Neural model generating klinotaxis behavior accompanied by a random walk based on C. elegans connectome

被引:0
|
作者
Mohan Chen
Dazheng Feng
Hongtao Su
Tingting Su
Meng Wang
机构
[1] Xidian University,School of Electronic Engineering
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Klinotaxis is a strategy of chemotaxis behavior in Caenorhabditis elegans (C. elegans), and random walking is evident during its locomotion. As yet, the understanding of the neural mechanisms underlying these behaviors has remained limited. In this study, we present a connectome-based simulation model of C. elegans to concurrently realize realistic klinotaxis and random walk behaviors and explore their neural mechanisms. First, input to the model is derived from an ASE sensory neuron model in which the all-or-none depolarization characteristic of ASEL neuron is incorporated for the first time. Then, the neural network is evolved by an evolutionary algorithm; klinotaxis emerged spontaneously. We identify a plausible mechanism of klinotaxis in this model. Next, we propose the liquid synapse according to the stochastic nature of biological synapses and introduce it into the model. Adopting this, the random walk is generated autonomously by the neural network, providing a new hypothesis as to the neural mechanism underlying the random walk. Finally, simulated ablation results are fairly consistent with the biological conclusion, suggesting the similarity between our model and the biological network. Our study is a useful step forward in behavioral simulation and understanding the neural mechanisms of behaviors in C. elegans.
引用
收藏
相关论文
共 50 条
  • [1] Neural model generating klinotaxis behavior accompanied by a random walk based on C. elegans connectome
    Chen, Mohan
    Feng, Dazheng
    Su, Hongtao
    Su, Tingting
    Wang, Meng
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [2] Connecting a Connectome to Behavior: An Ensemble of Neuroanatomical Models of C. elegans Klinotaxis
    Izquierdo, Eduardo J.
    Beer, Randall D.
    PLOS COMPUTATIONAL BIOLOGY, 2013, 9 (02)
  • [3] Self-optimization in a Hopfield neural network based on the C. elegans connectome
    Morales, Alejandro
    Froese, Tom
    ALIFE 2019: THE 2019 CONFERENCE ON ARTIFICIAL LIFE, 2019, : 448 - 453
  • [4] Training sensory-motor behavior in the connectome of an artificial C. elegans
    Portegys, Thomas E.
    NEUROCOMPUTING, 2015, 168 : 128 - 134
  • [5] Neural network model of C. elegans
    Shingai, Ryuzo
    Takahashi, Hisanori
    Iwasaki, Yuishi
    Wakabayashi, Tokumitsu
    Ogurusu, Tarou
    NEUROSCIENCE RESEARCH, 2010, 68 : E105 - E105
  • [6] Forward and backward locomotion patterns in C. elegans generated by a connectome-based model simulation
    Sakamoto, Kazuma
    Soh, Zu
    Suzuki, Michiyo
    Iino, Yuichi
    Tsuji, Toshio
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [7] Forward and backward locomotion patterns in C. elegans generated by a connectome-based model simulation
    Kazuma Sakamoto
    Zu Soh
    Michiyo Suzuki
    Yuichi Iino
    Toshio Tsuji
    Scientific Reports, 11
  • [8] Unsupervised Learning Facilitates Neural Coordination Across the Functional Clusters of the C. elegans Connectome
    Morales, Alejandro
    Froese, Tom
    FRONTIERS IN ROBOTICS AND AI, 2020, 7
  • [9] Periodic excitation in a model neural network of C. elegans
    Shingai, Ryuzo
    Takahashi, Hisanori
    Iwasaki, Yuishi
    Ogurusu, Tarou
    NEUROSCIENCE RESEARCH, 2011, 71 : E77 - E77
  • [10] Neural coding modulation by neuroglobin alters a behavior of C. elegans
    Oda, S.
    Toyoshima, Y.
    de Bono, M.
    EUROPEAN BIOPHYSICS JOURNAL WITH BIOPHYSICS LETTERS, 2015, 44 : S247 - S247