Modeling of Activity-Induced Changes in Signal Propagation Speed of Mechano-Electrically Stimulated Nerve Fiber
Troglio A, de Col R, Namer B, Kutafina E (2021)
Publication Type: Book chapter / Article in edited volumes
Publication year: 2021
Publisher: IOS Press
Edited Volumes: Public Health and Informatics
Series: Studies in Health Technology and Informatics
Book Volume: 281
Pages Range: 93-97
ISBN: 978-1-64368-185-6
DOI: 10.3233/SHTI210127
Abstract
One of the important questions in the research on neural coding is how the preceding axonal activity affects the signal propagation speed of the following one. We present an approach to solving this problem by introducing a multi-level spike count for activity quantification and fitting a family of linear regression models to the data. The best-achieved score is R2=0.89 and the comparison of different models indicates the importance of long and very short nerve fiber memory. Further studies are required to understand the complex axonal mechanisms responsible for the discovered phenomena.
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Germany (DE)How to cite
APA:
Troglio, A., de Col, R., Namer, B., & Kutafina, E. (2021). Modeling of Activity-Induced Changes in Signal Propagation Speed of Mechano-Electrically Stimulated Nerve Fiber. In John Mantas, Lăcrămioara Stoicu-Tivadar, Catherine Chronaki, Arie Hasman, Patrick Weber, Parisis Gallos, Mihaela Crişan-Vida, Emmanouil Zoulias, Oana Sorina Chirila (Eds.), Public Health and Informatics. (pp. 93-97). IOS Press.
MLA:
Troglio, Alina, et al. "Modeling of Activity-Induced Changes in Signal Propagation Speed of Mechano-Electrically Stimulated Nerve Fiber." Public Health and Informatics. Ed. John Mantas, Lăcrămioara Stoicu-Tivadar, Catherine Chronaki, Arie Hasman, Patrick Weber, Parisis Gallos, Mihaela Crişan-Vida, Emmanouil Zoulias, Oana Sorina Chirila, IOS Press, 2021. 93-97.
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