A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves.
A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves.
复制标题
DOI:
10.3389/fnins.2023.1072779
复制
发表时间:
2023
影响因子:
4.3
通讯作者:
Rajwa, Bartek
中科院分区:
文献类型:
--
作者:
Shemonti, Abida Sanjana;Plebani, Emanuele;Biscola, Natalia P.;Jaffey, Deborah M.;Havton, Leif A.;Keast, Janet R.;Pothen, Alex;Dundar, M. Murat;Powley, Terry L.;Rajwa, Bartek
关键词:
A thorough understanding of the neuroanatomy of peripheral nerves is required for a better insight into their function and the development of neuromodulation tools and strategies. In biophysical modeling, it is commonly assumed that the complex spatial arrangement of myelinated and unmyelinated axons in peripheral nerves is random, however, in reality the axonal organization is inhomogeneous and anisotropic. Present quantitative neuroanatomy methods analyze peripheral nerves in terms of the number of axons and the morphometric characteristics of the axons, such as area and diameter. In this study, we employed spatial statistics and point process models to describe the spatial arrangement of axons and Sinkhorn distances to compute the similarities between these arrangements (in terms of first- and second-order statistics) in various vagus and pelvic nerve cross-sections. We utilized high-resolution transmission electron microscopy (TEM) images that have been segmented using a custom-built high-throughput deep learning system based on a highly modified U-Net architecture. Our findings show a novel and innovative approach to quantifying similarities between spatial point patterns using metrics derived from the solution to the optimal transport problem. We also present a generalizable pipeline for quantitative analysis of peripheral nerve architecture. Our data demonstrate differences between male- and female-originating samples and similarities between the pelvic and abdominal vagus nerves.
登录
查看更多内容
影响因子:
4.7
作者:
Breit S;Kupferberg A;Rogler G;Hasler G
通讯作者:
Hasler G
影响因子:
2.5
作者:
HULSEBOSCH, CE;COGGESHALL, RE
通讯作者:
COGGESHALL, RE
影响因子:
--
作者:
BJAALIE, JG;DIGGLE, PJ;BRODAL, P
通讯作者:
BRODAL, P
影响因子:
--
作者:
HOFFMAN, HH;SCHNITZLEIN, HN
通讯作者:
SCHNITZLEIN, HN
DOI:
10.1023/b:visi.0000036836.66311.97
发表时间:
2004-12-01
影响因子:
19.5
作者:
Haker, S;Zhu, L;Angenent, S
通讯作者:
Angenent, S