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Zayıf Elektrik Balıklarında Duyumotor Kontrolcü ve Hareket Dinamiklerinin Alt Uzay Tabanlı Sistem Tanılaması

Year 2021, Issue: 25, 623 - 628, 31.08.2021
https://doi.org/10.31590/ejosat.937828

Abstract

Canlılarda duyusal ve motor sistemleri arasında muhteşem bir dinamik kapalı döngü etkileşim vardır. Davranışsal bir görev sırasında merkezi sinir sistemi çevreden gelen duyusal sinyalleri algılar ve belirli motor sinyalleri üretir. Ortaya çıkan bu motor sinyalleri ise iskelet ve kas sistemlerini tetikleyerek hareketi oluştururlar. Bu kapalı döngü sistemde merkezi sinir sistemi bir nevi ‘kontrolcü’, iskelet ve kas sistemleri ise bir nevi ‘plant’ olarak düşünülebilir. Bu çalışmanın amacı davranışsal görevler esnasında merkezi sinir sistemi tarafından uygulanan duyumotor kontrolcü ve gerçekleştirilen hareket dinamiklerinin sistem tanılamasını yapmaktadır. Bu amaçla zayıf elektrik balıklarının sığınak takibi davranışı sırasında toplanmış bir veri kümesinden faydalanılarak bu balıkların takip davranışı esnasında uygulakdıkları kontrolcü ve yüzme dinamikleri elde edilmiştir. Ortaya çıkan sistem modelini kontrol teorisi alanına taşıyabilmek adına altuzay tabanlı sistem tanılama kullanılmıştır. Böylece hem duyumotor kontrolcü hem de hareket dinamikleri için durum uzay matrisleri elde elde edilmiştir.

Supporting Institution

TÜBİTAK

Project Number

120E198

Thanks

Bu çalışma TÜBİTAK tarafından 120E198 numaralı proje kapsamında desteklenmektedir.

References

  • Cowan, N. J., & Fortune, E. S. (2007). The critical role of locomotion mechanics in decoding sensory systems. Journal of neuroscience, 27(5), 1123-1128.
  • Favoreel, W., Van Huffel, S., De Moor, B., Sima, V., & Verhaegen, M. (1999). Comparative study between three subspace identification algorithms. In 1999 European Control Conference (ECC) (pp. 821-826). IEEE.
  • Fifer, M. S., ..., & Crone, N. E. (2013). Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG. IEEE transactions on neural systems and rehabilitation engineering, 22(3), 695-705.
  • Hedrick, T. L., & Robinson, A. K. (2010). Within-wingbeat damping: dynamics of continuous free-flight yaw turns in Manduca sexta. Biology letters, 6(3), 422-425.
  • Kiemel, T., Zhang, Y., & Jeka, J. J. (2011). Identification of neural feedback for upright stance in humans: stabilization rather than sway minimization. Journal of neuroscien-ce, 31(42), 15144-15153.
  • Larimore, W. E. (1990). Canonical variate analysis in identification, filtering, and adaptive control. In 29th IEEE Conference on Decision and control (pp. 596-604).
  • Maladen, R. D., Ding, Y., Li, C., & Goldman, D. I. (2009). Undulatory swimming in sand: subsurface locomotion of the sandfish lizard. Science, 325(5938), 314-318.
  • Roth, E., Zhuang, K., Stamper, S. A., Fortune, E. S., & Cowan, N. J. (2011). Stimulus predictability mediates a switch in locomotor smooth pursuit performance for Eigenmannia virescens. Journal of experimental biology, 214(7), 1170-1180.
  • Sefati, S., Neveln, I. D., Roth, E., Mitchell, T. R., Snyder, J. B., MacIver, M. A., ... & Cowan, N. J. (2013). Mutually opposing forces during locomotion can eliminate the tradeoff between maneuverability and stability. Proceedings of the national academy of sciences, 110(47), 18798-18803.
  • Ting, L. H., & Macpherson, J. M. (2005). A limited set of muscle synergies for force control during a postural task. Journal of neurophysiology, 93(1), 609-613.
  • Uyanik, I., Sefati, S., Stamper, S. A., Cho, K. A., Ankarali, M. M., Fortune, E. S., & Cowan, N. J. (2020a). Variability in locomotor dynamics reveals the critical role of feedback in task control. eLife, 9, e51219.
  • Uyanik, I., Sefati, S., Stamper, S. A., Cho, K. A., Ankarali, M. M., Fortune, E. S., & Cowan, N. J. (2020b). Data associated with publication “Variability in locomotor dynamics reveals the critical role of feedback in task control”. Johns Hopkins University Data Archive, doi:10.7281/T1/UDTJPD, V1.
  • Van Der Kooij, H., & Peterka, R. J. (2011). Non-linear stimulus-response behavior of the human stance control system is predicted by optimization of a system with sensory and motor noise. Journal of computational neuroscience, 30(3), 759-778.

