li、Victoria A. Webster-Wood、Jeffrey P. Gill、Gregory P. Sutton、Hillel J. Chiel、Roger D. Quinn
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Department of Mechanical and Aerospace Engineering, Case Western Reserve University,Cleveland, OH 44106-7222, USA
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213,USA
Department of Biology, Case Western Reserve University, Cleveland, OH 44106-7080, USA
Department of Life Sciences, University of Lincoln, Lincoln, UK
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International conference on biomimetic and biohybrid systems
NETL
Springer Nature