Subspace-Based System Identification of Sensorimotor Control and Locomotor Dynamics of Weakly Electric Fish

Year 2021, Issue: 25, 623 - 628, 31.08.2021
https://doi.org/10.31590/ejosat.937828

Abstract

There is a fascinating dynamic closed-loop interaction between the sensory and motor systems in animals. During behavioral tasks, the central nervous system perceives the sensory signals from the environment and generates associated motor commands. Subsequently, these motor signals stimulate the musculoskeletal system to initiate movement. In this closed-loop interaction, the central nervous system plays the role of a ‘controller’, while the musculoskeletal system becomes the ‘plant’. The goal of this paper is to identify the sensorimotor controller and the locomotor dynamics adopted by animals during behavioral task control. To achieve this, we identified the sensorimotor controller and the locomotor dynamics of weakly electric fish during refuge tracking behavior. We used subspace identification to convey the estimated model to the control theory domain. Thus, we obtained a state-space representation both for the sensorimotor controller and the locomotor dynamics of the fish.

Project Number

120E198

References

  • Cowan, N. J., & Fortune, E. S. (2007). The critical role of locomotion mechanics in decoding sensory systems. Journal of neuroscience, 27(5), 1123-1128.
  • Favoreel, W., Van Huffel, S., De Moor, B., Sima, V., & Verhaegen, M. (1999). Comparative study between three subspace identification algorithms. In 1999 European Control Conference (ECC) (pp. 821-826). IEEE.
  • Fifer, M. S., ..., & Crone, N. E. (2013). Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG. IEEE transactions on neural systems and rehabilitation engineering, 22(3), 695-705.
  • Hedrick, T. L., & Robinson, A. K. (2010). Within-wingbeat damping: dynamics of continuous free-flight yaw turns in Manduca sexta. Biology letters, 6(3), 422-425.
  • Kiemel, T., Zhang, Y., & Jeka, J. J. (2011). Identification of neural feedback for upright stance in humans: stabilization rather than sway minimization. Journal of neuroscien-ce, 31(42), 15144-15153.
  • Larimore, W. E. (1990). Canonical variate analysis in identification, filtering, and adaptive control. In 29th IEEE Conference on Decision and control (pp. 596-604).
  • Maladen, R. D., Ding, Y., Li, C., & Goldman, D. I. (2009). Undulatory swimming in sand: subsurface locomotion of the sandfish lizard. Science, 325(5938), 314-318.
  • Roth, E., Zhuang, K., Stamper, S. A., Fortune, E. S., & Cowan, N. J. (2011). Stimulus predictability mediates a switch in locomotor smooth pursuit performance for Eigenmannia virescens. Journal of experimental biology, 214(7), 1170-1180.
  • Sefati, S., Neveln, I. D., Roth, E., Mitchell, T. R., Snyder, J. B., MacIver, M. A., ... & Cowan, N. J. (2013). Mutually opposing forces during locomotion can eliminate the tradeoff between maneuverability and stability. Proceedings of the national academy of sciences, 110(47), 18798-18803.
  • Ting, L. H., & Macpherson, J. M. (2005). A limited set of muscle synergies for force control during a postural task. Journal of neurophysiology, 93(1), 609-613.
  • Uyanik, I., Sefati, S., Stamper, S. A., Cho, K. A., Ankarali, M. M., Fortune, E. S., & Cowan, N. J. (2020a). Variability in locomotor dynamics reveals the critical role of feedback in task control. eLife, 9, e51219.
  • Uyanik, I., Sefati, S., Stamper, S. A., Cho, K. A., Ankarali, M. M., Fortune, E. S., & Cowan, N. J. (2020b). Data associated with publication “Variability in locomotor dynamics reveals the critical role of feedback in task control”. Johns Hopkins University Data Archive, doi:10.7281/T1/UDTJPD, V1.
  • Van Der Kooij, H., & Peterka, R. J. (2011). Non-linear stimulus-response behavior of the human stance control system is predicted by optimization of a system with sensory and motor noise. Journal of computational neuroscience, 30(3), 759-778.
There are 13 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

İsmail Uyanık 0000-0002-3535-5616

Project Number 120E198
Publication Date August 31, 2021
Published in Issue Year 2021 Issue: 25

Cite

APA Uyanık, İ. (2021). Zayıf Elektrik Balıklarında Duyumotor Kontrolcü ve Hareket Dinamiklerinin Alt Uzay Tabanlı Sistem Tanılaması. Avrupa Bilim Ve Teknoloji Dergisi(25), 623-628. https://doi.org/10.31590/ejosat.937828